Development and evaluation of a knowledge-based system for traffic congestion management and control

✍ Scribed by Filippo Logi; Stephen G. Ritchie

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 316 KB
• Volume: 9
• Category: Article
• ISSN: 0968-090X
• DOI: 10.1016/s0968-090x(01)00002-x

✦ Synopsis

This paper describes a real-time knowledge-based system (KBS) for decision support to Trac Operation Center personnel in the selection of integrated trac control plans after the occurrence of nonrecurring congestion, on freeway and arterial networks. The uniqueness of the system, called TCM, lies in its ability to cooperate with the operator, by handling dierent sources of input data and inferred knowledge, and providing an explanation of its reasoning process. A data fusion algorithm for the analysis of congestion allows to represent and interpret dierent types of data, with various levels of reliability and uncertainty, to provide a clear assessment of trac conditions. An ecient algorithm for the selection of control plans determines alternative trac control responses. These are proposed to an operator, along with an explanation of the reasoning process that led to their development and an estimation of their expected eect on trac. The validation of the system, which is one of only few examples of validation of a KBS in transportation, demonstrates the validity of the approach. The evaluation results, in a simulated environment demonstrate the ability of TCM to reduce congestion, through the formulation of trac diversion and control schemes.