TRASS: A Multi-Purpose Agent-Based Simulation Framework for Complex Traffic Simulation Applications

TRASS: A Multi-Purpose Agent-Based Simulation Framework for Complex Traffic Simulation Applications

Ulf Lotzmann (University of Koblenz, Germany)
Copyright: © 2009 |Pages: 29
DOI: 10.4018/978-1-60566-226-8.ch004
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In this chapter an agent-based traffic simulation approach is presented which sees agents as individual traffic participants moving in an artificial environment. There is no restriction on types of players, such as car drivers or pedestrians. A concept is introduced which is appropriate to model different kinds of traffic participants and to have them interact with each other in one single scenario. The scenario may not only include roads, but also stadiums, shopping malls and any other situations where pedestrians or vehicles of any kind move around. Core theme of the chapter is an agent model that is founded on a layered architecture. Experiences with implementation and usage of the agent model within the universal multi-agent simulation framework TRASS will be explained by means of several application examples which also support discussion about validation of concept and implementation.
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Since agent-based simulation began to be widely used to treat problems in the field of traffic and transportation, several approaches have been established based on different definitions of the term “agent”. This has led to a large number of implementations which are more or less narrowly coupled to dedicated software tools. There are two main kinds of implementations, both of which depend upon the user community:

  • In scientific research, the typical procedure is to build models for various components of a particular (type of) traffic system. Often general purpose programming languages are used, together with more or less universal development environments or frameworks, most of which are open source. These systems can be adapted to the requirements of the model or class of models under consideration. This approach requires a high level of computer science expertise.

  • Traffic planners and other practice-oriented users prefer the application of specialized, mainly commercial tools. Any adaptation of such a tool is restricted to representing the real-world target system with the available features. Often an integration with analytical methods and real-world traffic control systems is desired.

In any case, two components of traffic simulation with characteristic features can be identified:

  • A model of an environment as a network or a landscape, i.e. a topography with typical static entities such as streets, sidewalks, static obstacles,

  • A representation of the traffic flow within the modeled environment where attributes are the geometric forms and sizes of moving entities, and motion obeys physical laws (either macroscopically as flows or microscopically as individual entities).

The development of the TRASS framework presented in this chapter was guided by the goal to have a universal platform to design multi-agent-based simulations with maximum flexibility, representing the properties of traffic described, and its environment. Special attention was devoted to the agent model representing traffic participants. These are seen as human beings who participate in traffic in many different roles. This makes the integration of social and behavioral science aspects relevant for the agent model.

The following presents TRASS as a framework that can be used for research and practice-oriented purposes.



The literature offers a very broad spectrum of contributions on topics related to traffic simulation. Authors from diverse scientific backgrounds – social scientists, physicists, mathematicians, computer scientists and many others – are engaged in that field and hold even more diverse views on that theme.

In the following literature review we will present a few articles on traffic simulation, which represent the context of microscopic agent-based models and show some evolutions in this specific field. We pass on a description of important and well-known contributions on macroscopic (Lebacque, 2003) or Cellular Automata-based (Nagel & Schreckenberg, 1992) approaches.

One direction of evolution is the increasing complexity of simulation models and scenarios. An early conversion of a traditional approach on traffic simulation into an agent-based model was done by Klügl et al. (2000). Based on their simulation platform SeSAM the original Cellular Automaton design car following model by Nagel and Schreckenberg was implemented. Klügl et al. successfully replicated the original model behavior and predictions. This project marked a starting point for further activities in the field of traffic simulation (e.g. Klügl & Bazzan, 2004).

Since agent-based simulation became more established in the traffic simulation domain, numerous specific aspects of traffic systems were studied, employing different kinds of software tools.

Complete Chapter List

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List of Reviewers
Table of Contents
Ana Bazzan, Franziska Klügl
Ana Bazzan, Franziska Klügl
Chapter 1
Takeshi Takama
This study discusses adaptation effects and congestion in a multi-agent system (MAS) to analyse real transport and traffic problems. Both... Sample PDF
Adaptation and Congestion in a Multi-Agent System to Analyse Empirical Traffic Problems: Concepts and a Case Study of the Road User Charging Scheme at the Upper Derwent
Chapter 2
Qi Han, Theo Arentze, Harry Timmermans, Davy Janssens, Geert Wets
Contributing to the recent interest in the dynamics of activity-travel patterns, this chapter discusses a framework of an agent-based modeling... Sample PDF
A Multi-Agent Modeling Approach to Simulate Dynamic Activity-Travel Patterns
Chapter 3
Michael Balmer, Marcel Rieser, Konrad Meister, David Charypar, Nicolas Lefebvre, Kai Nagel
Micro-simulations for transport planning are becoming increasingly important in traffic simulation, traffic analysis, and traffic forecasting. In... Sample PDF
MATSim-T: Architecture and Simulation Times
Chapter 4
Ulf Lotzmann
In this chapter an agent-based traffic simulation approach is presented which sees agents as individual traffic participants moving in an artificial... Sample PDF
TRASS: A Multi-Purpose Agent-Based Simulation Framework for Complex Traffic Simulation Applications
Chapter 5
Paulo A.F. Ferreira, Edgar F. Esteves, Rosaldo J.F. Rossetti, Eugénio C. Oliveira
Trading off between realism and too much abstraction is an important issue to address in microscopic traffic simulation. In this chapter the authors... Sample PDF
Applying Situated Agents to Microscopic Traffic Modelling
Chapter 6
Andreas Schadschneider, Hubert Klüpfel, Tobias Kretz, Christian Rogsch, Armin Seyfried
Multi-Agent Simulation is a general and powerful framework for understanding and predicting the behaviour of social systems. Here the authors... Sample PDF
Fundamentals of Pedestrian and Evacuation Dynamics
Chapter 7
Rex Oleson, D. J. Kaup, Thomas L. Clarke, Linda C. Malone, Ladislau Bölöni
The “Social Potential”, which the authors will refer to as the SP, is the name given to a technique of implementing multi-agent movement in... Sample PDF
"Social Potential" Models for Modeling Traffic and Transportation
Chapter 8
Sabine Timpf
In this chapter, the authors present a methodology for simulating human navigation within the context of public, multi-modal transport. They show... Sample PDF
Towards Simulating Cognitive Agents in Public Transport Systems
Chapter 9
Kurt Dresner, Peter Stone, Mark Van Middlesworth
Fully autonomous vehicles promise enormous gains in safety, efficiency, and economy for transportation. In previous work, the authors of this... Sample PDF
An Unmanaged Intersection Protocol and Improved Intersection Safety for Autonomous Vehicles
Chapter 10
Heiko Schepperle, Klemens Böhm
Current intersection-control systems lack one important feature: They are unaware of the different valuations of reduced waiting time of the... Sample PDF
Valuation-Aware Traffic Control: The Notion and the Issues
Chapter 11
Charles Desjardins, Julien Laumônier, Brahim Chaib-draa
This chapter studies the use of agent technology in the domain of vehicle control. More specifically, it illustrates how agents can address the... Sample PDF
Learning Agents for Collaborative Driving
Chapter 12
Kagan Tumer, Zachary T. Welch, Adrian Agogino
Traffic management problems provide a unique environment to study how multi-agent systems promote desired system level behavior. In particular, they... Sample PDF
Traffic Congestion Management as a Learning Agent Coordination Problem
Chapter 13
Matteo Vasirani, Sascha Ossowski
The problem of advanced intersection control is being discovered as a promising application field for multiagent technology. In this context... Sample PDF
Exploring the Potential of Multiagent Learning for Autonomous Intersection Control
Chapter 14
Tomohisa Yamashita, Koichi Kurumatani
With maturation of ubiquitous computing technology, it has become feasible to design new systems to improve our urban life. In this chapter, the... Sample PDF
New Approach to Smooth Traffic Flow with Route Information Sharing
Chapter 15
Denise de Oliveira, Ana L.C. Bazzan
In a complex multiagent system, agents may have different partial information about the system’s state and the information held by other agents in... Sample PDF
Multiagent Learning on Traffic Lights Control: Effects of Using Shared Information
Chapter 16
Tamás Máhr, F. Jordan Srour, Mathijs de Weerdt, Rob Zuidwijk
While intermodal freight transport has the potential to introduce efficiency to the transport network,this transport method also suffers from... Sample PDF
The Merit of Agents in Freight Transport
Chapter 17
Lawrence Henesey, Jan A. Persson
In analyzing freight transportation systems, such as the intermodal transport of containers, often direct monetary costs associated with... Sample PDF
Analyzing Transactions Costs in Transport Corridors Using Multi Agent-Based Simulation
Chapter 18
Shawn R. Wolfe, Peter A. Jarvis, Francis Y. Enomoto, Maarten Sierhuis, Bart-Jan van Putten
Today’s air traffic management system is not expected to scale to the projected increase in traffic over the next two decades. Enhancing... Sample PDF
A Multi-Agent Simulation of Collaborative Air Traffic Flow Management
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