An Evolutionary Approach to Driving Tendency Recognition for Advanced Driver Assistance Systems

Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS). However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning met...

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Bibliographic Details
Main Authors: Lee, Jong-Hyun, Ahn, Chang Wook
Format: Conference Proceeding
Language:English
Subjects:
Advanced driver assistance systems
Automobile driving
Classification
Evolutionary computation
Machine learning
Recognition
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Summary:Driving tendency recognition is important for constructing Advanced Driver Assistance Systems (ADAS). However, it had not been a lot of research using vehicle sensing data, due to the high difficulty to define it. In this paper, we attempt to improve the learning capability of a machine learning method using evolutionary computation. We propose a driving tendency recognition method, with consideration of data characteristics. Comparison of our classification system with conventional methods demonstrated the effectiveness and accuracy over 92% in our system. Our proposed evolutionary approach is confirmed that improve the classification accuracy of the learning method through evolution in the experiment.
ISSN:2261-236X
2274-7214
2261-236X
DOI:10.1051/matecconf/20165602012