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

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

Takeshi Takama (University of Oxford, Stockholm Environment Institute, UK)
Copyright: © 2009 |Pages: 35
DOI: 10.4018/978-1-60566-226-8.ch001
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Abstract

This study discusses adaptation effects and congestion in a multi-agent system (MAS) to analyse real transport and traffic problems. Both methodological discussion and an empirical case study are presented in this chapter. The main focus is on the comparison of an analysis of a MAS simulation analysis and an analysis that solely uses discrete choice modelling. This study explains and discusses some important concepts in design empirical MAS in traffic and transportation, including validation Minority Game and adaptation effects. This study develops an empirical MAS simulation model based on real stated-preference data to analyse the effect of a real road-user charge policy and a complimentary park and ride scheme at the Upper Derwent Valley in the Peak District National Park, England. The simulation model integrates a transport mode choice model, Markov queue model, and Minority Game to overcome the disadvantages of a conventional approach. The results of the simulation model show that the conventional analysis overestimates the effect of the transportation and environment policy due to the lack of adaptation affects of agents and congestion. The MAS comprehensively analysed the mode choices, congestion levels, and the user utility of visitors while including the adaptability of agents. The MAS also called as agent-based simulation successfully integrates models from different disciplinary backgrounds, and shows interesting effects of adaptation and congestion at the level of an individual agent.
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Introduction

Traffic congestion and associated air pollution are considered the most significant threat to the UK tourism industry, as they leave a negative impression on visitors. In particular, tourists to National Parks are heavily dependent on their private cars. According to underlying economic theory, Road-User Charging is a suitable tool to ensure that road users (i.e. car drivers) pay for the external costs generated from their travel (Hensher & Puckett, 2005; Steiner & Bristow, 2000). Currently, one of the major objectives of installing Road-User Charging is to reduce traffic congestion levels. It is likely that a Road User Charging scheme around the Upper Derwent Valley (the Valley) in the Peak District National Park (Figure 1) will be considered a viable option for reducing traffic levels. At the same time, it is important to examine to the extent to which visitors feel uncomfortable about the scheme.

Figure 1.

The Upper Derwent Valley is located between two large cities, Manchester and Sheffield. The entrance to the Upper Derwent Valley by car is only from the A57 and only through Derwent Lane, which comes to a dead-end. There are four parking areas on the Derwent Lane.

This study develops a multi-agent system (MAS) simulation including a discrete choice model to analyse the effect of the Road User Charging at the Valley on congestion levels at parking areas and the mode choice of visitors. The focus of this study is the comparison of an analysis of MAS simulation modelling and an analysis that solely uses discrete choice modelling.

Case study site description

The Upper Derwent Valley is located between two large cities, Manchester and Sheffield (Figure 1). Access to the Valley by private cars is easy, not only from local towns but also from these nearby cities through the A57. The entrance to the Upper Derwent Valley by car is only from the A57 and only through Derwent Lane, which comes to a dead-end. There are four parking areas on Derwent Lane. The approximate parking capacity of each parking area is 134, 77, 58, and 18 vehicles respectively from the Information Centre. Only the first parking area requires a parking ticket, which costs £2.50 for one-day parking or 50 pence per hour. Tourists try to park as close to the parking area of the Upper Derwent Information Centre as possible since the Information Centre is the final parking area to visit the scenic area of the Valley. However, the Information Centre charges a parking fee, so tourists who are not willing to pay a parking fee will instead choose the Derwent Overlook (the second parking area). It is important to underline that even on the busiest days congestion on the roads such as the A57 and Derwent Lane is minimal, but severe congestion occurs around the Information Centre and the second parking area.

A bus service is also planned in this area as a complementary policy tool of the Road User Charging scheme. Overall, 700 questionnaires were distributed in the Valley during the summer of 2003, and 323 were returned (i.e. a return rate of 46.1%) to collect information about decision making processes of agents with the stated preference approach and the arriving rates of vehicles. Several key person interviews including parking officers and local authorities were also carried out.

The age distribution of visitors is highly skewed, and two modes at ‘35-44’ and ‘55-64’ are present in the distribution (‘Age’ in Figure 2). This age distribution matches observations made during the survey. In addition, the income distribution (‘Income’) also supports this trend. Some 20% of visitors to the Valley are non-workers, and most of these visitors are assumed to be elderly people, since the proportion of students is nominal (i.e. 5%). Some 27.0% and 12.8% of visitors from local areas and other areas come to the Upper Derwent Valley at least every other month.

Figure 2.

Proportions of visitors’ characteristics. The age and income distribution shows that visitors are largely family and elderly members. These visitors come from local villages as well as two large cities and visit as much as once a week, but not more.

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Table of Contents
Preface
Ana Bazzan, Franziska Klügl
Acknowledgment
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
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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
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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
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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
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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
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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
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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
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Chapter 8
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Kurt Dresner, Peter Stone, Mark Van Middlesworth
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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
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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
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Chapter 14
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