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Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic

Author

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  • Jieyu Fan

    (School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China
    Department of Human Factors, Faculty of Engineering, Computer Science and Psychology, Ulm University, 89069 Ulm, Germany)

  • Arsalan Najafi

    (Department of Architecture and Civil Engineering, Chalmers University of Technology, SE-412 96 Goteborg, Sweden)

  • Jokhio Sarang

    (Department of Human Factors, Faculty of Engineering, Computer Science and Psychology, Ulm University, 89069 Ulm, Germany)

  • Tian Li

    (School of Transportation and Logistics Engineering, Shandong Jiaotong University, Jinan 264209, China)

Abstract

Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NO x ) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NO x emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NO x emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NO x emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic.

Suggested Citation

  • Jieyu Fan & Arsalan Najafi & Jokhio Sarang & Tian Li, 2023. "Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic," Sustainability, MDPI, vol. 15(22), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:22:p:16118-:d:1283747
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    References listed on IDEAS

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    1. Barth, Matthew & Younglove, Theodore & Scora, George, 2005. "Development of a Heavy-Duty Diesel Modal Emissions and Fuel Consumption Model," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt67f0v3zf, Institute of Transportation Studies, UC Berkeley.
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    Cited by:

    1. Haiguang Zhao & Laihua Shi & Xiaoliu Xu & Jinshan Qiu & Lan Li & Junfang Wang & Wenhan Yu & Yunshan Ge, 2024. "Impact of Shortening Real Driving Emission (RDE) Test Trips on CO, NO X , and PN 10 Emissions from Different Vehicles," Sustainability, MDPI, vol. 16(21), pages 1-15, October.

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