Incorporating Driver Relaxation into Factory Adaptive Cruise Control to Reduce Lane-Change Disruptions

Hao Zhou, Anye Zhou, Jorge Laval, Yongyang Liu, Srinivas Peeta

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Current adaptive cruise control (ACC) systems adopt a fixed desired time headway, which often leads to abrupt speed changes in response to a close new leader after a cut-in or a lane change. These are disruptive maneuvers. In contrast, human drivers are willing to accept spacings much smaller than equilibrium values at the onset of these maneuvers and then gradually increase the spacing until they again reach equilibrium. This process, which typically lasts around 20 s or 30 s, is known as driver relaxation, which improves comfort and capacity. Therefore, this paper aims to incorporate relaxation into ACC systems. Based on the open-source factory-level ACC platform Openpilot by Comma.ai, the paper proposes a feasible relaxation model compatible with recent market ACC systems. The model is tested using simulation and road tests using a 2019 Honda Civic with its stock ACC hardware. The study further investigates the potential benefits of relaxation ACC on traffic operations. Comparative simulations suggest that incorporating relaxation into ACC can help: (i) reduce the magnitude of speed perturbations in both cut-in vehicles and followers; (ii) stabilize the lane-changing (LC) traffic by reducing the speed variance and preventing the lateral propagation of congestion; and (iii) increase the average flow speed and capacity after a bottleneck occurs.

Original languageEnglish
Pages (from-to)13-27
Number of pages15
JournalTransportation Research Record
Volume2676
Issue number9
DOIs
StatePublished - Sep 2022
Externally publishedYes

Keywords

  • automated/autonomous vehicles
  • operations
  • traffic flow

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