The influence of heavy vehicles on traffic dynamics around on-ramp system: Cellular automata approach

Dewen Kong, Xiucheng Guo () and Dingxin Wu ()
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Dewen Kong: School of Transportation, Southeast University Nanjing, Jiangsu, 210096, P. R. China
Xiucheng Guo: School of Transportation, Southeast University Nanjing, Jiangsu, 210096, P. R. China
Dingxin Wu: School of Transportation, Southeast University Nanjing, Jiangsu, 210096, P. R. China

International Journal of Modern Physics C (IJMPC), 2017, vol. 28, issue 06, 1-24

Abstract: Although the on-ramp system has been widely studied, the influence of heavy vehicles is unknown because researchers only investigate the traffic dynamics around on-ramp system under homogeneous traffic conditions, which is different in real-world settings. This paper uses an improved cellular automaton model to study the heterogeneous traffic around on-ramp system. The forward motion rules are improved by considering the differences of driving behavior in different vehicle combinations. The lane change rules are improved by reflecting the aggressive behavior in mandatory lane changes. The phase diagram, traffic flow, capacity and spatial-temporal diagram are analyzed under the influences of heavy vehicles. The results show that by increasing the percentage of heavy vehicles, there will be more severe traffic congestion around on-ramp system, lower saturated flow and capacity. Also, the interactions between main road and on-ramp have been investigated. Increasing the percentage of heavy vehicles at the upstream of the conflict area on the main road or restricting heavy vehicles on the outside lane of the main road will deteriorate the performance of on-ramp. While the main road will have better performance as the percentage of heavy vehicles on the on-ramp increases when the on-ramp inflow rate is not low.

Keywords: Traffic dynamics; cellular automata; on-ramp system; heavy vehicle (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (4)

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DOI: 10.1142/S0129183117500838

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