Characteristics of automatic emergency braking responses in passenger vehicles evaluated in the IIHS front crash prevention program.

Researchers can estimate the potential safety benefits of front crash prevention (FCP) systems by simulating system performance in rear-end crash scenarios reported to police or captured during naturalistic driving. Data to support assumptions about FCP systems in production vehicles, particularly automatic emergency braking (AEB), are limited. This study used detailed information from the Insurance Institute for Highway Safety's (IIHS's) FCP evaluation to characterize interventions in vehicles that performed well (superior-rated vehicles) and those that did not perform as well (basic/advanced-rated vehicles) when approaching a stationary surrogate vehicle on a test track at 20 and 40 km/h, and estimated performance in similar conditions at higher speeds. Vehicle and video data from 3,231 IIHS FCP tests conducted at 20 and 40 km/h and 51 IIHS FCP research tests conducted at 50, 60, and 70 km/h with AEB responses were analyzed. Forward collision warning (FCW) and AEB time-to-collision (TTC), mean deceleration, maximum deceleration, and maximum jerk from the beginning of automatic braking to the end of braking or impact were computed for each test. Each dependent measure was modeled with test speed (20 km/h, 40 km/h), IIHS FCP test rating (superior, basic/advanced), and the interaction between test speed and rating. The models were used to estimate each dependent measure at 50, 60, and 70 km/h, and model predictions were compared with the observed performance of six vehicles in IIHS research test data. Vehicles with superior-rated systems warned and began braking earlier, had a greater average rate of deceleration, reached a higher peak deceleration, and had greater jerk than vehicles with basic/advanced-rated systems, on average. The interaction between test speed and vehicle rating was significant in each linear mixed-effects model, indicating that these differences changed with test speed. FCW and AEB in superior-rated vehicles occurred 0.05 and 0.10 s earlier, respectively, per 10-km/h increase in test speed compared with basic/advanced-rated vehicles. Mean deceleration and maximum deceleration for FCP systems in superior-rated vehicles increased 0.65 m/s2 and 0.60 m/s2 more, respectively, per 10-km/h increase in test speed than for systems in basic/advanced-rated vehicles. Maximum jerk increased 2.78 m/s3 per 10-km/h increase in test speed for basic/advanced-rated vehicles but decreased 0.25 m/s3 for systems in superior-rated vehicles. The root mean square error between the observed performance and estimated values at 50, 60, and 70 km/h indicated that the linear mixed-effects model had reasonable prediction accuracy for every measure except jerk at these out-of-sample data points. The findings from this study provide insight into the characteristics that make FCP effective for preventing crashes. Based on performance in the IIHS FCP test, vehicles with superior-rated FCP systems had earlier TTC thresholds and braked with greater deceleration that increased with speed compared with basic/advanced-rated systems. The linear mixed-effects models that were developed can guide assumptions about AEB response characteristics for superior-rated FCP systems in future simulation studies.

Investigation of factors influencing submarining mitigation with child booster seats.

OBJECTIVE: Automobile booster seats are intended to improve belt fit for children that are too large for a harness-style child restraint, but not yet big enough to fit properly in an adult seat belt. Our objective was to prospectively study the relationship between booster seat design and interaction with the seat belt (specifically, submarining risk) for a child occupant using computer simulation of automobile crash events. METHODS: Frontal-impact simulations were performed with a 6-year-old child human body model. Simplified models of booster seats were developed using an automated process designed to capture key characteristics of booster geometry, stiffness, belt guide construction, and attachment to the vehicle seat. The child model was positioned in a range of postures from upright to slouched. Our main interest was submarining, where the child's pelvis slips under the lap belt and the belt loads into the abdomen (defined based on the motion of the lower lap belt edge relative to the ASIS). RESULTS: Among the parameters studied, the factors that had the greatest effect on submarining risk were the booster's stiffness and the child's posture. Booster models of a low-stiffness construction (similar to an inflatable booster) nearly always resulted in submarining, regardless of the other design characteristics of the booster. A slouched posture also substantially increased the likelihood of submarining (even for high-stiffness boosters). CONCLUSIONS: These results suggest that booster seats of a stiffer construction, and booster seats that promote an upright posture may provide a protective benefit compared to softer boosters and boosters that are more likely to result in slouching of the child.

Generating Human Arm Kinematics Using Reinforcement Learning to Train Active Muscle Behavior in Automotive Research.

Computational human body models (HBMs) are important tools for predicting human biomechanical responses under automotive crash environments. In many scenarios, the prediction of the occupant response will be improved by incorporating active muscle control into the HBMs to generate biofidelic kinematics during different vehicle maneuvers. In this study, we have proposed an approach to develop an active muscle controller based on reinforcement learning (RL). The RL muscle activation control (RL-MAC) approach is a shift from using traditional closed-loop feedback controllers, which can mimic accurate active muscle behavior under a limited range of loading conditions for which the controller has been tuned. Conversely, the RL-MAC uses an iterative training approach to generate active muscle forces for desired joint motion and is analogous to how a child develops gross motor skills. In this study, the ability of a deep deterministic policy gradient (DDPG) RL controller to generate accurate human kinematics is demonstrated using a multibody model of the human arm. The arm model was trained to perform goal-directed elbow rotation by activating the responsible muscles and investigated using two recruitment schemes: as independent muscles or as antagonistic muscle groups. Simulations with the trained controller show that the arm can move to the target position in the presence or absence of externally applied loads. The RL-MAC trained under constant external loads was able to maintain the desired elbow joint angle under a simplified automotive impact scenario, implying the robustness of the motor control approach.

Methodology for vehicle safety development and assessment accounting for occupant response variability to human and non-human factors.

The use of standardized anthropomorphic test devices and test conditions prevent current vehicle development and safety assessments from capturing the breadth of variability inherent in real-world occupant responses. This study introduces a methodology that overcomes these limitations by enabling the assessment of occupant response while accounting for sources of human- and non-human-related variability. Although the methodology is generic in nature, this study explores the methodology in its application to human response in far-side motor vehicle crashes as an example. A total of 405 human body model simulations were conducted in a mid-sized sedan vehicle environment to iteratively train two neural networks to predict occupant head excursion and thoracic injury as a function of occupant anthropometry, impact direction and restraint configuration. The neural networks were utilized in Monte Carlo simulations to calculate the probability of head-to-intruding-door impacts and thoracic AIS 3+ as a function of the restraint configuration. This analysis indicated that the vehicle used in this study would lead to a range of 667 to 2,448 head-to-intruding-door impacts and a range of 3,041 to 3,857 cases of thoracic AIS 3+ in the real world, depending on the seatbelt load limiter. These real-world results were later successfully validated using United States field data. This far-side assessment illustrates how the methodology incorporates the human and non-human variability, generates response surfaces that characterize the effects of the variability, and ultimately permits vehicle design considerations and injury predictions appropriate for real-world field conditions.

Occupant Restraint in Far-Side Impacts: Cadaveric and WorldSID Responses to a Far-Side Airbag.

Previous studies indicate that seatbelts may require supplementary restraints to increase their effectiveness in far-side impacts. This study aimed to evaluate the effectiveness of a novel, far-side-specific airbag in restraining and preventing injuries in far-side impacts, and to evaluate the WorldSID's response to the presence of a far-side airbag. A series of tests with three Post-Mortem Human Subjects and the WorldSID was conducted in a vehicle-based sled environment equipped with a far-side airbag. Results of these tests were evaluated and compared to a previous test series conducted without the airbag. All of the PMHS retained the shoulder belt on the shoulder. The airbag significantly reduced PMHS injury severity and maximum lateral head excursion. While the WorldSID exhibited a similar decrease in lateral excursion, it was unable to represent PMHS thoracic deflection or injury probability, and it consistently slipped out of the shoulder belt. This indicates that the WorldSID is limited both in its ability to evaluate the effect of changes in the seatbelt system and in its ability to predict thoracic injury risk and assess airbag-related injury mitigation countermeasures.

Submarining sensitivity across varied anthropometry in an autonomous driving system environment.

Objective: Self-driving technology will bring novelty in occupant seating choices and vehicle interior design. Thus, vehicle safety systems may be challenged to protect occupants over a wider range of potential postures and seating choices. This study aims to investigate the effects of occupant size, seat recline, and knee bolster position on submarining risk and injury prediction metrics for reclined occupants in frontal crashes.Methods: Frontal crash finite element (FE) simulations were performed with the 3 simplified Global Human Body Model Consortium (GHBMC) occupant models: small female, midsize male, and large male. Additionally, a detailed GHBMC midsize male model was used to compare with selected simplified cases. For each simulation, parameters including seatback recline angle (0.9°, 10.9°, 20.9°, 30.9°) and knee bolster position relative to the occupant (baseline, close, far, and no knee bolster) were varied. Impacts were simulated with the U.S. New Car Assessment Program 56 km/h frontal crash pulse. Occupant kinematics data were extracted from each simulation in a full-factorial sensitivity study to investigate how changes in anthropometry, seating position, and knee bolster position would affect submarining across all simulated cases.Results: Overall, increasing the occupant-to-knee bolster distance resulted in more submarining cases. The threshold for submarining was also affected by the seat recline angle. The lowest threshold observed occurred with 10.9° of recline with the small female model. Submarining was observed at recline angles at and above 20.9° for the midsize male model and 30° for the large male model. The initial lap belt position, pelvis orientation, and their relationship were good predictors of submarining. Increased lumbar flexion moment was observed with increased seat recline angle as well as occupant-to-knee bolster distance. The detailed GHBMC model was more prone to submarining than the simplified model.Conclusions: Submarining may be a major challenge to overcome for reclined occupants, which may become more prevalent with autonomous driving systems. This study shows that the angle of recline, anthropometric variation, and position of the knee bolster affect the risk of submarining. To our knowledge, this is the first study to computationally evaluate the occupant protection implications of seatback recline for multiple body sizes, postures, and positions relative to the vehicle interior.

PMHS and WorldSID Kinematic and Injury Response in Far-Side Events in a Vehicle-Based Test Environment.

Far-side kinematics and injury are influenced by the occupant environment. The goal of the present study was to evaluate in-vehicle human far-side kinematics, kinetics and injury and to assess the ability of the WorldSID to represent them. A series of tests with five Post-Mortem Human Subjects and the WorldSID were conducted in a vehicle-based sled test environment. The surrogates were subjected to a far-side pulse of 16.5 g in a 75-degree impact direction. The PMHS were instrumented with 6 degree-of-freedom sensors to the head, spine and pelvis, a chestband, strain gauge rosettes, a 3D tracking array mounted to the head and multiple single 3D tracking markers on the rest of the body. The WorldSID lateral head excursion was consistent with the PMHS. However, forward head excursion did not follow a PMHS-like trajectory after the point of maximum lateral excursion. All but one PMHS retained the shoulder belt on the shoulder during the entire test. However, the WorldSID consistently slipped out of the shoulder belt. The PMHS sustained an average of five rib fractures for which the seatbelt was observed to be the largest contributor. The WorldSID showed a maximum rib deflection of 25 mm. The first rib fracture occurred no later than 50 ms into the event. Anatomical differences between the WorldSID and the PMHS rib cage prevented the WorldSID from capturing the injury mechanisms related to interactions of the occupant with the seatbelt and the seat.