Journal Articles - SAE Mobilus

SAE journals provide rigorously peer-reviewed, archival research by subject matter experts--basic and applied research that is valuable to both academia and industry.

Items (11,226)
Investigating high-speed aerodynamics and aerothermodynamics presents a significant challenge for manned re-entry missions. The thermal effects on the surface of the re-entry vehicle and atmospheric stresses are primarily influenced by re-entry type and flight trajectory. This study investigates the monostability characteristics and aerothermodynamics of the Orion re-entry vehicle by incorporating static fins onto the aft fuselage of the vehicle, ensuring the lift-to-drag ratio remains unaffected throughout the numerical simulations. The study evaluated two different Mach numbers of 7 and 9 at various altitudes. The models were analyzed at different angles of attack from 0° to 90° in increments of 15°. The model with static fins exhibits a displacement in the monostable trim point, a reduction in the heat-shield pressure coefficient, and enhanced heat transfer throughout the re-entry vehicle.
Sabapathy, Santhosh
Agricultural vehicles operating in rough environments experience increased fatigue damage accumulation, which may decrease machine safety and reliability. Autonomous agricultural machines offer an opportunity to incorporate fatigue damage considerations into path planning. This work investigates whether machine learning can predict fatigue damage to a tractor chassis using light detection and ranging (LiDAR)-based terrain features, vehicle speed, and rotational vehicle state data (e.g., triaxial angle, angular velocity, and angular acceleration). Fatigue damage was estimated using the Rupp filter and the Durability Transfer Concept. Following poor predictive performance of the machine learning models, an exploratory analysis of damage histograms, dominant frequency, and acceleration magnitude was performed. Results indicated that most estimated fatigue damage occurred in the 0–2 Hz band, which coincides with the frequency range of terrain-induced acceleration. On-road driving led to
Govers, Megan EmilyHamilton-Wright, AndrewHassan, MarwanOliver, Michele L.
Passenger vehicles experience severe packaging constraints around the instrument panel, rendering glove-box operation a critical yet ergonomically underexplored interaction. Although glove-box interaction occurs frequently during routine vehicle use, its potential implications for ergonomic risk remain largely unexamined in existing automotive research. To isolate the influence of driver-side packaging constraints from component-level design effects, this study adopts a comparative evaluation of driver and co-driver glove-box interaction as a built-in control condition. This study introduces a discomfort-based evaluation framework that integrates Digital Human Modeling with India-specific anthropometric datasets. A composite loss-function scoring model is developed to quantify functional usability differences across four glove-box configurations, defined by variations in latch placement (center or side) and storage-bin mechanisms (fixed or rotating). Indians are utilized to assess
Jujjavarapu, SreeramRajakumaran, SriramKota, SrinivasKotkunde, NitinJasti, Naga Vamsi Krishna
The present review evaluates recent advances in the development of Welding-Based Additive Manufacturing (WBAM) technologies using arc, high-energy density, solid-state, and hybrid welding systems by providing an interdisciplinary assessment of technological aspects, sensing, process optimization, and multi-process strategies. It is concluded that, in spite of considerable progress in process optimization and control, there exist numerous paradoxes associated with relationships among process conditions, structure, and properties, especially those related to heat input effects on material microstructure and performance. An important finding is the fragmentation of predictive modeling approaches, where physics-based and data-driven methods remain inadequately integrated, limiting generalizability and accuracy. Another important conclusion is related to the dominance of the effect of thermal history and multi-physical phenomena on the mechanical performance of the material produced by WBAM
Santhana Babu, A.V.John Rajan, A.Mishra, AishwaryChakravarthy, P.Jayabalakrishnan, D.
Knowing a detailed operating cycle is critical for developing and testing equipment. Operating cycles can be separated by two clear distinctions: (1) regulatory or non-regulatory and (2) application at the engine-only or full machine level. The Environmental Protection Agency’s (EPA) Nonroad Transient Cycle (NRTC) may be a good representation of engine use in many types of equipment, but there is a gap in standardized and validated drive cycles specifically for nonroad material handlers. Lacking a standardized drive cycle makes it difficult to accurately benchmark machine performance and validate new powertrain technologies. The objective of this investigation is to illustrate the development of a custom drive cycle augmented with real-world customer use data that serves multiple purposes: (1) understand the range of operation and utilization that formulated inputs for electrified architecture analysis and (2) develop a repetitive and consistent maneuver to establish baseline energy
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, John
1Systems level and integration testing are an integral part of the design and development of Automated Vehicles (AVs). Measurement science plays a pivotal role in testing to ensure the safe and efficient operation of AVs. This science establishes a common understanding of the units of measurement, crucial in linking human activities. This article describes the significance of measurement in studying interactions between key system technologies in AVs, including AI for perception, sensing, communications, and cybersecurity. To address the complexities of these interactions, a novel, adaptable, and interactive framework called the System Technology Interaction Model (STIM) is introduced. STIM considers both designed and emergent interactions between these system technologies, allowing AV developers to explore tailored experiments with the flexibility of filtering for focused testing. The framework currently models system interactions statically, not in real-time, to define potential
Griffor, Edward R.Arora, MahimaKootbally, ZeidNguyen, Vinh
Occupant protection has been at the forefront of risk evaluation regarding vehicle crashworthiness design. However, the vehicle is a member of a larger transportation system with varied stakeholders. This article identifies an opportunity for assessing risk in a crash event through emerging safety science paradigms. Conventional Safety I and Safety II frameworks handle well-defined hazards but falter with uncertainty, variability, and emergent behaviors in real crashes. A comprehensive literature review was performed on peer-reviewed research to situate automotive crash safety risk within the Safety III paradigms. The review addresses two questions: (1) How is “risk” defined across the crash safety literature and adjacent safety science domains? and (2) What limitations arise from these definitions in practice? Findings show a dominant probabilistic framing alongside a minority of system-oriented interpretations. Current crash safety practice lacks a coherent, system-level definition
Rye, Patrick J.
A novel looped-freezing mean approach based on Detached Eddy Simulation (DES) approach is developed in context of assessing underhood cooling performance in heavy-duty vehicles. The method involves computing a temporally averaged flow field from DES simulations, which is then frozen and used by the energy solver to predict temperature distributions. This process is iteratively repeated until a statistically steady-state temperature field is achieved. It is demonstrated that traditional DES approach demonstrates superior accuracy in capturing forced convection heat transfer compared to the Reynolds-Averaged Navier–Stokes (RANS) method. The validation against experimental data for flow over a heated sphere at a Reynolds number of 105 shows that DES yields Nusselt numbers with better correlation than RANS. However, it is observed that DES approach captures unsteady flow features that introduce temporal fluctuations in heat transfer. In the context of underhood cooling evaluations where
Holay, SarangSankar, HariDixit, PritishSingh, Ramanand
Large language models (LLMs) have shown remarkable capabilities for perceiving driving environments and making interpretable, logical decisions for autonomous driving. However, their potential for more comprehensive driving strategies, especially concerning energy efficiency, remains underexplored. Most existing studies primarily focus on driving safety, which may inadvertently increase energy consumption. To address this issue, this study explores the use of LLMs as high-level controllers to jointly optimize driving safety and energy efficiency. A textual prompt is designed for the LLM, incorporating few-shot examples that describe scenarios, states, and actions. The LLM processes the scenario and state prompts describing the surrounding traffic environment. It generates a high-level control signal, which is then translated into low-level vehicle motion commands in a high-fidelity traffic simulator with realistic physics, vehicle dynamics, road slopes, and network topology
Wang, HaoyuLi, ZhenningWang, SiyingZhou, ZijingZhang, XiangYang, ZhifengOu, Shiqi (Shawn)Qi, Hao
In the present study, research was conducted to increase the combustion efficiency in a diesel engine by adding 100 and 200 ppm aluminum powder to diesel and biodiesel (produced from 10% spent coffee ground oil and 90% waste cooking oil) blends. Aluminum powder is a flammable metal. Due to this feature, it has been used as an additive to liquid fuels in many studies in the literature. In general, it has been reported that thermal efficiency increases with the addition of aluminum particles. However, the high explosion sensitivity of aluminum can affect its stable combustion. In addition, Al is a metal that can be easily oxidized. Therefore, coating aluminum is considered a good solution. Stearic acid has been suggested in the literature as a suitable material for coating aluminum. In this study, stearic acid, a saturated fatty acid, was used to coat aluminum particles. Stearic acid is a good surfactant, hydrophobic substance, and plasticizer. It is also a more environmentally friendly
Kül, Volkan SabriAkansu, Selahaddin OrhanSarıtaş, Mehmet
Over the last few years, there has been an uptick in the exploration and implementation of aluminum high-pressure die casting (HPDC) mega-castings as replacements for conventional stamped steel parts in vehicles. This trend is expected to increase with common justifications, including claims of reduced costs and lower environmental impacts associated with the replacement of dozens of individual parts with a single casted piece, along with reduced demands on associated tooling and machinery. However, the data and literature to support these claims are limited and at times contradictory, with some studies showing increased costs and energy demands for mega-casting technologies. This study presents the results of a literature review and a gate-to-gate life cycle inventory (LCI) adapted from conventional HPDC aluminum casting unit processes that may be used to quantify potential life cycle global warming potential (GWP), cumulative energy demand (CED), and other environmental impacts of
Sebastian, BrandieBalzer, Russ
Distributed drive electric vehicles (DDEVs) provide enhanced maneuverability through independent wheel torque control, but coordinating precise path tracking with lateral stability remains challenging under aggressive driving conditions. This paper presents a coordinated control strategy that integrates model predictive control (MPC) for path tracking with a proportional gain controller for stability regulation. The proposed framework adopts a hierarchical design. The path tracking control leverages MPC to compute front steering commands while accounting for vehicle dynamics and preview errors. The stability adjustment uses dual proportional gain controllers to generate an additional yaw moment, which is adaptively balanced through a phase plane coordination mechanism, enhancing yaw stability during path tracking. The generated yaw moment is subsequently distributed to individual in-wheel motors with an optimization torque allocation method, respecting tire force limitations. The
He, YangZhu, YuzhengGuo, RuixinZhu, YueyingXing, ChaoLiu, ShuangxiLin, Yier
Decarbonization efforts achieved through electrification in nonroad mobile machinery can realize a reduction in fuel consumption of more than 20%, thanks to concepts familiar to light-duty passenger vehicles. This case study compares the results of a hybrid-electric material handler to its conventional counterpart, utilizing machine-specific drive cycles presented in part one of this paper series. The hybrid prototype features an extended-range electric vehicle (EREV) powertrain that demonstrated substantial energy efficiency improvements. Specifically, there was a reduction in equivalent fuel consumption of 75% when operating in electric-only mode, and 33% when maintaining the battery by charging with an on-board generator. Together, the efficiency improvements can be extrapolated over a low-intensity, 8-h shift characterized by significant idle time and highly dynamic engine load for a 47% reduction in net energy consumption. Key technologies that led to this improvement included
Czarnecki, AlexanderGoodenough, BryantWorm, JeremyRobinette, DarrellLaTendresse, PhilWestman, JohnSubert, DavidHeath, MatthewKiefer, DylanBlack, Andrew
Abstract This study investigates and evaluates systematically the combustion, performance, and emissions characteristics of heavy-duty diesel engines fueled by diesel–ammonia–compressed natural gas triple blends. While dual-fuel systems are well-documented, the interactive effects of ammonia and CNG within a single compression ignition (CI) engine remain largely unexplored. Experiments were conducted on a 300 Nm, 660 rpm diesel engine by testing pure diesel, diesel–ammonia blends (10–20 wt.% aqueous ammonia), and triple-fuel mixtures containing 10% of the total energy from compressed natural gas. Pure diesel was first tested to provide baseline data, and subsequently blends were tested for a comparative study. The primary contribution of this work is the identification of a synergistic effect of the fuel triple blends on engine performance and emissions. Results indicate that all fuel blends improve thermal efficiency and reduce fuel consumption compared to conventional diesel. The
Sinkala, HappySarıtaş, MehmetKül, Volkan SabriAkansu, Selahaddin OrhanÜnalan, Sebahattin
Trajectory tracking control is a core technology in intelligent vehicle autonomous driving systems, directly influencing both driving safety and control accuracy. To overcome the limitations of traditional model predictive control (MPC) in real-time performance under complex operating conditions, as well as the limited robustness of linear quadratic regulators (LQR) against system uncertainties, this article proposes a hybrid iterative LQR–MPC (ILQR-MPC) control strategy. First, a dynamic model of the intelligent vehicle is developed to capture its behavior during high-speed driving and cornering. Next, an ILQR-MPC hybrid framework is designed. By exploiting the rapid iterative optimization capabilities of the ILQR algorithm, an initial control sequence is generated for the MPC, thereby reducing the computational load during MPC’s online rolling-horizon optimization. This approach preserves MPC’s advantages in handling constraints and maintaining robustness against parameter variations
Lai, FeiSun, JunhaoHuang, Chaoqun
The decarbonization of heavy-duty trucks (HDTs) is a crucial path for China to achieve its “dual-carbon” goals and transition to decarbonized freight transport. Zero-carbon fuels are key alternatives to fossil fuels for these high-emission vehicles. This study develops an integrated scenario analysis framework to quantify the theoretical CO₂e emission trajectories of China’s long-haul HDT fleet from 2020 to 2060. Functioning as a macro-level stress test, the model derives theoretical equivalent stock from anticipated logistics turnover demand, integrating them with well-to-wheel (WTW) emission factors under six distinct policy stringencies (Projects 1 through 6), representing varying paces of fossil fuel vehicle phase-out. The results demonstrate that policy stringency primarily governs the timing and depth of emission reductions, while fuel technology defines the minimum achievable emission level. Three-dimensional visualization analysis reveals a nonlinear “emission cliff” under
Wu, YunmeiHuang, HuaLi, RuiHe, GuijiaLiu, BoLiu, RuoweiXie, Yongliang
This study presents a torque distribution strategy for dual-motor electric vehicles utilizing a Deep Deterministic Policy Gradient reinforcement learning algorithm designed to optimize energy consumption. By using a simplified architecture and replicable reward functions, the proposed agents rely exclusively on standard CAN bus signals, commanded longitudinal force, and the motors’ velocities, eliminating the need for specialized sensors or complex plant models. Two reinforcement agents are trained using two different reward functions: power-based and State of Charge-based. These agents are validated through high-fidelity CarSim–Simulink co-simulations across soft, medium, and severe acceleration scenarios, in which they demonstrate superior performance to traditional adaptive methods. In the most demanding scenario, a typical adaptive strategy achieves an additional 7.8% of power consumption and 85% of optimal energy recovery, while the proposed reinforcement learning strategies reach
Meléndez-Useros, MiguelViadero-Monasterio, FernandoLópez-Boada, María JesúsLópez-Boada, Beatriz
Autonomous Vehicles (AVs) offer unprecedented opportunities to design control strategies that could be able to simultaneously enhance safety, performance, user experience, time efficiency, and the environmental impact of mobility. However, as automation levels increase, a paradigm shift becomes not only necessary but imperative: the integration of human needs into mobility objectives. This includes not only traditional comfort considerations but also minimizing Motion Sickness (MS), a largely under-explored challenge in control strategy design. In recent literature, several methodologies for modeling and mitigating MS have been proposed, yet their integration into vehicle control logics remains limited, often restricted to isolated and specific case studies, with the research area largely unexplored, particularly with respect to the generalization of the proposed methods. This work introduces a theoretically grounded multi-objective Nonlinear Model Predictive Control (NMPC) framework
Ponticelli, LorenzoBottiglione, FrancescoRini, GabrieleTimpone, FrancescoSakhnevych, Aleksandr
This article describes multi-body dynamics simulation to investigate door jitter issues caused by the limiter during door operations. A simulation model integrating a rigid limiter and a flexible door-body system was developed to replicate the dynamic process of wide-angle door opening/closing. Through iterative refinements—including correlation of simulation results with test data, optimization of internal door connection methods, and solid-element hinge modeling—simulation accuracy was improved to over 89.7%. Using the validated model, quantitative metrics were established to evaluate door jitter severity. Key parameters that influence the door operation smoothness were identified, and an optimization scheme was proposed for a specific vehicle model, incorporating slope-holding performance requirements under hill-parking conditions. Finally, prototype testing validated the approach’s effectiveness. The developed simulation method provides a technical foundation for virtually
Xiao, YongfuDeng, JianjiaoLi, JingtanYang, TaoHou, HangshenHan, ChaoGao, MengWang, YiqiLiu, Yihong
An accurate air spring model is essential for the design and optimization of air suspension systems to achieve superior performance. This article presents a novel stiffness model for a rolling lobe air spring (RLAS), formulated using stiffness characteristic parameters. Prediction models for these parameters, including effective area and its change rate, as well as effective volume and its change rate, are derived through geometric analysis, based on polynomial fitting of the irregular piston contour. The local contour cone angle of the piston is determined by differentiating the polynomial function, capturing the geometry-dependent variation across the profile. Additionally, a nonlinear hysteresis model for the rubber bellows is integrated, combining a Berg friction component and a Kelvin-Voigt fractional derivative viscoelastic model to represent the amplitude- and frequency-dependent behavior of the RLAS. The proposed model is parameterized through quasi-static and dynamic bench
Xia, XiaojunZhang, HongZou, YiYe, LeiLu, YiChen, RuiZou, HantongWang, Yang
Corner module vehicles (CMVs) achieve the decoupling of driving, braking, steering, and suspension, significantly enhancing vehicle handling potential, but under extreme operating conditions, the interactions between actuators severely constrain the improvement of vehicle handling performance. In order to mitigate conflicts between subsystems and enhance vehicle handling stability, a hierarchical hybrid game–based limit stability control method for CMVs is proposed in this article. Taking into account the handling potential of subsystems under limit conditions, a Stackelberg leader–follower game is designed by first designating Direct Yaw moment Control (DYC) as the leader and Active Rear Steering (ARS) as the follower. Subsequently, the DYC–ARS and Active Suspension System (ASS) were constructed into a non-cooperative game system, and the Nash equilibrium solution was solved through iteration. The lower-level controllers, respectively, established a tire force distribution model that
Peng, JinxinXiao, FengKe, YuanJin, Liqiang
In this article, the aerodynamic features of two configurations of Lotus EMEYA are introduced. The first configuration includes a fixed air dam and an active rear spoiler (ARS) assembly, which has two active blades in order to obtain the aerodynamic drag and lift performance required. The second configuration includes an Active Air Dam (AAD) assembly and a gurney flap mounted on the ARS in order to achieve more aggressive aerodynamic performance. The aerodynamic bandwidths and the lift balances of both configurations are demonstrated, and the strategies of active aero components of the two configurations are also introduced. Through active aerodynamics and control strategies, the two configurations of Lotus EMEYA can meet the performance requirements of users in different scenarios.
Yuan, QingpengYang, LeiLi, BoNi, LiTo, Chi HinXiong, Zhenfeng
Accurate prediction of load distribution in multi-bolt metal–composite joints relies heavily on high-fidelity modeling of single-bolt joint stiffness. Current models, however, inadequately capture the complex effects of bolt–hole clearance, including delayed load take-up and reduced bearing chord stiffness, as well as multi-interface friction interactions. To overcome these limitations, quasi-static tests were conducted on single-bolt, single-lap aluminum–CFRP joints with varying clearances. By integrating experimental findings with an analysis of the load-transfer mechanisms, we identified five distinct loading states and formulated corresponding analytical load-deformation equations along with explicit transition criteria, culminating in a novel piecewise-linear stiffness model. Enhancements over traditional tri-linear models encompass: (a) subdivision of the transition region into separate local and global slip phases, facilitating an accurate representation of asynchronous slip
Liu, HaolongSun, QingpingLiu, YangZhao, QiLiu, Yue
The reliability of welded joints is a vital factor in modern manufacturing, directly affecting product performance and durability. This study investigates methods to enhance the mechanical and metallurgical quality of butt joints in AISI 304L stainless steel welded by the gas tungsten arc (GTA) process. A systematic experimental design was implemented using the Taguchi method with an L9 orthogonal array, considering welding current, gas flow rate, and travel speed as the main parameters. To determine overall weld performance, the joints were characterized by measuring ultimate tensile strength (UTS), yield strength, percentage elongation, and examining their microstructural morphology. An experimental strategy based on the Taguchi approach has been implemented. The welding performance of the material was investigated, and the process parameters were optimized using multiresponse optimization through principal component analysis (PCA), incorporating an orthogonal array design, signal-to
Ghosh, NabenduRoy, Angshuman
Letter from the Editor-in-Chief
Hardy, Warren N.
Letter from the Guest Editor
Tylko, Suzanne
Autonomous vehicles exhibit extremely strong nonlinearity during drift. However, existing autonomous drift algorithms often neglect previewed path curvature and offer only limited consideration of road surface uncertainty because of the influence of vehicle nonlinear dynamics, which can affect tracking accuracy and robustness of drift control. To solve these problems, this study proposes a robust optimal drift control framework based on curvature preview. First, a preview vehicle kinematic model is constructed, and a preview model predictive control path-tracking controller that considers the forthcoming curvature is designed. Through the analysis of equilibrium points with additional yaw moment, a robust optimal drift controller is developed, which employs a three-degrees-of-freedom vehicle model with an additional yaw moment. This controller adopts integral sliding mode control with a super-twisting algorithm (STA) and exhibits good stability, which is verified through Lyapunov
Gan, YurunSong, ZiyuGu, TongtongDing, HaitaoXu, NanZhang, Jianwei
A full lithium-ion battery (LIB) pack has hundreds to thousands of cells, coolant flow lines and channels, and channel bends to control cell temperature within its operating window and minimize cell internal resistance, aging, and fire risk. A 75 kWh LIB pack has four modules, and each has 23–25 bricks. Two challenges in battery state predictions for hot and subzero temperatures are battery temperature (Tbatt ) and coolant flow within the whole pack. In this work, a 1D 75 kWh full-pack model with its thermal management system is developed using a holistic reverse-engineering method, which can predict Tbatt at any bricks/modules and inlet/outlet coolant flow characteristics. A Tesla Model Y equipped with dual e-motors is tested on an in-house state-of-the-art chassis dynamometer. The test data at V = 60–80 km/h, 100–150 A constant discharge, and Tbatt = −10°C to 40°C are used to develop the model. The 75 kWh pack model features 4000+ cylindrical cells (96S46P, Panasonic 21700-format
Sok, RatnakKusaka, Jin
Diesel engines used for the main power supplier of submarine normally run in high back pressure and low intake pressure, causing unstable performances. Furthermore, when a submarine runs under the sea the exhaust pipe of the diesel engine is under the seawater. Once the lowest pressure in the exhaust pipe is not sufficient to push all the water out, the water will flow into the exhaust pipe and damage the diesel engine. Modeling can provide a useful guide for designing diesel engines, intake and exhaust pipes, and turbocharging systems to avoid water flowing into diesel engine. However, existing simulation methods cannot well simulate the exhaust system of an underwater diesel engine, in which the interface between the liquid water and the exhaust gas is variable. To overcome the drawbacks of existing simulation methods in handling the variable interface between the two phases, a variable interface finite volume method (FVM) is proposed, and a corresponding model is developed in this
Guo, DongshaoZhang, LichengYang, ShiyouSun, YongAbidin, ZainalLin, Shujun
Research Question/Methods The study examined abdominal injuries of 87 belted occupants in CIREN frontal crashes for sex-based differences in abdominal injury patterns. It introduced a more anatomically detailed method for identifying injury locations in an abdominal-pelvic region that includes skeletal structures. The study introduces and applies a novel Abdominal New Injury Severity Score (AbNISS) to address limitations of traditional AIS coding in capturing sex-based differences in injury patterns. The operative reports/EDR/imaging data in CIREN cases enabled identification of sex-specific crash outcomes. The dominant analytical motif is Bertrand Russell’s knowledge by acquaintance and definite descriptions. Results Females had a higher rate of moderate to severe abdominal injuries than males: Only females sustained AIS 5 injuries, lumbar Chance fractures, posterior pelvic arch injuries, and more AIS 2, 3, and 4 injuries, with more injuries in superior-mid, left-superior, and medial
Halloway, DaleCurry, WilliamSomasundaram, KarthikPintar, Frank
Subaru has developed vehicle-based Injury Severity Predictions (ISP) models using data from the National Automotive Sampling System Crashworthiness Data System (NASS-CDS) covering calendar years 1999–2015, for integration into Advanced Automatic Collision Notification (AACN) systems. This study evaluates the accuracy of these ISP models by comparing predictions derived from Subaru vehicle telemetry with actual Injury Severity Scores (ISS) of transported occupants. Two crash databases were utilized: Subaru Telematics Assisted Accident Research (STAAR) data for calendar years 2021–2024, which includes Automatic Collision Notification (ACN) data, police reports, emergency medical services (EMS), and medical records from the medical centers across Michigan; and the Fatality Analysis Reporting System (FARS) data for calendar years 2021–2023, matched with ACN data to supplement serious injury cases. ISS values were obtained from medical records in STAAR, while fatal cases in FARS were
Ejima, SusumuZhang, PengCunningham, KristenWang, Stewart
This study aims to explore and evaluate the effect of various foot positions on the kinematic and kinetic response of the lower extremity during frontal crashes using a realistic vehicle interior. Frontal impact sled tests were performed with the Test Device for Human Occupant Restraint, 50th-percentile Male (THOR-50M) and Test Device for Human Occupant Restraint, 5th-percentile Female (THOR-05F) anthropometric test device (ATD) in the driver’s seat of a midsize SUV testing buck (with realistic interior components including an instrument panel with steering wheel and steering wheel airbag, seat, three-point seat belt with pretensioner and force-limiter, accelerator pedal, brake pedal, knee airbag, and seat belt retractor pretensioner). Six sled tests were performed in two principal directions of force (PDOF) [three each in frontal (0°) and oblique (−20°) configurations]. The right foot was positioned on the accelerator pedal, fully on the brake, and half on the brake. A single test was
Noss, JuniorDonlon, John-PaulMorris, AnnaSamier, GermainPark, JosephForman, Jason
Aims of the research This study aims to modify the lower body (the pelvis, thigh, and leg) of the mid-sized male pedestrian dummy FE model by considering the latest version of the physical dummy and to evaluate both the accuracy by comparing test results of the past studies and the biofidelity specified in SAE J2782 in both component and full-scale validations. Methods 1 Component validation The validation of the modified pelvis model was performed in dynamic lateral compression simulations. The sacrum and the pubis force-deflection responses of the iliac or the acetabulum impact were measured. The modified thigh and leg models were evaluated in a dynamic 3-point lateral bending simulation, measuring the force-deflection responses. The results from the simulations were compared with test results and the biofidelity requirements. 2 Full-scale validation The whole-body model was updated by incorporating these modified component models. The model of the generic buck developed for the
Asanuma, HiroyukiGunji, YasuakiMori, FumieNagashima, Akiko
Objective: This study investigated injury outcomes and body kinematics in obese occupants exposed to frontal impacts while seated in reclined postures. With increasing interest in non-traditional seating configurations and a growing population of obese vehicle occupants, the objective was to evaluate how seat stiffness and restraint features influence injury patterns and whole-body excursions. Methods: Nine obese post-mortem human surrogates (PMHS; mean age: 64 years, stature: 1.70 m, body mass: 102 kg, BMI: 35 kg/m2) were tested under frontal impact conditions simulating a delta-V of 50 kph. All specimens were seated on a spring-controlled seat with a 45° reclined seatback and restrained by a three-point belt system with pretensioner and load limiter. Three configurations were evaluated: (1) stiffer seat, (2) softer seat, and (3) stiffer seat with a knee bolster 100 mm from the knees. Each subject underwent one test. Whole-body kinematics were captured using a VICON motion analysis
Somasundaram, KarthikYoganandan, NarayanPintar, Frank
Vehicles equipped with an Automated Driving System (ADS) have the potential to significantly reduce road collisions. To enable widespread adoption of ADSs, rigorous safety assessment is essential. Valuable insights for ADS safety validation can be gained by simulating scenarios across a broad range of feature variations. A common challenge in simulating these scenarios is known as the curse of dimensionality, where increasing the number of scenario features requires a near-infinite number of simulations to cover all variations. This issue of complexity presents a need for reducing scenario features. Most related work focuses on identifying important scenario features, while few evaluate how reducing these features impacts ADS failure estimation. The present study aims to address this gap by employing a wide range of feature reduction methods and assessing their effect on ADS failure estimation. Previous research generated datasets for three distinct scenario categories by performing
Lankhorst, Bramde Gelder, ErwinJanssen, Christian P.Scholich, Andre
Currently, adult anthropomorphic test devices used in regulatory and consumer information crash testing in the United States are targeted to represent a small female (5th percentile) and an average male (50th percentile). The anthropometry determined previously might not represent the current population, or as investigated in the current study, those that are at least moderately injured during a motor vehicle crash. The objective of this study was to use field data to determine if the current frontal anthropomorphic test devices are representative. Data from the National Automotive Sampling System–Crashworthiness Data System (2010-2015) and Crash Investigation Sampling System (2017–2023) were queried for sex, age, size, and injury information for front seat occupants in frontal crashes. Additional datasets used were from the National Trauma Data Bank and the Centers for Disease Control and Prevention. According to field data, the most frequently injured female and male is approximately
McNeil, ElizabethAtwood, JonathanRudd, RodneyCraig, Matthew
Vehicle maneuver data are essential for perception and planning in advanced driver-assistance systems (ADAS) and automated driving systems (ADS). While high-quality annotations improve machine-learning performance, existing maneuver datasets remain fragmented, labor-intensive to annotate, and inconsistent in semantic richness. Challenges persist in scalability, interpretability, and contextual labeling. This article establishes a structured framework for maneuver data analysis by combining a systematic review of existing resources with the development of a new multimodal dataset. First, we conduct a systematic review of publicly available datasets such as HDD, KITTI, BDD-X, D2CAV, Brain4Cars, DrivingDojo, and the Driving Behavior Database. We further evaluate the data modality and sensor configurations including event data recorders, onboard logging systems, and smartphone sensing. We then propose the Matt3r Data Collection System with modern metadata management, which integrates video
Bai, LingYuan, ChongyuOsman, IslamLin, ZiruiMirab, GhazalSaheb, AmirParnian, NedaShapiro, EvgenyShehata, Mohamed S.Liu, Zheng
This research examined the performance of SAE Level 2 (L2) advanced driver assistance systems (ADAS) in crash-imminent scenarios (CIS), with particular attention to how vehicle configuration like body style and powertrain (internal combustion engine, plug-in hybrid, electric vehicle) influences vehicle system performance. The objectives were to (1) identify CIS relevant to L2-equipped vehicles using crash databases and naturalistic driving studies (NDSs), (2) develop scenario-based test procedures and test matrices, and (3) evaluate system and vehicle responses across configurations and conditions. Multiple crash data sources were analyzed, including NHTSA’s Standing General Order dataset of L2-related crashes, the Fatality Analysis Reporting System, the Crash Report Sampling System, and NDS data from the Second Strategic Highway Research Program and the Virginia Tech Transportation Institute L2 NDS. Coded variable analyses from the datasets identified three common CIS: lane and road
Beale, GregoryKefauver, KevinVenegas, MichaelLi, EricChen, JayHuggins, StevenGuduri, BalachandarLlaneras, Eddy
The aims of this study were to investigate the kinematics of child anthropomorphic test devices in a large sample of rear-facing child restraint system installations and the effects of anti-rebound features and load legs on the kinematics of rear-facing child anthropomorphic test devices. The test matrix included a general sample of 70 rear-facing child restraint system installations to observe trends in frontal crash tests; 14 full-scale crash tests with paired comparisons to investigate the effect of anti-rebound features; and five paired comparisons of rear-facing child restraint systems installed with and without a load leg. The paired t-test was used to determine the statistical significance of differences in kinematic responses. In the general sample, 84% of anthropomorphic test devices in infant seats with the base in outboard seats interacted with the first-row seat. In 52% of tests, the anthropomorphic test device head directly contacted the front seatback. Head accelerations
Tylko, SuzanneTang, Kathy
Programs that teach older drivers how to confidently and competently use advanced vehicle technologies (AVTs) are limited. The MOVETech study evaluated a training program specifically designed to teach older drivers how to use these technologies. Participants (n = 119) were randomized to the intervention (training program) or control group (brochure). The intervention involved an in-person classroom education session on the use and benefits of AVTs, and an on-road driving session where participants drove along a pre-defined route in a dual-controlled vehicle with instruction on AVT use by a driving instructor. All participants completed in-person and telephone assessments at baseline and 3 months. Driving performance and on-road AVT competence assessments were the primary outcomes. Self-reported driving confidence, competence, and confidence in use of AVT, crashes, citations, and count of vehicle damage were the secondary outcomes. Program fidelity was also evaluated using a checklist
Nguyen, HelenRen, KerrieCoxon, KristyNeville, NickO’Donnell, JoanCheal, BethBrown, JulieKeay, Lisa
Previous rear-facing post-mortem human subject (PMHS) studies utilizing a reinforced seat have prompted questions as to whether the seat could have been a contributing factor to the severe rib and pelvis injuries observed in those experiments. In response, a recent PMHS study used an unreinforced seat in a similar experiment, which was expected to mitigate severe injuries by dissipating energy from seatback deformations. However, the PMHS tested in the unreinforced seat sustained even more severe rib fracture numbers than in the reinforced seat. No studies have investigated how additional variables (i.e., countermeasures) may influence rib fractures in high-speed rear-facing frontal impacts (HSRFFI). Therefore, this study aimed to explore the effect of an airbag-equipped seat (AES) on male PMHS responses and injuries. Rear-facing sled tests were conducted using five mid-size male PMHS seated in the AES at ΔV of 56 km/h: PMHS1 with no airbag as a baseline, PMHS2 with a seatback airbag
Kang, Yun-SeokDeWitt, TimothyWensink, TimothyMarcallini, AngeloJung, Yong HyunLee, Dong GilHarm, Jae JunKo, SeokhoonHunter, RandeeAgnew, Amanda M.
To reduce traffic fatalities through vehicle safety measures, particular attention must be given to cyclist-related fatalities. Clarifying the characteristics of hazardous events leading to cyclist fatalities, not only by vehicle speed range but also by vehicle type, is essential and should be based on analyses of real-world accident data. Accordingly, this study aimed to characterize fatal cyclist accidents involving vehicles traveling at low and high speeds in Japan. We used macro accident data from the Japanese Institute for Traffic Accident Research and Data Analysis covering the period from 2013 to 2022. Based on nine vehicle types, we investigated the effects of road type, vehicle behavior, and accident type on cyclist fatalities. Additionally, we identified the five most frequent accident scenarios separately for each low- and high-speed category. At signalized intersections, the proportions of cyclist fatalities involving vehicles traveling at low speeds were higher than those
Matsui, YasuhiroOikawa, Shoko
This project was designed to better understand how the activation of SAE International Level 2 (L2) system features affect the duration of secondary task engagement. Four naturalistic driving datasets were used: one that included drivers without L2 experience, two that included drivers with L2 experienced, and one that included drivers of L0 vehicles. Dependent variables that were assessed include frequency of secondary tasks, duration of secondary task, and proportion of time that drivers engaged in cell phone tasks when L2 systems were active compared to when L2 systems were available but inactive. Results suggest that both the frequency and proportion of time drivers engaged in secondary tasks were significantly higher when L2 systems were active compared to when systems were available but inactive. Drivers without L2 experience took longer to perform tasks involving the center stack/instrument panel compared to experienced L2 drivers. These results suggest that drivers demonstrate
Klauer, SheilaDunn, NaomiAnderson, Gabrial T.Barnes, EllenHan, ShuFincannon, ThomasWeaver, Starla
This study provides an updated characterization of real-world frontal crash types—considering overlap and obliquity—based on their overall frequency and associated injury outcomes. The results of this study will support an evaluation of how well NHTSA’s frontal oblique crash test condition addresses the current population of serious frontal crashes, as compared to frontal test modes in existing crashworthiness programs. U.S. field crash data from 2017 to 2023 were analyzed to classify frontal crashes by coded damage characteristics. Oblique frontal crashes were defined as those with principal direction of force between 10°–40° and 320°–350°. Non-ejected belted first and second row occupants in model year 2000 and newer passenger vehicles absent a rollover event were included. Occupants were stratified by sex, age, and body mass index, and injury outcomes based on moderate, serious, and fatal thresholds were analyzed across crash configurations. Among the belted first row occupants
Rudd, Rodney W.
The objective of this study was to investigate occupant injury patterns and predictors in rear-impact crashes using recent US field data. Cases were queried from the Crash Investigation Sampling System (CISS, 2017–2023) and the Crash Injury Research and Engineering Network (CIREN, 2017–2024), yielding 1923 front-row outboard occupants from 1533 crashes. Crash documentation and vehicle photographs were manually reviewed to classify seatback deformation magnitude and secondary impact severity. Multivariable logistic regression models estimated associations between occupant, vehicle, and crash characteristics and Abbreviated Injury Scale (AIS) ≥ 2 and AIS ≥ 3 injury outcomes across body regions. Sensitivity analyses included CISS-only, weighted, single-event, and interaction models. Thoracic injuries were further subdivided into skeletal and cardiopulmonary categories. Findings reflect associations within the pooled CISS + CIREN analytic sample rather than nationally representative injury
Lockerby, JackRudd, Rodney
While an enlarged lead time from risk notifications to collisions is widely acknowledged to facilitate safe driving, it remains challenging to effectively notify drivers of invisible risks and non-apparent risks coming from uncertain behaviors on the part of road users. The current study examined whether verbal notifications are able to assist early awareness of predictive risks. We also attempted to identify human and environmental factors that could possibly improve the effectiveness of predictive risk information. Twenty-eight licensed drivers participated in a public road test conducted in two different urban areas on 3 days. They drove predefined courses on which potential risk locations were identified prior to the test, using a sport utility vehicle equipped with an automatic verbal notification system triggered based on the distance to the potential risk locations. After passing through the locations each time, the participants were instructed to verbally evaluate the shift in
Maruyama, MasakiKoyama, KeiichiroEzaki, ToruSakamoto, JunichiSawada, YutaMatsuoka, Takahiro
Automated Vehicles (AV) pose new challenges in road safety, multimodal interaction, and urban planning, requiring a holistic approach that prioritizes sustainability and protects all road users. The KASSA.AST project addresses this by deploying and evaluating an automated shuttle in southern Austria on three routes. The study area is a Park & Ride zone near a train station, enabling seamless transfers and higher transit use. To assess the safety impacts of the automated shuttle, four Mobility Observation Boxes (MOBs) were deployed. These AI-based systems detect and classify road users, track their trajectories and geospatial coordinates, and identify safety-critical events via Surrogate Safety Measures (SSMs). Over 10 days, a trajectory dataset captured interactions among vehicles and the shuttle. The resulting real-world dataset is a core contribution. This dataset underpins microscopic behavior modeling. Trajectory pairs yield car-following and interaction metrics (relative distance
Losada Arias, ÁngelRosenkranz, PaulHula, AndreasAleksa, MichaelSaleh, PeterErdelean, Isabela
Drivers frequently encounter Type II dilemma zones at signalized intersections, where the decision to stop or proceed during the onset of a yellow indication can be ambiguous. Decision-making relies on drivers’ expectations of the yellow change interval duration and behavioral factors. While boundaries of these zones are well studied, less is known about how familiar drivers are with their local yellow indication laws, which vary from state to state, and whether their typical reactions to yellow indications align with the laws. Existing interventions like signal timing adjustments, improved vehicle detection, and advance warning signs reduce the number of drivers caught in dilemma zones but may not reach distracted drivers. In-vehicle alerts tailored to dilemma zone scenarios are a potential solution not yet implemented widely in North America. This study addresses how drivers may interpret these alerts. A web-based survey of 640 licensed drivers in Michigan and Washington (ages 18–85
Anderson, ErikaJashami, HishamAhmed, AnannaHurwitz, David
This study investigated how vehicle front-end geometry, impact speed, and vehicle category influence injury risk to a midsize male pedestrian. Eighty-one generic vehicle (GV) models representing sedans, sport utility vehicles (SUVs), pickup trucks, and minivans sold in the United States were developed by morphing three base models using an automated pipeline. Front-end parameters that were varied included ground clearance (GC), bumper height (BH), hood leading-edge (HLE) height, hood length (HL), bumper lead angle (BLA), hood angle (HA), and windshield angle (WSA). Each vehicle impacted the Global Human Body Models Consortium 50th percentile male simplified pedestrian (GHBMC M50-PS) model at 30, 40, and 50 kph, totaling 243 simulations. Boundary conditions followed the European New Car Assessment Program (Euro NCAP) pedestrian test protocol. Thirty-five injury metrics were extracted across the head, neck, thorax, abdomen, pelvis, and lower extremities. Linear mixed-effects regression
Poveda, LuisMiller, Logan E.Edwards, Colin C.Pollock, MadelineArmstrong, William M.Hsu, Fang-ChiGayzik, Scott F.Weaver, Ashley A.Stitzel, Joel D.Devane, Karan S.
The objective of this study is to use parametric human body models (HBMs) to understand how geometric variability among individuals who have the same sex, stature, and body weight may affect the impact responses and injury outcomes, using midsize male and midsize female populations as representative cases. Methods were developed to quantify skeletal and external body surface variations using principal component analysis, regression, and residual error analysis. Based on this analysis, nine midsize male and nine midsize female geometric models were created, focusing on ribcage and pelvis variations, which account for most of the observed variability. These geometries were then applied to morph the simplified Global Human Body Model Consortium (GHBMC) midsize male model, producing 18 distinct HBMs. Each morphed HBM was subjected to nine impact scenarios, resulting in a total of 162 simulations to assess the effects of geometric variability. Substantial geometric variation was observed in
Hu, JingwenLin, Yang-ShenBoyle, KyleKhandare, SujataBonifas, AnneReed, Matthew P.Hasija, Vikas
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