Volume 39 Issue 2
Apr.  2021
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Article Navigation >  Journal of Transport Information and Safety  > 2021  >  39(2): 78-86
XU Liping, DENG Mingjun. A Speed Guidance Method at Signalized Intersections Based on Vehicle Infrastructure Cooperation[J]. Journal of Transport Information and Safety, 2021, 39(2): 78-86. doi: 10.3963/j.jssn.1674-4861.2021.02.010
Citation: XU Liping, DENG Mingjun. A Speed Guidance Method at Signalized Intersections Based on Vehicle Infrastructure Cooperation[J]. Journal of Transport Information and Safety, 2021, 39(2): 78-86. doi: 10.3963/j.jssn.1674-4861.2021.02.010
shu

A Speed Guidance Method at Signalized Intersections Based on Vehicle Infrastructure Cooperation

doi: 10.3963/j.jssn.1674-4861.2021.02.010

  • College of Transportation and Logistics, East China Jiaotong University, Nanchang 330013, China

  • Received Date: 2020-05-23
    Abstract
  • The existing speed guidance models for vehicles are not comprehensively considering the car-following behaviors and the roughdivision of guidance scenes. This paper studies four speed guidance models based on real-time optimization of eachvehicle in vehicle infrastructure cooperation. The vehicles are divided into queues, and the FVD car-following model is improved considering the influences of speed guidance. The vehicle platoon is used as the guidance unit, and the traffic conditions are subdivided into eight guidance scenarios. Withthe goals of optimizing the operating efficiency of the intersection without stopping or withless stopping, four vehicle speed guidance models are established to optimize vehicle acceleration/deceleration by calculating the target acceleration/deceleration based on the improved car-following model, that the following vehicles can cross the intersection stop line in a platoon at the same target speed withthe leading vehicle. The intersection between Haitang NorthRoad and Fenglin West Street in Nanchang is taken as a case study for verification. The results show that the proposed model can reduce vehicle travel time by 18.9%, maximum queue lengthby 58.8%, delay by 60.8%, and fuel consumption by 36.4%. It is suitable for different traffic saturation conditions, significantly improving the traffic at signalized intersections and reducing vehicle fuel consumption.

     

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