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. 2022 Dec 21;20(1):76.
doi: 10.3390/ijerph20010076.

Effect of Five Driver's Behavior Characteristics on Car-Following Safety

Junjie Zhang  1 , Can Yang  1 , Jun Zhang  1 , Haojie Ji  2
Affiliations

Effect of Five Driver's Behavior Characteristics on Car-Following Safety

Junjie Zhang et al. Int J Environ Res Public Health. .

Abstract

Driver's behavior characteristics (DBCs) influence car-following safety. Therefore, this paper aimed to analyze the effect of different DBCs on the car-following safety based on the desired safety margin (DSM) car-following model, which includes five DBC parameters. Based on the Monte Carlo simulation method, the effect of DBCs on car-following safety is investigated under a given rear-end collision (RECs) condition. We find that larger subjective risk perception levels can reduce RECs, a smaller acceleration sensitivity (or a larger deceleration sensitivity) can improve car-following safety, and a faster reaction ability of the driver can avoid RECs in the car-following process. It implies that DBCs would cause a traffic wave in the car-following process. Therefore, a reasonable value of DBCs can enhance traffic flow stability, and a traffic control strategy can improve car-following safety by using the adjustment of DBCs.

Keywords: car-following safety; desired safety margin; driver’s behavior characteristics; sensitivity analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Classification of DBCs.
Figure 2
Figure 2
Braking process between two successive vehicles during a car-following situation.
Figure 3
Figure 3
Cars moving on a straight road.
Figure 4
Figure 4
Varying of REC probability with response time.
Figure 5
Figure 5
Varying of REC probability with the limits of the DSM, (a) upper limit of the DSM; (b) lower limit of the DSM.
Figure 6
Figure 6
Varying of REC probability with the acceleration and deceleration preference coefficients, (a) acceleration preference coefficient; (b) deceleration preference coefficient.
Figure 7
Figure 7
Gap patterns of all vehicles with DBCs at: (a) t = 300 s; (b) t = 500 s; (c) t = 800 s; (d) t = 1000 s.
Figure 8
Figure 8
REC probability patterns of all other cars (except the leading car) under different DBCs.
Figure 8
Figure 8
REC probability patterns of all other cars (except the leading car) under different DBCs.
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References

    1. Ghaffari A., Khodayari A., Hosseinkhani N., Salehinia S. The effect of a lane change on a car-following manoeuvre: Anticipation and relaxation behaviour. Proc. Inst. Mech. Eng. Part D J. Automob. Eng. 2015;229:809–818. doi: 10.1177/0954407014547930. - DOI
    1. Tanaka M., Ranjitkar P., Nakatsuji T. Asymptotic stability and vehicle safety in dynamic car-following platoon. Transp. Res. Rec. 2008;2088:198–207. doi: 10.3141/2088-21. - DOI
    1. Tampere C., Hoogendoorn S., Van Arem B. A behavioural approach to instability, stop and go waves, wide jams and capacity drop. Transp. Traffic Theory. 2005;16:205–228.
    1. Huang D., Yan Y., Su C., Xu G. Prediction-based geographic routing over VANETs. Rev. Tec. Fac. Ing. Univ. Zulia. 2016;39:157–164.
    1. Administration N.H.T.S. National Automotive Sampling System–Crashworthiness Data System: 2012 Analytical User’s Manual. US Department of Transportation; Washington, DC, USA: 2014.

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