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A Review on Handicap Sections and Situations to Improve Driving Safety of Automated Vehicles

Sustainability. 2020;12(5509):5509 DOI 10.3390/su12145509

 

Journal Homepage

Journal Title: Sustainability

ISSN: 2071-1050 (Online)

Publisher: MDPI AG

LCC Subject Category: Technology: Environmental technology. Sanitary engineering: Environmental effects of industries and plants | Technology: Mechanical engineering and machinery: Renewable energy sources | Geography. Anthropology. Recreation: Environmental sciences

Country of publisher: Switzerland

Language of fulltext: English

Full-text formats available: PDF, HTML, ePUB, XML

 

AUTHORS


Chang-Gyun Roh (Smart Mobility Research Center, Department of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi 10223, Korea)

I-Jeong Im (Smart Mobility Research Center, Department of Future Technology and Convergence Research, Korea Institute of Civil Engineering and Building Technology, Gyeonggi 10223, Korea)

EDITORIAL INFORMATION

Blind peer review

Editorial Board

Instructions for authors

Time From Submission to Publication: 11 weeks

 

Abstract | Full Text

An automated vehicle performs self-driving by utilizing information gathered through sensors attached to the vehicle. Sensor accuracy is thus mentioned as the major technology for enhancing driving safety. However, since urban centers are replete with sections and situations that handicap driving such as sensor recognition limitations and failures, it is necessary to conduct a study that prepares for driving handicaps. As such, this study aims to derive the sections and situations where driving safety is depreciated and review those problems via an analytic hierarchy process (AHP) analysis on driving handicap factors. The analysis result showed that the importance of these handicap situations is high, and it was confirmed that it is necessary to first review off-road sections, environmental factors (heavy rain or snow), merge sections, and sections with poor lane conditions. The result of this research has significance in reviewing road sections and potential situations that require primary verification for securing the driving safety of automated vehicles. It is expected to be utilized in the relevant studies as a basic study.