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Intersection Signal Control Based on Speed Guidance and Reinforcement Learning
Technical Paper
2023-01-0721
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
As a crucial part of the intelligent transportation system, traffic signal control will realize the boundary control of the traffic area, it will also lead to delays and excessive fuel consumption when the vehicle is driving at the intersection. To tackle this challenge, this research provides an optimized control framework based on reinforcement learning method and speed guidance strategy for the connected vehicle network. Prior to entering an intersection, vehicles are focused on in a specific speed guidance area, and important factors like uniform speed, acceleration, deceleration, and parking are optimized. Conclusion, derived from deep reinforcement learning algorithm, the summation of the length of the vehicle’s queue in front of the signal light and the sum of the number of brakes are used as the reward function, and the vehicle information at the intersection is collected in real time through the road detector on the road network. Finally, the proposed method is implemented through the SUMO (Simulation of Urban Mobility) simulation platform. The results demonstrate the effectiveness of the proposed model by obtaining the space-time trajectory map of the vehicle before and after optimization, as well as the vehicle’s travel time and fuel consumption.
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Citation
Lu, G., Zhan, Z., Rehman, H., Chen, X. et al., "Intersection Signal Control Based on Speed Guidance and Reinforcement Learning," SAE Technical Paper 2023-01-0721, 2023, https://doi.org/10.4271/2023-01-0721.Also In
References
- Han , J. , Sciarretta , A. , Ojeda , L.L. , De Nunzio , G. et al. Safe- and Eco-Driving Control for Connected and Automated Electric Vehicles Using Analytical State-Constrained Optimal Solution IEEE Transactions on Intelligent Vehicles 3 2 2018 163 172
- Yang , H. , Rakha , H. , and Ala , M.V. Eco-Cooperative Adaptive Cruise Control at Signalized Intersections Considering Queue Effects IEEE Transactions on Intelligent Transportation Systems 18 6 2017 1575 1585 10.1109/TITS.2016.2613740
- Cheng , C. , Yang , Z. , Yao , D. et al. A Speed Guide Model for Collision Avoidance in Non-Signalized Intersections Based on Reduplicate Game Theory 2018 IEEE Intelligent Vehicles Symposium, Proceedings 2018 1614 1619
- Ding , H. , Cheng , Y. , Zheng , X. et al. Speed Guidance and Trajectory Optimization of Traffic Flow in a Low-Visibility Zone of a Highway Segment within Multiple Signalized Intersections Journal of Advanced Transportation 2021 1 14
- Yg , A. , Zq , A. , Xs , A. et al. A Novel Relationship Model between Signal Timing, Queue Length and Travel Speed Physica A: Statistical Mechanics and its Applications 583 2021 126331
- Zheng , G. , Zang , X. , Xu , N. et al. 2019
- Tang , T.Q. , Zhang , J. , and Liu , K. A Speed Guidance Model Accounting for the Driver’s Bounded Rationality at a Signalized Intersection Physica, A: Statistical Mechanics and its Applications 473 2017 45 52
- Tang , T.-Q. , Yi , Z.-Y. et al. A Speed Guidance Strategy for Multiple Signalized Intersections Based on Car-Following Model Physica A: Statistical Mechanics and its Applications 496 2018 399 409
- Zhao , J. and Li , P. An Extended Car-Following Model with Consideration of Speed Guidance at Intersections Physica A Statistical Mechanics & Its Applications 461 2016 1 8
- Xw , A. , Ml , A. , Yc , A. et al. Effectiveness of Driver’s Bounded Rationality and Speed Guidance on Fuel-Saving and Emissions-Reducing at a Signalized Intersection Journal of Cleaner Production 2021 325 129343
- Zhenlong , L. , Lei , Y. , Jingsi , Z. et al. A Speed Guidance Model Accounting for the Driver’s Bounded Rationality at Signalized Intersection Science Technology and Engineering 22 16 2022 6728 6733
- Zhimin , L. , Baolin , Y. , Yaodong , Z. , Yao Qing , W. et al. Traffic Signal Control Method Based on Deep Reinforcement Learning Journal of Zhejiang University (Engineering Edition) 56 06 2022 1249 1256
- Zhi , L. , Shipeng , C. et al. Single Intersection Signal Control Based on Improved Deep Reinforcement Learning Computer Science 47 12 2020 226 232
- Kumar , N. , Rahman , S.S. , and Dhakad , N. Fuzzy Inference Enabled Deep Reinforcement Learning-Based Traffic Light Control for Intelligent Transportation System IEEE Transactions on Intelligent Transportation Systems 22 8 2021 4919 4928
- Fenjiro , Y. and Benbrahim , H. Deep Reinforcement Learning Overview of the State of the Art Journal of Automation Mobile Robotics and Intelligent Systems 12 3 2018 20 39
- Arulkumaran , K. , Deisenroth , M.P. , Brundage , M. et al. Deep Reinforcement Learning: A Brief Survey IEEE Signal Processing Magazine 34 6 2017 26 38
- Lingping , X. and Mingjun , D. Speed Guidance Method at Signalized Intersection Based on Cooperative Vehicle Infrastructure Environment Traffic Information and Safety 39 02 2021 78 86