• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 57 Issue 2
Jul.  2022
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Article Contents
YANG Da, YANG Guo, LUO Xu, TANG Yandong, XU Lihua, PU Yun. Behavior Decision of Intelligent Connected Vehicles Considering Status of Preceding Vehicles at Intersections[J]. Journal of Southwest Jiaotong University, 2022, 57(2): 410-417, 433. doi: 10.3969/j.issn.0258-2724.20200553
Citation: YANG Da, YANG Guo, LUO Xu, TANG Yandong, XU Lihua, PU Yun. Behavior Decision of Intelligent Connected Vehicles Considering Status of Preceding Vehicles at Intersections[J]. Journal of Southwest Jiaotong University, 2022, 57(2): 410-417, 433. doi: 10.3969/j.issn.0258-2724.20200553

Behavior Decision of Intelligent Connected Vehicles Considering Status of Preceding Vehicles at Intersections

doi: 10.3969/j.issn.0258-2724.20200553
  • Received Date: 18 Aug 2020
  • Rev Recd Date: 30 Dec 2020
  • Publish Date: 03 Mar 2021
  • To enable intelligent connected vehicles (ICV) pass through signalized intersections efficiently and safely in complex traffic environments, on the basis of real-time acquisition of signal lights and preceding vehicle status information in the internet of vehicles, the driving behavior decision framework of ICV through signalized intersections in the ICV environment was established.The car-following model was used to derive the future driving status of ICV and vehicles ahead,then to predict whether the preceding vehicles will pass through the intersection, and further to judge the conditions for passing the intersection stop line when the ICVis the leader or the follower.The lane change was addedin the driving mode toseek higher traffic efficiency, and the method based on the lane change time model was used to judge the passing conditions after the ICV changesa lane.Through simulation comparison, the decision-making ability of the proposed model and the existing model was analyzed, the key factors that affect the decision-making process were discussed. Compared with the existing model, the decision method of combining signal lights and the driving intention of the preceding vehicle can improve the judgmentaccuracy of ICVs on passing conditions and realize reasonable decision-making.With the increasing of the remaining time per unit green light, the probability of vehicles passing through the intersection can be increased by 20%, and vehicle positions in the current lane have significant influence on decision result.

     

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