Parking a vehicle can often lead to frustration, air pollution and congestion due to limited availability of parking spaces. With increasing population density this problem can certainly increase unless addressed. Parking lots occupy large areas of scarce land resource therefore it is necessary to identify the driving behaviour in a parking lot to improve it further. This Paper tries study the driving behaviour in the parking lot and for this endeavours it conducted direct observation in three parking lots and used GPS data that was collected prior to this study by the University of Dalarna. To evaluate the driving behaviour in the parking lot direct observation was conducted to obtain overall indices of the parking lot vehicles movement. The parking route taken by the driver was compared with the optimal path to identify the driving behaviour in parking lot in terms of distance. The collected data was evaluated, filtered and analysed to identify the route, the distance and the time the vehicle takes to find a parking space. The outcome of the study shows that driving behaviour in the parking lots varies significantly among the parking user where most of the observed vehicles took unnecessary long time to complete their parking. The study shows that 56% of the 430 observed vehicles demonstrated inefficient driving behaviour as they took long driving path rather the than the optimal path. The study trace this behaviour to two factors, first, the absent of parking guidance in the parking lots and the second is the selectivity of the drivers when choosing the parking space. The study also shows that the ability of GPS data to identify the driving behaviour in the parking lots varies based on the time interval and the type of the device that is being used. The small the time interval the more accurate the GPS data in detecting the driving behaviour in the parking lots.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:du-29072 |
| Date | January 2018 |
| Creators | Ahmed, Salim Saif Saeed |
| Publisher | Högskolan Dalarna, Mikrodataanalys |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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