Cellular automaton models for traffic flow considering opposite driving of an emergency vehicle
Han-Tao Zhao (),
Jing-Ru Li and
Cen Nie
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Han-Tao Zhao: School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, Shandong, China
Jing-Ru Li: School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, Shandong, China
Cen Nie: School of Automotive Engineering, Harbin Institute of Technology, Weihai 264209, Shandong, China
International Journal of Modern Physics C (IJMPC), 2015, vol. 26, issue 07, 1-12
Abstract:
Aiming at two-lane road, this paper establishes three models to analyze the opposite-overtaking rules of emergency vehicle based on cellular automaton (CCA) model. Based on the simulation of mixed traffic flow for multi-density conditions, the density-speed diagrams have been obtained consequently. According to the analysis, when the traffic density of the opposite lane is low, the opposite driving behavior of emergency vehicle can improve the average speed effectively. At the same time, if the cocurrent lane is in high-density traffic, the traffic in the opposite lane will be disturbed, but the vehicles in the cocurrent lane will not be affected. The paper has further discussed the influence of different emergency vehicle driving behaviors on traffic. The results reveal that as the traffic of the opposite lane is in a low-density range, if emergency vehicle operates overtaking behavior precisely, the greater the density of the cocurrent lane is, the more obviously the speed improve. Meanwhile large random fluctuation of overtaking times will occur. While the risky lane change behavior displays different traffic characteristics, that is when the same direction lane is in high density, the speed increases slightly and the lane change number is changed regularly.
Keywords: Traffic flow; cellular automaton; emergency vehicle; opposite driving (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)
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DOI: 10.1142/S0129183115500795
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