An Unmanaged Intersection Protocol and Improved Intersection Safety for Autonomous Vehicles

An Unmanaged Intersection Protocol and Improved Intersection Safety for Autonomous Vehicles

Kurt Dresner (University of Texas at Austin, USA), Peter Stone (University of Texas at Austin, USA) and Mark Van Middlesworth (Harvard University, USA)
Copyright: © 2009 |Pages: 25
DOI: 10.4018/978-1-60566-226-8.ch009
OnDemand PDF Download:
$37.50

Abstract

Fully autonomous vehicles promise enormous gains in safety, efficiency, and economy for transportation. In previous work, the authors of this chapter have introduced a system for managing autonomous vehicles at intersections that is capable of handling more vehicles and causing fewer delays than modern- day mechanisms such as traffic lights and stop signs [Dresner & Stone 2005]. This system makes two assumptions about the problem domain: that special infrastructure is present at each intersection, and that vehicles do not experience catastrophic physical malfunctions. In this chapter, they explore two separate extensions to their original work, each of which relaxes one of these assumptions. They demonstrate that for certain types of intersections—namely those with moderate to low amounts of traffic—a completely decentralized, peer-to-peer intersection management system can reap many of the benefits of a centralized system without the need for special infrastructure at the intersection. In the second half of the chapter, they show that their previously proposed intersection control mechanism can dramatically mitigate the effects of catastrophic physical malfunctions in vehicles such that in addition to being more efficient, autonomous intersections will be far safer than traditional intersections are today.
Chapter Preview
Top

Introduction

Recent advances in technology have made it possible to construct a fully autonomous, computer-controlled vehicle capable of navigating a closed obstacle course. The DARPA Urban Challenge [DARPA 2007], at the forefront of this research, aims to create a full-sized driverless car capable of navigating alongside human drivers in heavy urban traffic. It is feasible that, in the near future, many vehicles will be controlled without direct human involvement. Our current traffic control mechanisms, designed for human drivers, will be upgraded to more efficient mechanisms, taking advantage of cutting-edge research in the field of Multiagent Systems (MAS).

Intersections are one aspect of traffic control that are particularly compelling multiagent systems. Often a source of great frustration for drivers, intersections represent both a sensitive point of failure as well as a major bottleneck in automobile travel. While fully autonomous open-road driving was demonstrated over ten years ago, events such as the DARPA Urban Challenge prove that city driving, including intersections, still pose substantial difficulty to AI and intelligent transportation systems (ITS) researchers.

Complete Chapter List

Search this Book:
Reset
List of Reviewers
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
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
$37.50
About the Contributors