Personalized real-time traffic information provision: Agent-based optimization model and solution framework

Authored by Xuesong Zhou, Jiaqi Ma, Brian L Smith

Date Published: 2016

DOI: 10.1016/j.trc.2015.03.004

Sponsors: No sponsors listed

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Model Documentation: Other Narrative Flow charts Mathematical description

Model Code URLs: Model code not found

Abstract

The advancement of information and communication technology allows the use of more sophisticated information provision strategies for real-time congested traffic management in a congested network. This paper proposes an agent-based optimization modeling frame-work to provide personalized traffic information for heterogeneous travelers. Based on a space-time network, a time-dependent link flow-based integer programming model is first formulated to optimize various information strategies, including elements of where and when to provide the information, to whom the information is given, and what alternative route information should be suggested. The analytical model can be solved efficiently using off-the-shelf commercial solvers for small-scale network. A Lagrangian Relaxation-based heuristic solution approach is developed for medium to large networks via the use of a mesoscopic dynamic traffic simulator. (C) 2015 Elsevier Ltd. All rights reserved.

Tags

Management transportation System Cell transmission model Solution algorithm Route guidance consistent Variable message signs Driver behavior Congested networks Assignment problem