Risky Traffic Situation Detection and Classification Using Smartphones-Reference-Cited by-同舟云学术

Risky Traffic Situation Detection and Classification Using Smartphones

Published:2023 Issue: Volume:4 Page:846-857
ISSN:2687-7813
Container-title:IEEE Open Journal of Intelligent Transportation Systems
language:
Short-container-title:IEEE Open J. Intell. Transp. Syst.

Author:

Uchiyama Akira¹^ORCID,Hiromori Akihito¹,Akikawa Ryota¹,Yamaguchi Hirozumi¹^ORCID,Higashino Teruo²^ORCID,Suzuki Masaki³^ORCID,Hiehata Yasuhiko⁴,Kitahara Takeshi⁴

Affiliation:

1. Graduate School of Information Science and Technology, Osaka University, Suita, Japan

2. Faculty of Engineering Department of Information and Computer Science, Kyoto Tachibana University, Kyoto, Japan

3. Core Network Laboratory, KDDI Research, Inc., Fujimino, Japan

4. Social Implementation Promotion Department, KDDI Corporation, Chiyoda, Tokyo, Japan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/8784355/9999144/10318156.pdf?arnumber=10318156

Reference44 articles.

1. Perceived traffic risk for cyclists: The impact of near miss and collision experiences

2. Driving Blind: Weather-Related Vision Hazards and Fatal Motor Vehicle Crashes

3. Vision-Based Nighttime Vehicle Detection Using CenSurE and SVM

4. A computational model of pedestrian road safety: The long way round is the safe way home

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