arrow
Return

A speed-maximization trajectory optimization model on a reservation-based intersection control system

delete2023-09-01
delete2
delete
OA
AI
M
Muting Ma
Z
Zhixia Li *
DOI:10.1016/j.trc.2023.104266delete
deleteOriginal
deleteShare
deleteSave
View PDF
Abstract

Abstract

En 中文
Cooperative CAV crossing a reservation-based intersection is an integrated control problem that consists of the trajectory modeling and scheduling optimization. In order to achieve the best system performance in the intersection, a final speed is traditionally modeled as large as possible when reaching the intersection in the trajectory modeling level, coupled with a delayminimization problem. However, the delay optimization problem may not find the best solution in terms of the system efficiency. This paper aims to theoretically justify the best objective function and propose an optimal integrated control model. A speed-maximization trajectory optimization model is proposed based on the queue theory. The optimization model is formulated as a discrete-time mixed integer programming model based on the trajectory analysis. Through extensive numerical simulations with platooning and turning movements, the optimization model achieves better system performance than state-of-the-art methods. The results validate the advantages of maximizing the average speed using the discrete-time trajectory modeling method.
Keywords:
Trajectory optimization
Average speed
Queue theory
Reservation-based intersection
Connected and autonomous vehicles
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Transportation Research Part C-Emerging Technologies cover
Transportation Research Part C-Emerging Technologies
IF:
7.9
Papers:
4.7K
Citations:
3.2W

Organization

University of Alabama System cover
University of Alabama System
Scholars:
4.2W
Papers: 3.7W
Citations: 68
U
university of alabama tuscaloosa
Scholars:
5.2K
Papers: 4.5K
Citations: 11