Categorization of driving characteristics using deep clustering심층 군집화를 이용한 운전 특성 분류

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Driving behavior is an effective means to analyze a driver who drives a vehicle. In order to reduce traffic crashes and environmental pollution problems caused by the increase in vehicles, various studies on the driver are being conducted. In particular, due to the recent development of various sensor technologies, it is possible to collect large-scale driving records from many drivers. However, the large-scale driving record is multidimensional time-series data, and there is a limit to quantitatively analyzing it. The purpose of this dissertation is to categorize driving characteristics from driving records and conduct driving behavior analyses using the characteristics. A methodology for deriving the elementary driving behavior (EDB), which is a norm driving behavior for each driving environment, is presented through deep clustering, and the EDB is extracted using the driving record data of taxi drivers. For a traffic safety study, the EDB-based abnormal driving score that can numerically represent drivers' propensities for each driving environment is developed, and the differences according to driver propensities are verified. For a traffic environment study, the EDB-based driving cycle generation model is developed to reflect various trajectories' characteristics. The driving behavior characterization method presented in this dissertation can be effectively used in transportation research in the mobility era, contributing to the construction of a safe and efficient transportation system.
Advisors
Jang, Kitaeresearcher장기태researcher
Description
한국과학기술원 :조천식모빌리티대학원,
Publisher
한국과학기술원
Issue Date
2022
Identifier
325007
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 조천식모빌리티대학원, 2022.8,[viii, 200 p. :]

Keywords

Driving behavior▼aDriving characteristics▼aDeep clustering▼aDriving record▼aDriving style▼aDriving cycle; 운전행동▼a운전특성▼a심층 군집화▼a주행기록▼a운전성향▼a주행사이클

URI
http://hdl.handle.net/10203/309307
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1007943&flag=dissertation
Appears in Collection
GT-Theses_Ph.D.(박사논문)
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