Journal of South China University of Technology (Natural Science Edition) ›› 2020, Vol. 48 ›› Issue (4): 123-131.doi: 10.12141/j.issn.1000-565X.190413

• Traffic & Transportation Engineering • Previous Articles     Next Articles

Day-to-Day Evolution Model of Road-Network Mixed Traffic Flow in Autonomous Driving Environment

TIAN Sheng XU Kai ZHU Zekun ZENG Lili   

  1. School of Civil Engineering and Transportation,South China University of Technology,Guangzhou 510640,Guangdong,China
  • Received:2019-07-03 Revised:2019-08-28 Online:2020-04-25 Published:2020-04-01
  • Contact: 许凯(1993-) ,男,硕士生,主要从事城市交通网络研究。 E-mail:ctxukai@mail.scut.edu.cn
  • About author:田晟(1969-) ,男,博士,副教授,主要从事交通运输工程研究。E-mail:shitian1@scut.edu.cn
  • Supported by:
    Supported by the Natural Science Foundation of Guangdong Province ( 2020A1515010382)

Abstract: A day-to-day model of hybrid traffic flow including traditional and autonomous vehicles was established, in order to study the influence of autonomous vehicles on the evolution of traffic flow. The different evolutionary ob- jects of the two flows were analyzed,and the prospect theory was used to describe the traveler’s behavior. The day-to-day model of traditional vehicle flow was established with the maximum prospect value of the path,and the day-to-day model of the autonomous vehicle flow was established with the minimum marginal impedance of the path. Finally,an example was used to simulate the day-to-day process of the hybrid traffic flow. The results show that,firstly,the time and evolutionary trend of the traffic flow between the traditional vehicle and the autonomous vehicle are significantly different,and the two interact with each other and constitute the evolution of hybrid flow; secondly,the higher proportion of autonomous vehicle,the less of total system time,and the path flow under differ- ent proportions evolves into different stable states; thirdly,the flow transfer threshold affects the stable condition of the hybrid flow,and its steady state is different from the no-threshold condition; finally,autonomous vehicles can affect the distribution of traffic flow before and after short-term events.

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