Abstract
This paper presents a novel approach for the preparation of real parking data for microscopic traffic simulation or similar applications. Against the backdrop of an incomplete database given from single parking spot sensors and manual countings on a few parking spaces in Munich, the data are cleaned and expanded by various methods, e.g. a neural network to forecast the total occupancy at each hour as well as an optimization model to generate the corresponding parking times of each car. This results in a list of realistic parking events for a certain location and day. The method is transferable to other use cases regarding off-street parking spaces, particularly with an incomplete and discontinuous detection of parking occupancy and times.
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Notes
- 1.
Here we consider three tolerance classes with absolute values (i.e. ± 5, ± 10 and ± 15%), whereby the second class also includes the first, and the third class also includes the second and first.
- 2.
We assume that a full trip with public transport (return included) takes at least 60 min. The maximum parking duration is officially restricted to 24 h by the parking operator.
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Acknowledgements
The authors would like to express special thanks to Mr. Wolfgang Großmann and Mrs. Mirjam Trebin from the ‘P+R Park & Ride GmbH’ in Munich for the temporary provision of the parking space ‘Lochhausen Nord’ and making available historic parking occupancy data. Besides, we thank Mr. Clemens Techmer from our project partner ParkHere, for the installation of parking sensors in ‘Lochhausen Nord’ and for providing us with the parking sensor data. Furthermore, we would like to thank the ‘Federal Ministry for Digital and Transport’ (BMDV, formerly BMVI) for funding the PAMIR project within the framework of the innovation initiative ‘mFUND’. Finally, we also thank our colleague, Mrs. Frances Ploewka, for proofreading this paper.
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Kaiser, A., Schade, J., Zadek, H. (2023). Modeling of Total Occupancy Curves with Integrated Single Parking Times as Input for Microscopic Traffic Simulation. In: Macioszek, E., Granà, A., Sierpiński, G. (eds) Advanced Solutions and Practical Applications in Road Traffic Engineering. TSTP 2022. Lecture Notes in Networks and Systems, vol 604. Springer, Cham. https://doi.org/10.1007/978-3-031-22359-4_5
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