Adaptive signal control and coordination for urban traffic control in a connected vehicle environment: A review

Li, Jiangchen; Peng, Liqun; Hou, Kaizhe; Tian, Yong; Ma, Yulin; Xu, Shucai; Qiu, Tony Z.

doi:10.48130/dts-2023-0008

Cited by 2 publications

(3 citation statements)

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“…This paper bridges all gaps in TSCS at V2X intersections identified in a research review [11] published just in 2023. Our case studies confirmed that the implemented optimized control saves 40% of delays at a low penetration rate of 10%.…”

Section: Introductionmentioning

confidence: 60%

“…In addition, estimating a non-CV queue is an integral part of the model. Li et al noticed that Feng's models require a 25% minimum penetration rate to perform [11]. Zhang et al [23] presented optimal control and coordination of connected and automated vehicles.…”

Section: Traffic Signal Control Systems At V2x Intersectionsmentioning

confidence: 99%

“…Artificial intelligence and deep learning have proven excellent approaches to the same problem in this research in recent decades, a few of which applied distributed intelligence as well. Li's review listed several research papers [11]. There is also a review of reinforcement-based TSCS [29].…”

Section: Traffic Signal Control Systems At V2x Intersectionsmentioning

confidence: 99%

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Distributed Traffic Signal Optimization at V2X Intersections

Zhang,

Zhang

2024

Mathematics

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This paper presents our research on a traffic signal control system (TSCS) at V2X intersections. The overall objective of the study is to create an implementable TSCS. The specific objective of this paper is to investigate a distributed system towards implementation. The objective function of minimizing queue delay is formulated as the integral of queue lengths. The discrete queueing estimation is mixed with macro and micro traffic flow models. The novel proposed architecture alleviates the communication network bandwidth constraint by processing BSMs and computing queue lengths at the local intersection. In addition, a two-stage distributed system is designed to optimize offsets, splits, and cycle length simultaneously and in real time. The paper advances TSCS theories by contributing a novel analytic formulation of delay functions and their first degree of derivatives for a two-stage optimization model. The open-source traffic simulation engine Enhanced Transportation Flow Open-Source Microscopic Model (ETFOMM version 1.2) was selected as a simulation environment to develop, debug, and evaluate the models and the system. The control delay of the major direction, minor direction, and the total network were collected to assess the system performance. Compared with the optimized TSCS timing plan by the Virginia Department of Transportation, the system generated a 21% control delay reduction in the major direction and a 7% control delay reduction in the minor direction at just a 10% penetration rate of connected vehicles. Finally, the proposed distributed and centralized systems present similar performances in the case study.

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Section: Introductionmentioning

confidence: 60%

Section: Traffic Signal Control Systems At V2x Intersectionsmentioning

confidence: 99%