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Aug 30, 2023
A Novel Variable Speed Limit Control for Freeway Work Zone Based on Deep Reinforcement Learning
Authors: Wei Lei [email protected], Zhe Han [email protected], Yu Han [email protected], and Mingmin Han [email protected]Author Affiliations
Publication: CICTP 2023
ABSTRACT
The reduction of available lanes in freeway work zone areas often induces bottlenecks, which have a negative impact on travel time, safety, and the environment. In this paper, a more effective framework for variable speed limit control based on deep deterministic policy gradient (DDPG) is developed for solving the problem, which can impose dynamic and distinct speed limits across lanes. To achieve higher learning efficiency, this paper improves the DDPG algorithm from two aspects: balancing exploration and exploitation and improving the efficiency of parameter updating. According to simulation results of open-source software Simulation of Urban Mobility (SUMO), the proposed DRL-based DVSL controller is able to improve the safety, efficiency, and environment-friendliness of the bottleneck section in freeway work zone.
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Published online: Aug 30, 2023
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ASCE Technical Topics:
- Algorithms
- Artificial intelligence and machine learning
- Business management
- Computer programming
- Computer software
- Computing in civil engineering
- Construction engineering
- Construction management
- Construction sites
- Engineering fundamentals
- Highway and road management
- Highway transportation
- Highways and roads
- Infrastructure
- Mathematics
- Neural networks
- Parameters (statistics)
- Practice and Profession
- Public administration
- Public health and safety
- Safety
- Statistics
- Traffic congestion
- Traffic engineering
- Traffic management
- Transportation engineering
- Work zones
Authors
Affiliations
1Hebei Provincial Communications Planning, Design and Research Institute Co. Ltd., Shijiazhuang, Hebei, China; Research and Development Center of Transport Industry of Self-Driving Technology, Shijiazhuang, Hebei, China. Email: [email protected]
2School of Transportation Engineering, Southeast Univ., Nanjing, Jiangsu, China. Email: [email protected]
3School of Transportation Engineering, Southeast Univ., Nanjing, Jiangsu, China. Email: [email protected]
4Hebei Provincial Communications Planning, Design and Research Institute Co. Ltd., Shijiazhuang, Hebei, China; Research and Development Center of Transport Industry of Self-Driving Technology, Shijiazhuang, Hebei, China. Email: [email protected]
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ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.
Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.