ParkUs: A Novel Vehicle Parking Detection System
| Autor: | Pietro Carnelli, Joy Yeh, Mahesh Sooriyabandara, Aftab Khan |
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| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Proceedings of the AAAI Conference on Artificial Intelligence. 31:4650-4656 |
| ISSN: | 2374-3468 2159-5399 |
| Popis: | Finding on-street parking in congested urban areas is a challenging chore that most drivers worldwide dislike. Previous vehicle traffic studies have estimated that around thirty percent of vehicles travelling in inner city areas are made up of drivers searching for a vacant parking space. While there are hardware sensor based solutions to monitor on-street parking occupancy in real-time, instrumenting and maintaining such a city wide system is a substantial investment. In this paper, a novel vehicle parking activity detection method, called ParkUs, is introduced and tested with the aim to eventually reduce vacant car parking space search times. The system utilises accelerometer and magnetometer sensors found in all smartphones in order to detect parking activity within a city environment. Moreover, it uses a novel sensor fusion feature called the Orthogonality Error Estimate (OEE). We show that the OEE is an excellent indicator as it’s capable of detecting parking activities with high accuracy and low energy consumption. One of the envisioned applications of the ParkUs system will be to provide all drivers with guidelines on where they are most likely to find vacant parking spaces within a city. Therefore, reducing the time required to find a vacant parking space and subsequently vehicle congestion and emissions within the city. |
| Databáze: | OpenAIRE |
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