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Assessing the impact of data availability on parking prediction accuracy : a case study using a simulation-based Approach

Hartvelt, S.J. (2020) Assessing the impact of data availability on parking prediction accuracy : a case study using a simulation-based Approach.

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Abstract:A case study is performed on the parking situation of the city centerof Kortrijk, in Flanders, Belgium, through a simulation of the study area.Using SUMO, a simulation is built using five different data sources aboutthe parking situation in Kortrijk. This simulation creates the possibilityto have detailed data on the occupation of every parking space in the studyarea, by equipping each simulated parking space with a simulated parkingoccupancy sensor. The dataset generated by the simulation is used to de-velop a baseline prediction algorithm using Long Short-Term Memory Re-current Neural Networks. Throughout a series of experiments, variationsto the sensor coverage level, the geographical distribution of the sensorsand the demand for parking are made. Furthermore, induction loops thatcount traffic are added in the simulation, and variations regarding theprediction area size are made. The results from these experiments showa linear relationship between the sensor coverage level and the accuracyof the parking occupancy predictions. Adding alternative data sourcessuch as traffic counts further increases the accuracy of the predictions.When using sensor information to predict parking occupancy, the optimalprediction area size is found to be between 25 and 100 parking spaces.To combat false negatives, where no parking spaces are available but theprediction algorithm concludes there are, sensor coverage should be 100% in the most congested areas with the highest demand for parking.
Item Type:Essay (Master)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science, 55 traffic technology, transport technology
Programme:Business Information Technology MSc (60025)
Link to this item:http://purl.utwente.nl/essays/81227
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