DocumentCode
1798188
Title
LOGAN´s Run: Lane optimisation using genetic algorithms based on NSGA-II
Author
Witheridge, Simon ; Passow, Benjamin N. ; Shell, Jethro
Author_Institution
Fac. of Technol., De Montfort Univ., Leicester, UK
fYear
2014
fDate
6-11 July 2014
Firstpage
63
Lastpage
68
Abstract
Whilst bus lanes are an important tool to ensure bus time reliability their presence can be detrimental to urban traffic. In this paper a Non-dominated Sorting Genetic Algorithm (NSGA-II) has been adopted to study the effect of bus lanes on urban traffic in terms of location and time of operation. Due to the complex nature of this problem traditional search would not be feasible. An artificial arterial route has been modelled from real data to evaluate candidate solutions. The results confirm this methodology for the purpose of studying and identifying bus lane locations and times of operation. Additionally it is shown that bus lanes can exist on an arterial link without exclusively occupying a continuous lane for large periods of time. Furthermore results indicate a use for this methodology over a larger scale and potential near real-time operation.
Keywords
genetic algorithms; public transport; road traffic; vehicle routing; LOGAN; artificial arterial route; bus lane locations; bus operation time reliability; lane optimisation using genetic algorithms based on NSGA-II; nondominated sorting genetic algorithm; urban traffic; Cities and towns; Genetic algorithms; Optimization; Roads; Sociology; Statistics; Vehicles;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), 2014 International Joint Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4799-6627-1
Type
conf
DOI
10.1109/IJCNN.2014.6889825
Filename
6889825
Link To Document