Morning Sessions

TRACK A

Protection in Frontal, Side, and Rear Impact Crashes

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Peer Review Abstract | Traditional Abstract

The automotive industry has made significant improvements in crash protection over the last four decades. As innovative vehicle technologies emerge and change the composition of vehicles on the roads, examining the effects on occupant protection and ensuring that that injury risk measurement methods remain appropriate and effective.  Papers are encouraged to discuss how to provide equitable occupant protection for these crash conditions. This session will include computational, experimental, and field studies that address occupant protection in frontal, side, and rear impacts with other road vehicles and roadside structures. Topics can include geometric and mass compatibility, occupant restraints, vehicle structure and interiors, and the measurement capabilities of Anthropomorphic Test Devices (ATDs).

TRACK B 

Driver Monitoring Systems to Prevent Crashes and Fatalities

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Peer Review Abstract | Traditional Abstract

Evolving vehicle technologies now provide opportunities to better understand both driver and occupant states. Applications of radar and camera-based vision systems may be used to detect unattended occupants and alert passersby to potential heatstroke. Additional camera-based vision systems may directly assess eye gaze direction or head/body position and classify a driver as distracted, asleep and/or drowsy, or otherwise incapacitated. Other systems may be able to interpret driver inputs such as lane position variability and acceleration patterns to infer drowsiness or other forms of impairment. Worldwide, more vehicles are being introduced to the market with differing driver and occupant monitoring systems. Papers related to differing technologies and methods to detect (or infer) driver and/or occupant states, their accuracy, reliability, and associated human-machine interfaces are invited.

TRACK C

Artificial Intelligence (AI) and Machine Learning (ML) for Enhanced Vehicle Safety

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Peer Review Abstract | Traditional Abstract

Artificial intelligence (AI) and machine learning (ML) approaches hold potential to synthesize large amounts of data to address hard problems and are rapidly being explored across a variety of industries and use cases. This session invites discussions around what AI means in the automotive context, how it is used both in vehicle systems and subsystems, and how it can be leveraged to develop actionable safety insights. Areas of interest include ways that AI/ML methods can use data from sources such as real-world crash databases, telemetry, and simulation to inform countermeasures and safety assessment methodologies. Papers are also invited that discuss AI/ML in vehicle system applications such as in-service system health monitoring and diagnostics, ADAS/ADS perception and planning, and driver monitoring. This includes the verification and validation of continuously evolving AI/ML systems, and questions around training set coverage, robustness, and explainability.

Afternoon Sessions

TRACK A

Protection of Vulnerable Non-Occupant Road Users

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Peer Review Abstract | Traditional Abstract

Crash injuries to pedestrians, bicyclists, motorcyclists, and other road users are major contributors to morbidity. Each of these road-user groups presents unique challenges for the assessment of injury risk and the design of safety countermeasures. This session will include computational, experimental, and field studies related to the protection of pedestrians, cyclists, motorcyclists, and innovative mobility devices, including micro-mobility devices such as e-scooters and e-bikes.

TRACK B

Human Factors in Driving Automation and the Role of the Driver and Occupants

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Peer Review Abstract | Traditional Abstract

Driving automation continues to evolve, and lower levels of automation have become more prevalent on the roadway. It is evident that there must be careful emphasis on design considerations for both system capabilities and drivers’ interactions with partial driving automation systems. This includes conveying information to the driver on when and where partial automation systems can be used and the limitations of those systems.  Implementing driver engagement measures is important – which may require technology to assess the driver’s state and carefully designing an effective human-machine interface to keep drivers engaged in the driving task when needed. In the case of SAE Level 3 automation, new human-machine interaction challenges arise including when to bring a driver back into the driving task and how this can be safely and effectively accomplished. In the case of ADS-operated vehicles, the focus shifts to providing appropriate information to the occupants. These needs will likely be different based on individual use-cases for the ADS (e.g., fixed route, ride-hail, personal ownership). Papers are invited on research related to the driver-vehicle interface (including transition of control strategies) for partial driving automation and ADS-equipped vehicles. In addition, for ADS technologies, particularly those without traditional controls, papers are invited on additional topics such as external communication, telltales, and other signaling that may be useful for occupants of ADS vehicles, and human factors design needs for people with disabilities.

TRACK C

Safety of Alternate Fueled Vehicles

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Peer Review Abstract | Traditional Abstract

As vehicle powertrains transition from internal combustion to electric and hydrogen fuel cell systems, new risks are emerging. These risks include fires in battery packs, combustible gas leakage, and tank overpressures. This session invites papers on safety considerations for alternate fuel vehicles, including stranded energy, fire incident response, sensors for safe operation, evaluation of damaged vehicles, charging and fueling safety, water immersion, and emerging technologies. Papers are invited to discuss both design, evaluation and incident response related to these rapidly evolving vehicle technologies.

Morning Sessions

TRACK A

Experimental and Computational Advances in Biomechanics and Human Injury Research

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Peer Review Abstract | Traditional Abstract

The study of human injury mechanisms and risks is essential to continued improvement in occupant and vulnerable road user crash protection. An enhanced understanding of the factors associated with injury outcomes may be gained through experimental testing or using computational tools. This technical session will include studies that address: (1) experimental and field data studies related to human biomechanical response and injury mechanisms; (2) development or improvement of computational human body models, including considerations for human variability related to sex, anthropometry, stature, age, and injury tolerance; (3) application of human body models for the development of innovative technologies; (4) advances in development of injury risk curves, injury criteria, and performance specifications.

TRACK B

Safety Assessments for ADS-Operated Vehicles (SAE Levels 3, 4 and 5)

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Peer Review Abstract | Traditional Abstract

As Automated Driving Systems (ADS) development activities continue toward the goal of removing reliance on human drivers, the assurance of their safety for public acceptance has never been more critical. This session aims to explore the multifaceted approaches to assessing the safety performance of ADS-equipped vehicles. This session invites papers that address innovative methodologies for evaluating safety, including metrics developed to quantify safety performance and the tools used to measure it. With diverse use cases ranging from low-speed shuttles and unoccupied delivery vehicles to hub-to-hub automated highway trucks, the unique challenges presented by ADS, including overall performance, occupant protection and crashworthiness, warrant rigorous scrutiny. There is particular interest in contributions that contextualize proposed assessment methods in relation to real-world outcomes, especially when alternative or mixed methods—such as virtual frameworks—are employed. Submissions may discuss fidelity measures for simulation approaches, independent validation techniques, operational safety monitoring approaches, methods associated with storing and analyzing large volumes of driving data, approaches to identifying minimum datasets to validate assumptions and system performance, approaches to independently evaluating sub-functions of driving automation, such as perception, prediction, planning, etc.; electronics systems safety (functional safety, safety of the intended functionality), cybersecurity and accompanying innovative strategies to establish a robust measure of trust in presented safety results. This session seeks to highlight not only the performance of ADS in navigating complex environments but also the implications for occupant safety and protection. We encourage researchers, practitioners, and industry experts to share their insights on the scientific methods driving safety assurance, thereby contributing to the ongoing dialogue about achieving maturity in ADS and fostering public confidence.

TRACK C

Consumer-Focused Approaches to Promote Vehicle Safety in the Automotive Market

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Peer Review Abstract | Traditional Abstract

Consumer information programs have become widely accepted in the United States, Europe, Japan, Australia, Korea, China, Latin America, and Asia. These programs provide a range of vehicle safety ratings for passive and active vehicle technologies. The motor vehicle industry continues to improve the safety performance of vehicles as it strives to receive the highest safety marks possible. In addition to assessing occupant crash safety, programs are emphasizing advanced driver assistance systems, occupant monitoring systems, and considering approaches for automated vehicle technologies. While assessment strategies vary from region to region, the programs all aim to encourage continuous improvements in motor vehicle safety. Papers are invited to discuss test conditions, performance measures, presentation and dissemination of results, public acceptance, and consideration of emerging safety technologies. Automated Driving Systems (ADS) introduce an integration of active and passive safety ratings and may increase the importance of virtual testing. 

Afternoon Sessions

TRACK A 

Advances in Crash Test Dummies, Instrumentation, and Data Analysis

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Peer Review Abstract | Traditional Abstract

Dummy developments to enhance biofidelity and measurement capabilities are necessary to correctly represent human responses and effectively evaluate safety countermeasures in physical tests. This session will include papers that address all aspects of dummy development, including, but not limited to, studies of biofidelity, durability, repeatability, and reproducibility. Studies related to test methodologies (e.g., dummy positioning protocols), dummy evaluation, instrumentation, and injury metrics will also be included. 

TRACK B

ADAS for Crash Avoidance and Mitigation: Innovative and Emerging Technologies

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Peer Review Abstract | Traditional Abstract

Advanced Driver Assistance Systems (ADAS) focused on crash avoidance and mitigation, are continuing to progress in both capability and market share, with increasing availability across product lines, from value-focused to luxury brands, and some systems becoming standard equipment on models.  These systems may provide driver warnings and active intervention in the longitudinal and/or lateral directions in crash imminent scenarios, based on system perception of other road actors, including vehicles and vulnerable road users, roadway characteristics and conditions.  Some examples of ADAS features focused on crash avoidance and mitigation include the following: forward collision warning, automatic emergency braking, pedestrian automatic emergency braking, lane departure warning, lane keeping assistance, blind spot warning, blind spot intervention, and rear cross-traffic alert.  In addition, innovative and emerging technologies are being developed to improve real-world system performance and help address other challenging crash imminent scenarios to increase potential safety benefits.  

This session invites papers related to ADAS crash avoidance and mitigation systems, particularly innovative and emerging technologies.  The intent of the session is to cover a broad range of relevant research in the field, which may include some of the following areas: advanced perception sensors; object detection and classification algorithms; perception system training for real-world robustness; methods to identify and reduce real-world false positives and negatives; virtual testing methods including simulation and XIL; closed track testing methods including test surrogates and equipment; on-road testing methods including field tests and operational safety monitoring; crash data analysis, scenario characterization, and safety benefits estimation; technology advancements to improve system performance for established and new scenarios (e.g. pedestrian, bicycle, motorcycle, other vulnerable road users, intersection, head-on, nighttime, weather, speeding); user acceptance, effectiveness, and potential unintended consequences.

TRACK C

New and Improved Field Data Collection, Analysis, and Benefits Assessment Methods

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Peer Review Abstract | Traditional Abstract

Crash data plays a crucial role in enhancing vehicle safety by informing research, policy development, regulations, and testing procedures. These data also play a leading role in the development of crash prevention and crash protection countermeasures. However, due to the rapid proliferation of advanced driver assistance systems (ADAS), the collection and analysis of data from these technologies needs to evolve to better understand the real-world performance and to quantify the benefits and limitations of these technologies. Data collected on event data recorders (EDRs), data loggers, or over-the-air transmissions during both crash and non-crash events will undoubtedly enable new research opportunities. Also, several naturalistic studies and testing of ADAS and Automated Driving Systems (ADSs) are in progress in various regions of the world that will provide additional insight into how crashes occur, providing additional information on prevention. Worldwide, data collection programs in Asia, Europe, Australia, and the United States. are being used more to drive research and facilitate informed decisions. This session invites papers aimed at a discussion of novel data collection and analysis methods. Papers related to such topics as telematics, on-board and off-board data recorders, naturalistic driving data, crash avoidance technologies, levels of driving automation, and crash reconstruction are welcome in this session. Also, papers on analytical methods for evaluating safety performance of new technologies are invited.

Morning Sessions

TRACK A 

Crash Protection for Children

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Peer Review Abstract | Traditional Abstract

The effectiveness of safety systems is influenced by anthropometry, sex, and age, as well as other characteristics of the occupant. This session will cover computational, experimental, and field studies as they relate to injuries of children.  Papers are encouraged that discuss the safety considerations by age, sex, and size and strategies to protect diverse populations. Topics can also include the evaluation of safety systems such as child restraints and aftermarket products. 

TRACK B

Overflow Session

TRACK C

Advancing Vehicle Safety Through Virtual Testing: Challenges and Opportunities

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Peer Review Abstract | Traditional Abstract

There is increasing activity around virtual testing for different aspects of motor vehicle safety, from crashworthiness testing to the evaluation of complex automated driving systems. This session would provide researchers with an opportunity to discuss the challenges they face in developing and validating test platforms, generating meaningful and reliable test results beyond simple graphical representations, and how virtual testing fits into broader testing and evaluation goals. Papers should focus on the potential uses of virtual testing for safety validation and oversight, rather than on simulation and modeling for other aspects of vehicle development.