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In some automotive electrical systems, it is advantageous to use power supplies and loads at two or more voltages. Often it is desirable to retain the single wire power architecture, with the car body providing the return circuit. A major difficulty in achieving this end is the matter of dealing with the possibility of a short circuit between feed wires at different voltages. It can be shown that source-side fuses cannot be relied upon to return the system to a safe state in all cases. Substantial effort was applied to this problem in the early years of the 21st century, but the results were less than completely satisfactory. Using entirely separate cable harnesses for each voltage, with physically separated routing, minimizes the risk of such a short occurring in the harness.

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.

The primary function of an airbag control module is to detect crashes, discriminate and predict if a deployment is necessary, then deploy the restraint systems including airbags and where applicable, pretensioners. At General Motors (GM), the internal term for airbag control module is Sensing and Diagnostic Module (SDM). In the 1994 model year, GM introduced its SDM on some of its North American airbag-equipped vehicles. A secondary function of that SDM and all subsequent SDMs is to record crash related data. This data can include data regarding impact severity from internal accelerometers and pre-crash vehicle data from various chassis and powertrain modules. Previous researchers have addressed the accuracy of both the velocity change data, recorded by the SDM, and the pre-crash data, but the assessment of the timing of the pre-crash data has been limited to a single family of modules (Delphi SDM-G).

The emergence of Plug-in hybrid electric vehicles (PHEVs) and electric vehicles (EVs) as a viable means of transportation has been coincident with the development of lithium-ion (Li-ion) battery technology and electronics. These developments have enabled the storage and use of large amounts of energy that were previously only possible with internal combustion engines. However, the safety aspects of using these large energy storage battery packs are a significant challenge to address. In addition, the rapid advances in electrode and electrolyte materials for Li-Ion batteries have made comparisons and ranking of safety parameters difficult because of the substantial variations in cell designs. In this work, we outline a method for quantifying the thermal safety aspects of Li-ion battery technologies using a Cone Calorimeter.

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 debate surrounding roof deformation and occupant injury potential has existed in the automotive community for over 30 years. In analysis of real-world rollovers, assessment of roof deformation and occupant compartment space starts with the post-accident roof position. Dynamic movement of the roof structure during a rollover sequence is generally acknowledged but quantification of the dynamic roof displacement has been limited. Previous assessment of dynamic roof deformation has been generally limited to review of the video footage from staged rollover events. Rollover testing for the evaluation of injury potential has typically been studied utilizing instrumented test dummies, on-board and off-board cameras, and measurements of residual crush. This study introduces an analysis of previously undocumented real-time data to be considered in the evaluation of the roof structure's dynamic behavior during a rollover event.

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.

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 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.

Fires involving cars, trucks, and other highway vehicles are a common concern for emergency responders. In 2013 alone, there were approximately 188,000 highway vehicle fires. Fire Service personnel are accustomed to responding to conventional vehicle (i.e., internal combustion engine [ICE]) fires, and generally receive training on the hazards associated with those vehicles and their subsystems. However, in light of the recent proliferation of electric drive vehicles (EDVs), a key question for emergency responders is, “what is different with EDVs and what tactical adjustments are required when responding to EDV fires?” The overall goal of this research program was to develop the technical basis for best practices for emergency response procedures for EDV battery incidents, with consideration for suppression methods and agents, personal protective equipment (PPE), and clean-up/overhaul operations.

Safety-critical systems in most modern applications are designed in a way such that they provide a fail-safe operation when a fault occurs, to pose minimum risk to the user. As these systems become more sophisticated with increased functionality, it is important that their design incorporates functional safety concepts which entail detection of a potential harmful condition that prompts a corrective action to prevent hazardous events. In this paper, we discuss the significance of safety-critical systems along with the implementation of fail-safe designs in these systems. We also aim to provide an overview of functional safety as addressed in some of the industry standards and through a case study demonstrate how the concepts can be used when developing a safety-critical system.

The operational safety of automated driving system (ADS)-equipped vehicles (AVs) needs to be quantified for an understanding of risk, requiring the measurement of parameters as they relate to AVs and human driven vehicles alike. In prior work by the Institute of Automated Mobility (IAM), operational safety metrics were introduced as part of an operational safety assessment (OSA) methodology that provide quantification of behavioral safety of AVs and human-driven vehicles as they interact with each other and other road users. To calculate OSA metrics, the data capture system must accurately and precisely determine position, velocity, acceleration, and geometrical relationships between various safety-critical traffic participants. The design of an infrastructure-based system that is intended to capture the data required for calculation of OSA metrics is addressed in this paper.

This study assesses the exposure distribution and injury rate (MAIS 4+F) to front-outboard non-ejected occupants by crash severity, belt use and head restraint type and damage in rear impacts using 1997-2015 NASS-CDS data. Rear crashes with a delta V <24 km/h (15 mph) accounted for 71% of all exposed occupants. The rate of MAIS 4+F increased with delta V and was higher for unbelted than belted occupants with a rate of 11.7% ± 5.2% and 6.0% ± 1.5% respectively in 48+ km/h (30 mph) delta V. Approximately 12% of front-outboard occupants were in seats equipped with an integral head restraint and 86% were with an adjustable head restraint, irrespective of crash severity. The overall injury rate was 0.14% ± 0.05% and 0.22% ± 0.06%, respectively. It was higher in cases where the head restraint was listed as “damaged”. Thirteen cases involving a lap-shoulder belted occupant in a front-outboard seat in which “damage” to the adjustable head restraint was identified.

Lane Departure Warning (LDW) systems, along with other types of Advanced Driver Assistance Systems (ADAS), are becoming more common in passenger vehicles, with the general aim of improving driver safety through automation of various aspects of the driving task. Drivers have generally reported satisfaction with ADAS with the exception of LDW systems, which are often rated poorly or even deactivated by drivers. One potential contributor to this negative response may be an increase in the cognitive load associated with lane-keeping when LDW is in use. The present study sought to examine the relationship between LDW, lane-keeping behavior, and concurrent cognitive load, as measured by performance on a secondary task. Participants drove a vehicle equipped with LDW in a demarcated lane on a closed-course test track with and without the LDW system in use over multiple sessions.

Micro-mobility is a fast-growing trend in the transportation industry with stand-up electric scooters (e-scooters) becoming increasingly popular in the United States. To date, there are over 350 ride-share e-scooter programs in the United States. As this popularity increases, so does the need to understand the performance capabilities of these vehicles and the associated operator kinematics. Scooter tip-over stability is characterized by the scooter geometry and controls and is maintained through operator inputs such as body position, interaction with the handlebars, and foot placement. In this study, testing was conducted using operators of varying sizes to document the capabilities and limitations of these e-scooters being introduced into the traffic ecosystem. A test course was designed to simulate an urban environment including sidewalk and on-road sections requiring common maneuvers (e.g., turning, stopping points, etc.) for repeatable, controlled data collection.

This study reports pedal activation forces and typical acceleration and deceleration rates during everyday driving activities. Twenty subjects of varying ages, height and weight participated in the study. Each subject was asked to drive a four-door sedan along 2.3 miles of roadway in DuPage County, Illinois. Vehicle speed, acceleration, and position were measured using a global positioning system that was synchronized with force data collected from load cells rigidly mounted on the vehicle's accelerator and brake pedals. Pedal forces and vehicle behavior were measured during common driving tasks such as, shifting the transmission into reverse, backing out of a parking spot, and, making a right hand turn from a stop sign. Our data suggests that simple vehicle dynamic tasks produced in experimental settings may not reliably reproduce vehicle and occupant behavior.

A significant portion of real-world passenger vehicle side impacts occur at lower speeds than testing conducted by the National Highway Traffic Safety Administration (NHTSA) or the Insurance Institute for Highway Safety (IIHS). Test data from low- to moderate-speed side impacts involving late-model passenger vehicles is limited, making the evaluation of vehicle impact response, occupant loading, and injury potential challenging. This study provides the results of low- to moderate-speed impact testing involving a late-model mid-size sedan. Two full-scale Non-Deformable Moving Barrier (NDMB) side impact crash tests were conducted at speeds of 6.2 mph (10.0 kph) and 13.4 mph (21.6 kph). Instrumentation on the late-model sedan used for the test series included tri-axis accelerometers and seat belt load cells.

A significant number of vehicle-to-vehicle collisions involve front-to-rear impacts at low- to moderate-speeds. While a variety of studies have been conducted since the 1990s involving fore-aft collisions, those discussing the response of late model passenger vehicles during progressively more severe impacts are limited. In this study, four inline, front-rear tests were conducted using two midsize sedans of the same make, model, and year. An instrumented Hybrid III 50th percentile-male Anthropomorphic Test Device (ATD) was located in the driver seat of each sedan and was restrained using the standard three-point seat belt system. Instrumentation on the vehicles included tri-axis accelerometers and seat belt load cells. For each test, the centerlines of the vehicles were aligned, and the striking vehicle impacted the stationary target vehicle at closing speeds of 4.6, 7.9, 13.5, and 20.9 mph (7.4, 12.7, 21.7, and 33.6 kph).

As lithium-ion cells and systems become larger and more ubiquitous in automotive applications, fire and explosion hazards that are rare or non-existent in smaller systems may exist in these larger systems. One potential hazard can occur when flammable gases emitted from a lithium-ion cell failure accumulate in or around automobiles and are ignited by electrical activity or by the cells themselves and result in a fire or explosion. In some instances, the safety aspects related to fires and explosions protection of electric vehicles and hybrid vehicles using these large energy storage battery packs are a significant challenge to address. This paper describes and characterizes the combustion and explosion hazards that can occur when a lithium ion battery pack fails and goes into thermal runaway in an enclosed space. Metrics such as gas composition, maximum overpressure, rate of pressure rise, and flammability limits are described.

As the deployment of automated vehicles (AVs) on public roadways expands, there is growing interest in establishing metrics that can be used to evaluate vehicle operational safety. The set of Operational Safety Assessment (OSA) metrics, that include several safety envelope-type metrics, previously proposed by the Institute of Automated Mobility (IAM) are a step towards this goal. The safety envelope OSA metrics can be computed using kinematics derived from video data captured by infrastructure-based cameras and thus do not require on-board sensor data or vehicle-to-infrastructure (V2I) connectivity, though either of the latter data sources could enhance kinematic data accuracy. However, the calculation of some metrics includes certain vehicle-specific parameters that must be assumed or estimated if they are not known a priori or communicated directly by the vehicle.