Max Pressure Signal Control Method for Collaborative Optimization of Motor and Nonmotor Vehicles

This study proposes a traffic signal control method based on the max pressure (MP) control algorithm to optimize the coordination of motor and nonmotor vehicles. The vehicle arrival rates at downstream intersections are determined using upstream arrival rates and Robertson’s platoon dispersion model. The total delays for both vehicle types under varying congestion levels are analyzed based on different arrival scenarios. The queue lengths at downstream intersections are predicted using Robertson’s model. By applying the MP control characteristics, the green time for each phase is optimized based on queue lengths to maximize the traffic travel service and prevent queue overflow. A simulation environment using SUMO was developed to test the model, with Beijing Road in Kunming as a case study. The results show significant reductions in queue lengths and intersection delays for both motor and nonmotor vehicles. The proposed method outperforms traditional controls, effectively managing oversaturation, preventing queue overflow, and increasing traffic throughput. This method is particularly effective in environments with high numbers of nonmotor vehicles.

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Publication Details

Journal
Journal of Transportation Engineering Part A Systems
Published
2025-05-15
DOI
https://doi.org/10.1061/jtepbs.teeng-8889
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
0.00
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article

Max Pressure Signal Control Method for Collaborative Optimization of Motor and Nonmotor Vehicles

Jiandong Gao, Juyuan Yin, Jielong Li, Bing Li et al.
Journal of Transportation Engineering Part A Systems
Autonomous Vehicle Technology and Safety
article

Max Pressure Signal Control Method for Collaborative Optimization of Motor and Nonmotor Vehicles

Jiandong Gao, Juyuan Yin, Jielong Li, Bing Li, Zhenghui Wang
article en

Abstract

This study proposes a traffic signal control method based on the max pressure (MP) control algorithm to optimize the coordination of motor and nonmotor vehicles. The vehicle arrival rates at downstream intersections are determined using upstream arrival rates and Robertson’s platoon dispersion model. The total delays for both vehicle types under varying congestion levels are analyzed based on different arrival scenarios. The queue lengths at downstream intersections are predicted using Robertson’s model. By applying the MP control characteristics, the green time for each phase is optimized based on queue lengths to maximize the traffic travel service and prevent queue overflow. A simulation environment using SUMO was developed to test the model, with Beijing Road in Kunming as a case study. The results show significant reductions in queue lengths and intersection delays for both motor and nonmotor vehicles. The proposed method outperforms traditional controls, effectively managing oversaturation, preventing queue overflow, and increasing traffic throughput. This method is particularly effective in environments with high numbers of nonmotor vehicles.

Journal of Transportation Engineering Part A SystemsVol. 151(7)
Kunming University of Science and Technology (CN)
Openalex Percentile: Top 90%
Autonomous Vehicle Technology and Safety
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Max Pressure Signal Control Method for Collaborative Optimization of Motor and Nonmotor Vehicles — Jiandong Gao, Juyuan Yin, et al. · Journal of Transportation Engineering Part A Systems (2025) | TGRS Research Map | TGRS