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The Advanced Driver Assistance System (ADAS) is a comprehensive feature set designed to aid a driver in avoiding or reducing the severity of collisions while operating the vehicle within specified conditions. In General Motors (GM) vehicles, the primary controller for the ADAS is the Active Safety Control Module (ASCM). In the 2013 model year, GM introduced an ASCM utilizing the GM internal nomenclature of External Object Calculation Module (EOCM) in some of their vehicles produced for the North American market. Similar to the Sensing and Diagnostic Module (SDM) utilized in the restraints system, the EOCM3 LC contains an Event Data Recorder (EDR) function to capture and record information surrounding certain ADAS or Supplemental Inflatable Restraint (SIR) events. The ASCM EDR contains information from external object sensors, various chassis and powertrain control modules, and internally calculated data.

While various Advanced Driver Assistance System (ADAS) features have become more prevalent in passenger vehicles, their ability to potentially avoid or mitigate vehicle crashes has limitations. Due to current technological limitations, forward collision mitigation technologies such as Forward Collision Warning (FCW) and Automated Emergency Braking (AEB) lack the ability to consistently perform in many unique and challenging scenarios. These limitations are often outlined in driver manuals for ADAS equipped vehicles. One such scenario is the case of a stationary lead vehicle at the side of the road. This is generally considered to be a challenging scenario for FCW and AEB to address because it can often be difficult for the system to discern this threat accurately and consistently from non-threatening roadway infrastructure without unnecessary or nuisance system activations.

There are established federal requirements and industry standards for frontal crash testing of motor vehicles. Consistently applied methods support reliability, repeatability, and comparability of performance metrics between tests and platforms. However, real world collisions are rarely identical to standard test protocols. This study examined the effects of occupant anthropometry and passive restraint deployment timing on occupant kinematics and biomechanical loading in a moderate-severity (approximately 30 kph delta-V) offset frontal crash scenario. An offset, front-to-rear vehicle-to-vehicle crash test was performed, and the dynamics of the vehicle experiencing the frontal collision were replicated in a series of three sled tests. Crash test and sled test vehicle kinematics were comparable. A standard or reduced-weight 50th percentile male Hybrid III ATD (H3-50M) or a standard 5th percentile female Hybrid III ATD (H3-5F) was belted in the driver’s seating position.

The increased prevalence of larger and more energy-dense battery packs for transportation and grid storage applications has resulted in an increasing number of severe battery thermal events. The implications on product reliability, consumer safety, and the surrounding environment are significant. While there are many potential root causes for battery thermal runaway, these events often start within a single battery cell or group of cells that cascade to neighboring cells and other combustible materials, rapidly increasing the hazard profile of the battery pack as more stored energy is released. Reducing these hazards requires preventing severe thermal runaway scenarios by mitigating cell-to-cell propagation through the improved design of both individual cells and battery packs.

The use of Lithium-ion batteries in the transportation sector has its own unique set of requirements such as high-power demands, cooling challenges, and risk of mechanical failure due to crashes. Active and passive components of thermal management systems in battery-powered products are designed to mitigate the effects of thermal runaway events and prevent cell-to-cell propagation. Designing safe battery-powered systems requires an understanding of how the battery pack will behave while undergoing thermal runaway, including critical data such as total energy yielded, rate of energy generation, as well as venting patterns and directions. Details such as thermal runaway energy fractions associated with the cell casing as well as vent gas and ejecta can be used to inform and optimize battery pack designs and the product as a whole. The NASA Fractional Thermal Runaway Calorimeter (FTRC) was created to measure these values.

Electric vehicles (EVs) and the development around them has been rapid in recent years. As the battery is the most essential component of an electric vehicle, a lot of research and analysis has been focused on ensuring safe and reliable performance of batteries. Considering the location, size, and operating conditions for EV batteries, they must be designed with an in-built safety infrastructure keeping in mind certain realistic scenarios such as fire exposure, mechanical vibration, collisions, over-charging, single cell failures, and others. In this paper, we discuss an overview of various EV battery failure mechanisms, present current safety and abuse testing methods and standards associated with such mechanisms and discuss the need for the development and implementation of additional testing standards to better characterize the safety performance of EV battery packs.

Airbag and seat belt pretensioner deployment characteristics depend on multiple factors, such as the magnitude, direction, and rate of vehicle deceleration as detected by vehicle crash sensors and evaluated by vehicle-specific algorithms. Frontal airbag and pretensioner deployments are likely to be commanded during frontal crash events with high initial vehicle deceleration typically associated with high vehicle change in velocity (delta-V). However, within a range of moderate changes in vehicle speeds, referred to as the “gray zone,” a vehicle-specific algorithm may or may not command deployment depending on crash pulse parameters and occupant sensing, among other items. Publicly available testing in the moderate-speed range is lacking and would be useful to evaluate the effects of airbag and pretensioner deployment on occupant kinematics and loading.

As the automated vehicle (AV) industry continues to progress, it is important to establish the level of operational safety of these vehicles prior to and throughout their deployment on public roads. The Institute of Automated Mobility (IAM) has previously proposed a set of operational safety assessment (OSA) metrics which can be used to quantify the operational safety of vehicles. The OSA metrics provide a starting point to consistently quantify performance, but a framework to interpret the metrics measurements is needed to objectively quantify the overall operational safety for a vehicle in a given scenario. This work aims to present an approach to applying a calculation of the safety envelope component of the OSA metrics to rear-world collisions for use in such an assessment. In this paper, the OSA methodology concept is introduced as a means for quantifying the operational safety of a vehicle.

Field data was analyzed on second-row children in front, side and rear impacts to study fatality trends by model year (MY) and calendar year (CY) with 1980-2020 MY vehicles. The different MY and CY perspectives show changes in rates that are useful for setting priorities for second-row child safety in rear impacts. 1990 to 2019 FARS was queried to assess the number of fatally injured and non-ejected second-row children (0-15 years old) in crashes without fires. The children included outboard occupants seated behind an occupied front seat and center occupants. The data was analyzed for rear, front and side impacts to assess crash frequency. 1990-2015 POLK was queried to assess exposure of registered vehicles and estimate a fatality rate. The FARS and POLK data were sub-grouped by MY of the vehicle and CY of the crash. There were 2.8-times more fatally injured children in frontal crashes than in the rear crashes. The ratio of frontal and rear crashes varied with CY sub-groups.

The risk for severe injury (MAIS 4+F) was determined by crash type, seatbelt use and crash severity (delta V) using 22 years of NASS-CDS from 1994-2015 with all light vehicles and occupants 15+ years old. There were 9 increments of delta V from <16-72+ km/h (<10-45+ mph). Crashes were grouped by the location of damage to the front, near-side, far-side and rear. Injury risk was calculated by dividing the number of severely injured (MAIS 4+F) by the number of exposure (MAIS 0+F) occupants using weighted data. Standard errors were determined. The data and plots provide a national estimate of injury by delta V in front, near-side, far-side and rear impacts based on the multi-year field data in NASS-CDS.

This study was conducted to assess the effects of differing rear impact pulse characteristics on restraint performance, front-seat occupant kinematics, biomechanical responses, and seat yielding. Five rear sled tests were conducted at 40.2 km/h using a modern seat. The sled buck was representative of a generic sport utility vehicle. A 50th percentile Hybrid III ATD was used. The peak accelerations, acceleration profiles and durations were varied. Three of the pulses were selected based on published information and two were modeled to assess the effects of peak acceleration occurring early and later within the pulse duration using a front and rear biased trapezoidal characteristic shape. The seatback angle at maximum rearward deformation varied from 46 to 67 degrees. It was lowest in Pulse 1 which simulates an 80 km/h car-to-car rear impact.

Assessment of the physical evidence on a seat belt restraint system provides one source of data for determining an occupant’s seat belt use or non-use during a motor vehicle crash. The evidence typically associated with loading from a restrained occupant has been extensively researched and documented in the literature. However, evidence of loading to the restraint system can also be generated by other means, including the interaction of an unrestrained occupant with a stowed restraint system. The present study evaluates physical evidence on multiple stowed restraint systems generated via interaction with unrestrained occupants during a full-scale dolly rollover crash test of a large multiple passenger van. Unbelted anthropomorphic test devices (ATDs) were positioned in the driver and right front passenger seats and in all designated seating positions in the third, fourth, and fifth rows.

The biomechanical injury assessment for an occupant in a planar vehicle-to-vehicle collision often requires a kinematic analysis of impact-related occupant motion. This analysis becomes more complex when the collision force is eccentric to the center of gravity on a struck vehicle because the vehicle kinematics include both translation and potentially significant yaw rotational rates. This study examines the significance of vehicle yaw on occupant kinematics in eccentric (off-center) planar collisions. The paper describes the calculation of the instantaneous center of rotation (ICR) in a yawing vehicle post-impact and explores how mapping this quantity may inform an occupant’s trajectory when using a free particle “occupant” analysis. The study initially analyzed the impact-related occupant motion for all the outboard seat positions in a minivan using several hypothetical examples of eccentric vehicle-to-vehicle crash configurations with varying PDOF, delta-V, and yaw rate.

In rear-end collisions, the seatback provides primary occupant restraint during initial rearward motion of the occupant relative to the vehicle interior as the vehicle is accelerated forward by collision forces. When properly used, seat belts contribute to limiting occupant excursion and loading by working in concert with the seatback, as well as managing forward excursion on rebound after rear-end impacts. A lack of data evaluating the role of seat belt restraint component technology in limiting occupant motion and loading during high-severity rear-end impacts has been identified. This knowledge gap is particularly apparent for occupants who are not seated normally, in position, at the time of impact. Previous static pretensioner deployment tests suggest that different combinations of latch plate design and pretensioner deployment strategies might have different effects on occupant restraint.

Vehicle rear structure stiffness has increased as a result of the requirements in the FMVSS 301R, which has also corresponded to an increase in front-row seat strength. This study evaluates the structural behavior and occupant response associated with production-level seats equipped with body-mounted D-rings, and very stiff all-belt-to-seat (ABTS) in a group of 12 deceleration sled tests. A double-haversine pulse with approximately 100-msec duration was used for all tests, with peak accelerations of approximately 19 g for the 40 km/h (25 mph) tests and peak accelerations of 28 g for the 56 km/h (35 mph) test. This generic pulse was designed to represent a severe rear impact crash involving vehicles with stiffer rear structures. The tests compared occupant responses and resulting structural deformation of an original equipment manufacturer (OEM) production-level driver seat from a pickup and a very stiff modified ABTS. Both seating systems were equipped with dual recliners.

The risk for severe injury (MAIS 4+F) was determined by crash type, seatbelt use and crash severity (delta V) using 22 years of NASS-CDS from 1994-2015 with all light vehicles and occupants 15+ years old. There were 9 increments of delta V from <16-72+ km/h (<10-45+ mph). Crashes were grouped by the location of damage to the front, near-side, far-side and rear. Injury risk was calculated by dividing the number of severely injured (MAIS 4+F) by the number of exposure (MAIS 0+F) occupants using weighted data. Standard errors were determined. The data and plots provide a national estimate of injury by delta V in front, near-side, far-side and rear impacts based on the multi-year field data in NASS-CDS.

Prior to developing or modifying the protocol of a performance evaluation test, it is important to identify field relevant conditions. The objective of this study was to assess the distribution of selected crash variables from rear crash field collisions involving modern vehicles. The number of exposed and serious-to-fatally injured non-ejected occupants was determined in 2008+ model year (MY) vehicles using the NASS-CDS and CISS databases. Selected crash variables were assessed for rear crashes, including severity (delta V), impact location, struck vehicle type, and striking objects. In addition, 15 EDRs were collected from 2017 to 2019 CISS cases involving 2008+ MY light vehicles with a rear delta V ranging from 32 to 48 km/h. Ten rear crash tests were also investigated to identify pulse characteristics in rear crashes. The tests included five vehicle-to-vehicle crash tests and five FMVSS 301R barrier tests matching the struck vehicle.

As micromobility devices (i.e., e-bikes, scooters, skateboards, etc.) continue to increase in popularity, there is a growing need to test these devices for varying purposes such as performance assessment, crash reconstruction, and design of new products. Although tests have been conducted across the industry for electric scooters (e-scooters), this paper describes a novel method for crash testing e-scooters with anthropomorphic test devices (ATDs) “riding” them, providing new sources for data collection and research. A sled fixture was designed utilizing a pneumatic crash rail to propel the scooters with an overhead gantry used for stabilization of the ATD until release just prior to impact. The designed test series included impacts with a 5.5-inch curb at varying incidence angles, a stationary vehicle, or a standing pedestrian ATD. Test parameter permutations included changing e-scooter tire sizes, impact speeds, and rider safety equipment.

The average body weight of the US population has increased over time. This study investigates the effect of increasing weight on seat and occupant responses in 15-18 km/h and 42 km/h rear sled tests. The effect of initial occupant posture is also discussed. Seven tests were conducted with lap-shoulder belted ATDs (anthropometric test device) placed on older and modern driver seats. Four tests were conducted with a 50th percentile male Hybrid III, two with 95th percentile male Hybrid III and one with a BioRID. The ATDs were ballasted to represent a Class I or II obese occupant in three tests. The tests were matched by seat model and sled velocity. The effect of occupant weight was assessed in three matches. The results indicated an increase in seatback deflection with increasing occupant weight.

The operational safety of automated driving system (ADS)-equipped vehicles (AVs) must be quantified using well-defined metrics in order to gain an unambiguous understanding of the level of risk associated with AV deployment on public roads. In this research, efforts to evaluate the operational safety assessment (OSA) metrics introduced in prior work by the Institute of Automated Mobility (IAM) are described. An initial validation of the proposed set of OSA metrics involved using the open-source simulation software Car Learning to Act (CARLA) and Scenario Runner, which are used to place a subject vehicle in selected scenarios and obtain measurements for the various relevant OSA metrics. Car following scenarios were selected from the list of 37 pre-crash scenarios identified by the National Highway Traffic Safety Administration (NHTSA) as the most common driving situations that lead to crash events involving two light vehicles.