Driver Behavior Soft-Sensor Based on Neurofuzzy Systems and Weighted Projection on Principal Components
This work has as main objective the development of a soft-sensor to classify, in real time, the behaviors of drivers when they are at the controls of a vehicle. Efficient classification of drivers’ behavior while driving, using only the measurements of the sensors already incorporated in the vehicle...
| Authors: | , , , , |
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| Format: | article |
| Publication Date: | 2020 |
| Country: | España |
| Institution: | Universidad Loyola Andalucía |
| Repository: | Brújula |
| OAI Identifier: | oai:repositorio.uloyola.es:20.500.12412/6291 |
| Online Access: | https://hdl.handle.net/20.500.12412/6291 |
| Access Level: | Open access |
| Keyword: | Driver behaviour Classifier Soft-sensor Neurofuzzy systems Principal component analysis |
| Summary: | This work has as main objective the development of a soft-sensor to classify, in real time, the behaviors of drivers when they are at the controls of a vehicle. Efficient classification of drivers’ behavior while driving, using only the measurements of the sensors already incorporated in the vehicles and without the need to add extra hardware (smartphones, cameras, etc.), is a challenge. The main advantage of using only the data center signals of modern vehicles is economical. The classification of the driving behavior and the warning to the driver of dangerous behaviors without the need to add extra hardware (and their software) to the vehicle, would allow the direct integration of these classifiers into the current vehicles without incurring a greater cost in the manufacture of the vehicles and therefore be an added value. In this work, the classification is obtained based only on speed, acceleration and inertial measurements which are already present in many modern vehicles. The proposed algorithm is based on a structure made by several Neurofuzzy systems with the combination of projected data in componentsof various PrincipalComponent Analysis.A comparisonwith several typesof classicalclassifyingalgorithms has been made. |
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