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Cradle-to-grave assessment of Austrian passenger car traffic based on actual vehicle movements and derivation of future forecasts for minimising greenhouse gas emissions

2026-01-0457To be published on 04/07/2026

As part of the decarbonisation process for passenger car fleet in Austria, battery electric cars in particular have been subsidised in recent years, as these vehicles are considered to be largely emission-free during use and are expected to reduce emissions in future. However, in order to sustainably reduce the global greenhouse gas emissions of Austrian passenger car traffic, taking into account all types of propulsion systems, it is necessary to apply a cradle-to-gate approach, as is commonly done in comparable analyses in the literature, which evaluates the emissions of the entire vehicle life cycle. The most important phase in the life cycle assessment remains the well-to-wheel phase, which includes emissions from energy supply and vehicle use. Due to the large number of influencing factors, highly simplified models are usually used for this phase in the literature. As part of this work, a methodology was developed that, allows an in-depth analysis of entire vehicle fleets by

Lischka, Gregor, Tober, Werner

New Inverter Switching Control Method to Enhance Sound Quality for Electric Vehicles

2026-01-0437To be published on 04/07/2026

Conventional inverter control uses a fixed switching frequency, which leads to a high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are generally much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A fixed pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound

He, Song, Gagas, Brent, Welchko, Brian, Ball, Kerrie, Gong, Cheng

From Propane to Pi: Affordable AI-Driven Solutions for Sustainable Bus Heating.

2026-01-0164To be published on 04/07/2026

The design of an affordably luxurious school bus means improving passenger comfort while greatly decreasing energy usage and emissions. The key consideration is to replace traditional propane heating with an electric heated-seat system and supported by green electricity/energy efficient smart power management. The system is designed from a 24V/48V battery system; to a Smart Energy Cube - a portable dock in power module requiring solar, battery and grid connection. Seat heating is only applied to seats that are occupied. The on-board image processing models (YOLOv5/YOLOv8, OpenCV, TensorFlow Lite) are run on affordable/portable microcomputers capable of detecting the number of occupied and available seats e.g. Raspberry Pi. There is one bottle neck when using the Raspberry Pi in the experiments to validate concept, when using low/medium power frame rates of ~ 1 fps for Raspberry Pi 3; to 7-8 fps with a Raspberry Pi 5. As a baseline, there is still potential for improvement and

Chikkala, Daney Bhargav, Zadeh, Mehrdad, TAN, Teik-Khoon, Ponnam, Jitin, BATTE, JAI RATHAN

In-Use Life Digital Twin and Swappable Use Case for Battery Durability

2026-01-0397To be published on 04/07/2026

In-Use Life Digital Twin and Swappable Use Case for Battery Durability By: Patricia Laskowsky, Josue Albarran, Justin Bunnell, and Andrew Zettel Abstract The UN GTR 22 is required as part of the Environmental Protection Agency’s legislative rulemaking for multi-pollutants emission standards for model years 2027 and later light-duty and medium duty vehicles. The EPA claims it has the right to govern requirements on ZEVs and BEVs. ZEVs, in their viewpoint, are “emission related” because it enables the vehicle to produce zero emissions. With the adoption by the EPA under its Tier 4 regulations of the UN GTR 22, comes several new tracking DIDs, Data Identifiers. These DIDs are tied battery durability and energy tracking They track conditions and usages of electric vehicles that may accelerate the loss of electric range and/or loss of efficiency of the propulsion energy storage and delivery. More specifically, tying these trackers to EPA emission related discussion, the loss of electric

Laskowsky, Patricia, Bunnell, Justin, Zettel, Andrew, Albarran, Josue

The Impact of Mid-level Ethanol Blends on Reliability, Performance and Emissions in Gasoline engine

2026-01-0302To be published on 04/07/2026

To reduce CO₂ emissions from automobiles, it is essential to enhance system efficiency through the electrification of vehicles equipped with internal combustion engines (ICEs), such as hybrid electric vehicles (HEVs) and plug-in hybrid electric vehicles (PHEVs), as well as through improvements in ICE thermal efficiency. Furthermore, biofuels and synthetic fuels are gaining attention as promising options for reducing CO₂ emissions, including from existing vehicles. Among these alternative fuels, ethanol - a bio-derived fuel - is already utilized in varying concentrations across many countries, and its further application is anticipated. While expanding the fleet of flex-fuel vehicles (FFVs) capable of operating on high ethanol blends is one approach, increasing the ethanol content in conventional gasoline fuels, which are more widely used, is considered to have a greater impact on CO₂ reduction. A key issue is the impact and adaptability of existing vehicles when ethanol concentrations

Matsubara, Naoyoshi, Sugata, Kenji, Koyama, Takashi, Ochi, Yuta, Aoki, Mizuki, Hashima, Takashi, Kodama, Kohei, Tomoda, Keiju, Kojima, Masakiyo

Effect of renewable fuel blends on particulate emissions in warm-up conditions in a GDI engine

2026-01-0304To be published on 04/07/2026

Renewable gasoline offers significant benefits in reducing greenhouse gas (GHG) emissions. In this study, five gasolines with different renewable hydrocarbon classes and varying distillation curves were taken to investigate their effect on particle number (PN) emissions in a spark-ignition GDI engine at 10 bar indicated mean effective pressure (IMEP) and 2000 rpm. The engine coolant temperature was varied from 90°C to 35°C to investigate the effect of fuel evaporation on soot formation. Injectors with various spray plume targets and start of injection (SOI) timing (300° and 260° bTDC) were used to assess how different gasolines affect engine performance and to determine engine calibration requirements. A simplified transient cycle examines how engine motoring influences PN emissions for test gasolines. A high-speed camera and endoscope were used to identify the sources of soot during fuel combustion. Simulations were done to assess the quality of fuel-air mixing in support of the

Muniappan, Krishnamoorthi, Dahlander, Petter, Helmantel, Ayolt, Alemahdi, Nika, Lehto, Kalle

Optimal Vehicle Sampling for Fleet-Wide Emissions Monitoring using Submodular Maximization

2026-01-0283To be published on 04/07/2026

This article addresses the problem of optimal vehicle sampling for fleet-wide in-use emissions monitoring, a necessity driven by the absence of direct emissions sensors in modern production vehicles and the variable impact of in-use changes and operational factors (mileage, time-in-service, workload) on emissions performance across a fleet. Recognizing that comprehensive fleet testing is impractical due to significant downtime and cost, we propose a novel approach to identify a small, yet optimally informative subset of vehicles for sampling. The proposed approach leverages submodular function maximization, a technique rooted in optimal experimental design, specifically D-optimal design, to maximize the determinant of the information matrix (e.g., of $X^TX$, where $X$ is the regressor/design matrix in the case of a linear in parameters model). This approach ensures that the collected data yields maximum information for refining and building accurate models for emissions characteristic

ZHANG, JIADI, Li, Xiao, Kolmanovsky, Ilya, Tsutsumi, Munecika, Nakada, Hayato

Combustion and Emission Characteristics of Biodiesel and Renewable Diesel in a 4-Stroke Locomotive Engine

2026-01-0315To be published on 04/07/2026

Rail transportation in North America consumes substantial amounts of fossil fuel, raising energy security and supply chain resilience concerns. Adopting renewable or alternative fuels is a practical approach to reduce petroleum dependence and improve supply security. The objective of this paper is to investigate the combustion and emission characteristics of biodiesel and renewable diesel as a drop-in fuel without engine modification. In this study, a single-cylinder, four-stroke locomotive engine was employed to investigate the combustion and emissions characteristics of four fuels: conventional Diesel No. 2, plant-based biodiesel, animal-based biodiesel, and renewable diesel. The experimental campaign was carried out under both part-load and full-load operating conditions at the constant load, with injection duration adjusted to achieve the targeted engine’s load and speed. Results indicate that biodiesel and renewable diesel deliver comparable peak in-cylinder pressure, indicated

Ewphun, Pop-Paul, Biruduganti, Munidhar, El-Hannouny, Essam, Longman, Douglas, Fu, Xiao, Subramanya, Raghavendra

Heavy duty hydrogen internal combustion engine emissions development to achieve ultra-low NOx

2026-01-0356To be published on 04/07/2026

This paper presents the emissions development of a heavy-duty hydrogen internal-combustion engine (H₂ ICE) targeting ultra-low NOx with a design goal of 20–35 mg/hp-hr. The approach integrates precise air–fuel-ratio control, transient-response enhancements to minimize rich/lean excursions, and advanced thermal management of the engine and aftertreatment, including an electric heater to accelerate light-off and sustain activity at low-load/idle conditions. A diesel-derived aftertreatment system (ATS) is selected to maximize practicality and component commonality, and a unified controls strategy spanning the engine and ATS is implemented to ensure emissions compliance over EPA certification and in-use testing cycles. The aftertreatment solution space is evaluated for catalyst sizing and backpressure while demonstrating particulate matter control without the need for a filter. The paper concludes with emphasis on catalyst aging and durability relative to diesel benchmarks, including long

Shakya, Bijesh, Xu, Hui, Yang, Zhao, stetter, John

Passive Soot Regeneration Observations on a GPF-equipped vehicle for PM exhaust emission control.

2026-01-0366To be published on 04/07/2026

The gasoline particulate filter (GPF) will be a common technology adopted by EPA Tier4 emission compliant vehicles, starting as early as model year 2017 in North America. For those Tier-4 compliant gasoline-powered powertrains, their GPF solutions will require that the captured soot can be safely removed through passive oxidation. This clean-out process is driven by occasional fuel-cut events, such as engine motoring, which would provide an excess of oxygen in the exhaust gas flow to the hot, soot-loaded GPF. Here, a study has been conducted where a modern vehicle with a 3L engine displacement was upfitted with appropriately sized GPFs for soot capture in the dual-bank exhaust line. These GPFs were weighed to track their soot-load trends between representative real-world driving routes, where sensor data and ECU parameters were recorded. Thus, characterization of the passive soot regeneration process in the GPF was linked to the preceding exposure of gaseous flow temperatures, oxygen

Craig, Angus, Warkins, Jason

Comparison of Ammonia Emission Characteristics Between Different Gasoline Vehicles Equipped with Three-Way Catalysts

2026-01-0374To be published on 04/07/2026

In recent years, the tightening of vehicle emission regulations has led to a decreasing trend in regulated pollutants such as NOₓ and CO. However, the emission of ammonia (NH₃), which is unintentionally generated during the purification process in three-way catalyst of gasoline vehicles, has become a growing concern. NH₃ emissions from vehicles can serve as a precursor to PM2.5 and have been reported to cause local roadside pollution. Therefore, there is a growing need for on-road testing to identify conditions under which NH₃ is likely to be emitted. Furthermore, since engine control strategies vary among vehicle types, it is desirable to consider differences in emission behavior across different models. In this study, on-road NH₃ emissions were measured for multiple vehicle models with different powertrains, and the effects of engine behaviors and engine operating duration across vehicles on NH₃ emissions were investigated. To analyze differences in NH₃ emission behavior among

Ashizawa, Keigo, Fukunaga, Chisato, Gao, Tianyi, Sato, Susumu

Physics-Based Simulation for Sustainable Fuels Part 2.2: Inter-Ring Pressure Measurements and 2D/3D Ring Dynamics Analysis Across Multiple Engine Platforms – Heavy Duty and Large Bore

2026-01-0280To be published on 04/07/2026

The growing demand for sustainable mobility and transportation is accelerating the adoption of alternative fuels, particularly hydrogen, in internal combustion engines. The first part of this publication series highlights the significance of 2D simulation as a crucial and computationally efficient tool for the precise development of hydrogen Power Cylinder Units. This approach demonstrates predictive capability proofed through engine tests, achieving a reduction in lube oil consumption by 5–7 g/h during high-load operations, alongside a 28% decrease in blow-by and an 11% reduction in hydrogen flow to the crankcase. To provide deeper insights into the complexities identified in Part 1, this study employs inter-ring pressure measurements across various engine types and configurations, including light vehicles, heavy-duty trucks, and large-bore applications, covering a broad range of engine displacements from 2 to almost 100 liters. Part 2.1 focuses on understanding the cyclic variations

Köser, Philipp, Moreira, Rui

Persistent Elevated Soot Emissions Induced by Clustered Stochastic Preignition Events

2026-01-0314To be published on 04/07/2026

Stochastic Preignition (SPI) is an abnormal combustion phenomenon that can occur in spark-ignition engines particularly under high-load operation. SPI is characterized by uncontrolled initiation of combustion prior to spark discharge, an abnormal combustion process that can lead to severe knock events and significant engine damage. SPI has been associated with fuel properties, lubricant composition, and engine design and operation. In this work, a single-cylinder test engine with a dry-sump oil system was utilized to study the SPI response of E10 and E25 fuels with a range of Reid Vapor Pressure (RVP). An automated test procedure was employed, consisting of ten square-waved load profile segments, with each segment composed of 5 min of low-load operation followed by 25 min of sustained high-load operation. These tests were replicated across multiple days of testing with a triple flush of lubricant between each test, and an online Fuel in Oil diagnostic measurement. Exhaust particulate

Splitter, Derek, Jatana, Gurneesh, DelVescovo, Dan, Douvry-Rabjeau, Julien, Fioroni, Gina, Chapman, Elana, Salyers, John

Advanced Multifunctional Catalysts for Emission Control in Hydrogen and Diesel Engines

2026-01-0367To be published on 04/07/2026

As hydrogen internal combustion engines (H₂-ICE) gain traction, optimizing exhaust aftertreatment technologies for nitrogen oxide (NOx) control has become increasingly critical. While selective catalytic reduction (SCR) systems remain the primary approach for NOx mitigation, oxidation catalysts are also being explored to facilitate hydrogen oxidation and improve overall exhaust treatment efficiency. This work presents a multifunctional catalyst (MFC) concept that combines supported Pd and Cu-zeolite to enable simultaneous NOx reduction and hydrogen oxidation within a single catalytic unit. Preliminary results show that hydrogen oxidation on supported Pd occurs above 300 °C, while Cu-zeolite achieves nearly complete NOx conversion. Experiments on individual components indicate that supported Pd initiates ammonia oxidation only after hydrogen is depleted. In the presence of hydrogen, ammonia conversion remains below 20%, indicating that hydrogen availability suppresses ammonia oxidation

Danghyan, Vardan, Becker, Jan Martin, Hünnekes, Edgar, Patchett, Joseph

Challenges to Ranking Diesel Fuels for NOx Emissions Using a Constant-Volume Combustion Chamber

2026-01-0348To be published on 04/07/2026

This study examined the use of a constant volume combustion chamber for the measurement of fuel effects on NOx emissions, with the goal of developing a method to rapidly screen or rank fuels in a small - volume experiment. A small amount of fuel was injected into the air at 650°C and 20 bars, where it ignited and burned. The chamber was sampled post-combustion using a chemiluminescence NOx analyzer. Extensive sampling method development was required to obtain repeatable results. Seven hydrocarbon fuels and two biodiesel fuels were tested, all of which have shown difference in NOx emissions in past engine studies. When using a single injection event to deliver the same amount of fuel energy, the test method could not clearly demonstrate the difference in NOx emissions between the hydrocarbon fuels as reported in engine combustion studies. To improve this, a dual-injection strategy was used. It included a small “pilot” injection followed by a main injection, timed based on each fuel’s

Luecke, Jon, Rahimi, Mohammad, Mohamed, Samah, Naser, Nimal, Chausalkar, Abhijeet, McCormick, Robert

Emission and Combustion Characteristics of a Hydrogen Direct-Injection Spark Ignition Engine using EGR

2026-01-0325To be published on 04/07/2026

Hydrogen is recognized as a promising alternative fuel for internal combustion engines as it contains no carbon, but in addition to NOx emissions during hydrogen combustion, unburned hydrogen emissions have recently emerged as an important environmental issue. In this study, a 400 cc single-cylinder direct-injection hydrogen engine based on a 1.6 L Hyundai Kappa engine was used to analyze the effects of injection and ignition timing on combustion characteristics and engine emissions. Experimental results showed that the formation state of the air-fuel mixture varied with injection and ignition timing. Under conditions where locally fuel-rich mixtures were formed, NOx emissions increased while unburned hydrogen decreased. In contrast, when the mixture was relatively homogeneous, NOx decreased but unburned hydrogen increased. These findings clearly confirmed the trade-off relationship between NOx and unburned hydrogen emissions. To address this issue, exhaust gas recirculation (EGR) was

Yang, Heetae, Ki, Youngmin, Kim, Jungho Justin, Kim, Jinsu

Behavioral Determinants of Electric Vehicle Battery Degradation: Evidence from Large-Scale Real-world Operations

2026-01-0458To be published on 04/07/2026

Electric vehicles (EVs) are central to sustainable transport, yet battery service life remains a limiting factor for cost and adoption. Distinct from traditional laboratory-based simulations that often fail to capture the complexity of field conditions, this study investigates how EV user behavior—including driving style and charging demands—influences capacity using large-scale, real-world operational data from daily EV usage. A data-driven framework is developed to quantify driving and charging behaviors through multidimensional feature extraction at the vehicle level and estimate battery State-of-Health (SOH) trajectories, enabling direct linkage between individual behavior patterns and degradation outcomes. Results reveal substantial heterogeneity in aging rates explicitly driven by diverse user behaviors: under identical urban conditions, vehicles with a radical driving style exhibit approximately 81% faster SOH decline per 20,000 km than those with a moderate style ; regarding

Liu, Tianyi, Jing, Hao, Zhu, Jiankuan, Chen, Yongjian, Ou, Shiqi(Shawn), Qian, Xiaodong

A Quantitative Approach for Mapping and Assessing Diesel Particulate Filter Regeneration Events in Diesel Engines

2026-01-0377To be published on 04/07/2026

Regeneration of diesel particulate filters (DPFs) is crucial for maintaining the performance of diesel engines and minimizing harmful particulate matter (PM) emissions from exhaust. However, conventional regeneration strategies often suffer from incomplete soot removal and inefficient monitoring. These issues lead to increased exhaust back pressure, reducing engine efficiency, and potentially damaging the particulate filter. In this paper, a new approach is proposed for mapping and quantifying the real-world DPF regeneration process for diesel engines complying with the stringent emission standards. We introduce a novel metric, the differential pressure drop percentage (DPDP), to detect regeneration events and quantify soot burn quality. The proposed method utilizes real-time sensor data obtained through the vehicle’s On-Board Diagnostics (OBD) system. The algorithm processes sensor data and robustly maps the regeneration quality. The performance of regeneration event detection and

Bagga, Harleen Kaur, Nagare, Mukund B., Patil, Bhushan D., Ravishankar, Hariharan, Melapudi, Vikram, Patil, Abhijit

SUNRISE - A Harmonised Safety Assurance Framework for Connected, Automated MobIlity Systems

2026-01-0060To be published on 04/07/2026

The SUNRISE project develops and demonstrates a harmonised Safety Assurance Framework (SAF) for Connected, Cooperative and Automated Mobility (CCAM) systems. The framework has been created in close alignment with the UNECE New Assessment/Test Method (NATM), and past and on-going international projects and initiatives. It also aligns with standardisation efforts in various standardisation bodies such as ISO, ASAM, SAE, and BSI. At the core of the SAF lies the Performance Assurance flow, which structures how safety evidence is generated and assessed. This flow is organised into three interconnected blocks: Scenario, Environment, and Safety Argument. The Scenario block encompasses the creation, formatting, and storage of scenarios that can be retrived to cover the system’s Operational Design Domain (ODD) and behaviour. The Environment block addresses the concretisation of test cases, their allocation across virtual, proving-ground, and real-world environments, and their execution. The

Zhang, Xizhe, Khastgir, Siddartha, de Vries, Stefan, Hillbrand, Bernhard, Op den Camp, Olaf, Bolovinou, Anastasia, Bourauel, Bryan, Ehrenhofer Gronvall, John Fredrik, Menzel, Thaddäus, Nieto, Marcos, Stettinger, Georg, Jennings, Paul

Enhancing Traditional Adaptive Cruise Control through Map-Based Feature Integration: A Performance evaluation Study on Stationary Vehicle Response at High Speeds

2026-01-0056To be published on 04/07/2026

Adaptive Cruise Control (ACC) has become a widely adopted driver-assist technology, designed primarily to regulate a vehicle’s longitudinal movement while maintaining a safe following distance from the preceding vehicle. A key performance criterion is the system’s ability to detect and respond to both moving and stationary target vehicles within the ego vehicle’s path. While manufacturers typically validate ACC performance within specific speed ranges, responding to stationary objects remains particularly challenging due to limited sensor range, difficulty in detecting distant stationary targets, and constrained deceleration capabilities. Beyond certified operating limits, overall system reliability may degrade. Nonetheless, increasing industry and regulatory expectations are driving the need to extend ACC functionality across wider and more clearly defined speed domains. Modern ACC systems are further evolving to recognize and respond to various road features, including traffic lights

Awathe, Arpit, Patel, Darsh, Mathur, Dhruv, Raut, Abhinandan Vijay

An Integrated Methodology for Sustainable Mobility Infrastructure Planning: The Atlanta Aerotropolis Case Study

2026-01-0097To be published on 04/07/2026

By the early 2020s, more than 4.5 billion people have been living in urban areas worldwide, compared to just 1 billion in 1960. Rising growth in urban populations present challenges to infrastructure and transportation systems. Higher traffic levels and reliance on conventional vehicles have contributed to heightened greenhouse gas (GHG) emissions, rising global temperatures, and irreversible environmental degradation. In response, emerging transportation solutions—including intelligent ridesharing, autonomous vehicles, zero-tailpipe-emission transport, and urban air mobility—offer opportunities for safer and more sustainable transportation ecosystems. However, their widespread adoption depends not only on technological performance and efficiency, but also on integration with current infrastructure, safety, resilience to unexpected disruptions, and economic viability. A dynamic, agent-based System-of-Systems (SoS) transportation model is developed to simulate vehicle traffic and human

Rana, Vishva, Balchanos, Michael, Mavris, Dimitri, Valenzuela Del Rio, Jose

Data-driven feedforward compensation-based trajectory tracking control

2026-01-0028To be published on 04/07/2026

Advanced autonomous driving is a critical component in the intelligent development of new-generation electric vehicles. Research on reliable chassis control algorithms ensures the safety and stability of autonomous vehicles during operation. To enhance the control performance of autonomous vehicles and improve the accuracy of trajectory tracking, this paper proposes a data-driven feedforward compensation trajectory tracking control approach. By optimizing the design of the feedforward compensation loop, systematic errors and latency in the vehicle’s steering system are mitigated, thereby enhancing the precision and robustness of the control algorithm. Initially, the paper analyzes the control errors present when the vehicle responds to controller commands. Subsequently, the paper focuses on the steering angle errors in trajectory tracking, identifying and analyzing the most relevant factors. A time-delay neural network (TDNN) based on data-driven principles is designed to model and

Yang, Yijin, Yuan, Yin, Wang, Zhenfeng, Su, Ailin, Zhang, Zhijie, Lu, Yukun

High Order Control Lyapunov Function - Control Barrier Function - Quadratic Programming Based Autonomous Driving Controller for Bicyclist Safety

2026-01-0034To be published on 04/07/2026

Ensuring the safety of vulnerable road users is a critical challenge in the development of advanced autonomous driving systems. Among vulnerable road users, bicyclists present unique characteristics that make their safety both critical and manageable. Compared to pedestrians, vehicles often travel at significantly higher relative speeds when interacting with bicyclists, yet bicyclist motion is generally more predictable and governed by clear traffic rules, offering opportunities for model-based control strategies. To address bicyclist safety in complex traffic environments, this study proposes a High-Order Control Lyapunov Function–High-Order Control Barrier Function–Quadratic Programming (HOCLF-HOCBF-QP) control framework. By using this approach, CLFs enforce system stability, ensuring the vehicle follows a desired trajectory, while CBFs define safety boundaries, preventing collisions between the ego-vehicle and other road users. The optimal control input is then obtained by solving a

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

The New Era for Automotive Cybersecurity An Opportunity for Standardization of Automotive Cybersecurity

2026-01-0086To be published on 04/07/2026

The automotive industry is moving from a reactive, self-determined approach to cybersecurity to a standardized, regulated one. This document, an update on collaborative work from the SAE TEVEES18B Committee and GlobalPlatform Automotive Task Force, outlines this transition. In the past, cybersecurity challenges in the automotive industry were seen as novel, and each company handled them individually. This era was characterized by self-determination of security mitigations and a unique justification for solutions. Companies often developed cybersecurity concepts based on past incidents and their own risk tolerance. A key tool during this time was the TARA (Threat Analysis and Risk Assessment), which organizations used to justify their security concepts or lack thereof. This led to company-specific policies and a lack of a global standard. The result was a fragmented market where every new project required a novel cybersecurity concept, hindering the development of a robust market for

Mazzara, Bill, Rawlings, Craig

Experimental Validation of a Multi-Row Tapered Roller Bearing Analytical Model for Relating Preload to Frequency Response Characteristics

2026-01-0008To be published on 04/07/2026

Roller bearings are used in many rotating power transmission systems in the automotive industry. During the assembly process of the power transmission system, some types of roller bearings (e.g., tapered roller bearings) require a compressive preload force. Those bearings' rolling resistance and lifespan strongly depend on the preload set during the installation process. Therefore, accurate setting of the preload can improve bearing efficiency, increase bearing lifespan and reduce maintenance costs over the life of the vehicle. A new method for bearing preload measurement has shown potential for both high accuracy and fast cycle time using the frequency response characteristics of the power transmission system. An open problem is experimental validation of the multi-row tapered roller bearing analytical model. After validation, the analytical model can be used to predict the assembled system damped natural frequency for a desired bearing preload. This work presents the experimental

Gruzwalski, David, Mynderse, James

Implementation and evaluation of a method to defend in-vehicle networks using SAE J1939-91C to authenticate network messages between multiple ECUs.

2026-01-0092To be published on 04/07/2026

The objective of this paper is to understand the effort required to integrate the hardware and software of in-vehicle cybersecurity systems. The in-vehicle cybersecurity method discussed is the SAE J1939-91C, which involves Network formation, Rekeying, and secure Message Exchange between Electronic Control Units (ECUs). The SAE J1939-91C network security protocol operates over a CAN-FD network to perform necessary cryptographic operations and key generation. To evaluate the method, test vectors were created to validate SAE J1939-91C key generations and cryptographic operations on the simulated ECU in-vehicle network system hardware. The evaluation results provide a benchmark for network system performance that can be used in a system test bench to assess compliance with the SAE J1939-91C standard and to test the standard's effectiveness in ambiguous edge cases. In the future, this benchmark could be utilized in "Plugtests" to assign test scores to non-uniform SAE J1939-91C

Zachos, Mark, Medam, Krishna Teja

Model-Based Design and dSPACE/MathWorks Environment Enable Innovative Engineering Education

2026-01-0073To be published on 04/07/2026

The exponentially growing complexity of engineering systems, such as a robotic system, an autonomous vehicle, and an unmanned aerial vehicle, requires sophisticated control strategies that can efficiently coordinate the system’s operation in various environments. The traditional control design approaches present significant challenges for control engineers to keep up with the increasing complexity and changing requirements. To advance embedded control system design, a paradigm shift from traditional development approaches toward more structured, systematic methodologies that can manage the multi-domain nature of control systems is critically needed. Model-based design approach is emerging as a solution for this demand. Model-based design approach uses a system model for control system development, from requirements capture to control system design, implementation, and testing. It provides an integrated environment for design, implementation, automatic code generation, and validation

Repaka, Sindhura, Chen, Bo

Ultra-Low Latency Video Pipeline Optimization for Perception-Centric Autonomous Systems

2026-01-0022To be published on 04/07/2026

Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages-sensor acquisition, video encoding, data transmission, decoding, and display-undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software

Indrakanti, Rama Kiran Kumar

LiDAR-Driven A* Path Planning with Dynamic Obstacle Avoidance for Autonomous Navigation in ROS

2026-01-0030To be published on 04/07/2026

Autonomous mobile robots are becoming a key part of everyday operations in industries like manufacturing, logistics, healthcare, and even home assistance. A core requirement for these robots is the ability to navigate efficiently and reliably within their operating environments. To do this automation, the robot needs to understand its surroundings, figure out where it is on a map, and find a safe path from where it is to where it needs to go without bumping into anything. This paper presents an effective grid-based path planning solution for autonomous indoor navigation with a mobile robot. Achieving reliable and collision-free navigation in changing environments is a major challenge for mobile robotics. This is especially true when obstacles can appear unexpectedly, requiring quick re-planning. To tackle this issue, an improved A* algorithm was implemented to work closely with LiDAR for environmental awareness. The improved algorithm was added to the robot’s navigation system, and

Devaraj, Sriram Sanjeev, Park, Jungme

Numerical Analysis of Operating Parameters Coupled Effects on Flow Instability Mechanisms at Supercritical Pressure

2026-01-0134To be published on 04/07/2026

Supercritical fluids (SCFs) are widely utilized in advanced energy systems due to their exceptional heat transfer characteristics. However, flow instability, particularly near pseudo-critical conditions, poses a significant challenge to their effective applications. Despite extensive research, the coupled effects of thermal and fluid dynamic mechanisms on flow instability remain insufficiently understood, particularly in supercritical water (SCW) systems. This study identifies the onset of flow instability (OFI) in the negative slope region of pressure drop curve during steady-state conditions, analyzing the relationship between pressure drop and mass flow rate. Transient analyses were then conducted to investigate the influence of operating parameters on oscillatory phenomena such as pressure drop oscillations (PDO), density wave oscillations (DWO), and thermal oscillations (ThO). The results show that higher mass flow rates and heat fluxes, reduce pressure oscillations by up to 20

Rehman, Attiq Ur, Ahmad, Hassaan, Du, Xiaocheng, Kanwal, Lubna

Ensemble of Experts for Generating Digital Parking Maps from Remote Sensing Images

2026-01-0107To be published on 04/07/2026

Being a vital component of transportation, parking and parking-related research are gaining increasing attention from the intelligent transportation and automotive industry research communities. A digital parking map with precise parking spot geospatial information is crucial for research such as automatic valet parking, parking spot recommendations, and parking route optimization. Currently, these maps are generated through costly and resource-intensive human annotation. To address the challenges of insufficient parking maps and the high costs of manual map creation, researchers have proposed the following two strategies for generating parking maps. The SLAM-based map generation for indoor parking lots and the remote sensing image-based map generation for outdoor parking lot. Our work mainly focuses on the outdoor high-definition parking map generation from remote sensing images. These images often suffer from occlusion, inconsistent resolution, and varying luminosity conditions. To

Shukla, Ajitesh, Cao, Xiaofei, Liu, Yongkang, Takeuchi, Yusuke, Sisbot, Akin

Climate Heat Recovery Energy Study in Electric Vehicles

2026-01-0129To be published on 04/07/2026

Climate control systems in Battery Electric Vehicles (BEVs), Plug-in Hybrid Electric Vehicles (PHEVs), and Extended Range Electric Vehicles (EREVs) rely on electrical energy to provide cabin heating. In winter conditions, the absence of waste heat from internal combustion engines necessitates increased energy consumption for thermal comfort, which directly impacts vehicle range. Conventional HVAC systems typically operate with a mixture of cold ambient air and recirculated cabin air. However, the proportion of recirculated air is limited due to windshield fogging risks, constraining energy-saving potential. To address this, MAHLE has developed modular heat recovery technologies that utilize the thermal energy of exhaust cabin air, that would normally leave the passenger compartment through vehicle body vents, to precondition incoming fresh air, thereby reducing the heating load. These solutions are engineered for scalable integration into existing HVAC architectures, allowing

Wolfe, Edward, Wochele, Kerstin, Reid, Bailey

Experimental Study on Macroscopic Characteristics of Ammonia Spray under Flash Boiling and Non-Flash Boiling Conditions with Large-Diameter single-hole Nozzles

2026-01-0339To be published on 04/07/2026

Ammonia is regarded as a potential alternative fuel, and its spray characteristics are crucial for efficient combustion in engines. For large-bore engines suitable for heavy-duty vehicles or ships, the adoption of large-diameter nozzles is expected to ensure an appropriate fuel flow rate while improving fuel-air mixing efficiency, thereby enhancing in-cylinder combustion performance. This paper conducted an experimental study on the characteristics of liquid ammonia sprays under wide thermodynamic conditions, a wide range of injection pressures, and a wide range of nozzle diameters. The study found that at room temperature, as the ambient pressure increases from 0.1 MPa to 4 MPa, the development of spray penetration slows down. However, at 0.05 MPa, the radial expansion of the near-field spray is greater, and the penetration is slightly behind that at 0.1 MPa. The liquid penetration increases with the increase in ambient temperature. This was because the increase in temperature reduced

Liu, Yi, Zhong, Jie, Hu, Yuchen, Zhu, Wuzhe, yunliang, Qi, QINGCHU, CHEN, Wang, Zhi

Autonomous Racing Control Using Reinforcement Learning with Racing Line Guidance

2026-01-0031To be published on 04/07/2026

In recent years, with the emergence of autonomous racing competitions such as Roborace, autonomous racing cars have become a prominent research focus and have undergone rapid development. This paper establishes a reinforcement learning-based decision-making and control framework for autonomous racing cars, achieving cooperative optimization between high-speed racing and safety control under extreme operating conditions. By integrating a Control Barrier Function constrained reward function for dynamic stability and a racing line-guided path optimization, the proposed framework achieves a synergistic balance between minimum lap time and operational safety. Dynamic stability domain constraints based on a two-degree-of-freedom single-mass rigid-body model and racing line optimization based on track geometric modeling are established. The phase plane stability boundary is constructed using the yaw rate method and double-line method, upon which Control Barrier Function constraints are

peng, tao, Zhang, Weiqi, Li, Zengwen, sudong, jiang

Modified Hybrid A* Collision-Free Path-Planning for Parking a Vehicle in Tight Spaces

2026-01-0046To be published on 04/07/2026

Parking a vehicle in tight spaces is a challenging task to perform due to the scarcity of feasible paths that are also collision-free. This paper presents a strategy to tackle this kind of maneuver with a modified Hybrid-A* path-planning algorithm that combines the feasibility guarantee inherent in the standard Hybrid A* algorithm with the addition of static obstacle collision avoidance. A kinematic single-track model is derived to describe the low-speed motion of the vehicle, which is subsequently used as the motion model in the Hybrid A* path-planning algorithm to generate feasible motion primitive branches. The model states are also used to reconstruct the vehicle centerline, which, in conjunction with an inflated binary occupancy map, facilitates static obstacle collision avoidance functions. Simulation study and animation are set up to test the efficacy of the approach, and the proposed algorithm proves to consistently provide kinematically feasible trajectories that are also

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

Research on Reliability Test Methods for Electric Drive Axle Differentials

2026-01-0007To be published on 04/07/2026

With the rapid socio-economic development, global issues such as the energy crisis and environmental pollution have become increasingly severe. Electric vehicles have garnered growing attention due to their environmental friendliness, simple structure, and high energy efficiency. Electric drive technology is regarded as the most ideal universal driving solution for pure electric vehicles, hybrid electric vehicles, and fuel cell vehicles. The electric drive axle, as a new type of integrated mechatronic transmission system, is being increasingly adopted owing to its advantages such as high drive efficiency, flexible spatial arrangement, and facilitation of digital and automated chassis control. This study focuses on reliability testing methods for the differential in electric drive axles, mainly including the extraction of reliability test conditions and feasibility analysis of the test scheme. The main research contents are as follows: First, based on specific parameters of an electric

Zheng, Hongyu, Li, Ziyu, Wang, Dajiang, tian, kai

Intersection Assist For Vehicle With Dual-Trailers Using Nonlinear Model Predictive Control And Unscented Kalman Filter

2026-01-0074To be published on 04/07/2026

This paper presents a novel approach utilizing Nonlinear Model Predictive Control (NMPC) and Unscented Kalman Filter (UKF) to predict system state and control the trajectory of the vehicle with double trailers in an intersection turn scenario. The UKF estimates vehicle and trailers’ lateral traversal velocity states and the NMPC controls the vehicle acceleration and steering to maintain the vehicle’s desired heading through the turn. The vehicle’s lateral traversal velocity function is formulated using Lyapunov based method which is used as a propagation function in the UKF to improve the estimation accuracy. The lateral traversal velocity is then used as one of the constraints in the NMPC problem. The overall estimation and the control scheme are formulated and assessed in the simulation environment. The simulation results show good tracking and curb avoidance performance.

Malla, Rijan

A Proposed Methodology for Human Operator Modeling and Development of a Virtual Operator Model for Control of a Simulated Compact Track Loader

2026-01-0146To be published on 04/07/2026

A methodology for performing Human Operator Modeling (HOM) using a Caterpillar Model 299D3 XE Compact Track Loader (CTL) is presented. The proposed method uses task analysis techniques to decompose a material excavation and moving task into smaller, individual tasks presented in a task list. A method for verifying and refining the task list is presented, along with a procedure for identifying relevant human operator sensory information and analyzing human decision making in the context of CTL operation. This methodology is then partially verified through the analysis of a non-expert human operator in Vortex Studio, a realistic construction equipment simulator. A modified test course is executed by a non-expert human operator in the simulation environment, and the recorded data is used to create a quantitative Human Operator Model. From this, a Virtual Operator Model (VOM) feedback controller simulating the performance of the human operator is developed. The VOM is implemented using a

Wang, Orson R., Norris, William R., Patterson, Albert E., Soylemezoglu, Ahmet, Nottage, Dustin S.

Simulink DevOps Evolution: Bridging Interactive Platforms for Accelerated Model-Based Workflows

2026-01-0080To be published on 04/07/2026

This paper builds on last year’s paper presenting DevOps automation in the context of model-based development. Following that paper, we interviewed Simulink users in passenger automotive, motorsports, commercial vehicles, aviation, rocketry, and industrial automation. We discovered that much of the benefit of DevOps platforms to reduce product development cycle time relies on their interactive features. We prototyped new tools to bridge interactive DevOps Git-based platforms with model-based development workflows, and then gathered reactions from another round of interviews. Here we present these interactive DevOps workflows with the feedback from these interviews to contextualize how engineering teams could adopt them to accelerate their own model-based workflows.

Mathews, Jon, Ferrero, Sergio, Tamrawi, Ahmed, Sauceda, Jeremias

Optimizing Virtual Scenario Testing for Autonomous Vehicles with Large-Scale Scenario Generation.

2026-01-0050To be published on 04/07/2026

The validation of Advanced Driver Assistance Systems (ADAS) and Automated Driving (AD) Systems, especially at higher automation levels such as SAE Level 3 or 4, demands the testing of a vast array of scenario variants far exceeding the scope of standard safety specifications like Euro NCAP (The European New Car Assessment Programme). Autonomous vehicles require thorough real-world testing to ensure automotive safety. However, public road tests are costly and risky. Instead, virtual scenarios - digital twins of real environments - offer a safe, cost-effective testing alternative. Exhaustive simulation across this high-dimensional scenario space, which includes variations in actor behavior, environmental conditions, and event characteristics, is computationally infeasible. We propose a constraint-solving approach to address this challenge that leverages mathematical and geometric techniques to analytically assess the existence and validity of scenario variants prior to simulation. Two

Karve, Omkar, Saurav, Saket, Purwar, Prabhanshu

Evolutionary Path to Vehicle Zonal E/E Architecture

2026-01-0071To be published on 04/07/2026

The automotive industry is undergoing a major transition in Electrical/Electronic (E/E) architecture, evolving from traditional distributed and domain-based designs to zonal configuration. The rapid growth of software-driven functionality, cross domain function integration, and demands for centralized management have exposed the limitations of distributed and domain-based designs in complexity, scalability, and cost. Zonal E/E architecture addresses these challenges by consolidating computing and I/O resources into high-performance controllers distributed across physical zones of the vehicle, greatly reducing wiring complexity, improving modularity, and enabling scalable, software-defined vehicles. However, this transition cannot be immediate because vehicle design and electrical system solutions have been built on decades of distributed and domain-based development. Moreover, the enabling technologies for realizing zonal E/E architecture, such as high-speed automotive Ethernet, zonal

Jiang, Shugang

Evaluation of PAEB Performance of a GM vehicle using EDR and Ground Truth Data

2026-01-0054To be published on 04/07/2026

In order to determine the on-board EDR data recording characteristics of a GM vehicle, a 2023 GMC Sierra Denali was tested in several pedestrian Automatic Emergency Braking (P-AEB) scenarios. Using a variety of test tools, including the STRIDE robotic platform and its onboard data systems, a GPS/IMU installed in the vehicle, and several camera units, the vehicle was put into collision imminent scenarios in which the crash avoidance systems were actuated. The flags in the EDR data, the order in which EDR events were written, and the correlation between the EDR and data recorded by the aforementioned external acquisition systems were examined for each test case. Testing was done in both forward and reverse scenarios and at low speeds only. These results provide a picture of the current state of the additional data available in current EDRs installed on GM vehicles equipped with P-AEB capability, as well as an insight into the accuracy and meaning of that data which should prove

Bartholomew, Meredith, Arnett, Michael, Guenther, Dennis

Signal Integrity in Distributed BMS: Reliable SPI and Ethernet Communication for Next-Gen EVs

2026-01-0171To be published on 04/07/2026

Distributed battery management systems (BMS) are critical for scaling electric vehicle packs to hundreds of cells, but reliable high-speed communication between modules remains a challenge. Daisy-chained SPI and CAN FD are widely deployed today, while Ethernet is being evaluated for next-generation systems that require higher bandwidth, synchronization, and diagnostics. This paper examines the signal integrity (SI) challenges facing distributed BMS communication, including skew, jitter, crosstalk, and electromagnetic interference (EMI) across PCB traces and wiring harnesses. HyperLynx and SPICE-based simulations are combined with experimental results on a 192-cell test platform to quantify the impact of layout constraints, impedance mismatches, and harness parasitics. Results show that poor SI design can reduce signal margins by more than 18 dB, leading to data corruption and diagnostic failures. Co-design strategies for PCB routing, termination, and shielding are proposed, achieving

Abdul Karim, Abdul Salam

Safety Monitor for Off-Road Planning with Uncertainty Bounded Bekker Costs

2026-01-0141To be published on 04/07/2026

Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance safety monitor that collaborates with any planner and uses a Bekker-based cost model with bounded uncertainty. The monitor builds an upper confidence traversal cost from a lightweight pressure sinkage model identified in field tests and checks each planned motion against two limits: maximum sinkage and rollover margin. If the risk of crossing either limit is too high, the monitor switches to a certified fallback that reduces vehicle speed, increases standoff from soft ground, or stops on firmer soil. This separation lets the planner focus on efficiency while the monitor keeps the vehicle within clear safety limits on board. Wheel geometry, wheel load estimate, and a soil raster serve as inputs, which tie safety directly to vehicle design and let the monitor set clear limits on speed, curvature, and stopping at

Naik, Akshay, Norris, William, Sreenivas, Ramavarapu S., Soylemezoglu, Ahmet, Nottage, Dustin S., Patterson, Albert

A decision-making framework for field manufacturability of vehicle parts in expeditionary environments

2026-01-0143To be published on 04/07/2026

Expeditionary environments (such as remote exploration missions, forward military operations, and disaster response zones) demand adaptive manufacturing solutions to support vehicle sustainment in the absence of traditional supply chains. This work introduces a conceptual mathematical framework for modeling the constraints and trade-offs inherent to expeditionary manufacturing, with a focus on vehicle repair and spare parts fabrication using low-energy and simple automated systems including desktop-scale 3D printers and CNC machines. The model integrates key variables such as energy availability, material transport cost, fabrication time, and environmental limitations to support rapid decision-making on part manufacturability and in-field feasibility. A case study involving the on-demand production of some common wear and failure parts on a vehicle, including suspension components and the water pump, is used to demonstrate how this framework can guide the selection of suitable

Mollan, Calahan, Pandey, Vijitashwa, Patterson, Albert E.

Thermal Management of Gasoline Fuel Tanks

2026-01-0114To be published on 04/07/2026

This study presents a fully integrated, vehicle-level thermal management model for gasoline fuel tanks, designed to predict transient fuel temperatures, tank wall heating, and vapor generation under real-world driving conditions. The model simulates coupled thermal contributions from exhaust radiation, transient underbody airflow, conductive heat transfer, in-tank pump heating, and dynamic changes in fuel composition and level. Validation against on-road measurements shows strong agreement for fuel temperature and vapor flow profiles. Results confirm that exhaust radiative heating is the dominant thermal load, particularly during the post-shutdown heat soak period. A well-designed heat shield reduced peak tank wall temperature by approximately 27 °C, significantly lowering fuel heating and evaporation. Parametric analysis indicates that while fuel Reid Vapor Pressure (RVP) and tank material influence evaporation, their effect is secondary to external heat mitigation. While this model

El-Sharkawy, Alaa, Asar, Mona, Taha, Nahla, Sheta, Mai

Prediction of Battery Self-Discharge Under Sparse Data Using Physics-Guided Machine Learning

2026-01-0155To be published on 04/07/2026

Predicting battery self-discharge across wide temperature ranges and extended durations remains a significant challenge due to the scarcity of physical test data, which is typically limited to a few temperature points and short observation windows. This limitation complicates generalization and increases the risk of inaccurate extrapolation. To address this, the paper introduces a machine learning–based framework designed to predict self-discharge behavior under diverse thermal conditions and long time horizons. Multiple modeling strategies are examined, including feedforward neural networks, long short-term memory (LSTM) architectures, synthetic data generation, and physics-informed integration of governing equations. Particular emphasis is placed on hybrid and physics-regularized models that embed first-principles relationships to guide extrapolation beyond the observed data domain. This approach mitigates the inherent instability and potential errors associated with purely data

Chavare, Sudeep, Zeng, Yangbing, Muppana, Sai Siddhartha, Miao, Yong, Xu, Simon

Benchmarking Driver Responses in Head-On Conflicts: Toward an Objective Protocol for Human and AV Evaluation

2026-01-0534To be published on 04/07/2026

Head-on emergency conflicts present a unique challenge for evaluating driver and automated vehicle (AV) performance. Unlike most emergency scenarios that follow a direct stimulus–response sequence, head-on encounters are characterized by a stimulus–wait–response pattern in which time to contact (TTC) strongly shapes driver behavior. Drawing on naturalistic and simulator data, this study quantified human responses to head-on conflicts. When the opposing vehicle crossed the centerline with more than 2 seconds of TTC, drivers delayed braking until an average of 1.3 seconds (SD = 0.8) before impact, regardless of the timing of the intrusion. By contrast, when TTC was less than 2 seconds, braking was initiated only 0 to 1.0 second before impact. As a result, many drivers applied the brakes less than half a second before collision. These findings provide a meta-analytically grounded benchmark for comparing human behavior to AV decision-making processes and demonstrate the need for conflict

Muttart, Jeffrey, Dinakar, Swaroop, Maloney, Tim, Adikhari, Bikram, Gernhard-Macha, Suntasty

Forensic Acquisition and Analysis of Unsupported Lexus Infotainment Modules via CMD42 Bypass and Data Carving

2026-01-0540To be published on 04/07/2026

Crashes involving passenger vehicles increasingly include models equipped with infotainment modules that are unsupported by commercial vehicle system forensics hardware and software. Examiners facing these systems must overcome challenges in acquiring and analyzing user data, requiring an understanding of both digital forensics principles and the proprietary characteristics of the modules. This paper presents a novel methodology for acquiring data from previously unsupported Lexus infotainment modules, including techniques to bypass CMD42 security locks on SD cards and extract data in a forensically sound manner. Once acquired, the paper outlines methods for analyzing user data through data carving techniques, enabling recovery of information from binary images even when the full file system cannot be reconstructed. Emphasis is placed on maintaining the integrity of the evidence and validating findings through controlled testing. These validation procedures ensure that the recovered

Burgess, Shanon

Leveraging Machine Learning for Occupant Body Size Estimation via B-Pillar Seatbelt Systems

2026-01-0559To be published on 04/07/2026

Occupant body size in vehicles varies significantly, encompassing differences in height, weight, and overall body composition. Adaptive restraint systems, featuring adjustable parameters such as belt load limiters, steering column load limiters and stroke, seat pan stiffness, and airbag pressure, can offer more equitable protection tailored to individual body sizes. In this study, a test rig modeled after the Volvo XC90 was used to collect data from 47 seated participants. Key seatbelt-related parameters, including D-ring angle, belt payout length, lap belt length, and buckle tension, were measured. These measurements were used to train machine learning models to predict occupant characteristics: height, weight, sitting height. The results demonstrate that low-cost sensors embedded in the seatbelt system can provide sufficiently accurate occupant body size estimations to inform adaptive restraint systems. The prediction errors across both training and test datasets were as follows

Wang, Da, Ahmed, Jawwad, Rowe, Mike, Brase, Dan

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