Comparison of Three Approaches for Scenario Classification for the Automotive Field

Abstract

To extend the functionalities of Advanced Driver Assistance Systems (ADAS) and have a more accurate control on the parameters of sensors mounted on an intelligent vehicle, a tool that can classify the scenarios which the vehicle moves in, is needed. This article presents a comparison of three classification techniques (PCA, ANN and SVM) to obtain a fast and robust scene classifier based only on images. The systems presented in this paper have been trained on three different categories of traffic scenarios: urban, highway, and rural, on a total of more than 23 hours of driving in different countries.

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The different versions of the original document can be found in:

• http://dx.doi.org/10.1007/978-3-642-41181-6_59

• https://link.springer.com/content/pdf/10.1007%2F978-3-642-41181-6_59.pdf