Kinetic and Kinematic Features of Pedestrian Avoidance Behavior in Motor Vehicle Conflicts

Abstract

The active behaviors of pedestrians, such as avoidance motions, affect the resultant injury risk in vehicle–pedestrian collisions. However, the biomechanical features of these behaviors remain unquantified, leading to a gap in the development of biofidelic research tools and tailored protection for pedestrians in real-world traffic scenarios. In this study, we prompted subjects (“pedestrians”) to exhibit natural avoidance behaviors in well-controlled near-real traffic conflict scenarios using a previously developed virtual reality (VR)-based experimental platform. We quantified the pedestrian–vehicle interaction processes in the pre-crash phase and extracted the pedestrian postures immediately before collision with the vehicle; these were termed the “pre-crash postures.” We recorded the kinetic and kinematic features of the pedestrian avoidance responses—including the relative locations of the vehicle and pedestrian, pedestrian movement velocity and acceleration, pedestrian posture parameters (joint positions and angles), and pedestrian muscle activation levels—using a motion capture system and physiological signal system. The velocities in the avoidance behaviors were significantly different from those in a normal gait (p < 0.01). Based on the extracted natural reaction features of the pedestrians, this study provides data to support the analysis of pedestrian injury risk, development of biofidelic human body models (HBM), and design of advanced on-vehicle active safety systems.

Can we reposition finite element human body model like dummies?

“…The original human–system interaction in virtual reality is one way. Volunteers visually perceive imminent car crashes by the eye and act physically to avoid them ( Li et al, 2021 ), but they will not be really hit if the attempts fail, so the message in passing is only virtual to physical. This study, instead, establishes a two-way interaction.…”

“…In terms of pedestrians, Nie et al (2021) established a virtual reality–based (VR) platform to investigate a pedestrian’s active avoidance maneuver against imminent car crashes ( Li et al, 2021 ). The instantaneous 3D poses of the volunteers are captured by an optical motion capture system (MoCap).…”

“…FIGURE 7Demonstration of the virtual reality-physical simulation pipeline. It is convenient to convert baseline THUMS pedestrian model into any arbitrary pose captured by the MoCap system (documented inLi et al, 2021; data visualized in OpenSim) with our method. The repositioned models are robust when exposed to 40 km/h impact from vehicle.…”

An Improved Social Force Model of Pedestrian Twice–Crossing Based on Spatial–Temporal Trajectory Characteristics

“…Qin et al introduced the theories of momentum conservation and energy conservation to establish a pedestrian crossing assessment model at intersections based on traffic conflict techniques [24]. Li et al analyzed the kinetic and kinematic features of pedestrians' active behaviors to quantify the pedestrian-vehicle interaction processes [25]. Liang et al used Newton's law of momentum conservation to explore the crowd pressure on pedestrian dynamics and recognize pedestrians' movement characteristics under various conditions [26].…”