DocumentCode
130865
Title
Study on a dynamic traffic route choice model with travel time reliability constrains of Intelligent Transportation Systems
Author
Xiaomei Sun
Author_Institution
Sch. of Eng. Technol., Changchun Vocational Inst. of Technol., Changchun, China
fYear
2014
fDate
27-29 June 2014
Firstpage
348
Lastpage
351
Abstract
For Intelligent Transportation Systems(ITS), dynamic traffic route choice is one of the most important technologies. Practical applications have shown that static route choice models can not meet passengers´ travel demands, because route choice is a typical multi-objective programming problem affected by many dynamic factors, such as real-time traffic state, link travel time, traffic incident, intersection delay and so on. In this paper, I proposed a multi-objective dynamic route choice function with the minimum of link travel time and distance as the target, which travelers paid most attention to when they chose the route. Also I got travel time reliability as the model constraint to against the complexity and indetermination of traffic flow. And I obtained the link travel time by short-term forecasting based on measured traffic data of the network. Finally, in order to test its reliability, I established a simulation road network for realtime traffic data, and solved the model I put forward by improved genetic algorithm. Fortunately, I obtained an exciting result.
Keywords
genetic algorithms; intelligent transportation systems; road traffic; vehicle routing; ITS; dynamic traffic route choice model; genetic algorithm; intelligent transportation systems; model constraint; multiobjective programming problem; road network simulation; travel time reliability constraints; Data models; Forecasting; Predictive models; Reliability; Roads; Vehicle dynamics; Route choice model; improved genetic algorithm; multi-objective programming; travel time reliability;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4799-3278-8
Type
conf
DOI
10.1109/ICSESS.2014.6933579
Filename
6933579
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