Improved action point model in traffic flow based on driver's cognitive mechanism

Wuhong Wang*, Wei Zhang, Dehui Li, Kiyotaka Hirahara, Katsushi Ikeuchi

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

21 Citations (Scopus)

Abstract

Car-following modelling in traffic flow theory has been becoming of increasing importance in traffic engineering and Intelligent Transport System(ITS), the point of concentration in this research field is how to analysis and measurement of driver cognitive behaviour. Based on qualitative description of driving behaviour with the new concept of driver's multi-typed information process and multi-ruled decision-making mechanism, this paper has analysed in more detail the AP (action point) model, and ameliorated AP model by eliminating its deficiency. The emphasis of this paper is placed on the deduction of the acceleration equations by considering that the following car is subjected in congested traffic flow. Furthermore, from the cybernetics perspective, this paper has carried out numeral simulation to car-following behaviour with deceleration and acceleration algorithms. The model validation and simulation results have shown that the improved action point car-following model can replicated car-following behaviour and be able to use to reveal the essence of traffic flow characteristics.

Original languageEnglish
Pages447-452
Number of pages6
Publication statusPublished - 2004
Event2004 IEEE Intelligent Vehicles Symposium - Parma, Italy
Duration: 14 Jun 200417 Jun 2004

Conference

Conference2004 IEEE Intelligent Vehicles Symposium
Country/TerritoryItaly
CityParma
Period14/06/0417/06/04

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