Research on Visual and Physiological Characteristics of Drivers Under Stress Scene

  • Xian-sheng Li
  • Da-wei Xing
  • Yuan-yuan RenEmail author
  • Fan-song Meng
  • Xue-lian Zheng
  • Jia-hui Yan
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 503)


To research the visual and physiological characteristics of drivers under stress scene, the visual and physiological data of drivers under different stress scenarios were analyzed. By using the method of dynamic clustering, Pearson test, and mathematical analysis, the visual and physiological characteristics of the driver in the stress situation were studied. In the meanwhile, the characteristics of the driver’s HRV were analyzed in time domain and frequency domain, which were selected as the analysis index. It shows that: the driver’s visual distribution is more concentrated under the stress scene and drivers are more accustomed to obtain traffic information from near the front of the region which they regard as the main area, when objects in the scene moving, the driver will judge the moving range of the object to selected 1–2 related auxiliary area for information retrieval. The driver used to gaze the main area and scan the auxiliary area. In terms of the rate of increase in heart rate, different stress scenarios will have a significant impact on the driver’s heart rate growth rate. In the HRV time domain characteristics, the driver to the two objectives of pedestrians and bicycles has a longer degree of tension, and the weather, the vehicle, the degree of tension of is intermittent. In the frequency domain characteristics of HRV, the driver’s mental workload has increased when he encounters pedestrians and bicycles, the driver’s mental workload has reduced when he encounters motor vehicles and external weather conditions.


Aerodynamic characteristics Stealth characteristics Numerical calculation Polarization 


  1. 1.
    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
  2. 2.
    Himes S, Gross F, Eccles K et al (2016) Multistate safety evaluation of intersection conflict warning systems. Transp Res Rec 2583:8–16CrossRefGoogle Scholar
  3. 3.
    Blom Henk AP, Bakker GJ (2015) Safety evaluation of ad-vanced self-separation under very high en route traffic demand. J Aerosp Inf Syst 12(6):413–427Google Scholar
  4. 4.
    (Su) Babu Markov (1983) Road conditions and traffic organization (trans: Qi Z). Chinese Architectural Industry Press, BeijingGoogle Scholar
  5. 5.
    Vedagiri P, Kadali BR (2016) Evaluation of pedestrian-vehicle conflict severity at unprotected midblock crosswalks in India. Transp Res Rec 2581:48–56CrossRefGoogle Scholar
  6. 6.
    Noble AM, Dingus TA, Doerzaph ZR (2016) Influence of in-vehicle adaptive stop display on driving behavior and safety. IEEE Trans Intell Transp Syst 17(10):2767–2776CrossRefGoogle Scholar
  7. 7.
    Brookhuis Karel A, De Waard D (1993) The use psychop-hysiology to assess driver status. Ergonomies 36(12):1099–1108CrossRefGoogle Scholar
  8. 8.
    Wu J (2009) Study on the method of heart rate variability analysis. Beijing Jiaotong University, College of computer and information technology, BeijingGoogle Scholar
  9. 9.
    Xiaofang L, Ye Z (2011) Analysis method and application of heart rate variability. Foreign Med Sci Biomed Eng 24(1):4245Google Scholar
  10. 10.
    Cheng Y, Li G, Gao X (2014) Changes in attention allocation characteristics of drivers driving on exp-ressway. China Saf Sci J 24(10):71–76Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xian-sheng Li
    • 1
  • Da-wei Xing
    • 1
    • 2
  • Yuan-yuan Ren
    • 1
    Email author
  • Fan-song Meng
    • 1
  • Xue-lian Zheng
    • 1
  • Jia-hui Yan
    • 3
  1. 1.School of TransportationJilin UniversityChangchunChina
  2. 2.Jilin Provincial Expressway AdministrationChangchunChina
  3. 3.Mitsubishi Electric (China) Co., Ltd. Shanghai BranchShanghaiChina

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