Identification of a Longitudinal Human Driving Model for Adaptive Cruise Control Performance Assessment
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The main purpose of this paper is to develop a longitudinal human driving model that is accurate enough for the performance evaluation of adaptive cruise control systems. Six driver models were evaluated based on selected data from two vehicle motion databases—the SAVME database and the ICCFOT database, both created at the University of Michigan Transportation Research Institute (UMTRI). Among the models we evaluated, the Gipps’ model was found to be the most promising and was further analyzed. A modified version of the model was suggested and evaluated. The modified model was implemented in a microscopic traffic simulator and was found to produce results that agree with macroscopic traffic behavior very well.
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2017 ◽
Vol 2615
(1)
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pp. 11-18
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1992 ◽
Vol 36
(5)
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pp. 480-484
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1979 ◽
Vol 46
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pp. 96-101
1969 ◽
Vol 33
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pp. 83-88
1995 ◽
Vol 59
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pp. 1113-1118
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