Browse Topic: Transportation Systems

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Indian City Electric Bus Powertrain Optimization Using Active Learning Simulation Methodology2026-26-0657To be published on 01/16/2026
Public transport electrification is going to play a massive role in India's COP26 pledge to achieve net zero emissions by 2070. India plans to electrify 800,000 buses in a push towards 30% EV penetration by 2030. Further encouraged by government incentives under National Electric Bus Program (NEBP), eBus market is expected to grow at a CAGR of ~86% annually over the next 5 years. With most OEMs going for fleet electrification for reducing CO2 emissions and to cater to growing demand in Indian cities for cleaner public transport, improving powertrain efficiency and performance of state-of-the-art eBuses is a natural progression of e-mobility sector development in India. The first step in designing powertrain for an electric city bus is to determine the motor(s) size and transmission specifications (number of gears, gear ratios etc.). Complications arise due to a wider and non-linear operation range of eBus. This study focuses on powertrain optimization for a medium duty electric city
Emran, Ashraf, Berry, Sushil, Xia, Feihong, Chen, Bicheng, Sandhu, Rouble
Revolutionary EV Motors Innovation in E-mobility in Depth Analysis of Emerging Technologies, Comparative Insights & Their Ground Breaking Impact on Electric Vehicle Performance2026-26-0073To be published on 01/16/2026
This paper delivers a forward-looking data-driven assessment of the transformative innovation in electric vehicle motor systems with targeting breakthroughs in the power density, energy efficiency, thermal robustness, manufacturability & better intelligent control. A rigorous Multi Criteria Decision Making (MCDM) framework is done to systematically evaluate and defining the rank of emerging motor technologies across eight weighted performance indicators. The findings reveal that which design strategies & material advancements offering the greatest potential for redefine propulsion performance that enabling lighter more compact & more efficient drivetrain capable of sustained high power operation. High ranking solution exhibit strong alignment with the industry's push toward scalable, low cost & rare earth-independent systems while other are identified as high risk/high reward pathway requiring targeted research to overcome critical problems. By integrating engineering performance
Jain, Gaurav, PREMLAL, P, Pathak, Rahul, Gore, Pandurang
Decision-fatigue mitigation in Automotive HMI System2026-26-0652To 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
"Design and process Optimization of Suspension Components Under RWUP-based Loading Conditions"2026-26-0514To be published on 01/16/2026
Title: Challenges faced during design and manufacturing of POM (Polyoxymethylene) ring in Macpherson strut suspension. Abstract: Designing and manufacturing a POM (Polyoxymethylene) ring for a MacPherson strut suspension system brings a unique set of challenges due to the high-performance and durability demands for Indian road application. POM ring along with bump used in the shock absorber is designed to absorb the strong shock coming from the road inputs when suspension travel reached to the maximum limit there by absorbing the impact energy and preventing it from transferring it to the body. A bump stopper for a suspension of a vehicle is made of poly urethane (PU) and POM ring (Polyoxymethylene). The bump stopper forms of a bellows shape during the absorption of impact energy. Bellow or wrinkle in which concaves and convexes are repeated is formed on the outer surface of the bump stopper. POM ring is placed in the concaves of bump stopper which will define load, deflection
Koritala, Ashok Kumar, Malekar, Amit, kulkarni, Purushottam, S, SIVASHANKAR, Mishra, Harshit, Ganesh, Mohan Selvakumar, Patnala, Avinash, J, Ramkumar, NAYAK, Bhargav, M, Sudhan
Establishing a Scalable Virtual Framework for ADAS Validation: Traffic Jam Pilot with Real-World Scene Integration2026-26-0506To be published on 01/16/2026
Advanced Driver Assistance Systems (ADAS) are instrumental in improving road safety and minimizing traffic-related incidents. However, their development and validation processes are resource-intensive, requiring substantial time, cost, and domain-specific expertise. Moreover, real-world testing introduces significant safety challenges. To address these issues, virtual simulation platforms offer high-fidelity environments for the secure and efficient testing of ADAS functions. This research presents a virtual validation framework for a Traffic Jam Pilot (TJP) algorithm utilizing such simulators. The framework features detailed models of camera and radar sensors, capturing essential parameters like detection range and field of view, alongside a vehicle plant model and road infrastructure modeling that includes elements such as curvature, slope, banking angles, and varying lane widths. A perception stack is developed using synthetic sensor data and is integrated with the TJP control
Agrawal, Mridul, Ithape, Avinash, Sharma, Prashant, Trivedi, Abhishek
Quantifying the Energy Consumption of HVAC Operation and Its Impact on the Range of Electric Buses Across Diverse Climatic Conditions2026-26-0204To be published on 01/16/2026
Electric buses (e-buses) are essential to sustainable public transport, but their real-world efficiency and range are heavily affected by auxiliary systems, particularly the Heating, Ventilation, and Air Conditioning (HVAC) system. This study investigates how ambient temperature variations and HVAC loads influence energy consumption, range, and efficiency in e-buses operating under diverse climatic conditions. The methodology combines field data collection from urban e-buses across seasons—including extreme summer and winter—with controlled lab testing. Field measurements included ambient temperature, HVAC demand, vehicle speed, state of charge (SOC) variation, and energy consumption. These inputs were used to develop real-world duty cycles, replicating actual thermal loads, passenger profiles, idling periods, and driving patterns. In the lab, these cycles were simulated using a chassis dynamometer and environmental chamber, with HVAC systems tested at controlled ambient temperatures
Vishe, Prashant, Dalela, Saurabh, Joshi, Madhusudan, Saraswat, Shubham
Integrating V2V and V2I Communications for Enhanced Traffic Safety and Efficiency in Connected Vehicular Networks2026-26-0271To be published on 01/16/2026
This paper presents a new approach to improve road safety and traffic flow by combining vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Our study focuses on a system that connects vehicles with each other and with traffic signals to share real-time data about speed, position, and road conditions. Using both analytical models and experimental simulations built in MATLAB/Simulink, we developed a system that predicts and advises the optimal speed for vehicles approaching an intersection. In our design, a Green Light Optimized Speed Advisory (GLOSA) feature suggests an ideal speed for drivers so that they can pass through green lights without unnecessary stopping. This not only improves traffic flow but also reduces fuel consumption and lowers the risk of accidents. We validated our system through a series of simulations and real-time traffic scenarios. The results show that our approach can adapt dynamically to changes in vehicle behavior and traffic density
PINTO, COLIN AUBREY, Shah, Ravindra, Karle, Ujjwala
Investigation and Reduction of Road Noise due to transient road inputs in Electric Vehicle2026-26-0358To be published on 01/16/2026
Higher road noise is perceived in the cabin when the test vehicle encounters road irregularities like bump or pothole in the public roads. The sudden transfer of transient road inputs inside the body caused objectionable cabin noise. Measurements are conducted on the test track at different road surfaces to identify the patch where the objective data well correlated with the noise measured at the public road. Wavelet analysis is carried out to identify the frequency zones since the events are transient in nature. Transfer Path Analysis (TPA) is conducted in both time domain and frequency domain to identify the nature of the noise and the limitation in each of the methodologies are explained. The dominant path through which the transient road forces are transferring inside the body are also identified. Based on the outcome of TPA, various countermeasures like reduction of dynamic stiffness of suspension and cradle bushes , structural modifications on the path are proposed to reduce the
S, Nataraja Moorthy
Optimizing Suspension Joint Reliability: Overcoming Bolt Loosening and Torque Variability in Automotive Production2026-26-0492To be published on 01/16/2026
In modern automotive manufacturing, ensuring the integrity of suspension joints under real-world driving conditions is a critical aspect of vehicle safety and performance. These joints endure substantial transverse loads and large vibrations due to irregular road surfaces, dynamic manoeuvres, and varying environmental factors. As a result, bolt loosening becomes a significant concern, compromising joint integrity and overall vehicle reliability. This paper delves into the challenges associated with maintaining joint integrity, specifically focusing on pre-load determination, torque application, and production-related issues. The pre-load generated during torquing is the primary factor that ensures a suspension joint remains securely fastened under dynamic road conditions. This pre-load is derived using road load data acquisition (RLDA) inputs, which capture the forces acting on the joint during actual driving scenarios. RLDA inputs provide critical insights into the forces experienced
Kumar, Sabeesh, Vasant Kumar, Jesse Daniel, Mishra, Harshit, Senthil Raja, T, NAYAK, Bhargav, M, Sudhan, NAMANI, Prasad, Vibhute, Shekhar
Revolutionizing Urban Mobility in India: The Emergence of the 2-3 Wheel Combi Vehicle and the L2-5 Regulatory Framework.2026-26-0187To be published on 01/16/2026
Urban mobility in India is evolving rapidly under the pressures of population growth, increasing congestion, and the demand for innovative transportation solutions. With infrastructure development and urbanization accelerating, there is a growing need for versatile vehicles that can adapt to both personal and commercial purposes while addressing urban vehicle density. To meet this demand, the 2-3 Wheel Combi Vehicle has emerged as a groundbreaking modular mobility solution, enabling seamless transitions between two-wheeled (2W) and three-wheeled (3W) configurations. This is world's 1st class changing vehicle, exemplified by Hero's SURGE. It offers a single, multi-functional platform that supports agile urban mobility, e-commerce deliveries, and income generation. This innovation is underpinned by India's pioneering and newly created L2-5 category, a unique regulatory framework established by the Ministry of Road Transport & Highways (MoRTH) under the Central Motor Vehicle Rules (CMVR
Ali Khan, Feroz, Gupta, Eshan
A Comprehensive Study: The Potential of Wireless Charging in Future E Mobility.2026-26-0195To be published on 01/16/2026
Electric mobility is no longer a distant vision, it is a global imperative in the journey of fight against the climate change and the urban pollution. Yet, despite of explosive growth in the electric vehicle adoptions, a major bottleneck remains which is efficient and convenient charging. The current reliance on physical plug in charging station creates inconvenient, time consuming experience and also faces significant technical and economic challenges those threaten to stall the smooth clean transportation revolution. Without innovation in how we recharge our vehicle the promise of electric mobility appears under threat which is undermined by less efficient, less compatible, and infrastructure hurdles. Wireless charging technology stand out as the game changing breakthrough poised to tackle these all critical problems head on. By enabling the effortless, cable-free charging system across the wide spectrum of electric vehicles, from the personal cars to the public transport fleets and
Jain, Gaurav, PREMLAL, P, Pathak, Rahul, Gore, Pandurang
GTSRB-Shield: A Novel Machine Learning Framework for Intrusion Detection in Autonomous Vehicles Leveraging the German Traffic Sign Recognition Benchmark2026-26-0611To be published on 01/16/2026
The escalating dependence of Autonomous Vehicles on Intelligent Transportation Systems (ITS) has highlighted the imperative for comprehensive security protocols to safeguard such vehicles against cyber threats. Intrusion Detection Systems (IDS’s) are pivotal in ensuring the protection of these systems by detecting and alleviating unauthorized access and nefarious activities. The German Traffic Sign Recognition Benchmark (GTSRB) database, which encompasses an extensive compilation of traffic sign imagery, functions as a vital asset for the advancement of machine learning-based IDS. This research elucidates an intrusion detection system (IDS) that employs machine learning algorithms to scrutinize the GTSRB database. The proposed IDS emphasize the preprocessing of the GTSRB dataset to extricate pertinent features that can be employed for the training of machine learning models. Research also focuses on model development with machine learning algorithms to classify traffic signs and
Patil, Kamalesh, Akbar Badusha, A., Jadhav, Savitri, Gunale, Kishanprasad
Path Planning and Control Strategies for a Semi-Autonomous Light Commercial Vehicle Navigating and Avoiding Static Obstacles in Urban Environments2026-26-0134To be published on 01/16/2026
This paper presents the design and implementation of a Semi-Autonomous Light Commercial Vehicle (LCV) capable of following a person while performing obstacle avoidance in urban and controlled environments. The LCV leverages its onboard 360-degree view camera, RTK-GNSS, Ultrasonic sensors, and algorithms to independently navigate the environment, avoiding obstacles and maintaining a safe distance from the person it is following. The proposed system employs a path planning algorithm that generates a secondary lateral path originating from the primary driving path to navigate around static obstacles. A Behavior Planner is utilized to decide when to generate the path and avoid obstacles, ensuring timely and efficient navigation adjustments. The primary objective is to ensure seamless and safe navigation in environments where obstacles are present. The LCV's path tracking is achieved using a combination of Pure Pursuit and Proportional-Integral (PI) controllers. The Pure Pursuit controller
Ayyappan, Vimal Raj, Dhanopia, Rashmi, Ali, Ashpak, N, Ragesh, Sato, Hiromitsu
Brake Judder Resolution through Experimental Testing2026-26-0587To be published on 01/16/2026
Brake judder is a critical concern in modern automotive systems, impacting both vehicle performance and passenger comfort. This phenomenon manifests as undesirable vibrations during braking, often caused by various factors such as vehicle architecture, different wheelbase, brake design considerations, load distribution, suspension characteristics etc. These vibrations not only compromise braking efficiency but also affect the overall driving experience, making it a priority issue for automotive engineers and researchers. This paper investigates the root causes of brake judder in a M3 Bus category vehicle having pneumatic brake system, focusing on its mechanical aspects and operational dynamics. By employing a combination of experimental testing and analytical evaluations, the study delves into the influence of brake torque generation and its consumption during vehicle deceleration for different wheelbase vehicles having similar brake system, revealing discrepancies that contribute to
Mundkar, Rameshwar, Shete, Rahul, Nayak, Nihar, Gavade, Sarjerao
Automotive Cybersecurity: Safeguarding Connected and Autonomous Mobility2026-26-0629To be published on 01/16/2026
As vehicles transform into complex cyber-physical systems within Intelligent Transportation Systems (ITS), automotive cybersecurity has become a foundational pillar in securing safe, reliable, and trustworthy transportation. This paper examines cybersecurity challenges in connected and autonomous vehicles (CAVs), focusing on Vehicle-to-Everything (V2X) communications technologies, including Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Pedestrian (V2P) and critical systems like electronic control units (ECUs), battery management units (BMUs), and sensor fusion modules. Key vulnerabilities, such as remote hacking, denial-of-service (DoS) attacks, malware injection, and data breaches, threaten vehicle functionality, passenger safety, and privacy. Key protection mechanisms, including encryption, intrusion detection systems (IDS), cryptographic protocols, secure over-the-air (OTA) updates, and Advanced Artificial Intelligence (AI) and Machine Learning (ML
Kumar, Om, Kumar, Rajiv, Sankar M, Gopi, Haregaonkar, Rushikesh Sambhaji
Software-Defined Vehicles: Architecting the Future of Intelligent and Connected Mobility2026-26-0691To be published on 01/16/2026
The rise of Software-Defined Vehicles (SDVs) marks a fundamental shift in automotive design, where software, rather than hardware, defines vehicle capabilities. This review explores the SDV paradigm within Intelligent Transportation Systems (ITS), emphasizing centralized computing, over-the-air (OTA) updates, and service-oriented architectures (SOA). Key enablers such as high-performance computing units, middleware platforms (e.g., AUTOSAR Adaptive), and digital twins support scalable, flexible software deployment and real-time functionality. Artificial Intelligence (AI) and Machine Learning (ML) enhance features like predictive maintenance, driver personalization, and autonomous decision-making. However, SDVs also introduce complex challenges, including software validation, real-time performance, and system interoperability. Cybersecurity becomes critical, especially as vehicles interface with cloud platforms, edge computing, and Vehicle-to-Everything (V2X) networks. The paper also
Ahmad, Aqueel, Hemanth, Khimavath, Kumar, Om, Kumar, Rajiv, Haregaonkar, Rushikesh Sambhaji
Real-time Helmet Detection and Closed-Loop Enforcement System for Two-Wheelers2026-26-0650To be published on 01/16/2026
Need: In India, two-wheelers account for a significant portion of road traffic and contribute heavily to the national burden of road fatalities. Despite regulatory mandates, helmet non-compliance remains widespread due to limited enforcement reach and behavioral inertia. Currently there is no intelligent system that enforces helmet usage autonomously in a closed loop directly at the vehicle level. Motivation: The existing enforcement strategies such as traffic policing or external camera-based surveillance are reactive, infrastructure-dependent, and ineffective at scale. To overcome these limitations, we propose a real-time helmet detection and closed-loop system that is integrated into the two-wheeler itself. This approach promotes proactive safety compliance without relying on external monitoring infrastructure. Methodology: The proposed model is AI-powered, vision-based system that leverages deep learning techniques for helmet detection, supported by a custom-built dataset
Kandimalla, Om Mahalakshmi, Shah, Ravindra, Karle, Ujjwala
Machine Learning Approach to ISO Road Class Prediction Using Multiple Linear Regression2026-26-0667To be published on 01/16/2026
The inertial profiler methodology is traditionally employed in RLDA (Road Load Data Acquisition) to measure road profiles and classify test routes into ISO road classes. However, this approach demands significant time and effort during instrumentation. Also, during data acquisition, laser height sensor data is affected especially during adverse conditions such as rainy seasons or on surfaces with improper reflectivity. Additionally, substantial resources are required for data processing to convert raw measurements into road classifications. To address these challenges, an initial attempt was made to establish a relationship between axle acceleration responses and road profiles, enabling axle acceleration measurements during RLDA to predict ISO road classes. However, this approach relied on a simple linear model that considered only axle acceleration responses, rendering the predictions susceptible to inaccuracies due to varying parameters such as vehicle speed. To overcome these
P, Praveen Kumar, P, Dayalan, Sriramulu, Yoganandam
A Scientific approach to identify the source of intermittent steering rattle noise and implementing the design solutions2026-26-0346To 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
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
Refinement of Road Induced Steering Wheel Vibration in Electric Vehicle2026-26-0337To 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
Regenerative braking control strategy for electric commercial bus under Indian road condition using artificial neural network2026-26-0645To be published on 01/16/2026
The main objective of this research is to create a more efficient regenerative braking control strategy for electric commercial buses operating under Indian road conditions. The strategy uses Artificial Neural Networks (ANNs) to optimize the regenerative braking process. Regenerative braking helps to recover energy that would otherwise be lost during braking and convert it back into usable power for the vehicle. The challenge is to design a system that works effectively on the diverse and often challenging road conditions found in India, such as varying gradients, traffic patterns, and road surface types. This study begins by collecting data (which includes vehicle speed, road gradient, traffic condition, etc.) from real-world driving conditions and aims to train an Artificial Neural Network (ANN) using a large set of driving data collected under various conditions to predict the most efficient regenerative braking settings for different driving scenarios. While the results are
Saurabh, Saurabh, Bhardwaj, Rohit, Patil, Nikhil, Gadve, Dhananjay, Amancharla, Naga Chaithanya
Revolutionizing Mass Mobility: Sustainable, Safe, and Smart Transport Ecosystems2026-26-0360To be published on 01/16/2026
Mass Mobility Systems are critical for a sustainable and progressive society. As the world confronts the serious challenges of global warming and urban traffic congestion, efficient mass mobility solutions become critical in reducing carbon footprints and enabling equitable access. Advancement in mass mobility is not limited to electric buses alone but also includes innovations across conventional ICE vehicles, autonomous vehicles, Trains and other integrated transport networks. Safety, and accessibility for users remain critical to the sustainability of future mass mobility concepts. The COVID-19 pandemic exposed vulnerabilities in public transportation, highlighting the urgent need for safer and more resilient systems. Road safety, passenger well-being, and hygienic standards must be deeply embedded into future mobility solutions. Furthermore, strong last-mile connectivity will be essential to ensure that mass mobility truly meets the needs of all citizens. An effective Mass Mobility
Vasudevan, M, Kumar S, Ashok, Sridevi, M, Kumar, Rajiv, Kumar, Om
Intelligent Transportation Systems in India: Current Trends, Infrastructure Development, and Future Prospects2026-26-0272To be published on 01/16/2026
Intelligent Transportation Systems (ITS) play a transformative role in enhancing the efficiency, safety, and sustainability of India’s transportation networks. As urbanization and vehicle ownership continue to grow, Indian cities face increasing demands on their infrastructure, resulting in challenges such as traffic congestion, pollution, and travel delays. ITS leverages advanced technologies-including real-time data analytics, communication networks, and automation-to optimize traffic management, improve public transport services, and provide timely information to commuters. In the Indian context, ITS applications such as electronic toll collection, adaptive traffic signals, smart parking solutions, and incident management systems have begun to demonstrate positive impacts on mobility and road safety. Government initiatives and policy frameworks are actively promoting the integration of ITS with ongoing infrastructure development projects, fostering innovation and encouraging
Bhat, Goutam, Bai N, Niha, Kumar, Vikas, Patil, Vishnureddy
Modelling and Simulation of Key Vehicle Dynamics Parameters for a Conceptual Race Car2026-26-0085To be published on 01/16/2026
Abstract Vehicle dynamics is a vital area of automotive engineering that focuses on analysing how a vehicle responds to driver inputs and external factors like road conditions and environmental influences. Achieving optimal performance, safety, and ride comfort requires a detailed understanding of longitudinal, lateral, and vertical dynamic behaviour. The objective of this paper is to develop and validate the model of a concept Race car and evaluate its vehicle dynamics behaviour using IPG CarMaker, a high-fidelity virtual testing environment widely used in industry. The model incorporates a range of vehicle parameters, including suspension parameters like spring and damper characteristics, mass distribution, tire properties and powertrain parameters. The evaluation is done using standard ISO test manoeuvres, including Constant Radius turn test (ISO 4138), Sine Steer test (ISO 8725) and other standard tests like Acceleration, Braking along with Ride and Comfort classification (as per
Agrewale, Mohammad Rafiq B., Vaish, Ujjwal
Road noise improvement of a passenger vehicle through end-to-end CAE-Simulation using Transfer Path Analysis (TPA) approach2026-26-0431To be published on 01/16/2026
Refined NVH performance of a vehicle is a mark of premium quality. Achieving the desired NVH performance in different vehicle operating conditions is always a Herculean task and early stage “CAE design recommendations” play crucial role in overall vehicle design development. This becomes tougher when the program is very much cost, weight and timeline sensitive. This paper explores simulation approach for addressing a major noise issue for a vehicle running at a constant speed on a rough road. The first and the most critical step is to identify the exact root cause of the issue. Hence, we propose a detailed full vehicle level “contribution analysis (CA) + transfer path analysis (TPA)” methodology (everything done through the simulation) and then go for the design recommendations to improve the performance. We used road excitation power spectral density (PSD) as the input at all the four wheels (spindle locations) calculated through MBD software. The first step i.e. contribution analysis
Mahajani, Mihir, Nascimento, Fabio, ADINARAYANA REDDY, KODIDELA, Matyal, Mahantesh, Tenagi, Irappa, Sardar, Chenna
Overview of Indian Government Policies, Evolution of Indian Automotive Regulations and Striking balance approach for adoption2026-26-0242To be published on 01/16/2026
A well-regulated vehicle design and manufacturing instils driver and passengers' safety and comfort, and lays the foundation for safe and clean mobility. Evolution of Automotive regulation has a long legacy across the globe. India has been closely following the Automotive regulatory progress in the Europe as a cornerstone for technical harmonization, cross learning, gauge benefits and economic implications. Even though India being a developing country, it has not only shown its willingness to harmonize world's best practices but also been making right preparations towards safe and clean mobility. Adoption of BS-VI directly from BS-IV is a testament to India's commitment. While doing so, Government of India (GOI) has always been striking a balanced approach between harmonization of regulations and business implications (ground reality, TCO, business sustenance and growth). Given the above context, the paper explores about: i)Trajectory of evolution of Automotive regulations in India
Patil, Dharmarayagouda
Enhanced Methodologies for predicting Automotive Wheel Bearing life and damage using RLDA2026-26-0482To be published on 01/16/2026
The durability of wheel bearings is assessed in terms of raceway life and flange life. Raceway life focuses on the performance and damage tolerance of rolling elements, while flange life evaluates the structural integrity of wheel flanges under operational stresses. Traditionally, durability predictions relied on conventional design methods and analytic formulas for raceway spalling, as well as static load assumptions for flange fatigue analysis. Recently, integrating design of experiments (DOE) with traditional approaches has enhanced these methods, enabling systematic evaluation of design variables and loading conditions. This paper introduces a methodology for analysing raceway life and damage in automotive wheel bearings using RLDA (Road Load Data Acquisition) data. The process involves acquiring raw deterministic load data, filtering it to preserve high-peaked signals, and transforming the filtered data into block cycles derived from load time histories. Each block cycle contains
Narendra, Vishwanath, Mane, Yogiraj, Paua, Ketan, Singh, Ram Krishnan, Vellandi, Vikraman
Cybersecurity threats for connected passenger EV Buses of state transport units in India.2026-26-0610To be published on 01/16/2026
There are several chances to enhance fleet management, passenger safety, and operational efficiency by integrating connected technology into electric passenger buses, especially in Indian state transport agencies. But this connectivity also brings with it a fresh set of cybersecurity threats that might jeopardize these cars' dependability and security. With an emphasis on India's state-run bus fleets, this study examines the cybersecurity risks unique to connected electric vehicles (EVs) utilized for public transportation. Vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and fleet management communication systems are examined for key vulnerabilities. Potential attack vectors are highlighted, including data interception, GPS spoofing, unauthorized access, and cyberattacks on charging stations. We also look at how these cybersecurity threats affect public safety, operational disruptions, and passenger privacy. This paper also assesses the difficulties Indian state transport
Mokhare, Devendra Ashok
Dynamic Integration of Bilateral and Adaptive Cruise Control for Intuitive Vehicle Behavior and Congestion Mitigation2026-26-0037To be published on 01/16/2026
Bilateral Cruise Control (BCC) is a new concept that has been shown to reduce traffic congestion and enhance fuel/energy efficiency compared to Adaptive Cruise Control (ACC). BCC considers both lead and trailing vehicles to determine the ego vehicle’s acceleration, effectively dampening any disturbance down the vehicle string and reducing possibilities for congestion. Despite the advantages demonstrated with BCC, one major limitation is its non-intuitive behavior, which stems from the fact that the BCC reacts not just to the lead vehicle but also to the trailing vehicle’s movement. This paper identifies key issues with BCC control and proposes solutions that retain the benefits of BCC while maintaining intuitive behavior. Specifically, a novel switching strategy is proposed to switch between ACC and BCC control modes by critically analyzing the driving conditions. The proposed system ensures acceptable driving behavior with predictable braking and acceleration, resulting in an
A, Arya, A, Aishwarya, D, Vishal Mitaran, M, Senthil Vel, Kumar, Vimal
Predictive Simulation Framework for Tyre Curb Impact Durability Assessment and Design Optimization2026-26-0396To be published on 01/16/2026
Tyre structural durability validation is a critical aspect of automotive design, considering the worsening road conditions. One of the key validation tests for assessing structural integrity is the curb impact test, which evaluates the tyre's ability to withstand sudden and concentrated impacts. Typically, this process involves physical testing of preliminary tyre samples, followed by iterative modifications to the tyre's construction to meet durability requirements. However, this approach often compromises ride performance, necessitating a more efficient and predictive methodology. To address this challenge, a frugal simulation-based prediction methodology has been developed to evaluate tyre curb impact durability before vehicle-level testing. This allows for the optimization of tyre design parameters early in the development process, ensuring structural performance while minimizing ride and handling (R&H) tuning iterations. By reducing the number of iterations, the methodology
Sundaramoorthy, Ragasruoban, LENKA., VISWESWARA
Vehicle-to-Vehicle negotiation via Manoeuvre Coordination Messages for Cooperative Cut-In scenarios2026-26-0274To be published on 01/16/2026
The automotive industry is rapidly extending the capabilities of automated systems by incorporating connectivity and cooperation features that enable real-time information exchange between vehicles and road infrastructure. Within the Connected, Cooperative, and Automated Mobility (CCAM) framework, Vehicle-to-Vehicle (V2V) communication is expected to play a key role in improving road safety, traffic efficiency, and driving comfort. This work addresses a practical implementation of the standardized Manoeuvre Coordination Messages (MCMs), as defined in the ongoing ETSI standard (ETSI TS 103 561). The proposed approach is demonstrated through a cooperative cut-in use case in which two vehicles negotiate a lane change manoeuvre. In the considered scenario, the ego vehicle, driven by a Highway Pilot (HWP) system, receives the intention to cut-in from a neighbouring cooperative vehicle through an MCM. In response, the ego vehicle adapts its behaviour by decelerating to generate a safe
Leiva Ricart, Gisela, Domingo Mateu, Bernat
AI-powered intelligent cognitive lens for driver monitoring for safe transportation and increased fleet efficiency2026-26-0634To be published on 01/16/2026
The rapid evolution of intelligent transportation systems has made drivers’ attentiveness and adherence to safety protocols more critical than ever. Traditional monitoring solutions often lack the adaptability to detect subtle behavioral changes in real time. This paper presents an advanced AI-powered Driver Monitoring System designed to continuously assess driver behavior, fatigue, distractions, and emotional state across various driving conditions. By providing real-time alerts and insights to vehicle owners, fleet operators, and safety personnel, the system significantly enhances road safety. The system integrates lightweight AI/ML algorithms, image processing techniques, perception models, and rule-based engines to deliver a comprehensive monitoring solution for multiple transportation modes, including automotive, rail, aerospace, and off-highway vehicles. Optimized for edge devices, the models ensure real-time processing with minimal computational overhead. Alerts are communicated
Mardhekar, Amogh, Sing, Sandip, Chikhale, Shraddha, Hivarkar, Umesh
non-SAE standard test - revision Standard for Safety Glazing Materials for Glazing Motor Vehicles and Motor Vehicle Equipment Operating on Land Highways - Safety Standardas-jms-1A (Current)09/23/2025
non-SAE standard test - revision Specifications, test methods, and usage provisions for safety glazing materials used for glazing of motor vehicles and motor vehicle equipment operating on land highways.
Automated Vehicle Safety Consortium
SAE TOMORROW TODAY - Digital Engineering for Defense and Beyond1352007/01/2025
If you were to build the perfect use case for the potential of digital engineering, you would be hard-pressed to choose a better sector than the defense industry. That's why the Pentagon isn't just intrigued by digital engineering-it's made it mandatory. As the U.S. military targets groundbreaking technology improvements that safeguard lives and improve defense capabilities, Ansys is helping connect the dots between people, processes, and technology with the predictive power of simulation. Establishing a digital engineering ecosystem, including digital twins, contributes to the resilience and adaptability of innovations across industries. To learn more, we sat down with Dr. Armond E. Sinclair, Sr. Technical Account Executive for Ansys Government Initiatives, to discuss how digital engineering is enabling smarter decision-making, reducing costs, and accelerating innovation at the Department of Defense (DoD) and beyond. We'd love to hear from you. Share your comments, questions and ideas
Hineman, Marcie
SAE TOMORROW TODAY - Removing Roadblocks to Fleet Electrification1351806/07/2025
What does it really take to electrify America's fleets? From skyrocketing insurance rates to policy risks to reduced incentives, the market dynamics are complex. Enter Electrada, a Cincinnati-based EV infrastructure company revolutionizing how fleets transition to clean energy. As the developer, owner, and operator of electric fueling assets, Electrada offers a unique 360 Charging-as-a-Service (CaaS) model that delivers zero capital investment, 99%+ uptime, predictable pricing, and expert management. Serving all fleet types across multiple transportation sectors, Electrada designs fully tailored, long-term EV charging solutions that reduce cost per mile from day one with no operational disruptions or price risk. Listen in as we sit down with Kevin Kushman, CEO of Electrada, to discuss the challenges and opportunities in the North American fleet electrification market. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org
Hineman, Marcie
SAE TOMORROW TODAY - Riding the EV Wave With Smarter Batteries1351705/29/2025
As OEMs race to deliver new vehicle lineups with greater speed and efficiency, the industry finds itself navigating a complex crossroads between full EVs and hybrid models. That's where ENNOVI steps in. With a focus on smarter battery management and cutting-edge electrical architecture, ENNOVI is staying agile--offering the right product mix to help OEMs and suppliers ride the wave of electrification, battery technology improvements, and market shifts without missing a beat. Listen in as we sit down with Ron Puhl, Global Director of Engineering and Product Portfolio, to discuss how ENNOVI's Current Collector System (CCS) is helping to improve the overall package size of batteries while reducing costs. It's a unique discussion with deep insight into consumer EV demand and industry trends. We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we
Hineman, Marcie
testing revisions on best practiceCUR1513-jms105/23/2025
revisions
AESQ Steering Group
SAE TOMORROW TODAY - Engineering with Purpose: The SAE Story You Need to Hear1351605/22/2025
Innovation isn't a solo act--it's a team sport. And if you're an engineer, the world needs your expertise now more than ever. SAE International is a place where engineers, dreamers, and doers unite to build a safer, smarter future. Our lively community is made up of cross-disciplinary volunteers who develop life-saving standards, mentor the next generation, and work collaboratively to build a strong and ethical foundation for powerful emerging technologies. Listen in as Dr. Jacqueline El-Sayed, CEO of SAE International, shares how SAE is setting the standard (literally) for tomorrow's mobility solutions while fostering professional growth and collaboration along the way. Ready to make an impact and level up your career? Whether you're passionate about safety standards, emerging tech, or mentoring the next generation, volunteering with SAE connects you with a global network of innovators just like you. You'll gain leadership experience, grow your expertise, and help drive real change in
Hineman, Marcie
SAE TOMORROW TODAY - Scalable AV Deployment Starts with Fewer Close Calls1351305/01/2025
The hallmark of exceptional autonomous driving technology isn't just how it reacts in a crisis but how it avoids one altogether. That's the vision behind May Mobility: a world where self-driving cars confidently navigate busy intersections, unexpected detours, and pedestrian-filled crosswalks with the instincts of a seasoned human driver. At the core of May Mobility's technology platform is its patented Multi-Policy Decision Making (MPDM) system. This breakthrough technology uses real-time, in-situ AI to interpret data, continuously learning and adapting to new, complex, and unpredictable driving conditions. By learning on the fly--much like a human driver--May Mobility's AVs can be deployed faster and more cost-effectively than traditional systems. To explore how May Mobility is scaling its AV technology, we spoke with Ed Olson, CEO and Founder, about the company's city-wide AV deployments, strategic partnerships with Toyota and NTT, and its entrance into the rideshare market through
Hineman, Marcie
A Power Split eCVT Hybrid for Sustainable Urban Mobility2024-32-002904/18/2025
The main drivers for powertrain electrification of two-wheelers, motorcycles and ATVs are increasingly stringent emission and noise limitations as well as the upcoming demand for carbon neutrality. Two-wheeler applications face significantly different constraints, such as packaging and mass targets, limited charging infrastructure in urban areas and demanding cost targets. Battery electric two wheelers are the optimal choice for transient city driving with limited range requirements. Hybridization provides considerable advantages and extended operation limits. Beside efficiency improvement, silent and zero emission modes with solutions allowing fully electric driving, combined boosting enhances performance and transient response. In general, there are two different two-wheeler base categories for hybrid powertrains: motorcycles featuring frame-integrated internal combustion engine (ICE) and transmission units, coupled with secondary drives via chain or belt; and scooters equipped with
Schoeffmann, W., Fuckar, G., Hubmann, C., Gruber, M.
Analysis of Lane Departure Caused by Inadequate Motorcycle Driving Maneuvers Due to Road Alignment2024-32-003404/18/2025
There are many riders who drive motorcycles on winding mountain roads and caused single motorcycle traffic accidents on curved roads by lane departure. Driving a motorcycle requires subtle balancing and maneuvering. In this study, in order to clarify the influence of lane departure caused by inadequate driving maneuvers against road alignment, the authors analyzed the required curve initial operation and driving maneuvers in curves depending on the traveling speed using a kinematics simulation for motorcycle dynamics. In addition, it was analyzed how inadequate driving maneuvers for curved roads can easily cause lane departure. As a result, it shows that the steering maneuvers and the lean of motorcycle body during the curves are highly affected by the vehicle speed, and the required maneuvers increases rapidly with increasing speed. The inadequate maneuver in the curves, especially for the lean of motorcycle body and steering torque, even by 10%, may cause failure to follow the
Kuniyuki, Hiroshi, Takechi, So
Fatigue Analysis of Motorcycle Rear Swing Arm on Different Road Surfaces2024-32-004604/18/2025
The rear swing arm, a crucial motorcycle component, connects the frame and wheel, absorbing the vehicle’s load and various road impacts. Over time, these forces can damage the swing arm, highlighting the need for robust design to ensure safety. Identifying potential vulnerabilities through simulation reduces the risk of failure during the design phase. This study performs a detailed fatigue analysis of the swing arm across different road conditions. Data for this research were collected from real-vehicle experiments and simulation analyses, ensuring accuracy by comparing against actual performance. Following CNS 15819-5 standards, road surfaces such as poorly maintained, bumpy, and uneven roads were tested. Using Motion View, a comprehensive multi-body dynamic model was created for thorough fatigue analysis. The results identified the most stress-prone areas on the swing arm, with maximum stress recorded at 109.6N on poorly maintained roads, 218.3N on bumpy surfaces, and 104.8N on
Chiou, Yi-Hau, Hwang, Hsiu-Ying, Huang, Liang-Yu
SAE TOMORROW TODAY UNPLUGGED - The Fragmentation of the Robotaxi Market1351004/10/2025
The robotaxi market is experiencing significant change, with the once-dominant Waymo now facing competition from new entrants like Nuro and Wayve who are licensing their autonomous driving technology -- a strategy that could reshape the industry. In addition, Tesla's Cybercab is aiming to launch a commercial service by the end of 2025 that allows owners to generate revenue through the Tesla network. Lyft and Uber are also adapting through the power of partnership, emphasizing the importance of fleet management in the operation and maintenance of robotaxis. In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte breaks it all down and discusses how the impact of a fragmented market will likely result in a convergence of personally owned AVs, traditional robotaxis, and niche players. Have your own thoughts on this topic? We'd love to hear from you! Share your comments, questions or ideas for future topics with Grayson on Twitter or send them to podcast@sae.org. Follow SAE on
Hineman, Marcie
bp w revbestPractice204/08/2025
sfg
SAE TOMORROW TODAY BRIEFS - NEVI and America's EV Charging Future1350904/03/2025
The National Electric Vehicle Infrastructure Program (NEVI) is a $5 billion initiative aimed at developing EV charging infrastructure across all 50 states and Puerto Rico. However, recent executive orders have put the program and its funding on hold. To dig into what this all means, Roberto Baldwin, Sustainability Editor, SAE Sustainable Mobility Solutions, recently sat down with Andrew Wishnia, Senior Vice President at Boundary Stone Partners, to discuss what NEVI is all about and what the future holds for this EV charging infrastructure initiative. For more information on the evolution of sustainability, head on over to sustainablecareers.sae.org. There, you can check out our drive of the new 2025 Ioniq 5, the first non-Telsa EV to hit the road with SAE J3400 (a.k.a., NACS). We'd love to hear from you. Share your comments, questions and ideas for future topics and guests to podcast@sae.org. Don't forget to take a moment to follow SAE Tomorrow Today--a podcast where we discuss
Hineman, Marcie
JMS BP initial productjms_bp_1-dup104/01/2025
JMS BP initial product
AESQ Steering Group
JMS BP initial productjms_bp_104/01/2025
JMS BP initial product
AESQ Steering Group
TitlebestPractice103/31/2025
Scope
Optimizing Electric Vehicle Charging Station Locations Based on Urban Road Network Congestion Tracing2025-01-721603/19/2025
Exhaust emissions from congested road segments constitute a significant source of urban air pollution. Resolving traffic congestion throughout the road network presents considerable challenges. However, alleviating tailpipe emissions on congested roads can be achieved by increasing the proportion of electric vehicles (EVs) in the traffic flow. Therefore, we propose a method for optimizing the layout of EV charging stations based on urban road networks congestion tracing. This method traces congestion sources through similarity between road networks, and evaluates the installation potential value of adjacent candidate installation points using the congestion contribution degree of the road segment as an indicator. The analysis is conducted on 100 routes within the Qinhuai district of Nanjing city, using spatiotemporal similarity metrics. The utilization of point-of-interest and traffic data from online mapping sources overcomes the complexity of road network structure and the sparsity
Zeng, Wenyi, Jian, Lu, Hu, Xiaojian
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