Smart City Gnosys

Smart city article details

Title	Decentralized Intersection Control Using Bayesian Game Theory
ID_Doc	17658
Authors	Bastianello N.; Badia L.
Year	2022
Published	Proceedings - ISMODE 2022: 2nd International Seminar on Machine Learning, Optimization, and Data Science
DOI	http://dx.doi.org/10.1109/ISMODE56940.2022.10180425
Abstract	Future smart cities are expected to have efficient control of vehicular traffic to provide satisfactory mobility and transportation of people and goods. Reliable and efficient control schedule design for signalized intersections is needed to alleviate vehicular congestions and improve the overall road network management. In the present paper, we propose an approach based on game theory to design a decentralized intersection traffic controller, able to adaptively react to changing traffic conditions and minimize the waiting time of the cars in queue. We adopt a Bayesian dynamic game framework, which is able to improve the existing state of the art alternatives by reducing the amount of data exchanged from monitoring roadside units. Moreover, we also introduce a tunable sharing factor that is a design element available to the traffic planner controlling the priority of access and allowing for prioritization. Finally, the proposed solution is extensively evaluated via simulation in different scenarios. © 2022 IEEE.
Author Keywords	Game theory; road traffic control; scheduling algorithms; smart cities

Similar Articles

Id	Similarity	Authors	Title	Published
39498	0.866	Alkhatib A.A.A.; Abu Maria K.; Alzu'bi S.; Abu Maria E.	Novel System For Road Traffic Optimisation In Large Cities	IET Smart Cities, 4, 2 (2022)
3904	0.865	Zhang L.; Lyu L.; Zheng S.; Ding L.; Xu L.	A Q-Learning-Based Approximate Solving Algorithm For Vehicular Route Game	Sustainability (Switzerland), 14, 19 (2022)
48920	0.865	Satkunarajah S.; Puvanendran R.	Simulation-Based Traffic Management Model To Minimize The Vehicle Congestion In Traffic Signals	ICAC 2023 - 5th International Conference on Advancements in Computing: Technological Innovation for a Sustainable Economy, Proceedings (2023)
57625	0.864	Ait Ouallane A.; Bahnasse A.; Bakali A.; Talea M.	Toward A Smart City: Reinforcement Learning For Traffic Light Control	Lecture Notes in Networks and Systems, 629 LNNS (2023)
25323	0.859	Chalaki B.; Beaver L.E.; Malikopoulos A.A.	Experimental Validation Of A Real-Time Optimal Controller For Coordination Of Cavs In A Multi-Lane Roundabout	IEEE Intelligent Vehicles Symposium, Proceedings (2020)
4034	0.853	Wang E.; Memar F.H.; Korzelius S.; Sadek A.W.; Qiao C.	A Reinforcement Learning Approach To Cav And Intersection Control For Energy Efficiency	Proceedings - 2022 5th International Conference on Connected and Autonomous Driving, MetroCAD 2022 (2022)
6267	0.852	Wang M.; Wang H.; Wei S.; Zhang D.	Adaptive Joint Control Of Intersection Traffic Signals And Variable Lanes Using Multi-Agent Learning	IET Intelligent Transport Systems, 19, 1 (2025)
21386	0.851	Wang J.; Wei J.; Chen S.; Yu H.; Ren Y.	Dynamic Route Optimization For Multi-Vehicle Systems With Diverse Needs In Road Networks Based On Preference Games	Computers, Materials and Continua, 83, 3 (2025)