Car-following theory has been receiving renewed attention for its use in the analysis of traffic flow characteristics and vehicle separation control under the IVHS. A car-following model that uses the fuzzy inference system, which consists of many straightforward natural language-based driving rules, is proposed. It predicts the reaction of the driver of the following vehicle (acceleration-deceleration rates) given the action of the leading vehicle. A range of possible reaction is predicted and expressed by the fuzzy membership function. The model is applied to the analysis of traffic stability and speed-density relationship. For traffic stability, the results are compared with those derived from the deterministic approach. The speed-density relationship derived from the model is compared with a set of actual flow data. The predicted range is found to be reasonable. The proposed fuzzy approach helps explain the scatter of the actual data as possibility rather than random variation.
[1]
Didier Dubois,et al.
Fuzzy sets and systems ' . Theory and applications
,
2007
.
[2]
Adolf D. May,et al.
Traffic Flow Fundamentals
,
1989
.
[3]
Robert Herman,et al.
Traffic Dynamics: Analysis of Stability in Car Following
,
1959
.
[4]
George J. Klir,et al.
Fuzzy sets, uncertainty and information
,
1988
.
[5]
Michio Sugeno,et al.
Fuzzy identification of systems and its applications to modeling and control
,
1985,
IEEE Transactions on Systems, Man, and Cybernetics.
[6]
D. Gazis,et al.
Nonlinear Follow-the-Leader Models of Traffic Flow
,
1961
.
[7]
Avishai Ceder,et al.
A DETERMINISTIC TRAFFIC FLOW MODEL FOR THE TWO-REGIME APPROACH
,
1976
.
[8]
Wilhelm Leutzbach.
Modelling of traffic flow
,
1994
.
[9]
F L Hall,et al.
THREE-DIMENSIONAL RELATIONSHIPS AMONG TRAFFIC FLOW THEORY VARIABLES
,
1989
.