Vehicle trajectory at curved sections of two-lane mountain roads: a field study under natural driving conditions

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.

Human-like driving behaviour emerges from a risk-based driver model

“…Lateral position: Research has shown that drivers exhibit ‘curve-cutting’, that is, they do not follow the centreline of the lane but try to increase the effective radius of travel 29 – 31 . For model validation, we selected the on-road study by Xu et al 32 because it provides the largest sampling of curve radii (0–200 m). They found that the amount of curve-cutting reduced as the curve radius increased (Fig.…”

Track Behavior and Crash Risk Analysis of Passenger Cars on Hairpin Curves of Two-Lane Mountain Roads

“…Due to the low traffic volume, drivers have a high degree of freedom when driving on two-lane mountain roads. Many drivers utilize the full width of the road, and their tracks, to some extent, deviate from the centerline of the road (an imaginary driving track in road design) [1]. In recent years, accidents that involve vehicles that deviate from traffic lanes in the curved sections of mountain roads (e.g., collisions and scratching between vehicles in opposite directions, overturns, collisions with the guardrail or mountain, and running off the road) have occurred frequently and even increased.…”

“…Llorca et al [4]; Kanagaraj et al [5]; and Raju et al [6] extracted vehicle tracks from captured images and examined driving behaviors (e.g., overtaking and lane changing, lateral positions, headway, and relative speed) or vehicle operation parameters and described the operating status of traffic. Xu et al [1] and Deng et al [7] conducted field driving tests on two-lane mountain roads in naturally driving conditions and determined vehicle tracks based on Global Positioning System (GPS) data combined with video images. In addition, by clustering tracks based on the shape characteristics of lateral deviation ratio curves, they identified the track patterns on the curved sections of mountain roads and analyzed the vehicle crash risks based on the topological relation between tracks and traffic lanes.…”

Differences in the Gaze Behaviours of Pedestrians Navigating between Regular and Irregular Road Patterns

“…[2,3]. These sophisticated systems not only impact the performance of transportation systems [4] and land use [5] but also strongly influence people's behaviours [6][7][8][9][10]. Many researchers have focused on the geometric attributes of road patterns and navigation solutions based on shortest time/distance routes [11,12] or other objective conditions [13].…”