Numerical investigation of the rider's head injury in typical single-electric self-balancing scooter accident scenarios

Impact of Vehicle Steering Strategy on the Severity of Pedestrian Head Injury

In response to the sudden violation of pedestrians crossing the road, intelligent vehicles take into account factors such as the road conditions in the accident zone, traffic rules, and surrounding vehicles' driving status to make emergency evasive decisions. Thus, the collision simulation models for pedestrians and three types of vehicles, i.e., sedans, Sport Utility Vehicles (SUVs), and Multi-Purpose Vehicle (MPVs), are built to investigate the impact of vehicle types, vehicle steering angles, collision speeds, collision positions, and pedestrian orientations on head injuries of pedestrians. The results indicate that the Head Injury Criterion (HIC) value of the head increases with the increase in collision speed. Regarding the steering angles, when a vehicle's steering direction aligns with a pedestrian's position, the pedestrian remains on top of the vehicle's hood for a longer period and moves together with the vehicle after the collision. This effectively reduces head injuries to pedestrians. However, when the vehicle's steering direction is opposite to the pedestrian's position, the pedestrian directly collides with the ground, resulting in higher head injuries. Among them, MPVs cause the most severe injuries, followed by SUVs, and sedans have the least impact. Overall, intelligent vehicles have great potential to reduce head injuries of pedestrians in the event of sudden pedestrian-vehicle collisions by combining with Automatic Emergency Steering (AES) measures. In the future, efforts need to be made to establish an optimized steering strategy and optimize the handling of situations where steering is ineffective or even harmful.

Analysis of the consequences of car to micromobility user side impact crashes

INTRODUCTION

The strong rise in modes of travel commonly referred to as micromobility has changed the mobility patterns and lifestyles in cities worldwide, especially after the COVID-19 pandemic. It has led to a significant increase in the number of crashes involving these types of vehicles, especially bicycles and stand-up e-scooters. The risk of crashes is higher at intersections where motor-vehicles perform a turning maneuver crossing a bike lane.

METHOD

The consequences of a passenger car-to-micromobility vehicle side-impact crashes, considering both bicycle and e-scooter, were studied based on the results of the simulation of several scenarios with PC-Crash software. Two injury criteria were applied: Head Injury Criterion (HIC15) and 3 ms chest acceleration criterion.

RESULTS

When motor-vehicle speed is lower than 50 km/h, the 3 ms chest acceleration never exceeds the 60 g threshold. However, at 50 km/h, it is close to 50 g in the case of e-scooter rides. At this speed, HIC15 is considerably greater than 1000, both for bicycles and for e-scooters, and the safety margin of 700 is exceeded at 45 km/h for e-scooters.

CONCLUSIONS

In case of motor vehicle-to-micromobility vehicle side-impact crash, riding a bicycle is safer than riding an e-scooter since the observed HIC15 experienced by the cyclists is lower than that experienced by the e-scooter rider when motor vehicle speed is greater than 30 km/h.

PRACTICAL APPLICATIONS

To reduce micromobility users injury risk at intersections, motor vehicle speed limit should be equal or lower than 40 km/h. At this impact speed, the activation of hood or bumper airbags could be justified.

A Numerical Investigation of Rider Injury Risks During Falls Caused by E-Scooter-Stopper Impacts

Within the past decade, injuries caused by electric scooter (e-scooter) crashes have significantly increased. A primary cause is front wheel collisions with a vertical surface such as a curb or object, generically referred to as a "stopper." In this study, various e-scooter-stopper crashes were simulated numerically across different impact speeds, approach angles, and stopper heights to characterize the influence of crash type on rider injury risk during falls. A finite element (FE) model of a standing Hybrid III anthropomorphic test device was used as the rider model after being calibrated against certification test data. Additionally, an FE model of an e-scooter was developed based on reconstructed scooter geometry. Forty-five FE simulations were run to investigate various e-scooter crash scenarios. Test parameters included impact speed (from 3.2 m/s to 11.16 m/s), approach angle (30 deg to 90 deg), and stopper height (52 mm, 101 mm, and 152 mm). Additionally, the perpendicular (90 deg) impact scenarios were run twice: once with Hybrid-III arm activation to mimic a rider attempting to break a fall with their hands and once without this condition. Overall, the risks of serious injury to the rider varied greatly; however, roughly half the impact scenarios indicated serious risk to the rider. This was expected, as the speeds tested were in the upper 25th percentile of reported scooter speeds. The angle of approach was found to have the greatest effect on injury risk to the rider, and was shown to be positively correlated with injury risk. Smaller approach angles were shown to cause the rider to land on their side, while larger approach angles caused the rider to land on their head and chest. Additionally, arm bracing was shown to reduce the risk of serious injury in two thirds of the impact scenarios.