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The goal of this study was to gather and compare kinematic response and injury data on both female and male whole-body Post-mortem Human Surrogates (PMHS) responses to Underbody Blast (UBB) loading. Midsized males (50th percentile, MM) have historically been most used in biomechanical testing and were the focus of the Warrior Injury Assessment Manikin (WIAMan) program, thus this population subgroup was selected to be the baseline for female comparison. Both small female (5th percentile, SF) and large female (75th percentile, LF) PMHS were included in the test series to attempt to discern whether differences between male and female responses were predominantly driven by sex or size. Eleven tests, using 20 whole-body PMHS, were conducted by the research team. Preparation of the rig and execution of the tests took place at the Aberdeen Proving Grounds (APG) in Aberdeen, MD. Two PMHS were used in each test.

The current approach for new Advanced Driver Assistance System (ADAS) and Connected and Automated Driving (CAD) function development involves a significant amount of public road testing which is inefficient due to the number miles that need to be driven for rare and extreme events to take place, thereby being very costly also, and unsafe as the rest of the road users become involuntary test subjects. A new development, evaluation and demonstration method for safe, efficient, and repeatable development, demonstration and evaluation of ADAS and CAD functions called Vehicle-in-Virtual –Environment (VVE) was recently introduced as a solution to this problem. The vehicle is operated in a large, empty, and flat area during VVE while its localization and perception sensor data is fed from the virtual environment with other traffic and rare and extreme events being generated as needed.

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.

The advent of Vehicle-to-Everything (V2X) communication has revolutionized the automotive industry, particularly with the rise of Advanced Driver Assistance Systems (ADAS). V2X enables vehicles to communicate not only with each other (V2V) but also with infrastructure (V2I) and pedestrians (V2P), enhancing road safety and efficiency. ADAS, which includes features like adaptive cruise control and automatic intersection navigation, relies on V2X data exchange to make real-time decisions and improve driver assistance capabilities. Over the years, the progress of V2X technology has been marked by standardization efforts, increased deployment, and a growing ecosystem of connected vehicles, paving the way for safer and more efficient automated navigation. The EcoCAR Mobility Challenge was a 4-year student competition among 12 universities across the United States and Canada sponsored by the U.S.

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.

Load legs on child restraint systems (CRS) protect pediatric occupants by bracing the CRS against the floor of the vehicle. Load legs reduce forward motion and help manage the energy of the CRS during a crash. As more CRS manufacturers in the United States (US) consider incorporating these safety features into their products, benchmark data are needed to guide their design and usage. The objective of this study is to develop benchmark geometrical data from both CRS and vehicle environments to help manufacturers to incorporate compatible load legs into the US market. A sample of vehicle environments (n=104 seating positions from n=51 vehicles, model years 2015 to 2022) and CRS with load legs (n=10) were surveyed. Relevant measurements were taken from each sample set to compile benchmark datasets. Corresponding dimensions were compared to assess where incompatibilities might occur.

Recent advancements towards autonomous heavy-duty vehicles are directly associated with increased interconnectivity and software driven features. Consequently, rise of this technological trend is bringing forth safety and cybersecurity challenges in form of new threats, hazards and vulnerabilities. As per the recent UN vehicle regulation 155, several risk-based security models and assessment frameworks have been proposed to counter the growing cybersecurity issues, however, the high budgetary cost to develop the tool and train personnel along with high risk of leakage of trade secrets, hinders the automotive manufacturers from adapting these third party solutions. This paper proposes an automated Threat Assessment & Risk Analysis (TARA) framework aligned with the standard requirements, offering an easy to use and fully customizable framework. The proposed framework is tailored specifically for heavy-duty vehicular networks and it demonstrates its effectiveness on a case study.

Emissions and fuel economy certification testing for vehicles is carried out on a chassis dynamometer using standard test procedures. The vehicle coastdown method (SAE J2263) used to experimentally measure the road load of a vehicle for certification testing is a time-consuming procedure considering the high number of distinct variants of a vehicle family produced by an automaker today. Moreover, test-to-test repeatability is compromised by environmental conditions: wind, pressure, temperature, track surface condition, etc., while vehicle shape, driveline type, transmission type, etc. are some factors that lead to vehicle-to-vehicle variation. Controlled lab tests are employed to determine individual road load components: tire rolling resistance (SAE J2452), aerodynamic drag (wind tunnels), and driveline parasitic loss (dynamometer in a driveline friction measurement lab). These individual components are added to obtain a road load model to be applied on a chassis dynamometer.

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.

With the advent of increasing autonomous vehicles on public roads, the safety of vulnerable road users such as pedestrians, cyclists, etc. has never been more important. These especially include Blind or Visually Impaired (BVI) pedestrians who face difficulty in making confident decisions in road crossings without the help of accessible pedestrian signals (APS). This paper addresses some of the safety measures that can be taken to improve and assess the safety of BVI pedestrians in a controlled environment like a BVI school campus where autonomous vehicles are operated. The majority of research on autonomous vehicle safety does not consider the edge cases of encounters with BVI pedestrians. Based on this motivation, requirements and characteristics of Non-BVI and BVI pedestrians have been stated along with the motion models used to predict their future movements. Existing tools based on Bayesian multi-model filters were used for pedestrian tracking and motion predictions.

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.

Automated driving systems (ADS) are one of the key modern technologies that are changing the way we perceive mobility and transportation. In addition to providing significant access to mobility, they can also be useful in decreasing the number of road accidents. For these benefits to be realized, candidate ADS need to be proven as safe, robust, and reliable; both by design and in the performance of navigating their operational design domain (ODD). This paper proposes a multi-pronged approach to evaluate the safety performance of a hypothetical candidate system. Safety performance is assessed through using a set of test cases/scenarios that provide substantial coverage of those potentially encountered in an ODD. This systematic process is used to create a library of scenarios, specific to a defined domain. Beginning with a system-specific ODD definition, a set of core competencies are identified.

Having connectivity among ground vehicles brings about benefits in fuel economy improvement, traffic mobility enhancement and undesired emission reductions. On the other hand, Unmanned Aerial Vehicles (UAV) have proven to help in getting aerial data to end users in an affordable manner. When UAVs are equipped with cameras, they can get information about the terrain they are flying over. Moreover, using Vehicle-to-Everything (V2X) communication technologies, it is possible to form a communication link between UAVs and the connected ground vehicle networks comprising of Connected and Autonomous vehicles (CAVs). To investigate and exploit the potential benefits and use cases of a broad vehicle network, a microscopic traffic simulator modified previously by our group with the addition of nearby UAVs is used to integrate simulated Connected UAVs flying above a realistic simulation of heterogeneous traffic flow containing both CAVs and non-CAVs.

A key enabler to maximizing the benefits from advanced powertrain technologies is to adopt a systems integration approach and develop optimized controls that consider the propulsion system and vehicle as a whole. This approach becomes essential when incorporating Advanced Driver Assistance Systems (ADAS) and communication technologies, which can provide information on future driving conditions. This may enable the powertrain control system to further improve the vehicle performance and energy efficiency, shifting from an instantaneous optimization of energy consumption to a predictive and “look-ahead” optimization. Benefits from this approach can be realized at all levels of electrification, from conventional combustion engines to hybrid propulsion systems and full electric vehicles, and at all levels of vehicle automation.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

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.

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.

Posterior cruciate ligament (PCL) injuries, although rarely life threatening, affect the quality of life of the person who sustains the injury. The PCL is the primary restraint to posterior tibial translation and can be injured when the tibia moves posteriorly relative to the femur. This type of injury is common in frontal crashes where the tibia may impact the dashboard or steering column. To quantify what happens during dynamic loading of the tibial plateau, isolated cadaveric lower limbs (n = 14) were impacted at dynamic rates with a linear pneumatic ram. During the testing, a static load was applied to the quadriceps tendon to simulate active musculature. Forces as well as the stretch of the PCL were measured. The most common injuries were tibia fractures and PCL tears. The stiffness for the tests at impact velocities of 1.4 and 2.9 m/s were on average 120 N/mm and 141N/mm, respectively. A trend towards increasing femur force with increasing velocity was found.

Prediction of power efficiency of gear boxes has become an increasingly important research topic since fuel economy requirements for passenger vehicles are more stringent, due to not only fuel cost but also environmental regulations. Under this circumstance, the automotive industry is dedicatedly focusing on developing a highly efficient gear box. Thus, the analysis of power efficiency of gear box should be performed to have a transmission that is highly efficient as much as possible at the beginning of design stage. In this study, a program is developed to analyze the efficiency of an entire gearbox, considering all components’ losses such as gear mesh, wet clutches, bearings, oil pump and so on. The analytical models are based on the formulations of each component power loss model which has been developed and published in many existing papers. The program includes power flow analysis of both a parallel gear-train and a planetary gear-train.

It has been discussed in numerous prior studies that in-neutral coasting, or sailing, can accomplish considerable amount of fuel saving when properly used. The driving maneuver basically makes the vehicle sail in neutral gear when propulsion is unnecessary. By disengaging a clutch or shifting the gear to neutral, the vehicle may better utilize its kinetic energy by avoiding dragging from the engine side. This strategy has been carried over to series production recently in some of the vehicles on the market and has become one of the eco-mode features available in current vehicles. However, the duration of coasting must be long enough to attain more fuel economy benefit than Deceleration Fuel Cut-Off (DFCO) - which exists in all current vehicle powertrain controllers - can bring. Also, the transients during shifting back to drive gear can result in a drivability concern.