Platoon Signal Priority in Connected-Autonomous Vehicle Environments: Algorithm Development and Testing

  • Milan Zlatkovic University of Wyoming
  • Andalib Shams Iowa State University
Keywords: Connected and Autonomous Vehicles; Signal Control; Vehicle Platoons; Microsimulation×

Abstract

As traffic congestion increases day by day, it becomes necessary to improve the existing roadway facilities to maintain satisfactory operational and safety performances. New vehicle technologies, such as Connected and Autonomous Vehicles (CAV) have a potential to significantly improve transportation systems. Using the advantages of CAVs, this study developed signalized intersection control strategy algorithm that optimizes the operations of CAVs and allows signal priority for connected platoons. The algorithm was tested in VISSIM microsimulation using a real-world urban corridor. The tested scenarios include a 2040 Do-Nothing scenario, and CAV alternatives with 25%, 50%, 75% and 100% CAV penetration rate. The results show a significant reduction in intersection delays (26% - 38%) and travel times (6% - 20%), depending on the penetration rate, as well as significant improvements on the network-wide level. CAV penetration rates of 50% or more have a potential to significantly improve all operational measures of effectiveness.

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Published
2019-12-22
How to Cite
Zlatkovic, M., & Shams, A. (2019). Platoon Signal Priority in Connected-Autonomous Vehicle Environments: Algorithm Development and Testing. Journal of Road and Traffic Engineering, 65(4), 1-9. https://doi.org/10.31075/PIS.65.04.01