Abstract

If connected and autonomous vehicles use highways under current lane management policy, only partial benefit can be reaped from the platooning of advanced vehicles. Agencies may have to update the existing policy in the near future because of the regular presence of connected and autonomous vehicles on the highways. The probable management approaches are likely to affect highway construction, rehabilitation, and fuel consumption cost. This paper studied a range of lane management approaches in terms of truck platooning and estimated construction and rehabilitation costs using existing models. It also developed a probabilistic approach of generating varying degrees of vehicle platooning to estimate fuel consumption in a simulated environment of highway segment. The results showed that, compared with a no-platoon approach, most of the approaches considered reduce construction cost but increase rehabilitation cost for a unit length of a highway. Fuel consumption cost decreases due to truck platooning with all possible approaches. If truck platooning is achieved by adding a separate truck-only lane, the fuel consumption benefits are considerably higher.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. Simulation and evaluation codes that support the findings of this study are available.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 147Issue 1January 2021

History

Received: Feb 6, 2020
Accepted: Aug 17, 2020
Published online: Nov 6, 2020
Published in print: Jan 1, 2021
Discussion open until: Apr 6, 2021

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Md. Mokaddesul Hoque, Ph.D. [email protected]
Short Term Consultant, The World Bank, Bangladesh Office, Plot E 32, Syed Mahbub Morshed Ave., Dhaka 1207, Bangladesh (corresponding author). Email: [email protected]
Associate Professor, Dept. of Civil and Environmental Engineering, Univ. of South Florida, 4202 E. Fowler Ave., ENG 030, Tampa, FL 33620. ORCID: https://orcid.org/0000-0002-9120-9218. Email: [email protected]
Transportation Research Analyst, Surface Transportation Div., Leidos, Inc., Reston, VA 20190. ORCID: https://orcid.org/0000-0002-0986-9840. Email: [email protected]
Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of South Florida, 4202 E. Fowler Ave., ENC 2006, Tampa, FL 33620. ORCID: https://orcid.org/0000-0003-3834-0759. Email: [email protected]

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