Latest revision as of 16:23, 12 February 2021

Abstract

Purpose The trajectory of a vehicle is comprehensively affected by the interactions between the vehicle, the driving behavior, and the road environment. High-risk driving behaviors and accident-prone road sections can be identified based on the relationship between the trajectory and road geometry. Previous related studies mostly focused on the trajectory deviation at a few points on the road, which cannot capture the continuous variation of the trajectory in an entire curve, and seldom considered the trajectory characteristics along curves with large deflection angles. The aim of this study is to investigate the trajectories passenger cars take on two-lane mountain roads and thus to determine the track patterns and its relevant risks. Methods Field driving experiments were performed on four two-lane mountain highways, and vehicle trajectories under natural driving conditions were acquired. The continuous change in the lateral deviation rate of the trajectory was also determined by putting the measured trajectories into the coordinate frame together with the edge line of roadway. Further, the morphological features of the vehicle trajectory and how it is affected by the highway geometry were analyzed. Results and conclusions The following were observed: i) Typical track patterns were determined according to features of LDRT profiles, four patterns for left-hand bends and five patterns for right-hand bends, which can be used to identify crash prone position and reveal the mechanism of crash. ii) Inertia may cause the vehicle to move too close to the outer side of the curve after a cut, for which reason the driver has to correct the trajectory, although overcorrection may move the vehicle into the oncoming lane. iii) A higher speed at curve entry adopt by the driver could result in a larger encroachment into opposite lane or shoulder. iv) The smaller the radius of the horizontal curve, the more frequently the trajectory entered the oncoming lane. These findings could provide a better understanding of the track behavior of passenger cars, judge the safety implications of driver behavior, and thus identify crash prone positioning and the potential mechanisms of head-on crashes, run-off-road and guardrail collisions.

Document type: Article

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The different versions of the original document can be found in:

• https://etrr.springeropen.com/track/pdf/10.1007/s12544-018-0284-x under the license http://creativecommons.org/licenses/by/4.0

• http://link.springer.com/article/10.1007/s12544-018-0284-x,

https://doaj.org/toc/1867-0717,

https://doaj.org/toc/1866-8887 under the license cc-by

• http://link.springer.com/article/10.1007/s12544-018-0284-x/fulltext.html,

http://link.springer.com/content/pdf/10.1007/s12544-018-0284-x.pdf,

http://dx.doi.org/10.1007/s12544-018-0284-x

• https://link.springer.com/content/pdf/10.1007%2Fs12544-018-0284-x.pdf,

https://etrr.springeropen.com/articles/10.1007/s12544-018-0284-x,

https://link.springer.com/article/10.1007/s12544-018-0284-x,

https://etrr.springeropen.com/track/pdf/10.1007/s12544-018-0284-x,

https://rd.springer.com/article/10.1007/s12544-018-0284-x,

https://academic.microsoft.com/#/detail/2788535460 under the license http://creativecommons.org/licenses/by/4.0