Multistory parking can accommodate a maximum number of vehicles in a limited space. However, in multistory and outdoor busy parking, it becomes challenging for drivers to find free parking slots, and they have to search in different parking lanes and floors. This results in the wastage of fuel and time and contaminates the atmosphere. To address this issue, the state-of-the-art solution exploits an optical sensor to detect if a car is present in the parking slot or not. The solution requires an optical sensor for each parking slot, which makes the optical sensor solution expensive and complex. Moreover, such a solution fails in harsh weather conditions in outdoor parking. A low-cost mm-wave radar-based solution is proposed to detect multiple cars using only one radar and pass the corresponding information to the developed computer/mobile app. Using the app, users can view the free parking slots in advance. Our proposed solution also provides free parking slot information at the parking entrance. A driver can select one from the available ones and park his car there. In the next version, people will be able to book the parking slots from the available ones. To detect the presence of vehicle in multiple parking slots, our proposed system uses Infineon’s Postion2Go module, which is one transmit and two receive antenna frequency-modulated continuous-wave (FMCW) radar. We develop a parking model using stationary objects, clutter, and vehicles in the parking. The vehicle detection algorithm is based on background subtraction and updation. First, the background is subtracted from each received snapshot to prominent the parking slot where the latest activity has been done. Then, once the activity is stable (the vehicle is fully parked or left), the background is updated. The algorithm also uses constant-false-alarm-rate (CFAR) for adaptive detection of vehicles and thresholds to detect different activities. The method of monitoring outdoor parking is simple, while the indoor parking is more challenging. Demonstrated results show the effectiveness of the proposed system.
| Identifer | oai:union.ndltd.org:kaust.edu.sa/oai:repository.kaust.edu.sa:10754/676470 |
| Date | 04 April 2022 |
| Creators | Li, Yingquan |
| Contributors | Alouini, Mohamed-Slim, Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division, Shihada, Basem, Shamim, Atif |
| Source Sets | King Abdullah University of Science and Technology |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Rights | 2023-04-24, At the time of archiving, the student author of this thesis opted to temporarily restrict access to it. The full text of this thesis will become available to the public after the expiration of the embargo on 2023-04-24. |
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