Stay As You Were: Unsupervised Driver Behavior Profiling through Discovering Normality on Smartphone Sensor Measurements

Kyung Ho Park, Eunji Park, Huy Kang Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publication2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages278-284
Number of pages7
ISBN (Electronic)9781728191423
DOIs
Publication statusPublished - 2021 Sep 19
Event2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021 - Indianapolis, United States
Duration: 2021 Sep 192021 Sep 22

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2021-September

Conference

Conference2021 IEEE International Intelligent Transportation Systems Conference, ITSC 2021
Country/TerritoryUnited States
CityIndianapolis
Period21/9/1921/9/22

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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