Image and Signal Processing
Submission DeadlineFeb. 20, 2020

Submission Guidelines: http://www.sciencepublishinggroup.com/home/submission

Lead Guest Editor
Yuanyuan Tian
School of Mechanical Engineering, Northeast Electric Power University, Jilin, China
Guest Editors
  • Yongchen Pei
    School of Mechanical and Aerospace Engineering, Jilin University, Changchun, Jilin, China
  • Zhanli Wang
    School of Mechatronic Engineering, Changchun University of Technology, Changchun, Jilin, China
  • Ggaojian Cui
    School of Mechatronic Engineering, Changchun University of Technology, Changchun, Jilin, China
  • Bangcheng Zhang
    School of Mechatronic Engineering, Changchun University of Technology, Changchun, Jilin, China
  • Haitao Guo
    College of Marine Information Engineering, Hainan Tropical Ocean University, Sanya, Hainan, China
  • Linlin Xia
    School of Automation Engineering, Northeast Electric Power University, Jilin, China
Introduction
After NCAP announced a regulation, the demand for driver monitoring systems in foreign markets has been already very clear. In September 2017, the European NCAP announced the Road Map 2025, which formulated driver Monitoring, AEB and many technologies as the primary security systems. That is, since 2020, only if the vehicles have a driver monitoring function, can you obtain the EU five-star safety certification. In the view of the impact of NCAP on insurance companies and consumers, the demand can be imagined in foreign markets.
Although no similar policies have been introduced at present in China, some provinces and cities have taken the lead in promoting pilot projects in some high-risk scenarios. Since 2017, logistics, “two passengers and one danger” and other industry fields have a large demand for driver monitoring, especially for fatigue or distracted driving. With the improvement of domestic production level and the development of people's economic level, automobiles have become one of the important means of transportation for more and more people going out, but the accidents and safety matters of automobiles have also become frequent. Therefore, researches aiming at how to avoid traffic accidents have received increasing attention. Among the predisposing factors of many traffic accidents, driver's fatigue driving is one of the main causes of traffic accidents. According to the information provided by the traffic police department, about 40% of the current traffic accidents caused by fatigue are caused by fatigue driving, so fatigue driving poses a great threat to safe driving. After a long period of consequent driving, the driver produces an imbalance of physiological functions and mental functions and objectively appears to have a decline in driving skills. At the same time, the poor and insufficient drivers' sleep qualities and a long time driving also could cause drives exhausted easily. In the fatigue driving state, the driver's reaction time becomes longer and the thinking is slow due to mental fatigue which affects the driver's attention, feeling, perception, thinking, judgment, will, decision and movement, etc. that increase the possibility of danger. This kind of traffic accident can be effectively avoided by using an effective measure to immediately issue an alarm when the driver's fatigue driving state occurs. Therefore, the study of driver fatigue driving condition monitoring is of the great significance for improving traffic safety.
Aims and Scope:
  1. Fatigue Driving
  2. Image Process
  3. Deep Learning
  4. Atifitial Intelligence
  5. EEG
  6. ECG
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