Automated parking surveys from a LIDAR equipped vehicle |
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| Institution: | 1. Battelle Memorial Institute, 505 King Avenue, Columbus, OH 43201, USA;2. Electrical and Computer Engineering, The Ohio State University, 2015 Neil Ave., Columbus, OH 43210, USA;3. Civil, Environmental and Geodetic Engineering, The Ohio State University, 2070 Neil Ave., Columbus, OH 43210, USA;1. Physics Department, Nelson Mandela Metropolitan University – Centre for Broadband Communication, P. O. Box 77000, Port Elizabeth 6031, South Africa;2. Square kilometer Array SKA South Africa, South Africa;1. Department of Biomedical Engineering, National University of Singapore, Singapore 117583, Singapore;2. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640, China;3. School of Automation, Northwestern Polytechnical University, Xi’an 710072, China;1. Department of Civil and Environmental Engineering, University of Illinois at Urbana-Champaign, 205 N Mathews Ave., Urbana, IL 61801, United States;2. Department of Computer Science, University of Illinois at Urbana-Champaign, 201 N Goodwin Ave., Urbana, IL 61801, United States;3. Department of Civil and Environmental Engineering and Department of Computer Science, University of Illinois at Urbana-Champaign, 205 N Mathews Ave., Urbana, IL 61801, United States;1. State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China;2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;3. School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China |
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| Abstract: | Parking surveys provide quantitative data describing the spatial and temporal utilization of parking spaces within an area of interest. These surveys are important tools for parking supply management and infrastructure planning. Parking studies have typically been performed by tabulating observations by hand, limiting temporal resolution due to high labor cost. This paper investigates the possibility of automating the data gathering and information extraction in a proof of concept study using a two-dimensional scanning Light Detection and Ranging (LIDAR) sensor mounted on a vehicle, though the work is compatible with other ranging sensors, e.g., stereo vision. This study examines parallel parking in the opposing direction of travel. The ranging measurements are processed to estimate the location of the curb and the presence of objects in the road. Occlusion and location reasoning are then applied to determine which of the objects are vehicles, and whether a given vehicle is parked or is in the traffic-stream. The occupancy of the parking area, vehicle size, and vehicle-to-vehicle gaps are then measured. The algorithm was applied to an area with unmarked, on-street parking near a large university campus. Vehicle counts from 29 trips over 4 years were compared against concurrent ground truth with favorable results. The approach can also be applied to monitor parking in the direction of travel, eliminating the possibility of occlusions and simplifying the processing. |
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| Keywords: | Parking survey Probe vehicle Vehicle detection and measurement Curb detection |
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