Edited by Aura Reggiani and Peter Nijkamp
Chapter 6: Intelligent Transportation Systems (ITS) Management Using Boolean Networks
6. Intelligent Transportation System (ITS) Management Using Boolean Networks Kingsley E. Haynes, Rajendra G. Kulkarni, Laurie A. Schintler and Roger R. Stough 6.1 INTRODUCTION Traditional regional transportation models are built on a land-use network forecasting procedure incorporating spatial interaction/gravity models using origin/destination matrices for traffic zones. These classic regional planning models are still useful and valid for planning purposes but increasingly in high density metropolitan regions, ‘real-time’ intervention is part of the traffic control strategy using intelligent transportation system (ITS) technology. What are the guidelines for such regional transport management strategies and what will be the fundamental building blocks for real-time intervention? This chapter suggests one strategy and illustrates it for a particular transport management situation typical of high density/highly congested regions. Urban road networks are characterized by traffic congestion, incidents and accidents resulting in travel delays for commuters and other trip takers on urban road networks. The interaction costs of such congestion in a regional economy are enormous (Arnott and Small 1994). Factoring in safety concerns of commuters and work time lost to business and commuters makes these costs astronomical, threatening the economic viability of many metropolitan regions. Increasing the capacity of existing freeways by adding more lanes is not always possible or environmentally desirable and does not always ease the delays. The much-studied Braess paradox tells us that congestion may increase as capacity is increased (Murchland 1970). Other models based on cellular automata modelling suggest that increased capacity can barely keep up with the latent demand (Helbing and...
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