Lane Management in the Era of CAV Deployment

Lane Management in the Era of CAV Deployment

Headshot of Mohammad Miralinaghi. The link directs to their bio page.
Mohammad Miralinaghi
Headshot of Samuel Labi. The link directs to their bio page.
Samuel Labi
Headshot of Shreyas Sundaram. The link directs to their bio page.
Shreyas Sundaram
Purdue University Logo. The link directs to the funded research led by this institution.

Principal Investigator(s):

Mohammad Miralinaghi, Research Associate – Purdue University
Samuel Labi, Professor of Civil Engineering – Purdue University
Director – NEXTRANS
Associate Director – Center for Connected and Automated Transportation (CCAT)
Shreyas Sundaram, Marie Gordon Associate Professor of Electrical and Computer Engineering – Purdue University
Co-Director – Center for Innovation in Control, Optimization, and Networks (ICON)

Project Abstract:
Smaller headways between vehicles provide an opportunity to address traffic congestion and its attendant adverse impacts. CAV-dedicated lanes can help reduce headway. However, building new lanes for CAV use is costly. Such cost can be reduced by redistributing/reallocating existing roadway space to HDV and CAV lanes. In doing this, however, the road agency must address planning-level questions on the influence of CAV market demand on CAV dedicated lane deployment feasibility and sustainability impacts, and operations-level issues regarding the impacts of the value of time, early/late arrival penalties on departure time choices of CAV and HDV commuters and congestion. This research first incorporates CAV market size uncertainties and width differentials between CAV and HDV lanes. The research develops and tests a solution algorithm on real road networks. Secondly, this project addresses a specific but common context of highway operations – a road section that has limited capacity and multiple lanes, commuters using either CAV or HDV during the morning peak period, with identical desired arrival times, early/late arrival penalty but different values of time.

Institution(s): Purdue University

Award Year: 2022

Research Thrust(s): Infrastructure Design & Management, Modeling & Implementation, Policy & Planning

Project Form(s):