Browse Topic: Advanced driver assistance systems (ADAS)

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STEERING AUTOMATION FOR LANE KEEP ASSISTANCE2026-28-0117To be published on 02/12/2026
The design of advanced driver-assistance systems (ADAS) is essential to improve the safety and autonomy of vehicles in harsh conditions. This work introduces the design and development of a steering automation system for Lane Keep Assistance (LKA) in a vehicle with a parallel steering system. The system utilizes an ArduCam module to take real-time images of the ground in front, and these are processed via machine learning techniques on a Raspberry Pi in order to identify lane edges with great precision. The corrective steering maneuvers are carried out by a motorized steering actuator based on the visual data after processing, and an encoder that is built into the actuator constantly tracks the steering angle and position. This closed-loop feedback affords accurate, real-time corrections to ensure lane discipline without driver intervention. Extensive calculations for steering effort, torque, and gear design confirm the system's mechanical viability. Combining low-cost vision sensing
A R, Arundas, Sadique, Anwar, Rafeek, Aayisha
Development of Advanced Rider Assistance System (ARAS) for Electric Motorcycles: A Level-1 Collision Avoidance and Emergency Braking Prototype Using Ultrasonic Sensors2026-28-0118To be published on 02/12/2026
This paper presents the design, development, and validation of an Advanced Rider Assistance System (ARAS) for electric motorcycles, focused on a Level-1 collision avoidance and emergency braking prototype using ultrasonic sensors. The motivation stems from the disproportionate risk faced by two-wheeler riders and the current lack of widespread ARAS deployment compared to Advanced Driver Assistance Systems (ADAS) in cars. The proposed system addresses this gap by integrating front and rear ultrasonic sensors (operating at 40 kHz, with a detection range of 2 cm to 4 m and ±1% accuracy) to continuously monitor the proximity of obstacles in real time, even when the motorcycle is inclined up to 30°. Sensor data is processed by an embedded microcontroller (STM32 series), which executes a collision risk assessment algorithm based on measured distance and relative speed. When the distance to an obstacle falls below a configurable safety threshold (typically 3 m), the system initiates a multi
Deepan Kumar, Sadhasivam, Karu, Ragupathy, Karthick, K N, R, Vishnu Ramesh Kumar, Kumar, V, Manojkumar, R, M, Karthick, M, Rishab
Intelligent Steering System to Improve Fuel Efficiency in Heavy Duty Vehicles2026-28-0103To be published on 02/12/2026
In commercial vehicles, conventional engine-driven hydraulic steering systems result in continuous energy consumption, contributing to parasitic losses and reduced overall powertrain efficiency. This study introduces an Electric Powered Hydraulic Steering (EPHS) system that decouples steering actuation from the engine and operates only on demand, thereby optimizing energy usage. Field trials conducted under loaded conditions demonstrated a 3–6% improvement in fuel economy, confirming the system’s effectiveness in real-world applications. A MATLAB-based simulation model was developed to replicate dynamic steering loads and vehicle operating conditions, with results closely aligning with field data, thereby validating the model’s predictive accuracy. The reduction in fuel consumption directly translates to lower CO₂ emissions, supporting regulatory compliance and sustainability goals, particularly in the context of tightening emission norms for commercial fleets. These findings position
T, Aravind Muthu Suthan, Mani, Kishore, Ayyappan, Rakshna, D, Senthil Kumar, S, Mathankumar
Predicting Cut-in Events Using LSTM Based Techniques2026-26-063601/16/2026
Road accidents involving cut-in and sudden brake events on highways present major challenges to driver safety, often outpacing the response time of traditional Advanced Driver Assistance Systems (ADAS). The objective of this study is to predict potential collisions caused by cut-ins before ADAS intervention becomes necessary, allowing for earlier driver alerts and enhanced vehicle response. The proposed method employs machine learning and deep learning approaches, specifically Long Short-Term Memory (LSTM) networks, to forecast collision risks 0.5 to 3 seconds in advance. Synthetic data generation techniques are used to create rare but critical cut-in and braking scenarios, complementing real-world data from test vehicles and accident records. Key predictive features monitored include relative velocity, lateral velocity, and lane overlap, which provide dynamic indicators of imminent risk. Results show that the system achieves an average early warning time of 1.35 seconds in 40.206% of
Srivastava, Rohan, Nayak, Apoorva S., Suvvari, Sai Dileep, Satwik, Rahul, Bhattacharya, Abhinov
Crowdsourcing Indian Traffic Scenarios for ADAS Development and Testing2026-26-004601/16/2026
In the Indian context, introduction of ADAS can play a positive role in improving road safety by assisting the driver and preventing unsafe driver behaviour. Technologies like Automated Emergency Braking (AEB), Lane Keep System, Adaptive Cruise Control, Driver Drowsiness Detection, Driver Alcohol detection etc., if deployed safely and used in a safe manner can help prevent many of the current road deaths in India. Safe deployment and safe use of such ADAS technologies require the systems to operate without failure within their operational design domains (ODD) and not surprise the drivers with sudden or unpredictable failures, to help develop their trust in the technology. As a result, identifying test scenarios remain a key step in the development of Advanced Driver Assistance Systems (ADAS). This remains a challenge due to the large test space especially for the Indian context due to the unpredictable traffic behaviour and occasional road infrastructure. In this paper, we introduce a
Serry, Hamid, Dodoiu, Tudor, Alakkad, Fadi, Zhang, Xizhe, Khastgir, Siddartha, Jennings, Paul
Optimizing Collision Warnings: A Shift from Time to Collide to Time to Brake2026-26-004701/16/2026
In automotive safety systems, Time to Collide (TTC) is traditionally used to trigger warnings in auto-emergency braking systems. However, TTC can lead to premature or inaccurate warnings as it is calculated based on the relative speed and distance between the ego and an obstacle. TTC does not consider the vehicle’s braking dynamics, such as brake prefill lag which varies across different vehicles, maximum deceleration, and the effectiveness of braking systems and assumes constant speed which may not always be realistic. We propose Time to Brake (TTB) as a more effective parameter for driver warnings. TTB directly relates to the action a driver needs to take—braking. It provides a clear indication of when braking should begin to avoid a collision, whereas TTC only tells us about the possibility of a collision. To calculate TTB we utilize the brake profile, which incorporates both deceleration and system jerk for improved accuracy. The proposed warning time is the sum of variable brake
Singh, Ashutosh Prakash, Kumawat, Himanshu, Gupta, Sara
Ocular-Behavioral Metrics for Driver State Classification for Indian Driving Contexts: KSS-Based Evaluation, Conformance and Implementation Challenges2026-26-066801/16/2026
With the growing adoption of Advanced Driver Assistance Systems (ADAS) in the Indian automotive landscape, the need for effective Driver Monitoring Systems (DMS) has become increasingly critical. This paper presents the design, development, and validation of a Driver Distraction and Attention Warning System (DDAWS) tailored to Indian driving conditions. The proposed system integrates two key modules: Driver Attention Monitoring and Drowsiness Detection, using a high-resolution driver-facing camera to analyse head pose, facial landmarks, and behavioural cues. The drowsiness module incorporates metrics such as PERCLOS and Eye Aspect Ratio (EAR), evaluated against the Karolinska Sleepiness Scale (KSS). Recognizing the limitations of self-assessed scales like KSS in dynamic driving environments, the study compares algorithmgenerated KSS values with self-reported scores to assess model accuracy. Additionally, the framework aligns with automotive safety standards such as AIS184,EU 2021/1341
Verma, Harshal, Kale, Jyoti Ganesh, Karle, Ujjwala
Digital Rack Load Estimation Methodology to Optimize Motor Sizing for Electric Power Steering2026-26-038301/16/2026
Rack load estimation during the pre-design stages is critical for the calibration of steering systems, particularly in achieving the desired steering feel and optimizing assistance strategies in Electric Power Assisted Steering (EPAS). Conventional approaches often depend on physical vehicle testing or simplified empirical equations, which may be time-consuming or lacks the fidelity required for early-stage analysis. This paper presents a 1D simulation strategy to address limitations from conventional approaches. The proposed rack force estimation model is based on multi-physics analytical equations that calculate tire-road friction forces and the resulting moments about the steering axis, delivering a physics-based yet computationally efficient solution. The rack force estimation model is further extended into EPAS system model by incorporating Direct Current (DC) brushed motor model. The rack force estimation model is validated against physical test data which demonstrates a high
Adsul, Sourabh, Iqbal, Shoaib
Dynamic Integration of Bilateral and Adaptive Cruise Control for Intuitive Vehicle Behavior and Congestion Mitigations2026-26-003701/16/2026
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 damping 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 intuitive
A, Arya, A, Aishwarya, D, Vishal Mitaran, M, Senthil Vel, Kumar, Vimal
Unlocking the Potential of In-Vehicle Edge AI2026-26-068601/16/2026
Edge Artificial Intelligence (AI) is poised to usher in a new era of innovations in automotive and mobility. In concert with the transition towards software-defined vehicle (SDV) architectures, the application of in-vehicle edge AI has the potential to extend well beyond ADAS and AV. Applications such as adaptive energy management, real-time powertrain calibration, predictive diagnostics, and tailored user experiences. By moving AI model execution right into edge, i.e. the vehicle, automakers can significantly reduce data transmission and processing costs, ensure privacy of user data, and ensure timely decision-making, even when connectivity is limited. However, achieving such use of edge AI will require essential cloud and in-vehicle infrastructure, such as automotive-specific MLOps toolchains, along with the proper SDV infrastructure. Elements such as flexible compute environments, deterministic and high-speed networks, seamless access to vehicle-wide data and control functions. This
Khatri, Sanjay, Sah, Mohamadali
Algorithm Development for AI Driven Path Planning Using Augmented Reality for Navigating in Indian Complex Road Scenarios2026-26-003801/16/2026
The road infrastructure in India has complex navigational challenges with most of the road unstructured especially in rural areas. Decision-making becomes a challenge for drivers in unpredictable environments such as narrow roads, flooded roads and heavy traffic. In this paper, an Augmented Reality based ML-Algorithm for Driver Assistance (ARMADA) has been proposed that improves awareness to safely maneuver in these conditions. The methodology for development and validation of this Augmented Reality (AR) based algorithm contains multiple steps. Firstly, extensive data collection is conducted using real time recording and benchmark datasets like Berkeley Deep Drive (BDD) and Indian Driving Dataset (IDD). Secondly, collected data are annotated and trained using an optimal machine learning (ML) model to accurately identify the complex scenario. In third step, an ARMADA algorithm is developed, integrating these models to estimate road widths, detect floods and provide seamless driver
Anandaraj, Prem Raj, Sivakumar, Vishnu, Thanikachalam, Ganesh, L, Radhakrishnan, Motoki, Yaginuma, Selvam, Dinesh Kumar
A Centralized Framework for Sustaining Safety-Critical Vehicle Systems Through Periodic Servicing2026-26-000301/16/2026
As vehicles are becoming more complex, maintaining the effectiveness of safety critical systems like adaptive cruise control, lane keep assist, electronic breaking and airbag deployment extends far beyond the initial design and manufacturing. In the automotive industry these safety systems must perform reliably over the years under varying environmental conditions. This paper examines the critical role of periodic maintenance in sustaining the long-term safety and functional integrity of these systems throughout the lifecycle. As per the latest data from the Ministry of Road Transport and Highways (MoRTH), in 2022, India reported a total of 4.61 lakh road accidents, resulting in 1.68 lakh fatalities and 4.43 lakh injuries. The number of fatalities could have been reduced by the intervention of periodic services and monitoring the health of safety critical systems. While periodic maintenance has contributed to long term safety of the vehicles, there are a lot of vehicles on the road
HN, Sufiyan Ahmed, Khan, Furqan, Srinivas, Dheeraj
Market Research on Actual User Experience and Efficacy of ADAS Features in Indian Driving Conditions2026-26-003501/16/2026
Advanced Driver Assistance Systems (ADAS) have become increasingly prevalent in modern vehicles, promising improved safety and reducing accidents. However, their implementation comes with several challenges and limitations. The efficacy of these systems in diverse and challenging road conditions of India, remains as a concern. For deeper understanding of the ADAS feature related concerns in Indian market due to the factors such as unique road conditions, traffic situations, driving patterns, an extensive study was done throughout Indian terrain. The functionality and performance of different ADAS features were evaluated in the real-world scenarios. The objective data of the observations and occurrence conditions were captured with help of data loggers & camera setups inside the vehicle. This research paper represents a comprehensive study on the challenges faced by user while using ADAS enabled cars in Indian road conditions. We captured the performance data of various ADAS features
Kumbhar, Prasad Uttam, Pyasi, Praveen
Real-Time Intrusion Detection System (IDS) for Vehicle Networks Using Machine Learning for Predictive Threat Analysis2026-26-061701/16/2026
The rapid adoption of connected vehicle technologies and advanced driver assistance systems (ADAS) necessitates robust security mechanisms capable of identifying and mitigating sophisticated cyber threats in real-time. Traditional signature-based intrusion detection systems (IDS) are often inadequate in addressing the dynamic and evolving nature of automotive cybersecurity threats, particularly in modern vehicle networks like Controller Area Network (CAN), CAN with Flexible Data-Rate (CAN-FD), and Automotive Ethernet. This research introduces a novel Real-time Intrusion Detection System utilizing advanced Machine Learning (ML) techniques designed specifically for automotive network environments. The proposed IDS framework employs supervised and unsupervised ML algorithms, including anomaly detection, behavioral analytics, and predictive threat modeling, to achieve high accuracy and rapid threat identification capabilities. Through extensive testing in simulated and actual vehicle
Chaudhary lng, Vikash, Desai, Manoj, Chatterjee, Avik
Vision-Based Framework for Automated Testing of Automotive HMI Systems Using Deep Learning Techniques2026-26-057101/16/2026
Nowadays, digital instrument clusters and modern infotainment systems are crucial parts of cars that improve the user experience and offer vital information. It is essential to guarantee the quality and dependability of these systems, particularly in light of safety regulations such as ISO 26262. Nevertheless, current testing approaches frequently depend on manual labor, which is laborious, prone to mistakes, and challenging to scale, particularly in agile development settings. This study presents a two-phase framework that uses machine learning (ML), computer vision (CV), and image processing techniques to automate the testing of infotainment and digital cluster systems. The NVIDIA Jetson Orin Nano Developer Kit and high-resolution cameras are used in Phase 1's open loop testing setup to record visual data from infotainment and instrument cluster displays. Without requiring input from the system being tested, this phase concentrates on both static and dynamic user interface analysis
Lad, Rakesh Pramod, Mehrotra, Soumya, Mishra, Arvind
Methodical Approach to Preparedness of India Specific Automotive Database Matrix with Example of AEB Scenarios2026-26-065101/16/2026
The purpose of this report is to identify systematic approach of formation of India specific automotive database matrix. At first the paper reviews the practices used to prepare automotive dataset catalogue with established pattern to showcase automotive dataset from which appropriate data clusters can be picked up judiciously in order to train ADAS algorithms. The work applies this framework which helps to establish strategy to build a grid in which Indian automotive dataset can be contoured and selection of serviceable data bunches can be picked. This would make sure prompt selection of database aiming model training with valid input. This serves the purpose of implementation and evaluation of varied ADAS levels in India which insist upon good quality of distinguished dataset pertaining to Indian scenarios. The paper describes the approach with the example of AEB scenarios and present appropriate matrix readiness comprising of relevant data objects excluding unnecessary junk data
Behere, Sayali Rajendra, Karle, Manish, Karle, Ujjwala
Mileage Accumulation Target Identification for Autonomous Emergency Braking System Validation for Medium & Heavy Trucks Considering Real-World Accidents in India2026-26-003601/16/2026
Robust validation of Advanced Driver Assistance Systems (ADAS) considering real-world conditions is a vital for ensuring safety. Mileage accumulation is a one of the validation method for ensuring ADAS system robustness. By subjecting systems to diverse real-world driving environments and edge-case scenarios, engineers can evaluate performance, reliability, and safety under realistic conditions. In accordance with ISO 21448 (SOTIF), known hazardous scenarios are explicitly tested during robustness validation in combination of virtual and physical testing at component, sub system and vehicle level, while unknown hazards may emerge through extended mileage by running vehicles on roads, allowing them to be identified and classified. However, defining a mileage target that ensures comprehensive safety remains a significant engineering challenge. This paper proposes a data-driven approach to define mileage accumulation targets for validating Autonomous Emergency Braking Systems (AEBS
Koralla, Sivaprasad, Ravjani, Amin, Tatikonda, Vijay, Gadekar, Ganesh
Innovative Inverted Cross Car Beam Design for Optimized Packaging of Advanced Driver Assistance Technologies in Global Vehicles2026-26-005101/16/2026
The integration of Advanced Driver Assistance Systems (ADAS) into modern vehicles necessitates innovative solutions for interior packaging that balance out safety, performance, and ergonomic considerations. This paper introduces an inverted U-shaped steel tube cross car beam (CCB) as a superior alternative to traditional straight tube designs, tailored for premium vehicle instrument panels. The U-shaped geometry overcomes the limitations of straight tube beams by creating additional packaging space for components such as AR-HUDs, steering columns, HVAC systems, and electronic control units (ECUs). This geometry supports efficient crunch packaging while accommodating ergonomic requirements like H-point, eyeball trajectory, and cockpit depth for optimal ADAS component placement. The vertical alignment of the steering column within the U-shaped design further enhances space utilization and structural integrity. This study demonstrates that the inverted U-shaped CCB is a transformative
Mahajan, Ajay Senu, Regatte, Ganesh, Nagarjuna, Kamisetti, Sahoo, Sandeep, Udugu, Kumaraswamy, JC, Sudheera
Estimating the Road Friction Coefficient Dynamically Using Machine Learning2026-26-063001/16/2026
In autonomous vehicles, it is vital for the vehicle to drive in a manner that ensures the driver is comfortable and has confidence in the system, which ensures he does not feel compelled to intervene or take control of the vehicle. The system must consider environmental factors and other aspects to provide the driver with a comfortable and stress-free drive. In this regard, the road friction coefficient, which quantifies the grip experienced by the tire on a road, is a critical parameter to be considered by several comfort and safety functions. An inaccurate estimation of road friction coefficient can lead to discomfort in worst case safety risks for the driver, as the system would be over or underestimating the tire’s grip on the road and this alters the vehicle’s response to control inputs. In the context of Advanced Driver Assistance Systems (ADAS), dynamically estimating the road friction coefficient can significantly improve the safety and comfort of driving functions. However
Rangarajan, Rishi, Sukumar Rajammal, Prem Kumar, Singh, Akshay Pratap, Kumaravel, Sujeeth Selvam, Kop, Anand, Bharadwaj, Pavan
Introducing a Novel System Engineering Framework for the Safe Deployment of Software Defined-Vehicles2026-26-069001/16/2026
The past decade has seen a systemic shift in the automotive landscape and the constituent parts of a vehicle. The automotive industry has shifted from a primarily hardware components industry to a software heavy industry, with software controlling majority of the vehicle functions. Coupled with the ability to fully update or evolve a vehicle’s capabilities or functionalities, post point of sale through software updates, the technical, commercial and service landscape of the automotive industry is rapidly changing. This has brought increasing focus to the concept of Software Defined Vehicle, where the vehicle is not only constantly evolving, but is also becoming more personalised by leveraging data collected through the life of the vehicle. This requires a rethink of the current development and deployment approaches for vehicles, which are software-intensive. In this paper, we introduce a novel four-step system engineering framework for the safe development and deployment of Software
El Badaoui, Halima, Jame-Elizebeth, Mariat, Khastgir, Siddartha, Jennings, Paul
Integrated Evaluation of Pre-Crash Braking and Crash Injury Outcomes Using Human Body Models and ATDs2026-26-001901/16/2026
Traditionally, occupant safety research has centered on passive safety systems such as seatbelts, airbags, and energy-absorbing vehicle structures, all designed under the assumption of a nominal occupant posture at the moment of impact. However, with increasing deployment of active safety technologies such as Forward Collision Warning (FCW) and Autonomous Emergency Braking (AEB), vehicle occupants are exposed to pre-crash decelerations that alter their seated position before the crash. Although AEB mitigates the crash severity, the induced occupant movement leads to out-of-position behavior (OOP), compromising the available survival space phase and effectiveness of passive restraint systems during the crash. Despite these evolving real-world conditions, global regulatory bodies and NCAP programs continue to evaluate pre-crash and crash phases independently, with limited integration. Moreover, traditional Anthropomorphic Test Devices (ATDs) such as Hybrid III dummies, although highly
Pendurthi, Chaitanya Sagar, THANIGAIVEL RAJA, T, Kondala, Hareesh, Sudarshan, B.Sudarshan, Nehe, Vaibhav, Rao, Guruprakash
Application of Multi-Tiered Approach in Validating UI Based Animation in Automotive Product2026-26-058601/16/2026
As part of their market segmentation strategy, each OEM is using UX (user experience) as a crucial aspect for product differentiation. Though there are many parts to UX, the one which would have a profound effect on the user is through animation of real-world aspects on the instrument panel, like falling snowflakes when it’s snowing outside, real time traffic conditions as part of Advanced Driver Assistance Systems (ADAS) or even a unique welcome or farewell message. The unique and realistic nature of such implementations and customizing it to the needs of market segments introduces a lot of complexity in evaluating the correctness of implementation with respect to design. This paper extensively evaluates the current practices in analyzing the test basis, test environment needs, test data, and test methods used in testing animation. The primary focus of this paper is to introduce a novel multi-tiered approach to evaluating animations - presenting a framework for selecting test methods
Kandrattha A, Mohammed Azharuddin, Kulkarni, Apoorva
Advancing Safe and Sustainable Mobility: A Review of Emerging Trends and Challenges in ADAS2026-26-004201/16/2026
India’s severe road safety challenges, marked by high accident rates and fatalities, necessitate innovative solutions like Advanced Driver Assistance Systems (ADAS) to align with SIAT 2026’s theme, “Innovative Pathways for Safe and Sustainable Mobility.” This paper synthesizes recent studies to explore ADAS’s role in enhancing safety and sustainability in India’s unique traffic environment. Technologies such as automatic emergency braking, lane departure warnings, and driver monitoring systems show promise in reducing crashes caused by human error, a leading factor in road incidents. However, India’s complex road conditions—unmarked lanes, dense urban traffic, and prevalent two-wheelers—pose significant challenges to ADAS effectiveness. There developed is a strong public support recently for ADAS, with many Indian road users recognizing its safety benefits and advocating for its integration into vehicles especially passenger vehicles. Despite growing adoption by automakers like Tata
Neelakanthu, Karra, Sreenivasulu, T, Kumar, Om, Haregaonkar, Rushikesh Sambhaji, Kumar, Rajiv
Single Radar: A Robust and Cost-Effective Solution for ADAS and Parking Functionality2026-26-004901/16/2026
With rapid advancements in Autonomous Driving (AD) & Advanced Driver Assistance Systems (ADAS), numerous sensors are integrated in vehicles to achieve higher and reliable level of autonomy. Due to the growing number of sensors and its fusion creates complex architecture which causes challenges in calibration, cost, and system reliability. Considering the need for further ADAS advancements and addressing the challenges, this paper evaluates a novel solution called One Radar - a single radar system with a wide field of view enabled by advanced antenna design. Placing the single radar at the rear of the vehicle eliminates the need for corner radars and ultrasonic sensors used for parking assistance. With rigorous real-world testing in different urban and low-speed scenarios, the single radar solution showed comparable accuracy in object detection with warning and parking assistance to the conventional combination of corner radars and ultrasonic sensors. The simple single sensor-based
Anandan, Ram, Sharma, Akash
Leveraging Road Accident Database to Enhance ADAS Features and Testing Protocols in Context of Indian Driving Conditions2026-26-001401/16/2026
ADAS i.e. Advanced Driver Assistance Systems are pivotal towards amplifying road safety by reducing human error and assisting drivers in critical situations. Most major ADAS technologies are developed and validated using data and test scenarios that are predominantly based on the driving conditions and road environments of developed countries. However, in a country like India, where driving behavior, traffic dynamics, road infrastructure, and accident characteristics differ significantly, the ADAS technologies and test scenarios validated by different forums create a critical gap in deploying such systems on vehicles to work on Indian roads. The major aim of this study was to determine and generate India-specific ADAS test scenarios from the Road Accident Sampling System India (RASSI) database, available MoRTH reports, and data from previously executed ADAS test cases. Through this research, we propose a methodology to identify, extract, and analyze accident scenarios pertaining to the
Adhikari, Mayur, Bhagat, Ajinkya, Verma, Harshal, Kale, Jyoti Ganesh, Karle, Ujjwala, Sharma, Chinmaya
Adapting ADAS to Indian Driving and User Needs2026-26-004501/16/2026
The penetration of ADAS in automotive markets is increasing rapidly. However, their effectiveness and acceptance are significantly influenced by regional driving behaviours and infrastructure. This study explores the interaction between naturalistic driver behaviour in India and the operational characteristics of ADAS 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. The study characterizes multiple driver’s driving pattern through naturalistic driving and ADAS systems behaviour in corresponding situations, notably how they adapt to unstructured Indian scenarios such as lane ambiguity, pedestrian unpredictability, traffic flow unpredictability and
Sankpal, Krishnath Namdev, Magar, Akshay, Khot, Ankush, Kulkarni, Alok, Perez, Marc
Virtual Validation of ADAS Algorithms Using Driver-in-the-Loop Simulation2026-26-005001/16/2026
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. By examining the current landscape of DIL simulator use cases, this paper critically focuses on Virtual Validation of ADAS algorithms by testing of repeatable scenarios and effect on driver response time through virtual stimuli of acoustic and optical warnings generated during simulation. To receive appropriate feedback from the driver, industrial grade actuators were integrated with a real-time controller, a high-performance workstation and simulation software called Virtual Test
Sharma, Chinmaya, Bhagat, Ajinkya, Kale, Jyoti Ganesh, Karle, Ujjwala
Advancing Complete Vehicle ADAS Simulation through Virtual Development and Global Collaboration2026-26-040901/16/2026
The automotive industry is currently undergoing a profound transformation, driven not only by the shift toward renewable propulsion systems but also by the increasing emphasis on the software-defined vehicle (SDV), which is particularly in the domain of ADAS and the qualification of vehicles towards higher levels of autonomy important. In combination with accelerating project timelines, this shift creates challenges in integrating electrical and electronic systems throughout the complete vehicle. Magna faces these challenges by intensifying the use of virtual development, a strategy that spans the entire vehicle development process and necessitates global collaboration among engineering teams. This publication presents a real-world example of how the automotive sector can transition from a traditional on-premises-environment (OPE) simulation setup to a Simulation-as-a-Service (SIMaaS) model. Our primary focus is on operational and collaborative dimensions, illustrating the significant
Wellershaus, Christoph, Wakharde, Sagar, Bernsteiner, Stefan
Artificially Intelligent Rapid Rescue Vehicle System2026-26-064201/16/2026
The rapid development of science and technology has impacted on the 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 an increased rate of many health-related issues like stress, anxiety, heart attacks, blood pressure and so on. The existing system in vehicles detects health emergency 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
Eswarappa, Asha, Nagaraj, Chaitra, Mudassir, Syed
Establishing a Scalable Virtual Framework for ADAS Validation Traffic Jam Pilot with Real-World Scene Integration2026-26-050601/16/2026
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
Torque Vectoring Control Techniques for Vehicle Parking2026-26-059001/16/2026
Parking in confined spaces can be quite challenging. It is often a herculean task to align the vehicle in the parking slots where the driver has to make several attempts to park properly. One such ingenious technology that augments vehicle handling, directional controlling and overall driving agility is torque vectoring. It is becoming a pioneer in creating smarter, more responsive vehicles unlike traditional vehicles. With torque vectoring, EV’s can precisely control the torque delivered to each wheel with independent motors per wheel. In confined spaces as well by selectively distributing torque to individual wheels, it optimizes traction and vehicle control, making tasks like parking, sharp turns, and navigating narrow streets smoother and more efficiently. This paper confers about the use of torque vectoring techniques in electric vehicles for smoother and more proficient vehicles handling in tight spaces like parking, which significantly reduces driver efforts while maximizing the
Gangad, Vikas Shridhar, Gautam, Era, Chaudhari, Gitesh, Penta, Amar
Advancing Automotive Radar Characterization: OTA HIL Testing for Enhanced ADAS Safety2026-26-004301/16/2026
The precise validation of radar sensor is necessary due to surging demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies. Over-the-Air (OTA) Hardware-in-the-Loop approach is the optimal solution for the current challenges facing with traditional on road testing. This approach supports productive, controllable and repetitive environment because of its lab-based setup which will eliminates the drawbacks such as high costs, limited repeatability, safety related issues. Key parameters of radar such as accurate detection of objects, analysis of doppler velocity, range estimation, angle of arrival measurement, can be tested dynamically. And this test setup offers wide range of testing scenarios, including varying distance of target, relative speeds, simulation of objects and environmental effects also supported.OTA provides the flexibility to eliminate the physical test tracks or targets so that developers can simulate the errors, by introducing
Jadhav, Tejas, Karle, Ujjwala, Paul, Harshit, SNV, Karthik
Microcontroller-Based Modular Mirror for Heavy and Mid-Commercial Vehicles2026-26-001801/16/2026
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 This will reduce the prone accidents due to non-visibility by approximately 30%, ensuring enhanced road safety and driver comfort. The Indian commercial vehicle segment needs this solution to be implemented when we look at the rate of increasing demand and also accident rates.
Jambagi, Vaibhavi Vyankatesh, Gangvekar, Onkar, Bhandari, Kiran Kamlakar
Integrated Quality Assurance Frameworks for Testing Advanced Automotive Systems in the Era of ADAS and E-Mobility2026-26-056801/16/2026
As the automotive industry rapidly transitions toward intelligent, electrified, and connected mobility, ensuring the safety and performance of advanced vehicle systems has become increasingly complex. Technologies such as Advanced Driver Assistance Systems (ADAS), electric powertrains, and software-defined architectures demand robust quality assurance (QA) frameworks capable of addressing the multi-domain nature of modern vehicle platforms. This paper presents an integrated QA methodology that combines traditional testing protocols with model-based validation, digital twin environments, and real-time system monitoring to comprehensively evaluate the reliability and functionality of next-generation automotive systems. The proposed framework focuses on end-to-end traceability from requirements to validation, encompassing hardware-in-the-loop (HIL), software-in-the-loop (SIL), and over-the-air (OTA) testing strategies. Emphasis is placed on simulating complex scenarios for ADAS, battery
Komanduri, Arun Srinivas, Srivastava, Anuj
Modeling and Validating Foreseeable Misuse in Safety of the Intended Functionality: A Case Study of Automated Emergency Braking12-09-03-001712/31/2025
This study presents a structured evaluation framework for reasonably foreseeable misuse in automated driving systems (ADS), grounded in the ISO 21448 Safety of the Intended Functionality (SOTIF) lifecycle. Although SOTIF emphasizes risks that arise from system limitations and user behavior, the standard lacks concrete guidance for validating misuse scenarios in practice. To address this gap, we propose an end-to-end methodology that integrates four components: (1) hazard modeling via system–theoretic process analysis (STPA), (2) probabilistic risk quantification through numerical simulation, (3) verification using high-fidelity simulation, and (4) empirical validation via driver-in-the-loop system (DILS) experiments. Each component is aligned with specific SOTIF clauses to ensure lifecycle compliance. We apply this framework to a case of driver overreliance on automated emergency braking (AEB) at high speeds—a condition where system intervention is intentionally suppressed. Initial
Kang, Do Wook, Kim, Woojin, Jang, Eun Hye, Chang, Mi, Yoon, Daesub, Jang, Youn-Seon
Safety, ADAS, and Cybersecurity: Vol. 4EPRCOMPV01202512/29/2025
Burton, Simon, Chalmers, Seth, Wishart, Jeffrey, Zheng, Ling
Zonal Architecture Integration into the ADAS System of Commercial Vehicles2025-36-013412/18/2025
In the automotive industry, zonal architecture is a design approach that organizes a vehicle’s electronic and communication architecture into specific zones. These zones group components based on their function into the same control unit, allowing for more efficient integration and simplified communication between the various systems of the vehicle. To improve the efficiency of information centralization, zonal architecture groups Electronic Control Units (ECUs) according to their functionalities, facilitating faster data exchange between them and enabling better prioritization filtering among different categories. An important aspect of this architecture is the implementation of the Controller Area Network Flexible Data-rate (CAN FD) protocol and Automotive Ethernet. These are serial communication protocols specifically developed for automotive applications, enabling higher transmission rates and larger data packets. With the growing need for higher speed and quality in communication
Santos, Felipe Carvalho, Paterlini, Bruno Scarano, Pereira, Luca Angelone Canhete, Baptistella, Luiz Felipe Leardini, Pedroso, Henrique Gomes, Milani, Pedro Henrique Pires, Gama, Ulisses Araujo
Development of an Adaptive Algorithm for the Automatic Emergency Braking System10-10-01-000812/13/2025
Automatic emergency braking (AEB) systems are crucial for road safety but often face performance challenges in complex road and climatic conditions. This study aims to enhance AEB effectiveness by developing a novel adaptive algorithm that dynamically adjusts braking parameters. The core of the contribution is a refined mathematical model that incorporates vehicle-specific correction coefficients and a real-time prediction of the road–tire friction coefficient. Furthermore, the algorithm features a unique driver-style adaptation module to optimize warning times. The developed system was functionally tested on a vehicle prototype in scenarios including dry, wet, and snow-covered surfaces. Results demonstrate that the adaptive algorithm significantly improves collision avoidance performance compared to a non-adaptive baseline, particularly on low-friction surfaces, without introducing excessive false interventions. The study concludes that the proposed adaptive approach is a vital step
Petin, Viktor, Keller, Andrey, Shadrin, Sergey, Makarova, Daria, Antonyan, Akop, Furletov, Yury
TOC99-07-06-0TOC12/02/2025
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Tobolski, Sue
DRIVING SAFETY FORWARD: How simulation and MODSIM accelerate ADAS innovation25AUTP12_0712/01/2025
Simulation has become mission-critical for ADAS development. Model-based systems engineering can integrate modeling and simulation from the start of the design process. Advanced Driver Assistance Systems (ADAS) are transforming vehicle safety, acting as the bridge between conventional driving and full autonomy. From adaptive cruise control to emergency braking and blind-spot detection, these technologies rely on a dense network of radar sensors, antennas, electronic control units and software. What unites them is the need for precise functionality under complex real-world situations. Achieving full reliability requires more than testing on the road; it demands a virtual approach grounded in simulation. Simulation has become mission-critical for ADAS development. As new vehicles integrate dozens of sensors into tightly constrained spaces, even subtle design decisions can affect system performance. Radar solutions, in particular, present unique challenges, especially as vehicle surfaces
Eichler, Jan
CARLA Hardware-in-the-Loop Simulation Environment for Autonomous Driving12-09-02-001511/20/2025
This article suggests a validation methodology for autonomous driving. The goal is to validate front camera sensors in advanced driver-assist systems (ADAS) based on virtually generated scenarios. The outcome is the CARLA-based hardware-in-the-loop (HIL) simulation environment (CHASE). It allows the rapid prototyping and validation of the ADAS software. We tested this general approach on a specific experimental application/setup for a vehicle front camera sensor. The setup results were then proven to be comparable to real-world sensor performance. The CARLA simulation environment was used in tandem with a vehicle CAN bus interface. This introduced a significantly improved realism to user-defined test scenarios and their results. The approach benefits from almost unlimited variability of traffic scenarios and the cost-efficient generation of massive testing data.
Cardozo, Shawn Moses, Hlavác, Václav
Analysis of Zonal and Distributed Based Architecture with MBSE Approach through Duration Simulation2025-28-033711/06/2025
Present study aims to analyze different E/E architectures trending in automotive industry currently. This study shows the comparison analysis done between zonal architecture and distributed architecture. Comparison methodology includes duration simulation performed for a vehicle feature on both architectures. Present study has adopted MBSE approach for the analysis. Study includes analysis done for distance control, airbag activation and rear park assist features developed on zonal and domain architecture. Duration simulation is also performed on same feature on both architectures. While performing duration simulation of all above features on both zonal and distributed architecture time constraints where assumed based on run time machine performance. Results shows that when only feature must be executed distributed architecture is more feasible. However, when feature has been made more updatable, upgradable and scalable Zonal architecture has been more feasible. To summarize study
Mishra, Ayush Manish
Automatic Brake Failure Detection with Electromagnetic Braking System2025-28-037310/30/2025
Brake failures in the vehicles can cause hazardous accidents so having a better monitoring and emergency braking system is very important. So, this project consists of an autonomous brake failure detector integrated with Automatic Braking using Electromagnetic coil braking which detects the braking failure at the time and applied the combinations of the brakes, to overcome this kind of accidents. So, here the system comprises of IR sensor circuit, control unit and electromagnetic braking system. How it works: The IR sensor monitors the brake wire, and if the wire is broken, the control unit activates the electromagnetic brakes, stopping the vehicle in a safe manner. This system enhances vehicle safety by ensuring immediate braking action without driver intervention. Key advantages include real-time brake monitoring, reduced mechanical wear, quick response time, and an automatic failsafe mechanism. The system’s minimal reliance on hydraulic components also makes it suitable for harsh or
Raja, Selvakumar, John, Godwin, Siddarth, J P, Senthilkumar, Akash, Mathew, Abhay, R. S., Nakandhrakumar, Nandagopal, Sasikumar, Arumugam, Sivasankar
TOC99-07-05-0TOC10/23/2025
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Tobolski, Sue
Research on The Architecture of Vehicle Front Collision Warning Function2025-99-006110/17/2025
The rapid development of the automobile industry has put forward higher requirements for safe travel, especially in today’s vigorous development of new energy vehicle technology, faster driving speed and more intelligent vehicle configuration, which makes the automobile safety technology become a key research direction. If you can judge the current driving state of the vehicle and provide early warning information to the driver, the occurrence of traffic accidents can be avoided to a large extent. However, in the current field of vehicle safety technology, vehicle collision warning systems are rarely involved. Therefore, this paper proposes a system functional architecture for vehicle front collision warning, which can provide the driver with collision warning according to the current state of the vehicle. If the driver fails to take effective actions within a specified time, the vehicle will automatically brake. This function can effectively avoid the occurrence of traffic accidents.
Shao, Youlin, Zhao, Guochu, Li, Xiaoqing, Shi, Ling, Cheng, Zhiqing
Adapted Intelligent Driver Model for Improved Vehicle Following and Assessment of Energy Impacts2025-01-038710/07/2025
Central to predicting the impacts of individual vehicle operations within microscopic traffic simulation is the driver model. A driver model determines a vehicle’s velocity profile in various driving scenarios and interactions with other vehicles. Characteristics including driver behavior and interactions with stop signs, traffic signals, and with a lead vehicle can be modeled and assessed with a representative driver model. This paper presents the application of an existing intelligent driver model (IDM) with an adaptation for vehicle following dynamics and the interaction with the lead vehicle to be more representative of driver assist systems concerning the relative distance between the lead and simulated ego vehicle. The method uses an additional control term to augment the existing IDM and reduce the inter-vehicle distance to the time gap. The impact on vehicle dynamics is compared and validated with real-world ego vehicle data recorded through driver-assist systems. The adapted
Udipi, Anirudh, Jadhav, Shreeprasad, Bhure, Mayur, Hegde, Bharatkumar, Poovalappil, Aman, Robare, Andrew, Apostol, Peter, Bahramgiri, Mojtaba, Naber, Jeffrey
SAE TOMORROW TODAY UNPLUGGED - ADAS Takeover: Are Drivers Ready to Let Go?1353710/03/2025
With Ford's BlueCruise logging 58 million miles in 2024 and GM's Super Cruise generating hundreds of millions in revenue, more and more drivers are embracing Advanced Driver Assistance Systems (ADAS) to arrive at their destination more relaxed and alert. In this Unplugged episode of SAE Tomorrow Today, host Grayson Brulte dives into reports from various automakers, Goldman Sachs, and Consumer Reports to show just how widespread ADAS adoption has become. He also explores the surprising benefits of "relaxed driving" and how hands-free driving systems could become as commonplace as cruise control. 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 LinkedIn, Instagram, Facebook, Twitter, and YouTube.
Patterson, Lori
Software Defined VehiclesR-59509/22/2025
Software Defined Vehicles This book provides a clear, in-depth introduction to the concept of software-defined vehicles (SDVs) and their role in the changing mobility ecosystem. It explores how software has become the core enabler of innovation, allowing manufacturers to deliver new features, safety functions, and comfort enhancements to their customers after a vehicle leaves the showroom floor. From advanced driver assistance systems (ADAS) to AI-powered co-pilots, SDVs are shifting the focus from hardware to dynamic, user-centric, service models that offer continuous software updates and upgrades. Software Defined Vehicles also delves into the broader societal and consumer shifts driving this change. Readers will gain insight into how new generations view transportation, how business models like Mobility as a Service (MaaS) are evolving, and why sustainability and flexibility now take precedence over traditional car ownership. Whether you're a technology professional, automotive
Pathrose, Plato
SAE TOMORROW TODAY - AVs in Europe: Balancing Innovation and Regulation1353509/18/2025
What does it take to bring safe, reliable autonomous vehicles to Europe's roads? From shifting to performance-based regulations for L3 and L4 systems to the role of human oversight, the European Commission Joint Research Centre is using technology, policy, and collaboration to drive the future of autonomy. Listen in as we sit down with members Akos Kriston, Officer, Scientific Research for ADAS, and Espedito Rusciano, Programme Manager, Scientific Research for Connected, Automated and Smart Mobility, to discuss the EU's evolving approach to semi and fully autonomous driving. You'll learn how projects like HIDDEN are pushing the boundaries of safety in complex urban environments, how the Open Regulatory Framework could shape the next decade of mobility, and why international collaboration is key to success. 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
Patterson, Lori
Using Vehicle Kinematics to Enhance Situational Awareness2025-01-047709/16/2025
Armored vehicles offer limited view to the driver and crew. Two-dimensional vision-based situational awareness (SA) systems provide the driver a view of the area around the vehicle. The addition of distance to objects can offer a more comprehensive understanding of the surroundings assisting the driver with the locations of obstacles and rollover hazards. Methods currently available or under development for depth perception have issues limiting their utility in the field.. Some interfere with crew operations, others are are too costly, are not covert or require excessive processing. We offer a low-cost and computationally efficient approach called Kinetically Enhanced Situational Awareness (KESA) that derives distance to objects using existing SA sensors and processors combined with a knowledge of vehicle kinematics. We demonstrate how range can be used to enhance and supplement AI based driver assistance and threat warnings.
Pilgrim, Robert A., Brown, Roy C.
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