Browse Topic: Sensors and actuators

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Multi-Storey AI Based Parking System2026-28-0129To be published on 02/01/2026
This paper presents a comprehensive design and implementation of an AI-based parking management system tailored to address the challenges of modern parking facilities. The system is designed to enhance efficiency, reduce manual intervention, and optimize operational costs while providing a seamless experience for drivers. The core architecture of the system integrates advanced technologies, including computer vision and IR sensors, thereby minimizing reliance on conventional sensors and streamlining the parking process. By leveraging computer vision, the system continuously monitors parking areas in real-time, accurately detecting vehicle occupancy status, and dynamically updating the availability of parking spaces. This real-time monitoring capability enables efficient space utilization, allowing for the optimization of parking resources. In addition to optimizing space allocation, the proposed system prioritizes security through the integration of video surveillance. Utilizing AI
N, Kalaiarasi, Gupta, Shivansh, Hajarnis, Mihir, anand, Vikas
STEERING AUTOMATION FOR LANE KEEP ASSISTANCE2026-28-0117To be published on 02/01/2026
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
MINER’S SAFETY BOT2026-28-0116To be published on 02/01/2026
Mining remains one of the most hazardous industries, with workers constantly exposed to life-threatening conditions such as toxic gases, high temperatures, and confined spaces. To address these concerns, we propose the design and development of an autonomous Miner’s Safety Bot aimed at enhancing underground safety through real-time environmental monitoring and intelligent navigation. The system is built around the ESP32 microcontroller, integrating critical sensors including the MQ7 gas sensor for detecting carbon monoxide and methane, the DHT11 sensor for measuring ambient temperature, and an ultrasonic sensor for obstacle detection. These components work to monitor hazardous parameters and assist the bot in navigating through narrow mine shafts. A servo motor connected to a remote-controlled chassis adjusts the bot's direction when obstacles are detected. The bot employs the ESP32-CAM module to transmit live visuals from the mining site to external observers. Furthermore, sensor data
D, SUCHITRA, D, ANITHA, MUTHUKUMARAN, BALASUBRAMANIAM, MOHANRAJ, SIDDHARTH, SUBASH CHANDRA BOSE, ROHAN
IoT-Enabled Cloud-Integrated Smart Parking System with Real-Time Monitoring and AI-Based Space Optimization for Next-Gen Mobility2026-28-0113To be published on 02/01/2026
This study presents the design and implementation of an advanced IoT-enabled, cloud-integrated smart parking system, engineered to address the critical challenges of urban parking management and next-generation mobility. The proposed architecture utilizes a distributed network of ultrasonic and infrared occupancy sensors, each interfaced with a NodeMCU ESP8266 microcontroller, to enable precise, real-time monitoring of individual parking spaces. Sensor data is transmitted via secure MQTT protocol to a centralized cloud platform (AWS IoT Core), where it is aggregated, timestamped, and stored in a NoSQL database for scalable, low-latency access. A key innovation of this system is the integration of artificial intelligence (AI)-based space optimization algorithms, leveraging historical occupancy patterns and predictive analytics (using LSTM neural networks) to dynamically allocate parking spaces and forecast demand. The cloud platform exposes RESTful APIs, facilitating seamless
Deepan Kumar, Sadhasivam, S, Balakrishnan, Dhayaneethi, Sivaji, Boobalan, Saravanan, Abdul Rahim, Mohamed Arshad, R, Jamuna, C, PRADEEPKUMAR, L, Rishi Kannan
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
Next-Gen Driver Health and Wellness Platform for Fatigue Detection and Emotional Wellbeing Monitoring2026-26-0639To be published on 01/16/2026
Driver fatigue and emotional distress are major contributors to traffic accidents, especially among long-haul and professional drivers, making their detection a critical area in road safety and public health. While existing research has explored various sensor-based and wearable solutions to monitor driver states, these approaches often suffer from high cost, intrusiveness, or limited scalability. Camera-based systems have recently gained attention for being less invasive and more practical for real-world deployment; however, many still depend on multiple sensors or cloud-based processing, which raise concerns around energy consumption, privacy, and integration complexity. To address these gaps, we present a sustainable, camera-only Driver Health and Wellness Platform for real-time fatigue detection and emotional wellbeing monitoring. The system leverages a single in-cabin camera and applies lightweight, edge-optimized computer vision models to analyze facial features, eye dynamics
Iqbal, Shoaib, Imteyaz, Shahma
Lightweight AI Deployment for Legacy Automotive ECUs: A Practical Optimization Approach2026-26-0663To be published on 01/16/2026
Automotive systems are increasing adopting data-driven and intelligent functionality in the areas of predictive maintenance, virtual sensors and diagnostics. This has led to a need for the AI models to be directly run on vehicle ECUs. However, most of these ECUs – especially those in cost-sensitive or legacy platforms lack the computational capacity and parallel processing support required for standard AI implementations. Given the stringent real-time and reliability requirements in automotive environments, deploying such models presents a unique challenge. This paper proposes a practical methodology to optimize both the training and deployment phases of AI models for low-computation ECUs that operate without parallelism. Designing lightweight model architectures, using pruning and quantization techniques to minimize resource utilization, and putting in place a strategy appropriate for single-threaded execution are the three main objectives of the developed approach. The goal is to
Sharma, Sahil, Mathew, Melvin John
Comprehensive Evaluation of Bolster Behavior: Field Data Insights for Design Modifications2026-26-0497To be published on 01/16/2026
Bogie suspension systems are increasingly being used in tipper vehicles to enhance their performance and durability, especially in demanding environments like construction and mining areas. Bolsters play a very crucial role in the bogie suspension systems of tipper vehicles, contributing significantly to their overall performance and durability. Bolsters help in evenly distributing the load across the suspension system, reducing stress on individual components and enhancing the vehicle’s stability. They act as shock absorbers, mitigating the impact of rough terrains and heavy loads, which is essential for maintaining the structural integrity of the vehicle. By dampening vibrations, bolsters improve ride comfort and reduce wear and tear on the vehicle’s components, leading to longer service life. Bolsters assist in maintaining proper alignment of the suspension system, ensuring optimal performance and safety. This study focuses on the comprehensive testing and evaluation of bolsters to
V Dhage, Yogesh, Kolage, Vikas
Automated evaluation of drive file simulation accuracy2026-26-0528To be published on 01/16/2026
In the area of structural durability testing using servo-hydraulic actuators, developing drive files for the actuators is a major step. Testing outcomes depend on ensuring the simulation accuracy of each drive file. These drive files are developed in an iterative process for different test track surfaces at different road and load combinations till the time we achieve better correlation. Evaluation of simulation accuracy of the drive files is an extensive manual review process, making it time-consuming and resource-intensive. To address this challenge, an application has been developed to automate the comparison of actuator signals with predefined target signal files. This tool enables quick and accurate analysis of each drive file in a test run, facilitating a comprehensive review of signal deviations. Each test run has thousands of drive files based on road-load mix and actuator settings. This application helped us significantly optimize the simulation workflow by reducing the manual
Soni, Yash, Katake, Vrishali, Mullapudi, Dattatreyudu, Chaskar, Mithun
Advanced Sensor less Machine Learning Technique for Early Detection of Engine Oil Degradation2026-26-0656To be published on 01/16/2026
Maximizing vehicle uptime and reducing maintenance costs are critical objectives in modern automotive systems, making efficient resource utilization a top priority. One key factor is engine oil degradation, which directly affects engine performance, longevity, and overall vehicle efficiency. Current Conventional oil monitoring approaches are real time based on dedicated sensors—can be inefficient, costly, or poorly adapted to varying usage conditions. While earlier studies have explored sensor-based or chemical analysis methods for oil health monitoring, these solutions often lack scalability and cost-effectiveness for widespread adoption. This paper introduces a Machine Learning-based Engine Oil Degradation Detection System that operates non-intrusively using existing vehicle CAN signals, requiring no additional sensors. Key engine parameters such as RPM, Torque, Gear Position, Engine Power, Coolant Temperature, and Odometer readings are trained with tri-bological properties
Dusane, Mangesh, Tade, Vilas, Iqbal, Shoaib
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
Smart Charge Port Housing with Integrated Single Shaft Self-Locking Mechanism for Electric Vehicles2026-26-0593To be published on 01/16/2026
This research presents the development of an advanced Smart Charge Port Housing system for electric vehicles that incorporates intelligent actuation and an integrated single shaft self-locking mechanism. Conventional charge port systems rely on communication with the vehicle’s Body Control Module or Vehicle Control Unit, limiting functionality when the vehicle is in an ignition-off state. The proposed Charge Port Housing addresses this limitation through a microcontroller-based rotary actuator capable of autonomous decision-making, storing the last known position of the lid and executing operations independently of the vehicle’s electronic control architecture. The actuator operates via wired input signals and supports seamless communication over the Local Interconnect Network protocol during ignition-on state. A key innovation lies in the mechanical design: a single shaft self-locking mechanism that combines actuation and locking into a compact, unified assembly, eliminating the need
Mohunta, Sanjay, Khadake, Sagar
A method of selectively elevating a Seamless Switch Integrated in Fabric2026-26-0596To be published on 01/16/2026
This research presents the construction and working principle of Selectively Elevated Seamless Fabric Switch technology aimed at advancing automotive interior design through enhanced aesthetics, functionality, and user experience by providing a tactile surface that is available for operation only during the activated, elevated state. Traditional mechanical switches often suffer from issues such as dust and water ingress, accidental activation, and a fragmented visual profile. The proposed system integrates concealed controls sandwiched with a fabric surface, with switches selectively elevated only upon user interaction. The design incorporates conductive fabric layers and electromagnetic actuation to achieve seamless integration with vehicle interiors while maintaining responsive tactile feedback. The input provided for activating the switch can be a signal such as gesture or proximity of the user’s finger. Upon activation the switch is selectively elevated and ready for operation due
Mohunta, Sanjay, Panchal, Girish, Puthran, Shaunak
AI based models as Virtual sensors to replace real sensors2026-26-0671To be published on 01/16/2026
Artificial Intelligence and Machine learning models have a large scope and application in Automotive embedded system. These models are used in automotive world for various applications like calibration, simulation, predictions etc. These models are generally very accurate and play the role of a virtual sensor. However, the AI/ML models are resource intensive which makes them difficult to execute on a largely optimized automotive embedded systems. The models also need to follow safety standards like ASIL-D. The current work involves creating a Global DoE with ASCMO to generate data from a 125cc single to create AI/ML model for the engine outputs like Torque, T3, Midcat temperatures etc. The created models were validated across the operating space of the engine and found to have good accuracies. With AI Coder, the torque and T3 prediction AI models were converted to embedded code which can be easily used as a virtual sensor in real time. Using these AI models, accurate predictions can be
Chouhan, Vineet Singh, Bulandani, Saurabh, Kumar, Alok, Varsha, Anuroopa, P R, Renjith
Hardware in Loop Validation of Rotary Switch with TFT Display2026-26-0540To be published on 01/16/2026
The increasing complexity of modern automotive drive control systems necessitates the adoption of robust validation methods to ensure functional safety, reliability and customer satisfaction. This paper presents the development and implementation of a comprehensive Hardware-in-the-Loop (HIL) testing framework designed specifically for a specific ECU known as Gear Selection Switch (GSS)/Drive control switch (DCS) system. Hardware-in-the-Loop (HIL) Testing is a simulation-based testing technique where real physical hardware (like an electronic control unit, switch or sensor) is tested by connecting it to a virtual simulation of the rest of the system — instead of testing it inside a real vehicle. Following the analysis of all the field failure incidents reported till date for GSS, detailed root cause investigations were conducted using in-house testing and Ishikawa diagram analysis. A critical failure mode was identified and addressed through targeted mechanical design modification and
Bhuyan, Anurag, Jahagirdar, Shweta, Khandekar, Dhiraj
Shaping the Future of Mobility with Innovative Power Tailgate Testing Solutions2026-26-0473To be published on 01/16/2026
Abstract With increasing demand for automation and user convenience in modern vehicles, Power Operated Tailgates (POT) have become standard in premium and mid-segment cars. However, validating such systems—comprising electronic control units (ECUs), sensors, actuators, and mechanical components poses significant challenges in safety, reliability, and cost. This paper introduces a Hardware-in-the-Loop (HiL) based validation framework that allows comprehensive, automated, and safe testing of POT systems without depending on full vehicle prototypes. The HiL platform integrates Real Time Hardware and Real Time software with dynamic models to simulate real-world behaviors. It enables automated validation of normal and fault scenarios—such as open/close commands, anti-pinch protection, voltage sensitivity, and communication errors—ensuring robust system performance. The proposed framework accelerates development, improves test coverage, and supports early fault detection, making it a
More, Shweta, Ghanwat, Hemant, Shetti, Suraj, Jape, Akshay, Kulkarni, Shraddha, Jagdale, Nitin
Determination of Acrylonitrile Content in Nitrile Butadiene Rubber Vulcanizates by Py-GCMS Techniques2026-26-0546To be published on 01/16/2026
Nitrile Butadiene Rubber (NBR), a copolymer of butadiene and acrylonitrile is known for its superior resistance to hydrocarbon oil, low gas permeability and excellent thermal stability. It is extensively used in seals, O-rings, conveyor belts and pneumatic tires. It is worth mentioning that these performance attributes are predominantly influenced by acrylonitrile content. While solid-state 13C Nuclear Magnetic Resonance (NMR) is an established technique for structural characterization of rubber vulcanizates, its high cost and accessibility limits its application in routine industrial analysis. This study aims to develop Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GCMS) as a robust, precise, cost-effective alternative to determine acrylonitrile content in NBR vulcanizates. This research demonstrates and establish a method to determine the acrylonitrile (ACN) content in finished rubber vulcanizates through pyrolysis gas chromatography-mass spectrometry (Py-GCMS). This method
Samanta, Rajyasree, Ghosh, Debojit, Anjana, Kanhaiya, Sen, Amit, Guria, Biswanath, Chanda, Jagannath, Samui, Barun, Ghosh, Prasenjit, Mukhopadhyay, Rabindra
Accelerating Product Development Life Cycle through Digitalization of Fatigue Life for Structural Components2026-26-0496To be published on 01/16/2026
In today’s competitive market, accelerating product development without compromising durability is critical. Durability is a key benchmark for assessing the quality and reliability of automotive products. To meet rising customer expectations and regulatory demands, the industry must develop vehicles that offer high performance and reduced weight while ensuring safety. A well-engineered vehicle must retain structural integrity and functionality under normal operating conditions and withstand extreme load events without critical failure. Achieving this requires effective Road Load Data Acquisition (RLDA), integrated with robust design practices and efficient validation processes. However, physical RLDA is time-consuming and costly, as it depends on prototype vehicles that are often available only in the later development stages. Failures identified during these late-stage tests can delay the product launch significantly. To address these challenges, this paper introduces a digital
Kokare, Sanjay, Dwivedi, Sushil, Siddiqui, Arshad, Iqbal, Shoaib
Real-Time Lane Change Risk Estimation Using Extended Lane Change Risk Index (ELCRI) and Fault Tree Analysis2026-26-0040To be published on 01/16/2026
Accidents during lane changes are increasingly becoming a problem due to various human based and environment-based factors. Reckless driving, fatigue, bad weather are just some of these factors. This research introduces an innovative algorithm for estimating crash risk during lane changes, including the Extended Lane Change Risk Index (ELCRI). Unlike existing studies and algorithms that mainly address rear-end collisions, this algorithm incorporates exposure time risk and anticipated crash severity risk using fault tree analysis (FTA). The risks are merged to find the ELCRI and used in real time applications for lane change assist to predict if lane change is safe or not. The algorithm defines zones of interest within the current and target lanes, monitored by sensors attached to the vehicle. These sensors dynamically detect relevant objects based on their trajectories, continuously and dynamically calculating the ELCRI to assess collision risk during lane changes. Additionally
Dharmadhikari, Mithil, S, Mrudula, Nair, Nikhil, Malagi, Gangadhar, Paun, Cristin, Brown, Lowell, Korsness, Thomas
Novel Approach on Material characterization Testing of various Wiring Harness2026-26-0548To be published on 01/16/2026
The automotive wiring harness (length of 4-5 km) is a very important and complex system in the development of a modern car due to a lot of new electric & electronic components and sensors. It is a very sensitive material unlike metals and is considered as a composite which is highly anisotropic in nature, as it consists of several different layers of copper/aluminum strands and insulation. Because of insulation, wiring harness exhibits viscous plastic behavior which is crucial in determining the durability and long-term performance of the cables. Material properties play an important role in determining the behavior of wiring harness after assembly into the car. Wiring harness may undergo Bending, Torsion and Tension loads, causing the stress and strain in the individual electrical wires. The lack of CAE validation of the wiring harness routing may lead to extra costs for the automotive OEMs over a period. This paper describes the novel method of Testing the Cables and Bundles used in
Beesetti, Siva, Kalkala Balakrishna, Prasad, James Aricatt, John, Shah, Dipam, Tas, Onur, Krogmann, Stephan
Single Radar: A Robust and Cost-Effective Solution for ADAS and Parking functionality2026-26-0049To be published on 01/16/2026
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 One 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 One 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
Intelligent Child-Safety Inhibition framework for preventing accidental vehicle activation2026-26-0013To be published on 01/16/2026
Modern vehicle technologies such as keyless entry, push-button start, digital switches have made it easier and more convenient to operate cars. However, this ease of operation has also introduced new safety concerns, particularly the increased risk of accidental operations by children. This can lead to unintentional vehicle movement, injuries, and even fatalities. Existing safety features (e.g., unattended child presence alarms) mitigate entrapment risks but do not prevent children from unintentionally starting or shifting while inside. This paper proposes implementation of a solution for child-safety system which inhibits certain functionalities to prevent accidental operations by underage occupants. The proposed system combines multiple existing technologies like weight sensors, seat position detection, facial recognition, in vehicle camera tracking to determine the child presence. With this, certain operations can be temporarily inhibited, or the vehicle can ask for secondary
Mote, Vaishal, Garg, Mudit, Pasupuleti, Raju
Predictive Modelling of Battery Behavior for Enhanced Energy Management in Electric Vehicles2026-26-0385To be published on 01/16/2026
As electric vehicles (EVs) and smart energy systems continue to evolve, optimizing energy usage and ensuring system reliability has become critical. However, battery pack modelling remains challenging due to its highly dynamic and nonlinear behavior due to the temperature variations, aging, and variable load conditions. This paper presents a 1D digital twin framework designed for predictive monitoring of the battery parameters, including State of Charge (SoC), terminal voltage, temperature, and an indicative assessment of State of Health (SoH). The battery is modelled using a Thevenin equivalent circuit that covers both steady-state and dynamic electrical characteristics. Key parameters such as open-circuit voltage (OCV), internal resistance, and dynamic characteristics were derived through pulse testing conducted in our laboratory. A thermal modelling is done to capture the heat generation and cell temperature. SoC estimation is carried out using the Coulomb counting method and
G, Ayana, Gumma, Muralidhar
Development of Advanced Thermoplastic Elastomeric Mat and Its Study on Thermal Performance of Wireless Charging System2026-26-0283To be published on 01/16/2026
This study aimed to develop a thermally conductive TPE mat and assess its performance in comparison to an existing antiskid rubber mat, specifically evaluating its impact on wireless charger efficiency. Moreover, morphological and thermal analyses were conducted to establish a correlation between the material behaviours of the new and current thermally conductive antiskid mats. The process of developing the thermally conductive TPE involved utilizing a two-roll mill followed by compression moulding to achieve a 2D sheet shape. Notably, the thermally conductive mat demonstrated a consistent enhancement in charging efficiency over the conventional antiskid mat. To examine the thermal characteristics, thermal characterization techniques including DSC and TGA were employed for both the existing and newly developed mats. FTIR spectroscopy was also utilized to confirm the presence of organic functional groups within the mat. The morphological analysis of the fillers used to enhance thermal
Naikwadi, Amol Tarachand, Mali, Manoj, Patil, Bhushan, Tata, Srikanth
Mapless Yet Accurate: Trajectory Prediction for traffic agents using online HD Map Reconstruction for Autonomous Driving2026-26-0039To be published on 01/16/2026
Accurate trajectory prediction of traffic agents is vital for enabling safer and more reliable autonomous driving. High-definition (HD) and standard-definition (SD) maps play a critical role in this process by providing detailed lane topology and directional cues essential for forecasting the movement of surrounding traffic agents. However, creating HD maps is both expensive and resource-intensive, often relying on complex SLAM systems and specialized sensors, while SD maps, though more readily available, lack the precision needed for accurate navigation in autonomous driving. In this work, we present a novel framework for trajectory prediction that uses online reconstruction of HD maps using images from vehicle-mounted cameras, offering a more scalable and cost-effective solution. Our method achieves notable improvements in prediction accuracy, especially in scenarios lacking access to pre-built maps. Additionally, we propose a new evaluation metric that emphasizes safety by
Upreti, Minali, Girijal, Rahul, B A, NaveenKumar, Thontepu, Phani, Ghosh, Shankhanil, Chakraborty, Bodhisattwa
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
Analysis of Engagement Probability for Dog Clutch Geometry Parameters in Heavy-Duty Automated Mechanical Transmissions.2026-26-0437To be published on 01/16/2026
This study presents a simulation-based approach to estimate the dog clutch engagement probability maps under different vehicle operating conditions. The developed probability function incorporates multiple critical parameters including initial speed differential between engaging components, application of countershaft brake, number of tooth in dog clutch, friction coefficients at tooth interfaces, applied actuation force, dog tooth geometry, and component inertia. Using MATLAB and Simulink, comprehensive simulation models were developed to analyze engagement dynamics and produce detailed probability maps at different vehicle speeds. The present work effectively outlines optimal operational zones for successful engagement while identifying critical regions prone to tooth clash and engagement failure. The effect of tooth geometry on engagement probability has been investigated to study its effect on the optimal mismatch speeds. The resulting engagement maps serve as valuable diagnostic
Khan, Mohammad Adeeb, Khan, Nuruzzama Mehadi, Koona, Rammohan
From Vision to Reality - Automotive UI/UX Concept Development at Magna2026-26-0477To be published on 01/16/2026
The development of automotive UI/UX relies on the latest technologies and features in modern vehicle design, focusing on enhancing user interaction. The Magna UI/UX team uses innovative tools to streamline the development of user interaction features. Our process is accessible to all stakeholders and applicable to all UI/UX projects. With extensive experience working with both new entrants and traditional OEMs, we leverage diverse insights and methodologies to create state-of-the-art user experiences. Beginning with the UI strategy, Magna defines the overall display and interaction strategy based on the latest UI/UX trends and benchmarking criteria for user experience. In this phase, Magna uses online clickdummies to evaluate initial wireframes and sketches, documenting UI elements (buttons, typography, colors, icons) and simulating feature interactions like music control. To develop a UI/UX concept based on customer vision, Magna creates the base screen layout and operation flow
Lechner, Michael
Advancing Automotive Radar Characterization: OTA HIL Testing for Enhanced ADAS Safety2026-26-0043To be published on 01/16/2026
The increasing demand for reliable Advanced Driver-Assistance Systems (ADAS) and autonomous driving technologies necessitates the precise validation of automotive radar sensors. Traditional on-road testing, while effective, presents challenges such as limited repeatability, high costs, and safety concerns. To address these limitations, this paper introduces an Over-the-Air (OTA) Hardware-in-the-Loop (HIL) methodology for radar characterization, providing a controlled and repeatable lab-based validation approach. This methodology enables dynamic testing of key radar parameters, including range estimation, angle of arrival measurement, Doppler velocity analysis, and object detection accuracy. The proposed setup supports diverse testing scenarios, such as variable target distances, relative speeds, multiple object simulation, and environmental effects, ensuring a comprehensive evaluation of radar behaviour under complex and safety-critical conditions. Through OTA testing, developers can
Jadhav, Tejas, Karle, Ujjwala, Paul, Harshit, SNV, Karthik
Multiphysics Analysis of Heat Sink Designs for Efficient Thermal Performance in Power Electronics Systems2026-26-0446To be published on 01/16/2026
The thermal management capability of power electronic (PE) systems has a critical impact on the performance and efficiency of electric, fuel cell, or hybrid vehicles. Bus bars, high resistance sensor devices, semiconductor switches, power capacitors are the primary components, which has major contribution in total heat generation in electrical drive unit. As PE packaging sizes are projected to become smaller, the challenge of managing increased heat dissipation becomes more critical. Hence, this paper numerically compares conventional and advanced cooling strategies to determine the best possible thermal management scenario. A multi-physics finite element model, integrating fluid, electrical, thermal, and structural fields, is employed to analyze heat generation within the PE system and the associated cooling mechanisms. Due to the significant impact of surface roughness and topology on electrical and thermal contact resistance, the Cooper-Mikic-Yovanovich (CMY) correlation is utilized
Singh, Praveen Kumar, Natarajan, Nesamani, Murali, Sariki
A review on 'sensor technologies', its application, regulatory standards & emerging trend towards safe hydrogen economy.2026-26-0111To be published on 01/16/2026
In a developing country like India, the growing energy demand across all sectors underscores the urgent need for clean, sustainable, and efficient energy alternatives. Hydrogen stands out as a promising fuel, offering virtually zero emissions and helping to reduce greenhouse gas (GHG) emissions, which directly contributes to mitigating global warming, ensuring a cleaner environment, and lowering dependency on fossil fuels. In line with Sustainable Development Goal 7 (SDG 7), which seeks to guarantee that everyone has access to modern, cheap, and sustainable energy, hydrogen is well-positioned to be a major player in India's energy transformation. However, hydrogen has unique properties such as its wide flammability range, high reactivity, and high energy content present significant challenges in terms of safety, particularly in its storage, transportation, and usage. Improper handling or inadequate safety measures can lead to hazardous incidents, making robust testing, certification
Pawar, Yuvraj, Dekate, Ajay Dinkar, Thipse, S, Belavadi Venkataramaiah, Shamsundara
Trajectory Reconstruction at Signalized Intersections in a Vehicle-to-Infrastructure Environment2025-99-0217To be published on 12/23/2025
Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically
Bai, Wei, Fu, Chengxin, Yao, Zhihong
Design of Intelligent Lighting System for Expressway Tunnel2025-99-0232To be published on 12/23/2025
A smart highway tunnels lighting system based on the technology of cloud platform and Internet of Things(IoTs) has been designed to address the common problems of high energy consumption and low level of intelligence in China's highway tunnel lighting system. The highway tunnel lighting system consists of four layers of architecture: platform management layer, local management layer, middle layer and terminal layer. The system collects real-time brightness, lamp brightness, traffic volume and other data outside the tunnel through various sensors deployed on site, and then uploads the collected data to the main controller through LoRa IoTs. The main controller combines the brightness calculation method of the lighting design rules to control the brightness of the tunnel lighting in real time, achieving real-time adjustment of the brightness of the tunnel LED lights and the brightness outside the tunnel, and realizing a safe and energy-saving lighting effect of "lights on when the car
Wang, Juntao, Liu, Jingyang, Liu, Yong, Feng, Xunwei
Comparison of Parameters and States Estimators for the Longitudinal Dynamics of a Military Heavy Vehicle2025-36-0126To be published on 12/18/2025
Technological innovations in military vehicles are essential for enhancing efficiency, safety, and operational capability in complex scenarios. Advances such as navigation system automation and the introduction of autonomous vehicles have transformed military mobility. State estimators enable the precise monitoring of critical variables that are not directly accessible by sensors, providing real-time information to controllers and improving dynamic response under variable conditions. Their integration is crucial for the development of advanced control systems. This study aims to develop and compare parameter and states estimators for military heavy vehicles using three methodologies: particle filter, extended Kalman filter, and moving horizon state estimation. Computational simulations employ Pacejka’s magic formula to model tire behavior, and the vehicle modeling is based on a simplified quarter-car model, with an emphasis on longitudinal dynamics. In the end, the estimators are
Barros, Leandro Silva, Sousa, Daniel Henrique Braz, Rodrigues, Gustavo Simão, Lopes, Elias Dias Rossi
Current Challenges and Technological Opportunities for Implementing Autonomous Vehicles in Urban Public Transport2025-36-0085To be published on 12/18/2025
Driven by technological advances in artificial intelligence, sensors, connectivity and sustainable mobility, autonomous buses are a reality in many contexts where their application is viable and efficient. The potential of the technology is a clear theme and has been widely discussed over the last two decades, due to various factors such as reducing accidents, increasing operating cost efficiency, improving the efficiency of public transport, reducing environmental impact and offering mobility solutions for increasingly congested urban areas. Due to the implementation of the General Safety Regulation (GSR II) in the European Union, with the aim of reducing traffic accidents and paving the way for fully autonomous vehicles, autonomous vehicles are getting closer to becoming a viable reality on the streets and highways of developed countries [1]. In order to guarantee the necessary safety in autonomous systems, data reliability is fundamental. To this end, it is essential to implement
Gameiro, João, Pirocchi, Amanda, Matias, Brenda, Paterlini, Bruno, Souza, Kerylli de, Angelone, Luca, Gama, Ulisses
Development of a PID Attitude Control System for Sounding Rockets in the International Rocket Engineering Competition2025-36-0105To be published on 12/18/2025
In rocketry competitions, such as the International Rocket Engineering Competition (IREC), unguided sounding rockets are the most commonly used, relying solely on aerodynamic stability to make necessary trajectory corrections during flight. However, this approach has limitations since these vehicles lack mechanisms to ensure apogee accuracy. The active control of a sounding rocket involves methods for orienting and stabilizing the vehicle during flight, using inertial sensors, GPS, and aerodynamic surfaces. These systems allow continuous trajectory and stability adjustments by processing real-time data. In this context, this work proposes the development of a PID-based attitude control system, aligned with IREC guidelines, to improve the accuracy of rocket apogee. For the PID controller design, the second method of the Ziegler-Nichols rule was adopted, based on a linearized transfer function, to calculate the control loop gains. Gain Scheduling technique was employed to estimate gains
Oliveira Junior, Wilson Luiz de, Fazzolari, Heloise Assis, Paiva Carvalho, Carlos Alberto de
Vehicle Electrical Architecture: A Review of Wiring Harness Routing Optimization Strategies2025-36-0130To be published on 12/18/2025
The modern vehicle electrical architecture consists, on average, of 30 integrated electronic modules (ABS, infotainment, instrument panel, etc.), also known as Electronic Control Units (ECUs), and approximately 300 peripherals such as sensors (collision, temperature, oxygen, position, pressure, etc.) and actuators (window motor, mirror motor, relays, airbag inflator, windshield wiper, etc.). This increase in component integration imposes significant challenges to system installation and design. The interconnection of multiple devices renders harness design an arduous and time-consuming task, especially when conducted manually, resulting in error-prone and suboptimal outcomes. Such a scenario highlights the pressing need for studies on harness routing optimization in the automotive industry. Historically, wiring harness design practices have transitioned from manual approaches to the adoption of advanced computational tools. This methodological transition encompasses the use of various
Ribeiro, Thiago, Reis, Breno, Barreto, Zeus, Galeno, Antônio, Pereira, Marcelo, Ferreira, Fláavio Fabrício V. M.
Research on SHM Acceleration Data Recovery Method Based on CNN-BILSTM2025-99-0341To be published on 12/17/2025
In the field of bridge structure condition monitoring, sensor systems often have abnormal or missing monitoring data due to environmental interference or equipment abnormalities. This situation may affect the accuracy of structural safety assessment. In this study, combined with deep learning, aiming at the problem of monitoring data completion, a prediction method based on BILSTM is proposed, and a CNN-BILSTM combined model is constructed for acceleration signal prediction. The prediction effects of the three algorithms, LSTM, BILSTM and CNN-BILSTM, were compared horizontally. Through the analysis of the MAX-MAE-RMSE-R2 index system and the fit degree of the prediction curve, it was confirmed that the combined model has better prediction performance. The experiment adopted the monitoring data of the accelerometer of the Hardanger Bridge in Norway as the training test set. Taking the H1E measurement point data as an example, the MAE index of CNN-BILSTM is 4.2% lower than that of BILSTM
Zhang, Xiangyi
Research on the Application of Flexible Pressure Sensor Array in Electric Vehicle Seats2025-99-0338To be published on 12/17/2025
In this study, an intelligent monitoring system for electric vehicle seats based on flexible pressure sensor array is proposed. Through the design of multi-layer composite film structure and the collaborative development of STM32 embedded platform, high-precision sensing (error<5%) and rapid response (<200ms) of pressure distribution are realized. The experimental results show that the linearity of the sensor array is ± 1.5% FS in the range of 0-100kpa, and the dynamic response time is 3.6 times higher than that of the traditional sensor; By establishing a three-level adjustment algorithm (fuzzy PID+LSTM prediction+genetic optimization), the seat comfort is improved by 20.5%, and the system energy consumption is reduced by 33.5%. The research provides theoretical and technical support for the transformation of intelligent seats from “passive support” to “active interaction”.
Huang, Yifeng, Rong, Daozhi, Lin, Guoyong, Huang, Zhengui, Wang, Ruliang, Tao, Chengxi
Vehicle Abnormal Detection Based on Multi-Source Data Fusion and Graph Neural Networks2025-99-043012/10/2025
Traffic abnormal detection is crucial in intelligent transportation systems, while the heterogeneity and weak spatio-temporal correlation of multi-source data make it difficult for traditional methods to effectively fuse and utilize multimodal information. Most of the existing studies use data-level or decision-level fusion, which fails to fully exploit the feature complementarity of multi-source data, resulting in limited detection accuracy. To this end, we propose a multi-source data fusion anomaly detection method based on graph autoencoder (GAE) and diffusion graph neural network (DiffGNN). First, a unified data preprocessing and fusion strategy is designed to perform feature-level fusion of data from on-board sensors, infrastructures, and external environments to eliminate inconsistencies in data format, temporal alignment, and spatial distribution. Then, GAE is employed for potential graph structure feature extraction to enhance the global representation of the data on the basis
Wang, Yaguang, Xiao, Yujie, Ma, Ying
Automotive Engineering: December 202525AUTP1212/04/2025
IAA 2025 Coverage from Munich of IAA 2025 Qualcomm's Superbrains are here to help with automated driving Arbe chipset improves automated driving decisions DeepDrive's MG 250 generator brings dual-rotor power to PHEVs Horse Powertrain's Future Hybrid System can hybridize EVs Reducing SoC and SoH estimation errors: challenges and solutions in modern BMS New approaches to make SoC and SoH parameters more accurate will be required as battery demand keeps growing in the coming years. Driving safety forward: How simulation and MODSIM accelerate ADAS innovation Simulation has become mission-critical for ADAS development. Model-based systems engineering can integrate modeling and simulation from the start of the design process. Revolutionizing vehicle technology through intelligent actuators A look at E/E complexity at the endpoints, where microcontrollers play a crucial role. Automated fiber placement with Ramy Harik AFP can build complex, lightweight structures, but cost concerns keep its
Smart Wound Monitor Poised to Improve Infection CareTBMG-5430012/01/2025
Researchers from RMIT University have developed a wearable wound monitoring device with integrated sensors that could reduce infection risks by minimizing the need for frequent physical contact.
3D LiDAR for Improved Rover Traversal and ImageryTBMG-5429512/01/2025
Planetary and lunar rover exploration missions can encounter environments that do not allow for navigation by typical, stereo camera-based systems. Stereo cameras meet difficulties in areas with low ambient light (even when lit by floodlights), direct sunlight, or washed-out environments. Improved sensors are required for safe and successful rover mobility in harsh conditions. NASA Goddard Space Flight Center has developed a Space Qualified Rover LiDAR (SQRLi) system that will improve rover sensing capabilities in a small, lightweight package. The new SQRLi package is developed to survive the hazardous space environment and provide valuable image data during planetary and lunar rover exploration.
Automation: How Custom Motion Control Transforms Medical Equipment DesignTBMG-5434012/01/2025
In today’s medical equipment market, reliability is not a luxury — it is a necessity. Every adjustment, every movement, and every interaction with the equipment must be performed flawlessly to ensure patient safety, caregiver efficiency, and long-term service life. Behind this design and precision are highly engineered motion control components, such as gas springs, electric linear actuators, and dampers, that ensure safe, ergonomic operation of medical equipment across a wide range of healthcare applications.
Thermal Model of a Traction Inverter for an Automotive Application, Including DC-Link Capacitor, Power Modules and Electrical Connections2025-01-051911/25/2025
In automotive applications a power electronic converter is used for energy conversion between battery and electrical machine. For high performance drives a lightweight design is demanded. Additionally, a higher efficiency of the inverter results in lower cooling requirements but is often achieved by increasing component weight. Hence, thermal modeling of the components and their interactions is essential to determine the best compromise between weight, efficiency and cooling requirements. In traction inverters the DC-link capacitors, power modules, high voltage electrical connections and low voltage devices dissipate power. In this paper the focus is on the thermal modeling of the DC-link capacitor, power modules and high voltage electrical connections and their system, as the performance of the inverter is defined by these components. The thermal models are derived based on physical properties and geometries. First, the DC-link capacitor thermal model is presented and considers the
Blaschke, Wolfgang Maximilian, Mengoni, Leonard, Pflüger, Robin, Kulzer, André Casal
Research on Overspeed Vehicle Detection Based on Fusion of Millimeter-Wave Radar and Visual Images2025-99-012911/11/2025
To address the limitations of conventional overspeed detection methods, this study proposes a vehicle overspeed detection approach based on the fusion of millimeter-wave radar (MWR) and vision sensors. The MWR captures target position and velocity data, while the vision sensor acquires vehicle image information. Radar-detected points are mapped onto visual images through coordinate transformation, and the Intersection over Union (IoU) method is employed to associate radar points with vision-detected vehicle bounding boxes. Subsequently, for radar-detected points exceeding the speed threshold, the corresponding vehicle images are identified, enabling real-time overspeed detection and data acquisition. This method not only facilitates prompt identification of speeding behavior but also extracts the associated vehicle images, ensuring both accuracy and informational integrity in overspeed monitoring. Experimental results demonstrate that the proposed method achieves high speed measurement
Li, Yuanchen, Wu, Zhichao, Xu, Haibo, Song, Liangliang, Huang, Hao
Cybersecurity: Applying Threat Modeling to Sensor-Control Architectures in Autonomous Off-Highway Vehicles2025-28-031611/06/2025
The rapid evolution of autonomy in Off-Highway Vehicles (OHVs)—spanning agriculture, mining, and construction—demands robust cybersecurity strategies. Sensor-control systems, the cognitive core of autonomous OHVs, operate in harsh, connectivity-limited environments. This paper presents a structured approach to applying threat modeling to these architectures, ensuring secure-by-design systems that uphold safety, resilience, and operational integrity.
Kotal, Amit
Technology Driven Solutions for Effective Tool Management2025-28-024911/06/2025
Tool management remains a persistent challenge in manufacturing, where misplaced or poorly calibrated tools such as torque guns and screwdrivers cause downtime, quality defects, and compliance risks. The Internet of Things (IoT) is transforming tool management from manual entries in spreadsheets and logs to real-time, data-driven solutions that enhance operational efficiency. With ongoing advancements in IoT architecture, a range of cost-effective tracking approaches is now available, including Ultra-Wideband (UWB), Bluetooth Low Energy (BLE), Wi-Fi, RFID, and LoRaWAN. This paper evaluates these technologies, comparing their trade-offs in accuracy, scalability, and cost for tool-management scenarios such as high-precision station tracking, zonal monitoring, and wide-area yard visibility. Unlike prior work that focuses on asset tracking in general, this study provides an ROI-driven, scenario-based comparison and offers recommendations for selecting appropriate technologies based on
Patel, Shravani Prashant
Automating Fault Detection Time Interval in Automotive Functional Safety Using HIL Simulation2025-28-027411/06/2025
Functional safety is driven by number of standards like in automotive its driven by ISO26262, in Aerospace its driven by DO-178C, and in Medical its driven by IEC 60601. Automotive electronic controllers must adhere to state-of-the-art functional safety standard provided by ISO26262. A critical functional safety requirement is the Fault Handling Time Interval (FHTI), which includes the Fault Detection Time Interval (FDTI) and Fault Reaction Time Interval (FRTI). The requirements for FHTI are derived from Failure Mode Effect Analysis (FMEA) conducted at the system level. Various fault categories are analyzed, including electrical faults (e.g., short to battery, short to ground, open circuits), systemic faults (e.g., sensor value stuck, sensor value beyond range), and communication faults (e.g., incorrect CAN message signal values). Controllers employ strategies such as debouncing and fault time maturity to detect these faults. Numerous FDTI requirements must be verified to ensure
Lengare, Sunil, Yadav, Vikaskumar, Shiraskar, Pallavi
Analysis of Simulators for Designing Network Architecture in Wireless Sensor Network Applications2025-28-033811/06/2025
Recent advancements in energy efficient wireless communication protocols and low powered digital sensor technologies have led to the development of wireless sensor network (WSN) applications in diverse industries. These WSNs are generally designed using Bluetooth Low Energy (BLE), ZigBee and Wi-Fi communication protocol depending on the range and reliability requirements of the application. Designing these WSN applications also depends on the following factors. First, the environment under which devices operate varies with the industries and products they are employed in. Second, the energy availability for these devices is limited so higher signal strength for transmission and retransmission reduces the lifetime of these nodes significantly and finally, the size of networks is increasing hence scheduling and routing of messages becomes critical as well. These factors make simulation for these applications essential for evaluating the performance of WSNs before physical deployment of
Periwal, Garvit, Koparde, Prashant, Sewalkar, Swarupanand
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