Cellular automaton model considering the effect of brake light and traffic light at the intersection

• Published in: International journal of communication systems 2022-08, Vol.35 (12), p.n/a
• Main Authors: Chen, Yu‐Feng, Dong, Zhang, Che, Kai, Xiang, Zheng‐Tao
• Format: Article
• Language: English
• Subjects: Brakes; Cellular automata; cellular automaton model; ChSch model; Collision avoidance; Deceleration; Roads; traffic accident; Traffic accidents; Traffic congestion; Traffic flow; Traffic intersections; Traffic models; Traffic signals
• ISSN: 1074-5351; 1099-1131
• DOI: 10.1002/dac.4251

Summary Traffic flow modeling of urban traffic on a single‐lane road with one traffic light operating as a bottleneck is the basis of research on urban road network. By introducing the brake light rules into ChSch model, we proposed a new cellular automaton traffic flow model of intersection considering the effect of brake light and traffic light to avoid running a red light and rear‐end collision. The first vehicle of the vehicle queue formed in front of the stop line at red light (FVoQ) is focused, and the evolution characteristics of intersection traffic flow are analyzed. Results show that the proposed model is more realistic than ChSch model in the following aspects: (a) The FVoQ decelerates more smoothly with the proposed model. The behavior of smooth deceleration reflects the driver's desire of comfortable driving in real traffic. (b) The proportion of the FVoQ's great and sudden deceleration to avoid running a red light is greatly reduced with the proposed model. In ChSch model, the proportion is larger than 80%, while in the proposed model, the proportion is less than 1%. The behavior of great and sudden deceleration reflects the aggressive driving pattern of a few drivers in real traffic. (c) The rear‐end collision accident rate caused by FVoQ's aggressive driving behaviors is greatly reduced with the proposed model, which conforms more to the real traffic. We proposed a new traffic flow model of intersection considering the brake light and traffic light to avoid running a red light and rear‐end collision. Our model performs better than ChSch model. The first‐vehicle of the vehicle queue formed in front of stop line at red light (FVoQ) decelerates more smoothly. The proportion of FVoQ's great and sudden deceleration to avoid running a red light and the rear‐end collision accident rate caused by FVoQ's aggressive driving behaviors are greatly reduced