This paper focuses on modelling on-street parking search time by using FCD data coming from probe vehicles. It is based on data detected by probe vehicles, which allow to identify the typical spiral around the destination that vehicles perform in the final part of the trip to find a parking place. The proposed model is suitable to be used either in real-time to support user information and dynamic routing, or off-line for a better assessment of transport plans. A real-size application to the city of Rome is presented to show the promising results obtained for the estimation of parking search time in urban areas.

Mannini, L., Cipriani, E., Crisalli, U., Gemma, A., Vaccaro, G. (2017). On-Street Parking Search Time Estimation Using FCD Data. In Transportation Research Procedia (pp.929-936). Elsevier B.V. [10.1016/j.trpro.2017.12.149].

On-Street Parking Search Time Estimation Using FCD Data

Mannini, L.;Cipriani, E.;Gemma, A.;
2017-01-01

Abstract

This paper focuses on modelling on-street parking search time by using FCD data coming from probe vehicles. It is based on data detected by probe vehicles, which allow to identify the typical spiral around the destination that vehicles perform in the final part of the trip to find a parking place. The proposed model is suitable to be used either in real-time to support user information and dynamic routing, or off-line for a better assessment of transport plans. A real-size application to the city of Rome is presented to show the promising results obtained for the estimation of parking search time in urban areas.
2017
Mannini, L., Cipriani, E., Crisalli, U., Gemma, A., Vaccaro, G. (2017). On-Street Parking Search Time Estimation Using FCD Data. In Transportation Research Procedia (pp.929-936). Elsevier B.V. [10.1016/j.trpro.2017.12.149].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/333362
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