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Article: Modeling level of urban taxi services using neural network

TitleModeling level of urban taxi services using neural network
Authors
Issue Date1999
PublisherAmerican Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.html
Citation
Journal Of Transportation Engineering, 1999, v. 125 n. 3, p. 216-223 How to Cite?
AbstractThis paper is concerned with the modeling of the complex demand-supply relationship in urban taxi services. A neural network model is developed, based on a taxi service situation observed in the urban area of Hong Kong. The input consists of several exogenous variables including number of licensed taxis, incremental charge of taxi fare, average occupied taxi journey time, average disposable income, and population and customer price index; the output consists of a set of endogenous variables including daily taxi passenger demand, passenger waiting time, vacant taxi headway, average percentage of occupied taxis, taxi utilization, and average taxi waiting time. Comparisons of the estimation accuracy are made between the neural network model and the simultaneous equations model. The results show that the neutral network-based macro taxi model can obtain much more accurate information of the taxi services than the simultaneous equations model does. Although the data set used for training the neural network is small, the results obtained thus far are very encouraging. The neural network model can be used as a policy tool by regulator to assist with the decisions concerning the restriction over the number of taxi licenses and the fixing of the taxi fare structure as well as a range of service quality control. ©ASCE,.
Persistent Identifierhttp://hdl.handle.net/10722/71029
ISSN
2015 Impact Factor: 0.801
2015 SCImago Journal Rankings: 0.627
References

 

DC FieldValueLanguage
dc.contributor.authorXu, Jen_HK
dc.contributor.authorWong, SCen_HK
dc.contributor.authorYang, Hen_HK
dc.contributor.authorTong, COen_HK
dc.date.accessioned2010-09-06T06:28:16Z-
dc.date.available2010-09-06T06:28:16Z-
dc.date.issued1999en_HK
dc.identifier.citationJournal Of Transportation Engineering, 1999, v. 125 n. 3, p. 216-223en_HK
dc.identifier.issn0733-947Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/71029-
dc.description.abstractThis paper is concerned with the modeling of the complex demand-supply relationship in urban taxi services. A neural network model is developed, based on a taxi service situation observed in the urban area of Hong Kong. The input consists of several exogenous variables including number of licensed taxis, incremental charge of taxi fare, average occupied taxi journey time, average disposable income, and population and customer price index; the output consists of a set of endogenous variables including daily taxi passenger demand, passenger waiting time, vacant taxi headway, average percentage of occupied taxis, taxi utilization, and average taxi waiting time. Comparisons of the estimation accuracy are made between the neural network model and the simultaneous equations model. The results show that the neutral network-based macro taxi model can obtain much more accurate information of the taxi services than the simultaneous equations model does. Although the data set used for training the neural network is small, the results obtained thus far are very encouraging. The neural network model can be used as a policy tool by regulator to assist with the decisions concerning the restriction over the number of taxi licenses and the fixing of the taxi fare structure as well as a range of service quality control. ©ASCE,.en_HK
dc.languageengen_HK
dc.publisherAmerican Society of Civil Engineers. The Journal's web site is located at http://www.pubs.asce.org/journals/te.htmlen_HK
dc.relation.ispartofJournal of Transportation Engineeringen_HK
dc.rightsJournal of Transportation Engineering. Copyright © American Society of Civil Engineers.en_HK
dc.titleModeling level of urban taxi services using neural networken_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0733-947X&volume=125&spage=216 &epage= 223&date=1999&atitle=Modeling+level+of+urban+taxi+services+using+neural+networken_HK
dc.identifier.emailWong, SC:hhecwsc@hku.hken_HK
dc.identifier.emailTong, CO:cotong@hku.hken_HK
dc.identifier.authorityWong, SC=rp00191en_HK
dc.identifier.authorityTong, CO=rp00178en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-0033133985en_HK
dc.identifier.hkuros41118en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0033133985&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume125en_HK
dc.identifier.issue3en_HK
dc.identifier.spage216en_HK
dc.identifier.epage223en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridXu, J=8850249000en_HK
dc.identifier.scopusauthoridWong, SC=24323361400en_HK
dc.identifier.scopusauthoridYang, H=7406556890en_HK
dc.identifier.scopusauthoridTong, CO=7202715087en_HK

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