An Evolutionary Approach to Driving Tendency Recognition for Advanced Driver Assistance Systems
| Autor: | Lee Jong-Hyun, Ahn Chang Wook |
|---|---|
| Jazyk: | English<br />French |
| Rok vydání: | 2016 |
| Předmět: | |
| Zdroj: | MATEC Web of Conferences, Vol 56, p 02012 (2016) |
| Druh dokumentu: | article |
| ISSN: | 2261-236X 81507712 |
| DOI: | 10.1051/matecconf/20165602012 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|