The Multi-Agent Transport Simulation MATSim
Andreas Horni (editor)
Politics & Social Sciences
The Multi-Agent Transport Simulation MATSim
Free
Description
Contents
Reviews

The MATSim (Multi-Agent Transport Simulation) software project was started around 2006 with the goal of generating traffic and congestion patterns by following individual synthetic travelers through their daily or weekly activity programme. It has since then evolved from a collection of stand-alone C++ programs to an integrated Java-based framework which is publicly hosted, open-source available, automatically regression tested. It is currently used by about 40 groups throughout the world. This book takes stock of the current status.

The first part of the book gives an introduction to the most important concepts, with the intention of enabling a potential user to set up and run basic simulations.The second part of the book describes how the basic functionality can be extended, for example by adding schedule-based public transit, electric or autonomous cars, paratransit, or within-day replanning. For each extension, the text provides pointers to the additional documentation and to the code base. It is also discussed how people with appropriate Java programming skills can write their own extensions, and plug them into the MATSim core.

The project has started from the basic idea that traffic is a consequence of human behavior, and thus humans and their behavior should be the starting point of all modelling, and with the intuition that when simulations with 100 million particles are possible in computational physics, then behavior-oriented simulations with 10 million travelers should be possible in travel behavior research. The initial implementations thus combined concepts from computational physics and complex adaptive systems with concepts from travel behavior research. The third part of the book looks at theoretical concepts that are able to describe important aspects of the simulation system; for example, under certain conditions the code becomes a Monte Carlo engine sampling from a discrete choice model. Another important aspect is the interpretation of the MATSim score as utility in the microeconomic sense, opening up a connection to benefit cost analysis.

Finally, the book collects use cases as they have been undertaken with MATSim. All current users of MATSim were invited to submit their work, and many followed with sometimes crisp and short and sometimes longer contributions, always with pointers to additional references.

We hope that the book will become an invitation to explore, to build and to extend agent-based modeling of travel behavior from the stable and well tested core of MATSim documented here.

Language
English
ISBN
978-1-909188-75-4
Cover
Title page
Copyright page
Contents
Cover Photos
Preface
Acknowledgements
Contributors
Introduction
Part I: Using MATSim
Chapter 1: Introducing MATSim (Andreas Horni, Kai Nagel and Kay W. Axhausen)
1.1 The Beginnings
1.2 In Brief
1.3 MATSim’s Traffic Flow Model
1.4 MATSim’s Co-Evolutionary Algorithm
Chapter 2: Let’s Get Started (Marcel Rieser, Andreas Horni and Kai Nagel)
2.1 Running MATSim
2.2 Building and Running a Basic Scenario
2.3 MATSim Survival Guide
Chapter 3: A Closer Look at Scoring (Kai Nagel, Benjamin Kickhöfer, Andreas Horni and David Charypar)
3.1 Good Plans and Bad Plans, Score and Utility
3.2 The Current Charypar-Nagel Utility Function
3.3 Implementation Details
3.4 Typical Scoring Function Parameters and their Calibration
3.5 Applications and Extensions
Chapter 4: More About Configuring MATSim (Andreas Horni and Kai Nagel)
4.1 MATSim Data Containers
4.2 Global Modules and Global Aspects
4.3 Mobility Simulations
4.4 Scoring
4.5 Replanning Strategies
4.6 Other Modes than Car
4.7 Observational Modules
Part II: Extending MATSim
Chapter 5: Available Functionality and How to Use It (Andreas Horni and Kai Nagel)
5.1 MATSim Modularity
5.2 An Overview of Existing MATSim Functionality
Subpart One: Input Data Preparation
Chapter 6: MATSim Data Containers (Marcel Rieser, Kai Nagel and Andreas Horni)
6.1 Time-Dependent Network
6.2 Person Attributes and Subpopulations
6.3 Counts
6.4 Facilities
6.5 Households
6.6 Vehicles
6.7 Scenario
Chapter 7: Generation of the Initial MATSim Input (Marcel Rieser, Kai Nagel and Andreas Horni)
7.1 Coordinate Transformations in Java
7.2 Network Generation
7.3 Initial Demand Generation
Chapter 8: MATSim JOSM Network Editor (Andreas Neumann and Michael Zilske)
8.1 Basic Information
8.2 Introduction
Chapter 9: Map-to-MapMatching Editors in Singapore (Sergio Arturo Ordóñnez)
9.1 Basic Information
Chapter 10: The “Network Editor” Contribution (Kai Nagel)
10.1 Basic Information
10.2 Short Description
Subpart Two: Mobsim
Chapter 11: QSim (Marcel Rieser, Kai Nagel and Andreas Horni)
11.1 Vehicle Types and Vehicles
11.2 Other
Subpart Three: Individual Car Traffic
Chapter 12: Traffic Signals and Lanes (Dominik Grether and Theresa Thunig)
12.1 Basic Information
12.2 Motivation
12.3 Traffic Signal Control
12.4 Network Representation & Traffic Flow
12.5 Iterations & Learning
12.6 Conclusion
Chapter 13: Parking (Rashid A.Waraich)
13.1 Basic Information
13.2 Introduction
13.3 Models
13.4 Applications
13.5 Usage
Chapter 14: Electric Vehicles (Rashid A.Waraich and Joschka Bischoff)
14.1 Introduction
14.2 Models
14.3 Application: Electric Taxis
14.4 Usage
Chapter 15: Road Pricing (Kai Nagel)
15.1 Basic Information
15.2 Introduction
15.3 Some Results
15.4 Invocation
Subpart Four: Other Modes Besides Individual Car
Chapter 16: Modeling Public Transport with MATSim (Marcel Rieser)
16.1 Basic Information
16.2 Introduction
16.3 Data Model and Simulation Features
16.4 File formats
16.5 Possible Improvements
16.6 Applications
Chapter 17: The “Minibus” Contribution (Andreas Neumann and Johan W. Joubert)
17.1 Basic Information
17.2 Paratransit
17.3 Network Planning or Solving the Transit Network Design Problem with MATSim
Chapter 18: Semi-Automatic Tool for Bus Route Map Matching (Sergio Arturo Ordóñnez)
18.1 Basic Information
18.2 Problem Definition
18.3 Solution Approach
18.4 Map-Matching Automatic Algorithm
18.5 Automatic Verification
18.6 Manual Editing Functionalities and Implemented Software
18.7 Conclusion and Outlook
Chapter 19: New Dynamic Events-Based Public Transport Router (Sergio Arturo Ordóñnez)
19.1 Basic Information
19.2 Events-Based Public Transport Router
19.3 Functional Results
19.4 Conclusion and Future Work
Chapter 20: Matrix-Based pt router (Kai Nagel)
20.1 Basic Information
20.2 Summary
Chapter 21: The “Multi-Modal” Contribution (Christoph Dobler and Gregor Lämmel)
21.1 Basic Information
21.2 Introduction
21.3 Modeling Approach and Implementation
21.4 Conclusions and Future Work
Chapter 22: Car Sharing (Francesco Ciari and Milos Balac)
22.1 Basic Information
22.2 Background
22.3 Modeling of Carsharing Demand in MATSim
22.4 Carsharing Membership
22.5 Validation
22.6 Applications
Chapter 23: Dynamic Transport Services (Michal Maciejewski)
23.1 Introduction
23.2 DVRP Contribution
23.3 DVRP Model
23.4 DynAgent
23.5 Agents in DVRP
23.6 Optimizer
23.7 Configuring and Running a DVRP Simulation
23.8 OneTaxi Example
23.9 Research with DVRP
Subpart Five: Commercial Traffic
Chapter 24: Freight Traffic (Michael Zilske and JohanW. Joubert)
24.1 Basic Information
24.2 Carriers
Chapter 25: WagonSim (Michael Balmer)
25.1 Basic Information
25.2 Summary
Chapter 26: freightChainsFromTravelDiaries (Kai Nagel)
Subpart Six: Additional Choice Dimensions
Chapter 27: Destination Innovation (Andreas Horni, Kai Nagel and Kay W. Axhausen)
27.1 Basic Information
27.2 Introduction
27.3 Key Issues in Developing the Module
27.4 Application of the Module
27.5 The Module in the MATSim Context
27.6 Lessons Learned
27.7 Further Reading
Chapter 28: Joint Decisions (Thibaut Dubernet)
28.1 Basic Information
28.2 Joint Decisions and Transport Systems
28.3 A Solution Algorithm for the Joint Planning Problem: A Generalization of the MATSim Process
28.4 Selected Results
28.5 Further Reading
Chapter 29: Socnetgen (Kai Nagel)
29.1 Basic Information
29.2 Summary
Subpart Seven: Within-Day Replanning
Chapter 30: Within-Day Replanning (Christoph Dobler and Kai Nagel)
30.1 Basic Information
30.2 Introduction
30.3 Simulation Approaches
30.4 Implementation
Chapter 31: Making MATSim Agents Smarter with the Belief-Desire-Intention Framework (Lin Padgham and Dhirendra Singh)
31.1 Basic Information
31.2 Introduction
31.3 Software Structure
31.4 Building an Application Using BDI Agents
31.5 Examples
Subpart Eight: Automatic Calibration
Chapter 32: CaDyTS: Calibration of Dynamic Traffic Simulations (Kai Nagel, Michael Zilske and Gunnar Flötteröd)
32.1 Basic Information
32.2 Introduction
32.3 Adjusting Plans Utility
32.4 Hooking Cadyts into MATSim
32.5 Applications
Subpart Nine: Visualizers
Chapter 33: Senozon Via (Marcel Rieser)
33.1 Basic Information
33.2 Introduction
33.3 Simple Usage
33.4 Use Cases and Examples
Chapter 34: OTFVis: MATSim’s Open-Source Visualizer (David Strippgen)
34.1 Basic Information
34.2 Introduction
34.3 Using OTFVis
34.4 Extending OTFVis
Subpart Ten: Analysis
Chapter 35: Accessibility (Dominik Ziemke)
35.1 Basic Information
35.2 Introduction
35.3 The Measure of Potential Accessibility
35.4 Accessibility Computation Integrated with Transport Simulation
35.5 Econometric Interpretation
35.6 Spatial Resolution, Data, and Computational Aspects
35.7 Conclusion
Chapter 36: Emission Modeling (Benjamin Kickhöfer)
36.1 Basic Information
36.2 Introduction
36.3 Integrated Approaches for Modeling Transport and Emissions
36.4 Emission Calculation
36.5 Software Structure
Chapter 37: Interactive Analysis and Decision Support with MATSim (Alexander Erath and Pieter Fourie)
37.1 Basic Information
37.2 Introduction
37.3 Requirements of a Decision Support Interface to MATSim
37.4 General Framework for Decision Support
37.5 Diaries from Events
Chapter 38: The “Analysis” Contribution (Kai Nagel)
38.1 Basic Information
38.2 Summary
Subpart Eleven: Computational Performance Improvements
Chapter 39: Multi-Modeling in MATSim: PSim (Pieter Fourie)
39.1 Basic Information
39.2 Introduction
39.3 Basic Idea
39.4 Performance
Chapter 40: Other Experiences with Computational Performance Improvements (Kai Nagel)
Subpart Twelve: Other Modules
Chapter 41: Evacuation Planning: An Integrated Approach (Gregor Lämmel, Christoph Dobler and Hubert Klüpfel)
41.1 Basic Information
41.2 Related Work
41.3 Download MATSim and Evacuation
41.4 The Fifteen-Minute Tour
41.5 Input Data (any Place and any Size)
41.6 Scenario Manager
41.7 Conclusion
Chapter 42: MATSim4UrbanSim (Kai Nagel)
42.1 Basic Information
42.2 Summary
Chapter 43: Discontinued Modules (Kai Nagel and Andreas Horni)
43.1 DEQSim
43.2 Planomat
43.3 PlanomatX
Subpart Thirteen: Development Process & Own Modules
Chapter 44: Organization: Development Process, Code Structure and Contributing to MATSim (Marcel Rieser, Andreas Horni and Kai Nagel)
44.1 MATSim’s Team, Core Developers Group, and Community
44.2 Roles in the MATSim Community
44.3 Code Base
44.4 Drivers, Organization and Tools of Development
44.5 Documentation, Dissemination and Support
44.6 Your Contribution to MATSim
Chapter 45: How to Write Your Own Extensions and Possibly Contribute Them to MATSim (Michael Zilske)
45.1 Introduction
45.2 Extension Points
Part III: Understanding MATSim
Chapter 46: Some History of MATSim (Kai Nagel and KayW. Axhausen)
46.1 Scientific Sources of MATSim
46.2 Stages of Development
Chapter 47: Agent-Based Traffic Assignment (Kai Nagel and Gunnar Flötteröd)
47.1 Introduction
47.2 From Route Swapping to Agent Plan Choice
47.3 Agent-Based Simulation
47.4 Conclusion
Chapter 48: MATSim as a Monte-Carlo Engine (Gunnar Flötteröd)
48.1 Introduction
48.2 Relaxation as a Stochastic Process
48.3 Existence and Uniqueness of MATSim Solutions
48.4 Analyzing Simulation Outputs
48.5 Summary
Chapter 49: Choice Models in MATSim (Gunnar Flötteröd and Benjamin Kickhöfer)
49.1 Evaluating Choice Models in a Simulated Environment
49.2 Evolution of Choice Sets in a Simulated Environment
49.3 Summary
Chapter 50: Queueing Representation of Kinematic Waves (Gunnar Flötteröd)
50.1 Introduction
50.2 Link Model
50.3 Node Model
50.4 Summary
Chapter 51: Microeconomic Interpretation of MATSim for Benefit-Cost Analysis (Benjamin Kickhöfer and Kai Nagel)
51.1 Revisiting MATSim’s Behavioral Simulation
51.2 Valuing Human Behavior at the Individual Level
51.3 Aggregating Individual Values
Part IV: Scenarios
Chapter 52: Scenarios Overview (Marcel Rieser, Andreas Horni and Kai Nagel)
Chapter 53: Berlin I: BVG Scenario (Andreas Neumann)
Chapter 54: Berlin II: CEMDAP-MATSim-Cadyts Scenario (Dominik Ziemke)
Chapter 55: Switzerland (Andreas Horni and Michael Balmer)
Chapter 56: Zürich (Nadine Rieser-Schüssler, Patrick M. Bösch, Andreas Horni and Michael Balmer)
56.1 Studies Based on the Zürich Scenario
Chapter 57: Singapore (Alexander Erath and Artem Chakirov)
57.1 Demand
57.2 Supply
57.3 Behavioral Parameters
57.4 Policy
57.5 Calibration and Validation
Chapter 58: Munich (Benjamin Kickhöfer)
Chapter 59: Sioux Falls (Artem Chakirov)
59.1 Demand
59.2 Supply
59.3 Behavioral Parameters
59.4 Results, Drawbacks and Outlook
Chapter 60: Aliaga (Pelin Onelcin, Mehmet Metin Mutlu and Yalcin Alver)
Chapter 61: Baoding: A Case Study for Testing a New Household Utility Function in MATSim (Chengxiang Zhuge and Chunfu Shao)
61.1 Introduction
61.2 Population and Demand Generation
61.3 Activity Locations, Network and Transport Modes
61.4 Historical Validation
61.5 Achieved Results
Chapter 62: Barcelona (Miguel Picornell and Maxime Lenormand)
62.1 Transport Supply: Network and Public Transport
62.2 Transport Demand: Population
62.3 Calibration and Validation
62.4 Results and More Information
Chapter 63: Belgium: The Use of MATSim within an Estimation Framework for Assessing Economic Impacts of River Floods (Ismauïl Saadi, Jacques Teller and Mario Cools)
63.1 Problem Statement
63.2 Data Collection
63.3 Input Preparation
63.4 General Modeling Framework
63.5 Modeling Network Disruption
63.6 Next Development Steps
Chapter 64: Brussels (Daniel Röder)
Chapter 65: Caracas (Walter J. Hernández B. and Héctor E. Navarro U.)
Chapter 66: Cottbus: Traffic Signal Simulation (Joschka Bischoff and Dominik Grether)
Chapter 67: Dublin (Gavin McArdle, Eoghan Furey, Aonghus Lawlor and Alexei Pozdnoukhov)
67.1 Introduction
67.2 Study Area
67.3 Network
67.4 Population Generation
67.5 Demand Generation
67.6 Activity Locations
67.7 Validation and Results
67.8 Achieved Results
67.9 Associated Projects and Where to Find More
Chapter 68: European Air- and Rail-Transport (Dominik Grether)
68.1 Air Transport Scenario
68.2 Simulation Results
68.3 Interpretation & Discussion
68.4 Conclusion
Chapter 69: Gauteng (Johan W. Joubert)
Chapter 70: Germany (Johannes Illenberger)
70.1 Demand and Supply Data
70.2 Imputation and Calibration
70.3 Simulation Results and Travel Statistics
Chapter 71: Hamburg Wilhelmsburg (Hubert Klüpfel and Gregor Lämmel)
71.1 Brief Description
71.2 Road Network
71.3 Evacuation Scenario
71.4 Simulation Results
Chapter 72: Joinville (Davi Guggisberg Bicudo and Gian Ricardo Berkenbrock)
Chapter 73: London (Joan Serras, Melanie Bosredon, Vassilis Zachariadis, Camilo Vargas-Ruiz, Thibaut Dubernet andMike Batty)
73.1 Supply
73.2 Demand
73.3 Calibration and Validation
73.4 More Information
Chapter 74: NelsonMandela Bay (JohanW. Joubert)
Chapter 75: New York City (Christoph Dobler)
Chapter 76: Padang (Gregor Linämmel)
Chapter 77: Patna (Amit Agarwal)
Chapter 78: The Philippines: Agent-Based Transport Simulation Model for Disaster Response Vehicles (Elvira B. Yaneza)
78.1 Literature Review
78.2 Design Details and Specifications
78.3 Model Scenarios
78.4 Validation
78.5 Achieved Results
78.6 Conclusions
Chapter 79: Poznan (Michal Maciejewski and Waldemar Walerjanczyk)
Chapter 80: Quito Metropolitan District (Rolando Armas and Hernán Aguirre)
Chapter 81: Rotterdam: Revenue Management in Public Transportation with Smart-Card Data Enabled Agent-Based Simulations (Paul Bouman and Milan Lovric)
Chapter 82: Samara (Oleg Saprykin, Olga Saprykina and Tatyana Mikheeva)
82.1 Study Area
82.2 Transport Demand
82.3 Transport Supply
82.4 Calibration and Validation
82.5 Intelligent Traffic Analysis
Chapter 83: San Francisco Bay Area: The SmartBay Project – Connected Mobility (Alexei Pozdnoukhov, Andrew Campbell, Sidney Feygin, Mogeng Yin and Sudatta Mohanty)
83.1 Introduction
83.2 The Study Area and Networks
83.3 Population and Demand Generation
83.4 Work Commute Model Evaluation
83.5 Extensions and Work in Progress
83.6 Conclusions and Acknowledgments
Chapter 84: Santiago de Chile (Benjamin Kickhöfer and Alejandro Tirachini)
84.1 Introduction
84.2 Data
84.3 Setting up the Open Scenario
84.4 Conclusion and Outlook
Chapter 85: Seattle Region (Kai Nagel)
Chapter 86: Seoul (Seungjae Lee and Atizaz Ali)
Chapter 87: Shanghai (Lun Zhang)
Chapter 88: Sochi (Marcel Rieser)
88.1 System Overview
88.2 Extensions to MATSim
88.3 Simulation of Sochi
88.4 Outlook
Chapter 89: Stockholm (Joschka Bischoff)
Chapter 90: Tampa, Florida: High-Resolution Simulation of Urban Travel and Network Performance for Estimating Mobile Source Emissions (Sashikanth Gurram, Abdul R. Pinjari and Amy L. Stuart)
90.1 Introduction
90.2 Study Area
90.3 Modeling Framework
90.4 Results
90.5 Future Work
90.6 Conclusion
Chapter 91: Tel Aviv (Christoph Dobler)
Chapter 92: Tokyo: Simulating Hyperpath-Based Vehicle Navigations and its Impact on Travel Time Reliability (Daisuke Fukuda, Jiangshan Ma, Kaoru Yamada and Norihito Shinkai)
92.1 Introduction
92.2 A Small-Sized Network Case
92.3 Simulation in Tokyo’s Arterial Road Network
92.4 Validation of Hyperpath-Based Navigation
Chapter 93: Toronto (Adam Weiss, Peter Kucireck and Khandker Nurul Habib)
93.1 Study Area
93.2 Population, Demand Generation and Activity Locations
93.3 Network Development and Simulated Modes
93.4 Calibration, Validation, Results
Chapter 94: Trondheim (Stefan Flügel, Julia Kern and Frederik Bockemühl)
Chapter 95: Yarrawonga and Mulwala: Demand-Responsive Transportation in Regional Victoria, Australia (Nicole Ronald)
Chapter 96: Yokohama: MATSim Application for Resilient Urban Design (Yoshiki Yamagata, Hajime Seya and Daisuke Murakami)
96.1 Introduction
96.2 Results
Chapter 97: Research Avenues (Kai Nagel, Kay W. Axhausen, Benjamin Kickhöfer and Andreas Horni)
97.1 MATSim and Agents
97.2 Within-Day Replanning and the User Equilibrium
97.3 Choice Set Generation
97.4 Scoring/Utility Function and Choice
97.5 Double-Queue Mobsim
97.6 Choice Dimensions, in particular, Expenditure Division
97.7 Considering Social Contacts
Acronyms
Glossary
Symbols and Typographic Conventions
Bibliography
The book hasn't received reviews yet.
You May Also Like
Immigrant and Refugee Families
Free
Co-edited with equal contribution by Jaime Ballard
Immigrant and Refugee Families
Principles of Social Psychology
Free
[Author removed at request of original publisher]
Principles of Social Psychology
A New Perspective on Poverty in the Caribbean
$9.99
Juliet Melville; Eleanor Wint
A New Perspective on Poverty in the Caribbean
Introduction to Psychology
Free
[Author removed at request of original publisher]
Introduction to Psychology
Sociology: Understanding and Changing the Social World
Free
[Author removed at request of original publisher]
Sociology: Understanding and Changing the Social World
Social Problems: Continuity and Change
Free
[Author removed at request of original publisher]
Social Problems: Continuity and Change
Research Methods in Psychology
Free
Paul C. Price, Rajiv S. Jhangiani, and I-Chant A. Chiang
Research Methods in Psychology