Browse Topic: Safety

Items (19,848)

Enhancing Airworthiness Security: SysML-Based Approach to Modelling Security Scope Definitions

2025-01-0172To be published on 05/02/2025

Airworthiness certification of aircraft requires an Airworthiness Security Process (AWSP) to ensure safe operation under potential unauthorized interactions, particularly in the context of growing cyber threats. Regulatory authorities mandate the consideration of Intentional Unauthorized Electronic Interactions (IUEI) in the development of aircraft, airborne software, and equipment. As the industry increasingly adopts Model-Based Systems Engineering (MBSE) to accelerate development, we aim to enhance this effort by focusing on security scope definitions – a critical step within the AWSP for security risk assessment that establishes the boundaries and extent of security measures. However, our findings indicate that, despite the increasing use of model-based tools in development, these security scope definitions often remain either document-based or, when modeled, are presented at overly abstract levels, both of which limit their utility. Furthermore, we found that these definitions

Hechelmann, Adrian, Mannchen, Thomas

Determining Worst-Case Execution Time Bounds for Multi-core Processors

2025-01-0155To be published on 05/02/2025

Demonstrating deadline adherence for real-time tasks is a common requirement in all safety norms, including ISO 26262 and DO-178C. Timing verification has to address two levels: the code level (worst-case execution time) and the scheduling level (worst-case response time). Determining which methodology is suited best depends on the characteristics of the target processor. All contemporary microprocessors try to maximize the instruction-level parallelism by sophisticated performance-enhancing features that make the execution time of a particular instruction dependent on the execution history. On multi-core systems, the execution time additionally is influenced by interference effects on shared resources caused by concurrent activities on the different cores, which are not controlled by the scheduling algorithm. In the avionics domain, the new FAA AC 20-193 / EASA AMC 20-193 guidance documents formalize predictability aspects of multi-core systems and derive adequate measures for timing

Kaestner, Daniel, Gebhard, Gernot, Huembert, Christian, Pister, Markus, Wegener, Simon, Ferdinand, Christian

The Why of Development Assurance

2025-01-0154To be published on 05/02/2025

In the domain of aircraft certification, Development Assurance is what some would call a useful tool to gain confidence in the development of complex systems, and what others would call a necessary evil. But what does it actually do? Why is it necessary for certification of modern aircraft? What, epistemologically, does it bring to the table? This paper aims to show why development assurance activities, at all levels from aircraft to item, close the epistemological holes created when complex systems are chosen for implementation. It will map the different sources and types of uncertainty encountered in system verification and explain how each type is dealt with within a certification context, working from simple mechanical systems up to complex and highly integrated systems using software and airborne electronic hardware and beyond. It will show that Development Assurance, far from being an arbitrary set of activities, systematically brings personal and corporate expertise to bear to

Laflin, Cory R.

Research on Crash Simulation and Safety of Automotive Power Battery

2025-01-8226

04/01/2025

In recent years, energy scarcity and environmental pollution have intensified globally, prompting increased research and development in new energy vehicles as countries prioritize environmental protection and energy conservation. Compared to fuel-powered vehicles, new energy vehicles have relatively larger battery volumes and weights, which can increase damage and the risk of fires and explosions in collisions. To analyze and optimize the safety performance of a specific vehicle model's battery pack, we constructed a finite element model using existing software and performed pre-processing, simulation, and analysis of modal, random vibration, and extrusion characteristics. This revealed specific damage scenarios and enabled reliability analysis under working conditions. To enhance safety and reduce mass, we parametrically modeled power pack components and optimized parameters via multi-objective genetic algorithms under three road conditions. Results indicate reduced mass and improved

Wang, Zhi

End-to-End Style Parking Algorithm Development Pipeline Based on Procedural Parking Scenario Synthetic Data Generation

2025-01-8060

04/01/2025

Less costs and higher efficiency may be constant technological pursuit. Despite the great success, data-driven AI development still requires multiple stages such as data collection, cleaning, annotation, training, and deployment to work together. We expect an end-to-end style development process that can integrate these processes, achieving an automatic data production and algorithm development process that can work with just clicks of the mouse. For this purpose, we explore an end-to-end style parking algorithm development pipeline based on procedural parking scenario synthetic data generation. Our approach allows for the automated generation of parking scenarios according to input parameters, such as scene construction, static and dynamic obstacles arrangement, material textures modification, and background changes. It then combines with the ego-vehicle trajectories into the scenarios to render high-quality images and corresponding label data based on Blender software. Utilizing

Li, Jian, Wang, Hanchao, Zhang, Song, Meng, Chao, Rui, Zhang

Advancing Verification and Validation for ADAS and ADS

2025-01-8052

04/01/2025

Emerging automotive technologies like advanced driver assistance systems (ADAS) and automated driving systems (ADS) hold promise for improving safety for the traveling public; however, effective verification and validation (V&V) of these systems has proven to be challenging. Traditional testing methodologies may serve in limited cases for systems exhibiting low levels of automation, but recent studies show that these systems that have been brought to market perform poorly in practice. Further, these traditional methods do not serve for testing systems with high levels of automation where a human driver simply serves as a fallback ready user or is out of the loop altogether. New V&V methods are required to assess whether these systems can perform their intended functions in their intended operating environments, and to assess whether they can do so safely across the expansive and variable operating space. This paper presents an overview of ADAS and ADS challenges and novel approaches to

Thorn, Eric, Knisley, Veronica, Auchter, Joseph

Development of an Advisory System for Parking a Car with Trailer

2025-01-8035

04/01/2025

Trailer parking is a challenging task due to the unstable nature of the vehicle-trailer system in reverse motion and the unintuitive steering actions required at the vehicle to accomplish the parking maneuver. This paper presents a strategy to tackle this kind of maneuver with an advisory graphic aid to help the human driver with the task of manually backing up the vehicle-trailer system. A kinematic vehicle-trailer model is derived to describe the low-speed motion of the vehicle-trailer system, and its inverse kinematics is established by generating an equivalent virtual trailer axle steering command. The advisory system graphics is generated based on the inverse kinematics and displays the expected trailer orientation given the current vehicle steer angle and configuration (hitch angle). Simulation study and animation are set up to test the efficacy of the approach, where the user can select both vehicle speed and vehicle steering angle freely, which allows the user to stop the

Cao, Xincheng, Chen, Haochong, Aksun Guvenc, Bilin, Guvenc, Levent, Link, Brian, Harber, John, Richmond, Peter, Fan, Shihong, Yim, Dokyung

Deriving Architectural Requirements for SAE J3016 ^TM Level 3 System from Functional Safety Perspective

2025-01-8009

04/01/2025

Vehicles with SAE J3016TM Level 3 systems are exposed to road infrastructure, Vulnerable Road Users (VRUs), traffic and other actors on roadways. Hence safe deployment of Level 3 systems is of paramount importance. One aspect of safe deployment of SAE Level 3 systems is the application of functional safety (ISO 26262) to their design, development, integration, and testing. This ensures freedom from unreasonable risk, in the event of a system failure and sufficient provisions to maintain Dynamic Driving Task (DDT) and to initiate Minimum Risk Maneuver (MRM), in the presence of random hardware and systematic failures. This paper explores leveraging ISO 26262 standard to develop architectural requirements for enabling SAE Level 3 systems to maintain DDT and MRM during fault conditions and outlines the importance of fail-operability for Level 3 systems, from a functional safety perspective. At a high-level, UN Regulation No. 157 – Automated Lane Keeping Systems (ALKS) is used as a baseline

Mudunuri, Venkateswara Raju, Jayakumar, Namitha

Damage Analysis of Traction Battery For New Energy Vehicle Based on Bottom Impact

2025-01-8125

04/01/2025

As the high-quality development of the new energy vehicle (NEV) and traction battery industries, the safety of traction batteries has become a global focus. Typically mounted at the bottom of NEVs, traction battery systems are particularly vulnerable to mechanical damage caused by bottom impacts, posing serious safety risks. This study investigates the damage sustained by NEV traction battery systems during bottom impact collisions, using computer tomography analysis to detail the damage mechanisms. The findings provide valuable data to enhance the safety and protective performance of traction batteries under such scenarios.

Yan, Pengfei, Wang, Fang, Ma, Tianyi, Han, Ce, He, Gaiyun

Tube-MPC Based Path Tracking for I Vehicle Considering Data-Driven Stable Region and External Disturbances

2025-01-8262

04/01/2025

Path tracking is a key function of intelligent vehicles, which is the basis for the development and realization of advanced autonomous driving. However, the imprecision of the control model and external disturbances such as wind and sudden road conditions will affect the path tracking effect and even lead to accidents. This paper proposes an intelligent vehicle path tracking strategy based on Tube-MPC and data-driven stable region to enhance vehicle stability and path tracking performance in the presence of external interference. Using BP-NN combined with the state-of-the-art energy valley optimization algorithm, the five eigenvalues of the stable region of the vehicle β−β̇ phase plane are obtained, which are used as constraints for the Tube-MPC controller and converted into quadratic forms for easy calculation. In the calculation of Tube invariant sets, reachable sets are used instead of robust positive invariant sets to reduce the calculation. Simulation results demonstrates that the

Zhang, Haosen, Li, Yihang, Wu, Guangqiang

Overview of Seat Design Changes and Performance

2025-01-8729

04/01/2025

The National Highway Traffic Safety Administration (NHTSA) published an Advance Notice of Proposed Rulemaking (ANPRM) to update the Federal Motor Vehicle Safety Standard (FMVSS) 207. Part of the ANPRM is to assess the merit of conducting quasi static body block seat pull tests and conducting FMVSS 301 rear crash tests at 80 km/h or higher with a 95th percentile ATD lap-shoulder belted in the front seats and limiting seatback deflection to 15 to 25 degrees. Prior to updating regulations, it is important to understand the seating design history and implications. This study was conducted to provide a historical background on seat design and performance using literature and test data. One objective was to first define the terminology used to describe occupant kinematics in rear crashes. Secondly, seat design evolution is then discussed. Third, test methods and test results were summarized, and fourth, the field performance are synopsized and discussed with respect to 2nd row occupant

Parenteau, Chantal, Burnett, Roger, Davidson, Russell

Advanced Driver Assistance Systems (ADAS): Assessing the Efficacy of Non-Impact Testing for Evaluating the Performance of Frontal Collision Mitigation Technology

2025-01-8056

04/01/2025

As Automatic Emergency Braking (AEB) systems become standard equipment in more light duty vehicles, the ability to evaluate these systems efficiently is becoming critical to regulatory agencies and manufacturers. A key driver of the practicality of evaluating these systems’ performance is the potential collision between the subject vehicle and test target. AEB performance can depend on vehicle-to-vehicle closing speeds, crash scenarios, and nuanced differences between various situational and environmental factors. Consequently, high speed impacts that may occur while evaluating the performance of an AEB system, as a result of partial or incomplete mitigation by an AEB activation, can cause significant damage to both the test vehicle and equipment, which may be impractical. For tests in which impact with the test target is not acceptable, or as a means of increasing test count, an alternative test termination methodology may be used. One such method constitutes the application of a late

Kuykendal, Michelle, Easter, Casey, Koszegi, Giacomo, Alexander, Ross, Paradiso, Marc, Scally, Sean

FIT File Processing for Accident Reconstruction

2025-01-8696

04/01/2025

It is becoming increasingly common for bicyclists to record their rides using specialized bicycle computers and watches, the majority of which save the data they collect using the Flexible and Interoperable Data Transfer (.fit) Protocol. The contents of .fit files are stored in binary and thus not readily accessible to users, so the purpose of this paper is to demonstrate the differences induced by several common methods of analyzing .fit files. We used a Garmin Edge 830 bicycle computer with and without a wireless wheel speed sensor to record naturalistic ride data at 1 Hz. The .fit files were downloaded directly from the computer, uploaded to the chosen test platforms - Strava, Garmin Connect, and GoldenCheetah - and then exported to .gpx, .tcx and .csv formats. Those same .fit files were also parsed directly to .csv using the Garmin FIT Software Developer Kit (SDK) FitCSVTool utility. The data in those .csv files (henceforth referred to as “SDK data”) were then either directly

Sweet, David, Bretting, Gerald

Dynamic Testing and Analysis of Autocycle Vehicles for Accident Reconstruction

2025-01-8687

04/01/2025

The Autocycle is a style of vehicle that most often utilizes a reverse-tricycle design with two front wheels and a single rear wheel. Modern autocycles in the United States are often utilized in a recreational role. This work presents physical measurements of two modern autocycles for use in accident reconstruction and pursues a deeper understanding of the unique attributes and handling associated with these vehicles. Vehicles were used to measure physical properties and subjected to cornering tests presented herein, and the data is compared to that for a conventional automobile. Observations on tire scuff marks are made from cornering tests unique to these vehicles. Strengths and challenges with this type of vehicle design are presented for various use cases as compared to conventional automobiles. Data and knowledge from this study are published to aid accident reconstruction efforts.

Warner, Wyatt, Swensen, Grant, Warner, Mark

An Introduction and Evaluation of Apple iOS Device Data for Use in Crash Reconstruction

2025-01-8706

04/01/2025

The integration of mobile device data in accident/crash/collision reconstruction methodologies offers significant potential in analyzing collision events. This study evaluates the utility of iPhone-recorded data, specifically Global Navigation Satellite System (GNSS) position and speed data, along with Coordinated Universal Time (UTC) based time and date information associated with application usage and device activity events. By conducting controlled tests, the accuracy, precision, and reliability of iPhone GNSS data were compared against high-accuracy reference systems, including a Racelogic VBox Video HD2 25 Hz GPS data logger and VBox Sport 25 Hz GPS data logger. The synchronicity between recorded app events and device activities with physical events was also analyzed to assess the temporal resolution of the data. Results highlight the strengths and limitations of iPhone data for reconstructing crash events, including potential discrepancies in GNSS accuracy under varying

Burgess, Shanon, Phy, Lance, Levan, Matthew

Assessment of Injuries in Rear Impacts

2025-01-8727

04/01/2025

Rear impacts make up a significant portion of crashes in the United States. To date, regulations on rear impacts have focused on fuel system integrity and seat performance, while most research has focused on seat performance in relation to occupants’ injuries, with some analyses of crash severity and seat belt effects. The performance of seats and seat belts may vary depending on the size of the occupant. Understanding how occupant characteristics, as well as crash scenarios, affect injury outcomes can show opportunities for further enhancements in rear impact occupant protection. This paper presents analyses using survey weighted logistic regression models to understand the factors affecting serious injury outcomes (i.e., MAIS 3+) in rear impacts, exploring the potential for improving occupant outcomes. Three separate models are evaluated, focusing on 1) overall injury level, 2) head, neck, and cervical-spine injuries, and 3) thorax, abdomen, thoracic- and lumbar-spine injuries for

Greib, Joshua, Jurkiw, Renee, Kryzaniwskyj, Tanja, Owen, Susan, Van Rooyen, Paul, Whelan, Stacey, Williamson, John

Lightweight Optimization of an Electric Bus Body Frame Based on the C ² oDE Algorithm

2025-01-8654

04/01/2025

In this work, design optimization for the lightweight of the body frame of a commercial electric bus with the requirements of stiffness, strength and crashworthiness is presented. The technique for order preference by similarity to ideal solution (TOPSIS) is applied to calculate the components that have a great impact on the output response of the static modal model and the rear-end collision model. The thickness of the five components with the highest contribution in the two models is determined as the final design variable. Design of experiment (DOE) is carried out based on the Latin Hypercube sampling method, and then the surrogate models are fitted by the least squares regression (LSR) method based on the DOE sampling data. The error analysis of the surrogate model is carried out to determine whether it can replace the finite element (FE) model for optimization, then the optimization scheme for lightweight optimization of electric bus frame is implemented based on the algorithm of

Yang, Xiujian, Tian, Dekuan, Liu, Jiaqi, Cui, Yan, Lin, Qiang

Parameter Calibration Method of Johnson-Cook Constitutive Model based on Tensile and Compression Tests

2025-01-8242

04/01/2025

In new energy vehicles, aluminum alloy has gained prominence for its ability to achieve superior lightweight properties. During the automotive design phase, accurately predicting and simulating structural performance can effectively reduce costs and enhance efficiency. Nevertheless, the acquisition of accurate material parameters for precise predictive simulations presents a substantial challenge. The Johnson-Cook model is widely utilized in the automotive industry for impact and molding applications due to its simplicity and effectiveness. However, variations in material composition, processing techniques, and manufacturing methods of aluminum alloy can lead to differences in material properties. Additionally, components are constantly subjected to complex stress states during actual service. Conventional parameter calibration methods primarily rely on quasi-static and dynamic tensile tests, offering limited scope in addressing compression scenarios. This paper proposes an inversion

Kong, Deyu, Gao, Yunkai

Developing a Camera-Based Perspective Transformation Method for Quantifying Driver Direct Visibility for Passenger Vehicles

2025-01-8667

04/01/2025

This study outlines a camera-based perspective transformation method for measuring driver direct visibility, which produces 360-degree view maps of the nearest visible ground points. This method is ideal for field data collection due to its portability and minimal space requirements. Compared with ground truth assessments using a physical grid, this method was found to have a high level of accuracy, with all points in the vehicle front varying less than 0.30 m and varying less than 0.6 m for the A- and B-pillars. Points out of the rear window varied up to 2.4 m and were highly sensitive to differences in the chosen pixel due to their greater distance from the camera. Repeatability through trials of multiple measurements per vehicle and reproducibility through measures from multiple data collectors produced highly similar results, with the greatest variations ranging from 0.19 to 1.38 m. Additionally, three different camera lenses were evaluated, resulting in comparable results within

Mueller, Becky, Bragg, Haden, Bird, Teddy

Exploring Hybrid TPMS Designs for Improved Energy Absorption

2025-01-8726

04/01/2025

Triply Periodic Minimal Surface (TPMS) structures have gained significant attention in recent years due to their excellent mechanical properties, lightweight characteristics, and potential for energy absorption in various engineering applications, particularly in automotive safety. This study explores the design, manufacturing, and mechanical performance of both general and hybrid TPMS structures for energy absorption. Three types of fundamental TPMS unit cells—Primitive, Gyroid, and IWP—were modeled using implicit functions and combined to form hybrid structures. The hybrid designs were optimized by employing Sigmoid functions to achieve smooth transitions between different unit cells. The TPMS structures were fabricated using Selective Laser Melting (SLM) technology with 316L stainless steel and subjected to quasi-static compression tests. Numerical simulations were conducted using finite element methods to verify the experimental results. The findings indicate that hybrid TPMS

Liu, Zhe, Wang, MingJie, Guo, Pengbo, Li, Youguang, Lian, Yuehui, Zhong, Gaoshuo

Role of AI in an Autonomous Vehicle Perception Systems: Use of Convolutional Neural Network Approach to Design the Vehicle Perception System

2025-01-8012

04/01/2025

Artificial Intelligence has gained lot of traction and importance in the 21st century with use cases ranging from speech recognition, learning, planning, problem solving to search engines etc. Artificial Intelligence also has played a key role in the development of autonomous vehicles and robots ranging from perception, localization, decision to controls. Within the big AI umbrella there is machine learning which is all about using your computer to "learn" how to deal with problems without “programming". Deep learning is a branch of machine learning based on a set of algorithms that learn to represent the data directly from the input such as an image, text, Sound, etc. Within deep learning there are Convolutional Neural Networks and Recurrent Neural Networks (CNN/RNN). The study here used convolutional neural network approach to perform image/object recognition. Given that the objective of the autonomous or semi-autonomous vehicle is to promote safety and reduce number of accidents, it

Mansour, Iyad, Singh, Sanjay

Responsible AI System Development in Automotive Applications: A Framework

2025-01-8102

04/01/2025

With the surge in adoption of artificial intelligence (AI) in automotive systems, especially Advanced Driver Assistance Systems (ADAS) and autonomous vehicles (AV), comes an increase of AI-related incidents–several of which have ended in injuries and fatalities. These incidents all share a common deficiency: insufficient coverage towards safety, ethical, and/or legal requirements. Responsible AI (RAI) is an approach to developing AI-enabled systems that systematically take such requirements into account. Existing published international standards like ISO 21448:2022 (Safety of the Intended Functionality) and ISO 26262:2018 (Road Vehicles – Functional Safety) do offer some guidance in this regard but are far from being sufficient. Therefore, several technical standards are emerging concurrently to address various RAI-related challenges, including but not limited to ISO 8800 for the integration of AI in automotive systems, ISO/IEC TR 5469:2024 for the integration of AI in functional

Nelson, Jody, Lin, Christopher

Comprehensive Injury Assessment of Reclined Occupants across Varied Seat Configurations with the THUMS Human Body Model

2025-01-8739

04/01/2025

The development of autonomous driving technology will liberate the space in the car and bring more possibilities of comfortable and diverse sitting postures to passengers, but the collision safety problem cannot be ignored. The aim of this study is to investigate the changes of injury pattern and loading mechanism of occupants under various reclined postures. A highly rotatable rigid seat and an integrated three-point seat belt were used, with a 23g, 50kph input pulse. Firstly, the sled test and simulation using THOR-AV in a reclined posture were conducted, and the sled model was verified effective. Based on the sled model, the latest human body model, THUMS v7, was used for collision simulation. By changing the angle of seatback and seat pan, 5 seat configurations were designed. Through the calculation of the volunteers' pose regression function, the initial position of THUMS body parts in different seat configurations was determined. The responses of human body parts were output

Yang, Xiaoting, Wang, Qiang, Liu, Yu, Fei, Jing, Wang, Peifeng, Li, Zhen, Bai, Zhonghao

Modular Dynamometer Testing Framework to Evaluate Energy Impacts of Longitudinal Automated Driving Systems

2025-01-8065

04/01/2025

As longitudinal Automated Driving System (ADS) technologies, such as Adaptive Cruise Control (ACC), become more prevalent, robust testing frameworks that encompass both simulation and vehicle-in-the-loop (VIL) methodologies are essential to ensure system reliability, safety, and performance refinement. Although significant research has focused on ACC algorithm development and simulation testing, existing VIL dynamometer testing frameworks are typically tailored to specific vehicle models and sensor simulation tools. These highly customized approaches often fail to account for broader interoperability while overlooking energy consumption as a key performance metric. This paper presents a novel modular framework for ACC dynamometer testing, designed to enhance interoperability across a diverse range of vehicle platforms, simulation tools, and dynamometer facilities with a focus on evaluating impacts of automated longitudinal control on the overall energy consumption of the vehicle. The

Goberville, Nicholas, Hamilton, Kayla, Di Russo, Miriam, Jeong, Jongryeol, Das, Debashis, Ord, David, Misra, Priyashraba, Crain, Trevor

Solving Vehicle Speed and Acceleration from Video Evidence Using Optimization

2025-01-8683

04/01/2025

Abstract This paper introduces a method to solve the instantaneous speed and acceleration of a vehicle from one or more sources of video evidence by using optimization to determine the best fit speed profile that tracks the measured path of a vehicle through a scene. Mathematical optimization is the process of seeking the variables that drive an objective function to some optimal value, usually a minimum, subject to constraints on the variables. In the video analysis problem, the analyst is seeking a speed profile that tracks measured vehicle positions over time. Measured positions and observations in the video constrain the vehicle’s motion and can be used to determine the vehicle’s instantaneous speed and acceleration. The variables are the vehicle’s initial speed and an unknown number of periods of approximately constant acceleration. Optimization can be used to determine the speed profile that minimizes the total error between the vehicle’s calculated distance traveled at each

Snyder, Sean, Callahan, Michael, Wilhelm, Christopher, Johnk, Chris, Lowi, Alvin, Bretting, Gerald

Occupant Responses in High-Speed Rear Sled Tests: Focus of Initial Position, Seat Strength and ATD Size

2025-01-8731

04/01/2025

The National Highway Safety Administration (NHTSA) recently published an Advanced Notice of Proposed Rulemaking (ANPRM) to evaluate seat performance in rear impacts [1]. The ANPRM was issued partially in response to two petitions requesting an increase in seatback strength requirements and high-speed testing with various size Anthropometric Test Devices (ATDs). To better understand the effect of these requests, this study evaluates ATD responses with two high-speed rear sled conditions, three occupant sizes and various seat designs. Seat designs varied from modern conventional seats with yielding properties to stronger and stiffer seats represented by seat integrated restraint (SIR) designs, and rigidized SIR seats. Twenty-four rear sled tests were analyzed. The tests were matched by crash severity, seat designs (strength), ATD sizes and initial postures (nominal/in-position, leaned forward and leaned outboard). The test data and videos were reviewed to identify time coinciding with

Parenteau, Chantal, Burnett, Roger

Validation of Pedestrian Collision Reconstruction Using the PC-Crash Multibody Pedestrian Model

2025-01-8681

04/01/2025

This study validates the use of the pedestrian multibody model in the simulation software PC-Crash. If reasonable inputs are used, the pedestrian model will yield accurate simulations of pedestrian collisions, particularly in terms of accurately simulating the contact points between the pedestrian and the vehicle and in predicting the throw distance of the pedestrian. This study extends prior studies of the PC-Crash pedestrian multibody model by simulating additional staged collisions, by comparing the results of the model to widely utilized throw distance equations, by providing guidance on inputs for the pedestrian multibody, and by providing documentation of the characteristics of the multibody pedestrian. In addition, two new staged pedestrian collisions are discussed and simulated. This study demonstrates the following: (1) The center of gravity height of the PC-Crash pedestrian model is comparable to the center of gravity height reported for pedestrians in anthropometric data. (2

Rose, Nathan, Smith, Connor, Carter, Neal, Metanias, Andrew

Path Planning and Following Control of All-Wheel Steering Vehicle with Dual Modular Chassis

2025-01-8793

04/01/2025

A large-scale logistics transport vehicle composed of two skateboard chassis is investigated in this paper. This unmanned vehicle with dual-modular chassis (VDUC) is suitable for transporting varying size of goods. The two chassis can be used jointly or driving separately as needed, which enhancing the reconfigurability of transport vehicle. Considering the road environment uncertainty and the rollover safety problem associated with large transport vehicle, this paper proposes the path planning of VDUC using the Artificial Potential Field(APF)+Model Predictive Control(MPC) while incorporating the rollover stability index. Due to the independent operation of the two modular chassis, based on the hierarchical control approach, the path following controller of the two modular chassis are designed separately according to the vehicle’s planned path. Distributed model predictive control is applied to coordinate the front and rear modular chassis, so it can realize the path following for the

Liu, Zuyang, Shen, Yanhua, Wang, Kaidi, wang, Haoshuai

Study of Indian Population’s Eye Point to Adapt Indian Vehicle Design to Indian Anthropometry for Accident Risk Mitigation

2025-01-8665

04/01/2025

India has one of the highest accident rates in the world. Quite a few accidents have been attributed to poor driver visibility. Driver visibility is an important factor that can help mitigate the risk of accidents. The optimal visibility of in-vehicle controls is also essential for improving driver experience. Optimized driver visibility improves driving comfort and gives confidence to the driver, ensuring the safety of drivers and subsequently that of pedestrians. Driver visibility is an important consideration for vehicle occupant packaging and SAE has defined various standards and regulations for the same. These guidelines are defined considering American anthropometry, helping OEMs create global vehicles with uniform checkpoints. However, due to anthropometric differences, a need was felt to capture and analyze Indian-specific eyellipse and eye points. To measure the eye point of the user in a controlled environment, the interiors of a passenger vehicle were simulated using a

P H, Salman, Kalra, Prerita, Rawat, Ashish, Sharma, Deepak, Singh, Ashwinder

Predicting Head Injury Criterion in Real-World Frontal Impacts

2025-01-8709

04/01/2025

Research on modeling head injury metrics and head acceleration waveforms from real-world collisions has been limited compared to vehicle crash pulses. Prior studies have used rectangular, triangular, polynomial, half-sine, and haversine pulse functions to model vehicle crash pulses and have employed more complex approximations for head injury metrics. This study aimed to develop a method to predict 15 ms Head Injury Criterion (HIC15) in frontal passenger vehicle impacts using these simple pulse functions, where only occupant peak head acceleration and head impact duration are known. Vehicle crash tests from the New Car Assessment Program (NCAP) were selected for frontal impacts that included driver occupants. Head acceleration and shoulder belt load channels of Hybrid III 50th percentile male anthropomorphic test devices were collected and separated for training a set of ratios and testing their performance. Rectangular, triangular, quadratic, half-sine, and haversine pulse functions

Westrom, Clyde, Tanczos, Rachel, Adanty, Kevin, Shimada, Sean

Research on Dangerous Driving Behavior Recognition Algorithm Based on LSTM

2025-01-8204

04/01/2025

To address the issue of high accident rates in road traffic due to dangerous driving behaviors, this paper proposes a recognition algorithm for dangerous driving behaviors based on Long Short-Term Memory (LSTM) networks. Compared with traditional methods, this algorithm innovatively integrates high-frequency trajectory data, historical accident data, weather data, and features of the road network to accurately extract key temporal features that influence driving behavior. By modeling the behavioral data of high-accident-prone road sections, a comprehensive risk factor is consistent with historical accident-related driving conditions, and assess risks of current driving state. The study indicates that the model, in the conditions of movement track, weather, road network and conditions with other features, can accurately predict the consistent driving states in current and historical with accidents, to achieve an accuracy rate of 85% and F1 score of 0.82. It means the model can

Huang, Yinuo, Zhang, Miaomiao, Xue, Ming, Jin, Xin

Active and Passive Security Generalization Algorithm and Typical Case Analysis

2025-01-8744

04/01/2025

In order to effectively predict the vehicle safety performance and reduce the cost of enterprise safety tests, a generalized simulation model for active and passive vehicle safety was proposed. The frontal driver-side collision model under the intervention of the Autonomous Emergency Braking (AEB) was created by using the MADYMO software. The collision acceleration obtained from the sled test was taken as the original input of the model to conduct simulation for the working conditions under different sitting postures of the human body. The injury values of various parts of the Hybrid III 50th dummy were read. Based on the correlation between the two, an active and passive simulation model was established through the Back Propagation (BP) neural network. The input of the model was the inclination angle centered on the dummy's waist, and the output was the acceleration of the dummy's head. The results showed that the comprehensive prediction accuracy rate exceeded 80%. Therefore, the

Ge, Wang, fengyao, LV

Improved Distance Estimation in Dynamic Environments through Multi-Sensor Fusion with Extended Kalman Filter

2025-01-8034

04/01/2025

The application of multi-sensor fusion for enhanced distance estimation accuracy in dynamic environments is crucial for advanced driver assistance systems (ADAS) and autonomous vehicles. The Limitations of single sensors such as cameras or radar in adverse conditions motivate the use of combined camera and radar data to improve reliability, adaptability, and object recognition. A multi-sensor fusion approach using an Extended Kalman Filter (EKF) is proposed to combine sensor measurements with a dynamic system model, achieving robust and accurate distance estimation. The research utilizes the Mississippi State University Autonomous Vehicular Simulator (MAVS), a physics-based simulation platform, to generate realistic synthetic datasets incorporating sensor imperfections such as noise and missed detections to create a controlled environment for data collection. Data analysis is performed using MATLAB. Qualitative metrics such as visualization of fused data vs ground truth and

Ebu, Iffat Ara, Islam, Fahmida, Rafi, Mohammad AbdusShahid, Rahman, Mahfuzur, Iqbal, Umar, Ball, John

Drop Test Correlation in Front & Rear Landing Scenario for Two-Wheeler (Motorcycle) using Multibody Simulation

2025-01-8638

04/01/2025

Two wheelers motorcycles are used for many purposes e.g. commuting from one place to another, long highway rides, racing and off-roading. Motorcycles which are used in off-road conditions require higher suspension strokes to absorb large oscillations due to terrain conditions. These motorcycles undergo jumps of varying heights and different vehicle orientations. In some of the dynamic situations front wheel may land on the ground before the rear and in other cases it may be vice versa. To make sure that the vehicle is durable enough to withstand loads in such operating conditions, vehicle drop test was developed in test lab where vehicle is dropped from predefined heights in both front & rear wheel landing conditions. Same test case is simulated in multibody dynamics to capture loads at important connections of the frame. This paper presents the correlation exercise carried out to validate MBD model and simulation process with test data captured during lab test. Accelerations at

Jain, Arvind Kumar, Nirala, Deepak

Application of 1.7GPa Martensitic Steel in Dash Lower Cross Member to Enhance Automotive Frontal Impact Safety

2025-01-8218

04/01/2025

The rapid growth of electric vehicles (EVs) has led to a significant increase in vehicle mass due to the integration of large and heavy battery systems. This increase in mass has raised concerns about collision energy and the associated risks, particularly in high-speed impacts. As a consequence, crashworthiness evaluations, especially front-impact regulations, have become increasingly stringent. Crash speed between the vehicle and the Mobile Progressive Deformable Barrier (MPDB) is increasing, reflecting the growing emphasis on safety in the automotive industry. Moreover, a new frontal pole crash scenario is under consideration for future regulatory standards, highlighting the continuous evolution of crash testing protocols. To ensure occupant protection and battery safety, manufacturers have traditionally used Hot Blow Forming technology for producing closed-loop dash lower cross member components. However, this process is both costly and energy-intensive, necessitating more

Lee, Jongmin, Kim, Donghyun, Jang, Minho, Kim, Geunho, Seongho, Yoo, Kim, Kyu-Rae

Tire–Road Friction Estimation and Classification Based on a CNN using Tire Acoustical Signals for Autonomous Driving Vehicles

2025-01-8761

04/01/2025

Advanced driver assistance systems (ADASs) and driving automation system technologies have significantly increased the demand for research on vehicle-state recognition. However, despite its critical importance in ensuring accurate vehicle-state recognition, research on road-surface classification remains underdeveloped. Accurate road-surface classification and recognition would enable control systems to enhance decision-making robustness by cross-validating data from various sensors. Therefore, road-surface classification is an essential component of autonomous driving technologies. This paper proposes the use of tire–pavement interaction noise (TPIN) as a data source for road-surface classification. Traditional approaches predominantly rely on accelerometers and visual sensors. However, accelerometer signals have inherent limitations because they capture only surface profile properties and are often distorted by the resonant characteristics of the vehicle structure. Similarly, image

Yoon, Youngsam, Kim, Hyungjoo, Lee, Sang Kwon, Lee, Jaekil, Hwang, Sunguk, Ku, Sehwan

Discrepancies between Metadata and Actual Camera Field of View: A Photogrammetric Approach

2025-01-8686

04/01/2025

Camera matching photogrammetry is widely used in the field of accident reconstruction for mapping accident scenes, modeling vehicle damage from post collision photographs, analyzing sight lines, and video tracking. A critical aspect of camera matching photogrammetry is determining the focal length and Field of View (FOV) of the photograph being analyzed. The intent of this research is to analyze the accuracy of the metadata reported focal length and FOV. The FOV from photographs captured by over 20 different cameras of various makes, models, sensor sizes, and focal lengths will be measured using a controlled and repeatable testing methodology. The difference in measured FOV versus reported FOV will be presented and analyzed. This research will provide analysts with a dataset showing the possible error in metadata reported FOV. Analysts should consider the metadata reported FOV as a starting point for photogrammetric analysis and understand that the FOV calculated from the image

Smith, Connor A., Erickson, Michael, Hashemian, Alireza

Improving Modal Frequencies in Class 5 Truck Fuel Cell Tank Structure through Topology Optimization

2025-01-8648

04/01/2025

In addition to electric vehicles (EVs), hydrogen fuel cell systems are gaining attention as energy-efficient propulsion options. However, designing fuel cell vehicles presents unique challenges, particularly in terms of storage systems for heavy hydrogen tanks. These challenges impact factors such as NVH (noise, vibration, and harshness) and safety performance. This study presents a topology optimization study for Hydrogen Energy Storage System (HESS) tank structure in Class 5 trucks, with a focus on enhancing the modal frequencies. The study considers a specific truck configuration with a HESS structure located behind the crew cab, consisting of two horizontally stacked hydrogen tanks and two tanks attached on both sides of the frame. The optimization process aimed to meet the modal targets of this hydrogen tank structure in the fore-aft (X) and lateral (Y) directions, while considering other load cases such as a simplified representation of GST (global static torsion), simplified

Yoo, Dong Yeon, Chavare, Sudeep, Viswanathan, Sankar, Mouyianis, Adam

Adapting the Technology Readiness Level (TRL) Framework to Automated Vehicle Development

2025-01-8671

04/01/2025

Abstract The technological advancements in the automotive industry have seen a significant leap with the introduction of automated driving system (ADS)-equipped Vehicles (AVs), with potential for enhanced safety, efficiency, and mobility. As the development of an AV transitions from the stages of conceptual design to deployment, assessing the maturity of the technology through a structured framework is crucial. This paper proposes the adaptation of the Technology Readiness Level (TRL) framework originally developed by NASA (and adopted widely in a variety of industries) to the AV industry to provide a consistent, understandable, and transparent method to describe an AV product’s stage of development. The TRL framework is mated to the existing safety case framework (SCF) developed in the Automated Vehicle – Test and Evaluation Process (AV-TEP) Mission, a collaboration between Science Foundation Arizona and Arizona State University. The claim that the AV is ready to transition from one

Swaminathan, Sunder, Wishart, Jeffrey, Zhao, Junfeng, Russo, Brendan, Rahimi, Shujauddin

High-Speed FCW & AEB Testing of Tesla Model 3's Across Software Updates

2025-01-8695

04/01/2025

A total of 148 tests were conducted to evaluate the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) systems in five different Tesla Model 3 vehicles between model years 2018 and 2020 across four calendar years. These tests involved stationary vehicle targets, including a foam Stationary Vehicle Target (SVT), a Deformable Stationary Vehicle Target (DSVT), a live vehicle with brake lights, and a SoftCar360 designed for high-speed impact tests. The evaluations were conducted at speeds of 35, 50, 60, 65, 70, 75, and 80 miles per hour (mph) during both daytime and nighttime conditions and utilized early and medium FCW settings. These settings, part of Tesla's Collision Avoidance AssistTM, modify object detection alerts and the timing of visual and auditory warnings issued to drivers. The 2018 to 2020 vehicles initially utilized cameras, radar and ultrasonic sensors (USS) for object detection. Tesla updated their Autoilot software and detection algorithms to a vision

Harrington, Shawn, Nagarajan, Sundar Raman

Synchronizing Real-Time Control in Centralized Automotive E/E Architectures

2025-01-8072

04/01/2025

Automotive technologies have been rapidly evolving with the introduction of electric powertrains, Advanced Driver-Assistance Systems (ADAS) and Over-The-Air (OTA) upgradability. Existing decentralized architectures are not an optimal choice for these applications, due to significant increases in cost and complexity. The transition to centralized architectures enables heavy computation to be delegated to a limited number of powerful Electronic Control Units (ECUs) called domain or zone controllers. The remaining ECUs, known as smart actuators, will perform well defined and specific tasks, receiving new parameters from the dedicated domain/zone controller over a network. Network bandwidth and time synchronization are the two major challenges in this transition. New automotive standards have been developed to address these challenges. Automotive Ethernet and Time Sensitive Networking (TSN) are two standards that are well-suited for centralized architectures. This paper presents a

Ayesh, Mostafa, Bandur, Victor, Pantelic, Vera, Wassyng, Alan, Wasacz, Bryon, Lawford, Mark

Developing a Vehicle-in-Virtual-Environment (VVE) Based Autonomous Driving Function Development and Evaluation Pipeline for Vulnerable Road User Safety

2025-01-8061

04/01/2025

Traditional methods for developing and evaluating autonomous driving functions, such as model-in-the-loop (MIL) and hardware-in-the-loop (HIL) simulations, heavily depend on the accuracy of simulated vehicle models and human factors, especially for vulnerable road user safety systems. Continuation of development during public road deployment forces other road users including vulnerable ones to involuntarily participate in the development process, leading to safety risks, inefficiencies, and a decline in public trust. To address these deficiencies, the Vehicle-in-Virtual-Environment (VVE) method was proposed as a safer, more efficient, and cost-effective solution for developing and testing connected and autonomous driving technologies by operating the real vehicle and multiple other actors like vulnerable road users in different test areas while being immersed within the same highly realistic virtual environment. This VVE approach synchronizes real-world vehicle and vulnerable road user

Chen, Haochong, Cao, Xincheng, Guvenc, Levent, Aksun Guvenc, Bilin

The Effects of Collision-Related Power Loss on Toyota Safety Sense 2.5+ Event Data

2025-01-8713

04/01/2025

Toyota vehicles equipped with Toyota Safety Sense (TSS) can record detailed information surrounding various driving events, including crashes. Often, this data is employed in accident reconstruction. TSS data is comprised of three main categories: Vehicle Control History (VCH), Freeze Frame Data (FFD), and image records. Because the TSS data resides in multiple Electronic Control Units (ECUs), the data recording is susceptible to catastrophic power loss. In this paper, the effects of a sudden power loss on the VCH, FFD, and images are studied. Events are triggered on a TSS 2.5+ equipped vehicle by driving toward a stationary target. After system activation, a total power loss is induced at various delays after activation. Results show that there is a minimum time required after system initiation in order to obtain full VCH, FFD, and image records. Power losses occurring within this time frame produce incomplete records. Data accuracy is unaffected, even in partial records.

Getz, Charles, DiSogra, Matthew, Spivey, Heath, Johnson, Taylor, Patel, Amit

A Model for the Design of Automated Vehicle Event Data Recorders

2025-01-8678

04/01/2025

When vehicle accidents occur, investigators rely on event data recorders for accident investigations. However current event data recorders do not support accident investigation involving automated or self-driving vehicles when there is state information that needs to be recorded, for example ADS modes, changes in the ODD that the vehicle operates under, and the various states of vehicle features such as intelligent cruise control, automated lane changes, autonomous emergency braking, and others. In this paper, we propose a model to design new types of event data recorders that supports accident investigations involving automated vehicles when there is state information to be recorded. The model is generic enough to be adapted to any automation level and any set of automated vehicle functional features. The model has been instantiated to a specific ADAS system.

Pimentel, Juan

Empirical Analysis on Machine Vision Recognition of Green Bike Lanes for Vulnerable Road Users Safety

2025-01-8017

04/01/2025

Deliberate modifications to infrastructure can significantly enhance machine vision recognition of road sections designed for Vulnerable Road Users, such as green bike lanes. This study evaluates how green bike lanes, compared to unpainted lanes, enhance machine vision recognition and vulnerable road users safety by keeping vehicles at a safe distance and preventing encroachment into designated bike lanes. Conducted at the American Center for Mobility, this study utilizes a vehicle equipped with a front-facing camera to assess green bike lane recognition capabilities across various environmental conditions including dry daytime, dry nighttime, rain, fog, and snow. Data collection involved gathering a comprehensive dataset under diverse conditions and generating masks for lane markings to perform comparative analysis for training Advanced Driver Assistance Systems. Quality measurement and statistical analysis are used to evaluate the effectiveness of machine vision recognition using

Ponnuru, Venkata Naga Rithika, Das, Sushanta, Grant, Joseph, Naber, Jeffrey, Bahramgiri, Mojtaba

Effect of Aftermarket Modifications on ADAS Functionality – 2021 Ford F-150 Light Vehicle

2025-01-8057

04/01/2025

Both automotive aftermarket vehicle modifications and Advanced Driver Assistance Systems (ADAS) are growing. However, there is very little information available in the public domain about the effect of aftermarket modifications on ADAS functionality. To address this deficiency, a research study was previously performed in which a 2022 Chevrolet Silverado 1500 light truck was tested in four different hardware configurations. These included stock as well as three typical aftermarket configurations comprised of increased tire diameters, a suspension level kit, and two different suspension lift kits. Physical tests were carried out to investigate ADAS performance of lane keeping, crash imminent braking, traffic jam assist, blind spot detection, and rear cross traffic alert systems. The results of the Silverado study showed that the ADAS functionality of that vehicle was not significantly altered by aftermarket modifications. To determine if the results of the Silverado study were

Bastiaan, Jennifer, Muller, Mike, Morales, Luis

RGB2BEV-Net: A PyTorch-Based End-to-End Pipeline for RGB to BEV Segmentation Using an Extended Dataset for Autonomous Driving

2025-01-8023

04/01/2025

In this study, we introduce RGB2BEV-Net, an end-to-end pipeline that extends traditional BEV segmentation models by utilizing raw RGB images with Bird’s Eye View (BEV) generation. While previous work primarily focused on pre-segmented images to generate corresponding BEV maps, our approach expands this by collecting RGB images alongside their affiliated segmentation masks and BEV representations. This enables direct input of RGB camera sensors into the pipeline, reflecting real-world autonomous driving scenarios where RGB cameras are commonly used as sensors, rather than relying on pre-segmented images. Our model processes four RGB images through a segmentation layer before converting them into a segmented BEV, implemented in the PyTorch framework after being adapted from an original implementation that utilized a different framework. This adaptation was necessary to improve compatibility and ensure better integration of the entire system within autonomous vehicle applications. We

Hossain, Sabir, Lin, Xianke

Leveraging the Automated Mobility Partnership (AMP) to Support the Evaluation of Safety of the Intended Functionality (SOTIF) in Automated Driving Systems

2025-01-8674

04/01/2025

The Automated Mobility Partnership (AMP) is a consortium of industry and academic stakeholders dedicated to advancing Automated Driving Systems (ADS) through a comprehensive suite of tools, datasets, and methodologies. The AMP portal integrates events from over 35 million miles of naturalistic driving data including thousands of annotated crashes and near-crashes and a decade of U.S. police-reported crash data curated by the Virginia Tech Transportation Institute. The portal enables data discovery, visualization, processing, and analysis through secured web access. This paper briefly describes the AMP portal and examines its utility in developing and evaluating the safety of ADS using standardized processes. For the examination, we provide examples based on generic automated driving functions, guided by the Safety of the Intended Functionality (SOTIF) framework. The results show that AMP is instrumental in identifying recorded real-world cases in which the hazardous behavior of a

Antona-Makoshi, Jacobo, Williams, Vicki, Ali, Gibran, Sullivan, Kaye, Terranova, Paolo, Kefauver, Kevin, Hatchett, Alex

Decelerations for Vehicles with Anti-Lock Brake Systems (ABS) during Wet-to-Dry Transitions on Asphalt and Concrete Road Surfaces

2025-01-8703

04/01/2025

The braking performance of newer anti-lock braking system (ABS) equipped vehicles on roads with varying wetness levels is not well studied. Two late-model ABS-equipped vehicles were used to perform ABS-engaged braking tests on dry and wet asphalt and concrete surfaces from which vehicle speed and deceleration as a function of time were calculated. Tests were initially conducted on a dry surface before a water truck distributed water onto the road to create a wet road condition. A continuous series of tests were then performed until the road dried and the cycle was repeated multiple times. Across all tests of both vehicles on both road surfaces, deceleration levels generally decreased when the road was wet and returned to dry levels only when less than 25% of the road surface remained wet. Also, wet deceleration levels were high compared to the historical values used for wet roads. These findings provide a useful and readily identifiable boundary between what can be considered a dry and

Miller, Ian, King, David, Siegmund, Gunter

Machine Learning-Enabled Optimization of Vehicle Restraint Systems – Demonstration in a Real-World Crash Scenario

2025-01-8722

04/01/2025

Vehicle restraint systems, such as seat belts and airbags, play a crucial role in managing crash energy and protecting occupants during vehicle crashes. Designing an effective restraint system for a diverse population is a complex task. This study demonstrates the practical implementation of state-of-the-art Machine Learning (ML) techniques to optimize vehicle restraint systems and improve occupant safety. An ML-based surrogate model was developed using a small Design of Experiments (DOE) dataset from finite element human body model simulations and was employed to optimize a vehicle restraint system. The performance of the ML-optimized restraint system was compared to the baseline design in a real-world crash scenario. The ML-based optimization showed potential for further enhancement in occupant safety over the baseline design, specifically for small-female occupant. The optimized design reduced the joint injury probability for small female passenger from 0.274 to 0.224 in the US NCAP

Lalwala, Mitesh, Lin, Chin-Hsu, Desai, Megha, Rao, Shishir

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