Left-Turn Spillback Probability Estimation in a Connected Vehicle Environment

Author:

Cao Xiaowei1,Jiao Jian1,Zhang Yunlong1,Wang Xiubin1

Affiliation:

1. Zachry Department of Civil Engineering, Texas A&M University, College Station, TX

Abstract

At intersections in which the left-turn bay does not have sufficient length or the left-turn volume is relatively high, left-turn vehicles may spill back and block the adjacent through traffic. This paper aims to develop quantitative measures of the left-turn spillback, and by using the results on spillback probability, develop a suitable signal control strategy. We first develop an improved queue length estimation method for vehicles in the left-turn bay based on Comert and Cetin’s general queue length estimation method with connected vehicles, after which we propose a probabilistic model to measure the left-turn spillback probability at an intersection in a connected environment. The model accuracy is validated with results from microscopic traffic simulation. The effect of bay length is also studied. In the end, a signal control demonstration is presented to show the efficiency of the proposed method in signal control.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Left-turn queue spillback identification based on single-section license plate recognition data;Transportmetrica B: Transport Dynamics;2024-06-11

2. Evaluation of the Severity of Deadlock at a Signalized Intersection with Auxiliary Lanes Using Trajectory Data;Transportation Research Record: Journal of the Transportation Research Board;2024-04-17

3. Characterizing the dynamics and uncertainty of queues at signalized intersections with left-turn bay;Physica A: Statistical Mechanics and its Applications;2022-08

4. Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings;Transportation Research Record: Journal of the Transportation Research Board;2021-04-21

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