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Development of location-based services for recommending departure stations to park and ride users

2014; Elsevier BV; Volume: 48; Linguagem: Inglês

10.1016/j.trc.2014.08.019

1879-2359

Zhirong Chen, Jianhong Xia, Buntoro Irawan, Craig Caulfied,

Transportation and Mobility Innovations

More and more commuters are beginning to favour public transportation. Fast and convenient park and ride (PnR) services provided by public transportation authorities are the result of changes of household demographics and household, increasing fuel prices and a focus on environmental sustainability. However, lack of parking spaces in PnR facilities creates a major bottleneck to this service. The aim of this research is to develop a location-based service (LBS) application to help PnR users choose the best train station to use to reach their destination using a multicriteria decision making model. A fuzzy logic method is used to estimate parking availability when a user is estimated to arrive at a PnR facility. Two surveys are conducted to collect traffic flow, travel behaviour and service quality data at four selected Perth Western Australia train stations. With the proposed approach and survey data, a prototype of LBS application, Station Finder, was developed using the Android SDK 4.0 and Google API 16. This application is a useful and practical tool to save travel cost and time of PnR users'.