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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.

Accident data show that the head and the chest are the most frequently injured body regions in side impact fatal accidents. Curtain side air bag (CSA) and thorax side air bag (SAB) have been installed by manufacturers for the protection devices for these injuries. In this research, first we studied the recent side impact accident data in Japan and verified that the head and chest continued to be the most frequently injured body regions in fatal accidents. Second, we studied the occupant seating postures in vehicles on the roads, and found from the vehicle's side view that the head location of 56% of the drivers was in line or overlapped with the vehicle's B-pillar. This observation suggests that in side collisions head injuries may occur frequently due to contacts with the B-pillar. Third, we conducted a side impact test series for struck vehicles with and without CSA and SAB.

As software (SW) becomes more and more an important aspect of embedded system development, project schedules are requiring the earlier development of software simultaneously with hardware (HW). In addition, verification has increasingly challenged the design of complex mixed-signal SoC products. This is exacerbated for automotive safety critical SoC products with a high number of analogue interfaces (sensors and actuators) to the physical components such as an airbag SoC chipset. Generally, it is widely accepted that verification accounts for around 70% of the total SoC development. Since integration of HW and SW is the most crucial step in embedded system development, the sooner it is done, the sooner verification can begin. As such, any approaches which could allow verification and integration of HW/SW to be deployed earlier in the development process and help to decrease verification effort, (e.g.: accelerate verification runs) are of extreme interest.

The experimental campaign discussed in publication 2019-01-0635 was extended to emulate more vehicle parameters and also to increase severity leading to deployment event. The engine speed (RPM) and Accelerator Pedal Position (APP) were emulated using LabVIEW and added to the previously reported emulated parameters of wheel speeds and brake status. Overlapping non-deployment events were generated and the EDR data is presented enriched with additional (faster) CAN bus data sniffed from the vehicle harness. While the non-deployment events were still generated using the rubber mallet in pendulum configuration as in 2019-01-0635, a series of tests were performed using an Izod pendulum to incrementally increase event severity until deployment event was generated. The Izod pendulum was instrumented with a rotational potentiometer to measure its instantaneous angle while laboratory accelerometers were used to separately measure acceleration.

Transfer or response equations are important as they provide relationships between the responses of different surrogates under matched, or nearly identical loading conditions. In the present study, transfer equations for different body regions were developed via mathematical modeling. Specifically, validated finite element models of the age-dependent Ford human body models (FHBM) and the mid-sized male Hybrid III (HIII50) were used to generate a set of matched cases (i.e., 192 frontal sled impact cases involving different restraints, impact speeds, severities, and FHBM age). For each impact, two restraint systems were evaluated: a standard three-point belt with and without a single-stage inflator airbag. Regression analyses were subsequently performed on the resulting FHBM- and HIII50-based responses. This approach was used to develop transfer equations for seven body regions: the head, neck, chest, pelvis, femur, tibia, and foot.

This paper is based on, and in continuation of the work previously published in ASEE NCS Conference held in Grand Rapids, MI [1]. Automotive seating rail structures are one of the key components in the automotive industry because they carry the entire weight of passenger and they hold the structure for seating foams and other assembled key components such as side airbag and seatbelt systems. The entire seating is supported firmly and attached to the bottom bodywork of the vehicle through the linkage assembly called the seat rails. Seat rails are adjustable in their longitudinal motion which plays an important role in giving the passengers enough leg room to make them feel comfortable. Therefore, seat rails under the various operating conditions, should be able to withstand the weight of the passenger along with the other assembled parts as mentioned above. Also, functional requirements such as crash safety is very important to avoid or to minimize injuries to the occupants.

In highly automated vehicles (HAVs), new seat configurations may be desirable to allow occupants to perform new activities. One of the current HAV concepts is the swiveled seat layout, which might facilitate communication between occupants. The main objective of this study was to investigate the effects of seat swiveling angles on occupant kinematics and injury risk predicted by a Human Body Model (HBM) during a frontal impact. A detailed 50th percentile male HBM (GHBMC M50-O) was subjected to two frontal crash pulses in a sled setup. The model was positioned on a semi-rigid seat and restrained using a pre-inflated airbag and a three-point seatbelt. Simulations included four seat swiveling angles (0, -10, -20, and -30 degrees), three occupant positions (Sedan driver, large VAN driver or Laptop user), two airbag initial locations (nominal or matching the head Y location), and the inclusion of lateral supports on the seat pan.

This SAE Standard describes the interface between an on-vehicle Mayday detection, reporting system and the off-vehicle response center that will manage the response to the vehicle's call for assistance. The automatic detection and reporting by either the intelligent vehicle itself or by the intelligent roadway of a vehicle that is disabled or involved in an accident, [referred to as Automatic Mayday], is one of the key services identified by the ITS America program plan road map. This effort has been identified, as STD SAE J2313 in recent DOT-FHWA efforts to advance needed National standards. This document primarily addresses the responsibilities of a vehicle in detecting and reporting such an event. Equipment suites on each vehicle will vary widely, as will the communications channel employed to report the incident.

The objective of this document is to enhance the test procedure that is used for ejection mitigation testing per the NHTSA guidelines as mentioned in the FMVSS226 Final Rule document (NHTSA Docket No. NHTSA-2011-0004). The countermeasure for occupant ejection testing is to be tested with an 18kg mass on a guided linear impactor using the featureless headform specifically designed for ejection mitigation testing. SAE does not endorse any particular countermeasure for ejection mitigation testing. However, the document reflects guidelines that should be followed to maintain consistency in the test results. Examples of currently used countermeasures include the Inflatable Curtain airbags and Laminated Glass.

The objective of this document is to enhance the test procedure that is used for ejection mitigation testing per the NHTSA guidelines as mentioned in the FMVSS226 Final Rule document (NHTSA Docket No. NHTSA-2011-0004). The countermeasure for occupant ejection testing is to be tested with an 18kg mass on a guided linear impactor using the featureless headform specifically designed for ejection mitigation testing. SAE does not endorse any particular countermeasure for ejection mitigation testing. However, the document reflects guidelines that should be followed to maintain consistency in the test results. Examples of currently used countermeasures include the Inflatable Curtain airbags and Laminated Glass.

The new sound and vibration laboratory at Autoliv’s Ogden Technical Center (OTC) was purpose-built with a focus on automotive safety restraint product development (air bags, seat belts, steering wheels, etc.). The laboratory requirements stem from the continued industry trend of quieter vehicles which drives the need for components with extremely low levels of rattle noise. The laboratory at OTC complements similar Autoliv testing facilities around the world. Test articles range from several cubic inches up to approximately one cubic foot and contain varying degrees of moving elements. With the new laboratory at OTC, Autoliv can test new product designs earlier in the development process and obtain test results and feedback faster. The function of the OTC test lab is vibration-induced rattle noise; shake components with a known input and measure the resulting noise.

This investigation addresses and evaluates: (1) belted drivers in frontal crashes; (2) crashes divided into low, medium, and high severity; (3) air-bag-equipped passenger vehicles separated into either model years 1985 - 1997 (with airbags) or model years 1998 - 2008; (4) rate of Harm as a function of crash severity and vehicle model year; and (5) injury patterns associated with injured body regions and the involved physical components, by vehicle model year. Comparisons are made between the injury patterns related to drivers seated in vehicles manufactured before 1998 and those manufactured 1998 or later. The purpose of this comparative analysis is to establish how driver injury patterns may have changed as a result of the introduction of more recent safety belt technology, advanced airbags, or structural changes.

Abstract Modern driver compartment restraint systems have at least three key components that work together: safety belt system, airbags, and collapsible steering column. During a crash, a steering column will collapse at a predetermined force called breakaway force. Once the force of a crash has reached the breakaway force threshold, the column will move towards the motor area. When the column moves, the drivers’ peak forces and acceleration are decreased because the time and distance that are given to decelerate are increased. The usage of a breakaway force element inside the steering column allows car manufacturers to control the movement of the steering column at a certain point during a crash. Any load below the breakaway force, such as airbag deployment and normal or misuse forces applied by the driver, is absorbed by the system. Today’s force-based systems are optimized (design/configure) using various crash configurations, leading to one specific behavior of the column.

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).

In an attempt to predict the responses of side crash pressure sensors, the Corpuscular Particle Method (CPM) was adopted and enhanced in this research. Acceleration-based crash sensors have traditionally been used extensively in automotive industry to determine the air bag firing time in the event of a vehicle accident. The prediction of crash pulses obtained from the acceleration-based crash sensors by using computer simulations has been very challenging due to the high frequency and noisy responses obtained from the sensors, especially those installed in crash zones. As a result, the sensor algorithm developments for acceleration-based sensors are largely based on prototype testing. With the latest advancement in the crash sensor technology, side crash pressure sensors have emerged recently and are gradually replacing acceleration-based sensor for side impact applications.

An Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors in an attempt to assist pressure sensor algorithm development by using computer simulations. Acceleration-based crash sensors have traditionally been used to deploy restraint devises (e.g., airbags, air curtains, and seat belts) in vehicle crashes. The crash pulses recorded by acceleration-based crash sensors usually exhibit high frequency and noisy responses depending on the vehicle's structural design. As a result, it is very challenging to predict the responses of acceleration-based crash sensors by using computer simulations, especially those installed in crush zones. Therefore, the sensor algorithm developments for acceleration-based sensors are mostly based on physical testing.

It is very common that a microcontroller is used in a safety relevant system to acquire data from sensors, process the data and then control actuators. With the shrink of technology every few years it becomes ever more common to use digital serial interfaces and high speed PWM links for both inputs and outputs. The microcontroller vendors have responded to the need for functional safety in the CPU cores by lock-stepping them and adding ECC to buses and memories. They are also implementing highly flexible and complex timer peripherals to be able to automate much of the real-time processing of the digital signals. However these timers are becoming significantly large, and many have their own embedded sequence engines or microkernels, which although powerful, often lack the rigorous diagnostic mechanisms required to reach ASILD.

A new highly biofidelic side impact dummy, the WorldSID 50th percentile male, has been developed under the supervision of the International Organization for Standardization in order to harmonize a number of existing side impact dummies in one single dummy. Momentum is growing for using the WorldSID in safety tests in the EU and the US. In the present study, two Euro-NCAP pole side impact tests were conducted to compare ES-2 and WorldSID responses in a mid-size SUV with respective seating positions as stipulated in the Euro-NCAP test conditions and fitted with the same side airbag. It was found that, compared with ES-2, the chest, abdomen and pelvis accelerations of WorldSID are more sensitive to variation in the applied external load transmitted by the deployed side airbag and door intrusion.

In an attempt to assist pressure sensor algorithm and calibration development using computer simulations, an Arbitrary Lagrangian Eulerian (ALE) approach was adopted in this study to predict the responses of side crash pressure sensors for body-on-frame vehicles. Acceleration based, also called G-based, crash sensors have been used extensively to deploy restraint devices, such as airbags, curtain airbags, seatbelt pre-tensioners, and inflatable seatbelts, in vehicle crashes. With advancements in crash sensor technologies, pressure sensors that measure pressure changes in vehicle side doors have been developed recently and their applications in vehicle crash safety are increasing. The pressure sensors are able to detect and record the dynamic pressure change when the volume of a vehicle door changes as a result of a crash.