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Deep Reinforcement Learning for Addressing Disruptions in traffic light control

Computers, Materials & Continua 2022年第5期71卷 2225-2247页

作者： Faizan Rasheed Kok-Lim Alvin Yau Rafidah Md Noor Yung-Wey Chong School of Engineering and Computer Science University of HertfordshireHatfieldAL109ABUK Department of Computing and Information Systems Sunway UniversitySubang Jaya47500Malaysia Faculty of Computer Science and Information Technology University of MalayaKuala Lumpur50603Malaysia National Advanced IPv6 Centre Universiti Sains MalaysiaUSMPenang11800Malaysia

This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.

关键词： Artificial intelligence traffic light control traffic disruptions multi-agent deep Q-network deep reinforcement learning

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Optimizing urban traffic control using a rational agent

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Journal of Zhejiang University-Science C(Computers and Electronics) 2014年第12期15卷 1123-1137页

作者： Salvador IBARRA-MARTíNEZ José A.CASTN-ROCHA Julio LARIA-MENCHACA Engineering School Autonomous University of Tamaulipas

This paper is devoted to developing and evaluating a set of technologies with the objective of designing a methodology for the implementation of sophisticated traffic lights by means of rational agents. These devices would be capable of optimizing the behavior of a junction with multiple traffic signals, reaching a higher level of autonomy without losing reliability, accuracy, or efficiency in the offered services. In particular, each rational agent in a traffic signal will be able to analyze the requirements and constraints of the road, in order to know its level of demand. With such information, the rational agent will adapt its light cycles with the view of accomplishing more fluid traffic patterns and minimizing the pollutant environmental emissions produced by vehicles while they are stopped at a red light, through using a case-based reasoning(CBR) adaptation. This paper also integrates a microscopic simulator developed to run a set of tests in order to compare the presented methodology with traditional traffic control methods. Two study cases are shown to demonstrate the efficiency of the introduced approach, increasing vehicular mobility and reducing harmful activity for the environment. For instance, in the first scenario, taking into account the studied traffic volumes, our approach increases mobility by 23% and reduces emissions by 35%. When the roads are managed by sophisticated traffic lights, a better level of service and considerable environmental benefits are achieved, demonstrating the utility of the presented approach.

关键词： Rational agents traffic light control Optimization traffic mobility

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Mathematical Modeling,Field Calibration and Numerical Simulation of Low-Speed Mixed traffic Flow in Cities

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Advances in Manufacturing 1998年第2期 86-88页

作者： Doctoral Candidate: Feng SuweiAdvisor: Prof. Dai Shiqiang

Ｗｉｔｈｔｈｅｒａｐｉｄｄｅｖｅｌｏｐｍｅｎｔｏｆｔｒａｎｓｐｏｒｔａｔｉｏｎａｎｄａｕｔｏｍｏｂｉｌｅｉｎｄｕｓｔｒｙ，ｔｈｅｃｏｎｆｌｉｃｔｂｅｔｗｅｅｎｍｏｔｏｒｍａｎｕｆａｃｔｕｒｅａｎｄｈｉｇｈｗａｙｃｏｎ... 详细信息

Ｗｉｔｈｔｈｅｒａｐｉｄｄｅｖｅｌｏｐｍｅｎｔｏｆｔｒａｎｓｐｏｒｔａｔｉｏｎａｎｄａｕｔｏｍｏｂｉｌｅｉｎｄｕｓｔｒｙ，ｔｈｅｃｏｎｆｌｉｃｔｂｅｔｗｅｅｎｍｏｔｏｒｍａｎｕｆａｃｔｕｒｅａｎｄｈｉｇｈｗａｙｃｏｎｓｔｒｕｃｔｉｏｎｂｅｃｏｍｅｓｓ...

关键词： low speed mixed traffic flow in cities mathematical modeling numerical simulation field calibration vehicular parking traffic light control

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Optimal Coordinated traffic control of Adjacent Intersections Based on Multiple Objectives Programming Techniques

Optimal Coordinated Traffic Control of Adjacent Intersection...

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第二十七届中国控制会议

作者： Yuan Erming 1,Li Biao 2,Feng Ying 3 1.Doctor,lecturer,School of Management,Tianjin Polytechnic University,Tianjin 300387,P.R.China 2.Post doctor,Management school,Tianjin University.Tianjin 300070,P.R.China 3.Doctor,School of Information Technology Science,Nankai University,Tianjin 300071,P.R.China

An adjacent intersections traffic light coordinated control model based on mixed integer programming formulation is proposed in this paper.On a special moment,we can compute to obtain departure rate in the upstream intersection.Then,by switching the green light time,we can control arrival rate of downstream intersection.The contribution of the paper is that a special objective functions differing from other literatures is adapted that minimizes the sum of time needed to pass downstream in-tersection for the first vehicle of each cycle during K cycles.Finally,the paper makes simulation research for the model’s ability of coordinated control by an example.And the simulation results show the efficiency of the proposed method to reduce waiting time of vehicles.

关键词： traffic model traffic light control Arrival rate Departure rate Coordinated control

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