TY - JOUR
T1 - In-Vehicle Sensing for Smart Cars
AU - Zeng, Xiaolu
AU - Wang, Fengyu
AU - Wang, Beibei
AU - Wu, Chenshu
AU - Liu, K. J.Ray
AU - Au, Oscar C.
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2022
Y1 - 2022
N2 - Driving safety has been attracting more and more interest due to the unprecedented proliferation of vehicles and the subsequent increase of traffic accidents. As such the research community has been actively seeking solutions that can make vehicles more intelligent and thus improve driving safety in everyday life. Among all the existing approaches, in-vehicle sensing has become a great preference by monitoring the driver's health, emotion, attention, etc., which can offer rich information to the advanced driving assistant systems (ADAS) to respond accordingly and thus reduce injuries as much/early as possible. There have been many significant developments in the past few years on in-vehicle sensing. The goal of this paper is to provide a comprehensive review of the motivation, applications, state-of-the-art developments, and possible future interests in this research area. According to the application scenarios, we group the existing works into five categories, including occupancy detection, fatigue/drowsiness detection, distraction detection, driver authentication, and vital sign monitoring, review the fundamental techniques adopted, and present their limitations for further improvement. Finally, we discuss several future trends for enhancing current capabilities and enabling new opportunities for in-vehicle sensing.
AB - Driving safety has been attracting more and more interest due to the unprecedented proliferation of vehicles and the subsequent increase of traffic accidents. As such the research community has been actively seeking solutions that can make vehicles more intelligent and thus improve driving safety in everyday life. Among all the existing approaches, in-vehicle sensing has become a great preference by monitoring the driver's health, emotion, attention, etc., which can offer rich information to the advanced driving assistant systems (ADAS) to respond accordingly and thus reduce injuries as much/early as possible. There have been many significant developments in the past few years on in-vehicle sensing. The goal of this paper is to provide a comprehensive review of the motivation, applications, state-of-the-art developments, and possible future interests in this research area. According to the application scenarios, we group the existing works into five categories, including occupancy detection, fatigue/drowsiness detection, distraction detection, driver authentication, and vital sign monitoring, review the fundamental techniques adopted, and present their limitations for further improvement. Finally, we discuss several future trends for enhancing current capabilities and enabling new opportunities for in-vehicle sensing.
KW - Artificial intelligence
KW - advanced driving assistant systems (ADAS)
KW - distraction/inattention
KW - driver authentication
KW - fatigue/drowsiness
KW - in-vehicle sensing survey
KW - occupancy detection
KW - smart car
KW - vital sign monitoring
KW - wireless sensing
UR - http://www.scopus.com/inward/record.url?scp=85132043716&partnerID=8YFLogxK
U2 - 10.1109/OJVT.2022.3174546
DO - 10.1109/OJVT.2022.3174546
M3 - Article
AN - SCOPUS:85132043716
SN - 2644-1330
VL - 3
SP - 221
EP - 242
JO - IEEE Open Journal of Vehicular Technology
JF - IEEE Open Journal of Vehicular Technology
ER -