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With the development of vehicles equipped with automated driving systems, the need for systematic evaluation of AV performance has grown increasingly imperative. According to ISO 34502, one of the safety test objectives is to learn the minimum performance levels required for diverse scenarios. To address this need, this paper combines two essential methodologies - scenario-based testing procedures and scoring systems - to systematically evaluate the behavioral competence of AVs. In this study, we conduct comprehensive testing across diverse scenarios within a simulator environment following Mcity AV Driver Licensing Test procedure. These scenarios span several common real-world driving situations, including BV Cut-in, BV Lane Departure into VUT Path from Opposite Direction, BV Left Turn Across VUT Path, and BV Right Turn into VUT Path scenarios.

Automated vehicles, in the form we see today, started off-road. Ideas, technologies, and engineers came from agriculture, aerospace, and other off-road domains. While there are cases when only on-road experience will provide the necessary learning to advance automated driving systems, there is much relevant activity in off-road domains that receives less attention. Implications of Off-road Automation for On-road Automated Driving Systems argues that one way to accelerate on-road ADS development is to look at similar experiences off-road. There are plenty of people who see this connection, but there is no formalized system for exchanging knowledge. Click here to access the full SAE EDGETM Research Report portfolio.

Making manned and remotely-controlled wheeled and tracked vehicles easier to drive, especially off-road, is of great interest to the U.S. Army. If vehicles are easier to drive (especially closed hatch) or if they are driven autonomously, then drivers could perform additional tasks (e.g., operating weapons or communication systems), leading to reduced crew sizes. Further, poorly driven vehicles are more likely to get stuck, roll over, or encounter mines or improvised explosive devices, whereby the vehicle can no longer perform its mission and crew member safety is jeopardized. HMI technology and systems to support human drivers (e.g., autonomous driving systems, in-vehicle monitors or head-mounted displays, various control devices (including game controllers), navigation and route-planning systems) need to be evaluated, which traditionally occurs in mission-specific (and incomparable) evaluations.

Engaging in visual-manual tasks such as selecting a radio station, adjusting the interior temperature, or setting an automation function can be distracting to drivers. Additionally, if setting the automation fails, driver takeover can be delayed. Traditionally, assessing the usability of driver interfaces and determining if they are unacceptably distracting (per the NHTSA driver distraction guidelines and SAE J2364) involves human subject testing, which is expensive and time-consuming. However, most vehicle engineering decisions are based on computational analyses, such as the task time predictions in SAE J2365. Unfortunately, J2365 was developed before touch screens were common in motor vehicles.

Knee airbags (KABs) are one countermeasure in newer vehicles that could influence lower extremity (LEX) injury, the most frequently injured body region in frontal crashes. To determine the effect of KABs on LEX injury for drivers in frontal crashes, the analysis examined moderate or greater LEX injury (AIS 2+) in two datasets. Logistic regression considered six main effect factors (KAB deployment, BMI, age, sex, belt status, driver compartment intrusion). Eighty-five cases with KAB deployment from the Crash Injury Research and Engineering Network (CIREN) database were supplemented with 8 cases from the International Center for Automotive Medicine (ICAM) database and compared to 289 CIREN non-KAB cases. All cases evaluated drivers in frontal impacts (11 to 1 o’clock Principal Direction of Force) with known belt use in 2004 and newer model year vehicles. Results of the CIREN/ICAM dataset were compared to analysis of a similar dataset from NASS-CDS (5441 total cases, 418 KAB-deployed).

Exhaust Gas Recirculation (EGR) coolers are commonly used in on-road and off-road diesel engines to reduce the recirculated gas temperature in order to reduce NOx emissions. One of the common performance behaviors for EGR coolers in use on diesel engines is a reduction of the heat exchanger effectiveness, mainly due to particulate matter (PM) deposition and condensation of hydrocarbons (HC) from the diesel exhaust on the inside walls of the EGR cooler. According to previous studies, typically, the effectiveness decreases rapidly initially, then asymptotically stabilizes over time. Prior work has postulated a deposit removal mechanism to explain this stabilization phenomenon. In the present study, five field aged EGR cooler samples that were used on construction machines for over 10,000 hours were analyzed in order to understand the deposit structure as well as the deposit composition after long duration use.

Little information is available on passenger preferences for posture and support in highly reclined seat configurations. To address this gap, a laboratory study was conducted with 24 adult passengers at seat back angles from 23 to 53 degrees. Passenger preferences for head and neck posture with and without head support were recorded. This paper presents the characteristics of the passengers’ preferred head support with respect to thorax, head, and neck posture.

Motion sickness in road vehicles may become an increasingly important problem as automation transforms drivers into passengers. The University of Michigan Transportation Research Institute has developed a vehicle-based platform to study motion sickness in passenger vehicles. A test-track study was conducted with 52 participants who reported susceptibility to motion sickness. The participants completed in-vehicle testing on a 20-minute scripted, continuous drive that consisted of a series of frequent 90-degree turns, braking, and lane changes at the U-M Mcity facility. In addition to quantifying their level of motion sickness on a numerical scale, participants were asked to describe in words any motion-sickness-related sensations they experienced.

Crash safety researchers have an increased concern regarding the decreased thoracic deflection and the contributing injury causation factors among the elderly population. Sternum fractures are categorized as moderate severity injuries, but can have long term effects depending on the fragility and frailty of the occupant. Current research has provided detail on rib morphology, but very little information on sternum morphology, sternum fracture locations, and mechanisms of injury. The objective of this study is two-fold (1) quantify sternum morphology and (2) document sternum fracture locations using computed tomography (CT) scans and crash data. Thoracic CT scans from the University of Michigan Hospital database were used to measure thoracic depth, manubriosternal joint, sternum thickness and bone density. The sternum fracture locations and descriptions were extracted from 63 International Center for Automotive Medicine (ICAM) crash cases, of which 22 cases had corresponding CT scans.

This paper presents a simple method of using Voronoi partitions for estimating vehicle fuel economy from a limited set of engine operating conditions. While one of the overarching goals of engine research is to continually improve vehicle fuel economy, evaluating the impact of a change in engine operating efficiency on the resulting fuel economy is a non-trivial task and typically requires drive cycle simulations with experimental data or engine model predictions and a full suite of engine controllers over a wide range of engine speeds and loads. To avoid the cost of collecting such extensive data, proprietary methods exist to estimate fuel economy from a limited set of engine operating conditions. This study demonstrates the use of Voronoi partitions to cluster and quantize the fuel consumed along a complex trajectory in speed and load to generate fuel consumption estimates based on limited simulation or experimental results.

The purpose of this study was to use detailed medical information to evaluate thoracic injuries in elderly patients in real world frontal crashes. In this study, we used analytic morphomics to predict the effect of torso geometry on rib fracture, a major source of injury for the elderly. Analytic morphomics extracts body features from computed tomography (CT) scans of patients in a semi-automated fashion. Thoracic injuries were examined in front row occupants involved in frontal crashes from the International Center for Automotive Medicine (ICAM) database. Among these occupants, two age groups (age < 60 yr. [Nonelderly] and age ≥ 60 yr. [Elderly]) who suffered severe thoracic injury were analyzed. Regression analyses were conducted to investigate injury outcomes using variables for vehicle, demographics, and morphomics. Compared to the nonelderly group, the elderly group sustained more rib fractures.

Analyzing dynamic postures of vehicle occupants in various situations is valuable for improving occupant accommodation and safety. Accurate tracking of an occupant’s head is of particular importance because the head has a large range of motion, controls gaze, and may require special protection in dynamic events including crashes. Previous vehicle occupant posture studies have primarily used marker-based optical motion capture systems or multiple video cameras for tracking facial features or markers on the head. However, the former approach has limitations for collecting on-road data, and the latter is limited by requiring intensive manual postprocessing to obtain suitable accuracy. This paper presents an automated on-road head tracking method using a single Microsoft Kinect V2 sensor, which uses a time-of-flight measurement principle to obtain a 3D point cloud representing objects in the scene at approximately 30 Hz.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

Recent field data have shown that the occupant protection in vehicle rear seats failed to keep pace with advances in the front seats likely due to the lack of advanced safety technologies. The objective of this study was to optimize advanced restraint systems for protecting rear seat occupants with a range of body sizes under different frontal crash pulses. Three series of sled tests (baseline tests, advanced restraint trial tests, and final tests), MADYMO model validations against a subset of the sled tests, and design optimizations using the validated models were conducted to investigate rear seat occupant protection with 4 Anthropomorphic Test Devices (ATDs) and 2 crash pulses.

This study evaluated the ISO 5353 Seat Index Point Tool (SIPT) as an alternative to the SAE J826 H-point manikin for measuring military seats. A tool was fabricated based on the ISO specification and a custom back-angle measurement probe was designed and fitted to the SIPT. Comparisons between the two tools in a wide range of seating conditions showed that the mean SIP location was 5 mm aft of the H-point, with a standard deviation of 7.8 mm. Vertical location was not significantly different between the two tools (mean - 0.7 mm, sd 4.0 mm). A high correlation (r=0.9) was observed between the back angle measurements from the two tools. The SIPT was slightly more repeatable across installations and installers than the J826 manikin, with most of the discrepancy arising from situations with flat seat cushion angles and either unusually upright or reclined back angles that caused the J826 manikin to be unstable.

Automotive seats are commonly described by one-dimensional measurements, including those documented in SAE J2732. However, 1-D measurements provide minimal information on seat shape. The goal of this work was to develop a statistical framework to analyze and model the surface shapes of seats by using techniques similar to those that have been used for modeling human body shapes. The 3-D contour of twelve driver seats of a pickup truck and sedans were scanned and aligned, and 408 landmarks were identified using a semi-automatic process. A template mesh of 18,306 vertices was morphed to match the scan at the landmark positions, and the remaining nodes were automatically adjusted to match the scanned surface. A principal component (PC) analysis was performed on the resulting homologous meshes. Each seat was uniquely represented by a set of PC scores; 10 PC scores explained 95% of the total variance. This new shape description has many applications.

Law enforcement officers (LEO) make extensive use of vehicles to perform their jobs, often spending large portions of a shift behind the wheel. Few LEO vehicles are purpose-built; the vast majority are modified civilian vehicles. Data from the field indicate that LEO suffer from relatively high levels musculoskeletal injury that may be due in part to poor accommodation provided by their vehicles. LEO are also exposed to elevated crash injury risk, which may be exacerbated by a compromise in the performance of the occupant restraint systems due to body-borne equipment. A pilot study was conducted to demonstrate the application of three-dimensional anthropometric scanning and measurement technology to address critical concerns related to vehicle design. Detailed posture and belt fit data were gathered from five law enforcement officers as they sat in the patrol vehicles that they regularly used and in a mockup of a mid-sized vehicle.

Model Predictive Control (MPC) design methods are becoming popular among automotive control researchers because they explicitly address an important challenge faced by today’s control designers: How does one realize the full performance potential of complex multi-input, multi-output automotive systems while satisfying critical output, state and actuator constraints? Nonlinear MPC (NMPC) offers the potential to further improve performance and streamline the development for those systems in which the dynamics are strongly nonlinear. These benefits are achieved in the MPC framework by using an on-line model of the controlled system to generate the control sequence that is the solution of a constrained optimization problem over a receding horizon.

The objective of this study is to develop a method that uses a combination of field data analysis, naturalistic driving data analysis, and computational simulations to explore the potential injury reduction capabilities of integrating passive and active safety systems in frontal impact conditions. For the purposes of this study, the active safety system is actually a driver assist (DA) feature that has the potential to reduce delta-V prior to a crash, in frontal or other crash scenarios. A field data analysis was first conducted to estimate the delta-V distribution change based on an assumption of 20% crash avoidance resulting from a pre-crash braking DA feature. Analysis of changes in driver head location during 470 hard braking events in a naturalistic driving study found that drivers’ head positions were mostly in the center position before the braking onset, while the percentage of time drivers leaning forward or backward increased significantly after the braking onset.

The aging population is a growing concern as the increased fragility and frailty of the elderly results in an elevated incidence of injury as well as an increased risk of mortality and morbidity. To assess elderly injury risk, age-specific computational models can be developed to directly calculate biomechanical metrics for injury. The first objective was to develop an older occupant Global Human Body Models Consortium (GHBMC) average male model (M50) representative of a 65 year old (YO) and to perform regional validation tests to investigate predicted fractures and injury severity with age. Development of the GHBMC M50 65 YO model involved implementing geometric, cortical thickness, and material property changes with age. Regional validation tests included a chest impact, a lateral impact, a shoulder impact, a thoracoabdominal impact, an abdominal bar impact, a pelvic impact, and a lateral sled test.