Injury Risks of Rear Occupant in Typical Four-door Type of Pick-up Truck under Vehicle Collision

This research explores the injury risks of occupants in four-door type of pick-up truck using experimental based collision with Hybrid III dummy for occupant injury indicators. The full-sized crash laboratory was developed to conduct full frontal impact based on standard regulation. To verify performance of full-sized crash laboratory and vehicle deceleration, low and high speed tests were conducted at the same vehicle. The Hybrid III dummy with head and chest sensors was used at the rear outboard seat during high speed test. Consequently, the deflection and thoracic viscous criteria, which represent the chest injuries, are up to 93 mm and 3.96 m/s, respectively, high beyond the standard requirement. Moreover, the most important finding of this research is that the four-door pickup truck is subjected to the 2nd impact up to 116.51 G at dummy head with higher resultant acceleration than the 1st impact (65.62 G) due to the limited space behind the rear headrest and thinner backrest of rear seat. This research also investigates the post-crash results to illustrate the suggestive idea for improving crashworthiness of future design resulting in mitigation of occupant injuries.

Effects of sedan wheelbase size on left rear-seat occupant injury risk in small offset crashes

The objective of this study was to investigate the effect of sedan wheelbase size on the kinematics and injury severity of left rear-seat occupants by using the finite element (FE) modeling method. A total of 270 cases with detailed accidental information records were analyzed to define the influence laws of wheelbase size and impact speed on the injury of left rear-seat occupants. First, the THUMS (Ver. 4.0.2) FE model was used to reconstruct two small offset collisions with different wheelbases size and unbelted left rear-seat occupants, and the effectiveness of the accident model was verified. Then, seatbelts were added to the left rear-seat occupant models. Finally, LS-DYNA software was used to study the correlation among head and chest injury and five sedan wheelbases sizes (2300, 2450, 2600, 2750, and 2905 mm) at three impact velocities (54, 64, and 74 km/h). The results showed that the occupants’ chest injuries showed an upward trend at the impact velocity of 64 and 74 km/h when the wheelbases sizes was reduced to 2300 mm. This research illustrated that at higher impact velocities, excessively small wheelbases might increase the chest injury severity of left rear-seat occupants.

Use of Real-Time Traffic and Signal Timing Data in Modeling Occupant Injury Severity at Signalized Intersections

This study explored the use of real-time traffic events and signal timing data to determine the factors influencing the injury severity of vehicle occupants at intersections. The analysis was based on 3 years (2017–2019) of crash and high-resolution traffic data. The best fit regression was first identified by comparing the conventional regression model and logistic models with random effect. The logistic model with a heavy-tailed distribution random effect best fitted the data set, and it was used in the variable assessment. The model results revealed that about 13.6% of the unobserved heterogeneity comes from site-specific variations, which underlines the need to use the logistic model with a random effect. Among the real-time traffic events and signal-based variables, approach delay and platoon ratio significantly influenced the injury severity of vehicle occupants at 90% Bayesian credible interval. Additionally, the manner of a collision, occupant seat position, number of vehicles involved in a crash, gender, age, lighting condition, and day of the week significantly affected the vehicle occupant injury. The study findings are anticipated to provide valuable insights to transportation agencies for developing countermeasures to mitigate the crash severity risk proactively.

Design and dynamics simulation of vehicle active occupant restraint protection system

A restraint protection system for front row occupant is designed according to the collision danger level. An algorithm based on driver response time margin is designed to determine the danger level of collision. The algorithm gives different possibility of collision, corresponding to different danger level, and corresponding starting different constraint protection device. The simulation model of automobile frontal collision was established in the dynamic simulation software MADYMO and verified by experiment. Compared with the traditional occupant restraint protection system, the simulation results show that the proposed active restraint protection system improves the protection effect of the occupant’s head and hip, while the damage evaluation indexes such as peak neck bending moment, chest acceleration and chest compression decrease obviously. Therefore, the designed active occupant restraint protection system can effectively reduce the degree of occupant injury.