Study on the Take‐over Performance of Level 3 Autonomous Vehicles Based on Subjective Driving Tendency Questionnaires and Machine Learning Methods-Reference-Cited by-同舟云学术

Study on the Take‐over Performance of Level 3 Autonomous Vehicles Based on Subjective Driving Tendency Questionnaires and Machine Learning Methods

Published:2022-05-09 Issue:1 Volume:45 Page:75-92
ISSN:1225-6463
Container-title:ETRI Journal
language:en
Short-container-title:ETRI Journal

Author:

Kim Hyunsuk¹^ORCID,Kim Woojin¹^ORCID,Kim Jungsook¹^ORCID,Lee Seung‐Jun¹^ORCID,Yoon Daesub¹^ORCID,Kwon Oh‐Cheon¹,Park Cheong Hee²^ORCID

Affiliation:

1. Cognition & Transportation ICT Research Section Electronics and Telecommunications Research Institute Daejeon Republic of Korea

2. Department of Computer Science and Engineering Chungnam National University Daejeon Republic of Korea

Publisher

Wiley

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Link

https://onlinelibrary.wiley.com/doi/pdf/10.4218/etrij.2021-0241

Reference43 articles.

1. SAE J3016 Taxonomy and definitions for terms related to driving automation systems for on‐road motor vehicles September2016.

2. KOTSA (http://dvirnd.katri.kr 2017).

3. National Transportation Safety Board NTSB's report collision between a sport utility vehicle operating with partial driving automation Feb. 25 2020.

4. ISO/PDTR 21959 ISO TC 22/SC 139/WG 8 Road vehicles: Human performance and state in the context of automated driving: Part 1—Terms and definitions Jan.2018.

5. H. S.Kim W. J.Kim J. S.Kim S.Jun Lee andD. S.Yoon An analysis of transition characteristics of driver control authority according to NDRT type (Proceedings of the 5th International Symposium on Future Active Safety Technology toward Zero Accidents Blacksburg VA USA) Sept.2019.

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