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Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. This paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios.

Driver’s license examinations require the driver to perform either a parallel parking or a similar maneuver as part of the on-road evaluation of the driver’s skills. Self-driving vehicles that are allowed to operate on public roads without a driver should also be able to perform such tasks successfully. With this motivation, the S-shaped maneuverability test of the Ohio driver’s license examination is chosen here for automatic execution by a self-driving vehicle with drive-by-wire capability and longitudinal and lateral controls. The Ohio maneuverability test requires the driver to start within an area enclosed by four pylons and the driver is asked to go to the left of the fifth pylon directly in front of the vehicle in a smooth and continuous manner while ending in a parallel direction to the initial one. The driver is then asked to go backwards to the starting location of the vehicle without stopping the vehicle or hitting the pylons.

Automated driving has become a very promising research direction with many successful deployments and the potential to reduce car accidents caused by human error. Automated driving requires automated path planning and tracking with the ability to avoid collisions as its fundamental requirement. Thus, plenty of research has been performed to achieve safe and time efficient path planning and to develop reliable collision avoidance algorithms. This paper uses a data-driven approach to solve the abovementioned fundamental requirement. Consequently, the aim of this paper is to develop Deep Reinforcement Learning (DRL) training pipelines which train end-to-end automated driving agents by utilizing raw sensor data. The raw sensor data is obtained from the Carla autonomous vehicle simulation environment here. The proposed automated driving agent learns how to follow a pre-defined path with reasonable speed automatically.

The Large Omnidirectional Child (LODC) developed by the National Highway Traffic Safety Administration (NHTSA) has an improved biofidelity over the currently available Hybrid III 10-year-old (HIII-10C) Anthropomorphic Test Device (ATD). The LODC design incorporates enhancements to many body region subassemblies, including a redesigned HIII-10C head with pediatric mass properties, and the neck, which produces head lag with Z-axis rotation at the atlanto-occipital joint, replicating the observations made from human specimens. The LODC also features a flexible thoracic spine, a multi-point thoracic deflection measurement system, skeletal anthropometry that simulates a child's sitting posture, and an abdomen that can measure belt loading directly. This study presents the development and validation of a dynamic nonlinear finite element model of the complete LODC dummy. Based on the three-dimensional CAD model, Hypermesh was used to generate a mesh of the finite element (FE) LODC model.

The Test Device for Human Occupant Restraint (THOR) is an advanced crash test dummy designed for frontal impact. Originally released in a 50th percentile male version (THOR-50M), a female 5th version (THOR-05F) was prototyped in 2017 (Wang et al., 2017) and compared with biofidelity sub-system tests (Wang et al., 2018). The same year, Trosseille et al. (2018) published response corridors using nine 5th percentile female Post Mortem Human Subjects (PMHS) tested in three sled configurations, including both submarining and non-submarining cases. The goal of this paper is to provide an initial evaluation of the THOR-05F biofidelity in a full-scale sled test, by comparing its response with the PMHS corridors published by Trosseille et al. (2018). Significant similarities between PMHS and THOR-05F were observed: as in Trosseille et al. (2018), the THOR-05F did not submarine in configuration 1, and submarined in configurations 2 and 3.

During high-speed rear impacts with delta-V > 25 km/h, the front seats may rotate rearward due to occupant and seat momentum change leading to possibly large seat deflection. One possible way of limiting this may be by introducing a structure that would restrict large rotations or deformations, however, such a structure would change the front seat occupant kinematics and kinetics. The goal of this study was to understand the influence of seat back restriction on head, neck and torso responses of front seat occupants when subjected to a moderate speed rear-impact. This was done by simulating a rear impact scenario with a delta-V of 37.4 km/h using LS-Dyna, with the GHBMC M50 occupant model and a manufacturer provided seat model. The study included two parts, the first part was to identify worst case scenarios using the simplified GHBMC M50-OS, and the second part was to further investigate the identified scenarios using the detailed GHBMC M50-O.

Roundabout is a unique approach of managing traffic at intersections because it relies on driver’s instincts of safety. Roundabouts are considered safer than other ways of intersection traffic management due to low speed limits, smoother merging, and reduced fatal accidents. Despite their benefits and increasing usage, there is lack of clear understanding of the roundabouts, particularly due to scarcity of data and simulation models and the complexity of the structure. Real-time and offline traffic data recorded at a roundabout provides a basis for 1) identification of the safety issues, 2) understanding unexpected and risky driver behavior, 3) proposing potential mobility solutions, and 4) developing simulation models. The processed data may be used in controlling metered roundabouts, communicating with connected and automated vehicles (CAVs) etc. In this paper an approach to obtain useful traffic information from video feed data at a roundabout is presented.

This study is focused on exploring the possibilities of using camera and route planner images for autonomous driving in an end-to-mid learning fashion. The overall idea is to clone the humans’ driving behavior, in particular, their use of vision for ‘driving’ and map for ‘navigating’. The notion is that we humans use our vision to ‘drive’ and sometimes, we also use a map such as Google/Apple maps to find direction in order to ‘navigate’. We replicated this notion by using end-to-mid imitation learning. In particular, we imitated human driving behavior by using camera and route planner images for predicting the desired waypoints and by using a dedicated control to follow those predicted waypoints. Besides, this work also places emphasis on using minimal and cheaper sensors such as camera and basic map for autonomous driving rather than expensive sensors such Lidar or HD Maps as we humans do not use such sophisticated sensors for driving.

The assessment of fuel economy of new vehicles is typically based on regulatory driving cycles, measured in an emissions lab. Although the regulations built around these standardized cycles have strongly contributed to improved fuel efficiency, they are unable to cover the envelope of operating and environmental conditions the vehicle will be subject to when driving in the “real-world”. This discrepancy becomes even more dramatic with the introduction of Connectivity and Automation, which allows for information on future route and traffic conditions to be available to the vehicle and powertrain control system. Furthermore, the huge variability of external conditions, such as vehicle load or driver behavior, can significantly affect the fuel economy on a given route. Such variability poses significant challenges when attempting to compare the performance and fuel economy of different powertrain technologies, vehicle dynamics and powertrain control methods.

Several studies, available in the literature, were conducted to establish the most relevant criterion for predicting the thoracic injury risk on the THOR dummy. The criteria, such as the maximum deflection or a combination of parameters including the difference between the chest right and left deflections, were all developed based on given samples of Post Mortem Human Subject (PMHS). However, they were not validated against independent data and they are not always consistent with the observations from field data analysis. For this reason, 8 additional PMHS and matching THOR tests were carried out to assess the ability of the criteria to predict risks. Accident investigations showed that a reduction of the belt loads reduces the risk of rib fractures. Two configurations with different levels of force limitation were therefore chosen. A configuration representing an average European vehicle was chosen as a reference.

The Elderly Female Dummy (EFD) is an omni-directional ATD developed to represent a vulnerable population. The EFD it is able to be 3D printed and quickly altered to meet design requirements. A recent side impact sled test series suggested that small, elderly females may be at risk of thoracic injuries in side impact crashes due to combined loading from the belt pre-tensioner and side airbag. The EFD was altered to add four IR-TRACCs to the thoracic region to allow both x-axis and y-axis displacement to be evaluated in a similar test. While the IR-TRACCs did record the displacement due to combined loading, the rate of displacement and timing of the peak displacements did not match external chestband outputs. The next step for the EFD is to revise the locations of IRTRACCs in the thorax and begin component testing in lateral and frontal directions to improve thoracic biofidelity.

In the last decade, extensive efforts have been made to understand the physics of submarining and its consequences in terms of abdominal injuries. For that purpose, 27 Post Mortem Human Subject (PMHS) tests were performed in well controlled conditions on a sled and response corridors were provided to assess the biofidelity of dummies or human body models. All these efforts were based on the 50th percentile male. In parallel, efforts were initiated to transfer the understanding of submarining and the prediction criteria to the THOR dummies. Both the biofidelity targets and the criteria were scaled down from the 50th percentile male to the 5th percentile THOR female. The objective of this project was to run a set of reference PMHS tests in order to check the biofidelity of the THOR F05 in terms of submarining. Three series of tests were performed on nine PMHS, the first one was designed to avoid submarining, the second and third ones were designed to result in submarining.

This study aims to provide a set of reference post-mortem human subject tests which can be used, with easily reproducible test conditions, for developing and/or validating pedestrian dummies and computational human body models against a road vehicle. An adjustable generic buck was first developed to represent vehicle front-ends. It was composed of four components: two steel cylindrical tubes screwed on rigid supports in V-form represent the bumper and spoiler respectively, a quarter of a steel cylindrical tube represents the bonnet leading edge, and a steel plate represents the bonnet. These components were positioned differently to represent three types of vehicle profile: a sedan, a SUV and a van. Eleven post-mortem human subjects were then impacted laterally in a mid-gait stance by the bucks at 40 km/h: three tests with the sedan, five with the SUV, and three with the van.

The rapid development of driver assistance systems, such as lane-departure warning (LDW) and lane-keeping support (LKS), along with widely publicized reports of automated vehicle testing, have created the expectation for an increasing amount of vehicle automation in the near future. As these systems are being phased in, the coexistence of automated vehicles and human-driven vehicles on roadways will be inevitable and necessary. In order to develop automated vehicles that integrate well with those that are operated in traditional ways, an appropriate understanding of human driver behavior in normal traffic situations would be beneficial. Unlike many research studies that have focused on collision-avoidance maneuvering, this paper analyzes the behavior of human drivers in response to cut-in vehicles moving at similar speeds. Both automated and human-driven vehicles are likely to encounter this scenario in daily highway driving.

Past studies have found that a pressure based injury risk function was the best predictor of liver injuries due to blunt impacts. In an effort to expand upon these findings, this study investigated the biomechanical responses of the abdomen of post mortem human surrogates (PMHS) to high-speed seatbelt loading and developed external response targets in conjunction with proposing an abdominal injury criterion. A total of seven unembalmed PMHS, with an average mass and stature of 71 kg and 174 cm respectively were subjected to belt loading using a seatbelt pull mechanism, with the PMHS seated upright in a free-back configuration. A pneumatic piston pulled a seatbelt into the abdomen at the level of the umbilicus with a nominal peak penetration speed of 4.0 m/s. Pressure transducers were placed in the re-pressurized abdominal vasculature, including the inferior vena cava (IVC) and abdominal aorta, to measure internal pressure variation during the event.

The aim of this study was to investigate the sacroiliac joint injury mechanism. Two test configurations were selected from full scale car crashes conducted with the WorldSID 50th dummy resulting in high sacroiliac joint loads and low pubic symphysis force, i.e. severe conditions for the sacroiliac joint. The two test conditions were reproduced in laboratory using a 150-155 kg guided probe propelled respectively at 8 m/s and 7.5 m/s and with different shapes and orientations for the plate impacting the pelvis. Nine Post Mortem Human Subject (PMHS) were tested in each of the two configurations (eighteen PMHS in total). In order to get information on the time of fracture, eleven strain gauges were glued on the pelvic bone of each PMHS. Results - In the first configuration, five PMHS out of nine sustained AIS2+ pelvic injuries. All five presented sacroiliac joint injuries associated with pubic area injuries.

Injury Risk Curves are developed from cadaver data for sternal deflections produced by anterior, distributed chest loads for a 25, 45, 55, 65 and 75 year-old Small Female, Mid-Size Male and Large Male based on the variations of bone strengths with age. These curves show that the risk of AIS ≥ 3 thoracic injury increases with the age of the person. This observation is consistent with NASS data of frontal accidents which shows that older unbelted drivers have a higher risk of AIS ≥ 3 chest injury than younger drivers.

When the Hybrid III 10-year old (HIII-10C) anthropomorphic test device (ATD) was adopted into Code of Federal Regulations (CFR) 49 Part 572 as the best available tool for evaluating large belt-positioning booster seats in Federal Motor Vehicle Safety Standard (FMVSS) No. 213, NHTSA stated that research activities would continue to improve the performance of the HIII-10C to address biofidelity concerns. A significant part of this effort has been NHTSA’s in-house development of the Large Omnidirectional Child (LODC) ATD. This prototype ATD is comprised of (1) a head with pediatric mass properties, (2) a neck that produces head lag with Z-axis rotation at the atlanto-occipital joint, (3) a flexible thoracic spine, (4) multi-point thoracic deflection measurement capability, (5) skeletal anthropometry representative of a seated child, and (6) an abdomen that can directly measure belt loading.

Despite the increasing knowledge of the thorax mechanics, the effects of inter-individual differences on the mechanical response are difficult to take into account. Several methods are available in the literature to refine the biofidelity corridors or to extrapolate them to other populations (eg: children, small females, large males). Because of the lack of concrete cases, the relevance of the assumptions is rarely investigated. In 2014, Baudrit et al. published data on thorax dynamic responses of small female and midsize male Post Mortem Human Subjects in side and forward oblique impact tests. The impactor mass was 23.4 kg for all the tests and the nominal impact speed was 4.3 m/s. The diameter of the rigid disk was 130 and 152 mm respectively for the small female specimens and for the midsize male specimens. The authors found that the maximum impact force was a function of the total body mass for each loading.

High-speed biplane x-ray was used to research the kinematics of the small intestine in response to seatbelt loading. Six driver-side 3-point seatbelt simulations were conducted with the lap belt routed superior to the pelvis of six unembalmed human cadavers. Testing was conducted with each cadaver perfused, ventilated, and positioned in a fixed-back configuration with the spine angled 30° from the vertical axis. Four tests were conducted with the cadavers in an inverted position, and two tests were conducted with the cadavers upright. The jejunum was instrumented with radiopaque markers using a minimally-invasive, intraluminal approach without inducing preparation-related damage to the small intestine. Tests were conducted at a target peak lap belt speed of 3 m/s, resulting in peak lap belt loads ranging from 5.4-7.9 kN. Displacement of the radiopaque markers was recorded using high-speed x-ray from two perspectives.