Objective: Though autonomous emergency braking (AEB) systems for car-to-cyclist collisions have been under development, an estimate of the benefit of AEB systems based on an analysis of accident data is needed for further enhancing their development. Compared to the data available from in-depth accident data files, data provided by drive recorders can be used to reconstruct car-to-cyclist collisions with greater accuracy because the position of cyclists can be observed from the videos. In this study, using data from drive recorders, the performance and limitations of AEB systems were investigated. Method: Data of drive recorders involving taxi-to-cyclist collisions were collected. Using the images collected from the drive recorders of those taxis, 40 cases of 90° car-to-cyclist intersection collisions were reconstructed using PC-Crash. Then, the collisions were reconstructed again utilizing car models with AEB systems installed while changing the sensor’s field of view (FOV) and the delay time of initiating vehicle deceleration. Results: The angle of FOV has a significant influence on avoiding car-to-cyclist collisions. Using a 50° FOV with a braking delay time of 0.5 s resulted in avoiding 6 collisions, and using a 90° FOV resulted in avoiding an additional 14 collisions. Even when installing an ideal AEB system providing 360° FOV and no delay time for braking, 8 collisions were not avoided, though the impact velocities were reduced for all of these remaining collisions. These collisions were caused by the cyclists’ sudden appearance in front of cars, and the time-to-collision (TTC) when the cyclists appeared was less than 0.9 s. Conclusion: The AEB systems were effective for mitigating collisions that occurred due to driver perception delay. Because cyclists have a traveling velocity, a wide-angle FOV is effective for reduction of car-to-cyclist intersection collisions. The reduction of delay time in braking can reduce the number of collisions that are close to the braking performance limit. The collisions that remained even with an ideal AEB system in the PC-Crash simulation indicate that such collisions could still occur for autonomous cars if the traffic environment does not change.

Objective: In vehicle frontal impacts, vehicle acceleration has a large effect on occupant loadings and injury risks. In this research, an optimal vehicle crash pulse was determined systematically to reduce injury measures of rear seat occupants by using mathematical simulations. Method: The vehicle crash pulse was optimized based on a vehicle deceleration-deformation diagram under the conditions that the initial velocity and the maximum vehicle deformation were constant. Initially, a spring–mass model was used to understand the fundamental parameters for optimization. In order to investigate the optimization under a more realistic situation, the vehicle crash pulse was also optimized using a multibody model of a Hybrid III dummy seated in the rear seat for the objective functions of chest acceleration and chest deflection. A sled test using a Hybrid III dummy was carried out to confirm the simulation results. Finally, the optimal crash pulses determined from the multibody simulation were applied to a human finite element (FE) model. Results: The optimized crash pulse to minimize the occupant deceleration had a concave shape: a high deceleration in the initial phase, low in the middle phase, and high again in the final phase. This crash pulse shape depended on the occupant restraint stiffness. The optimized crash pulse determined from the multibody simulation was comparable to that from the spring–mass model. From the sled test, it was demonstrated that the optimized crash pulse was effective for the reduction of chest acceleration. The crash pulse was also optimized for the objective function of chest deflection. The optimized crash pulse in the final phase was lower than that obtained for the minimization of chest acceleration. In the FE analysis of the human FE model, the optimized pulse for the objective function of the Hybrid III chest deflection was effective in reducing rib fracture risks. Conclusions: The optimized crash pulse has a concave shape and is dependent on the occupant restraint stiffness and maximum vehicle deformation. The shapes of the optimized crash pulse in the final phase were different for the objective functions of chest acceleration and chest deflection due to the inertial forces of the head and upper extremities. From the human FE model analysis it was found that the optimized crash pulse for the Hybrid III chest deflection can substantially reduce the risk of rib cage fractures. Supplemental materials are available for this article. Go to the publisher's online edition of Traffic Injury Prevention to view the supplemental file.

This study introduces injury risk curves for the lumbar spine for use in the risk assessment of low back pain (LBP) caused by manual lifting of heavy loads. LBP has been a longstanding problem among industrial workers, giving rise to the development of assistive devices. However, quantitative evaluation methods to verify the safety of such devices have not yet been established. The notable biomechanical criterion of 3.4 kN of lumbar compressive force, defined by the National Institute for Occupational Safety and Health, applies only to young, healthy workers with a fixed risk level. This study on injury risk curves clarified the risk level of injury to the lumbar spine due to lumbar compressive force for individuals within a wide age range. The findings can be applied for the design and evaluation of assistive devices as well as the design of ergonomic guidelines for manual work.

The chest deflection and chest acceleration (3 ms) have been used as chest injury measures of Hybrid III dummy in frontal crash tests. In this research, the relationship between two chest injury measures was investigated based on finite element analysis of Hybrid III in a frontal impact. The equation of motion of the chest was established using the external (seatbelt force and airbag contact force) and internal forces (neck, shoulder joint, lumbar spine force) that are exert on the chest. Based on this formula, the mechanism of the chest acceleration that was generated can be examined with time. The chest deflection is related to the external forces (seatbelt and airbag force), and the chest acceleration is related to the external and internal forces. The influence that the restraint conditions (seatbelt path and force limiter) has on the chest acceleration and chest deflection was also investigated. The seatbelt path affected the rib cage deformation mode and the chest sternum deflection, but it has little effect of on the chest acceleration. Lowering the seatbelt force limiter value also reduced the chest deflection substantially, but it did not show any clear relationship with the chest acceleration since the kinematics and the internal forces of the Hybrid III dummy changed with varying force limiter values.