This paper investigates the application and optimization of intelligent traffic signal control systems and networked autonomous vehicles in mixed-traffic environments. By integrating advanced control algorithms and communication technologies, the study aims to enhance traffic efficiency and safety. The primary objectives include evaluating the effectiveness of intelligent traffic signals in reducing congestion and improving travel time, as well as examining the interaction between autonomous and non-autonomous vehicles. Key methodologies involve Deep Q-Network (DQN) based assessments and real-world data analysis. The results indicate notable enhancements in both traffic flow and safety metrics., demonstrating the promise of these technologies in contemporary transportation systems.
Application and optimization of intelligent traffic signal control and networked autonomous vehicles in mixed traffic environments
Workshop on Electronics Communication Engineering (WECE 2024) ; 2024 ; Wuhan, China
Proc. SPIE ; 13553
2025-03-12
Conference paper
Electronic Resource
English
Asymmetric traffic flow signal control optimization method in networked traffic environment
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