Bilevel optimization approach to design of network of bike lanes

Mesbah, Mahmoud, Thompson, Russell and Moridpour, Sara (2012) Bilevel optimization approach to design of network of bike lanes. Transportation Research Record, 2284 2284: 21-28. doi:10.3141/2284-03

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Author Mesbah, Mahmoud
Thompson, Russell
Moridpour, Sara
Title Bilevel optimization approach to design of network of bike lanes
Journal name Transportation Research Record   Check publisher's open access policy
ISSN 0361-1981
Publication date 2012-01
Sub-type Article (original research)
DOI 10.3141/2284-03
Open Access Status File (Publisher version)
Volume 2284
Issue 2284
Start page 21
End page 28
Total pages 8
Place of publication Washington, DC, United States
Publisher U.S. National Research Council * Transportation Research Board
Collection year 2013
Language eng
Abstract A bike lane is an effective way to improve cycling safety and to decrease greenhouse gas emissions with the promotion of cycling. Improvements include high-quality off-road facilities and on-road bike lanes. Whereas construction of off-road lanes is not always possible because of urban land constraints and construction costs, on-road lanes can be a cost-effective alternative. An optimization framework for the design of a network of bike lanes in an urban road network was proposed. This framework identified links on which a bike lane could be introduced. Allocation of a lane to cyclists would increase the use of cycling, although it could disadvantage auto traffic. The presented approach balances the effects of a bike lane for all stakeholders. A bilevel optimization was proposed to encompass the benefits of cyclists and car users at the upper level and a model for traffic and bike demand assignment at the lower level. The objective function was defined by a weighted sum of a measure for private car users (total travel time) versus a measure for bike users (total travel distance on bike lanes). A genetic algorithm was developed to solve the bilevel formulation, which included introduction of a special crossover technique and a mutation technique. The proposed optimization will help transport authorities at the planning stage to quantify the outcomes of various strategies for active transport.
Keyword Genetic-algorithms
Route choice
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Civil Engineering Publications
Official 2013 Collection
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 3 times in Scopus Article | Citations
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Created: Sun, 23 Dec 2012, 01:01:23 EST by System User on behalf of School of Civil Engineering