Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services
Park-and-ride (PnR) facilities provided by Australian transport authorities have been an effective way to encourage car drivers to use public transport such as trains and buses. However, as populations grow and vehicle running costs increase, the demand for more parking spaces has escalated. Often,...
| Main Authors: | , , |
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| Format: | Journal Article |
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Gordon and Breach
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/3943 |
| _version_ | 1848744374227173376 |
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| author | Chen, Zhirong Xia, Jianhong (Cecilia) Irawan, Buntoro |
| author_facet | Chen, Zhirong Xia, Jianhong (Cecilia) Irawan, Buntoro |
| author_sort | Chen, Zhirong |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Park-and-ride (PnR) facilities provided by Australian transport authorities have been an effective way to encourage car drivers to use public transport such as trains and buses. However, as populations grow and vehicle running costs increase, the demand for more parking spaces has escalated. Often, PnR facilities are filled to capacity by early morning and commuters resort to parking illegally in streets surrounding stations. This paper reports on the development of a location-based parking finding service for PnR users. Based on their current location, the system can inform users which is the best station to park their cars during peak period. Two criteria—parking availability and the shortest travel time—were used to evaluate the best station. Fuzzy logic forecast models were used to estimate the uncertainty of parking availability during the peak parking demand period. A prototype using these methods has been developed based on a case study of the Oats Street and Carlisle PnR facilities in Perth, Western Australia. The system has proved to be efficacious and has the potential to be applied to other parking systems. |
| first_indexed | 2025-11-14T06:00:27Z |
| format | Journal Article |
| id | curtin-20.500.11937-3943 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:00:27Z |
| publishDate | 2013 |
| publisher | Gordon and Breach |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-39432017-09-13T14:31:37Z Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services Chen, Zhirong Xia, Jianhong (Cecilia) Irawan, Buntoro Park-and-ride (PnR) facilities provided by Australian transport authorities have been an effective way to encourage car drivers to use public transport such as trains and buses. However, as populations grow and vehicle running costs increase, the demand for more parking spaces has escalated. Often, PnR facilities are filled to capacity by early morning and commuters resort to parking illegally in streets surrounding stations. This paper reports on the development of a location-based parking finding service for PnR users. Based on their current location, the system can inform users which is the best station to park their cars during peak period. Two criteria—parking availability and the shortest travel time—were used to evaluate the best station. Fuzzy logic forecast models were used to estimate the uncertainty of parking availability during the peak parking demand period. A prototype using these methods has been developed based on a case study of the Oats Street and Carlisle PnR facilities in Perth, Western Australia. The system has proved to be efficacious and has the potential to be applied to other parking systems. 2013 Journal Article http://hdl.handle.net/20.500.11937/3943 10.1155/2013/473471 Gordon and Breach fulltext |
| spellingShingle | Chen, Zhirong Xia, Jianhong (Cecilia) Irawan, Buntoro Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title | Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title_full | Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title_fullStr | Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title_full_unstemmed | Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title_short | Development of Fuzzy Logic Forecast Models for Location-Based Parking Finding Services |
| title_sort | development of fuzzy logic forecast models for location-based parking finding services |
| url | http://hdl.handle.net/20.500.11937/3943 |