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Recent SAE Edge™ Research Reports

Browse All 177

Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response

EPR202501711/24/2025

The wing-in-ground effect (WIG) vehicle represents a significant advancement in aerodynamics and vehicle design, leveraging the ground effect phenomenon to enhance lift and reduce drag when flying close to the surface. This unique capability allows WIG vehicles to achieve higher payloads, longer range, and greater fuel efficiency compared to traditional aircraft, making them an attractive option for modern military and global disaster response applications. Wing-in-Ground Effect Vehicles: From Modern Military and Commercial Development to Global Disaster Response discusses future disaster response, logistics, and military applications for WIG vehicles, including the ongoing development of aerospace and transportation technology. Relavant advancements in materials and propulsion systems holds promise for further enhancing WIG performance and operational range. Additionally, cost-effective and powerful flight computers with various types of mission-enabling sensor suites from the

Next-gen AI for Aerospace Engineering

EPR202501609/22/2025

Despite growing investments, the widespread adoption and scalable deployment of generative artificial intelligence (AI) remains a challenge due to data trustworthiness, regulatory uncertainty, interpretability, and ethical governance. The need to accelerate automation and maintain the human-in-the-loop demonstrates broader questions of responsibility and transparency. Next-gen AI for Aerospace Engineering investigates the transformative role of GenAI within aerospace engineering, examining its shift from conventional workflows toward more AI-driven solutions in design, manufacturing, and maintenance. It emphasizes GenAI’s emerging ability to automate repetitive mundane tasks, reduce design complexity, and optimize engineering pipelines. The report underscores the need for validation methods that must align AI-generated outputs with physics-informed models, integration with legacy engineering tools (e.g., computational fluid dynamics, finite element analysis, digital twins), and

Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles

EPR202501509/22/2025

The next generation of mobility, driven by shared, driverless, connected, and electrified vehicles, holds strong potential to advance sustainability through lower emissions and improved resource efficiency. However, critical questions remain regarding their true environmental impact, including battery lifecycle management, material consumption, and circular manufacturing practices. Sustainable Circular Future Mobility: Environmental Impact of Next-gen Vehicles explores these unresolved issues, focusing on the shift from internal combustion to electric vehicles, supply chain challenges, regulatory gaps, and the operational realities of sustainable productization. It also critically examines the risks of greenwashing, the need for consistent standards, and the role of intersectoral collaboration—with energy, urban planning, information and communications technologies, and waste management sectors—in building resilient, scalable solutions. The report provides strategic recommendations and

Small, Mobile, and Autonomous Agricultural Robots

EPR202501208/13/2025

The automation of labor-intensive picking and planting operations is having an immediate impact in the agricultural indutry. In its simplest form, robotic automation can reduce the labor and soil disturbance while enabling organic soil cover and increasing species diversification through precision approaches to planting, weeding, and spraying. With this, pesticides and fertilizers can be applied in a more targeted way, and with machinery visiting fields more frequently, earlier and more targeted intervention can occur before pests become established. Small, Mobile, and Autonomous Agricultural Robots identifies issues that need to be resolved fo for this technology to thrive, including improving methods of acquiring and labeling training data to facilitate more accurate models for specific applications. It also discusses concepts such as general-purpose mechanical platforms for use as carriers of agricultural automation systems with high stability, positional accuracy, and variable

Safety Impacts of Active Safety and Driving Automation Features

EPR202501308/13/2025

Advanced technologies that assist the human driver or reduce (or even eliminate) the human driver’s role are becoming increasingly prevalent in new light-duty vehicles used by the general public. These technologies are divided between Active Safety features that monitor the human driver and vehicle motion and act intermittently to mitigate and avoid crashes, and Driving Automation features that assume some or all of the dynamic driving task from the human driver. Both types of technologies have the potential to reduce injuries and save lives by reducing the frequency and/or severity of crashes. Safety Impacts of Active Safety and Driving Automation Features addresses the current capabilities and future potential for Active Safety and Driving Automation features to reduce crash frequency and severity and provides an overview of the state of the industry for both types of features, including current deployments, trends, and anticipated rollouts. Gaps in knowledge, unsettled issues, and

Hybrid Data- and Physical Model-driven Safe and Intelligent Motion Planning and Control for Autonomous Vehicles

EPR202501407/18/2025

Autonomous vehicle motion planning and control are vital components of next-generation intelligent transportation systems. Recent advances in both data- and physical model-driven methods have improved driving performance, yet current technologies still fall short of achieving human-level driving in complex, dynamic traffic scenarios. Key challenges include developing safe, efficient, and human-like motion planning strategies that can adapt to unpredictable environments. Data-driven approaches leverage deep neural networks to learn from extensive datasets, offering promising avenues for intelligent decision-making. However, these methods face issues such as covariate shift in imitation learning and difficulties in designing robust reward functions. In contrast, conventional physical model-driven techniques use rigorous mathematical formulations to generate optimal trajectories and handle dynamic constraints. Hybrid Data- and Physical Model-Driven Safe and Intelligent Motion Planning and

Product Assurance in the Age of Artificial Intelligence

EPR202501105/21/2025

Driven by the vast consumer marketplace, the electronics megatrend has reshaped nearly every sector of society. The advancements in semiconductors and software, originally built to serve consumer demand, are now delivering significant value to non-consumer industries. Today, electronics are making inroads into traditionally conservative, safety-critical sectors such as automotive and aerospace. In doing so, electronics—now further propelled by artificial intelligence—are disrupting the functional safety architectures of these cyber-physical systems. Electronics have created the world of cyber-physical systems, raising broader concerns about the broader category of product assurance. Product Assurance in the Age of Artificial Intelligence continues the work of previous SAE Edge Research Reports in examining open research challenges arising from this shift, particularly in automotive systems, as core electronic technologies (e.g., the combination of software and communications) have even

Edge Artificial Intelligence in Connected, Cooperative and Automated Mobility

EPR202500905/20/2025

With many stakeholders involved, and major investments supporting it, the advancements in automated driving (AD) are undoubtedly there. Generally speaking, the motivation for advancing AD is driver convenience and road safety. Regarding the development of AD, original equipment manufacturers, technology start-ups, and AD systems developers have taken different approaches for automated vehicles (AVs). Some manufacturers are on the path toward stand-alone vehicles, mostly relying on onboard sensors and intelligence. On the other hand, the connected, cooperative, and automated mobility (CCAM) approach relies on additional communication and information exchange to ensure safe and secure operation. CCAM holds great potential to improve traffic management, road safety, equity, and convenience. In both approaches, there are increasingly large amounts of data generated and used for AD functions in perception, situational awareness, path prediction, and decision-making. The use of artificial

Leveraging Advanced Data Technologies for Smart Traffic Management

EPR202500805/20/2025

The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and

Automated Vehicles and Infrastructure Enablers: Dedicated Lanes

EPR202500704/24/2025

Dedicated lanes provide a simpler operating environment for ADS-equipped vehicles than those shared with other roadway users including human drivers, pedestrians, and bicycles. This final report in the Automation and Infrastructure series discusses how and when various types of lanes whether general purpose, managed, or specialty lanes might be temporarily or permanently reserved for ADS-equipped vehicles. Though simulations and economic analysis suggest that widespread use of dedicated lanes will not be warranted until market penetration is much higher, some US states and cities are developing such dedicated lanes now for limited use cases and other countries are planning more extensive deployment of dedicated lanes. Automated Vehicles and Infrastructure: Dedicated Lanes includes a review of practices across the US as well as case studies from the EU and UK, the Near East, Japan, Singapore, and Canada. Click here to access the full SAE EDGETM Research Report portfolio.

Latest Journal Issues

Browse All 16

Passenger Vehicle Systems

Electrified Vehicles

Advances and Current Practices in Mobility

Sustainable Transportation, Energy, Environment, & Policy

Connected and Automated Vehicles

Transportation Cybersecurity and Privacy

Vehicle Dynamics, Stability, and NVH

Transportation Safety

Alternative Powertrains

Commercial Vehicles

Engines

Materials and Manufacturing

Fuels and Lubricants

Aerospace

Passenger Cars - Mechanical Systems

Recent Books

Browse All 718

Safety, ADAS, and Cybersecurity: Vol. 4

EPRCOMPV01202512/29/2025

Electrification: Vol. 3

EPRCOMPV04202512/29/2025

Manufacturing and Industry 4.0 : Vol. 2

EPRCOMPV06202512/29/2025

Commercial Vehicles: Vol. 2

EPRCOMPV05202512/29/2025

Aerospace Developments: Vol. 7

EPRCOMPV07202512/29/2025

Infrastructure Enablers for Automation: Vol. 4

EPRCOMPV02202512/29/2025

Automated Vehicles: Development, Testing, and Validation: Vol. 4

EPRCOMPV03202512/29/2025

The Racing & High-Performance Tire

R-59412/17/2025

The Racing & High-Performance Tire originally published in 2003 and continues to be a best-seller. Following up on his first two books, Inside Racing Technology and Inside Racing: A Season with the PacWest CART Team, Paul Haney presents a new book revealing the complexities of tires, how they influence vehicle dynamics, and how to use tires in the engineering of racing and high-performance cars. More than 150 photos and drawings help the reader learn the colorful history and unique characteristics that make the pneumatic tire one of the world's most complex and useful products.

Manufacturing Reliability Growth for Automotive Engineering Volume III

R-55112/11/2025

As the third installment in SAE International's DOE for Product Reliability Growth series, this volume explores the critical intersection of manufacturing processes, reliability, and profitability in automotive engineering. With a sharp focus on innovation, cost-efficiency, and customer satisfaction, this book demonstrates how design of experiments (DOE) methodologies can transform product quality through smarter manufacturing decisions. From structural assemblies to additive manufacturing, Volume III offers hands-on, data-driven guidance for engineers and professionals. Key topics include: • Structural Joints: Analyze and optimize bonded and mechanical joints-bolts, rivets, welds, adhesives, and more-using real-world DOE case studies to ensure robust assembly. • Mechanical Fabrication: Improve precision and consistency in processes like injection molding, drilling, heat treatment, and surface finishing through targeted DOE applications. • Electronic Fabrication: Harness DOE to enhance

Pedestrian Accident Reconstruction

R-59010/30/2025

As technology advances, so too must the methods we use to investigate and understand pedestrian collisions. Pedestrian Accident Reconstruction provides a much-needed update to the field—one that reflects the dramatic rise in digital evidence and the growing role of simulation in modern reconstructions. While earlier texts laid the foundation for understanding pedestrian impacts, they were written before the widespread use of video footage, onboard vehicle sensors, and powerful simulation software. This book addresses that shift. It introduces updated methods that incorporate event data recorders, surveillance video, dash cams, and advanced simulation tools like the PC-Crash multibody pedestrian model. These technologies allow for more precise, repeatable, and illustrative reconstructions than ever before. The book highlights when and how simulation can enhance an investigation—especially in complex scenarios such as roof vaults, sideswipes, or collisions that defy conventional

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CONNECTOR ACCESSORIES, ELECTRICAL, BACKSHELL, ENVIRONMENTAL, CABLE SEALING, 90°, CATEGORY 1A (FOR AS50151 CRIMP, MIL-DTL-26482 SERIES 2, AS81703 SERIES 3, AND MIL-DTL-83723 SERIES III CONNECTORS)

AS85049/9D (Current)

01/20/2026

AE-8C1 Connectors Committee

Steel, Corrosion-Resistant, Investment Castings, 16Cr - 4.1Ni - 0.28Cb - 3.2Cu, Homogenization, Solution, and Precipitation Heat Treated (H900), 180 ksi (1241 MPa) Tensile Strength (17-4)

AMS5344H (Current)

01/19/2026

This specification covers a corrosion-resistant steel in the form of investment castings homogenized and solution and precipitation heat treated to 180 ksi (1241 MPa) tensile strength.

AMS F Corrosion and Heat Resistant Alloys Committee

Human-Centric Automotive Interior Lighting Assessment: A Feedback-Based Approach

2026-26-0132

01/16/2026

In today’s world, automotive interior lighting systems not only need to meet rigorous internal test standards but also need to adapt with the changing customer’s expectation across different vehicle segments. As per technological advancements and consumer demands, these systems have become increasingly advanced and software driven. Traditionally, validation relied on physical integration with vehicle hardware, particularly infotainment system. However, this conventional approach presents several limitations, including dependency on mature hardware and software, challenges in testing and synchronization across multiple lighting modules, and constraints in design validation accuracy. To address these limitations, this paper introduces an innovative approach that employs real-time hardware-in-the-loop (HIL) simulation for virtual lamp testing. This method facilitates autonomous testing, enabling independent validation of interior lighting systems within a controlled virtual environment

Shah, Kunal, Joshi, Vivek S., Mandloi, Prince

A Study of Electric Motor Configuration for Multi Axle Electric Heavy Duty Commercial Truck Application to Attain Maximum Potential of Torque Vectoring

2026-26-0084

01/16/2026

As the air pollution level rises around the globe, the need for alternative sources of energy increases, and this need applies to automotive industry also. Commercial vehicles are one of the major sources of air pollution around the world as they have impactful applicability in our day to day life. With growing advancement in mobility solutions, commercial vehicles are undergoing transformation to improve efficiency, safety and performance. One of the emerging technologies is of torque vectoring which is a concept used to provide better traction and stability to the vehicle in different driving conditions and used in the vehicle having multi motor configuration. Advance torque vectoring concept coupled with electric motor can react to dynamic driving conditions by providing instant torque. The concept of torque vectoring can be useful for heavy commercial vehicles used in off-road applications such as mining because torque vectoring helps in better weight management, cornering

Agarwal, Pranjal, Chaudhari, Gitesh, Gangad, Vikas, Penta, Amar

Safer Trucks for India: Smart Tech Fusion

2026-26-0031

01/16/2026

Commercial vehicle sector (especially trucks) has a major role in economic growth of a nation. With improving infrastructure, increasing number of trucks on roads, accidents are also increasing. As per RASSI (Road Accident Sampling System India) FY2016-23 database, commercial vehicles are involved in 42% of total accidents on Indian roads. Involvement of trucks (N2 & N3) is over 25% of total accidents. Amongst all accident scenarios of N2 &N3, frontal impacts are the most frequent (26%) and causing severe occupant injuries. Today, truck safety development for frontal impact is based on passive safety regulations (viz. front pendulum – AIS029) and basic safety features like seatbelts. In any truck accident, it is challenging rather impossible to manage comprehensive safety only with passive safety systems due to size and weight. Accident prevention becomes imperative in truck safety development due to extremely high energy involved in front impact scenarios. The paper presents a unique

Joshi, Kedar Shrikant, Gadekar, Ganesh, Date, Atul, Koralla, Sivaprasad

A Comparative Analysis of Road Accident Data Collected: A Multi Country Study of Traffic Accidents in India and Western Nations

2026-26-0247

01/16/2026

This paper presents a comparative analysis of road accident datasets from India, the United States, France, and the United Kingdom, utilizing authoritative sources such as Open Government Data (OGD), the National Highway Traffic Safety Administration (NHTSA), GOV.UK, and the French Road Safety Observatory. The research aims to uncover cross-country trends and discrepancies in accident reporting practices and assess whether enhanced documentation can contribute to reducing accident frequency. Effectively reducing the incidence of road accidents necessitates a rigorous understanding of their underlying causal mechanisms, which can only be achieved through comprehensive, data-driven analyses of accident records and systematic parameter comparisons with the Integrated Road Accident Database (iRAD). The primary objective is to identify documentation gaps within the Indian context and propose improvements to ensure comprehensive, high-quality data availability for researchers and

Raj, Aswin, Raja, Dheepan, Abhimanyu Shinde, Antriksh

A Case Study of Emission Optimization using Machine Learning

2026-26-0229

01/16/2026

The Exhaust Emission Control is a vital part of automotive development aimed at ensuring effective control of pollutants such as NOx, CO, and HC. The traditional method of calibrating emission control strategies is a highly time-consuming process, which requires extensive vehicle testing under a variety of operating conditions. The frequent updates in emission legislation requires a high-efficiency process to achieve a faster time-to-market. The use of Machine Learning (ML) in the domain of emission calibration is the need of the hour to proactively improve the process efficiency and achieve a faster time-to-market. This paper attempts to explores emerging trend of Machine Learning (ML) based data analysis that have improved the overall process efficiency of emission control calibration. The data generated by automated programs could be used directly in data analysis with minimal or no need for data cleaning. The Machine Learning (ML) models could be trained by historical data from

Dhayanidhi, Hukumdeen, Balasubramanian, Karthick, A, Akash

Advanced Driver Assistance for Sunroof Misuse: Alarm Trigger and Speed Limiting System

2026-26-0041

01/16/2026

Sunroof-equipped vehicles are gaining rapid popularity in India, especially among young and urban users. However, unsafe practices like occupants protruding through the sunroof during driving have led to increasing injuries and fatalities, particularly in sudden braking or collisions. This behavior, prohibited under the Motor Vehicles Act, remains an overlooked safety risk in today’s vehicles. This paper presents an industry-first innovation: an Automated Safety Alarm and Speed Control System designed to detect and prevent sunroof misuse. Using integrated photoelectric and infrared beam sensors, the system detects human extension beyond the sunroof boundary while the vehicle is in motion. Upon detection, it triggers a tiered safety response: an immediate dashboard warning, an audible alert if vehicle speed exceeds 15 km/h and an active speed limiter that restricts vehicle speed to 20 km/h until safe conditions are restored. This marks a shift from passive warnings to active vehicle

Padmanapan, Gopi, Yadav, Sanjeev

Algorithm Development for AI Driven Path Planning Using Augmented Reality for Navigating in Indian Complex Road Scenarios

2026-26-0038

01/16/2026

The road infrastructure in India has complex navigational challenges with most of the road unstructured especially in rural areas. Decision-making becomes a challenge for drivers in unpredictable environments such as narrow roads, flooded roads and heavy traffic. In this paper, an Augmented Reality based ML-Algorithm for Driver Assistance (ARMADA) has been proposed that improves awareness to safely maneuver in these conditions. The methodology for development and validation of this Augmented Reality (AR) based algorithm contains multiple steps. Firstly, extensive data collection is conducted using real time recording and benchmark datasets like Berkeley Deep Drive (BDD) and Indian Driving Dataset (IDD). Secondly, collected data are annotated and trained using an optimal machine learning (ML) model to accurately identify the complex scenario. In third step, an ARMADA algorithm is developed, integrating these models to estimate road widths, detect floods and provide seamless driver

Anandaraj, Prem Raj, Sivakumar, Vishnu, Thanikachalam, Ganesh, L, Radhakrishnan, Motoki, Yaginuma, Selvam, Dinesh Kumar

Crowdsourcing Indian Traffic Scenarios for ADAS Development and Testing

2026-26-0046

01/16/2026

In the Indian context, introduction of ADAS can play a positive role in improving road safety by assisting the driver and preventing unsafe driver behaviour. Technologies like Automated Emergency Braking (AEB), Lane Keep System, Adaptive Cruise Control, Driver Drowsiness Detection, Driver Alcohol detection etc., if deployed safely and used in a safe manner can help prevent many of the current road deaths in India. Safe deployment and safe use of such ADAS technologies require the systems to operate without failure within their operational design domains (ODD) and not surprise the drivers with sudden or unpredictable failures, to help develop their trust in the technology. As a result, identifying test scenarios remain a key step in the development of Advanced Driver Assistance Systems (ADAS). This remains a challenge due to the large test space especially for the Indian context due to the unpredictable traffic behaviour and occasional road infrastructure. In this paper, we introduce a

Serry, Hamid, Dodoiu, Tudor, Alakkad, Fadi, Zhang, Xizhe, Khastgir, Siddartha, Jennings, Paul

Real-Time Lane Change Risk Estimation Using Extended Lane Change Risk Index (ELCRI) and Fault Tree Analysis

2026-26-0040

01/16/2026

Accidents during lane changes are increasingly becoming a problem due to various human based and environment-based factors. Reckless driving, fatigue, bad weather are just some of these factors. This research introduces an innovative algorithm for estimating crash risk during lane changes, including the Extended Lane Change Risk Index (ELCRI). Unlike existing studies and algorithms that mainly address rear-end collisions, this algorithm incorporates exposure time risk and anticipated crash severity risk using fault tree analysis (FTA). The risks are merged to find the ELCRI and used in real time applications for lane change assist to predict if lane change is safe or not. The algorithm defines zones of interest within the current and target lanes, monitored by sensors attached to the vehicle. These sensors dynamically detect relevant objects based on their trajectories, continuously and dynamically calculating the ELCRI to assess collision risk during lane changes. Additionally

Dharmadhikari, Mithil, S, Mrudula, Nair, Nikhil, Malagi, Gangadhar, Paun, Cristin, Brown, Lowell, Korsness, Thomas

Pre-Crash Characteristics of Motorized Two-Wheeler Crashes on Indian Roads

2026-26-0034

01/16/2026

India has emerged as the world’s largest market for motorized two-wheelers (M2Ws) in 2024, reflecting their deep integration into the country’s transportation fabric. However, M2Ws are also a highly vulnerable road user category as according to the Ministry of Road Transport and Highways (MoRTH), the fatality share of M2W riders rose alarmingly from 27% in 2011 to 44% in 2022, underlining the urgency of understanding the circumstances that lead to such crashes. This study aims to investigate the pre-crash behavior and crash-phase characteristics of M2Ws using data from the Road Accident Sampling System – India (RASSI), the country’s only in-depth crash investigation database. The analysis covers 3,632 M2Ws involved in 3,307 crash samples from 2011 to 2022, representing approximately 5 million M2Ws nationally. Key variables examined include crash configuration, collision partner, road type, pre-event movement, travel speed, and human contributing factors. The study finds that straight

Govardhan, Rohan, Padmanaban, Jeya, Jethwa, Vaishnav

Market Research on Actual User Experience and Efficacy of ADAS Features in Indian Driving Conditions

2026-26-0035

01/16/2026

Advanced Driver Assistance Systems (ADAS) have become increasingly prevalent in modern vehicles, promising improved safety and reducing accidents. However, their implementation comes with several challenges and limitations. The efficacy of these systems in diverse and challenging road conditions of India, remains as a concern. For deeper understanding of the ADAS feature related concerns in Indian market due to the factors such as unique road conditions, traffic situations, driving patterns, an extensive study was done throughout Indian terrain. The functionality and performance of different ADAS features were evaluated in the real-world scenarios. The objective data of the observations and occurrence conditions were captured with help of data loggers & camera setups inside the vehicle. This research paper represents a comprehensive study on the challenges faced by user while using ADAS enabled cars in Indian road conditions. We captured the performance data of various ADAS features

Kumbhar, Prasad Uttam, Pyasi, Praveen

System-Level Simulation to Design a Hydrogen Powered Refuse Collection Vehicle Based on Real-World Fleet Operational Data

2026-26-0399

01/16/2026

This study addresses one of the challenges in the energy transition of heavy-duty vehicles by converting a diesel Refuse Collection Vehicle (RCV) into a hydrogen-powered prototype. The research is part of the VeH2Dem project funded by NextGenerationEU and focuses on dimensioning the complete hydrogen propulsion system for a RCV, including the energy storage capacity, without compromising payload or operational functionality. The development of the propulsion system is based on a comprehensive analysis of operational data extracted from fleet management systems, complemented by detailed instrumental monitoring of various collection routes. This methodology ensured that the prototype inherits performance equivalent to the original internal combustion engine vehicle across all evaluated scenarios. The vehicle performance objectives were established following a comparative analysis with solutions currently available in the RCV market, incorporating statistical analyses to ensure continuous

Cano, Pablo, Barrio, Roberto, Roche, Marina, de-Lima, Daniela, Batista, Sara, Bertolí, Xavier

Virtual Reality in Assembly Simulations: Outpacing Tecnomatix Process Simulate for Faster Time-To-Market

2026-26-0398

01/16/2026

Virtual Reality technology is emerging as a transformative solution in the manufacturing industry. It offers significant advantages over traditional tools like Tecnomatix Process Simulate in assembly & ergonomic simulations. Analysis using PS is time-consuming and lacks real-time human interaction as it relies on detailed modelling and sequential workflows, which will delay the identification of assembly no-build conditions and ergonomic issues. This paper evaluates the time and the cost-saving potential of VR in assembly processes and explores its role in minimizing the need for physical prototypes across various stages of vehicle development. VR provides interactive environments, enabling interaction with 3D models and real-time collaboration with various teams across the globe. This leads to faster identification of assembly process flaws, quicker iteration cycles, and a reduced need for physical prototypes in the station development process for the lines. VR allows individuals to

Nagendran, Rakesh Kumar

1D Simulation Approach for Common Rail Injection Systems for a Marine 2 Stroke Diesel Engine

2026-26-0395

01/16/2026

This study presents a comprehensive 1D simulation approach of an automotive solenoid-based diesel fuel injector and a common rail injection system for a marine engine using Simcenter AMESim. The injector model was developed to analyse the injection rate and total injected fuel at various solenoid actuation durations (1.2 ms and 2.0 ms) and common rail pressures. The experimental results from a well-established research study are used for validating the simulation results of the solenoid-based injector. Overall error in total fuel injected ranges from -6.14 percent to 1.93 percent, while timing errors for the start of injection vary from 1.7° crank angle (CA) to 0.08° CA and the end of injection from 2.8° CA to 0.20° CA at 1200 rpm demonstrating strong agreement at higher rail pressures (above 1000 bar) and solenoid actuation times. Building on this validated injector model, a detailed marine common rail system was developed incorporating key hydraulic components: a check valve to

Bhoware, Yash, Pise, Uday, Saha, Dipta, Gaikwad, Nilesh

Occupant Kinematics and Injuries during High Speed Side Impacts: An Analysis of ARAI Data 2016-2024

2026-26-0027

01/16/2026

The objective of the present study is to examine trends in occupant kinematics and injuries during side impact tests carried out on vehicle models over the period of time. Head, shoulder, torso, spine, and pelvis kinematic responses are analysed for driver dummy in high speed side impacts for vehicle model years, MY2016-2024. Side impact test data from the tests conducted at The Automotive Research Association of India (ARAI) is examined for MY2016-2024. The test procedure is as specified in AIS099 or UNECE R95, wherein a 950kg moving deformable barrier (MDB) impacts the side of stationary vehicle at 50km/hr. An Instrumented 50th percentile male EUROSID-2 Anthropomorphic Test Device is positioned in the driver seat on the impacting side. Occupant kinematic data, including head accelerations, Head Injury Criterion (HIC15), Torso deflections at thorax and abdominal ribs, spine accelerations at T12 vertebra, and pelvis accelerations are evaluated and compared. The “peak” and “time to

Mishra, Satish, Borse, Tanmay, Kulkarni, Dileep, Mahajan, Rahul

Integrated Side Fairing and Crash Protection System for High Voltage EV Battery Safety

2026-26-0028

01/16/2026

This paper presents a novel structural solution for side impact protection of high-voltage battery packs in electric trucks. While electric vehicles offer benefits like zero emissions and independence from fossil fuels, in turn present challenges in meeting crashworthiness standards and safety regulations. The device addresses the critical need for effective battery protection & styling of battery electric vehicles. The integration of a hybrid corrugated panel system with plastic side fairings is innovative, combining crashworthiness with aerodynamic and aesthetic benefits. The crash protection features two hat-section steel channels at the top and bottom and corrugated steel sheet with alternating ridges is attached to these channels. Corrugated panels are enforced with help of backing strips. This assembly is mounted on shear plates at both ends, secured to the vehicle's frame rail. During a side impact event, the plastic side fairings absorb the initial impact, crumpling easily. If

Badgujar, Prathamesh, Devendra, Awachare, Hansen, Benjamin

Boosting the Development of a BEV Rear Twist Beam Suspension Through a Pioneering Approach: ADAMS Real Time on Driving Simulator

2026-26-0397

01/16/2026

Twist beam suspensions are widely utilised in passenger vehicles because of their simplicity and cost-efficiency, yet they provide engineers with a complex challenge as their performance depends entirely upon the structural properties of the beam itself. Traditional methodologies rely on the generation of Modal Neutral Files (MNF) based upon vehicle dynamics requirements and packaging constraints, which is a highly time-consuming process that starts failing to fulfil the demands of a market where development times are being exponentially reduced. Besides this, part of flexible body’s real behaviour might be lost in the process of converting multibody models into parametric ones, which, in turn, presents difficulties in modifying compliant-related items. Thanks to a novel approach followed jointly by Applus+ IDIADA & Mahindra, quick identification and optimisation of key tuneable items is achieved by employing a hybrid solution that combines full flexible and FE elements in Hexagon

Osorio, Alejandro García, Prabhakara Rao, Vageesh, Asthana, Shivam, Rasal, Shraddhesh

Method and System of Detecting Obstacle around Vehicle Door

2026-26-0026

01/16/2026

Vehicle door-related accidents, especially in urban environments, pose a significant safety risk to pedestrians, infrastructure and vehicle occupants. Conventional rear view systems fails to detect obstacles in blind spots directly below the Outside Rear View Mirror (ORVM), leading to unintended collisions during door opening. This paper presents a novel vision-based obstacle detection system integrated into the ORVM assembly. It utilizes the monocular camera and a projection-based reference image technique. The system captures real-time images of the ground surface near the door and compares them with calibrated reference projections to detect deviations caused by obstacles such as pavements, potholes or curbs. Once such an obstacle is detected the vehicle user is alerted in the form of a chime.

Bhuyan, Anurag, Khandekar, Dhiraj, Jahagirdar, Shweta

Addressing Safety Belt Discomfort among Female Driving Population through Data Collection and Simulation

2026-26-0016

01/16/2026

The number of female drivers in India is increasing alongside the rapid growth of the Indian automotive industry. A driving comfort survey conducted among female drivers revealed that many of them experienced discomfort when wearing safety belts—while driving and as front-seat passengers. This discomfort is primarily due to a phenomenon referred to as “neck cutting.” The root cause of neck cutting is likely related to vehicle design, which is traditionally based on Anthropometric Test Devices (ATD’s) representing the 5th, 50th & 95th percentile (%tile) of the global population. However, a literature review indicated that the anthropometric dimensions of the Indian populations are generally smaller than those of the global for the respective candidate. To validate the neck-cutting issue, various female candidates were asked to sit in the Driver’s seat for physical measurements trials. Accordingly, methodology was developed to quantify neck cutting parameters objectively. A correlation

Kulkarni, Nachiket A, Chitodkar, Vivek V, Eknath Chopade, Santosh, Mahajan, Rahul, Yamgar, Babasaheb S

Adaptive Restraints for Equitable Protection

2026-26-0015

01/16/2026

Real-world crashes involve diverse occupants, but traditional restraint systems are designed for a limited range of body types considering the applicable regulations and protocols. While conventional restraints are effective for homogeneous occupant profiles, these systems often underperform in real-world scenarios with diverse demographics, including variations in age, gender, and body morphology. This study addresses this critical gap by evaluating adaptive restraint systems aligned with the forthcoming EURO NCAP 2026 protocols, which emphasize real-world crash diversity and occupant type. Through digital studies of frontal impact scenarios, we analyze biomechanical responses using adaptive restraints across varied occupant demographics, focusing on head and chest injury (e.g., Chest Compression Criterion [CC]). This study used a Design of Experiments (DOE) approach to optimize occupant protection by timing the actuating of these adaptive systems. The results indicate that activating

satija, Anshul, Suryawanshi, Yuvraj, Chavan, Avinash, Rao, Guruprakash

Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization

2026-26-0396

01/16/2026

With increased deterioration of road conditions worldwide, automotive OEMs face significant challenges in ensuring the durability of structural components. The tyre being the primary point of contact with the road is expected to endure harshest of impacts while maintaining the other performance functions such as Ride & Handling, Rolling resistance, Braking. Thus, it is considered as the most challenging component in terms of design optimization for durability. The current development method relies on physical testing of initial samples, followed by iterative construction changes to meet durability requirements, often giving trade-off in Ride & Handling performance. To overcome these challenges, a frugal simulation-based methodology has been developed for predicting tyre curb impact durability before vehicle-level testing so that corrective action can be taken during the design stage.

Sundaramoorthy, Ragasruoban, Lenka, Visweswara

Vehicle Usage Digital Twins: Mobility Analysis Test Case

2026-26-0394

01/16/2026

In the evolving landscape of the automotive industry, this study presents an innovative approach to developing digital twins for driver profiles, establishing a standardized and scalable procedure for collecting and analyzing driving data on a global scale. The proposed methodology centers on the development of a robust cloud infrastructure, including Data Lake and associated services, designed for efficient storage and processing of large volumes of data from multiple markets and vehicle types. The research introduces an adaptable procedure for data collection campaigns, applicable to diverse global markets and encompassing a wide range of vehicles, from internal combustion engines to electric and hybrid models. A key feature of this approach is the establishment of advanced data decoding protocols, enabling precise interpretation of CAN network information from vehicles of different manufacturers and models, even when the CAN structure is not previously known. The study defines

Arturo, Rubio, Marín Saltó, Anna, Diaz, Francisco, Olivencia, Sergio

Multiphysics Simulation Approach for Evaluating Thermo-Structural Performance of Electric Motors Using Spatial Electromagnetic Loss Mapping

2026-26-0387

01/16/2026

High power and torque density electric motor is finding increasing demands in modern-day electric and hybrid vehicles because of compact and light-weight designs. These high-performance requirements are achieved by increasing the current flow, strengthening the magnetic field as well as downsizing the motor dimensions and hence can lead to multiple failure modes if not designed properly. Higher current flow results in increased magnitude of losses within the motor components such as ohmic loss, iron loss, hysteresis loss and mechanical losses. All these localized losses contribute to higher operating temperature and temperature gradient that can act as a catalyst to several modes of failure. Hence, accurate prediction of temperature distribution across the motor components is very crucial to come up with a robust and durable motor design. A common approach of predicting component temperature is by assuming bulk losses for lamination stack, hairpin and magnets. This approach might be

Munshi, Irshad Ahmed, Elango, Gokul, Karmakar, Nilankan, Prasad, Praveen

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