Analysis and Validation of Surrogate Safety Measures by Types of Lead and Following Vehicles

2017 ◽  
Vol 2659 (1) ◽  
pp. 137-147 ◽  
Author(s):  
Peibo Zhao ◽  
Chris Lee

This study analyzed rear-end collision risk in a mixed traffic flow of cars and heavy vehicles on a freeway using two surrogate safety measures: time to collision (TTC) and postencroachment time (PET). The study estimated surrogate safety measures for types of lead and following vehicles (car or heavy vehicle) by using the individual vehicle trajectory data. The vehicle trajectory data were collected from a segment of the US-101 freeway in Los Angeles, California. It was found that the distributions of TTC and PET were significantly different between types of lead and following vehicles. Also, the mean values of TTC and PET were higher for heavy vehicles following cars than for cars following cars and for cars following heavy vehicles. The study also validated TTC by using the simulated traffic data for a few minutes before the time of crashes that occurred on a section of the Gardiner Expressway in Toronto, Ontario, Canada. It was found that TTC reflects higher collision risk in the time intervals closer to the crash time and it reflects higher collision risk for the crash case than for the noncrash case. The findings suggest that the difference in rear-end collision risk between types of vehicle pairs should be considered in safety assessment of mixed traffic flow of cars and heavy vehicles.

2013 ◽  
Vol 838-841 ◽  
pp. 2117-2120
Author(s):  
Xiao Fang Yang ◽  
Jian Rong Wang ◽  
Xin Zhu Wang

This paper presents a new lane-changing model of multi-lane mixed traffic flow. The influences of heavy vehicles on lane-changing are analyzed. An improved accumulated speed benefit model is proposed in which drivers generate lane-changing intentions based on accumulated speed benefit of preceding vehicle in target lane over the preceding vehicle in current lane, not just relative to the speed and desired speed of subject vehicle. Drivers may accelerate or decelerate during lane-changing due to different traffic conditions. Simulations show that with the increase in the proportion of heavy vehicles, lane changing frequency first increases and then decreases. The model is validated with empirical data.


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