Abstract
Driver behavior profiling is a significant technology in intelligent transportation as it provides contextual knowledge regarding the driver's aggressiveness. The prior studies analyzed the data's temporal characteristics and established classifiers between the normal and aggressive driver behavior in a supervised manner. However, there exist limits that the practitioner should acquire a labeled dataset, and the model could not identify unseen driver behaviors a priori. To hedge the aforementioned limits, our study proposes a novel driver behavior profiling approach under the normality discovery paradigm, which is unsupervised learning. First, we presented practical feature engineering steps to transform the smartphone IMU's raw sensor measurements to the sequence of driving data. Second, we established an unsupervised driver profiling approach that necessitates the driving data of normal driver behavior only for the model training. Third, we figured out each aggressive driver behavior has a different sequence length to represent its unique patterns. Lastly, we compared our approach's performance with a supervised approach and resulted in our unsupervised model achieved similar performance in identifying aggressive right turn, left turn, and left lane change, but required further improvements in recognizing an aggressive left lane change, aggressive braking, and aggressive acceleration.
Original language | English |
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Title of host publication | 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 278-284 |
Number of pages | 7 |
ISBN (Electronic) | 9781728191423 |
DOIs | |
Publication status | Published - 2021 Sept 19 |
Externally published | Yes |
Event | 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 - Indianapolis, United States Duration: 2021 Sept 19 → 2021 Sept 22 |
Publication series
Name | IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC |
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Volume | 2021-September |
Conference
Conference | 2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 |
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Country/Territory | United States |
City | Indianapolis |
Period | 21/9/19 → 21/9/22 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
ASJC Scopus subject areas
- Automotive Engineering
- Mechanical Engineering
- Computer Science Applications