Premium
Game theoretic approach on Real‐time decision making for IoT‐based traffic light control
Author(s) -
Bui KhacHoai Nam,
Jung Jai E.,
Camacho David
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4077
Subject(s) - intersection (aeronautics) , stackelberg competition , computer science , traffic flow (computer networking) , controller (irrigation) , game theory , floating car data , netlogo , real time computing , control (management) , distributed computing , simulation , traffic congestion , artificial intelligence , computer network , engineering , transport engineering , mathematics , mathematical economics , agronomy , programming language , economics , biology , microeconomics
Summary Smart traffic light control at intersections is 1 of the major issues in Intelligent Transportation System. In this paper, on the basis of the new emerging technologies of Internet of Things, we introduce a new approach for smart traffic light control at intersection. In particular, we firstly propose a connected intersection system where every objects such as vehicles, sensors, and traffic lights will be connected and sharing information to one another. By this way, the controller is able to collect effectively and mobility traffic flow at intersection in real‐time. Secondly, we propose the optimization algorithms for traffic lights by applying algorithmic game theory. Specially, 2 game models (which are Cournot Model and Stackelberg Model) are proposed to deal with difference scenarios of traffic flow. In this regard, based on the density of vehicles, controller will make real‐time decisions for the time durations of traffic lights to optimize traffic flow. To evaluate our approach, we have used Netlogo simulator, an agent‐based modeling environment for designing and implementing a simple working traffic. The simulation results shows that our approach achieves potential performance with various situations of traffic flow.