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Journal Article

Citation

Faber T, Sharma S, Snelder M, Klunder G, Tavasszy L, van Lint H. Transp. Res. Rec. 2020; 2674(10): 525-547.

Copyright

(Copyright © 2020, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/0361198120935443

PMID

unavailable

Abstract

Truck platooning is the application of cooperative adaptive cruise control where multiple trucks are electronically linked using vehicle-to-vehicle communication. Although truck platoons might bring fuel savings and emission reductions, their interactions with surrounding traffic and resulting impact on traffic operations and safety are not fully understood. The objective of this paper is to evaluate traffic efficiency and safety in a critical traffic situation when truck platoons are introduced in the system. This paper presents a case study of a merging section, located on A15 motorway, near the port of Rotterdam in the Netherlands. We consider two scenarios: platoons on a mainline carriageway and platoons merging onto a mainline carriageway. We simulate the movements of truck platoons in a microscopic traffic simulator. Longitudinal and lateral controllers for truck platoons, proposed in this paper, can ensure their collision-free, string-stable, and smooth driving behavior. Simulation experiments are conducted by varying platoon characteristics such as market penetration, length, intra-platoon headway, platoon speed, and their ability to create a gap for changing lanes. The results suggest that truck platoons on the mainline carriageway may be detrimental to traffic efficiency and safety in high traffic intensity, whereas truck platoons originating from an on-ramp produce limited impacts. Further, we conduct both local and global sensitivity analyses to analyze the impact of platoon characteristics on traffic efficiency and safety. The findings emphasize that uncertainty in traffic efficiency and safety strongly depends on the interactions among platoon characteristics, traffic demand, and traffic scenarios.


Language: en

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