Clustering strategies of cooperative adaptive cruise control: Impacts on human-driven vehicles

Zijia Zhong, Joyoung Lee, Mark Nejad, Earl E. Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

As a promising application of connected and automated vehicles (CAVs), Cooperative Adaptive Cruise Control (CACC) is expected to be deployed on the public road in the near term. Thus far the majority of the CACC studies have been focusing on the overall network performance with limited insight on the potential impact of CAVs on human-driven vehicles (HVs). This paper aims to quantify the influence of CAVs on HVs by studying the high-resolution vehicle trajectory data that is obtained from microscopic simulation. Two clustering strategies for CACC are implemented: an ad hoc coordination one and a local coordination one. Results show that the local coordination outperforms the ad hoc coordination across all tested market penetration rates (MPRs) in terms of network throughput and productivity. The greatest performance difference between the two strategies is observed at 30% and 40% MPR for throughput and productivity, respectively. However, the distributions of the hard braking observations (as a potential safety impact) for HVs change significantly under local coordination strategy. Regardless of the clustering strategy, CAVs increase the average lane change frequency for HVs. 30% MPR is the break-even point for local coordination, after which the average lane change frequency decreases from the peak 5.42 to 5.38. Such inverse relationship to MPR is not found in the ah hoc case and the average lane change frequency reaches the highest 5.48 at 40% MPR.

Original languageEnglish (US)
Title of host publication2019 IEEE 2nd Connected and Automated Vehicles Symposium, CAVS 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728136165
DOIs
StatePublished - Sep 2019
Event2nd IEEE Connected and Automated Vehicles Symposium, CAVS 2019 - Honolulu, United States
Duration: Sep 22 2019Sep 23 2019

Publication series

Name2019 IEEE 2nd Connected and Automated Vehicles Symposium, CAVS 2019 - Proceedings

Conference

Conference2nd IEEE Connected and Automated Vehicles Symposium, CAVS 2019
CountryUnited States
CityHonolulu
Period9/22/199/23/19

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Automotive Engineering
  • Control and Optimization

Keywords

  • CAV Clustering
  • Cooperative Adaptive Cruise Control
  • Mixed Traffic Condition
  • Traffic Flow Characteristics
  • Vehicle Trajectory Analysis

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