Driver Status Monitoring Systems for Smart Vehicles Using Physiological Sensors A safety enhancement system from automobile manufacturers

Automobiles provide a convenient form of transportation, and the number of automobiles in the world has been increasing rapidly, from 193 million in 1970 to more than 796 million in recent years [1]. However, automobiles have created a number of serious problems, such as accidents, traffic congestion, and air pollution, among which traffic accidents are one of the most serious and urgent problems threatening the safety of automobile users. The U.S. Department of Transportation National Highway Traffic Safety Administration found that traffic accidents are mostly caused by drivers' inattention, high-speed driving, drunken driving, misperception, decision errors, and driver incapacitation (e.g., falling asleep or having a heart attack while driving). Among these causes, drunken driving and driver incapacitation account for about 25% of total traffic accidents [2]. In 2014, the American Automobile Association Foundation for Traffic Safety in the United States reported that an average of 328,000 traffic accidents annually involve a drowsy driver [3]. In Europe, 20-25% of total traffic accidents were due to drowsy drivers [4]: In France in 2011, there were 3,970 fatal accidents on the road, in which 732 cases occurred on straight roads; 85% of these accidents were due to drowsy drivers [4]. In Germany, 25% of all fatal road traffic accidents were caused by drowsy drivers [4]. From 2006 to 2010, in Finland, 17% of fatal motor vehicle accidents were related to fatigued drivers; they were responsible for 18% of deaths on the road [4]. Driver status monitoring (DSM) systems have emerged as an innovative technology to prevent traffic accidents from driver incapacitation. In recent developments of DSM systems, medical technologies used for patient diagnosis, including those utilizing electrocardiogram (ECG) and photoplethysmogram (PPG), are considered for the acquisition of driver's physiological signals, which is an effective approach that should be given a special attention.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2016-11
Language
English
Citation

IEEE SIGNAL PROCESSING MAGAZINE, v.33, no.6, pp.22 - 34

ISSN
1053-5888
DOI
10.1109/MSP.2016.2602095
URI
http://hdl.handle.net/10203/214396
Appears in Collection
GT-Journal Papers(저널논문)
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