File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Designing cycle networks to maximize health, environmental, and travel time impacts: An optimization-based approach

TitleDesigning cycle networks to maximize health, environmental, and travel time impacts: An optimization-based approach
Authors
KeywordsBicycle network design
bicycling
collisions
cost-benefit analysis
health impacts
Issue Date2020
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/15568318.asp
Citation
International Journal of Sustainable Transportation, 2020, v. 14 n. 5, p. 361-374 How to Cite?
AbstractThere has been a recent surge of research interest in quantifying the health and environmental impacts of increased cycling in urban environments. Although there is general agreement that the benefits of increased cycling outweigh the risks, most of the methodologies developed have had limited value for evaluating real-world transport policies. This is because they are based on hypothetical scenarios where increased cycling takes place but give no consideration to the courses of action which may help policymakers to achieve the scenarios. A useful extension to these methodologies would be one which allowed a user to find the optimal infrastructure design and/or policies which would maximize total societal benefit, taking into account the health and environmental impacts of cycling. In this study, a Network Design Problem is formulated for systematically designing cycling network layouts in order to maximize the net benefits to the network users and society. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and a solution approach based on a genetic algorithm (GA) is provided to solve the problem. The problem formulation and solution algorithm are tested using a numerical example. The GA algorithm was shown to efficiently converge to an optimal or near-optimal solution for the cycle network design. The proposed optimization framework may be adopted by transport authorities and/or urban planners as a decision support tool to help them to systematically identify the best design for a cycle network which balances the benefits and risks to all stakeholders. © 2019, © 2019 Taylor & Francis Group, LLC.
Persistent Identifierhttp://hdl.handle.net/10722/276313
ISSN
2023 Impact Factor: 3.1
2023 SCImago Journal Rankings: 1.222
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorDoorley, R-
dc.contributor.authorPakrashi, V-
dc.contributor.authorSzeto, WY-
dc.contributor.authorGhosh, B-
dc.date.accessioned2019-09-10T03:00:29Z-
dc.date.available2019-09-10T03:00:29Z-
dc.date.issued2020-
dc.identifier.citationInternational Journal of Sustainable Transportation, 2020, v. 14 n. 5, p. 361-374-
dc.identifier.issn1556-8318-
dc.identifier.urihttp://hdl.handle.net/10722/276313-
dc.description.abstractThere has been a recent surge of research interest in quantifying the health and environmental impacts of increased cycling in urban environments. Although there is general agreement that the benefits of increased cycling outweigh the risks, most of the methodologies developed have had limited value for evaluating real-world transport policies. This is because they are based on hypothetical scenarios where increased cycling takes place but give no consideration to the courses of action which may help policymakers to achieve the scenarios. A useful extension to these methodologies would be one which allowed a user to find the optimal infrastructure design and/or policies which would maximize total societal benefit, taking into account the health and environmental impacts of cycling. In this study, a Network Design Problem is formulated for systematically designing cycling network layouts in order to maximize the net benefits to the network users and society. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and a solution approach based on a genetic algorithm (GA) is provided to solve the problem. The problem formulation and solution algorithm are tested using a numerical example. The GA algorithm was shown to efficiently converge to an optimal or near-optimal solution for the cycle network design. The proposed optimization framework may be adopted by transport authorities and/or urban planners as a decision support tool to help them to systematically identify the best design for a cycle network which balances the benefits and risks to all stakeholders. © 2019, © 2019 Taylor & Francis Group, LLC.-
dc.languageeng-
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/15568318.asp-
dc.relation.ispartofInternational Journal of Sustainable Transportation-
dc.rightsAOM/Preprint Before Accepted: his article has been accepted for publication in [JOURNAL TITLE], published by Taylor & Francis. AOM/Preprint After Accepted: This is an [original manuscript / preprint] of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI]. Accepted Manuscript (AM) i.e. Postprint This is an Accepted Manuscript of an article published by Taylor & Francis in [JOURNAL TITLE] on [date of publication], available online: http://www.tandfonline.com/[Article DOI].-
dc.subjectBicycle network design-
dc.subjectbicycling-
dc.subjectcollisions-
dc.subjectcost-benefit analysis-
dc.subjecthealth impacts-
dc.titleDesigning cycle networks to maximize health, environmental, and travel time impacts: An optimization-based approach-
dc.typeArticle-
dc.identifier.emailSzeto, WY: ceszeto@hku.hk-
dc.identifier.authoritySzeto, WY=rp01377-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/15568318.2018.1559899-
dc.identifier.scopuseid_2-s2.0-85064048938-
dc.identifier.hkuros303137-
dc.identifier.volume14-
dc.identifier.issue5-
dc.identifier.spage361-
dc.identifier.epage374-
dc.identifier.isiWOS:000465696200001-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl1556-8318-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats