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GPS data in urban bicycle-sharing: Dynamic electric fence planning with assessment of resource-saving and potential energy consumption increasement
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, 4800 Cao'an Road, Shanghai, 201804, China.
Mälardalen University, School of Business, Society and Engineering, Future Energy Center. Center for Spatial Information Science, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa-shi, Chiba, 277-8568, Japan.ORCID iD: 0000-0002-4641-0641
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2022 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 322, article id 119533Article in journal (Refereed) Published
Abstract [en]

As a newly-emerging option of shared transportation, Internet-enabled dockless bicycle sharing is well accepted by the public. The implementation of electric fences has great potential to tackle the problem of random parking in bicycle sharing services. However, the deployment of electric fences would have a negative impact on the convenience of bicycle sharing services, which might lead to an increase in energy consumption among customers who switch their methods of transportation. This paper proposes a dynamic electric fence planning method with an assessment of resource-saving and potential energy consumption increasement. An agent-based model is proposed to simulate the trips and evaluated the performance of static and dynamic electric fences. The results show that dynamic electric fences require significantly shorter walking distances than static electric fences. The implementation of electric fences in the city center can significantly avoid random parking and improve the parking tidiness of bicycles. The implementation of dynamic and static electric fences can averagely save 25.31% and 27.76% bicycle resources. By estimating travel mode shifting, dynamic electric fence can reduce energy consumption by 5.79% per day compared to the static electric fence situation. 

Place, publisher, year, edition, pages
Elsevier, 2022. Vol. 322, article id 119533
Keywords [en]
Agent-based model, Bicycle resource-saving, Bicycle-sharing, Electric fence, Spatial analysis
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-59531DOI: 10.1016/j.apenergy.2022.119533ISI: 000828540800001Scopus ID: 2-s2.0-85132859241OAI: oai:DiVA.org:mdh-59531DiVA, id: diva2:1681350
Available from: 2022-07-06 Created: 2022-07-06 Last updated: 2022-08-03Bibliographically approved

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Zhang, HaoranYan, Jinyue

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