A New Method of Vehicle Positioning Using Bumps and Road Surface Defects
| Autor: | Patrick McLaughlin, Christopher Vagg |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Signal processing
Computer science business.industry Mechanical Engineering Real-time computing Intelligent vehicles Driver information systems Vehicle control Track (rail transport) Localisation Standard deviation Suspension (motorcycle) Displacement (vector) Position location estimation Computer Science Applications Position (vector) Road surface Automotive Engineering Global Positioning System business |
| Zdroj: | Mclaughlin, P & Vagg, C 2022, ' A New Method of Vehicle Positioning Using Bumps and Road Surface Defects ', IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, 9616399, pp. 13655-13665 . https://doi.org/10.1109/TITS.2021.3126465 |
| DOI: | 10.1109/TITS.2021.3126465 |
| Popis: | This paper presents the first usage of road surface defects as a means of vehicle position detection. Whilst several applications are possible, this work focuses on use in Formula E racing, where several driver information systems depend heavily upon accurate vehicle position estimation, including energy management advice and split time information, and where use of common positioning systems such as GPS is forbidden. Teams currently estimate the position on track by integrating vehicle speed, but this is susceptible to error accumulation throughout a lap, diminishing the precision and value of driver information systems. This work presents a method to improve the vehicle's position estimate by detecting bumps in the road surface using suspension damper displacement data, an approach which is novel because it is independent of common positioning techniques such as GPS. These bumps are used as positionally-fixed checkpoints around the track, allowing the positional estimate to be regularly corrected, mitigating drift in the original estimated position. Results of the bump detection algorithm developed show for the first time that this technique can pinpoint the vehicle position with a precision of 1.41m standard deviation, with scope for further improvement. This result is significant for positioning surface vehicles where other more standard techniques are precluded. In the Formula E application the approach is found to improve the precision (consistency) of the vehicle positional estimate for large parts of the circuit, which will allow higher quality and more reliable information to be given to the driver, thereby giving a competitive advantage. |
| Databáze: | OpenAIRE |
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