Permissive left turn traffic flow queuing model at signalized intersections

Linyan Wei; Hualing Liu

doi:10.1117/12.3030444

16 May 2024 Permissive left turn traffic flow queuing model at signalized intersections

Linyan Wei, Hualing Liu

Proceedings Volume 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024); 131600Y (2024) https://doi.org/10.1117/12.3030444
Event: 4th International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 2024, Beijin, China

Abstract

Traditional target signalized intersections assume that the arrival of vehicles on the shared lane for left turns and straight traffic is Poisson's, meaning that the home of vehicles is independent and arrives one by one. But according to the actual road network, it is found that multiple vehicles always arrive at the signalized intersection together. Therefore, in response to the permissible phase of left turn traffic flow at intersections, this paper establishes a left turn traffic queueing model with a Markov arrival process and vacation, and uses matrix analysis techniques to evaluate the traffic performance of left turn vehicles at intersections. This model considers many factors, including the demand for direct traffic and the demand for vehicles within shared lanes. By conducting numerical experiments on these factors, we aim to obtain the queueing process of vehicles at signalized intersections that dynamically change with the cycle under different factors. Combine the obtained experimental results with the intersections in the actual road network to optimize the left turn queueing problem and reduce traffic congestion.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Linyan Wei and Hualing Liu "Permissive left turn traffic flow queuing model at signalized intersections", Proc. SPIE 13160, Fourth International Conference on Smart City Engineering and Public Transportation (SCEPT 2024), 131600Y (16 May 2024); https://doi.org/10.1117/12.3030444

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