Development of Urgent Decleration Safety Indicator Designed for Opportune Detection of Rear-End Conflict

Message:
Abstract:
A large number of traffic accidents are due to the human errors. Advanced driver assistance systems can reduce human errors and thereby the number of accidents. An important issue in developing such systems is the use of a proper warning strategy, which warns the driver when the situation is critical and immediate reaction is required. Although time-to-collision (TTC) has been recently suggested and used, as a cue for decision-making in ADAS, but this indicator is unable to detect potential rear-end collisions. On the other hand, short time headway (THDW) during carfollowing period indicates that there is a high potential risk of collision, as soon as the lead vehicle starts braking. In this paper, a new safety indicator, urgent deceleration index (UDI), is developed. UDI can detect critical situations a few seconds sooner than TTC giving the driver more time for reaction planning, and hence providing a better margin of safety. To compare the sufficiency of UDI, TTC and THDW, as safety indicators, percent time spent unsafe, during following period is computed per lane using the detailed data gathered in the NGSIM project for I-80 freeway. Results indicate that the percentage frequency of time in rear-end conflict is 3, 63 and 76 percent, based on TTC, UDI and THDW, respectively. Also, the average correlation coefficient of critical situations based on UDI and THDW is about 0.644. In all, results indicate that UDI is more capable than TTC in detecting rear-end conflict.
Language:
Persian
Published:
Journal of Transportation Engineering, Volume:1 Issue: 3, 2010
Page:
27
https://magiran.com/p851090  
سامانه نویسندگان
  • Safarzadeh، Mahmoud
    Corresponding Author (2)
    Safarzadeh, Mahmoud
    Professor Faculty of Civil and Environmental Engineering, Tarbiat Modares University, تهران, Iran
  • Mamdoohi، Amir Reza
    Author (3)
    Mamdoohi, Amir Reza
    Associate Professor Civil & Environmental Engineering, Tarbiat Modares University, تهران, Iran
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