Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment

The advent of connected vehicles holds significant promise for enhancing existing traffic signal and vehicle speed control methods. Despite this potential, there has been a lack of concerted efforts to address issues related to vehicle fuel consumption and emissions during travel across multiple intersections controlled by traffic signals. To bridge this gap, this research introduces a novel technique aimed at optimizing both traffic signals and vehicle speeds within transportation networks. This approach is designed to contribute to the improvement of transportation networks by simultaneously addressing issues related to fuel consumption and pollutant emissions. Simulation results vividly illustrate the pronounced the effectiveness of the proposed traffic signal and vehicle speed control methods of alleviating vehicle delay, reducing stops, lowering fuel consumption, and minimizing CO<sub>2</sub> emissions. Notably, these benefits are particularly prominent in scenarios characterized by moderate traffic density, emphasizing the versatility and positive impact of the method across varied traffic conditions.

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Publication Details

Journal
Sensors
Published
2024-10-13
DOI
https://doi.org/10.3390/s24206597
Primary Topic
Traffic control and management
Type
article
Field-Weighted Citation Impact
0.00

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article

Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment

Xiaoqing Zeng, Zihao Yuan
Sensors
Traffic control and management
article

Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment

Xiaoqing Zeng, Zihao Yuan
article en

Abstract

The advent of connected vehicles holds significant promise for enhancing existing traffic signal and vehicle speed control methods. Despite this potential, there has been a lack of concerted efforts to address issues related to vehicle fuel consumption and emissions during travel across multiple intersections controlled by traffic signals. To bridge this gap, this research introduces a novel technique aimed at optimizing both traffic signals and vehicle speeds within transportation networks. This approach is designed to contribute to the improvement of transportation networks by simultaneously addressing issues related to fuel consumption and pollutant emissions. Simulation results vividly illustrate the pronounced the effectiveness of the proposed traffic signal and vehicle speed control methods of alleviating vehicle delay, reducing stops, lowering fuel consumption, and minimizing CO<sub>2</sub> emissions. Notably, these benefits are particularly prominent in scenarios characterized by moderate traffic density, emphasizing the versatility and positive impact of the method across varied traffic conditions.

SensorsVol. 24(20)
Tongji University (CN)
Science and Technology Commission of Shanghai Municipality
Affordable and clean energy
Openalex Percentile: Top 79%
Traffic control and management
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