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- Title
A DATA-DRIVEN METHOD FOR VEHICLE SPEED ESTIMATION.
- Authors
Bonfitto, Angelo; Feraco, Stefano
- Abstract
This paper presents a method based on Artificial Neural Networks for estimation of the vehicle speed. The technique exploits the combination of two tasks: a) speed estimation by means of regression neural networks dedicated to different road conditions (dry, wet and icy); b) identification of the road condition with a pattern recognition neural network. The training of the networks is conducted with experimental datasets recorded during the driving sessions performed with a vehicle on different tracks. The effectiveness of the proposed approach is validated experimentally on the same car by deploying the algorithm on a dSPACE computing platform. The estimation accuracy is evaluated by comparing the obtained results to the measurement of an optical sensor installed on the vehicle and to the output of another estimation method, based on the mean value of velocity of the four wheels.
- Subjects
SPEED of motor vehicles; SPEED limits; ARTIFICIAL neural networks; ARTIFICIAL intelligence; VARIABLE speed limits
- Publication
Komunikácie, 2021, Vol 23, Issue 3, pB165
- ISSN
1335-4205
- Publication type
Article
- DOI
10.26552/com.C.2021.3.B165-B177