Evaluation of the General Motors based car-following models and a proposed fuzzy inference model

✍ Scribed by Partha Chakroborty; Shinya Kikuchi

• Publisher: Elsevier Science
• Year: 1999
• Tongue: English
• Weight: 538 KB
• Volume: 7
• Category: Article
• ISSN: 0968-090X
• DOI: 10.1016/s0968-090x(99)00020-0

✦ Synopsis

This paper evaluates the properties of the General Motors (GM) based car-following models, identi®es their characteristics, and proposes a fuzzy inference logic based model that can overcome some of the shortcomings of the GM based models. This process involves developing a framework for evaluating a carfollowing model and comparing the behavior predicted by the GM models with the behavior observed under the real world situation. For this purpose, an instrumented vehicle was used to collect data on the headway and speeds of two consecutive vehicles under actual trac conditions. Shortcomings of the existing GM based models are identi®ed, in particular, the stability conditions were analyzed in detail. A fuzzy-inference based model of car-following is developed to represent the approximate nature of stimulus± response process during driving. This model is evaluated using the same evaluation framework used for the GM models and the data obtained by the instrumented test vehicle. Comparison between the performance of the two models show that the proposed fuzzy inference model can overcome many shortcomings of the GM based car-following models, and can be useful for developing the algorithm for the adaptive cruise control for automated highway system (AHS).