The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Analysing the Performance of a Fuzzy Lane Changing Model Using Data Mining
Abstract
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.
Related Content
Tutita M. Casa, Fabiana Cardetti, Madelyn W. Colonnese.
© 2024.
14 pages.
|
R. Alex Smith, Madeline Day Price, Tessa L. Arsenault, Sarah R. Powell, Erin Smith, Michael Hebert.
© 2024.
19 pages.
|
Marta T. Magiera, Mohammad Al-younes.
© 2024.
27 pages.
|
Christopher Dennis Nazelli, S. Asli Özgün-Koca, Deborah Zopf.
© 2024.
31 pages.
|
Ethan P. Smith.
© 2024.
22 pages.
|
James P. Bywater, Sarah Lilly, Jennifer L. Chiu.
© 2024.
20 pages.
|
Ian Jones, Jodie Hunter.
© 2024.
20 pages.
|
|
|