A platoon regulation algorithm to improve the traffic performance of highway work zones

Abstract

This paper presents a cooperative traffic control strategy to increase the capacity of nonrecurrent bottlenecks such as work zones by making full use of the spatial resources upstream of work zones. The upstream area is divided into two zones: the regulation and the merging areas. The basic logic is that a large gap is more efficient in accommodating merging vehicles than several small and scattered gaps with the same total length. In the regulation area, a nonlinear programming model is developed to balance both traffic capacity improvements and safety risks. A two‐step solving algorithm is proposed for finding optimal solutions. In the merging area, the sorting algorithm is used to design lane‐changing trajectories based on the regulated platoons. A case study is conducted, and the results indicate that the proposed model is able to significantly improve work zone capacity with minor disturbances to the traffic.

Merging control strategies of connected and autonomous vehicles at freeway on-ramps: a comprehensive review

“…Second, this review focuses on the CAV on-ramp merging situation studies. However, further studies covering the strategies for comparable situations, such as merging at work zones (Cao et al , 2021), lane drops (Zhang et al , 2019) and lane change at off-ramps and weaving sections (Zheng, 2014; Amini et al , 2021; Nagalur Subraveti et al , 2021) may benefit the overall understanding of CAV merging problem in general. Therefore, a survey including such studies is part of our ongoing review plan.…”

Intersection control with connected and automated vehicles: a review

“…As intersection control is still excluded, the main motivation here is to develop general platoon control models and algorithms that can be applied to common road bottlenecks such as signalized intersections, highway ramps and work zones. (Cao et al, 2021). A similar framework was also used in the study of Cai et al (2022), in which the A Ã algorithm was replaced with a conflict-based searching algorithm.…”

Flow-level coordination of connected and autonomous vehicles in multilane freeway ramp merging areas

“…The emerging Connected and Autonomous Vehicles (CAVs) present an opportunity to regulate individual vehicles and achieve cooperative driving in various bottleneck areas (Zhou et al, 2017, Debada et al, 2018, Mirheli et al, 2019, Wu et al, 2020, Cao et al, 2021, Zhu et al, 2021a. Compared to the Human-Driven Vehicles (HDVs), CAVs can obtain more accurate and comprehensive traffic information through the vehicle communication technologies, and they are capable of more precise and timely execution of the dynamic driving tasks.…”