State Complexity Reduction in Reinforcement Learning based Adaptive Traffic Signal Control (CROSBI ID 693929)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Miletić, Mladen ; Kušić, Krešimir ; Gregurić, Martin ; Ivanjko, Edouard
engleski
State Complexity Reduction in Reinforcement Learning based Adaptive Traffic Signal Control
The throughput of a signalized intersection can be increased by appropriate adjustment of the signal program using Adaptive Traffic Signal Control (ATSC). One possible approach is to use Reinforcement Learning (RL). It enables model-free learning of the control law for the reduction of the negative impacts of traffic congestion. RL based ATSC achieves good results but requires many learning iterations to train optimal control policy due to high state-action complexity. In this paper, a novel approach for state complexity reduction in RL by using Self-Organizing Maps (SOM) is presented. With SOM, the convergence rate of RL and system stability in the later stages of learning is increased. The proposed approach is evaluated against the traditional RL approach that uses Q-Learning on a simulated isolated intersection calibrated according to realistic traffic data. Presented simulation results prove the effectiveness of the proposed approach regarding learning stability and traffic measures of effectiveness.
Intelligent Transportation Systems ; Adaptive Traffic Signal Control ; Reinforcement Learning ; Self-Organizing Maps ; Machine Learning
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
nije evidentirano
Podaci o prilogu
61-66.
2020.
objavljeno
10.1109/ELMAR49956.2020.9219024
Podaci o matičnoj publikaciji
Proceedings of ELMAR-2020
Muštra, Mario ; Vuković, Vuković ; Zovko-Cihlar, Branka
Zagreb: Fakultet elektrotehnike i računarstva Sveučilišta u Zagrebu
979-1-7281-5972-0
Podaci o skupu
62nd International Symposium ELMAR-2020
predavanje
14.09.2020-15.09.2020
Zadar, Hrvatska
Povezanost rada
Elektrotehnika, Računarstvo, Tehnologija prometa i transport