Browse Topic: Human Factors and Ergonomics

Items (9,026)

Development of a GUI-Based Pitch Sequence Optimization Tool for Tyre Noise Reduction

2026-26-0330To be published on 01/16/2026

Minimizing tyre noise is essential for enhancing ride comfort, especially in electric vehicles where the absence of engine noise makes tyre-generated sound more prominent. This work presents the development of a GUI-based pitch sequence optimization tool to support tyre design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. This tool plays a pivotal role in the tire development process, serving as one of the key evaluation criteria for tread pattern approval before mould fabrication. By enabling engineers to generate balanced, low-noise pitch sequences that align with both acoustic targets and engineering constraints, the tool facilitates faster design iterations and smooth integration with downstream processes. Its successful

Sampathraghavan, Lakshmi, Ramarathnam, Krishna Kumar, Mantripragada PhD, Krishna Teja, Ramachandran, Neeraj

An Outer Waist Seal with Integrated Glass Wiping Mechanism for a Window Frame of a Vehicle

2026-26-0011To be published on 01/16/2026

This innovation addresses a major safety concern where drivers experience poor visibility of the Outside Rear View Mirror due to rain, fog, dust, or ice accumulation on the side door window glass. Existing solutions like hydrophobic coatings and heated door window glasses offer limited effectiveness, leading to the need for a more reliable and efficient system. To solve this issue, we have modified Outer Waist Seal by integrating Glass Wiping Mechanism in it. The Outer Waist Seal is a weatherproof strip located at the bottom edge of a vehicle’s side window, attached to the door panel. It prevents heavy water flow, dust, and debris from entering the door cavity while also supporting the window glass during its movement. This system features a stationary fixed arm and a rotating arm with an attached wiper blade, driven by a low-speed, high-torque motor and connected with the vehicle's Body Control Module. Upon activation, the rotating arm with blade wipes the Outside Rear View Mirror

Neelam, Rajat, Chowdhury, Ashok, Panchal, Girish, Kumar, Saurav

Safety Locking and alert system for Container trailers with Geo fencing

2026-26-0273To be published on 01/16/2026

The Container trailer is used worldwide to transport goods & materials especially e-commerce applications with valuable materials. These container trailers are presently locked with a mechanical locking system and often broken and unlocked by unauthorized people. During transportation time, the driver stops for natural calls, food or any other breakdown, the attempt is made to steal the materials. Many cases were known only after damages are done. It has become a serious issue nowadays in the transportation industry. To avoid these problems, we have designed and developed a system that operates pneumatically with digital locking control. The system is designed to ensure proper safety by rigid mechanical locking. It is actuated by a pneumatic system consisting of Directional control valve & pneumatic cylinders. The lock and unlock inputs are given through digitally and the digital controller provides the appropriate input to solenoid operated direction control valve. Based on the

kumaran, Rajasekar

Virtual Validation of ADAS Algorithms Using Driver-in-the-Loop Simulation

2026-26-0050To be published on 01/16/2026

Driver-in-the-Loop (DIL) simulators have become crucial tools across automotive, aerospace, and maritime industries in enabling the evaluation of design concepts, testing of critical scenarios and provision of effective training in virtual environments. With the diverse applications of DIL simulators highlighting their significance in vehicle dynamics assessment, Advanced Driver Assistance Systems (ADAS) and autonomous vehicle development, testing of complex control systems is crucial for vehicle safety. A comprehensive review of current research trends reveals key areas of focus such as realism of simulated experiences through improved vehicle dynamics models and advanced sensory feedback. The integration of virtual and augmented reality technologies help to create more immersive and informative simulations to improve the cost-effectiveness and accessibility of DIL simulation platforms. By examining the current landscape of DIL simulator use cases, this paper critically focuses on

Sharma, Chinmaya, Bhagat, Ajinkya, Kale, Jyoti Ganesh, Karle, Ujjwala

Development of an Software Algorithm Based Semi-automated Data Acquisition System for Gasoline Vehicle Calibration on Chassis Dynamometer

2026-26-0535To be published on 01/16/2026

Vehicle level testing is one of the crucial part of the calibration development. In this, chassis dynamometer is used to collect the vehicle level data. Different engine and vehicle level parameters are logged at various speed and load points covering the entire engine operational zone. This data acquisition is a repetitive activity and covers over 30-40% of the total testing duration. This phase includes base calibration verification, transient development, and emissions-related calibrations, all of which follow a standardized and repetitive sequence. However, these tasks are predominantly performed manually, leading to potential human error and inefficiencies. This paper presents a novel and comprehensive algorithm developed using INCA FLOW software; the first of its kind for this application. Here, crucial vehicle data acquisition activities are identified, mapped into detailed steps. The algorithm introduces a semi-automated, stepwise process for data acquisition during chassis

Kavekar, Pratap Chandrashekhar, Tyagarajan, Sethuramalingam, Agarwal, Nishant Kumar, Shaikh, Wasim, Karadi, Subramanya

Microcontroller-based modular mirror for Heavy and Mid commercial vehicles

2026-26-0018To be published on 01/16/2026

Existing ICE Mid and Heavy commercial vehicles in the Indian and international market are recording a large number of mishaps due to blind spots and non accessibility of the driver to the opposite side mirror in real-time driving. Non-driver side rear view mirror adjustment creates the need for the driver to get down and adjust the mirror manually/ get support from the co-passenger. The paper proposes a solution for a Microcontroller-based compact mirror adjustment system, which will run with minimal economy and highest efficiency. This will assist drivers in aesthetically and safely monitoring of mirror to check on specific blind spots in day conditions. Mirror will be actuated via a Modular control panel, a Dashboard with audio input or button-operated system based on vehicle type and customer need, along with a quick response mechanism to operate the mirror. This will reduce the prone accidents due to non-visibility by approximately 30%, ensuring enhanced road safety and driver

Jambagi, Vaibhavi Vyankatesh, Gangvekar, Onkar, Bhandari, Kiran Kamlakar

The Impact of Color Correlated Temperature (CCT) on Automotive Headlights Performance and Driver Perception

2026-26-0130To be published on 01/16/2026

Automotive lighting has been evolved from simple incandescent lamps to advanced LED based AFS and ADB functions. These lighting play crucial role in road traffic enhancing better visibility and safety to driver as well as other road users. Today’s Automotive Headlights use different light sources viz., Halogen, HID (Xenon), LED, and Laser each emitting light at different correlated color temperatures (CCT), measured in Kelvin (K). Color temperature not only influences visibility but also impacts the amount and perception of glare experienced by other drivers. The study was undertaken to evaluate the effect of correlated color temperature of automotive headlamps on driver visibility and comfort during night driving conditions. The experiment was conducted in a controlled laboratory environment using headlamps with different CCTs ranging from 3000K to 6500K. Participants from various age groups and genders were involved to capture diverse perceptions. Studies confirm that both CCT and

Patil, Mahendra Govind, Kirve, Jyoti Kirve, Parlikar, Padmakumar

Design and Validation of a Collapsible Brake Pedal System for Lower-Leg Protection in Frontal Impacts

2026-26-0500To be published on 01/16/2026

Indian Passenger car accident data indicates that approximately 44% of crashes are frontal impacts. Among the injuries sustained in these crashes, lower leg injuries are notably critical, contributing to nearly 25% of driver occupant injuries. To evaluate such injuries, the Bharat New Car Assessment Program (BNCAP) includes lower leg injury metrics as part of the Frontal Offset Deformable Barrier (ODB64) test. While the overall injury performance is assessed at the vehicle level, BNCAP also monitors vehicle interior intrusions—particularly pedal intrusions—as key contributors to lower limb injury severity. A major challenge in frontal crashes is the intrusion of the vehicle's front-end structure into the occupant compartment. Rigid components, particularly the brake pedal assembly, can be displaced rearward during a crash, significantly increasing the risk of lower leg injuries. Therefore, minimizing pedal intrusions into the driver footwell is critical to enhancing lower leg

Shetti, Rahul R., Kudale, Shailesh, Naik, Nagaraj, Bisen, Badal, Kotak, Vijay, Dudhewar, Swapnil Dudhewar, Bhagat, Amit, Durgaprasad, HNV

Decision-fatigue mitigation in Automotive HMI System

2026-26-0652To be published on 01/16/2026

Abstract - With advent of digital displays in driver cabins in commercial vehicles, the drivers are getting offered with many features. Due to availability of vast number of features, drivers face decision fatigue in choosing the appropriate features. Many are unaware of all available functionalities displayed in the HMI System, leading to a bare minimum usage or complete neglect of helpful features. This not only affects the driving efficiency but also increases cognitive load, especially in complex driving scenarios. Instead of manually choosing between multiple settings, the driver can simply activate a recommendation mode, allowing the system to optimize selections dynamically. Novelty of this proposal focuses on introducing Intelligence in HMI Systems in such a way that it will maximize the usage index and reduce decision fatigue in drivers. To achieve this, an AI-driven recommendation system is introduced, based on User Customization and Adaptive Learning Model along with ML

K, Sunil, Dhoot, Disha

Proactive AI-Enhanced Cybersecurity for Next-Gen Automotive Infotainment ECU

2026-26-0619To be published on 01/16/2026

Abstract With the rapid advancement of connected vehicle technologies, infotainment Electronic Control Units (ECUs) have become central to user interaction and connectivity within modern vehicles. However, this enhanced functionality has introduced new vulnerabilities to cyberattacks. This paper explores the application of Artificial Intelligence (AI) in enhancing the cybersecurity framework of infotainment ECUs. The study introduces AI-powered modules for threat detection and response, presents an integrated architecture, and validates performance through simulation using MATLAB, CANoe, and NS-3. This approach addresses real-time intrusion detection, anomaly analysis, and voice command security. Key benefits include zero-day exploit resistance, scalability, and continuous protection via OTA updates. The paper references real-world automotive cyberattack cases such as Tesla's OTA vulnerability patches, BMW ConnectedDrive exploits, and Jeep Cherokee's Uconnect hack, emphasizing the

More, Shweta, Kulkarni, Shraddha, Kumar, Priyanshu, GHANWAT, HEMANT, Joshi, Vivek

Analysis of Road Accident Statistics for Females in India and Gaps in Safety Regulations

2026-26-0020To be published on 01/16/2026

This paper investigates the current state of road safety for female occupants in India, with a particular focus on road accident statistics and the gaps in safety regulations. According to the Road Accident in India 2022 report by the Ministry of Road Transport and Highways (MoRTH), female occupants constitute 16% of passenger car fatalities. Leveraging a comprehensive dataset of 525 passenger car accidents involving at least one female occupant from the Road Accident Sampling System – India (RASSI), this study evaluates the severity and patterns of injuries sustained by female drivers and passengers. The analysis identifies critical shortcomings in existing safety measures, particularly in addressing anatomical disparities and male-centric safety designs. Gender-disaggregated injury trends reveal heightened vulnerabilities for women in crash scenarios, including disproportionate risks to the chest, neck, and pelvis. Current regulatory frameworks rely on crash test dummies developed on

Ayyagari, Chandrashekhar, G, Santhosh Kumar, Rao, Guruprakash

Driving behavior modelling with Graph Attention Networks using spatial data

2026-26-0661To be published on 01/16/2026

In automotive engineering, understanding driving behavior is crucial for decision on specifications of future system designs. This study introduces an innovative approach to modeling driving behavior using Graph Attention Networks (GATs). By leveraging spatial relationships encoded in H3 indices, we construct a graph-based model that captures dependencies between various vehicle operational parameters and their operational regions using H3 indices. The model utilizes CAN signal features such as speed, fuel efficiency, engine temperature, and categorical identifiers of vehicle type and sub-type. Additionally, regional indices are incorporated to enrich the contextual information. The GAT model processes these heterogeneous features, learning to identify patterns indicative of driving behavior. This approach offers several significant advantages. Firstly, it enhances the accuracy of driving behavior modeling by effectively capturing the complex spatial and operational dependencies

Salunke, Omkar

Integrated Evaluation of Pre-Crash Braking and Crash Injury Outcomes Using Human Body Models and ATDs

2026-26-0019To be published on 01/16/2026

Traditionally, vehicle occupant safety research has focused on passive safety aspects like crashworthiness and occupant restraint systems. However, with the advent of Active Safety technologies such as Forward Collision Warning (FCW) and Autonomous Emergency Braking (AEB), research has expanded to include occupant kinematics during the pre-crash phase. AEB, by inducing occupant movement, often leads to out-of-position (OOP) behavior, compromising available space during the crash phase. Current Anthropometric Test Devices (ATDs) are limited in simulating occupant kinematics during the pre-crash phase, especially in the neck and torso regions. These devices are rigid and unable to replicate human body dynamics during low-acceleration events like AEB. To address this gap, Human Body Models (HBMs) such as THUMS, GHBMC, and SAFER are used to provide more biofidelic simulations. This study begins with physical vehicle trials conducted with human volunteers at various speeds to measure

Pendurthi, Chaitanya Sagar, THANIGAIVEL RAJA, T, Kondala, Hareesh, Sudarshan, B.Sudarshan, Nehe, Vaibhav, Rao, Guruprakash

Configurable and Standardized Test Case Generation using VBA Script

2026-26-0557To be published on 01/16/2026

Test Cases plays a vital and very important role in Software and System testing to verify the functionality as per requirements and meets the customer expectations. The traditional approach of test case generation in the testing field is predominantly manual, time consuming, and prone to human error but less expensive. Each tester tends to have their own approach to creating test cases, which may not cover experience-based test scenarios leading to inconsistencies, and lack of standardization. This lack of uniformity can cause testing deficiencies and make it difficult to ensure comprehensive test coverage. The objective is to develop an automation framework to generate standardized, configurable, modular, reusable and human error free test cases as per user defined inputs based on system requirement specifications. The framework proposed in this paper is known as the Automated Test Case Generator tool. This framework is designed using Visual Basic Applications (VBA) Scripts, in which

Pallavi, Yerragudi, Umarji, Shruti, Tavhare Sr, Sarika, Anilkumar, Sandhya

"Addressing Reflection-Related Issues in Vehicle Interiors: Ensuring Safer and More Comfortable Driving Experiences"

2026-26-0553To be published on 01/16/2026

Reflection significantly influences vehicle driving conditions, impacting both driver comfort and safety. Direct reflections from sunlight or artificial lighting can lead to stress, fatigue, and impaired road visibility, increasing the risk of accidents. Indirect reflections, such as glare from mirrors or dashboard surfaces, pose temporary challenges by distracting drivers and affecting their focus. The intensity and direction of reflections vary with the position of the sun during the day and artificial lights at night, creating visibility issues. Reflection is categorized into daytime reflection, characterized by sunlight-induced glare, and night reflection, driven by internal displays, headlights, and streetlights. To address this, our study focuses on design, vehicle interiors, colour and Pattern to mitigate the Reflection related issues. Our study also focuses on Innovative solutions like anti-reflective coatings, polarized accessories to minimize these effects, ensuring safer and

Jayapandiyan, Raja, DWARAPUDI, DURGAPRASAD, BALU, LAXSHMAANJI, Muthu, Karthikeyan, RANGARAJAN BHARATWAJ, Barath, Natarajasundaram, Balasubramanian

Study of Drive Trace Indices and their correlation with CO2 in Chassis Dynamometer testing

2026-26-0517To be published on 01/16/2026

With introduction of CAFÉ norms in India, the manufacturers of all M1 Category vehicles (not exceeding 3,500kg GVW) must ascertain that they comply with Annual Corporate average CO2 target as defined in regulation. Moreover, this target will become stricter in different stages in upcoming years. Hence CO2 emissions are becoming one of the major focus parameters during vehicle development. There are various factors that can impact CO2 emissions during measurement in test cycle such as MIDC/WLTC. One such major factor is driving variations. Although speed and time tolerances are provided during the test (as part of AIS 137/AIS 175) limit the variation, even within these tolerances, drive-related effects can be significant contributors to test results variability. Monitoring and control of such variations is important to understand the true fuel economy potential of the vehicle. Drive Trace indices are standardized metrics that can be used to evaluate the driving variations. The aim of

ER, Shivram, Rawat, Vijaypal, Khandelwal, Vineet, Kumar, Arun, Malhotra, Jitendra

Reverse Gear Duty Cycle Generation Using Virtual RLD Simulation

2026-26-0405To be published on 01/16/2026

Keywords: RLD (Road Load Data), AVL VSM, AVL Route Studio, Duty Cycle, Transmission, Reverse Gear, Durability The development of transmission systems involves creating duty cycles for bench-level durability evaluations for both forward and reverse gears. For forward gear, vehicles are driven under various real-world conditions over thousands of kilometers, equipped with numerous sensors and components tailored for data collection. In contrast, duty cycles for reverse gear are often based on prior experience or rough estimations due to the lack of clear definition of real world use case. Reverse gear RLD is particularly scarce, especially for heavy-duty vehicles operating in off-road or mining environments, where specific reverse driving paths are not typically followed. This paper presents a detailed methodology highlighting the importance of reverse gear duty cycles by leveraging virtual RLD simulations on various gradients using tools such as AVL Route Studio and AVL VSM. By

Kansagara, Smit, Patel, Hiral, kira, Lucas, Sutar, Suresh, Soor, Debasis

A Noval methodology of compact cooling unit design for Truck applications by using CAE CFD simulation

2026-26-0460To be published on 01/16/2026

The implementation of AC unit on truck as compulsory as per government guideline demands the AC supplier to design a compact and modular AC unit within the available package space. The installation of AC unit inside the vehicle helps the driver to drive safely due to better cabin comfort. This will reduce fatigue due to the long driving of the truck drivers. Thereby the safety of the truck and driver will be saved with the implementation. But there are challenges for AC manufactures to design the compact size AC unit. The challenges like performance, durability, cost and less noise to be met as per customer requirement. To overcome the issue of design at the early stage and compact AC unit within small space is possible with the support of simulation software. AE and CFD plays a major role in this regard. So first unit level CAE and CFD analysis conducted to predict the result. AE used for checking the strength of the mounting bracket of cooling unit and CFD used for verifying the air

Parayil, Paulson

Systemic modelling and simulation approach to estimate Brake response time in a Pneumatic brake systems

2026-26-0469To be published on 01/16/2026

Brake response time in truck air brake systems is crucial for ensuring safety and operational efficiency. This paper presents the development of a simulation model designed to meet all necessary regulatory requirements for Brake response time and as an input to the stopping distance calculations. The actual pneumatic circuit, including brake valves, relay valves, brake chambers, and plumbing have been replicated. The focus is on utilizing 1D simulations to predict the compliance of response time during both the pressurizing (brakes applied) and depressurizing (brakes released) phases of the brake system. A mathematical model is developed using a commercially available 1D simulation tool. This model employs a lumped parameter approach for the pneumatic components, with governing equations derived from compressible flow theory and empirical valve flow characteristics. A parametric study is carried out on variables such as plumbing length, system pressure, and valve orifice diameters. The

Kumbar, Praful, Murugesan, Karthik, Shannon, Rick

Q-Series Child Dummy FE model development and validation for child occupant safety assessment in Automotive crashes

2026-26-0390To be published on 01/16/2026

The Ministry of Road Transport and Highways (MoRTH), Government of India has established BHARAT NCAP to provide a fair, meaningful, and objective assessment of the crash safety performance of cars. This program evaluates vehicles across three key areas, including Child Occupant Protection (COP). A critical component of the COP assessment involves dynamic testing using Q-series child dummies representing a 1½-year-old (Q1.5) and a 3-year-old child (Q3). As per the BHARAT NCAP protocol these dummies are placed in the second-row outboard seating position within Child Restraint Systems (CRSs) and subjected to two primary dynamic impact tests: Offset Deformable Barrier (ODB) conducted at speed of 64 km/hr. and Mobile Deformable Barrier (MDB) Side Impact tests conducted at 50 km/hr. The dynamic assessment of these child dummies is primarily focused on the head, neck, and chest regions to evaluate the effectiveness of the CRSs and overall vehicle safety system in protecting young occupants

Khopekar, Maria, Lakshminarayana, Apoorva, Mohan, Pradeep, Kurkuri, Mahendra

Machine Learning based Engine Mount NVH Life Health Monitoring System

2026-26-0359To be published on 01/16/2026

Refinement for NVH (Noise, Vibration, and Harshness) performance, and long-term vehicle reliability are rapidly evolving in today’s automotive industry. Engine mounts play a central role in isolating powertrain-induced vibrations; their deterioration can significantly affect cabin comfort, powertrain integrity, and customer satisfaction. Prior work in this area has primarily focused on direct mount sensors and physical inspection at service centre after failure. While effective in controlled environments, such methods are not scalable, add system complexity, and increase vehicle cost due to sudden breakdowns—challenges that restrict practical OEM deployment. This paper introduces a novel indirect health monitoring method that leverages a driver seat rail-mounted accelerometer to capture driver specific vibrational responses. By analyzing these signals using machine learning models and domain-specific analytical features, engine mount health is inferred without requiring sensors on the

Iqbal, Shoaib, Dusane, Mangesh

Ambient Light Reflection Analysis using Dimensional Modelling Tools

2026-26-0476To be published on 01/16/2026

The primary motivation is to improve driver safety and visual comfort. This is driven by the need to address the negative impact of ambient light reflecting off Head-Up Displays (HUDs), which can impair visibility through the windshield. There is a need for tools and methods to address this issue proactively during the vehicle design phase. Ambient light reflecting off internal components, specifically the Head-Up Display (HUD), creates unwanted reflections on the windshield. These reflections can obscure the driver's field of view, potentially compromising safety and reducing visual comfort. The extent of this obscuration is influenced by geometrical factors such as the angle of the HUD and the curvature of the windshield, which needs to be analyzed and managed. The study employs a tool-based modeling methodology to trace the pathways of ambient light from its source, reflecting off the HUD, and onto the windshield using a dimensional modeling tool. It focuses on geometrical factors

Muchchandi, Vinod, AKULA, SATYA JAYANTH, Mahindrakar, Pramod, G S, Sharath

Adapting ADAS to Indian Driving and User Needs

2026-26-0045To be published on 01/16/2026

To enhance ADAS usability, safety, and localization in India, this study aims to identify gaps in ADAS system performance and Indian drivers’ expectations by capturing customer’s voice, underlining the need for context-aware ADAS development tailored to emerging Indian markets. The penetration of ADAS in automotive markets is increasing rapidly. However, their effectiveness and acceptance are significantly influenced by regional driving behavior and infrastructure. This study explores the interaction between naturalistic driver behaviour in India and the operational characteristics of ADAS Level 2 systems (FCW, ACC, LCF and BSD) with focus on cars. Using real-world driving data collected from Indian roads, the research aims to highlight the divergence between ADAS design assumptions often based on structured Western traffic environments and the complex, dynamic nature of Indian traffic, characterized by frequent human negotiation, informal road practices, and different vehicle types

SANKPAL, KRISHNATH NAMDEV, Magar, AKSHAY, KHOT, ANKUSH, KULKARNI, ALOK, Perez, Marc

Advanced Defect Detection Techniques Using AI, CAD Data, and Computer Vision

2026-26-0644To be published on 01/16/2026

In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data , By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically . This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.

Kulkarni, Prasad Ramesh, Sahu, Dilip, Joshi, Chandrashekhar, Khatavkar, Akshay, Poddar, Shivani, Deep, Amar

Advanced Sensor less Machine Learning Technique for Early Detection of Engine Oil Degradation

2026-26-0656To be published on 01/16/2026

Maximizing vehicle uptime and reducing maintenance costs are critical objectives in modern automotive systems, making efficient resource utilization a top priority. One key factor is engine oil degradation, which directly affects engine performance, longevity, and overall vehicle efficiency. Current Conventional oil monitoring approaches are real time based on dedicated sensors—can be inefficient, costly, or poorly adapted to varying usage conditions. While earlier studies have explored sensor-based or chemical analysis methods for oil health monitoring, these solutions often lack scalability and cost-effectiveness for widespread adoption. This paper introduces a Machine Learning-based Engine Oil Degradation Detection System that operates non-intrusively using existing vehicle CAN signals, requiring no additional sensors. Key engine parameters such as RPM, Torque, Gear Position, Engine Power, Coolant Temperature, and Odometer readings are trained with tri-bological properties

Dusane, Mangesh, Tade, Vilas, Iqbal, Shoaib

Experimental Study to Investigate and Control Image Blurriness due to IRVM Vibration

2026-26-0321To be published on 01/16/2026

Vibration is one of the prominent factors that determine the quality & comfort level of a vehicle. Moreover, if vibration occurs in areas that are almost entirely within customer touchpoints (during either city or highway driving conditions), it could become a critical factor behind the deterioration of brand image within the market. The interior rear-view mirror (IRVM) is one of the important components inside passenger cabin, providing drivers with a clear view of the rear traffic. However, vibrations induced by engine operation, road irregularities, and aerodynamic forces can cause the IRVM to oscillate, leading to image blurriness and compromised visibility and safety. This paper investigates the underlying causes of IRVM vibrations and their impact on image clarity. Through a combination of experimental analysis and computational modelling, we identify key factors contributing to mirror instability. The findings indicate the specific frequencies of vibration, particularly those

Khan, Aamir Naved, Saraswat, Vivek, Jha, Kartik, SINGH, HEMENDRA, Seenivasan, Gokulram, Khan, Nafees

Crash Pulse Characterization for the Passenger Vehicle Fleet in India.

2026-26-0029To be published on 01/16/2026

A crash pulse is the signature of the deceleration experienced by a vehicle and its occupants during a crash. The deceleration-time plot or crash pulse provides key insights into occupant kinematics, occupant restraints, occupant loading and efficiency of the structure in crash energy dissipation. Analysing crash pulse characteristics like shape, slope, maximum deceleration, and duration helps in understanding the impact of the crash on occupant safety and vehicle crashworthiness. This paper represents the crash pulse characterization study done for the vehicles tested at ARAI as per the ODB64 test protocol. Firstly, the classification and characterization of the crash pulses is done on the basis of the unladen masses of the vehicles. The same are further analysed for suitability of mathematical waveform models such as Equivalent Square Wave (ESW), Equivalent Triangular Wave (ETW), Equivalent Sine Wave (ESW), Equivalent Haversine Wave (EHSW) as well as EDTW (Equivalent dual trapezia

Jaju, Divyan, Mishra, Satish, Kulkarni, Dileep, Borse, Tanmay, Mahindrakar, Rahula Ashok, Mahajan, Rahul

Data analytics methodology for vehicle quality complaint analysis

2026-26-0654To be published on 01/16/2026

Automobiles have become a part of people's everyday life. Customers base their trust on a brand's reputation while making a buying decision. With the evolving trends, feature advancements, automobiles have become a complex system. Ensuring product quality amidst system complexities is necessary to maintain the brand value & ensure customer satisfaction. Efficient addressal of customer quality complaints is pivotal in maintaining product quality. Until recent times, manual analysis using traditional data processing tools has been used for vehicle complaint analysis. However, considering the large quantum of data in new age vehicles with more number of control units, it becomes time-consuming, expertise dependent and susceptible to human errors. Given this & the advent of new age machine learning techniques & data analysis tools that can handle large amount of data, it is imperative to adopt them for vehicle complaint analysis. This research paper puts forth a method to analyze vehicle

Venkatesan, Prasanna, Raju, Vivek

Representative Drive cycle velocity profiles Prediction using ML Algorithms for Energy Efficiency

2026-26-0638To be published on 01/16/2026

Maximizing vehicle energy efficiency and performance is a high priority for the automotive industry as customer expectations rise. Engineers constantly face the challenge of balancing the conflicting goals of achieving superior performance and maximizing energy efficiency, all while meeting increasingly tight development timelines. Leveraging digital methods can potentially enable a considerable reduction in development lead times. Driving cycles act as standardized measurement procedures for certifying a vehicle's fuel efficiency and driving range. Representative velocity profiles condense numerous real-life driving cycles to enable quicker energy analysis and driver feedback evaluation. This paper introduces a novel methodology for generating synthetic drive cycles, such as average velocity cycles and ideal consumption velocity cycles, based on real-life driving scenarios. In this study, the importance of creating representative drive cycles to enhance vehicle performance and energy

Kanakannavar, Rohit, Kelkar, Kshitij, Sadalge, Anand

Data-Driven Prediction of Damper durability Cycles Using AIML Techniques

2026-26-0550To be published on 01/16/2026

The suspension dampers play a pivotal role in controlling suspension dynamics, especially during rapid suspension movements such as pothole impacts, speed bumps, and off-road conditions. The dampers directly influence the ride comfort, vehicle stability. Ensuring the durability of these valves is essential to maintain consistent performance throughout the vehicle's lifecycle. To validate the valve configuration at high speed, in current development practices, durability cycles are typically derived through physical data collection on actual vehicle driven on proven ground tracks. While this method provides accurate real world validation, it is highly time consuming and resource intensive. The dependency on full vehicle testing also limits early phase of validation, creating bottlenecks in the product development cycle. An AIML based methodology is presented in this paper to predict the HSVD cycles for damper validation. The AIML algorithm was trained using the historical test data and

Kabbin, Chetan D., Suryawanshi, Vishal, Daphal, Pratap, Kulkarni, Prasad

NVH Refinement on the Agriculture Tractor using Coupled Test and Simulation Approach

2026-26-0316To be published on 01/16/2026

The Indian farmers choice of agriculture tractor brand is driven by the ease of operation and fuel efficiency. However, the customer preference for operator comfort is driving many tractor OEMs for improvement in noise and vibration at the operator location. Also, the compliance to CMVR regulation for noise at operator ear location and vibration at driver touch point location are mandatory for all the tractors in India. NVH refinement development of the tractor plays a critical role in achieving the regulated noise level and improved tactile vibration In presented work, Noise Source Identification (NSI) is carried out to identify and rank airborne and structure borne noise sources at tractor level through elimination method followed by engine level testing in hemi anechoic chamber to identify the major noise radiating components by using noise and vibration measurement, sound intensity mapping tools. The outcome of NSI has revealed silencer, timing gear cover and oil sump to be highest

Gaikwad, Atul Annasaheb, Bankar, Harshal, Yadav, Prasad S, Harishchandra Walke, Nagesh

Optimizing Brake Pedal Feel and Driver Comfort in Buses with Pneumatic Braking Systems

2026-26-0536To be published on 01/16/2026

Brakes are a critical safety component in vehicles, and every parameter of the braking system plays a vital role in vehicle operation. Among these, brake pedal feel and driver confidence are key factors, in addition to achieving the required brake force, deceleration, and stopping distance. These aspects depend on the system-generated torque, available pneumatic pressure, lining material properties, and Electronic Braking System (EBS) parameters. This paper focuses on the factors influencing brake pedal feel while maintaining a balance between driver comfort and confidence during bus operation. Under optimal braking conditions, brake pedal response and brake torque gradient must align with the driver’s deceleration demands. The braking system must respond promptly, completing the application in the shortest possible duration. The brake torque gradient values specified in the EBS file should neither be too low nor too high, and the brake pedal feel must remain consistent throughout the

Pujari, Sachin, Salunkhe, Swapnil, Ali, Tauqeer

Infotainment-Free Sunroof Control Testing Using National Instruments Framework

2026-26-0519To be published on 01/16/2026

Verification of sunroof operation via voice commands conventionally necessitates a fully assembled vehicle platform integrated with an updated Body Control Module (BCM) and infotainment software. This hardware-software dependency presents significant limitations, particularly during the early stages of development, where rapid validation and iteration are critical. Additionally, vehicle availability and software readiness often act as bottlenecks in the validation process. To address this, a novel approach has been developed to simulate sunroof operations—including both physical switch and voice command inputs—using a National Instruments (NI) system. This setup eliminates the reliance on the vehicle’s BCM and infotainment system by simulating LIN commands directly through the NI interface. The integration of the sunroof module with the NI system facilitates comprehensive bench-level testing, including functional validation, endurance evaluation, and abuse case simulation. This

GHANWAT, HEMANT, Lad, Aniket Suryakant, Joshi, Vivek, More, Shweta

Early prediction of relaxation voltage & detection of state of battery for functional safety

2026-26-0166To be published on 01/16/2026

During parking condition of vehicle, state of the battery is uncertain as it goes through the relaxation process. In such scenarios the battery voltage may exceed the functional safety limits. If we cross the functional safety limits it is hazardous to the driver as well as the occupant. In this case relaxed voltage plays a crucial role in identifying the safe state of the battery. To estimate the relaxed cell voltage there are methods such as RC filter time constat modeling and relaxation voltage error method. The problem with these solutions is the waiting time and accuracy to determine the relaxation voltage. In this manuscript a solution is proposed which ensures the above problem gets reduced. To achieve the reduction of relaxation voltage estimation time, a python sparse identification of nonlinear dynamics (PySindy) is used which identifies and fits an equation model based on observing the battery characteristics at different SOC and temperatures. The implementation is done and

Pandey, Priyanshu, Nilajkar, Ankur, Panda, Abinash

Artificially Intelligent Rapid Rescue Vehicle System

2026-26-0642To be published on 01/16/2026

human lifestyle. The automotive industry plays a crucial role as travel is an integral part of human lifestyle. This indeed has increased the need and demand for automotive domain to step ahead with technology and innovations. Especially, related to ADAS features and AI/ML based algorithms to provide comfort, safety, and many other factors for the consumers. The busy life of human beings has shown increased rate of many health-related issues like stress, anxiety, heart attacks, blood pressure, accidents etc. The existing system in vehicles detects health emergencies and triggers SOS to the emergency service center. However, several catastrophic events occur due to delayed information, thus there is a need for a proactive solution that combines technology and human safety. In this work, we have investigated the different methods which detect the health issues of occupants in a vehicle by monitoring their stress level, heart rate, blood pressure etc., We propose a solution which helps to

Eswarappa, Asha, Nagaraj, Chaitra, Mudassir, Syed

Driving performance impact analysis on EV components for efficient, safe, and intelligent mobility

2026-26-0655To be published on 01/16/2026

Electric vehicles (EVs) are the cornerstone of sustainable transportation, but their performance and component longevity are heavily influenced by driving behaviors. This study proposes a comprehensive analytical framework to assess how different driving styles affect the operational health of key EV components such as the battery pack, motor, and DC-DC converter. Various driving styles such as aggressive, moderate, and economical are discriminated against using dynamic vehicle operation signatures including acceleration and braking intensity, turning profiles, and load variations. These behavioral patterns are reflected in the electrical responses, namely current and voltage waveforms across power electronic systems. By analyzing these electrical signatures, a range of KPIs can be estimated for each component, offering insights into their operational stress and degradation trends. Experimental analysis using real-time EV datasets validates the framework’s ability to predict and

Deole, Kaushik, Kumar, Pankaj, Hivarkar, Umesh

Material Optimization in console armrest to comply occupant safety in crash test

2026-26-0007To be published on 01/16/2026

Indian passenger vehicles sales touched an all-time high in FY25.Today’s customer expects high level of aesthetics, safety and connected features in the vehicle Interiors. This has created more diverse and demanding customer base that values interior design and quality. This has led OEMs to offer modern Indian mass car interiors with features like big infotainment system, Console Armrest…etc. The vehicle console armrest assembly is an integral part of a car's interior, designed to enhance comfort, ergonomics, and functionality for the driver and passengers. The console armrest is a complex assembly of many child parts like Armrest cushion/ sliding mechanism/ latch, locking mechanism/ hinge mechanism and storage compartment etc., Console hard plastic parts are the primary source of injuries when occupants interact with them in the event of an accident. Poorly designed armrests can contribute to flyoff of child parts in the event crash and can cause injuries to occupant. Therefore

A D, BALAMURUGA, BADDAM, SATHISH, MANGAL, GAUTAM, SINGH, DEEPAK, Shekhar, Ravi, Singh, Amit

Cabin Heat-up Thermal Assessment for Human Comfort in Passenger Car

2026-26-0408To be published on 01/16/2026

The HVAC (Heating, Ventilation and Air conditioning) system is designed to fulfil the thermal comfort requirement inside vehicle cabin. Thermal comfort is significantly subjective which predominantly dependent on occupant’s physiological condition. Vehicle AC performance is evaluated by air flow and local temperature thus, thermal comfort assessment is carried out by mapping of velocity and temperature at various places inside cabin. There is need to have Simulation methodology for heating cabin during cold climate to assess ventilation system effectiveness. Thermal comfort modelling involves human manikin, complex cabin material along with environmental condition in expensive transient simulation. Present study employed with LBM (Lattice-Boltzmann Method) based PowerFLOW solver coupled with finite element based PowerTHERM solver to simulate the cold soaking and heating up of cabin. Thermal comfort is subjective to human physiological modelling thus in-built Berkeley human comfort

Baghel, Devesh Kumar, Kandekar, Ambadas, Kumar, Ravi, Dimble, Nilesh

A Data-Centric Approach to Identify Optimal NVH simulation Tools and Solvers

2026-26-0356To be published on 01/16/2026

The world is rapidly evolving towards a data-driven paradigm, with widespread adoption of tools and techniques such as Artificial Intelligence, Machine Learning, Digital Twins, and Cloud Computing. In the automotive sector, vast amounts of data are being generated through both physical and digital test evaluations. Among these, Computer-Aided Engineering (CAE) stands out as one of the largest contributors to data generation, as physical testing is often cost-prohibitive due to the need for prototypes and complex test setups. The field of Automotive Noise, Vibration, and Harshness (NVH) is advancing exponentially, driven by stringent regulatory norms and growing customer demand for comfort. Digitally advanced techniques are playing a pivotal role in revolutionizing NVH processes. Data generation via CAE tools has become an integral part of engineers' daily operations, with the selection of appropriate CAE software and solvers being critical. This choice impacts factors such as user

Hipparge, Vinod, masurkar, Nikita, Arabale, Vinand, Billade, Dayanand

New generation Natural Rubber-Based Bump Stopper with Improved NVH Characteristics

2026-26-0292To be published on 01/16/2026

In automotive suspension systems, components like bump stoppers and jounce bumpers play critical roles in controlling suspension travel and enhancing ride comfort. Material selection for these components is driven by functional demands and performance criteria. Traditionally, Natural rubber (NR) has traditionally been favoured for bump stopper applications due to its excellent vibration absorption, tear resistance, cost-effectiveness, and biodegradability. However, in more demanding environments, it has been largely replaced by microcellular polyurethane (PU) elastomers, which offer superior durability, environmental resistance, and enhanced noise, vibration, and harshness (NVH) performance. PU's high compressibility, low lateral expansion, and low compression set make it the material of choice across automotive, aerospace, and industrial sectors. Other materials like thermoplastic elastomers (TPE/TPU) and EPDM rubber are also used, offering advantages such as recyclability, ease of

Murugesan, Annarajan, Perumal, Mathavan

Next-Gen Driver Health and Wellness Platform for Fatigue Detection and Emotional Wellbeing Monitoring

2026-26-0639To be published on 01/16/2026

Driver fatigue and emotional distress are major contributors to traffic accidents, especially among long-haul and professional drivers, making their detection a critical area in road safety and public health. While existing research has explored various sensor-based and wearable solutions to monitor driver states, these approaches often suffer from high cost, intrusiveness, or limited scalability. Camera-based systems have recently gained attention for being less invasive and more practical for real-world deployment; however, many still depend on multiple sensors or cloud-based processing, which raise concerns around energy consumption, privacy, and integration complexity. To address these gaps, we present a sustainable, camera-only Driver Health and Wellness Platform for real-time fatigue detection and emotional wellbeing monitoring. The system leverages a single in-cabin camera and applies lightweight, edge-optimized computer vision models to analyze facial features, eye dynamics

Iqbal, Shoaib, Imteyaz, Shahma

Calibration strategy to address abnormal engine noise in cold transient driving condition

2026-26-0585To be published on 01/16/2026

Passenger vehicle users often maneuver their cars in diverse and unpredictable driving patterns. The vast and varied terrain of the Indian subcontinent further complicates this scenario, introducing unique challenges due to differences in driving expertise, vehicle usage, and environmental conditions. A specific challenge addressed in this paper arises during cold to ambient engine temperatures and transient driving conditions—a critical phase for engine calibration to ensure optimal drivability and emissions performance. With current calibration practices, an after-burn like abnormal engine noise was observed during certain transient driving patterns in cold to ambient temperature conditions. This paper presents a novel calibration methodology designed to eliminate such abnormal noise. The proposed approach involves a step-by-step transient calibration strategy refinement, making the calibration process more robust and adaptable to any driving behavior. The paper outlines the specific

Suna, Bhagyashree, Tyagarajan, Sethuramalingam, Pise, Chetan, Aishwarya, Amritansh

A Scientific approach to identify the source of intermittent steering rattle noise and implementing the design solutions

2026-26-0346To be published on 01/16/2026

Body-on-frame vehicles are well-regarded for their durability and off-road capabilities, but their structural design often makes them more vulnerable to noise, vibration, and harshness (NVH) issues. Vibrations originating from uneven roads are transmitted through the suspension and steering assemblies, sometimes resulting in rattles or other disturbances. These vibrations can be amplified by the inherent flexibility in the body-to-frame mounting system. In such vehicles, the steering system plays a critical role in driver comfort and is highly sensitive to vibrational inputs from the road surface, especially on coarse or uneven terrain. Occasionally, these inputs result in subtle rattle noises that are perceptible only to the driver and may not be detected under controlled testing environments. This poses a challenge for engineers trying to isolate and resolve such intermittent NVH phenomena. Identifying the source requires a combination of real-world driving evaluations, structural

Ramesh Chand, Karan Kumar, Gopinathan, Haridoss, Kabdal, Amit

Addressing Seat Belt Discomfort Among Indian Female Driving Population Through Anthropometric Data Collection and Simulation

2026-26-0016To be published on 01/16/2026

The rate 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 experiences dis-comfort when wearing seat belts—whether while driving or 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 50th percentile 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. This highlighted the need to collect region-specific anthropometric data for India. During this research work, Indian anthropometric data was collected through the Size India 2.0 project, covering a wide demographic region across India. This study was in

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

Comprehensive research study examining Tyre wear and its Indian perspective.

2026-26-0604To be published on 01/16/2026

Automobile emissions refer to the gases and particles released into the atmosphere by vehicles during their operation. These emissions contribute to environmental pollution and have an impact on human health and the environment. This paper assimilates findings from a comprehensive research study examining tyre wear and its Indian perspective. Tyre wear understood as a factor affecting road safety, environmental health, and economic sustainability. The study identifies factors affecting tyre wear and provides overview regarding tyre wear generation in India, encompassing road infrastructure, vehicle characteristics, driving patterns, and environmental factors. Moreover, it examines the adverse effects of these particles on human health, such as respiratory ailments and cardiovascular diseases, as well as their impact on ecosystems. This paper delves measures to measure tyre wear and safeguard both environmental and public health. It also covers the tyre wear measurement methodologies to

Joshi, Amol, Khairatkar, Vyankatesh, Belavadi Venkataramaiah, Shamsundara

Reverse Engineering of CAN (Controller Area network) of an Electric vehicle

2026-26-0150To be published on 01/16/2026

The communication between different vehicle electronic controller units (ECU) for various applications (I.e. To propel the vehicle or for In-vehicle Infotainment) CAN (Controller Area Network) is most frequently used for In-Vehicle communication. Given the proprietary nature and lack of standardization in CAN (Controller Area Network) configurations, which are often not disclosed by manufacturers, the process of CAN reverse engineering becomes highly complex and cumbersome. Additionally, the scarcity of publicly accessible data on electric vehicles, coupled with the rapid technological advancements in this domain, has resulted in the absence of a standardized and automated methodology for reverse engineering the Controller Area Network (CAN). This process is further complicated by the diverse CAN configurations implemented by various Original Equipment Manufacturers (OEMs), which are often not disclosed to the public. In this paper the manual approach is taken for reverse engineering

KUMAR, ROHIT, Sahu, Hemant, Penta, Amar, Bhatt, Purvish

Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation

2026-26-0672To be published on 01/16/2026

Artificial Intelligence (AI) is fundamentally reshaping the landscape of automotive engineering, particularly in passenger vehicles where comfort, safety, and customization are paramount. This paper presents a comprehensive review of current and emerging AI-driven applications in passenger cars, including intelligent vehicle insurance, real-time traffic optimization, personalized driving experiences, emotion recognition, and advanced EV battery management. The integration of AI technologies—ranging from machine learning and computer vision to natural language processing and deep neural networks—enables predictive maintenance, adaptive driver-assist systems, and next-generation human-machine interfaces. AI’s role in vehicle insurance is also explored through behaviour-based risk scoring and claims automation. Furthermore, emotion-aware cabin systems are discussed, which aim to detect driver fatigue, stress, or distraction to improve road safety and mental wellness. The paper also

Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip

Refinement of Road Induced Steering Wheel Vibration in Electric Vehicle

2026-26-0337To be published on 01/16/2026

Nowadays, customers expect excellent cabin insulation and superior ride comfort in electric vehicle. OEMs focuses on fine tuning the suspension system in electric vehicle to isolate the road shocks which finally offers superior ride quality. This paper focuses on the enhancing the ride comfort by reducing the steering wheel vibration which mainly originates due to road inputs. Higher steering wheel vibrations are perceived on the test vehicle when driven on rough road at the speed of 50 kmph. To determine the predominant force transfer path, Multi reference Transfer Path Analysis (MTPA) is performed on the front and rear suspension. Based on the finding from MTPA, various recommendations are explored and the effect of each modification is discussed. Apart from this, Operational Deflection Shape (ODS) analysis is carried out on the entire steering system to identify the deflection shape at the operating condition. Based on ODS findings, recommendations like dynamic stiffness

S, Nataraja Moorthy

Beyond ATD Dummies-Investigating Pelvic Locking and Torso Kinematics Using Human Body Models in Frontal Impact Scenarios

2026-26-0002To be published on 01/16/2026

Occupant Safety systems are usually developed using anthropomorphic test devices (ATDs), such as the Hybrid III, THOR-50M, ES-2, and WorldSID. However, in compliance with NCAP and regulatory guidelines, these ATDs are designed for specific crash scenarios, typically frontal and side impacts involving upright occupants. As vehicles evolve (e.g., autonomous layouts, diverse occupant populations), ATDs are proving increasingly inadequate for capturing real-world injury mechanisms. This has led to the adoption of computational Human Body Models (HBMs), such as the Global Human Body Models Consortium (GHBMC) and Total Human Model for Safety (THUMS), which offer superior anatomical fidelity, variable anthropometry, active muscle behaviour modelling, and improved postural flexibility. HBMs can predict internal injuries that ATDs cannot, making them valuable tools for future vehicle safety development. This study uses a sled CAE simulation environment to analyze the kinematics of the HBMs

Raj, Pavan, Rao, Guruprakash, Pendurthi, Chaitanya Sagar, Nehe, Vaibhav, Chavan, Avinash

Occupant Kinematics and injuries during high speed side impacts: An analysis of ARAI data 2016-2024

2026-26-0027To be published on 01/16/2026

The objective of the present study was 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 analyzed for driver dummy in high speed side impacts for vehicle model years, MY2016-2024. Automotive Research Association of India side impact crash data is examined. The test procedure involved a 50.0 km/h moving deformable barrier (MDB) impacting the sides of stationary vehicles. Instrumented 50th-percentile male EURO SID-2 dummy was positioned in the driver seat. Occupant kinematics data, including head accelerations, Head Injury Criterion (HIC15), Torso deflections at thorax and abdominal ribs, spine accelerations at T12, and pelvis accelerations were evaluated and compared. The “peak” and “time to- peak” responses were compared across different vehicle model years. The effect of delta-V, vehicle MY, on occupant kinematics was examined. For

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

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