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Algorithms for the Traffic Light Setting Problem on the Graph Model

As the number of vehicles increases rapidly, traffic congestion has become a serious problem in a city. Over the past years, a considerable number of studies have been made on traffic light setting. The traffic light setting problem is to investigate how to set the given traffic lights such that the total waiting time of vehicles on the roads is minimized. In this thesis, we use a graph model to represent the traffic network. On this model, some characteristics of the setting problem can be presented and analyzed. We first devise a branch and bound algorithm for obtaining the optimal solution of the traffic light setting problem. In addition, the genetic algorithm (GA), the particle swarm optimization (PSO) and the ant colony optimization (ACO) algorithm are also adopted to get the near optimal solution. Then, to extend this model, we add the assumption that each vehicle can change its direction. By comparing the results of various algorithms, we can study the impact of these algorithms on the traffic light setting problem. In our experiments, we also transform the map of Kaohsiung city into our graph model and test each algorithm on this graph.

Identiferoai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0828107-073809
Date28 August 2007
CreatorsChen, Shiuan-wen
ContributorsChang-Biau Yang, Yue-Li Wang, Jensen Lin, Ngai-Ching Wong, Shiue-Hung Shiau
PublisherNSYSU
Source SetsNSYSU Electronic Thesis and Dissertation Archive
LanguageEnglish
Detected LanguageEnglish
Typetext
Formatapplication/pdf
Sourcehttp://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0828107-073809
Rightsoff_campus_withheld, Copyright information available at source archive

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