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The Influence of Driving Experience on the Physiological Characteristics of the Driver Under Stress Scene

  • Xian-sheng Li
  • Fan-song Meng
  • Yuan-yuan Ren
  • Xue-lian Zheng
  • Jing-hai Zhang
  • Jia-hui Yan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 503)

Abstract

To study the influence of driving experience on physiological characteristics of drivers under the stress scene, it carries out the principal component analysis method to select the appropriate physiological indexes to analyze of the physiological data of different driving experience drivers. By means of mathematical statistics, the physiological data of drivers were analyzed and compared, and the physiological characteristics of drivers with different driving experiences were obtained. It shows that drivers with fewer experiences showed great physiological load in various stress scenarios; and experienced drivers due to situational awareness have less physiological fluctuations in the baseline period and the recovery period; experienced drivers show the superiority under stress scenarios which the risk appears slowly, while the risk appears suddenly, the advantage of experienced drivers have lower superiority. The growth rate of skin electric rate and heart rate can reflect the influence of driver’s experience on physiology.

Keywords

Aerodynamic characteristics Stealth characteristics Numerical calculation Polarization 

Notes

Conflict of Interests

Drivers’ Physiological signal used in the academic paper entitled “Influence of Driving Experience on the Physiological Characteristics of the Driver under Stress Scene” did not showed any clue to reveal test participants’ identity. The manuscript had been checked by the delegate of test participants, and obtained approval for report publication.

The authors of this manuscript declare that there is no conflict of interests regarding the publication of this article.

References

  1. 1.
    Vedagiri P, Kadali BR (2016) Evaluation of pedestrian-vehicle conflict severity at unprotected midblock crosswalks in India. Transp Res Rec 2581:48–56CrossRefGoogle Scholar
  2. 2.
    Kadali BR, Vedagiri P (2016) Proactive pedestrian safety evaluation at unprotected mid-block crosswalk locations under mixed traffic conditions. Saf Sci 89:94–105CrossRefGoogle Scholar
  3. 3.
    Himes S, Gross F, Eccles K et al (2016) Multistate safety evaluation of intersection conflict warning systems. Transp Res Rec 2583:8–16CrossRefGoogle Scholar
  4. 4.
    Peng-fei YANG, Rui FU, Peng-cheng YU (2013) Time characteristics of drivers’ stress perception in virtual urban road environment. J Chang’an Univ (Natural Science Edition) 33(2):73–78Google Scholar
  5. 5.
    Shen H, Zhou K (2016) In 2015 the rapid growth of motor vehicles and drivers of new car about 17810000 car ownership growth record of. Veh Saf (2):41–41Google Scholar
  6. 6.
    Chen Y, Pan L, Wei W (2011) Using kinetic energy to evaluate the severity of different types of traffic conflict at signalized intersections. ICCTP 2011Google Scholar
  7. 7.
    Pei Y, Zhou K, Zhang C (2011) Analysis of driver’s psycho-physiological and eye movement characteristics under alcohol effect. J Harbin Inst Technol 13(5):80–86Google Scholar
  8. 8.
    Miriam CI, Eduardo LC, Mikel I (2014) Muscle conduction velocity, surface electromyography variables, and echo intensity during concentric and eccentric fatigue. Muscle d Nerve 49(3):389–397Google Scholar
  9. 9.
    Li X, Shin L, Zhou P et al (2014) Pear spectral analysis of surface electromyography (EMG) at matched contraction levels of the first dorsal in muscle in stroke survivors. CI Finical Veuro Physiology 125(5):988–994Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xian-sheng Li
    • 1
  • Fan-song Meng
    • 1
  • Yuan-yuan Ren
    • 1
  • Xue-lian Zheng
    • 1
  • Jing-hai Zhang
    • 1
  • Jia-hui Yan
    • 2
  1. 1.School of TransportationJilin UniversityChangchunChina
  2. 2.Mitsubishi Electric (China) Co., Ltd. Shanghai BranchShanghaiChina

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