# Assistant conversation SEZGQP - Canonical URL: - Resource IRI: - Type: assistant conversation - Mode: import ## Transcript ### 1. User let's import these papers [Uploaded PDFs] - helbing-1998-evolution-human-trail-systems.pdf: Sheaf file #W5R7HH - helbing-1998-active-walker-trail-systems.pdf: Sheaf file #EA5FPJ - hata-2008-mountain-trail-active-walker.pdf: Sheaf file #8LXP2E - california-2019-trail-layout-design.pdf: Sheaf file #QZJB7X ### 2. Tool result: get_document DOCUMENT #9YMD2E Title: SNAP and SPAN: Towards Dynamic Spatial Ontology Outline: - 1 #RBL6PZ SNAP and SPAN: Towards Dynamic Spatial Ontology - 1.1 #K6SSVN 1 Philosophical Background - 1.1.1 #GFRTYB Basic Formal Ontology - 1.1.2 #DK4RJ9 Temporal Modes of Being - 1.1.3 #PYHEWY Spatiotemporal Ontologies in BFO - 1.1.4 #26SD7J Granularity and Ontological Zooming - 1.1.5 #9SZRQM Taxonomies of SNAP and SPAN - 1.2 #395KH6 2 Formal Framework for BFO - 1.2.1 #KQ4RXW 2.1 Entities and Ontologies - 1.2.1.1 #2UAYWR Ontologies and Ontology Forms - 1.2.1.2 #5QDPLY Material Universals - 1.2.1.3 #XZBGMM Taxonomies of Universals in BFO - 1.2.2 #Y9WM7Q 2.2 Mereology - 1.2.2.1 #QNNQ5Y Mereology and Universals - 1.2.3 #BK3QCV 2.3 Formal Relations - 1.2.3.1 #9AERBS Ontological Indices of Relations. - 1.3 #QZ35CZ 3 SNAP - 1.3.1 #UQH4XU 3.1 Spatial Regions - 1.3.2 #LGE6EY 3.2 Substantial Entities - 1.3.3 #CAHEN5 3.3 SNAP Dependent Entities - 1.3.4 #P4DE3U 3.4 Universals - 1.4 #35MC29 4 SPAN - 1.4.1 #FV9PQR 4.1 Processual Entities - 1.4.2 #QLNXDB 4.3 Temporal Regions - 1.4.3 #WWCQX4 4.4 Spatiotemporal Regions - 1.5 #4NQATC 5 Trans-Ontology in BFO - 1.5.1 #5YQFU8 SNAP-SNAP Trans-Ontology - 1.5.1.1 #LFHHPS Qualitative Change - 1.5.1.2 #VZ3SDB Spatial and Locational Change - 1.5.1.3 #FHYAX6 Substantial Change - 1.5.2 #4WUBEQ Genidentity - 1.5.3 #3YPE9U Reasoning with SPAN Ontologies - 1.5.4 #854NA2 SNAP-SPAN Trans-ontology - 1.6 #XVCM25 6 Case Study: The Ontology of Geodynamic - 1.6.1 #UYMYEH Geographical Ontology - 1.6.2 #BS2RJT 6.1 Georegions and Geo-Ontologies - 1.6.2.1 #PKYEV9 Geospatial Regions. - 1.6.2.2 #4D6KJ8 Geotemporal and Geospatiotemporal Regions - 1.6.2.3 #684DED Geo-Ontologies - 1.6.3 #7MRJ7Z 6.3 The SNAP Geographical Object Ontology - 1.6.4 #YVHQGW 6.4 The SPAN Geographical Process Ontology - 1.6.4.1 #BGCHQQ Patterns and Features of Processes - 1.6.5 #DUUBT3 6.5 The SNAP Geographical Fields Ontology - 1.6.5.1 #UMMP8H Relations in SNAP Field Ontologies. - 1.7 #QU7ELJ Conclusion - 1.8 #TCMAHV Acknowledgements - 1.9 #UDNAWL References ### 3. Assistant tool calls #### Tool call: `read` ```json { "blocks": [ "K6SSVN", "QU7ELJ" ], "expand": true } ``` ### 4. Assistant tool calls #### Tool call: `document_import` ```json { "action": "extract", "run_id": "KYMWYA" } ``` ### 5. Assistant tool calls #### Tool call: `update_document_metadata` ```json { "document_id": "9YMD2E", "micro_abstract": "BFO's bicategorial framework: SNAP snapshot ontologies of continuants and a SPAN ontology of processes in spacetime, linked by trans-ontological relations to capture change — demonstrated on the ontology of geodynamics." } ``` #### Tool call: `generate_image` ```json { "prompt": "A striking conceptual illustration for a philosophy-of-ontology paper about time and space. Split composition: the left half shows a crisp frozen snapshot of a landscape — a mountain, a river, a small city — rendered as clean three-dimensional geometric forms suspended at a single instant, like a museum diorama sliced by a luminous vertical plane of glass labeled by nothing, just light. The right half shows the very same landscape smeared into elegant four-dimensional \"worms\": the river becomes a braided translucent ribbon flowing through a stack of ghosted time-slices, the city grows and shifts through layered translucent strata, storm systems trace glowing helical trails through a deep indigo spacetime volume. Thin golden threads arc across the central glass plane, stitching objects on the frozen side to their corresponding process-ribbons on the flowing side. Style: refined scientific-romantic digital painting, deep indigo and slate palette with warm amber and gold accents, subtle grid of spacetime coordinates fading into darkness, no text, cinematic lighting, high detail." } ``` ### 6. Tool result: get_document DOCUMENT #BYG3BQ Title: Wholeness as a Hierarchical Graph to Capture the Nature of Space Outline: - 1 #V2MHRV Wholeness as a Hierarchical Graph to Capture the Nature of Space - 1.1 #QT5RF7 Abstract - 1.2 #3KT2GU 1. Introduction - 1.3 #LWK7XQ 2. The 15 properties - 1.3.1 #7DFB5R Levels of scale - 1.3.2 #VKHKZE Strong centers - 1.3.3 #ZEFTKL Thick boundaries - 1.3.4 #3ZAA2T Alternating repetition - 1.3.5 #8F5QLZ Positive space - 1.3.6 #5XAZE9 Good shape - 1.3.7 #TPHRL2 Local symmetries - 1.3.8 #HRMBT3 Deep interlock and ambiguity - 1.3.9 #KJVTM2 Contrast - 1.3.10 #ZBHUGU Gradients - 1.3.11 #CJKJCA Roughness - 1.3.12 #QBQVH3 Echoes - 1.3.13 #GWEVEN Void - 1.3.14 #CUK2M3 Simplicity and inner calm - 1.3.15 #FGVYNH Not-separateness - 1.4 #9FK8U9 3. Wholeness as a hierarchical graph - 1.4.1 #JH73PK 3.1 Measuring the degrees of life using the PageRank scores for the centers - 1.4.2 #ATC4YW 3.2 Measuring the degree of life using ht-index for the wholeness - 1.5 #TXBKLJ 4. Case studies: Computing the degrees of life - 1.5.1 #B54GRW 4.1 The plan of Alhambra - 1.5.2 #3NPEFU 4.2 The streets of Manhattan and Sweden - 1.6 #7HNVWB 5. Further discussions on the mathematical model of wholeness - 1.7 #GM64DB 6. Conclusion - 1.8 #J9877W Acknowledgment - 1.9 #WVAHUB References: ### 7. Tool result: get_document DOCUMENT #MJKTBB Title: Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space Outline: - 1 #YXCQD2 Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space - 1.1 #K2N49X Abstract - 1.2 #7WXQSD 1. Introduction - 1.3 #QF78BG 2. Living structure, the degree of structural beauty or livingness, and two laws - 1.4 #KXUAWS 3. A recursive approach to computing the structural beauty of images - 1.4.1 #LB8R59 3.1 Head/tail breaks and two laws of living structure - 1.4.2 #KK923R 3.2 The recursive approach - 1.5 #563UCF 4. Case studies - 1.5.1 #TM4DU2 4.1 Verification of the recursive approach - 1.5.2 #7V2LAA 4.2 Centroids of the substructures capture the skeleton of the images - 1.5.3 #AKW33C 4.3 Decomposable substructures and their centroids - 1.6 #266PRV 5. The livingness of space: Related work, application, and implication - 1.7 #AMFSDX 6. Conclusion - 1.8 #KNGJAN Data and code availability statement - 1.9 #BMA3YP References: - 1.10 #2KSWYX Appendix A: Verification of the recursive approach against georeferenced images ### 8. Assistant tool calls #### Tool call: `update_document_metadata` ```json { "cover_image_id": "3M6RAX", "document_id": "9YMD2E" } ``` ### 9. Tool result: get_document DOCUMENT #4TH488 Title: Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation Outline: - 1 #TS8HQQ Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation - 1.1 #YCT748 I. INTRODUCTION - 1.2 #2WYVSE II. RELATED WORK - 1.2.1 #TLPY7Z A. Black-Box XAI approaches - 1.2.2 #MGG2UN B. White-Box XAI approaches - 1.2.3 #P92MF3 C. Mixed-Initiative Co-Creative Systems - 1.2.4 #G9HJMX D. Measuring Explanations - 1.3 #2RSV2N III. EXPLAINING EXPLAINABILITY - 1.4 #KYV5WL IV. EXPLAINABLE AI FOR DESIGNERS (XAID) - 1.5 #N4TMHB V. MAPPING THE SPACE OF XAID - 1.5.1 #Y48SHT A. Spectrum of Explainability - 1.5.2 #ZXY6H4 B. Spectrum of Initiative - 1.5.3 #A3Q6W7 C. Spectrum of Domain Overlap - 1.6 #L7TGN5 VI. THREE USE CASES - 1.6.1 #PG7W2U A. Use Case 1: White-Box PCG System - 1.6.2 #KG32FP B. Use Case 2: Black-box PCG System - 1.6.3 #AK3WD7 C. Use Case 3: Black-box NPC Behavior System - 1.7 #8R8CBL VII. OPEN CHALLENGES - 1.7.1 #GVAXNH A. White-Box Systems - 1.7.2 #HV85DW B. Black-Box Systems - 1.7.3 #XNNY82 C. Combined approaches - 1.8 #MGUBR3 VIII. CONCLUSIONS - 1.9 #XNEDKE ACKNOWLEDGEMENTS - 1.10 #CXQ7B9 REFERENCES ### 10. Tool result: get_document DOCUMENT #XDESU9 Title: Scalable real‐time animation of rivers Outline: - 1 #Y6CNDB Scalable Real-Time Animation of Rivers - 1.1 #DHLFEL ► To cite this version: - 2 #B9LYTR Scalable real-time animation of rivers - 2.1 #RQUAEM Abstract - 2.2 #UJRUGW 1. Introduction - 2.3 #JW4T3Z 2. Previous work - 2.3.1 #CVHDLT 2.1. Fluid velocity - 2.3.2 #HEUBG3 2.2. Fluid surface - 2.4 #XF2N2Y 3. Overview - 2.4.1 #LFKVYW Algorithm 1 Scalable real-time animation of rivers - 2.5 #S3P9T2 4. Computing flow velocities - 2.5.1 #89NKTG 4.1. Finding the volumetric flow rate from the hydro geometry - 2.5.2 #R6ERAY 4.2. Interpolation of stream function - 2.5.3 #XB2KH8 4.3. Handling obstacles - 2.5.4 #TPMQZV 4.4. Fast distance calculation - 2.6 #NRD5JU 5. Adaptive texture advection - 2.6.1 #7RRTRY 5.1. Dynamic particle distribution - 2.6.1.1 #C52JGF Algorithm 2 Dynamic particle distribution - 2.6.2 #KWALBE 5.2. Sprite-based texturing - 2.6.2.1 #AL6Q7V Algorithm 3 Fragment shader for fluid meshes - 2.7 #LQXUW2 6. Implementation and results - 2.8 #TJAYJS 7. Discussion and limitations - 2.9 #RD97PY 8. Conclusion and future work - 2.10 #R6KZ4N References ### 11. Tool result: get_document DOCUMENT #PBM2TC Title: Water surface wavelets Outline: - 1 #RNVWWR Water Surface Wavelets - 1.1 #JPDLVU ACM Reference Format: - 1.2 #ZTWDW3 1 INTRODUCTION - 1.3 #MGX8HM 2 RELATED WORK - 1.3.1 #2W6Q6T 2.1 Spectrum-based approaches - 1.3.2 #SJKC5Z 2.2 Numerical solutions to Partial Differential Equations - 1.3.3 #C6S3T5 2.3 Hybrid approaches - 1.3.4 #B4G3KW 2.4 Art-directing waves - 1.4 #5EX6YK 3 THEORY - 1.4.1 #9RASZL 3.1 Motivation - 1.4.2 #ARD5T6 3.2 Derivation - 1.4.3 #UL9HZ6 3.3 Discussion - 1.5 #2KAQMF 4 DISCRETIZATION - 1.5.1 #6AJDFD 4.1 Discretizing \mathcal{A} - 1.5.2 #JGKFAU 4.2 Discretizing Advection - 1.5.3 #KQNQXW 4.3 Height field evaluation - 1.6 #MU7P6S 5 ALGORITHM SUMMARY - 1.6.1 #AJK8ET Algorithm 1 Pseudocode for the algorithms used in our paper - 1.7 #MEQNZV 6 EXTENSIONS - 1.7.1 #B6SYLX 6.1 Dissipation - 1.7.2 #5W242X 6.2 Pre-computing wave motions - 1.7.3 #UTTFQ9 6.3 Solid-Fluid Coupling - 1.8 #8LZWQ3 7 ARTISTIC CONTROL - 1.8.1 #CXPF2K 7.1 Selecting the basis function \psi(k) - 1.8.2 #AV6VHK 7.2 Manually overriding \mathcal{A} - 1.9 #AL43YK 8 RESULTS - 1.10 #W3R46F 9 DISCUSSION - 1.11 #ERWM2J ACKNOWLEDGMENTS - 1.12 #95PXLR REFERENCES - 1.13 #QXS3UP A AMPLITUDE DYNAMICS - 1.14 #FFTTEG B \mathcal{A} IS LOWER FREQUENCY THAN \eta - 1.15 #ZHSTA4 C CONTINUUM LIMIT OF WATER WAVE PACKETS ### 12. Assistant tool calls #### Tool call: `read` ```json { "blocks": [ "F9QBNZ", "VZP285", "5RMF3P", "4PR2LM", "HX4K49", "VJ7KYS", "QT5RF7", "K2N49X", "TZM794", "YCT748", "RQUAEM", "ZTWDW3" ], "expand": false } ``` ### 13. Tool result: read SECTION #F9QBNZ Document: #DMTA8Y Terrain Generation Using Procedural Models Based on Hydrology Context: #DMTA8Y Terrain Generation Using Procedural Models Based on Hydrology #RULAFW Terrain Generation Using Procedural Models Based on Hydrology #F9QBNZ Abstract Children: - #7CSK9U excerpt - We present a framework that allows quick and intuitive modeling of terrains using concepts inspired by hydrology. The terrain is generated from a simple initial sketch, and its ge… - #GE8WDB excerpt - CR Categories: I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling; I.3.6 [Computer Graphics]: Methodology and Techniques—Interaction Techniques I.6.8 [Simulatio… - #4KYSN6 excerpt - Keywords: procedural modeling, terrain generation, hydrology - #5FY3UR excerpt - Links: DL PDF WEB VIDEO - #STCJQ5 excerpt - *e-mail:eric.galin@liris.cnrs.fr - #DHJ3KE excerpt - ACM Reference Format Gnevaux, J., Galin, E., Gurin, E., Peytavie, A., Bene, B. 2013. Terrain Generation Using Procedural Models based on Hydrology. ACM Trans. Graph. 32, 4,… - #G6YCHT excerpt - Copyright Notice Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or di… SECTION #VZP285 Document: #AK7NGE Procedural Riverscapes Context: #AK7NGE Procedural Riverscapes #JJE8HN Procedural Riverscapes #VZP285 Abstract Children: - #DBZ8GU excerpt - This paper addresses the problem of creating animated riverscapes through a novel procedural framework that generates the inscribing geometry of a river network and then synthesiz… SECTION #5RMF3P Document: #NV2YRW FastFlow: GPU Acceleration of Flow and Depression Routing for Landscape Simulation Context: #NV2YRW FastFlow: GPU Acceleration of Flow and Depression Routing for Landscape Simulation #6UY46T FastFlow: GPU Acceleration of Flow and Depression Routing for Landscape Simulation #5RMF3P Abstract Children: - #BKN6BV excerpt - Terrain analysis plays an important role in computer graphics, hydrology and geomorphology. In particular, analyzing the path of material flow over a terrain with consideration of… - #LS5PD7 excerpt - In this paper, we propose a novel GPU flow routing algorithm that computes the water discharge in \mathcal{O}(\log n) iterations for a terrain with n vertices (assuming n processo… SECTION #4PR2LM Document: #B6P8L4 Active walker model for the formation of human and animal trail systems Context: #B6P8L4 Active walker model for the formation of human and animal trail systems #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Children: - #H2R66Q excerpt - Active walker models have recently proved their great value for describing the formation of clusters, periodic patterns, and spiral waves as well as the development of rivers, die… - #FZGBXK excerpt - Our trail formation model includes an equation of motion, an equation for environmental changes, and an orientation relation. It contains some model functions, which are specified… - #J3PYTL excerpt - #8DNZZS excerpt - #4MJ457 excerpt - #LFS7S4 excerpt - Whereas pedestrians leave footprints on the ground, ants produce chemical markings for their orientation. Nevertheless, it is more important that pedestrians steer towards a certa… - #PCL35Q excerpt - The trail formation model can be used as a tool for the optimization of pedestrian facilities: It allows urban planners to design convenient way systems which actually meet the ro… - #8CUJT6 excerpt - #LKQP8X excerpt - #5X4JB4 excerpt SECTION #HX4K49 Document: #GY93FG Mountain Trail Formation and the Active Walker Model Context: #GY93FG Mountain Trail Formation and the Active Walker Model #G4BEE9 Mountain trail formation and the active walker model #HX4K49 6. Summary Children: - #S2VCY4 excerpt - We have developed an extension to the active walker model to handle the formation of trails on inclines. Our simulations are in qualitative agreement with empirical observations o… - #WE9YUA excerpt - #2XEL3Y excerpt - #BQSVBB excerpt - The preference of walkers to take consecutive steps in the same direction could also be relevant for the understanding of trail formation in flat areas, and it is our opinion that… SECTION #VJ7KYS Document: #XDEFZS Procedural Generation of Roads Context: #XDEFZS Procedural Generation of Roads #UR2SY7 Procedural Generation of Roads #VJ7KYS Abstract Children: - #R83ZL9 excerpt - In this paper, we propose an automatic method for generating roads based on a weighted anisotropic shortest path algorithm. Given an input scene, we automatically create a path co… - #WD3XJZ excerpt - Categories and Subject Descriptors (according to ACM CCS): [Computer Graphics]: Three-Dimensional Graphics and Realism - #EFY56P excerpt - Keywords: Procedural modeling, road generation, discrete anisotropic shortest path. SECTION #QT5RF7 Document: #BYG3BQ Wholeness as a Hierarchical Graph to Capture the Nature of Space Context: #BYG3BQ Wholeness as a Hierarchical Graph to Capture the Nature of Space #V2MHRV Wholeness as a Hierarchical Graph to Capture the Nature of Space #QT5RF7 Abstract Children: - #HDXQZV excerpt - According to Christopher Alexander's theory of centers, a whole comprises numerous, recursively defined centers for things or spaces surrounding us. Wholeness is a type of global … - #EZR65U excerpt - Keywords: Centers, ht-index, head/tail breaks, big data, complexity, scaling SECTION #K2N49X Document: #MJKTBB Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space Context: #MJKTBB Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space #YXCQD2 Living Images: A Recursive Approach to Computing the Structural Beauty of Images or the Livingness of Space #K2N49X Abstract Children: - #47VNT4 excerpt - According to Gestalt theory, any image is perceived subconsciously as a coherent structure (or whole) with two contrast substructures: figure and ground. The figure consists of nu… - #NQGKKH excerpt - Keywords: Substructures, living structure, wholeness, structural beauty, head/tail breaks, livingness of space SECTION #TZM794 Document: #7GR3AQ Procedural Content Generation through Quality Diversity Context: #7GR3AQ Procedural Content Generation through Quality Diversity #DZ9GFC Procedural Content Generation through Quality Diversity #TZM794 I. INTRODUCTION Children: - #AQNL9X excerpt - Since ROGUE (Toy and Wichman, 1980) and Elite (Acornsoft, 1984) in the 1980s, certain genres of digital games have relied on algorithmic processes to generate content such as leve… - #TMBRXU excerpt - In sum, it has been established that many PCG problems require both quality and diversity of the generated content [3]. This poses a challenge for many existing PCG methods, which… - #QBCZCH excerpt - Quality-Diversity (QD) algorithms are a novel family of evolution-like algorithms that simultaneously maintain the quality and diversity of their solutions by rewarding divergence… SECTION #YCT748 Document: #4TH488 Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation Context: #4TH488 Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation #TS8HQQ Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation #YCT748 I. INTRODUCTION Children: - #T7RH8U excerpt - With the swift development of artificial intelligence (AI) and machine learning (ML) in recent years, their applications (digital games included) have become more sophisticated. W… - #NJWGK9 excerpt - In this vision paper, we focus on one group of human users. We propose a new research area of eXplainable AI for Designers (XAID) and specifically for game designers. The increase… - #8XQUW4 excerpt - By focusing on a specific user group, their needs and tasks, we provide the basis of a human-centered XAID approach which facilitates game designers to co-create with AI/ML techni… - #LPGKEQ excerpt - and planning. We believe that, although fundamental understandings of the properties of different AI/ML techniques are essential, the goal of XAID includes investigating the actua… - #FY6X96 excerpt - Below, Section II presents related work on XAI and mixed-initiative human-AI co-creativity. We present our framework on explainability and the three axes of XAID in Sections III a… SECTION #RQUAEM Document: #XDESU9 Scalable real‐time animation of rivers Context: #XDESU9 Scalable real‐time animation of rivers #B9LYTR Scalable real-time animation of rivers #RQUAEM Abstract Children: - #3UZ7TP excerpt - Many recent games and applications target the interactive exploration of realistic large scale worlds. These worlds consist mostly of static terrain models, as the simulation of a… SECTION #ZTWDW3 Document: #PBM2TC Water surface wavelets Context: #PBM2TC Water surface wavelets #RNVWWR Water Surface Wavelets #ZTWDW3 1 INTRODUCTION Children: - #KZQGW5 excerpt - This paper concerns the efficient and physically plausible animation and art-direction of water surface waves at large scales. Current solutions to this problem invoke numerical s… - #RFLQDX excerpt - Our work proposes a novel transformation to speed up the computation of water surface waves. Instead of discretizing the wave height and momentum at each point on a grid (like pre… - #784244 excerpt - We derive new equations for propagating these local frequency dependent amplitudes through space; these equations result in simple 2D advection and diffusion operations that can b… - #XMSZWB excerpt - The contributions of our paper are: - #GJXVEJ excerpt - • Eulerian Wavelet Transformation: A new theoretical model for water wave transport based on the theory of slowly modulated waves. • Low-frequency simulation variables: Our discre… - #EMZ6QE excerpt - water height itself, so we can represent them on lower resolution grids. This change of variables allows more efficient computation and larger computational domains (Figure 1). - #BSWBFW excerpt - • Novel artistic control: In addition to determining the amplitude function using the physical equations of motion, we also experiment with overwriting these wave amplitudes for a… ### 14. Assistant You’ve got **39 sources** here: 25 journal articles, 10 conference/research papers, 2 book chapters, and 2 reports. They cluster into six main themes. ### 1. Procedural terrain, rivers, and erosion This is the technical core of the collection. - **Hydrology-based terrain generation** constructs terrain and drainage networks together, often from minimal user input (#DMTA8Y). The framework begins with a sketch and derives terrain using hydrological concepts (#7CSK9U). - **Procedural Riverscapes** goes further by generating river geometry, carving the riverbed, and synthesizing animated flow within one workflow (#AK7NGE; #DBZ8GU). - **FastFlow**, **Priority-Flood**, and the recent erosion papers focus on efficient flow routing, depression handling, watershed analysis, and landscape evolution—especially relevant for interactive generation (#NV2YRW; #BKN6BV; #MTDKDE; #DWXKYQ). - **Large Scale Terrain Generation** connects tectonic uplift with fluvial erosion (#96ZMGK). **Main question:** How can geomorphological processes become fast, controllable procedural models? ### 2. Trails, roads, and emergent paths These papers offer two contrasting ways to produce paths. - The **active walker** papers model trails as self-organizing feedback: walkers alter the environment, and those alterations influence later walkers (#B6P8L4; #H2R66Q). The mountain extension adds incline and walking biomechanics (#GY93FG; #S2VCY4). - The **road-generation** papers instead formulate path placement as optimization. Peytavie et al. use weighted anisotropic shortest paths with terrain-sensitive costs (#XDEFZS; #R83ZL9). - The trail-design handbook supplies practical constraints and terminology (#LXV9AT), while procedural street modeling covers interactive urban networks (#V4TQYB). **Main question:** Should a path be optimized directly, or emerge through repeated agent–environment interaction? ### 3. Real-time water simulation and rendering This cluster is mainly about making water visually convincing without full expensive fluid simulation. - **Scalable Real-Time Animation of Rivers**, river textures, and Lagrangian texture advection address velocity fields and moving surface detail (#XDESU9; #RQUAEM; #WZMZGY; #92XRH7). - **Water Surface Wavelets** represents waves through lower-frequency local amplitudes, improving scalability while retaining artistic control (#PBM2TC; #RFLQDX). - Other papers cover particles, shallow water, breaking waves, foam, ocean techniques, and the production-oriented *Portal 2* solution (#RBS5K6; #8SERGP; #CWC7H9; #869NHK; #C4AY2M; #A2QB8L). **Main question:** What combination of physical plausibility, scalability, and art direction is appropriate for interactive landscapes? ### 4. PCG, search, and human–AI co-creation These sources provide the broader procedural-design framework. - **PCGML** surveys content generation using learned models (#CQBDX4). - **Quality Diversity** argues that generators should return a varied collection of good solutions rather than one optimum (#7GR3AQ; #QBCZCH). - **Explainable AI for Designers** treats explanation as part of the designer’s interaction with a co-creative system, organized around explainability, initiative, and domain overlap (#4TH488; #NJWGK9). - The mixed-initiative industry paper emphasizes whether such tools are usable and acceptable in real production (#NRBMD5). - The autonomous-agent paper and platformer-physics paper concern evaluating or inferring properties of generated content (#WZ8DHP; #9NQ94D). **Main question:** How can a procedural system expose meaningful choices rather than behaving like an opaque generator? ### 5. Living structure, wholeness, and beauty This appears to be the theoretical and evaluative strand. - Alexander’s texts describe design as a sequence of **structure-preserving transformations** that progressively strengthens the larger whole (#ZU8GZV; #PXG56P). - Jiang formalizes Alexander’s “centers” as a hierarchical graph and uses measures such as PageRank and the ht-index (#BYG3BQ; #HDXQZV). - The later papers extend this into computational measures of structural beauty and image “livingness” (#3XSLTA; #MJKTBB; #47VNT4). - **Beautimeter** is the newest application, using GPT to assess architecture and urban form through Alexander’s 15 properties (#MH5J8D). - **Generative Codes** applies the same family of ideas to neighborhood-scale development (#XW22YY). **Main question:** Can the coherence or “life” of generated environments be represented computationally without reducing it to a simplistic aesthetic score? ### 6. Peripheral but potentially useful methods - Racing trajectories provide a fast two-stage trajectory-optimization analogy (#G3TBNG). - Geography’s “third view of space” supplies a broader spatial ontology (#SKRF4C). - Ocean rendering papers are useful references, although less directly tied to river and trail generation. ## Overall shape of the library The collection supports a thesis about **procedurally generating coherent landscapes through interacting processes**: 1. **Terrain and water establish environmental structure.** 2. **Walkers, trails, roads, and rivers create networks through feedback or optimization.** 3. **Real-time methods make the result interactive.** 4. **Mixed-initiative PCG gives the designer control.** 5. **Living-structure theory supplies a possible criterion for evaluating the resulting whole.** The strongest starting set is **Terrain Generation Using Procedural Models Based on Hydrology** (#DMTA8Y), **Procedural Riverscapes** (#AK7NGE), **Active Walker Model** (#B6P8L4), **Mountain Trail Formation** (#GY93FG), **Quality Diversity** (#7GR3AQ), **Explainable AI for Designers** (#4TH488), and **Wholeness as a Hierarchical Graph** (#BYG3BQ). ### 15. Assistant tool calls #### Tool call: `document_import` ```json { "action": "metadata", "run_id": "KYMWYA" } ``` ### 16. Tool result: document_import { "action": "metadata", "run_id": "KYMWYA", "documents": [ { "status": "already_resolved", "document_id": "B6P8L4" }, { "match": { "reason": "no DOI or ISBN found", "source": "none", "score": 0.0, "accept?": false }, "metadata": { "title": "Mountain trail formation and the active walker model", "usage": { "reasoning_tokens": 0, "cost": { "total": 6.45e-4, "tokens": 6.45e-4, "tools": 0.0, "images": 0.0, "storage": 0.0, "input_cost": 4.35e-4, "output_cost": 2.1e-4, "reasoning_cost": 0.0, "line_items": [ { "count": 1741, "id": "token.input", "kind": "tokens", "component": "token.input", "cost": 4.35e-4, "quantity": 1741 }, { "count": 140, "id": "token.output", "kind": "tokens", "component": "token.output", "cost": 2.1e-4, "quantity": 140 } ] }, "output_tokens": 140, "input_tokens": 1741, "total_cost": 6.45e-4, "input_cost": 4.35e-4, "output_cost": 2.1e-4, "reasoning_cost": 0.0, "cached_tokens": 0, "total_tokens": 1881, "tool_usage": {}, "image_usage": {}, "cache_creation_tokens": 0 }, "year": "2009", "model": "google:gemini-3.1-flash-lite-preview", "notes": "Information extracted from pre-print header metadata available on the first page.", "source_filename": "7b7049e41a8e8be81ce70dc3c2e9d1d8d7d33f1e7941f7834ff686f97d7b52c1.pdf", "authors": [ "S. J. GILKS", "J. P. HAGUE" ], "doi": null, "pages": "1-3", "isbn": null, "publication": "arXiv", "volume": "0812.1536v2", "issue": null, "confidence": "high" }, "document_id": "GY93FG", "wrote": false }, { "match": { "reason": "no DOI or ISBN found", "source": "none", "score": 0.0, "accept?": false }, "metadata": { "title": "Trails Handbook", "usage": { "reasoning_tokens": 0, "cost": { "total": 6.14e-4, "tokens": 6.14e-4, "tools": 0.0, "images": 0.0, "storage": 0.0, "input_cost": 4.35e-4, "output_cost": 1.79e-4, "reasoning_cost": 0.0, "line_items": [ { "count": 1741, "id": "token.input", "kind": "tokens", "component": "token.input", "cost": 4.35e-4, "quantity": 1741 }, { "count": 119, "id": "token.output", "kind": "tokens", "component": "token.output", "cost": 1.79e-4, "quantity": 119 } ] }, "output_tokens": 119, "input_tokens": 1741, "total_cost": 6.14e-4, "input_cost": 4.35e-4, "output_cost": 1.79e-4, "reasoning_cost": 0.0, "cached_tokens": 0, "total_tokens": 1860, "tool_usage": {}, "image_usage": {}, "cache_creation_tokens": 0 }, "year": "null", "model": "google:gemini-3.1-flash-lite-preview", "notes": "Metadata extracted from the front matter pages of the handbook chapter 5", "source_filename": "965fbb2d4f4ea2ed184f388254244b49db89bd3adc97d97588fc74d2cbe59745.pdf", "authors": [ "California State Parks" ], "doi": null, "pages": "5-i to 5-iii", "isbn": null, "publication": "California State Parks Trails Handbook", "volume": "null", "issue": "null", "confidence": "high" }, "document_id": "LXV9AT", "wrote": false }, { "match": { "reason": "no DOI or ISBN found", "source": "none", "score": 0.0, "accept?": false }, "metadata": { "title": "Modelling the Evolution of Human Trail Systems", "usage": { "reasoning_tokens": 0, "cost": { "total": 6.28e-4, "tokens": 6.28e-4, "tools": 0.0, "images": 0.0, "storage": 0.0, "input_cost": 4.35e-4, "output_cost": 1.93e-4, "reasoning_cost": 0.0, "line_items": [ { "count": 1741, "id": "token.input", "kind": "tokens", "component": "token.input", "cost": 4.35e-4, "quantity": 1741 }, { "count": 129, "id": "token.output", "kind": "tokens", "component": "token.output", "cost": 1.93e-4, "quantity": 129 } ] }, "output_tokens": 129, "input_tokens": 1741, "total_cost": 6.28e-4, "input_cost": 4.35e-4, "output_cost": 1.93e-4, "reasoning_cost": 0.0, "cached_tokens": 0, "total_tokens": 1870, "tool_usage": {}, "image_usage": {}, "cache_creation_tokens": 0 }, "year": "1998", "model": "google:gemini-3.1-flash-lite-preview", "notes": "Metadata extracted from the arXiv preprint header and content.", "source_filename": "d9cac52f1c5b68bec9d3059b7bc009bc24e8512fa3bf0720db56dc9c821d350d.pdf", "authors": [ "Dirk Helbing", "Joachim Keltsch", "Péter Molnár" ], "doi": null, "pages": "1-3", "isbn": null, "publication": "arXiv", "volume": null, "issue": null, "confidence": "high" }, "document_id": "UYLTYJ", "wrote": false } ] } ### 17. Assistant tool calls #### Tool call: `document_import` ```json { "action": "validate", "run_id": "KYMWYA" } ``` ### 18. Tool result: document_import { "action": "validate", "run_id": "KYMWYA", "documents": [ { "title": "Active walker model for the formation of human and animal trail systems", "valid": true, "document_id": "B6P8L4", "readable_chunks": 203, "source_pages": 34, "reader_path": "/B6P8L4" }, { "title": "Untitled thesis", "valid": true, "document_id": "GY93FG", "readable_chunks": 131, "source_pages": 22, "reader_path": "/GY93FG" }, { "title": "Untitled thesis", "valid": true, "document_id": "LXV9AT", "readable_chunks": 352, "source_pages": 64, "reader_path": "/LXV9AT" }, { "title": "Untitled thesis", "valid": true, "document_id": "UYLTYJ", "readable_chunks": 40, "source_pages": 11, "reader_path": "/UYLTYJ" } ], "search_rows": 625, "embedding_status": "completed", "embedding_errors": 0 } ### 19. Assistant All four reader records validate and the search index completed with no embedding errors. Three records remain untitled because automatic metadata matching refused to write unverified, DOI-free metadata; I’m checking their imported title pages and outlines so I can report the exact review state rather than silently accepting bad citations. #### Tool call: `get_document` ```json { "id": "B6P8L4" } ``` #### Tool call: `get_document` ```json { "id": "GY93FG" } ``` #### Tool call: `get_document` ```json { "id": "LXV9AT" } ``` #### Tool call: `get_document` ```json { "id": "UYLTYJ" } ``` ### 20. Tool result: get_document DOCUMENT #B6P8L4 Title: Active walker model for the formation of human and animal trail systems Outline: - 1 #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems - 1.1 #4PR2LM Abstract - 1.2 #TTL9MC I. INTRODUCTION - 1.3 #YEVN37 II. ACTIVE WALKER MODEL OF TRAIL FORMATION - 1.4 #P3AR99 III. TRUNK TRAIL FORMATION BY ANTS - 1.5 #3WQXTG IV. HUMAN TRAIL FORMATION - 1.5.1 #FG65J6 A. Scaling to dimensionless equations - 1.5.2 #CAN22D B. Macroscopic formulation of trail formation - 1.6 #T6PSLK V. SUMMARY AND OUTLOOK - 1.6.1 #DTECU9 A. Trail formation as a self-organization phenomenon - 1.6.2 #CN7EEL B. Implications for urban planners: Optimization of way systems - 1.6.3 #98Y5GR C. Current research directions - 1.7 #BN5TSX REFERENCES - 1.8 #SUKVEK ACKNOWLEDGMENTS - 1.9 #NPCWBQ FIGURES ### 21. Tool result: get_document DOCUMENT #GY93FG Title: Untitled thesis Outline: - 1 #G4BEE9 Mountain trail formation and the active walker model - 1.1 #2F9V87 1. Introduction - 1.2 #A5Y7MA 2. Active walker model for human trails - 1.3 #43C2RF 3. The biomechanics of walking on inclines - 1.4 #MKLE5Y 4. A model of mountain walkers - 1.4.1 #U98348 4.1. New rules for mountain walking - 1.4.2 #KAWSKG 4.2. Discretization scheme - 1.4.3 #CVMHHZ 4.3. Algorithm one - 1.4.4 #GC25R6 4.4. Algorithm two - 1.5 #NBFQAN 5. Results - 1.5.1 #TPVRFV 5.1. Algorithm one - 1.5.2 #AKE5NT 5.2. Algorithm two - 1.6 #HX4K49 6. Summary - 1.7 #VB6JS4 Acknowledgments - 1.8 #J7A25L References ### 22. Tool result: get_document DOCUMENT #LXV9AT Title: Untitled thesis Outline: - 1 #XRDH78 Figures - 2 #P3P37A Photos - 3 #HE95FY Chapter 5. Principles of Trail Layout and Design - 3.1 #92S5AZ 5.1. Life of a Trail - 3.2 #QB5YWT 5.2. Elements of a Good Trail - 3.3 #4DMRYZ 5.3. Identification of Need - 3.4 #JZHJ8Q 5.4. Identification of Trail Use Types, Classifications, and Design Standards - 3.5 #BUKYGV 5.5. Mechanical Wear - 3.5.1 #V5SGUS 5.5.1. Identification of Mechanical Wear by Use Type - 3.5.1.1 #U4N4Q8 5.5.1.1. Hardness and Shape of User Surface. - 3.5.1.2 #MBW44W 5.5.1.2. User Weight and Surface Contact Area - 3.5.1.3 #LR2Y76 5.5.1.3. Velocity, Angle of Impingement, and Coefficient of Kinetic Friction - 3.5.1.4 #PEUZYA 5.5.1.4. Acceleration, Braking, and Turning/Curving - 3.5.1.4.1 #YE7XWW 5.5.1.4.1. Pedestrians - 3.5.1.4.2 #W4PRY2 5.5.1.4.2. Equestrians - 3.5.1.4.3 #73D857 5.5.1.4.3. Mountain Bikers - 3.5.1.4.4 #XLMSSL 5.5.1.4.4. Off Highway Vehicles - 3.5.2 #FG5UFB 5.5.2. Linear Mechanical Wear - 3.5.3 #UGJ3ZE 5.5.3. Vertical Point Depression Features - 3.5.4 #8BXTCV 5.5.4. Sudden Grade Changes - 3.5.5 #SUVWGE 5.5.5. Parent Soil Strength and Durability - 3.5.6 #RQKELJ 5.5.1. Natural Erosion - 3.5.6.1 #MCFMJS 5.5.1.1. Water - 3.5.6.2 #AVSTPC 5.5.1.2. Wind - 3.5.6.3 #GKGP2X 5.5.1.3. Mechanical Wear and Natural Erosion - 3.5.7 #KN98KH 5.5.2. Categories of Mechanical Wear - 3.5.7.1 #W33EV6 5.5.2.1. Low Mechanical Wear - 3.5.7.1.1 #WA59GU Trail design, construction, and management techniques for low mechanical wear include: - 3.5.7.2 #R28ZKS 5.5.2.2. Moderate Mechanical Wear - 3.5.7.2.1 #EGEBBG Trail design, construction, and management techniques for moderate mechanical wear include: - 3.5.7.3 #BXPQJ9 5.5.2.3. Heavy Mechanical Wear - 3.5.7.3.1 #RZ9JXT Trail design, construction, and management techniques for heavy mechanical wear include: - 3.5.8 #YNAMST 5.5.3. Comparative Mechanical Wear Rankings - 3.6 #M2FCT4 5.6. Maintaining Natural Drainage - 3.7 #EEPQMJ 5.7. Trail Layout - 3.7.1 #7XTB8T 5.7.1. Review of Existing Information - 3.7.2 #D9NVQC 5.7.2. Major Control Points and Average Linear Grades - 3.7.3 #XSQ2CN 5.7.3. Maximum Sustainable Linear Grades - 3.7.3.1 #2YGFFK 5.7.3.1. Soil Strength and Durability - 3.7.3.2 #ZFYZXZ 5.7.3.2. Annual Rainfall - 3.7.3.3 #74WYLZ 5.7.3.3. Rainfall Intensity - 3.7.3.4 #Y3XWQH 5.7.3.4. Canopy Cover - 3.7.3.5 #7FRMWX 5.7.3.5. Percent of Hillslope - 3.7.3.6 #SB9AAG 5.7.3.6. Location on the Hillslope - 3.7.3.7 #VGA57R 5.7.3.7. Season of Use - 3.7.3.8 #DQ4WG4 5.7.3.8. Evaluation of Existing Trails - 3.7.3.9 #BRLU95 5.7.3.9. Evaluating and Interpreting the Criteria - 3.7.4 #ZGJXBS 5.7.4. Designed Linear Grades - 3.7.5 #9WNHGK 5.7.5. Field Reconnaissance - 3.7.5.1 #7JBFFE 5.7.5.1. Minor Control Point Identification - 3.7.5.1.1 #4U7TV6 TRAIL LAYOUT AND DESIGN - 3.7.5.2 #XG25M6 5.7.5.2. Designed Control Points - 3.7.5.2.1 #XDF6ZN 5.7.5.2.1. Watercourse Crossings - 3.7.5.2.2 #9EED3X 5.7.5.2.2. Turns - 3.7.5.2.3 #W2A9QZ 5.7.5.2.3. Topographic Control Points - 3.7.5.2.4 #UM24VH 5.7.5.2.4. Problematic Topography - 3.7.5.2.5 #AG3WMA 5.7.5.2.5. Orientation/Aspect - 3.7.6 #NQEU6U 5.7.6. Final Grade Reconciliation - 3.7.7 #8BZAPC 5.7.7. Flagging the Trail Alignment - 3.7.7.1 #AGRR47 5.7.7.1. Initial Flagging Process - 3.7.7.1.1 #K2KA8X LEVELING EXERCISE - 3.7.7.1.2 #CRJ2SY SHOOTING GRADE - 3.7.7.1.3 #ADY5XK CLINOMETER - 3.7.7.1.4 #SKHQPC SIGHTING FOR GRADE WITH CLINOMETER - 3.7.7.1.5 #A8QPLC TRAVELWAY EXCAVATIONS - 3.7.7.2 #P4ZHEP 5.7.7.2. Second Flagging of the Alignment - 3.8 #W8FRQE 5.8. Developing Trail Work Logs and Cost Estimates ### 23. Tool result: get_document DOCUMENT #UYLTYJ Title: Untitled thesis Outline: - 1 #BSSYS2 Modelling the Evolution of Human Trail Systems - 2 #NTZWM2 REFERENCES - 2.1 #25JSQ6 ACKNOWLEDGMENTS - 2.2 #5LE8NQ FIGURES ### 24. Assistant tool calls #### Tool call: `search_text` ```json { "document_id": "GY93FG", "limit": 10, "query": "Mountain trail formation active walker model authors arXiv" } ``` #### Tool call: `search_text` ```json { "document_id": "LXV9AT", "limit": 10, "query": "California State Parks Trails Handbook Chapter 5 Principles Trail Layout Design date" } ``` #### Tool call: `search_text` ```json { "document_id": "UYLTYJ", "limit": 10, "query": "Modelling Evolution Human Trail Systems Dirk Helbing Joachim Keltsch Peter Molnar" } ``` #### Tool call: `search_text` ```json { "document_id": "B6P8L4", "limit": 10, "query": "Active walker model formation human animal trail systems authors DOI" } ``` ### 25. Tool result: search_text Exact matches 1. Source: (#GY93FG), p. 17 Context: #G4BEE9 Mountain trail formation and the active walker model #HX4K49 6. Summary Matching excerpt #BQSVBB: The preference of walkers to take consecutive steps in the same direction could also be relevant for the understanding of trail formation in flat areas, and it is our opinion that a persistence of direction parameter should also be included when simulating trail systems on level ground. Thus, our main conclusions are that (1) correlation between consecutive step directions should be included in the active walker model and that (2) an extension of the active walker model to include forbidden angles, correlation between consecutive steps and the combination of walkers moving both up- and down-hill is suitable to understand the formation of mountain paths. 2. Source: (#GY93FG), p. 3 Context: #G4BEE9 Mountain trail formation and the active walker model #A5Y7MA 2. Active walker model for human trails Matching excerpt #BLYR6Y: In order to investigate trail formations on mountains we use a modified form of the active walker model, which was introduced in Refs. 7 and 9. In this section, we review the rules of the unmodified active walker model following the scheme introduced in Ref. 7. Since the active walker model forms the basis of our extension to mountain trails, it is our aim to ensure that all specific features of the active walker model are clear, before introducing our extensions to the model in section 4. 3. Source: (#GY93FG), p. 2 Context: #G4BEE9 Mountain trail formation and the active walker model #2F9V87 1. Introduction Matching excerpt #UWUSQ2: This article continues as follows. We review the rules of the active walker model in section 2. In section 3 we briefly discuss aspects of the biomechanics of walking on inclines. Extensions of the active walker model for mountain trail systems are introduced in section 4. Results of simulations are shown in section 5. Finally we summarize in section 6. 4. Source: (#GY93FG), p. 0 Context: #G4BEE9 Mountain trail formation and the active walker model Matching excerpt #2QALPN: We extend the active walker model to address the formation of paths on gradients, which have been observed to have a zigzag form. Our extension includes a new rule which prohibits direct descent or ascent on steep inclines, simulating aversion to falling. Further augmentation of the model stops walkers from changing direction very rapidly as that would likely lead to a fall. The extended model predicts paths with qualitatively similar forms to the observed trails, but only if the terms suppressing sudden direction changes are included. The need to include terms into the model that stop rapid direction change when simulating mountain trails indicates that a similar rule should also be included in the standard active walker model. 5. Source: (#GY93FG), p. 0 Context: #G4BEE9 Mountain trail formation and the active walker model Matching excerpt #7K9TW3: Keywords: Active walker model; Mountain trails 6. Source: (#GY93FG), p. 1 Context: #G4BEE9 Mountain trail formation and the active walker model #2F9V87 1. Introduction Matching excerpt #364B8H: The energetics of walking on an incline have been discussed by Alexander in a simple model of bipedal locomotion 1 . From energy considerations, walkers aim to change the angle of ascent from the vertical if a hill reaches a steep enough gradient. In Ref. 1, human walkers are omniscient, and are able to assess the energetic outlay for an entire route. In this way, they can assess if more energy would be expended taking a shallower and longer route, or if a quick hike up a steep route would be more favorable. We consider that it is unlikely that the information about all possible routes is available for global decisions to influence route and planning, and expect that decisions are more likely to be local. Moreover, modeling has concluded that humans choose well trodden paths in a more local manner 8 . We therefore consider that insight into mountain trail formation could be gained from active walker simulations of inclined planes. 7. Source: (#GY93FG), p. 16 Context: #G4BEE9 Mountain trail formation and the active walker model #HX4K49 6. Summary Matching excerpt #S2VCY4: We have developed an extension to the active walker model to handle the formation of trails on inclines. Our simulations are in qualitative agreement with empirical observations of mountain path formations. Such trails are characterized by a zig-zag pattern. Our extension took account of the inability of walkers to walk directly up or down very steep gradients. We have shown that some supplementary rules need to be included in the active walker model to achieve features consistent with mountain trails. Those additional rules are that (a) the consecutive steps of walkers tend to be in the same direction and that (b) there is a maximum permitted angle of motion down an incline to avoid falling and (c) there is a maximum angle of ascent for physiological reasons such as limited ankle flexibility. When rules to encourage consecutive steps are not present, we find that walkers travel in an unusual manner, only taking a single step before changing direction. We also found that the presence of walkers moving both uphill and downhill (with different forbidden angles) is important for forming well defined zig-zag paths. Walkers traveling downhill with a larger forbidden angle are constrained to form zigzags but create rather diffuse paths unless those paths are complemented by walkers traveling uphill. This happens because the walkers with more angular freedom become attracted to and reinforce the paths. 8. Source: (#GY93FG), p. 6 Context: #G4BEE9 Mountain trail formation and the active walker model #MKLE5Y 4. A model of mountain walkers #U98348 4.1. New rules for mountain walking Matching excerpt #ZHYXRP: It is our aim extend the active walker model to construct a “mountain walker model”. As we have discussed in section 3, our model should take account of the inability of walkers on steep inclines to walk directly up or down a slope if the gradient becomes too great, and avoid sudden changes of direction that can cause instability. 9. Source: (#GY93FG), p. 12 Context: #G4BEE9 Mountain trail formation and the active walker model #NBFQAN 5. Results #TPVRFV 5.1. Algorithm one Matching excerpt #WUZ6YE: In this section, results from the mountain walker extension to the active walker model are shown. We begin by considering only walkers traveling down the slope. The following parameters were used for the simulations: the maximum ground potential was set to G_{\max} = 200\text{m}^{-1} (the units of G are set by Eq. 3 and Eq. 4) while the minimum ground potential was set to G_0 = 0 . Larger values of G_{\max} lead to larger attraction to the path. A new walker descended the inclined area as soon as the existing walker reached the destination (tests showed that there was little difference between this scheme and starting a walker every 100s). The visibility, \sigma of the paths was set to 10m and the intensity, I was set to l^2 G_{\max}/N , where N is the number of footprints needed to wear the ground condition to 1/e of its maximum value. N was set to 50 footfalls and the weathering parameter was initially set to T = 1000\text{s} . The values of N and T are smaller than in a real trail system, where N would be of the order of several hundred footfalls and T would be of the order of a few days. This still leads to realistic simulations since Helbing et al. have found that a combination of several parameters of the active walker model could be represented by the single parameter \kappa = IT/\sigma = G_{\max}T/N\sigma 7 . Individual walkers were assigned a random speed between 0.5m/s and 1.5m/s. In the simulation, walkers were given the starting position \mathbf{r}_{\text{initial}} = (0\text{m}, 5\text{m}) and a destination of \mathbf{r}_{\text{final}} = (25\text{m}, 5\text{m}) with the x -direction being the distance down the incline and y -direction the distance across the incline. Initially, 25000 walkers traversed the incline in each simulation. 10. Source: (#GY93FG), p. 4 Context: #G4BEE9 Mountain trail formation and the active walker model #A5Y7MA 2. Active walker model for human trails Matching excerpt #NPX9NY: The active walker model has been successful in describing some of the unexpected features that have been observed in trail systems. The application of the active walker model to the winding paths found on steep inclines has not yet been considered. In the following section, we discuss the biomechanics of walking on inclined planes with the aim of developing additional rules to explain the wiggles observed in trail systems on hills. Approximate matches 1. Source: (#GY93FG), p. 3 Context: #G4BEE9 Mountain trail formation and the active walker model #A5Y7MA 2. Active walker model for human trails Score: 0.03 Related excerpt #BLYR6Y: In order to investigate trail formations on mountains we use a modified form of the active walker model, which was introduced in Refs. 7 and 9. In this section, we review the rules of the unmodified active walker model following the scheme introduced in Ref. 7. Since the active walker model forms the basis of our extension to mountain trails, it is our aim to ensure that all specific features of the active walker model are clear, before introducing our extensions to the model in section 4. 2. Source: (#GY93FG), p. 16 Context: #G4BEE9 Mountain trail formation and the active walker model #HX4K49 6. Summary Score: 0.029 Related excerpt #S2VCY4: We have developed an extension to the active walker model to handle the formation of trails on inclines. Our simulations are in qualitative agreement with empirical observations of mountain path formations. Such trails are characterized by a zig-zag pattern. Our extension took account of the inability of walkers to walk directly up or down very steep gradients. We have shown that some supplementary rules need to be included in the active walker model to achieve features consistent with mountain trails. Those additional rules are that (a) the consecutive steps of walkers tend to be in the same direction and that (b) there is a maximum permitted angle of motion down an incline to avoid falling and (c) there is a maximum angle of ascent for physiological reasons such as limited ankle flexibility. When rules to encourage consecutive steps are not present, we find that walkers travel in an unusual manner, only taking a single step before changing direction. We also found that the presence of walkers moving both uphill and downhill (with different forbidden angles) is important for forming well defined zig-zag paths. Walkers traveling downhill with a larger forbidden angle are constrained to form zigzags but create rather diffuse paths unless those paths are complemented by walkers traveling uphill. This happens because the walkers with more angular freedom become attracted to and reinforce the paths. 3. Source: (#GY93FG), p. 12 Context: #G4BEE9 Mountain trail formation and the active walker model #NBFQAN 5. Results #TPVRFV 5.1. Algorithm one Score: 0.028 Related excerpt #WUZ6YE: In this section, results from the mountain walker extension to the active walker model are shown. We begin by considering only walkers traveling down the slope. The following parameters were used for the simulations: the maximum ground potential was set to G_{\max} = 200\text{m}^{-1} (the units of G are set by Eq. 3 and Eq. 4) while the minimum ground potential was set to G_0 = 0 . Larger values of G_{\max} lead to larger attraction to the path. A new walker descended the inclined area as soon as the existing walker reached the destination (tests showed that there was little difference between this scheme and starting a walker every 100s). The visibility, \sigma of the paths was set to 10m and the intensity, I was set to l^2 G_{\max}/N , where N is the number of footprints needed to wear the ground condition to 1/e of its maximum value. N was set to 50 footfalls and the weathering parameter was initially set to T = 1000\text{s} . The values of N and T are smaller than in a real trail system, where N would be of the order of several hundred footfalls and T would be of the order of a few days. This still leads to realistic simulations since Helbing et al. have found that a combination of several parameters of the active walker model could be represented by the single parameter \kappa = IT/\sigma = G_{\max}T/N\sigma 7 . Individual walkers were assigned a random speed between 0.5m/s and 1.5m/s. In the simulation, walkers were given the starting position \mathbf{r}_{\text{initial}} = (0\text{m}, 5\text{m}) and a destination of \mathbf{r}_{\text{final}} = (25\text{m}, 5\text{m}) with the x -direction being the distance down the incline and y -direction the distance across the incline. Initially, 25000 walkers traversed the incline in each simulation. 4. Source: (#GY93FG), p. 4 Context: #G4BEE9 Mountain trail formation and the active walker model #A5Y7MA 2. Active walker model for human trails Score: 0.028 Related excerpt #NPX9NY: The active walker model has been successful in describing some of the unexpected features that have been observed in trail systems. The application of the active walker model to the winding paths found on steep inclines has not yet been considered. In the following section, we discuss the biomechanics of walking on inclined planes with the aim of developing additional rules to explain the wiggles observed in trail systems on hills. 5. Source: (#GY93FG), p. 0 Context: #G4BEE9 Mountain trail formation and the active walker model Score: 0.027 Related excerpt #2QALPN: We extend the active walker model to address the formation of paths on gradients, which have been observed to have a zigzag form. Our extension includes a new rule which prohibits direct descent or ascent on steep inclines, simulating aversion to falling. Further augmentation of the model stops walkers from changing direction very rapidly as that would likely lead to a fall. The extended model predicts paths with qualitatively similar forms to the observed trails, but only if the terms suppressing sudden direction changes are included. The need to include terms into the model that stop rapid direction change when simulating mountain trails indicates that a similar rule should also be included in the standard active walker model. 6. Source: (#GY93FG), p. 3 Context: #G4BEE9 Mountain trail formation and the active walker model #A5Y7MA 2. Active walker model for human trails Score: 0.026 Related excerpt #W2NAB3: The aim of the active walker model is to describe the formation of paths in soft ground. As pedestrians walk on soft surfaces such as grass, the ground becomes worn and a path emerges. In the active walker model, the wear on the soft surface is assumed to be represented by a function, G(\mathbf{r}, t) , which represents the ground condition at time t and position \mathbf{r} . As is common in statistical physics, G(\mathbf{r}, t) is assumed to evolve according to a first-order rate equation, 7. Source: (#GY93FG), p. 2 Context: #G4BEE9 Mountain trail formation and the active walker model #2F9V87 1. Introduction Score: 0.024 Related excerpt #UWUSQ2: This article continues as follows. We review the rules of the active walker model in section 2. In section 3 we briefly discuss aspects of the biomechanics of walking on inclines. Extensions of the active walker model for mountain trail systems are introduced in section 4. Results of simulations are shown in section 5. Finally we summarize in section 6. 8. Source: (#GY93FG), p. 1 Context: #G4BEE9 Mountain trail formation and the active walker model #2F9V87 1. Introduction Score: 0.024 Related excerpt #364B8H: The energetics of walking on an incline have been discussed by Alexander in a simple model of bipedal locomotion 1 . From energy considerations, walkers aim to change the angle of ascent from the vertical if a hill reaches a steep enough gradient. In Ref. 1, human walkers are omniscient, and are able to assess the energetic outlay for an entire route. In this way, they can assess if more energy would be expended taking a shallower and longer route, or if a quick hike up a steep route would be more favorable. We consider that it is unlikely that the information about all possible routes is available for global decisions to influence route and planning, and expect that decisions are more likely to be local. Moreover, modeling has concluded that humans choose well trodden paths in a more local manner 8 . We therefore consider that insight into mountain trail formation could be gained from active walker simulations of inclined planes. 9. Source: (#GY93FG), p. 17 Context: #G4BEE9 Mountain trail formation and the active walker model #HX4K49 6. Summary Score: 0.024 Related excerpt #BQSVBB: The preference of walkers to take consecutive steps in the same direction could also be relevant for the understanding of trail formation in flat areas, and it is our opinion that a persistence of direction parameter should also be included when simulating trail systems on level ground. Thus, our main conclusions are that (1) correlation between consecutive step directions should be included in the active walker model and that (2) an extension of the active walker model to include forbidden angles, correlation between consecutive steps and the combination of walkers moving both up- and down-hill is suitable to understand the formation of mountain paths. 10. Source: (#GY93FG), p. 16 Context: #G4BEE9 Mountain trail formation and the active walker model #NBFQAN 5. Results #TPVRFV 5.1. Algorithm one Score: 0.023 Related excerpt #WJQCMK: combined effect of walkers moving in both directions are trails with zig-zag patterns that have a similar angle to the largest of the two forbidden angles. The walkers with a smaller forbidden angle round off the sharp turns in the paths that were found on the zig-zags formed when walkers are only permitted to move in a single direction. This rounding is a direct consequence of the attraction term in the active walker model and may explain the curved nature of spontaneously formed mountain trails. Moreover, the inclusion of walkers with different minimum safe angles leads to well defined trails (rather than the diffuse trails found previously). This is probably because the walkers with smaller forbidden angles have more freedom to change direction, allowing the active walker rules to function effectively. ### 26. Tool result: search_text Exact matches 1. Source: (#LXV9AT), p. 5 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #JZHJ8Q 5.4. Identification of Trail Use Types, Classifications, and Design Standards Matching excerpt #MNKS7H: Before a designer can layout a trail, they must know for whom they are designing the trail and with what standards for design and construction they must comply. During the planning process, the use for a proposed trail is identified. (See Chapter 3, Planning and Environmental Compliance .) Trails are pedestrian, equestrian, mountain biking, motorized (off highway vehicle), or multi-use. New pedestrian trails that start at a trailhead or connect to an accessible trail may be required to meet accessibility criteria. The layout and design process determines the feasibility of meeting accessibility requirements. Federal, State, and local design and construction standards, as well as the potential use types are identified. Once the use types have been identified, the proposed trail is classified using a matrix. (See Chapter 2, Trail System Development and Management .) Each classification has minimum design and construction standards that must be incorporated along with use type standards. Additionally, the potential rate of mechanical wear associated with the use type must be identified and compensated for in design, layout, and construction. 2. Source: (#LXV9AT), p. 4 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #4DMRYZ 5.3. Identification of Need Matching excerpt #M7S2ZY: The design and layout of a new trail or trail reroute need to follow a well thought out process. This chapter outlines a process that will assist designers in laying out trails that protect natural and cultural resources, meet user needs, and are sustainable. This process will also expedite the time it takes to layout and flag a new trail alignment. It will reduce the frustration associated with traditional trail layout practices and will ensure that the best possible trail alignment has been located on the landform. 3. Source: (#LXV9AT), p. 15 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #BUKYGV 5.5. Mechanical Wear #8BXTCV 5.5.4. Sudden Grade Changes Matching excerpt #WHZ4PN: Because of the increased mechanical wear, sudden grade changes should be avoided by following the layout and design principles identified in this chapter and Chapter 14, Drainage Structures . If a drainage structure such as a grade reversal is used, the grades going into and out of the structure should be gradual and never exceed the maximum sustainable linear grade. 4. Source: (#LXV9AT), p. 4 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #4DMRYZ 5.3. Identification of Need Matching excerpt #43VP2F: Trail design and layout begins with the concept that a trail is needed to provide access to an area or destination, which may include several points of interest or connections with other trails. Starting and ending points are then identified for the trail. Usually, these locations tie into existing trail systems or developed recreational facilities that are part of a larger facility management plan. A facility management plan may be general or specific in nature and, in identifying the need for a trail, the benefits of the new trail may have been weighed against the potential impact. (See Chapter 3, Planning and Environmental Compliance .) At this point, the proposed trail alignment is purely conceptual—a broad corridor between the starting and ending points. Its exact location on the landform has yet to be determined. Figure 5.1 illustrates a broad conceptual trail corridor (in brown) that connects a campground to a backcountry camp. 5. Source: (#LXV9AT), p. 26 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #M2FCT4 5.6. Maintaining Natural Drainage Matching excerpt #53UT2Z: CALIFORNIA STATE PARKS 6. Source: (#LXV9AT), p. 38 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #9WNHGK 5.7.5. Field Reconnaissance #7JBFFE 5.7.5.1. Minor Control Point Identification #4U7TV6 TRAIL LAYOUT AND DESIGN Matching excerpt #5J3H67: CALIFORNIA STATE PARKS 7. Source: (#LXV9AT), p. 55 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #8BZAPC 5.7.7. Flagging the Trail Alignment #AGRR47 5.7.7.1. Initial Flagging Process #SKHQPC SIGHTING FOR GRADE WITH CLINOMETER Matching excerpt #6CRK7R: CALIFORNIA STATE PARKS 8. Source: (#LXV9AT), p. 61 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #8BZAPC 5.7.7. Flagging the Trail Alignment #AGRR47 5.7.7.1. Initial Flagging Process #A8QPLC TRAVELWAY EXCAVATIONS Matching excerpt #ULQNZG: CALIFORNIA STATE PARKS 9. Source: (#LXV9AT), p. 49 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #9WNHGK 5.7.5. Field Reconnaissance #XG25M6 5.7.5.2. Designed Control Points #UM24VH 5.7.5.2.4. Problematic Topography Matching excerpt #8SAPUK: Another common trail design and layout mistake is to route a trail through a meadow. Again, most meadows are on flat and poorly drained ground. Once the trail is constructed, the trail bed is lower than the surrounding soil horizons. The trail collects water, causing the trail bed to become saturated, deformed, and eroded. Once the trail reaches this condition, trail users will no longer stay within the trail bed and will develop a trail parallel to the degraded one. If left uncorrected, this situation often leads to multiple parallel trails developing across the meadow, each one replacing the entrenched and degraded trail that preceded it. (See Photo 5.34.) 10. Source: (#LXV9AT), p. 3 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design Matching excerpt #YJ94UZ: Trail layout and design are the processes of applying modern trail design concepts to a systematic approach of laying out trails. They are used to determine the location and construction standards for a trail and are the most important elements of a trail system because if they are not performed correctly the trail will not be sustainable and will always be a liability. Trail layout and design are as much art as they are science, and a well-designed trail has both form and function. Layout and design concepts include: Approximate matches 1. Source: (#LXV9AT), p. 4 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #4DMRYZ 5.3. Identification of Need Score: 0.03 Related excerpt #M7S2ZY: The design and layout of a new trail or trail reroute need to follow a well thought out process. This chapter outlines a process that will assist designers in laying out trails that protect natural and cultural resources, meet user needs, and are sustainable. This process will also expedite the time it takes to layout and flag a new trail alignment. It will reduce the frustration associated with traditional trail layout practices and will ensure that the best possible trail alignment has been located on the landform. 2. Source: (#LXV9AT), p. 5 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #JZHJ8Q 5.4. Identification of Trail Use Types, Classifications, and Design Standards Score: 0.029 Related excerpt #MNKS7H: Before a designer can layout a trail, they must know for whom they are designing the trail and with what standards for design and construction they must comply. During the planning process, the use for a proposed trail is identified. (See Chapter 3, Planning and Environmental Compliance .) Trails are pedestrian, equestrian, mountain biking, motorized (off highway vehicle), or multi-use. New pedestrian trails that start at a trailhead or connect to an accessible trail may be required to meet accessibility criteria. The layout and design process determines the feasibility of meeting accessibility requirements. Federal, State, and local design and construction standards, as well as the potential use types are identified. Once the use types have been identified, the proposed trail is classified using a matrix. (See Chapter 2, Trail System Development and Management .) Each classification has minimum design and construction standards that must be incorporated along with use type standards. Additionally, the potential rate of mechanical wear associated with the use type must be identified and compensated for in design, layout, and construction. 3. Source: (#LXV9AT), p. 3 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design Score: 0.028 Related excerpt #YJ94UZ: Trail layout and design are the processes of applying modern trail design concepts to a systematic approach of laying out trails. They are used to determine the location and construction standards for a trail and are the most important elements of a trail system because if they are not performed correctly the trail will not be sustainable and will always be a liability. Trail layout and design are as much art as they are science, and a well-designed trail has both form and function. Layout and design concepts include: 4. Source: (#LXV9AT), p. 4 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #4DMRYZ 5.3. Identification of Need Score: 0.028 Related excerpt #43VP2F: Trail design and layout begins with the concept that a trail is needed to provide access to an area or destination, which may include several points of interest or connections with other trails. Starting and ending points are then identified for the trail. Usually, these locations tie into existing trail systems or developed recreational facilities that are part of a larger facility management plan. A facility management plan may be general or specific in nature and, in identifying the need for a trail, the benefits of the new trail may have been weighed against the potential impact. (See Chapter 3, Planning and Environmental Compliance .) At this point, the proposed trail alignment is purely conceptual—a broad corridor between the starting and ending points. Its exact location on the landform has yet to be determined. Figure 5.1 illustrates a broad conceptual trail corridor (in brown) that connects a campground to a backcountry camp. 5. Source: (#LXV9AT), p. 48 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #9WNHGK 5.7.5. Field Reconnaissance #XG25M6 5.7.5.2. Designed Control Points #UM24VH 5.7.5.2.4. Problematic Topography Score: 0.026 Related excerpt #DY8MQW: If a trail is to be located along a ridge, it is much better design practice to locate it just below the ridge top where hillside construction will facilitate sheet flow across the trail bed. The trail is close enough to the top of the ridge to offer good views yet facilitate natural surface runoff. This layout practice may also provide opportunities to have the trail cross the ridge top where a low point or saddle occurs. This design offers the trail user different views in a dramatic fashion rather than just seeing the same view for an extended period of time. (See Figure 5.9.) 6. Source: (#LXV9AT), p. 52 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #NQEU6U 5.7.6. Final Grade Reconciliation Score: 0.026 Related excerpt #L3XFUM: At this point in the design and layout process, the trail designer determines if the proposed trail alignment is sustainable or not. If it is sustainable, move forward with flagging the trail alignment. If it is not sustainable, the findings should be documented and the proposed trail should not be pursued. However, in some cases, if the trail alignment is determined to be not sustainable but is maintainable, and the proposed trail is required due to critical operational needs or public demand, then the designer should identify the deficiencies in the proposed trail and quantify the additional costs to construct and maintain the proposed trail. Appropriate managers should then determine if the proposed trail alignment should be pursued. 7. Source: (#LXV9AT), p. 3 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #92S5AZ 5.1. Life of a Trail Score: 0.025 Related excerpt #CNZ78C: How well a trail performs is influenced by the quality of its design. The design process can take from days to months to complete. The more time and effort spent evaluating the landform and identifying the appropriate location, the better the trail will perform over its lifetime. Thus, a detailed planning and design process must be followed. Even the best-constructed trails will not perform well if the initial design is inadequate. 8. Source: (#LXV9AT), p. 4 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #QB5YWT 5.2. Elements of a Good Trail Score: 0.024 Related excerpt #T4XNYZ: A trail is more than a route to a desired destination; it is an experience. The designer integrates points of interest and aesthetic experiences with a technically sound alignment. A well-designed trail seamlessly traverses the natural setting. The focus of the user is on the environment they are passing through and not on the trail. 9. Source: (#LXV9AT), p. 52 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #NQEU6U 5.7.6. Final Grade Reconciliation Score: 0.024 Related excerpt #JTLEZB: Once all major and minor control points are located within the trail corridor, the average and maximum sustainable linear grades between control points are identified. These grades can then be compared to the designed trail grade. If there are no conflicts, the trail alignment can be finalized. The final linear grade between each control point must be equal to or less than the maximum sustainable linear grade and the designed grade, which may require reconciling segments where the average linear grade exceeds these limits. Additional linear run can be obtained through topographical turns, climbing turns, or switchbacks. Engineered and constructed solutions may also be necessary to work through minor controls and reduce linear grades, which can require many days in the field. By completing this trail design process, the designer will gain a thorough knowledge of the landform and be aware of all the issues and proposed design solutions. By the end of field reconnaissance, the designer should have explored every possible routing and selected one that represents the best possible alignment. For pedestrian trails, the designer can now determine if the proposed alignment meets accessibility standards. By now, every option should have been explored to design and construct an accessible trail. 10. Source: (#LXV9AT), p. 34 Context: #HE95FY Chapter 5. Principles of Trail Layout and Design #EEPQMJ 5.7. Trail Layout #9WNHGK 5.7.5. Field Reconnaissance Score: 0.023 Related excerpt #SBRLFV: Once a proposed trail corridor that incorporates major control points and average linear grades between the points is identified on a map, field reconnaissance is performed along the route to verify the landform. It is a good idea to involve resource specialists, including engineering geologists, hydrologists, botanists, resource ecologists, wildlife biologists, archeologists, and historians. Getting their involvement early in the design and layout process improves the evaluation of the landform, enhances the synergy that occurs between disciplines, and reduces any conflict that may occur before the environmental review. Some specialists prefer to wait until there is a flag line on the ground before they perform an assessment. Either way, the sooner resource specialists are involved, the better the layout process will be. ### 27. Tool result: search_text Exact matches 1. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #RKYUN2: Joachim Keltsch 2. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #7HHF2H: Dirk Helbing 3. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #CR8C3T: Many human social phenomena, such as cooperation [1–3], the growth of settlements [4], traffic dynamics [5–7] and pedestrian movement [7–10], appear to be accessible to mathematical descriptions that invoke self-organization [11,12]. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are [13], and whether optimal path systems can be predicted for urban planning. We use an ‘active walker’ model [14–19] that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical [14–16], chemical [17] and biological [18,19] systems. We find that our model is able to reproduce many of the observed large-scale spatial features of trail systems. 4. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #9VG852: Péter Molnár 5. Source: (#UYLTYJ), p. 1 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #F6A63D: Previous studies have shown that various observed self-organization phenomena in pedestrian crowds can be simulated very realistically. This includes the emergence of lanes of uniform walking direction and oscillatory changes of the passing direction at bottlenecks [7,10]. Another interesting collective effect of pedestrian motion, which we have investigated very recently, is the formation of trail systems in green areas. In many cases, the pedestrians' desire to take the shortest way and the specific properties of the terrain are insufficient for an explanation of the trail characteristics. It is essential to include the effect of human orientation. To simulate the typical features of trail systems, we have extended the aforementioned model of pedestrian motion to an active walker model by introducing equations for environmental changes and their impact on the chosen walking direction. 6. Source: (#UYLTYJ), p. 4 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #NZURVZ: In summary, the presented active walker model is able to describe the self-organization and the typical structural properties of human trail systems. It will be interesting to relate our model to the work on space syntax [23]. Repulsive interactions between pedestrians can be taken into account by generalizing equation (4) in accordance with the social force model of pedestrian motion [7,10]. However, these are only relevant in cases of frequent pedestrian interactions, in which they lead to broader trails. 7. Source: (#UYLTYJ), p. 3 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #7WG2F4: Therefore, we suggest to use the above model as a tool for urban planners and landscape gardeners, who have the dilemma to build most comfortable way systems at minimal construction costs. For planning purposes one needs to know the entry points and destinations within the considered area and the rates of usage of their connections. If necessary, these can be estimated by trip chaining models [22], which are also needed in cases of complex lines of access and sight. The effects of the physical terrain and already existing ways can be taken into account by the function G_0(\vec{r}) . By varying the model parameter \kappa , the overall length of the resulting trail system can be influenced (Figures 2 and 3). In the same way, one can check its structural stability. Presently, we are evaluating typical parameter values of \lambda and \kappa by comparison of simulation results with real pedestrian flows which are reconstructed from video films by image processing. These values shall be used for designing convenient way systems in residential areas, parks, and recreation areas by means of computer simulations (Figure 3). We expect that such way systems will actually be accepted, since they take into account the route choice habits of pedestrians. 8. Source: (#UYLTYJ), p. 3 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #PG7BAQ: A direct way system (which provides the shortest connections, but covers a lot of space) only develops if all ways are almost equally comfortable. If the advantage \kappa of using existing trails is large, the final trail system is a minimal way system (which is the shortest way system that connects all entry points and destinations). For realistic values of \kappa , the evolution of the trail system stops before this state is reached (Figure 2). Thus, \kappa is related to the average relative detour of the walkers. We conjecture that the resulting way system is the shortest one which is compatible with a certain accepted relative detour. In this sense, it yields an optimal compromise between convenience and shortness. 9. Source: (#UYLTYJ), p. 2 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #4DF7BV: A comparison of simulation results with photographs shows that the above described model is in good agreement with empirical observations. In particular, the evolution of the unexpected ‘island’ in the middle of the trail system in Figure 1 can be correctly described (Figure 2). The goodness of fit of the model is quite surprising, since it contains only two independent parameters \kappa = IT/\sigma^2 and \lambda = V^0 T/\sigma , where V^0 denotes the average of the desired velocities v_\alpha^0 . This can be shown by scaling the model to dimensionless equations. The parameter \lambda was kept constant. 10. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Matching excerpt #M2D4A8: The Center of Theoretical Studies of Physical Systems, 223 James P. Brawley Drive, Atlanta, Georgia 30314, USA Approximate matches 1. Source: (#UYLTYJ), p. 0 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.03 Related excerpt #CR8C3T: Many human social phenomena, such as cooperation [1–3], the growth of settlements [4], traffic dynamics [5–7] and pedestrian movement [7–10], appear to be accessible to mathematical descriptions that invoke self-organization [11,12]. Here we develop a model of pedestrian motion to explore the evolution of trails in urban green spaces such as parks. Our aim is to address such questions as what the topological structures of these trail systems are [13], and whether optimal path systems can be predicted for urban planning. We use an ‘active walker’ model [14–19] that takes into account pedestrian motion and orientation and the concomitant feedbacks with the surrounding environment. Such models have previously been applied to the study of complex structure formation in physical [14–16], chemical [17] and biological [18,19] systems. We find that our model is able to reproduce many of the observed large-scale spatial features of trail systems. 2. Source: (#UYLTYJ), p. 3 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.029 Related excerpt #ST8FZE: At the beginning, pedestrians take the direct ways to their respective destinations. However, after some time they begin to use already existing trails, since this is more comfortable than to clear new ways. By this, a kind of selection process [20,21,16] between trails sets in: Frequently used trails are more attractive than others. For this reason they are chosen very often, and the resulting reinforcement makes them even more attractive. However, the weathering effect destroys rarely used trails and limits the maximum length of the way system which can be supported by a certain rate of trail usage. As a consequence, the trails begin to bundle, especially where different trails meet or intersect. This explains, why pedestrians with different destinations use and produce common parts of the trail system (Figures 2 and 3). 3. Source: (#UYLTYJ), p. 3 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.029 Related excerpt #7WG2F4: Therefore, we suggest to use the above model as a tool for urban planners and landscape gardeners, who have the dilemma to build most comfortable way systems at minimal construction costs. For planning purposes one needs to know the entry points and destinations within the considered area and the rates of usage of their connections. If necessary, these can be estimated by trip chaining models [22], which are also needed in cases of complex lines of access and sight. The effects of the physical terrain and already existing ways can be taken into account by the function G_0(\vec{r}) . By varying the model parameter \kappa , the overall length of the resulting trail system can be influenced (Figures 2 and 3). In the same way, one can check its structural stability. Presently, we are evaluating typical parameter values of \lambda and \kappa by comparison of simulation results with real pedestrian flows which are reconstructed from video films by image processing. These values shall be used for designing convenient way systems in residential areas, parks, and recreation areas by means of computer simulations (Figure 3). We expect that such way systems will actually be accepted, since they take into account the route choice habits of pedestrians. 4. Source: (#UYLTYJ), p. 4 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.027 Related excerpt #NZURVZ: In summary, the presented active walker model is able to describe the self-organization and the typical structural properties of human trail systems. It will be interesting to relate our model to the work on space syntax [23]. Repulsive interactions between pedestrians can be taken into account by generalizing equation (4) in accordance with the social force model of pedestrian motion [7,10]. However, these are only relevant in cases of frequent pedestrian interactions, in which they lead to broader trails. 5. Source: (#UYLTYJ), p. 1 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.027 Related excerpt #F6A63D: Previous studies have shown that various observed self-organization phenomena in pedestrian crowds can be simulated very realistically. This includes the emergence of lanes of uniform walking direction and oscillatory changes of the passing direction at bottlenecks [7,10]. Another interesting collective effect of pedestrian motion, which we have investigated very recently, is the formation of trail systems in green areas. In many cases, the pedestrians' desire to take the shortest way and the specific properties of the terrain are insufficient for an explanation of the trail characteristics. It is essential to include the effect of human orientation. To simulate the typical features of trail systems, we have extended the aforementioned model of pedestrian motion to an active walker model by introducing equations for environmental changes and their impact on the chosen walking direction. 6. Source: (#UYLTYJ), p. 2 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.026 Related excerpt #4DF7BV: A comparison of simulation results with photographs shows that the above described model is in good agreement with empirical observations. In particular, the evolution of the unexpected ‘island’ in the middle of the trail system in Figure 1 can be correctly described (Figure 2). The goodness of fit of the model is quite surprising, since it contains only two independent parameters \kappa = IT/\sigma^2 and \lambda = V^0 T/\sigma , where V^0 denotes the average of the desired velocities v_\alpha^0 . This can be shown by scaling the model to dimensionless equations. The parameter \lambda was kept constant. 7. Source: (#UYLTYJ), p. 1 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.025 Related excerpt #QCBYWJ: First, we represent the ground structure at place \vec{r} and time t by a function G(\vec{r}, t) which reflects the comfort of walking. Trails are characterized by particularly large values of G . On the one hand, at their positions \vec{r} = \vec{r}_\alpha(t) , all pedestrians \alpha leave footprints on the ground (e.g. by trampling down some vegetation). Their intensity is assumed to be I(\vec{r})[1 - G(\vec{r}, t)/G_{\max}(\vec{r})] , since the clarity of a trail is limited to a maximum value G_{\max}(\vec{r}) . This causes a saturation effect [1 - G(\vec{r}, t)/G_{\max}(\vec{r})] of the ground's alteration by new footprints. On the other hand, the ground structure changes due to the vegetation's regeneration. This will lead to a restoration of the natural ground conditions G_0(\vec{r}) with a certain weathering rate 1/T(\vec{r}) which is related to the durability T(\vec{r}) of trails. Thus, the equation of environmental changes reads 8. Source: (#UYLTYJ), p. 2 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.024 Related excerpt #FXKR3R: The trail potential V_{\text{tr}}(\vec{r}_\alpha, t) reflects the attractiveness of walking at place \vec{r}_\alpha . It describes indirect long-range interactions via environmental changes, which are essential for the characteristics of the evolving patterns [18]. 9. Source: (#UYLTYJ), p. 3 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.024 Related excerpt #PG7BAQ: A direct way system (which provides the shortest connections, but covers a lot of space) only develops if all ways are almost equally comfortable. If the advantage \kappa of using existing trails is large, the final trail system is a minimal way system (which is the shortest way system that connects all entry points and destinations). For realistic values of \kappa , the evolution of the trail system stops before this state is reached (Figure 2). Thus, \kappa is related to the average relative detour of the walkers. We conjecture that the resulting way system is the shortest one which is compatible with a certain accepted relative detour. In this sense, it yields an optimal compromise between convenience and shortness. 10. Source: (#UYLTYJ), p. 2 Context: #BSSYS2 Modelling the Evolution of Human Trail Systems Score: 0.024 Related excerpt #PMPCXQ: Our simulations base on a discretization of the considered area in small quadratic elements of equal size, which converts the integral (2) into a sum. Temporal and spatial derivatives are approximated by difference quotients. The presented examples begin with plain, homogeneous ground. All pedestrians have their own destinations and entry points, from which they start at a randomly chosen point in time. In Figure 2 (Figure 3) pedestrians move between all possible pairs of three (four) fixed places. While in Figure 4 the entry points and destinations are distributed over the small ends of the ground. ### 28. Tool result: search_text Exact matches 1. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 0 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Matching excerpt #H2R66Q: Active walker models have recently proved their great value for describing the formation of clusters, periodic patterns, and spiral waves as well as the development of rivers, dielectric breakdown patterns, and many other structures. It is shown that they also allow to simulate the formation of trail systems by pedestrians and ants, yielding a better understanding of human and animal behavior. A comparison with empirical material shows a good agreement between model and reality. 2. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 3 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Matching excerpt #T9CE9W: In Section II, the active walker model for trail formation is formulated in terms of a Langevin equation for the movement of the walkers, an equation for environmental changes, and a relation describing the orientation of the walkers with respect to existing trails. As one application of the model, Section III describes the formation of trunk trails in ant colonies, which are commonly used to exploit food sources. As a second application, in Section IV the evolution of pedestrian trail systems is modelled. Both Sections III and IV present a comparison of computational results with real trail systems, indicating a good agreement between model and empirical facts. In Section IV.A, the equations for pedestrian trail systems are scaled to dimensionless equations, in order to demonstrate that the evolving trail systems are (apart from the boundary conditions) only determined by two parameters. In Section IV.B, a macroscopic formulation of human trail formation is derived from the microscopic equations, allowing analytical investigations and an efficient calculation of the stationary solution by a self-consistent field method. Our conclusions and an outlook, which suggests an application of the model to the optimization of trail systems, are presented in Section V. 3. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 3 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Matching excerpt #8TZ5BY: Active walker models have proved their versatility in a variety of applications, such as formation of complex structures [36–42], pattern formation in physico-chemical systems [43–46], aggregation in biological [47,48] or urban [49] systems, and generation of directed motion [50,51]. The approach provides a quite stable and fast numerical algorithm for simulating processes involving large density gradients, and it is applicable also in cases where only small particle numbers govern the structure formation. In particular, the active walker model is applicable to processes of pattern formation which are intrinsically determined by the history of their creation, such as the formation of trail systems, discussed in this paper. 4. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 21 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #T6PSLK V. SUMMARY AND OUTLOOK #DTECU9 A. Trail formation as a self-organization phenomenon Matching excerpt #653HKK: With respect to the formation of trunk trails, our model indicates that these patterns can be obtained also under the restrictions, that (i) no visual navigation and internal storage of information is provided, (ii) in the beginning, no chemical signposts exist which lead the ants to the food sources and afterwards back to the nest. Rather, the formation of trail systems can be described as a process of self-organization. Based on the interactions of the active walkers on a local or ‘microscopic’ level, the emergence of a global or ‘macroscopic’ structure occurs. The basic interaction between the active walkers can be considered as indirect communication mediated by an external storage medium [43,63]. This is a collective process in which all active walkers are involved. The information which an active walker produces in terms of chemical markings affects the behaviors of the others. It can be amplified during the evolution process or disappear again, thus leading to a correlation between the information generated and to the self-organization of the walkers on a spatial level. 5. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 21 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #T6PSLK V. SUMMARY AND OUTLOOK #DTECU9 A. Trail formation as a self-organization phenomenon Matching excerpt #FPQ37S: In the example of trail formation by certain ant species, the major difference to biology is, that the active walkers used in the simulations have far less complex capabilities than the biological creatures. They almost behave like physical particles which respond to local forces in a quite simple manner, without “implicit and explicit intelligence” [56]. Compared to the complex ‘individual-based’ models in ecology [8], the active walker model proposed here provides a very simple but efficient tool to simulate a specific structure only with a few adjustable parameters. 6. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 2 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Matching excerpt #RF3SZN: In this paper, we draw the attention to the specific collective phenomenon of trail formation [33,34], which is widely spread in the world of animals and humans. Regarding their shape, duration and extension, trail systems of different animal species and humans differ, of course. However, more striking is the question, whether there is a common underlying dynamics which allows for a generalized description of the formation and evolution of trail systems. 7. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 20 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #T6PSLK V. SUMMARY AND OUTLOOK Matching excerpt #9RBRRU: We showed that the active walker concept is suitable for modeling and understanding trail formation by pedestrians and animals. Our model turned out to be in good agreement with observations. It included an equation of motion of the walkers, an equation describing environmental changes by the markings which they leave and their decay, a relation reflecting the attractiveness of already existing trails, and an equation delineating their influence on orientation. Whereas frequently used trails are reinforced, rarely chosen trails are vanishing in the course of time. This causes a tendency of trail bundling, which can be interpreted as an agglomeration phenomenon. However, the evolving patterns are not localized since the active walkers intend to reach certain destinations, starting from their respective entry points. 8. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 22 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #T6PSLK V. SUMMARY AND OUTLOOK #98Y5GR C. Current research directions Matching excerpt #564U43: Besides of possible applications, our present research focusses on two questions: (i) How must our trail formation model be specified in order to be applicable to trail formation by hoofed animals or mice [64,65]? (ii) Can our model be generalized in a way that allows to understand human decision making , in particular processes of finding suitable compromises? Interestingly enough, one says that someone “follows in somebody’s footsteps” or that someone “treads new paths”. Therefore, a related theory for a more abstract space (which represents the set of behavioral alternatives) may describe the evolution of social norms and conventions [11]. 9. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 1 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Matching excerpt #PCL35Q: The trail formation model can be used as a tool for the optimization of pedestrian facilities: It allows urban planners to design convenient way systems which actually meet the route choice habits of pedestrians. 10. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 7 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #P3AR99 III. TRUNK TRAIL FORMATION BY ANTS Matching excerpt #JF22FC: We will neglect these abilities, in order to show that they are not necessary for trail formation. The active walkers in our model merely count on the local information provided by the chemical trail, in order to guide themselves. They do not have additional navigation or information processing capabilities, and are not subject to long-range attracting forces to the food sources or to the nest. Hence, the formation of trunk trails in the following model is clearly a self-organizing process, based on the local interactions of the walkers [51]. Approximate matches 1. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 20 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #T6PSLK V. SUMMARY AND OUTLOOK Score: 0.026 Related excerpt #9RBRRU: We showed that the active walker concept is suitable for modeling and understanding trail formation by pedestrians and animals. Our model turned out to be in good agreement with observations. It included an equation of motion of the walkers, an equation describing environmental changes by the markings which they leave and their decay, a relation reflecting the attractiveness of already existing trails, and an equation delineating their influence on orientation. Whereas frequently used trails are reinforced, rarely chosen trails are vanishing in the course of time. This causes a tendency of trail bundling, which can be interpreted as an agglomeration phenomenon. However, the evolving patterns are not localized since the active walkers intend to reach certain destinations, starting from their respective entry points. 2. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 2 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Score: 0.014 Related excerpt #KXXUJY: As our experience tells us, trails are adapted to the requirements of their users. In the course of time, frequently used trails become more developed, making them more attractive, whereas rarely used trails vanish again. Trails with large detours become optimized by creating shortcuts. New destinations or entry points are connected to an existing trail system. These dynamical processes occur basically without any common planning or direct communication among the users. Instead, the adaptation process can be understood as a self-organization phenomenon, resulting from the non-linear feedback between the users and the trails [35]. 3. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 2 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Score: 0.013 Related excerpt #RF3SZN: In this paper, we draw the attention to the specific collective phenomenon of trail formation [33,34], which is widely spread in the world of animals and humans. Regarding their shape, duration and extension, trail systems of different animal species and humans differ, of course. However, more striking is the question, whether there is a common underlying dynamics which allows for a generalized description of the formation and evolution of trail systems. 4. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 11 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #3WQXTG IV. HUMAN TRAIL FORMATION Score: 0.013 Related excerpt #JN4H6B: Trail formation by pedestrians has been investigated only very recently [60]. It can be interpreted as a complex interplay between pedestrian motion, human orientation, and environmental changes: On the one hand, pedestrians tend to take the shortest way to their destination. On the other hand, they avoid to walk on bumpy ground, since this is uncomfortable. Therefore, they prefer to use existing trails, but they build a new shortcut, if the relative detour would be too large. In the latter case they generate a new trail, since footprints clear some vegetation. Examples of the resulting trail systems can be found in green areas, like public parks (cf. Fig. 3). 5. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 0 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Score: 0.013 Related excerpt #FZGBXK: Our trail formation model includes an equation of motion, an equation for environmental changes, and an orientation relation. It contains some model functions, which are specified according to the characteristics of the considered animals or pedestrians. Not only the kind of environmental changes differs: 6. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 1 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Score: 0.013 Related excerpt #PCL35Q: The trail formation model can be used as a tool for the optimization of pedestrian facilities: It allows urban planners to design convenient way systems which actually meet the route choice habits of pedestrians. 7. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 0 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems Score: 0.013 Related excerpt #SCV38X: The Center of Theoretical Studies of Physical Systems, 223 James P. Brawley Drive, Atlanta, Georgia 30314, USA 8. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 3 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #TTL9MC I. INTRODUCTION Score: 0.012 Related excerpt #8TZ5BY: Active walker models have proved their versatility in a variety of applications, such as formation of complex structures [36–42], pattern formation in physico-chemical systems [43–46], aggregation in biological [47,48] or urban [49] systems, and generation of directed motion [50,51]. The approach provides a quite stable and fast numerical algorithm for simulating processes involving large density gradients, and it is applicable also in cases where only small particle numbers govern the structure formation. In particular, the active walker model is applicable to processes of pattern formation which are intrinsically determined by the history of their creation, such as the formation of trail systems, discussed in this paper. 9. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 4 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #YEVN37 II. ACTIVE WALKER MODEL OF TRAIL FORMATION Score: 0.012 Related excerpt #XWN67Y: In order to introduce our model, we first describe the process of trail formation within a general stochastic framework. Hence, in this section the active walkers are not specified as pedestrians or animals. Rather, they are considered as arbitrary moving agents, who continuously change their environment by leaving markings while moving. These markings can, for example, be imagined as damaged vegetation on the ground (as in the case of hoofed animals or pedestrians) or as chemical markings (as in the case of ants). 10. Source: Active walker model for the formation of human and animal trail systems (#B6P8L4), Dirk Helbing, Frank Schweitzer, Joachim Keltsch, Péter Molnár, p. 0 Context: #E9C9Y2 Active Walker Model for the Formation of Human and Animal Trail Systems #4PR2LM Abstract Score: 0.012 Related excerpt #H2R66Q: Active walker models have recently proved their great value for describing the formation of clusters, periodic patterns, and spiral waves as well as the development of rivers, dielectric breakdown patterns, and many other structures. It is shown that they also allow to simulate the formation of trail systems by pedestrians and ants, yielding a better understanding of human and animal behavior. A comparison with empirical material shows a good agreement between model and reality. ### 29. Assistant Imported and validated all four PDFs: - **Modelling the Evolution of Human Trail Systems** — Helbing, Keltsch & Molnár (1998): #UYLTYJ - **Active Walker Model for the Formation of Human and Animal Trail Systems** — already present: #B6P8L4 - **Mountain Trail Formation and the Active Walker Model**: #GY93FG - **Chapter 5: Principles of Trail Layout and Design**, *California State Parks Trails Handbook*: #LXV9AT All reader pages are valid; 625 searchable rows were indexed with no embedding errors. **Metadata needs review:** the uploaded “Hata 2008” file identifies itself internally as a 2009 preprint by S. J. Gilks and J. P. Hague, while the California handbook extract does not establish a publication year. Sheaf therefore left those records—and #UYLTYJ—untitled rather than writing unverified citation metadata. Public metadata lookup also failed during this run. ### 30. User can you try the web search stuff again? we fixed some bugs in the web search result handling just now ### 31. Assistant I’ll retry canonical-source searches for all four records, focusing on author lists, publication year, venue, and DOI or report details. #### Tool call: `web_search` ```json { "query": "Verify canonical bibliographic metadata for \"Modelling the Evolution of Human Trail Systems\" by Dirk Helbing, Joachim Keltsch, and Peter Molnar: publication year, venue, volume, pages, DOI, and canonical publisher page." } ``` #### Tool call: `web_search` ```json { "query": "Verify canonical bibliographic metadata for \"Active Walker Model for the Formation of Human and Animal Trail Systems\" by Dirk Helbing et al.: publication year, journal, volume, issue, pages, DOI, and canonical publisher page." } ``` #### Tool call: `web_search` ```json { "query": "Verify canonical bibliographic metadata for \"Mountain trail formation and the active walker model\": correct authors, year, venue, volume, pages, DOI or arXiv identifier, and canonical source. Check whether it is by Hata (2008) or S. J. Gilks and J. P. Hague." } ``` #### Tool call: `web_search` ```json { "query": "Verify bibliographic metadata and canonical California State Parks source for \"Chapter 5. Principles of Trail Layout and Design\" from the California State Parks Trails Handbook: handbook title, edition/publication year (possibly 2019), corporate author, and official URL." } ``` ### 32. Tool result: web_search {"error":"no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1"} ### 33. Tool result: web_search {"error":"no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1"} ### 34. Tool result: web_search {"error":"no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1"} ### 35. Tool result: web_search {"error":"no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1"} ### 36. Assistant The batched retry still hit the same result-conversion error. I’m testing a single, shorter query directly to distinguish a batching issue from a general web-search issue. #### Tool call: `web_search` ```json { "query": "\"Mountain trail formation and the active walker model\" authors DOI" } ``` ### 37. Tool result: web_search {"error":"no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1"} ### 38. Assistant The retry still fails, including a direct non-batched query. The current error remains: `no function clause matching in Sheaf.Assistant.ToolResultText.to_text/1` So the failure is in web-search result conversion, not batching or query complexity. I made no metadata changes to #UYLTYJ, #B6P8L4, #GY93FG, or #LXV9AT. ### 39. User "The new errors are still the old formatter error, not a new bug. The reason is that this conversation was created before the deployment, and its long-lived chat process retained the old web_search callback closure even though the module files were hot-loaded. Every retry in that same chat therefore kept executing the stale callback." try now ### 40. Assistant tool calls #### Tool call: `web_search` ```json { "query": "\"Mountain trail formation and the active walker model\" authors DOI" } ``` ### 41. Tool result: web_search {"error":"Tool web_search not found"} ### 42. Assistant The chat process no longer has `web_search` registered at all now — the tool isn't in my available toolset for this session. The tools I currently have are the Sheaf reading, searching, and editing tools plus `document_import` and `tag_paragraphs`. If you start a fresh chat, web_search should be available and I can verify the three untitled records' metadata against public sources. ### 43. User do you see any new tools now? ### 44. Assistant (no text)