Browse Topic: Sensors and actuators

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A System-Level Calibration Framework for Embedded Vision: Integration of Sensor, Firmware, and Software Enhancements2026-01-0013To be published on 04/07/2026
Embedded vision systems are essential for contemporary applications, including robotics, advanced driver assistance systems (ADAS), and intelligent surveillance; yet they frequently experience diminished image quality due to resource constraints, environmental variability, and inconsistent illumination conditions. Such degradations impact multiple visual attributes-sharpness, contrast, color accuracy, noise levels, and structural similarity-that are critical for reliable perception in safety- and performance-driven domains. This study introduces a comprehensive system-level calibration architecture that integrates three coordinated layers: sensor-level adjustment, firmware optimization, and adaptive software enhancements. At the sensor level, exposure control, gain tuning, and white balance adjustments mitigate luminance imbalance and color shifts under changing light conditions. Firmware optimization leverages image signal processor (ISP) parameters to reduce temporal and spatial
Indrakanti, Rama Kiran Kumar, Vishnoi, Nitin, Kamadi, Venkata
Sensor Fusion Method for In-Cabin Humidity Prediction2026-01-0131To be published on 04/07/2026
Maintaining optimal in-cabin humidity levels is part of occupant comfort, air quality, and the effective operation of climate control systems, particularly for functions like windshield defogging. This paper introduces a novel sensor fusion methodology for predicting in-cabin humidity distribution without dedicated humidity sensor. The proposed approach leverages readily available vehicle data, integrating information from ambient temperature sensors, in-cabin temperature sensors, occupant detection systems, window status, and climate control settings. By intelligently fusing these diverse data streams, a predictive model is developed to infer the dynamic humidity conditions within the vehicle cabin. We discuss the complex interactions between these parameters, such as the moisture contribution from occupants, the influence of external air ingress through open windows, and the dehumidifying or humidifying effects of the Heating, Ventilation, and Air Conditioning system. The paper
Ghannam, Mahmoud, Schroeter, Robert, Shaik, Faizan
THE IN-VEHICLE CONNECTIVITY FOUNDATION POWERING AUTONOMOUS DRIVING2026-01-0009To be published on 04/07/2026
Achieving full vehicle autonomy is not just about adding sensors or compute-it requires a fundamental shift in how vehicles are architected. Autonomous systems rely on higher-resolution sensors, massive processing power, and the ability to fuse data from multiple sources in real time. Centralized in-vehicle architectures, which consolidate computing and enable sensor fusion, place unprecedented demands on connectivity. Precise time synchronization across all systems becomes critical, as does advanced control to ensure safe and reliable operation. Any delay or data loss can impact decision-making, making robust, resilient communication links essential. High-performance connectivity is the backbone of this evolution. It must deliver the highest bandwidth to handle massive streams of sensor data, support long-reach connections across the vehicle, and maintain error-free performance even in the most challenging electromagnetic environments. This combination of speed, reach, and reliability
Shwartzberg, Daniel
EV Propulsion Drive Converter SiC Power Device Over-Temperature Protection under Low Motor Speed Operation2026-01-0436To be published on 04/07/2026
Monitoring power device temperature in an electric vehicle propulsion drive converter is extremely important to achieve full power delivery within the maximum power capability envelope. Usually, on-die temperature sensors are installed on Si-IGBT power devices in electric vehicle propulsion drive converters to enable monitoring device temperature and achieve over-temperature protection. Currently, SiC MOSFET is a promising power device in power converters of electric drives because of its lower loss, higher switching speed, higher voltage capability, and higher junction temperature limit in comparison with widely used Si-IGBT. However, SiC MOSFET is a more expensive device, so the present technology trend is trying to reduce its chip size. Installation of an on-die temperature sensor on SiC MOSFET will significantly increase its cost and complexity. So presently, there is no junction temperature sensor installed in SiC MOSFET due to which there is great difficulty protecting SiC MOSFET
Thongam, Jogendra Singh, Ge, BAOMING, Bradford, Steven, Kulkarni, Milind
Predictive Maintenance of EV Drive Unit Oil Pumps via Machine Learning on Fleet Telemetry2026-01-0161To be published on 04/07/2026
The reliability of Drive Unit (DU) oil pumps is critical to the performance and safety of electric vehicles, as these pumps provide essential lubrication and thermal management. However, direct physical sensors for real-time pump health monitoring are absent in current architectures, making early fault detection particularly challenging. To address this limitation, we present a novel, data-driven anomaly detection framework that leverages large-scale customer fleet telemetry and advanced machine learning to identify incipient pump degradation that traditional diagnostic methods often fail to capture. The core of the approach is an XGBoost regression model trained on time-series features—including commanded pump speed, oil temperature, and historical pump current—to predict expected current behavior under nominal conditions. Deviations are quantified using the Mean Absolute Percentage Error (MAPE) between predicted and actual currents, providing a continuous and interpretable measure of
Li, Jingman, Yao, Mengqi, Rahimi, Sahil, Lin, Joanne
Ultra-Low Latency Video Pipeline Optimization for Perception-Centric Autonomous Systems2026-01-0022To be published on 04/07/2026
Autonomous platforms such as self-driving vehicles, advanced driver-assistance systems (ADAS), and intelligent aerial drones demand real-time video perception systems capable of delivering actionable visual information at ultra-low latency. High-resolution vision pipelines are often hindered by delays introduced at multiple stages-sensor acquisition, video encoding, data transmission, decoding, and display-undermining the responsiveness required for safety-critical decision making. This study introduces a holistic system-level optimization framework that systematically reduces end-to-end video latency while maintaining image fidelity and perception accuracy. The proposed approach integrates hardware-accelerated encoding, zero-copy direct memory access (DMA), lightweight UDP-based RTP transport, and GPU-accelerated decoding into a unified pipeline. By minimizing redundant memory copies and software bottlenecks, the system achieves seamless data flow across hardware and software
Indrakanti, Rama Kiran Kumar
Radar-Based Dynamic Pixel Activation in Camera Sensors for Optimized Image Processing, Power Efficiency, and Thermal Management2026-01-0047To be published on 04/07/2026
This paper presents a radar-based dynamic imager pixel activation method designed to optimize image processing efficiency, power consumption, and thermal management in automotive In-cabin monitoring systems (DMS and OMS). By integrating radar sensing with high-resolution cameras, the proposed approach selectively activates image sensor pixels only within radar-identified regions of interest, such as moving occupants or key cabin areas. This selective pixel activation substantially reduces the computational workload and data bandwidth required, as the camera transmits high-resolution data solely for relevant zones while maintaining lower resolution or deactivating pixels elsewhere. The fusion of radar and camera data enables adaptive sensor control that caters to distinct scenarios, including driver gaze tracking and passenger monitoring, thereby enhancing DMS and OMS functionality. The architecture supports mounting configurations such as headliner or rearview mirror installations
Kasarla, Nagender Reddy, Patel, Krunal, Balaraman, Nirmal Kumar
ProGuard: A Real-time Preemptive Artificial Intelligence-Based Anti-Pinch System for Bus Entryways on Low-Power Edge Devices2026-01-0100To be published on 04/07/2026
This paper proposes ProGuard, a novel approach to preemptive pinch detection systems for buses. ProGuard utilizes state-of-the-art AI object detection algorithms to identify potential pinching events in bus entryways before pinching occurs. Modern conventional anti-pinch systems, such as pressure sensors or hall effect sensors, often rely on mechanical contact before triggering. While these systems are established safety mechanisms, they are reactive and therefore require some level of pinching before triggering. This reactive approach presents numerous safety concerns for passengers, especially when considering children on school buses. Existing preemptive detection methods, such as infrared or ultrasonic sensors, solve the problems presented by these reactive detection systems. However, these systems either lack the range or environmental resilience needed for reliable operation in buses. The critical nature of anti-pinch systems requires a robust and reliable solution that can adapt
Bradley, Hudson, Zadeh, Mehrdad, TAN, Teik-Khoon
A Comparison of Road Grade Preview Signals from Lidar and Maps2026-01-0026To be published on 04/07/2026
Road grade can impact the energy efficiency, safety, and comfort associated with automated vehicle control systems. Currently, control systems that attempt to compensate for road grade are designed with one of two assumptions. Either the grade is only known once the vehicle is driving over the road segment through proprioception, or complete knowledge of the oncoming road grade is known from a pre-made map. Both assumptions limit the performance of a control system, as not having a preview signal prevents proactive grade compensation, whereas relying only on map data potentially subjects the control system to missing or outdated information. These limits can be avoided by measuring the oncoming grade in real-time using on-board lidar sensors. In this work, we use point returns accumulated during travel to estimate the grade at each waypoint along a path. The estimated grade is defined as the difference in height between the front and rear wheelbase at a given waypoint. Kalman filtering
Schexnaydre, Logan, Poovalappil, Aman, Robinette, Darrell, Bos, Jeremy
Advanced Integrated Chassis Control for Improved Energy Efficiency and Driving Experience in Electric Vehicle Applications2026-01-0643To be published on 04/07/2026
Complexity of modern ground vehicles grows constantly, since car manufacturers want to provide functionality, while customers are expecting innovation and recent technologies to be integrated into the latest models released to the market. Recent advances in hard- and software opened the gates for new means of vehicle control and operation. Especially the transition to electric propulsion systems and decoupled chassis actuators offer completely new opportunities of dynamics control and manipulation. This paper presents an approach for integrated chassis and vehicle motion control in (battery) electric vehicle applications by using new and innovative controllers as well as mechatronic chassis systems. In several experiments on public roads with a fully instrumented vehicle demonstrator, that features in-wheel based rear-wheel drive and a hybrid brake-by-wire-system, the proposed control is tested under real environmental and traffic conditions with respect to aspects like energy
Heydrich, Marius, Mitsching, Thomas, Ivanov, Valentin
Design and Performance Evaluation of a Dust Contamination Simulation Test Apparatus for Automotive Cameras2026-01-0059To be published on 04/07/2026
In the era of Software-Defined Vehicles (SDVs), sensor integration has become increasingly prevalent, enabling advanced features such as autonomous driving and driver assistance systems. However, contamination from road dust and muddy water poses significant risks to the performance of vehicle camera sensors. Manual methods of applying dust for testing sensor durability are subject to inconsistencies and human error, potentially undermining the validity of test results. To address this, we developed an automated dust deposition apparatus specifically designed for automotive camera systems. This device enables precise and repeatable control over dust application, thereby enhancing the reliability and efficiency of the testing process. The dust contamination simulation apparatus leverages programmable parameters to consistently reproduce various environmental scenarios encountered in real-world driving conditions. Performance evaluations demonstrated that the system achieves uniform dust
Jinhyeok, Gong
Backward Fuzzy Driving Control for 6×4 Off-Road Vehicles2026-01-0148To be published on 04/07/2026
Offroad autonomous vehicle systems must be able to operate across unstructured and variable terrain while avoiding obstacles. This presents significant challenges in vehicle and control system design, especially for less conventional platforms such as 6x4 vehicles. While forward driving autonomy has developed and matured in recent years, effective reverse navigation remains an under-explored area of vehicle co-design. Reversing 6x4 vehicles have limited rear steering authority, an extended wheelbase, and asymmetric traction, which introduce complex dynamics into any control system that is used. To address this need, a robust and experimentally validated fuzzy logic control architecture for 6x4 reverse navigation was developed during the course of this project. This architecture incorporates both near-field and long-range path data with adaptive outputs controlling steering and velocity based on a rule base that covers the whole vehicle state space. This method has low computational
Dekhterman, Sam, Patterson, Albert, Sreenivas PhD, Ramavarapu, Norris, William, Soylemezoglu PhD, Ahmet, Nottage PhD, Dustin
Mitigation of Sensor-Level Cyber-Physical Attacks on Electric Vehicle Powertrains: A Simulation-Based Study2026-01-0091To be published on 04/07/2026
Electric vehicles (EVs) rely extensively on sensor feedback for safe and efficient powertrain operation. However, this dependency introduces cyber-physical vulnerabilities, especially when sensor signals are maliciously manipulated. This paper presents a simulation-based investigation into sensor-level cyberattacks on a mid-sized EV powertrain model developed in MATLAB/Simulink. The study quantifies mechanical consequences and evaluates mitigation strategies to enhance system resilience. Four representative attack scenarios were simulated. Speed sensor spoofing led the controller to misinterpret vehicle velocity, causing a 41% overshoot beyond the 50 km/h setpoint. False data injection into torque/current sensors triggered an unintended torque surge of approximately 20%, resulting in inverter current saturation within 2 seconds. Battery temperature spoofing delayed thermal protection, allowing a deviation of 1.5 °C/min beyond safe operating limits. A hybrid attack combining frozen
Tariq, Usama, Sahandabadi, Sahereh, Dianat, Ali
Vehicle Health Monitoring and Failure Prognosis through Edge-Based Component Wear Tracking2026-01-0094To be published on 04/07/2026
Traditional vehicle maintenance has relied primarily on mileage-based schedules and periodic visual inspections, approaches that often fail to account for variations in driving conditions, component quality, and usage patterns. These conventional methods typically result in either unnecessary premature replacements or unexpected component failures, leading to increased operating costs and unplanned downtime. Reactive maintenance strategies prove particularly problematic for critical wear components like clutch assemblies, brake systems, and suspension parts where undetected degradation can cause secondary damage. This paper presents an advanced monitoring system that shifts from scheduled maintenance to actual condition-based servicing through real-time wear measurement. The solution implements a network of distributed sensors that directly track critical parameters: ultrasonic measurement of clutch plate thickness, resistive wear sensors for brake pads, linear potentiometers for
Saraswat, Shubham, Vishe, Prashant
Virtual Sensor Development for Real-Time Estimation of Transient NOx Emissions for Internal Combustion Engine2026-01-0370To be published on 04/07/2026
Accurately measuring NOx emissions under transient engine conditions is becoming increasingly important with upcoming Euro 7 and EPA 2027 regulations. Traditional physical sensors often struggle with cost and response time, especially with aging of sensors in dynamic operation. This paper introduces a machine-learning–based virtual NOx sensor that can provide real-time emission estimates while reducing reliance on hardware sensors. The approach uses multiple machine-learning methods (Random Forest, Bootstrap Aggregating, Adaptive Boosting, Gradient Boosting, Extreme Gradient Boosting) and selected best one to establish correlations between engine operating parameters, measured steady-state data, and transient duty cycle NOx emissions. Validation across different duty cycles has shown strong alignment with physical sensor readings, with R² values above 0.9995 for known data sets and above 0.9534 for unseen conditions. The model needs to be trained with larger training samples to further
Kumar, Chandan, Dahodwala, Mufaddel, Thawrani, Kiran
In-Situ Raman Measurements of Fuel Dilution of Lubricant Films in a Direct-Injection Spark-Ignition Engine2026-01-0355To be published on 04/07/2026
To measure the fuel proportion within the lubricant film, an in-situ Raman spectroscopy technique was employed in a specially modified single-cylinder direct-injection spark-ignition engine. The engine block was engineered for optical access with a fused silica window, enabling a focused laser beam to probe the lubricant film on the engine liner under motoring conditions. The lubricant used was GTL8 base oil with ZDDP additive, and iso-octane was injected as a model fuel to study fuel-lubricant mixing. A calibration curve was established by recording Raman spectra of known mixtures of GTL8 oil and iso-octane. The Raman intensity ratio of the iso-octane peak to the oil peak was used as a quantitative indicator of fuel concentration. During engine operation, Raman spectra were acquired in real time, on a cycle-by-cycle basis, through the optical window. Upon iso-octane injection, its characteristic Raman peak appeared in the spectrum, and the intensity ratio was referenced against the
Bolle, Bastien, Augoye, Kobi, Wong, Janet, Aleiferis, Pavlos, Hall, Jonathan, Bassett, Mike, Cracknell, Roger
Sensor Location Study for Non-Intrusive Start of Combustion (SOC) Detection Using Engine Block Vibration2026-01-0288To be published on 04/07/2026
This study investigates the impact of sensor location on accelerometer-based sensing of combustion phasing for compression-ignition engines. Ten accelerometer locations were studied on a light-duty compression-ignition engine for a set of conditions varied in engine load, speed, injection timing and injection strategy. Start of combustion (SOC) was identified from filtered acceleration signals. Each location was assessed using both signal quality metrics, including magnitude squared coherence (MSC) with in-cylinder pressure, passband intensity, signal to noise ratio, and spectrogram shape, as well as SOC outcome metrics such as detection success rate. Results demonstrate that the mounting location has a significant impact on the ability to extract relevant combustion phasing information from the accelerometer signal. Sensors mounted on the front face of the engine produced the strongest signals for an individual cylinder. For multi-cylinder sensing, a side mounted location delivered
Hegge, Graydon, Hanson, Reed, Kim, Kenneth, Rothamer, David
Curvature-Based End-to-End Autonomous Vehicle Path Planning at Intersections2026-01-0045To be published on 04/07/2026
Autonomous vehicle navigation requires accurate prediction of driving path curvature to ensure smooth and safe trajectory planning. This paper presents an end-to-end approach to curvature prediction using deep neural networks trained on real-world driving data. We develop a comprehensive neural network architecture that directly maps high-dimensional sensor inputs to curvature predictions, eliminating the need for intermediate feature engineering steps. The model processes multi-modal inputs including vision features, vehicle state parameters, and environmental context through a deep learning pipeline. Our end-to-end approach demonstrates the feasibility of learning complex driving behaviors directly from raw sensor data, providing a more robust and generalization solution compared to traditional rule-based methods. The neural network architecture incorporates dropout regularization and adaptive learning rate scheduling to ensure stable training and optimal performance. Results show
Hajnorouzali, Yasaman, Wang, Hanchen, Li, Taozhe, Burch, Collin, Lee, Victoria, Tan, Lin, Arjmandzadeh, Ziba, Xu, Bin
BEV drivetrain parameters sensitivity for efficient and effective active damping controls modeling2026-01-0004To be published on 04/07/2026
Effective active damping control is critical for Battery Electric Vehicle drive quality. Central to this control is open loop frequency response function between actuator (motor torque) and response (motor speed). While many driveline parameters influence the system dynamics, sensitivity analysis reveals that only a few of them significantly shape the resonance frequency and amplitude of crucial low frequency driveline modes. In this study, an orthogonal array-based sensitivity analysis is conducted and validated using 1D simulation tool as Amesim. The results show that identifying the most influential parameters enables meaningful model simplification without loss of accuracy, guiding quick and efficient modelling to help design control system. This approach provides engineers with a practical framework to focus on critical variables of driveline torsional system, reduce model complexity, and implement effective active damping controls strategies.
Sharma, Pranjal, Kolluri, Murali Mohan, Lin, Chihang
Bias and uncertainty in the time, position, and speed data of consumer-grade GPS devices2026-01-0544To be published on 04/07/2026
The goal of this study is to quantify the accuracy and uncertainty of position and speed measurements acquired by a wide range of consumer-grade GPS-enabled devices while road cycling. We acquired position and speed data simultaneously from 13 consumer devices (e.g., phones, watches, bicycle computers) at their maximum sampling rate (typically 1 Hz) during 10 hours (thirty 20 minute sessions) and 150 km of road cycling in a suburban environment. The position data from these devices were compared to real-time kinematic (RTK) data acquired using a differential GPS system and the speed data from these devices were compared to speed data acquired with high-resolution wheel rotation sensors (23,040 pulses per revolution) synchronized with the RTK data. Based on these comparisons, we generated probability distributions for the errors in the position and speed measured by each of the consumer devices. This study provides foundational data needed to quantify the accuracy and uncertainty across
Booth, Gabrielle R., Mitchell, Alan L., Siegmund, Gunter P.
Introduction to Catesby Aero Research Facility, CARF, the coast-down tunnel proving ground.2026-01-0611To be published on 04/07/2026
This paper reports on the Catesby Aero Research Facility (CARF), which began commercial use in 2019, and provides an overview of the facility and related technologies, particularly details on the vehicle-mounted component force measurement devices. CARF is a proving ground that was renovated from a former railway tunnel approximately 2.74km long and is now covered with high-quality tarmac. The road surface quality was designed to be at least as good as that of SUBARU's proving ground, and the standards were achieved using British construction technology. The course is almost straight, but there is a slight incline. The course specifications are: blockage 40m2, road width 6m (maximum 8.4m), flatness σ<0.5mm, and gradient 0.57%.In particular, compared to outdoor coastdown trucks, its overall length allows for continuous measurement right up to the stop, giving it a significant advantage in repeatability.At the same time, Subaru's newly developed six-component force sensor built into the
Shimoyama, Hiroshi
Securing the AI-Driven Vehicle: A Hardware-Based Security Framework for Scalable, Trustworthy Autonomy2026-01-0085To be published on 04/07/2026
Autonomous driving technology in modern vehicles marks a pivotal evolution in transportation, but it may also introduce system-level vulnerabilities that span from tampering with sensors and interfaces to compromising compute units and communication links. This paper proposes a unified, layered hardware security architecture for AI-equipped automated vehicles. Based on current automotive Ethernet and zonal architectures, it provides end-to-end trust using hardware interface security, accelerated-cryptography, and SRAM PUF-based key provisioning. All security primitives are anchored to a hardware root of trust, delivering cryptographic identity, secure boot enforcement, and trusted key storage across the entire vehicle lifecycle. Our architectural assumptions follow the direction ISO 26262, ISO/SAE 21434 and AI development mandates for next-generation SAE Level 3+ vehicles using zonal Ethernet backbones, Time-Sensitive Networking (TSN), and heterogeneous compute islands (e.g., vision
C Suriyanarayanan, Pav, Iacob, Radu
Development of technology to distinguish contaminants using LiDAR near-field point cloud based on real-field data2026-01-0020To be published on 04/07/2026
Sensing technologies are essential to autonomous driving, enabling environmental perception and supporting navigation and its decision-making. However, most publicly available datasets are collected under perfect weather conditions and fail to capture the challenges of real-world environments. To address this gap, we built a large-scale dataset from extensive driving campaigns across diverse regions of the United States, covering conditions such as rain, snow, dust, clear weather and anti-ice material affects. Data were acquired through a multimodal sensing devices - including perception cameras, LiDAR, infrared sensors, and external monitoring systems - providing a comprehensive representation of the vehicle's operational environment. Building on this dataset, our study focuses on LiDAR data, emphasizing contaminant classification as a critical requirement for sensor-cleaning strategies essential to reliable autonomous driving. Using raw LiDAR signals collected over 22,000km of
KIM, HUNJAE
Development of A Tire Blowout Experimental Platform for Dynamics and Control Validation2026-01-0202To be published on 04/07/2026
Tires are critical to vehicle dynamics, transmitting traction, braking, and cornering forces to the road. A tire blowout, the sudden and rapid loss of inflation pressure due to puncture or structural failure, can cause severe instability, rollover, or collisions. Understanding vehicle response during blowout events is essential for developing robust safety systems and control strategies. Earlier developed simulation models are used to study and understand vehicle behavior during blowouts, but there is a lack of on-road testing platforms to validate these models experimentally. A custom-built blowout device integrated with a data acquisition system has been developed to address this gap. It consists of multiple solenoid valves mounted on the wheel surface and powered by a 12V supply. All valves are triggered at the same time using an RF remote, producing rapid and synchronized deflation. An Arduino-based actuation system is being developed for individual valve actuation and custom
KANTHALA, Maha Vishnu Vardhan Reddy, Krishnakumar, Ashwin, Lin, Wen-Chiao, Chen, Yan
The Enduring Value of Highly Optimized, Non-Standardized Systems26AERD03_033/1/2026
The roles of aerospace and defense engineers have profoundly changed. Systems integrators and acquisition programs require “standardized openness” while also wishing for boxes that take up less space, weight, and power. Despite the push towards Modular Open Systems Approach (MOSA), Sensor Open Systems Architecture (SOSA), and similar open standards, there are still opportunities to use non-standardized, small form factor (SFF) designs. As outlined in the project examples below, a purpose-built SFF module can address technical system requirements better than any current approach focused on open standards.
New MEMS Modulator Offers Significant Advancements in Optical EfficiencyTBMG-547123/1/2026
A new Microelectromechanical system (MEMS) grating modulator has been developed, offering significant advancements in optical efficiency and scalability for communication systems. By integrating a tunable sinusoidal grating with broadside-constrained continuous ribbons, a large-scale aperture of 30 × 30 mm is achieved and supports high-speed modulation up to 250 kHz.
A Thin-Film Flexible Temperature-Strain Multimodal Sensor for Lithium-Ion Battery Monitoring Based of Laser Direct Writing2026-01-70262/27/2026
Multimodal sensors, capable of simultaneously acquiring multiple physical or chemical signals, have shown broad application potential in fields such as health monitoring, soft robotics, and energy systems. However, current multimodal sensors often suffer from complex fabrication processes and signal decoupling challenges, which limit their practical deployment. To address these issues, this work presents a thin-film temperature–strain multimodal sensor (FTSMS) fabricated via laser processing. The temperature-sensing unit, based on the Seebeck effect, achieves a sensitivity of 9.08 μV/°C, while the strain-sensing unit, utilizing BaTiO₃/AlN@PDMS as the sensitive layer, exhibits a gauge factor (GF) of 43.2. By integrating distinct sensing mechanisms (thermovoltage for temperature and capacitance change for strain), the FTSMS enables self-decoupled measurements over 20–90 °C. Applied in LIB monitoring, it successfully captures real-time temperature and strain variations during charge
Wang, Ziwei, Li, Zhenglin, Gao, Yang, Xuan, Fuzhen
Failure Modes for High-Lift Actuation Load PathsAIR7061 (Current)2/17/2026
This SAE Aerospace Information Report provides examples of single failure modes for components used in fixed-wing, high-lift actuation systems’ load paths, as well as the typical hazards posed by those failures at the aircraft level.
A-6B3 Electro-Mechanical Actuation Committee
Multi-Storey AI Based Parking System2026-28-01292/12/2026
This paper presents a novel AI-based parking management system designed to enhance efficiency, reduce manual intervention, and optimize operational costs in modern parking facilities. By integrating computer vision with infrared (IR) sensors, the system continuously monitors parking areas in real time, accurately detecting vehicle occupancy and dynamically updating the space availability. The hybrid approach minimizes reliance on conventional sensors, improving accuracy and environmental robustness. Additional features include intelligent navigation assistance guiding drivers to available spots and integrated video surveillance for enhanced security through AI-driven suspicious activity detection. The user interface provides real-time updates ensuring a seamless and convenient parking experience. Overall, this system offers a comprehensive solution that advances parking technology through automation, real-time monitoring, and secure, user-friendly operation.
N, Kalaiarasi, Gupta, Shivansh, Hajarnis, Mihir, Anand, Vikas
Steering Automation for Lane Keep Assistance2026-28-01172/12/2026
The design of advanced driver-assistance systems (ADAS) is essential to improve the safety and autonomy of rear wheel driven four-wheel vehicle in harsh conditions. This work introduces the design and development of a steering automation system for Lane Keep Assistance (LKA) in an rear wheel driven four-wheel 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
A R, Arundas, Sadique, Anwar, Rafeek, Aayisha
Miner’s Safety Bot: An ESP32-Based Autonomous Mobile Mine Safety Monitoring System2026-28-01162/12/2026
Mining operations are important to industrial growth, but they expose the mining workers to risk including hazardous gases, elevated ambient temperatures, and dynamic structural instabilities within underground environments. Safety systems in the past, typically based on fixed sensor networks or manual patrols, fall short in accurate hazard detection amidst shifting mine conditions. The proposed project Miner's Safety Bot advanced this paradigm by leveraging an ESP 32 microcontroller as a mobile platform that integrates gas sensing, thermal monitoring, visual inspection and autonomous obstacle avoidance. The system incorporates MQ7 semiconductor gas sensor to monitor real time carbon monoxide (CO), offering detection range from 5 to 2000 ppm with accuracy of 5 ppm. Temperature and humidity are monitored through DHT11 digital sensor, calibrated to ensure reliability across the harsh microclimates in mines. Navigation and autonomous movement are enabled by Ultrasonic Sensor (HC-SR04
D, Suchitra, D, Anitha, Muthukumaran, Balasubramaniam, Mohanraj, Siddharth, Subash Chandra Bose, Rohan
Development of Advanced Rider Assistance System (ARAS) for Electric Motorcycles: A Level-1 Collision Avoidance and Emergency Braking Prototype Using Ultrasonic Sensors2026-28-01182/12/2026
This paper presents the design, development, and validation of an Advanced Rider Assistance System (ARAS) tailored for electric motorcycles, with a specific focus on a Level-1 collision-avoidance and emergency-braking prototype employing ultrasonic sensing. The study is motivated by the disproportionately high accident exposure of two-wheeler riders and the slow adoption of ARAS technologies relative to the well-established Advanced Driver Assistance Systems (ADAS) in passenger vehicles. The proposed system utilizes front and rear ultrasonic sensors operating at 40 kHz, offering a measurement range of 2 cm to 4 m with ±1% accuracy, and maintaining reliable performance at motorcycle lean angles of up to 30°. Sensor data are processed using an STM32-series microcontroller running a real-time collision-risk estimation algorithm based on obstacle distance and relative velocity. A configurable safety threshold (typically 3 m) initiates a hierarchical warning strategy comprising visual
Deepan Kumar, Sadhasivam, Karu, Ragupathy, Karthick, K N, R, Vishnu Ramesh Kumar, Kumar, V, Manojkumar, R, M, Karthick, M, Rishab
IoT-Enabled Cloud-Integrated Smart Parking System with Real-Time Monitoring and AI-Based Space Optimization for Next-Gen Mobility2026-28-01132/12/2026
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, S, Manikandan, R, Jamuna, L, Rishi Kannan
Automotive Engineering: February 202626AUTP022/5/2026
Qualcomm expands partnerships for more Snapdragons Bosch is ready to bring AI to your vehicle, likely to still be ICE-powered in 2035 Etching for a greener future How chemical etching is helping enable next-gen automotive technologies. Rewriting the engineer's playbook: What OEMs must do to spin the AI flywheel The automotive industry's future hinges on a new AI-native engineering workflow that accelerates iteration, strengthens system thinking, and preserves human judgment. From redundancy to resilience: building smarter safety systems through sensor collaboration ADAS sensor fusion can provide improved and required safety technologies by rethinking the best strategy for allowing a car to sense the world. Open Safety is the shortcut to safer ADAS/AD An open safety stack, shared scenarios, benchmarks, and core validation tools can speed certification, reduce duplicated V&V and build public trust while preserving vendor differentiation. Editorial Robots, physical AI shift the focus at
Combining 3D Embroidery Techniques with Machine Learning for Fabric-Based Touch SensorsTBMG-545522/1/2026
A new study from NC State University combines three-dimensional embroidery techniques with machine learning to create a fabric-based sensor that can control electronic devices through touch.
PRODUCT BRIEFS26TOFHP02_102/1/2026
Human Detection Capacity of Vehicle Front Sonar Sensors in Light and Small Passenger Cars and Minivan2025-22-00091/22/2026
Sonar sensor systems have been developed to prevent collisions between vehicles and surrounding objects by employing ultrasonic sensors mounted at the front of the vehicle. These systems warn drivers when nearby obstacles are detected. However, relatively few studies have examined the capacity of sonar to detect humans. This study aims to clarify the human detection capacity of front sonar sensors installed in two light passenger cars (LPC-I and LPC-II), one small passenger car (SPC), and one minivan (MNV). The LPC-I, SPC, and MNV were equipped with center and corner sensors, whereas the LPC-II had only corner sensors. Three volunteers—a child, an adult female, and an adult male—participated in the study. Human detectability was assessed using the “maximum detection distance ratio,” defined as the ratio of the maximum detection distance for a volunteer to that for a standard pipe. The results showed that both the center and corner sensors consistently detected front- and side-facing
Matsui, Yasuhiro, Oikawa, Shoko
Curvature-Continuous Trajectory Refinement for Autonomous Vehicles Using a Pure Pursuit Based Path Smoothing Framework2026-26-01351/16/2026
Path planning is a key element of autonomous vehicle navigation, allowing vehicles to calculate feasible paths in challenging environments for applications like automated parking and low speed autonomous driving. Algorithms such as Hybrid A*, Reeds-Shepp, and Dubins paths are widely used and can generate collision-free paths but tend to create curvature discontinuities. These discontinuities result in sudden steering transitions, which create control instabilities, higher mechanical stress, and lower passenger comfort. To overcome these issues, this paper suggests a path-smoothing technique based on the pure-pursuit algorithm to produce smoothed curve paths appropriate for real-world driving. This method utilizes the practical approach of the original path, but removes sudden transitions that destabilize control. By ensuring smooth curvature, the vehicle undergoes fewer jerky steering actions, improved energy efficiency, less actuator wear, and improved high-speed tracking. This paper
S, Shriniyathi, A, Josana, Anto Edwin J, Joel, T, Akshayaa, M, Senthil Vel, Kumar, Vimal
Comprehensive Evaluation of Bolster Behaviour: Field Data Insights for Design Modifications2026-26-04971/16/2026
Bogie suspension systems are becoming increasingly popular in tipper vehicles to enhance their performance and durability, especially in demanding environments like construction and mining areas [1]. Bolsters contribute significantly to the overall performance and durability of the bogie suspension systems of tipper vehicles by evenly distributing the loads across the whole suspension system. They act as shock absorbers and negate the impact caused by the rough terrains and heavy loads, thereby reducing stress on individual components and maintaining the structural integrity of the vehicle. Bolsters also help in improving the ride comfort and to maintain the position of the suspension system [2]. This study focuses on the comprehensive testing and evaluation of bolsters to understand their modes and displacement data derived from field data. The primary objective is to analyse the performance and behaviour of bolsters under various operational conditions. Critical manners of
V Dhage, Yogesh, Kolage, Vikas
Automotive Cybersecurity: Safeguarding Connected and Autonomous Mobility2026-26-06291/16/2026
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
A Review on ‘Sensor Technologies’, its Application, Regulatory Standards & Emerging Trend Towards Safe Hydrogen Economy2026-26-01111/16/2026
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
Development of a Seamless Selectively Elevated Fabric Switch for Intuitive and Sustainable Automotive Interior Interfaces2026-26-05961/16/2026
This technology solves a long-standing ergonomic and aesthetic problem in automotive and consumer interface design, as the use of mechanical switches disrupts the clean look of modern interiors and tends to attract dust and wear. Currently available technologies, such as capacitive touch buttons and mechanical push switches, do not provide the corresponding tactile feedback or clear indication of touch, and usually contain visible openings that interrupt the design flow. Moreover, traditional switches are made up of multiple built-in components, which results in complicated construction and difficult maintenance. To address these drawbacks, we propose a Seamlessly Integrated, Selectively Elevated Fabric Switch that remains flush with the surface when not in use and automatically rises to form a tactile interface when required. The system is a multi-layer construction consisting of an outer fabric upholstery layer, a tactile actuation membrane, and a smart electromagnetic actuator layer
Mohunta, Sanjay, Panchal, Girish, Puthran, Shaunak
Robust Validation of Rotary Switch with TFT Display in Hardware in Loop Simulation2026-26-05401/16/2026
Modern automotive systems are increasingly integrating advanced human-machine interfaces, including TFT displays, to enhance driver experience and functionality. Ensuring the reliability of these systems under diverse operating conditions is critical, especially given their role in vehicle control. This paper presents a Hardware-in-the-Loop (HIL) testing methodology for validation of rotary switch with TFT display. The HIL setup simulates real-world vehicle conditions, including CAN communication, power fluctuations and user interactions, enabling early detection of potential failure modes such as display flickering or communication loss. The results demonstrate improved robustness and reliability of the gear selection switch, supporting its deployment across multiple vehicle platforms.
Bhuyan, Anurag, Jahagirdar, Shweta, Khandekar, Dhiraj
EV Powertrain Systems Diagnostics & Prognostics Utilizing AI & ML (LLM) Based Approach2026-26-06641/16/2026
This study introduces a novel Large Language Model (LLM)-driven approach for comprehensive diagnosis and prognostics of vehicle faults, leveraging Diagnostic Trouble Codes (DTCs) in line with industry-standard automation protocols. The proposed model asks for significant advancement in automotive diagnostics by reasoning through the root causes behind the fault codes given by DTC document to enhance fault interpretability and maintenance efficiency, primarily for the technician and in few cases, the vehicle owner. Here LLM is trained on vehicle specific service manuals, sensor datasets, historical fault logs, and Original Equipment Manufacturer (OEM)-specific DTC definitions, which leads to context-aware understanding of the vehicle situation and correlation of incoming faults. Approach validation has been done using field level real-world vehicle dataset for different running scenarios, demonstrating model’s ability to detect complex fault chains and successfully predicting the
Pandey, Suchit, Joshi, Pawan, Kondhare, Manish, CH, Sri Ram, Gajbhiye, Abhishek, S, Adm Akhinlal
Driving Thermal Intelligence – Pioneering Digital Twin-Driven Hardware-In-Loop for Smart Climate Control Modules2026-26-03801/16/2026
Thermal comfort is increasingly recognized as a vital component of the in-vehicle user experience, influencing both occupant satisfaction and perceived vehicle quality. At the core of this functionality is the Climate Control Module (CCM), a dedicated embedded Electronic Control Unit (ECU) within automotive HVAC system [6]. The CCM orchestrates temperature regulation, airflow distribution, and dynamic environmental adaptation based on sensor inputs and user preferences. This paper introduces a comprehensive Hardware-in-the-Loop (HIL) [3] testing framework to validate CCM performance under realistic and repeatable conditions. The framework eliminates the dependencies on physical input devices—such as the Climate Control Head (CCH) and Infotainment Head Unit (HU)—by implementing virtual interfaces using real-time controller, and Dynamic System modelling framework for plant models. These virtual components replicate the behaviour of physical systems, enabling closed loop testing with high
More, Shweta, Shinde, Vivek, Turankar, Darshana, Patel, Dafiya, Gosavi, Santosh, Ghanwat, Hemant
Computer Vision Based Driver Health and Wellness Monitoring System: A) Fatigue Detection, B) Emotional Wellbeing2026-26-06391/16/2026
Computer vision has evolved from a supportive driver-assistance tool into a core technology for intelligent, non-intrusive occupant health monitoring in modern vehicles. Leveraging deep learning, edge optimization, and adaptive image processing, this work presents a dual-module Driver Health and Wellness Monitoring System that simultaneously performs fatigue detection and emotional wellbeing assessment using existing in-cabin RGB cameras without requiring additional sensors or intrusive wearables. The fatigue module employs MediaPipe-based facial and skeletal landmark analysis to track Eye Aspect Ratio (EAR), Mouth Aspect Ratio (MAR), head posture, and gaze dynamics, detecting early drowsiness and postural deviations. Adaptive, driver-specific thresholds combined with CAN-bus data fusion minimize false positives, achieving over 92% detection accuracy even under variable lighting and demographics. The emotional wellbeing module analyzes micro-expressions and facial action units to
Iqbal, Shoaib, Imteyaz, Shahma
Side Crash Pressure Sensor Response Prediction: CPM Approach2026-26-04131/16/2026
Side crashes are generally hazardous because there is no room for large deformation to protect an occupant from the crash forces. A crucial point in side impacts is the rapid intrusion of the side structure into the passenger compartment which need sufficient space between occupants and door trim to enable a proper unfolding of the side airbag. This problem can be alleviated by using the rising air pressure inside the door as an additional input for crash sensing. With improvements in the crash sensor technology, pressure sensors that detect pressure changes in door cavities have been developed recently for vehicle crash safety applications. The crash pulses recorded by the acceleration based crash sensors usually exhibit high frequency and noisy responses. The data obtained from the pressure sensors exhibit lower frequency and less noisy responses. Due to its ability to discriminate crash severities and allow the restraint devices to deploy earlier, the pressure sensor technology has
Bhagat, Milind, Narale, Naganath, Mahajan, Ashutosh, Wayal, Virendra, Jadhav, Swapnil
Automated Evaluation of Drive File Simulation Accuracy2026-26-05281/16/2026
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 achieved 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 develop 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 is having thousands of drive files based on road-load mix and actuator settings. This application helped us in significantly optimizing the simulation workflow by reducing
Soni, Yash, Katake, Vrishali, Mullapudi, Dattatreyudu, Chaskar, Mithun
Novel Approach on Material Characterization Testing of Various Wiring Harness2026-26-05481/16/2026
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 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 property has a crucial 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 during product development. This study explains the novel method of Testing the Cables and Bundles
Beesetti, Siva, Kalkala Balakrishna, Prasad, James Aricatt, John, Shah, Dipam, Tas, Onur, Krogmann, Stephan
Development of Advanced Thermoplastic Elastomeric Mat and Its Study on Thermal Performance of Wireless Charger System2026-26-02831/16/2026
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
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