Abstract
All drivers have their own habitual choice of driving behavior, causing variations in fuel consumption. It would be beneficial to classify these driving styles and extract the most economical and ecological driving patterns. However, driving style of each driver is not consistent and may vary within a single trip. Therefore, this paper proposes a novel technique to robustly classify driving style using the Support Vector Clustering approach, which attempts to differentiate the variations in individual's driving pattern and provides an objective driver classification. Real driving data of three human participants were collected using an instrumented vehicle. For data processing, each trip data were first segmented into separate event groups. Prominent factors were then extracted by applying Principal Component Analysis on both statistical and spectral features of all signals. Afterwards, Support Vector Clustering was performed to classify driving style during the trip. The trained classifier was used to indicate the driving pattern variations in percentage. The validity of the proposed method was evaluated using the jerk profile, where a high correlation was found between the classification results and jerk distributions. Moreover, a positive relation between fuel consumption and driving aggressivity was also confirmed. Furthermore, it was found that weather condition, time of the day and ultimately, the driver's eagerness, can cause significant variations in driving style.
Original language | English |
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Title of host publication | 2018 3rd IEEE International Conference on Intelligent Transportation Engineering, ICITE 2018 |
Publisher | IEEE |
Pages | 264-268 |
Number of pages | 5 |
ISBN (Electronic) | 9781538678312 |
DOIs | |
Publication status | Published - 18 Oct 2018 |
Event | 3rd IEEE International Conference on Intelligent Transportation Engineering, ICITE 2018 - Singapore, Singapore Duration: 3 Sept 2018 → 5 Sept 2018 |
Publication series
Name | 2018 3rd IEEE International Conference on Intelligent Transportation Engineering, ICITE 2018 |
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Conference
Conference | 3rd IEEE International Conference on Intelligent Transportation Engineering, ICITE 2018 |
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Country/Territory | Singapore |
City | Singapore |
Period | 3/09/18 → 5/09/18 |
Funding
ACKNOWLEDGMENT This research is supported by the China Scholarship Council (Grant No. 201508060041) and the University of Bath Graduate School Scholarship.
Keywords
- Driving style classification
- Fuel consumption
- Principal component analysis
- Support vector clustering
ASJC Scopus subject areas
- Decision Sciences (miscellaneous)
- Automotive Engineering
- Civil and Structural Engineering
- Control and Optimization
- Transportation
- Urban Studies