@inproceedings{dc327461d48d496287348d6e0e307b4e,
title = "An Evolutionary Based Approach for the Traffic Lights Optimization Problem",
abstract = "We consider the traffic lights optimization problem which arises in city management due to continuously growing traffic. Given a road network and predictions (or statistical data) about the traffic flows through the arcs of this network the problem is to define the offsets and phase length for each traffic light in order to improve the overall quality of the service. The latter can be defined through a number of criteria, such as average speed, average trip duration, total waiting time etc. For this problem, we present an evolutionary based heuristic approach. We use a simulation model on the basis of the SUMO modeling system to evaluate the quality of obtained solutions. The results of numerical experiments on real data confirm the efficiency of the proposed approach.",
keywords = "Evolutionary algorithm, Simulation modeling, SUMO, Traffics lights sheduling",
author = "Ivan Davydov and Daniil Tolstykh",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 18th International Conference on Mathematical Optimization Theory and Operations Research, MOTOR 2019 ; Conference date: 08-07-2019 Through 12-07-2019",
year = "2019",
month = jan,
day = "1",
doi = "10.1007/978-3-030-33394-2_2",
language = "English",
isbn = "9783030333935",
series = "Communications in Computer and Information Science",
publisher = "Springer International Publishing AG",
pages = "19--29",
editor = "Igor Bykadorov and Vitaly Strusevich and Tatiana Tchemisova",
booktitle = "Mathematical Optimization Theory and Operations Research - 18th International Conference, MOTOR 2019, Revised Selected Papers",
address = "Switzerland",
}