Abstract
This paper proposes a two-layer hierarchical longitudinal control approach that optimizes travel time and trajectories along multiple intersections on an arterial under mixed traffic of connected automated vehicles (CAV) and human-driven vehicles (HV). The upper layer optimizes the travel time in an optimization loop, and the lower layer formulates a longitudinal controller to optimize the movement of CAVs in each block of an urban arterial by applying optimal control. Four scenarios are considered for optimal control based on the physical constraints of vehicles and the relationship between estimated arrival times and traffic signal timing. In each scenario, the estimated minimized travel time is systematically obtained from the upper layer. As the results indicate, the proposed method significantly improves the mobility of the signalized corridor with mixed traffic by minimizing stops and smoothing trajectories, and the travel time reduction is up to 29.33% compared to the baseline when no control is applied.
Highlights
The problem of the longitudinal control of connected automated vehicles has been widely studied, the control for CAVs in mixed traffic is hard when considering consecutive signalized arterials, which can lead to a problem of variable control horizon
To fill in the gap, this paper provides a new approach of hierarchical longitudinal control that can address mixed traffic, tackle the variable horizon of CAVs, and give insight into the scenarios of CAV control on a signalized corridor
Travel time benchmark), 35.87% and 39.00% travel time savings savings were shown, even when the penetration rate was as low as 20%
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Rakha and Kamalanathsharma developed eco-driving strategies for vehicles at an isolated intersection by integrating microscopic fuel consumption models in objective functions to minimize environmental adverse effects [19] They proposed a dynamic programming-based method to control the speed of a vehicle by splitting the process of approaching a signalized intersection into three states, showing that the method can save fuel and travel time significantly for an individual vehicle [20]. The problem of the longitudinal control of connected automated vehicles has been widely studied, the control for CAVs in mixed traffic is hard when considering consecutive signalized arterials, which can lead to a problem of variable control horizon.
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