Title: A Large-scale Urban Traffic Decision Support System with Dynamic Traffic Assignment
Abstract: A large-scale Decision Support System (DSS) has been developed and will be applied for Beijing city in China. The main purpose is to be able to propose best suitable measures for a giv en (either recurrent or non-recurrent) traffic situation, and to ap ply it to a real-life traffic management, with focus on the application a round the Olympics Area. A major issue for operational management is to be able fast to recognize primary problems and to be quick to recommend/retrieve corresponding solutions. This paper p roposes a novel self-learning approach using conjointly expert know ledge-based choice and case-based reasoning. Key aspects to sup port such process include: (a) problem identification that is ba sed on a mesoscopic large-scale network dynamic simulation with dynamic traffic assignment; (b) measures that have been successfully implemented in a priori cases would serve as new initial scenarios to the new situations, and (c) measure evaluation that can be perfo rmed according to performance indictors. Effective scenarios (measure to problem) are stored into KBEST (knowledge-based expert system) and made available for offline and online calls. System buil ding and a calibration process are being followed, and an implementat ion of such system to an incident management and route guidance is foreseen and being designed.
Publication Year: 2010
Publication Date: 2010-06-30
Language: en
Type: book-chapter
Indexed In: ['crossref']
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