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

Moridpour, S 2013, 'Analysing the performance of a fuzzy lane changing model using data mining' in Vishal Bhatnagar (ed.) Data Mining in Dynamic Social Networks and Fuzzy Systems, IGI Global, United States, pp. 289-315.


Document type: Book Chapter
Collection: Book Chapters

Title Analysing the performance of a fuzzy lane changing model using data mining
Author(s) Moridpour, S
Year 2013
Title of book Data Mining in Dynamic Social Networks and Fuzzy Systems
Publisher IGI Global
Place of publication United States
Editor(s) Vishal Bhatnagar
Start page 289
End page 315
Subjects Transport Engineering
Summary 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.
Copyright notice © 2013 IGI Global
ISBN 9781466642133
Versions
Version Filter Type
Access Statistics: 200 Abstract Views  -  Detailed Statistics
Created: Mon, 02 Dec 2013, 09:16:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us