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Analysing the performance of a fuzzy lane changing model using data mining

chapter
posted on 2024-10-30, 20:21 authored by Sara MoridpourSara Moridpour
Heavy vehicles have substantial impact on traffic flow particularly during heavy traffic conditions. Large amount of heavy vehicle lane changing manoeuvres may increase the number of traffic accidents and therefore reduce the freeway safety. Improving road capacity and enhancing traffic safety on freeways has been the motivation to establish heavy vehicle lane restriction strategies to reduce the interaction between heavy vehicles and passenger cars. In previous studies, different heavy vehicle lane restriction strategies have been evaluated using microscopic traffic simulation packages. Microscopic traffic simulation packages generally use a common model to estimate the lane changing of heavy vehicles and passenger cars. The common lane changing models ignore the differences exist in the lane changing behaviour of heavy vehicle and passenger car drivers. An exclusive fuzzy lane changing model for heavy vehicles is developed and presented in this chapter. This fuzzy model can increase the accuracy of simulation models in estimating the macroscopic and microscopic traffic characteristics. The results of this chapter shows that using an exclusive lane changing model for heavy vehicles, results in more reliable evaluation of lane restriction strategies.

History

Start page

289

End page

315

Total pages

27

Outlet

Data Mining in Dynamic Social Networks and Fuzzy Systems

Editors

Vishal Bhatnagar

Publisher

IGI Global

Place published

United States

Language

English

Copyright

© 2013 IGI Global

Former Identifier

2006041248

Esploro creation date

2020-06-22

Fedora creation date

2013-12-01

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