Title
Traffic control model and algorithm based on decomposition of MDP
Abstract
In this paper, a new method based on decomposition of Markov Decision Process (MDP) for traffic control at isolated intersection is proposed. The conflicting traffic flows should be grouped into different combinations which can occupy the conflict zone concurrently. Thus, for purpose of traffic delay reduction, the optimal policy of signal sequence and duration among different combinations is studied by minimizing the number of vehicles waiting in the queue. In order to reduce the computation of probabilities in large state transition matrix, the decomposition method proposed classifies states into several parts as rule of traffic signal transition. Each part contains the vehicle states in all traffic flows. This method firstly achieves the full-states calculation in stochastic traffic control system. Moreover, the simulation results indicate that MDP approach is more efficient to improve the performance of traffic control than other comparing methods, such as fixed-time control and actuated control.
Year
DOI
Venue
2014
10.1109/CoDIT.2014.6996897
CoDIT
Keywords
Field
DocType
Markov processes,matrix algebra,road traffic control,MDP decomposition,Markov decision process decomposition,large state transition matrix,stochastic traffic control system,traffic control model,traffic delay reduction,traffic signal transition
Traffic generation model,Markov model,Algorithm,Engineering,Decomposition
Conference
Citations 
PageRank 
References 
2
0.39
5
Authors
3
Name
Order
Citations
PageRank
Biao Yin143.12
Dridi, M.261.23
El Moudni, A.3345.56