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ATS International Journal
Editor in Chief: Prof. Alessandro Calvi
Address: Via Vito Volterra 62,
00146, Rome, Italy.
Mail to: alessandro.calvi@uniroma3.it

Study on the impact of driver behavior differences on traffic guidance efficiency

S.Q. Long, J.Y. Zhang, S.F. Wang
Pages: 119-136

Abstract:

Urban traffic guidance system is the key solution to modern traffic congestion, and drivers are the main participants in traffic travel, so it is particularly important to explore the mechanism of the influence of driver's driving behavior differences on the induction efficiency of traffic guidance system. According to different driving styles, this paper divides the road network drivers into three types: conservative, ordinary and aggressive. This paper studies the influence of driver's path choice behavior and vehicle driving behavior characteristics on traffic guidance efficiency, quantifies its decision error and vehicle driving efficiency on traffic guidance information. As for route selection behaviour, based on SP (Stated Preference) questionnaire data, a driver path selection model was constructed using a binary Logit model to predict the probability of different types of drivers changing paths when receiving traffic guidance information. In terms of vehicle driving behavior characteristics, according to the different driving behavior habits of different types of drivers, the corresponding driver driving characteristics model is established to simulate the actual state of vehicles driving in the road network. Finally, a traffic guidance system based on system optimization was constructed based on SUMO simulation platform and simulation experiments were conducted. The average vehicle speed, CO2 and CO emissions were used as indicators to evaluate the traffic guidance efficiency of the road network. The results show that, compared with other drivers, ordinary drivers have the best performance on the traffic guidance system. After induction, the vehicle speed increases by 10.59%, the CO2 emission decreases by 0.93%, and the CO emission decreases by 10.19%.
Keywords: traffic induction efficiency; driving behavior; Logit model; routing; vehicle driving behavior characteristics

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