Browse Topic: Medical, health, and wellness

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Quasi-Static Head Restraint Pull-Tests to Assess Retention Performance: Maximum Load and Damage Characteristic2026-01-0564To be published on 04/07/2026
Head restraint requirements and designs have evolved to minimize the delay in head support and reduce differential loading in the neck. As a result, head restraints have become bigger and more angled forward, sitting, closer to the occupant’s head. Head restraints separation from seatbacks are sometimes observed in the field. Are head restraint detachments resulting from occupant comfort issues prior to the crash, occupant loading during the crash or were they removed by emergency personnel for extrication? Understanding the retention strength of head restraints and the type of evidence left behind by a forced removal may help researchers resolve the question of how a head restraint may be found post-crash separated from the seat. Quasistatic pull tests were conducted to measure vertical retention capabilities, compare vertical adjustment and release mechanisms, and document deformation and damage. Eighteen different front seat head restraint designs were evaluated. The model years
Parenteau, Chantal, Burnett, Roger, Davidson, Russell
Occupant and Seat Responses in Various Rear Impact Conditions: Focus on Head-to-Head Restraint Interactions2026-01-0565To be published on 04/07/2026
Head restraint requirements and designs have evolved to minimize the delay in head support and reduce differential loading in the neck. As a result, they have become bigger, closer to the occupant’s head, and angled forward relative to the seat back. Head restraints have been found missing or detached in the field; they may be removed pre-crash due to occupant comfort issues, or post-crash for better accessibility during extrication. Additionally, although rare, head restraints may become detached in severe rear impacts due to occupant loading. To better understand occupant-to-head restraint dynamic interactions, nine rear sled tests were conducted. The test conditions were selected to represent worst case severe loading scenarios. An instrumented 50th Hybrid III ATD (Anthropomorphic Test Device) was lap-shoulder belted on a right-front seat. The neck was equipped with a bracket and lower neck load cell designed for rear impacts. Three series of sled tests were performed wherein the
Parenteau, Chantal, Burnett, Roger, Davidson, Russell
Development and Application of SAE J3260 & J3290 Recommended Practice for Minimizing Spread of Infections in Motor Vehicles2026-01-0128To be published on 04/07/2026
In response to COVID pandemic, and at the persistent urging of the late Ward Atkinson, long-time SAE leader in Interior Climate Control Committees, the SAE Cabin Disinfection Practices Committee was formed in May 2021. Towards that end, two SAE J-standards have been produced by this committee: SAE J3260, Identification of Acceptable Cleaning and Disinfection Products for Vehicle Interior Surfaces and Exterior Touch Points, and SAE J3290, Selection and Use of Technologies and Methods for Vehicle Cabin Air Disinfection. This SAE paper will unpack the background and application of these J-Standards to minimize the probability of spreading of infection during the operation of motor vehicles while in normal operation, before and after vehicle servicing, and when in use as paid-for-hire operation - for both ‘normal’ environmental conditions, and during times of pandemic emergencies. Additionally, recent advances in air and surface disinfection technologies—including methods relevant to SARS
Schaeber, Steven, Mathur, Gursaran, Taylor, Dwayne
Machine Learning based Meta-Analysis of IIHS Moderate Overlap Frontal Crash Test for Rear Seat Occupant Safety Performance2026-01-0579To be published on 04/07/2026
A machine learning (ML)-based meta-analysis was conducted to evaluate rear seat occupant safety performance in the Insurance Institute for Highway Safety (IIHS) Moderate Overlap Frontal (MOF) 2.0 crash test. ML models were trained on historical IIHS crash test data to predict rear passenger injury metrics using vehicle architecture, restraint system characteristics, crash pulse parameters, and vehicle kinematics as input features. The models demonstrated high predictive accuracy and were subsequently used in a Sobol sensitivity analysis to identify critical design parameters influencing injury outcomes. The analysis revealed that rear passenger injury metrics were most sensitive to restraint system parameters. Specifically, crash pulse magnitude was the dominant factor for head injury metrics, pretensioner activation time for neck tension force, and lap belt force for the Neck Injury Criterion (Nij). For chest-related metrics—sternum deflection, dynamic belt position, and maximum belt
Lalwala, Mitesh, Kim, Wonhee, Furton, Lisa, Song, Jay
A Helical Compression Spring Fracture under Impact Velocity in Pump Operation by Theoretical Study and FEA2026-01-0271To be published on 04/07/2026
Helical compression springs have been used widely in various industries from automotive, aerospace and heavy-duty industries to electronics and medical devices. In the automotive industry, they appear in many places such as suspension, valvetrain, etc., especially in the discharge check valve of Gasoline Direct Injection (GDI) pump, which is the subject of study due to a recent fracture in lab testing. A theoretical study is conducted first to establish equation governing spring dynamic motion under impact velocity, which can be in high magnitude with surging shock wave along spring axis. A new spring shock wave equation is developed for spring axial motion coupled with coil torsional effect. This newly derived shock wave equation has a broad term than the classic spring formula found in engineering book. In the paper, it proves that the classic spring shock wave equation is only a special case for the new general wave equation discovered. Also, a formula on spring shock wave
Pang, Michael L., GUNTURU, SRINU, Norkin, Eugene
Optimization of Active–Passive Integrated Evaluation Weighting for Pedestrian Protection2026-01-0577To be published on 04/07/2026
Pedestrians, as the most vulnerable road users, largely determine the severity of traffic accidents through the extent of their injuries. Traditional vehicle safety evaluations have primarily emphasized passive safety. However, with the widespread implementation of active safety technologies such as Automatic Emergency Braking (AEB), passive-only assessments no longer adequately reflect a vehicle’s true pedestrian protection performance.This study employed finite element models of a sedan and an SUV to analyze changes in pedestrian head and lower limb injury metrics before and after AEB intervention, thereby quantifying the associated injury-mitigation benefits. The results show that AEB reduced the maximum head injury value (HIC15) by about 50%, lowering the proportion of severe head injuries from 0.217 to 0.118. Conversely, braking-induced pitch effects increased the proportions of severe femur and tibia bending moment injuries to 0.235 and 0.294, respectively, making them higher
shi, Xinxin, YE, BIN, Liu, Yu, Zhan, Zhenfei, Sun, Bowen, Zhao, yuanyi, zhu, lei
Effects of Child Anthropometry, Seatback Angle, Seat Rotation Angle, Seatbelt Force Limiting, and Collision Type on Injury Risk of Child Occupants in Highly Automated Vehicles2026-01-0570To be published on 04/07/2026
This study aimed to evaluate the influence of child anthropometry, seat posture (recline and rotation), seatbelt force limiting, and frontal collision scenarios on the kinematic response and injury risk to children in highly automated vehicles. The TUST IBMs 6YO-O model was conducted the frontal collisions in sled tests. This simulation matrix includes five percentiles six-year-old occupants (P3, P25, P50, P75, and P97), three seatback angles (20°, 30°, and 45°), four seat rotation angles (0°, 90°, 180°, and 270°), three seatbelt force limiting (2.6 kN, 3.6 kN, and 4.6 kN), and three collision types. Injury risks were assessed including the child occupant's head, neck, chest/abdomen, and lumbar region in each simulation (n=540). The results indicate that the child anthropometry, the seatback angle, and the seat rotation angle have a significant influence on the motion responses. Statistically significant differences between all the groups within each independent variable category were
Wang, Yanxin, Zhao, Hongqian, Li, Haiyan, He, Lijuan, Cui, Shihai, Lv, Wenle
Use inertial sliding of reclined seat to enhance occupant retention under rear-end crash2026-01-0563To be published on 04/07/2026
Smart cabin of autonomous vehicle may lead more passengers to recline their seat for comfort. However, reclined seat is disadvantageous for holding occupant in seat when vehicle is subjected to rear-end crash. Under severe rear-end crash and large reclining angle, the backward inertia could completely throw occupant out of seat. Or, even if occupant body can be restrained well by seatbelt, the occupant head could slide out of the head restraint area. Any of these situations may potentially cause severe injuries. To address this safety concern, we developed a sliding seat system designed to enhance occupant retention. Activated by impact inertia from rear-end collision, the system allows the seat sliding backward along its track in a controlled manner, and the sliding stroke is accompanied by a restraint force and absorbs some amount of kinetic energy during the sliding. Meanwhile, the backward sliding of seat, together with backward sliding of occupant, makes the ride-down process more
Dai, Rui, Zhou, Qing, Puyuan, Tan, Shen, Wenxuan
AI-Based Prediction of Motion Sickness in Autonomous Vehicles Using Passenger Profiles and Driving Route Data2026-01-0154To be published on 04/07/2026
Autonomous Vehicles (AV) are expected to significantly reshape travel experiences. Drivers will no longer be responsible for operating the vehicle and will instead take on the role of occupants, free to engage in personal activities such as reading or using phones. Consequently, motion sickness arises from a mismatch between the motion perceived by the body and the motion expected by the brain. Motion sickness detection in AVs has typically been approached through sensor-driven methods that monitor vehicle dynamics as well as passenger conditions, requiring continuous streams of data for reliable predictions. However, while vehicle-mounted sensors can be seamlessly integrated into the system, passenger-oriented solutions often rely on wearable devices, which may not always be practical for wide use in everyday settings. To address this gap, we introduce a ProfileFusion model, a multimodal deep learning model providing a more user-friendly solution that requires minimal user input. It
Khosravifard, Mina, Malik, Usama Zaid, Nguyen, Trang, Grosseruschkamp PhD, Marc, Lichtenberg, Frank
Sensorless Estimation of In-Cabin CO2 Concentration for Model-Based Air Recirculation Control2026-01-0130To be published on 04/07/2026
This paper introduces a sensorless approach for data-driven modeling of in-cabin CO2 concentration to optimize air recirculation flap control without the need for a dedicated CO2 sensor. Elevated CO2 concentrations, resulting from passenger exhalation, can impair occupants’ cognitive function and comfort. Current state-of-the-art solutions rely either on time-based control strategies, which lack responsiveness to actual cabin conditions, or on direct CO2 measurements via sensors, which increase system complexity and costs. In contrast, the proposed approach aims to replicate the benefits of sensor-based control without requiring physical sensors. In this study, a model-based methodology is presented, utilizing empirical CO2 measurement data collected from real-world test drives at varying occupancies, fan stages, vehicle speeds, and flap positions. Data acquisition involves a multi-gas analyzer positioned within the passengers’ breathing zone under controlled operation of the vehicle’s
Stürmer, Michael, Geier, Bertram, Hofstetter, Martin, Hirz, Mario
Numerical Investigation on Thorax Rib Deflections of 50th Male in Vehicle Side Oblique Pole Impact Using Human Body Model2026-01-0566To be published on 04/07/2026
The WorldSID-50M dummy is an advanced side impact dummy that has been adopted extensively in regulatory testing and third party testing such as Euro-NCAP and C-NCAP. However, with increased testing modalities, excessive upper thorax rib deflection was observed in some vehicle side impact tests. It is believed that interaction between arm and thorax rib causes excessive deflection of upper thorax rib in side oblique pole impact with a large side airbag, which has better protection to the shoulders of an occupant. The objectives of the study was as following: (1) Excessive upper thoracic rib deflection of WorldSID-50M dummy are presented in the side oblique pole crash tests while this observation was not found in side impact tests with the barrier. (2) The effect of the interaction between arm and thorax of a 50th male occupant on upper thorax rib deflection was studied using Human Body Models (HBMs). The study indicates that the interaction between arm and thorax ribs has minor effect
Zhou, DY, Chen, Shaopeng, Yan, Li, Wu, Jing, Liu, Chong, Lv, Xiaojiang, Yang, Heping
Risk analysis of occupant injuries with different lower limb postures during vehicle frontal impact2026-01-0572To be published on 04/07/2026
To investigate the biomechanical characteristics of injuries sustained by occupants with different lower limb postures during frontal impact, the human body finite element models- THUMS AM50 under standard sitting posture and sitting posutres with 100° calf bend, 90° calf bend, and crossed legs were analyzed in the frontal impact at 56 km/h. Injury biomechanical analysis demonstrates that the occupant under the sitting posture with crossed legs has the highest overall injure risk, e.g, the highest HIC (Head Injury Critirion) value, peak value of head accerelation, VC (Viscous Crterion) values, strain of the thracic organs, stress of pelvic cortical bone and knee ligments, and so on. In summary, different lower limb postures can affect the overall risk of occupant injury: the smaller the calf flexion angle and the more complex the leg posture, the higher the risk of overall injury. In the future study it is necessary to strengthen the protection of occupants in non-standard seating
Li, Dongqiang, jiang, Yejie, Tan, Chun, Li, Yanyan, HeQuan, Wu, Jiang, Binhui, Zhu, Feng
A study on the injury risk of occupant with different head and neck rotating positions2026-01-0574To be published on 04/07/2026
Drivers obtain road information through head and neck rotation. In order to study the impact of head and neck rotation posture on occupant injury in frontal collision, this paper studies the biomechanical response of occupants with five different head and neck rotation posture under 56 km/h frontal collision based on THUMS human model. Firstly, the kinematic response and head center-of-mass acceleration curves of the dead body and THUMS were compared to verify the validity of the vehicle model. Then, THUMS was adjusted to the standard occupant pose and five different head and neck rotation poses of ±20° and ±40°, and frontal collision simulation was conducted for each of the five poses with or without airbags. The results show that with the increase of head and neck rotation Angle, the risk of neck injury increases while the risk of chest injury decreases. 4 ribs are broken under standard posture, and only 2 ribs are broken when the left rotation of head and neck is 40°. The neck Nij
Li, Dongqiang, jiang, Yejie, Li, Yanyan, Tan, Chun, Jiang, Binhui
A Cooperative Hand Gesture Recognition System for Human Machine Interface to Control Robotic Arms2026-01-0252To be published on 04/07/2026
In the context of Industry 5.0, effective collaboration between humans and machines demands seamless and natural interaction. Hand-Gesture Recognition (HGR) is a promising technology for creating intuitive human-machine interfaces (HMIs) that allow users to control robots without physical devices or wearables. This research introduces a real-time HGR system designed to control a 6-Degree-of-Freedom (DoF) robotic arm using YOLOv10, a state-of-the-art deep learning model for hand gesture recognition. While YOLOv10 offers high accuracy, its computational demands exceed the capabilities of edge devices typically attached to robotic arms, posing a significant hardware challenge. To overcome this, we propose a cooperative client-server architecture that distributes the workload between the edge device and a more powerful remote server. An RGB camera mounted on the robotic arm captures hand gesture images and sends image data to the server using User Datagram Protocol (UDP). The server
DeHaven, Aaron Lee, Park, Jungme
High Biofidelity Modification of Thoracolumbar Structure in THOR model for Reclined Occupant2026-01-0196To be published on 04/07/2026
With the rapid development of automated driving and the increasing adoption of zero-gravity seats, the crash safety of highly reclined occupants has become a critical issue. The current THOR model, designed for frontal impacts in the standard upright posture, shows limitations when applied directly for reclined occupants, including excessive thoracolumbar flexion stiffness and large backward pelvis rotation. In this study, we analyzed the thoracolumbar spine kinematics of the THUMS human body model, which had been reconstructed against post-mortem human subject (PMHS) tests. A two-segment fitting was used to “dummy-ize” the spinal flexion response, yielding a virtual rotation hinge located close to the thoracic hinge of the original THOR model. The hinge rotation angle exhibited a strong linear correlation with the flexion moment of the L1–T12 segment. Based on this relationship, angular stiffness derived from the fitting was applied to the thoracolumbar hinge of the dummy. Additional
Guo, Wencheng, Kuang, Gaoyuan, Shen, Wenxuan, Tan, Puyuan, Zhou, Qing
Development of Smart Climate Control with Multiple Level Auto Calibrations2026-28-00082/12/2026
Electric Vehicles (EVs) are rapidly transforming the automotive landscape, offering a cleaner and more sustainable alternative to internal combustion engine vehicles. As EV adoption grows, optimizing energy consumption becomes critical to enhancing vehicle efficiency and extending driving range. One of the most significant auxiliary loads in EVs is the climate control system, commonly referred to as HVAC (Heating, Ventilation, and Air Conditioning). HVAC systems can consume a substantial portion of the battery's energy—especially under extreme weather conditions—leading to a noticeable reduction in vehicle range. This energy demand poses a challenge for EV manufacturers and users alike, as range anxiety remains a key barrier to widespread EV acceptance. Consequently, developing intelligent climate control strategies is essential to minimize HVAC power consumption without compromising passenger comfort. These strategies may include predictive thermal management, cabin pre-conditioning
Mulamalla, Sarveshwar Reddy, SV, Master Eniyan, M, Nisshok, Anugu, Anil, E A, Muhammed, Guturu, Sravankumar
Methodology for Shower Water Management in Electric Car Applications2026-28-00682/12/2026
All automotive vehicles with enclosed compartments must pass the shower test standard - IS 11865 (2006). One of the most severe and critical areas of water leakage is “water entry into HVAC (heating, ventilation, and air conditioning) opening”. Excess water flow at high-pressure conditions and seepage during long-time low-pressure conditions could potentially have a significant impact on water entry inside the HVAC suction cutout given on BIW (body in white) and subsequently into the cabin. The present study clearly indicates that for making leak proof HVAC opening (suction interface), it is crucial for the structure of BIW plenum, plenum applique, and its sealing components to be robust enough to effectively collect and divert the water during rainy seasons.
Gunasekaran, Mohanraj, Namani, Prasad, Ramaraj, Rajasekar, Junankar, Ashish, Raju, Kumar
Wearable Monitors Heart Rate Recovery to Predict RiskTBMG-545272/1/2026
Scientists used a “smart” shirt equipped with an electrocardiogram to track participants’ heart-rate recovery after exercise and developed a tool for analyzing the data to predict those at higher or lower risk of heart-related ailments.
Crashworthiness of WC19 Wheelchairs in Horizontal Dynamic Aircraft Seating Tests09-14-02-00011/23/2026
At present, commercial air travel rules do not allow people to sit in their own wheelchairs during flight. However, airline seating often does not meet medical needs. In response to current requests to allow this seating option, we researched the crashworthiness and safety of wheelchairs for potential use in aircraft. For motor vehicle travel, many wheelchairs meet voluntary standards for crashworthiness and safety per RESNA WC19. This project assesses whether WC19-compliant wheelchairs can meet FAA aircraft seating standards when secured using 4-point tiedowns. For the FAA horizontal impact testing, computer modeling indicated that a trapezoidal sled pulse was sufficient to represent the more typical triangular pulse, and that due to the flexibility of the tiedown webbing, the effect of the simulated pitch/roll element was minimal. During the initial two horizontal impact tests, fracture of the left front wheelchair caster was observed. The remaining five wheelchairs were tested with
Klinich, Kathleen D., Manary, Miriam A., Boyle, Kyle J., Vallier, Tyler, Orton, Nichole R.
Adaptive Restraints for Equitable Protection2026-26-00151/16/2026
Real-world crashes involve diverse occupants, but traditional restraint systems are designed for a limited range of body types considering the applicable regulations and protocols. While conventional restraints are effective for homogeneous occupant profiles, these systems often underperform in real-world scenarios with diverse demographics, including variations in age, gender, and body morphology. This study addresses this critical gap by evaluating adaptive restraint systems aligned with the forthcoming EURO NCAP 2026 protocols, which emphasize real-world crash diversity and occupant type. Through digital studies of frontal impact scenarios, we analyze biomechanical responses using adaptive restraints across varied occupant demographics, focusing on head and chest injury (e.g., Chest Compression Criterion [CC]). This study used a Design of Experiments (DOE) approach to optimize occupant protection by timing the actuating of these adaptive systems. The results indicate that activating
satija, Anshul, Suryawanshi, Yuvraj, Chavan, Avinash, Rao, Guruprakash
Machine Learning Model to Predict Chest Injury during Thorax Impact on Human Body Models2026-26-06651/16/2026
In recent years, virtual models have been extremely helpful in predicting potential injury risk to occupants in vehicle crashes. Virtual models offer detailed occupant anthropometry and closest possible bio-fidelity over existing test devices. This study focuses on the assessment of chest deflections in frontal thorax impacts using virtual human body models of a few anthropometries and transforming the assessment of injuries for a broader range of anthropometries (sections of the population). The study utilizes machine learning to enable injury assessment across a wide range of body types. A standard test scenario (Kroell load case) with a frontal blunt thoracic impact is considered for this study. Results from physical tests and simulations from various finite element human body models (HBMs) from literature are used to train supervised machine learning models. The combination of virtual simulation and machine learning reduces the reliance on physical prototypes and expands the reach
Sridhar, Raam, Arya, Bibhu, Divakar, Prajwal, R, Udhaya Kumar, Bhutki, Prasad, Kumar, Devendra, Kurkuri, Mahendra, Mohan, Pradeep
Comprehensive Research Study Examining Tyre Wear and its Indian Perspective2026-26-06041/16/2026
Automobile emissions refer to the gases and particles released into the atmosphere by vehicles during their operation. These emissions contribute to environmental pollution and have an impact on human physiology and environment. This paper assimilates findings from a comprehensive research study examining tyre wear and its Indian perspective. Tyre wear understood as a factor affecting road safety, environmental health, and economic sustainability. The study identifies factors affecting tyre wear and provides overview regarding tyre wear generation in India, encompassing road infrastructure, vehicle characteristics, driving patterns, and environmental factors. Moreover, it examines the adverse effects of these particles on human health, such as respiratory ailments and cardiovascular diseases, as well as their impact on ecosystems. This paper delves measures to measure tyre wear and safeguard both environmental and public health. It also covers the tyre wear measurement methodologies to
Joshi, Amol, Khairatkar, Vyankatesh, Belavadi Venkataramaiah, Shamsundara
Occupant Kinematics and Injuries during High Speed Side Impacts: An Analysis of ARAI Data 2016-20242026-26-00271/16/2026
The objective of the present study is to examine trends in occupant kinematics and injuries during side impact tests carried out on vehicle models over the period of time. Head, shoulder, torso, spine, and pelvis kinematic responses are analysed for driver dummy in high speed side impacts for vehicle model years, MY2016-2024. Side impact test data from the tests conducted at The Automotive Research Association of India (ARAI) is examined for MY2016-2024. The test procedure is as specified in AIS099 or UNECE R95, wherein a 950kg moving deformable barrier (MDB) impacts the side of stationary vehicle at 50km/hr. An Instrumented 50th percentile male EUROSID-2 Anthropomorphic Test Device is positioned in the driver seat on the impacting side. Occupant kinematic data, including head accelerations, Head Injury Criterion (HIC15), Torso deflections at thorax and abdominal ribs, spine accelerations at T12 vertebra, and pelvis accelerations are evaluated and compared. The “peak” and “time to
Mishra, Satish, Borse, Tanmay, Kulkarni, Dileep, Mahajan, Rahul
Investigating Pelvic Locking and Torso Kinematics Using Human Body Models in Frontal Impact Scenarios2026-26-00021/16/2026
Occupant Safety systems are usually developed using anthropomorphic test devices (ATDs), such as the Hybrid III, THOR-50M, ES-2, and WorldSID. However, in compliance with NCAP and regulatory guidelines, these ATDs are designed for specific crash scenarios, typically frontal and side impacts involving upright occupants. As vehicles evolve (e.g., autonomous layouts, diverse occupant populations), ATDs are proving increasingly inadequate for capturing real-world injury mechanisms. This has led to the adoption of computational Human Body Models (HBMs), such as the Global Human Body Models Consortium (GHBMC) and Total Human Model for Safety (THUMS), which offer superior anatomical fidelity, variable anthropometry, active muscle behaviour modelling, and improved postural flexibility. HBMs can predict internal injuries that ATDs cannot, making them valuable tools for future vehicle safety development. This study uses a sled CAE simulation environment to analyze the kinematics of the HBMs
Raj, Pavan, Rao, Guruprakash, Pendurthi, Chaitanya Sagar, Nehe, Vaibhav, Chavan, Avinash
Artificially Intelligent Rapid Rescue Vehicle System2026-26-06421/16/2026
The rapid development of science and technology has impacted on the human lifestyle. The automotive industry plays a crucial role as travel is an integral part of human lifestyle. This indeed has increased the need and demand for automotive domain to step ahead with technology and innovations. Especially, related to ADAS features and AI/ML based algorithms to provide comfort, safety, and many other factors for the consumers. The busy life of human beings has shown an increased rate of many health-related issues like stress, anxiety, heart attacks, blood pressure and so on. The existing system in vehicles detects health emergency and triggers SOS to the emergency service center. However, several catastrophic events occur due to delayed information, thus there is a need for a proactive solution that combines technology and human safety. In this work, we have investigated the different methods which detect the health issues of occupants in a vehicle by monitoring their stress level, heart
Eswarappa, Asha, Nagaraj, Chaitra, Mudassir, Syed
Q-Series Child Dummy FE Model Development and Validation for Child Occupant Safety Assessment in Automotive Crashes2026-26-03901/16/2026
The Ministry of Road Transport and Highways (MoRTH), Government of India, has established BHARAT NCAP to provide a fair, meaningful, and objective assessment of the crash safety performance of cars. This program evaluates vehicles across three key areas, including Child Occupant Protection (COP). A critical component of the COP assessment involves dynamic testing using Q-series child dummies representing a 1½-year-old (Q1.5) and a 3-year-old child (Q3). As per the BHARAT NCAP protocol, these dummies are placed in the second-row outboard seating position within Child Restraint Systems (CRSs) and subjected to two primary dynamic impact tests: Offset Deformable Barrier (ODB) conducted at a speed of 64 km/hr. and Mobile Deformable Barrier (MDB) Side Impact tests conducted at 50 km/hr. The dynamic assessment of these child dummies is primarily focused on the head, neck, and chest regions to evaluate the effectiveness of the CRSs and overall vehicle safety system in protecting young
Khopekar, Maria, Lakshminarayana, Apoorva, Mohan, Pradeep, Kurkuri, Mahendra
Decision-Fatigue Mitigation in Automotive HMI System2026-26-06521/16/2026
With the advent of digital displays in driver cabins in commercial vehicles, drivers are being offered many features that convey some useful or critical information to drivers or prompt the driver to act. Due to the availability of a vast number of features, drivers face decision fatigue in choosing the appropriate features. Many are unaware of all available functionalities displayed in the Human Machine Interface (HMI) System, leading to a bare minimum usage or complete neglect of helpful features. This not only affects driving efficiency but also increases cognitive load, especially in complex driving scenarios. To alleviate the fatigue faced by drivers and to reduce the induced lethargy to choose appropriate features, we propose an AI driven recommendation agent/system that helps the driver choose the features. Instead of manually choosing between multiple settings, the driver can simply activate the recommendation mode, allowing the system to optimize selections dynamically. The
K, Sunil, Dhoot, Disha
Real-Time in-Cabin Vital Sensing and Response System Using Ultra-Wideband Radar in Automotive2026-26-00121/16/2026
This study introduces a novel in-cabin health monitoring system leveraging Ultra-Wideband (UWB) radar technology for real-time, contactless detection of occupants' vital signs within automotive environments. By capturing micro-movements associated with cardiac and respiratory activities, the system enables continuous monitoring without physical contact, addressing the need for unobtrusive vehicle health assessment. The system architecture integrates edge computing capabilities within the vehicle's head unit, facilitating immediate data processing and reducing latency. Processed data is securely transmitted via HTTPS to a cloud-based backend through an API Gateway, which orchestrates data validation and routing to a machine learning pipeline. This pipeline employs supervised classifiers, Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest (RF) to analyze features such as temporal heartbeat variability, respiration rate stability, and heart rate. Empirical
Singh, Samagra, Pandya, Kavita, Jituri, Keerti
Study of Real Time Impact on Automotive Cabin Air Quality due to the Various Usage Conditions in the Severely Polluted City2026-26-05311/16/2026
This study investigates the concentrations of PM2.5 and PM10 inside an automobile under real-world driving conditions, one of the most polluted cities globally. India faces severe air pollution challenges in many cities, including Delhi, which are consistently ranking among the most polluted cities in the world. Major contributors to this pollution include vehicular emissions, industrial activities, construction dust, and biomass burning. Exposure to PM2.5 and PM10 has been linked to numerous adverse health effects, including respiratory and cardiovascular diseases, aggravated asthma, decreased lung function, and premature mortality. PM2.5 particles, being smaller, can penetrate deeper into the lungs and even enter the bloodstream, causing more severe health issues. In big cities like New Delhi, long driving times exacerbate exposure to these pollutants, as commuters spend extended periods in traffic. Measurements were taken both inside and outside the vehicle to assess the real-world
Gupta, Rajat, Pimpalkar, Ankit, Patel, Abhishek, Kumar, Shubham, Joshi, Rishi, Kumar, Mukesh
An Innovative Collision Sensing Architecture for Robust Functionality of Safety Restraint Systems in Different Challenging Real World Accident Scenarios2026-26-00171/16/2026
In emerging markets, especially in India and other similar countries, the growing traffic density on the roads leads to different types of accidents, including frontal head-on collisions, rear-end collisions, side-impact collisions, collisions with fixed objects such as electric poles, trees, road guard rails, road dividers, and accidents involving pedestrians, cyclists, and two-wheelers. These accidents could be due to over speeding, distracted driving, violation of traffic rules, and inadequate road infrastructure etc. Providing the necessary safety restraint systems (Airbags and Seat belts) in vehicles and ensuring their robust functionality in different real-world accident scenarios will be challenging for vehicle manufacturers. It is high time to redefine the traditional collision-sensing architecture strategies with a logical approach based on a thorough study of available accident data statistics, types of objects, and scenarios leading to severe accidents. Among these, rear-end
KOVALAM, SUNIL KUMAR
Thoracic Injury Mechanisms Due to Front Seatback–Rear Seat Pan Interaction in Severe Rear-Impact Collisions: A Case Study2026-26-00051/16/2026
Severe rear-impact collisions can cause significant intrusion into the occupant compartment when the structural integrity of the rear survival space is insufficient. Intrusion patterns are influenced by impact configuration—underride, in-line, or override—with underride collisions channeling forces below the beltline through the rear wheels as a primary load path. This force concentration rapidly propels the rear seat-pan forward, contacting the rearward-rotating front seatback. The resulting bottoming-out phenomenon produces a forward impulse that amplifies loading on the front occupant’s upper torso, increasing the risk of thoracic injury even when the head is properly supported by the head restraint. This study analyzes a real-world rear-impact collision that resulted in fatal thoracic injuries to the driver, attributed to the interaction between the driver’s seatback and the forward-moving rear seat pan. A vehicle-to-vehicle crash test was conducted to replicate similar intrusion
Thorbole, Chandrashekhar
Design and Validation of a Collapsible Brake Pedal System for Lower-Leg Protection in Frontal Impacts2026-26-05001/16/2026
Indian passenger car accident data indicates that approximately 44% of crashes are frontal impacts (Refer fig 1). Among the injuries sustained in these crashes, lower leg injuries are notably critical, contributing to nearly 25% of driver occupant injuries (Refer fig 2). To evaluate such injuries, the Bharat New Car Assessment Program (BNCAP) includes lower leg injury metrics as part of the Frontal Offset Deformable Barrier (ODB64) test. While the overall injury performance is assessed at the vehicle level, BNCAP also monitors vehicle interior intrusions—particularly pedal intrusions—as key contributors to lower limb injury severity. A major challenge in frontal crashes is the intrusion of the vehicle's front-end structure into the occupant compartment. Rigid components, particularly the brake pedal assembly, can be displaced rearward during a crash, significantly increasing the risk of lower leg injuries. Therefore, minimizing pedal intrusions into the driver foot-well is critical for
Shetti, Rahul R., Kudale, Shailesh, Naik, Nagaraj, Bisen, Badal, Kotak, Vijay, Dudhewar, Swapnil, Bhagat, Amit, Durgaprasad, HNV
An Outer Waist Seal with Integrated Glass Wiping Mechanism for a Window Frame of a Vehicle2026-26-00111/16/2026
This invention solves a significant safety issue where drivers have low visibility of the Outside Rear View Mirror (ORVM) in the case of rain, fog, dust or ice formation on the Side Door Window Glass (SDWG). Currently developed methods, such as hydrophobic finishing or films and heated window glass on the doors, provide temporary or weak results, and thus, a more successful and dependable method is demanded. In order to address this problem, we have modified the Outer Waist Seal, which includes a Glass Wiping Mechanism in it. Outer Waist Seal is a type of weather strip fixed on the bottom of the side window of a vehicle on the panel of the door. It does not allow the flow of heavy water, dust and debris into the door cavity, besides supporting the glass on the window when it is in a movement process. The stationary fixed arm of this system is coupled with a rotating arm and an attached wiper blade powered by a low-speed-high-torque motor and interfaced with the Body Control Module (BCM
Neelam, Rajat, Chowdhury, Ashok, Panchal, Girish, Kumar, Saurav
Weaving Data Fabric with AITBMG-544301/6/2026
One of the biggest goals for companies in the field of artificial intelligence (AI) is developing “agentic” systems. These metaphorical agents can perform tasks without a guiding human hand. This parallels the goals of the emerging urban air mobility industry, which hopes to bring autonomous flying vehicles to cities around the world. One company wants to do both and got a head start with some help from NASA.
Conductive Hydrogel Holds Promise for ImplantsTBMG-544101/1/2026
Bioelectronics, such as implantable health monitors or devices that stimulate brain cells, are not as soft as the surrounding tissues due to their metal electronic circuits. A team of scientists has developed a soft polymer hydrogel that can conduct electricity as well as metal can. As the material is both flexible and soft, it is more compatible with sensitive tissues. This finding has the potential for a large number of applications, for example, in biocompatible sensors and in wound healing.
Electronic Fiber Provides Stretchable SensingTBMG-544211/1/2026
EPFL researchers have engineered a fiber-based electronic sensor that remains functional even when stretched to over 10 times its original length. The device holds promise for smart textiles, physical rehabilitation devices, and soft robotics.
Biosensor Could Lead to Breath Test for Lung CancerTBMG-544181/1/2026
University of Texas at Dallas researchers have developed biosensor technology that when combined with artificial intelligence (AI) shows promise for detecting lung cancer through breath analysis.
Hard(ware) to the CoreTBMG-544411/1/2026
Spinoff is NASA’s annual publication featuring successfully commercialized NASA technology. This commercialization has contributed to the development of products and services in the fields of health and medicine, consumer goods, transportation, public safety, computer technology, and environmental resources.
Tiny Neural Implant Wirelessly Tracks BrainTBMG-544171/1/2026
Cornell researchers and collaborators have developed a neural implant so small that it can rest on a grain of salt, yet it can wirelessly transmit brain activity data in a living animal for more than a year.
Probe Powerfully Records Neural Circuits During BehaviorTBMG-544201/1/2026
Trying to document how single brain cells participate in networks that govern behavior is a daunting task. Brain probes called Neuropixels, which feature high-density silicon arrays, have enabled scientists to collect electrophysiological data of this nature from a variety of animals. These include fish, reptiles, rodents, and primates, as well as humans.
3D Printing Method ‘Grows’ Ultra-Strong MaterialsTBMG-544081/1/2026
Researchers have pioneered a 3D printing method that grows metals and ceramics inside a water-based gel, resulting in exceptionally dense, yet intricate constructions for next-generation biomedical technologies.
Wearable Health Tech Brings Research to PeopleTBMG-544061/1/2026
Researchers are exploring new ways to utilize microwave technology in monitoring and assessing health conditions. The results of experiments conducted with realistic models are promising. Bras that detect breast cancer, leg sleeves that identify blood clots, and a helmet that monitors the effects of radiation therapy offer a glimpse into what future healthcare might look like.
Microcatheter Delivers Therapies to the Tiniest Blood VesselsTBMG-544241/1/2026
EPFL researchers have invented a remarkably small and ultraflexible neurovascular microcatheter. Powered by blood flow, it can safely navigate the most intricately branched arteries in a matter of seconds.
Bioadhesive Sponge Stops Internal BleedingTBMG-544071/1/2026
Researchers combined mussel adhesive protein with decellularized extracellular matrix (dECM) to develop a composite hemostatic sponge that offers both strong tissue adhesion and biocompatible biodegradability.
Biosensor Identifies Protein Linked to DepressionTBMG-544091/1/2026
A low-cost, portable biosensor can quickly identify a protein whose altered levels are associated with psychiatric disorders, such as depression, schizophrenia, and bipolar disorder. When it becomes commercially available in the future, it may contribute to early detection, which is essential for treating and monitoring patients’ clinical conditions.
An Interpretable Deep Learning Decision-Making Framework for Autonomous Lane-Change Inspired by Human Driving Experiences2025-01-733912/31/2025
Lane change plays a critical role in autonomous driving and directly affects traffic safety and efficiency. Although deep learning-based lane-change decision-making frameworks have achieved promising results, they still face fundamental challenges in producing human-consistent and trustworthy behavior, mainly due to: 1) Inadequate psychology-informed personalization, as most frameworks focus on physical variables but neglect psychological factors (e.g., risk tolerance, urgency), limiting their ability to capture individual differences in lane-change motivations. 2) Limited holistic understanding of traffic context, most frameworks lack consideration of high-level and interpretable indicators (e.g., traffic pressure) in comprehensively assessing dynamic traffic scenarios, limiting their capacity for human-like contextual understanding. 3) Lack of transparent and interpretable decision logic, as many frameworks operate as black boxes with opaque reasoning processes, hindering human
Chen, Yanbo, Chen, Jiaqi, Yu, Huilong, Xi, Junqiang
Detection of Dangerous Driving Postures Based on Depth Images Using an Anchor Regression Method2025-01-734312/31/2025
Perceiving the movement characteristics of specific body parts of a driver is crucial for determining their activity. Moreover, the driver’s body posture significantly impacts personnel safety during collision. This study investigates the creation of a dataset using Kinect depth camera for acquiring, organizing, annotating with skeleton tracking assistance, and optimizing interpolation. The pose recognition methods enhanced through an anchor regression mechanism, leading to the refinement of a lightweight anchor regression network capable of end-to-end learning ability from depth images. The improved backbone neck head structure offers advantages of reduced model parameters and enhanced accuracy. This engineering optimization makes it better suited for practical applications within vehicles with limited computational resources limitations and high real-time demands.
Xu, Hailan, Li, Wuhuan, Lu, Jun, Wang, Xin, He, Wenhao, Chen, Zhenming, Liu, Yunjie
Deconstructing Driver State in Smart Cockpits: Physiological Validation of Perceived Risk, Trust, and Fatigue during Automated Driving2025-01-734512/31/2025
For driver-automation collaborative driving, accurately monitoring driver state in smart cockpits is crucial for enhancing safety, comfort, and human-computer interactions. However, existing research lacks clarity regarding the relationships among driver states, and there is no consensus on the optimal physiological channels to reliably capture these states. This study examined three critical psychological constructs (i.e., perceived risk, trust in the automated driving system, and driver fatigue) using a 37-participant driving simulation experiment. We manipulated multiple factors to induce distinct driver states among participants and recorded subjective scale ratings, heart rate variability, galvanic skin response, and eye movement data. Subjective scale ratings were adopted as the ground truth to examine the corresponding measurement relationships between different physiological signals and the three targeted dimensions of driver states. Our results proved that perceived risk
Wang, Zhenyuan, Li, Qingkun, Wang, Wenjun, Liu, Weimin, Sun, Zhaocong, Cheng, Bo
Design and Implementation of a Multimodal Driver Data Collection and Processing Apparatus for Naturalistic Driving Scenarios2025-01-734612/31/2025
As intelligent cockpit technology continues to evolve, the ways in which information is presented and interacted with within vehicle systems are becoming increasingly diverse, driving the development of driver-machine interaction toward multi-modal integration, proactive sensing, and personalized responses. As the core perception object of the intelligent cockpit, the accuracy of driver state recognition directly impacts the intelligence level of cockpit interaction and driving safety. In response to the increasing trend of task diversity and behavioral response complexity in natural driving scenarios, there is an urgent need to develop a driver multimodal data collection and processing tool with high timeliness, non-intrusiveness, and multi-source synchronization capabilities, serving as the key foundation for driver state modeling and intelligent interaction support. Based on multiple resource theory (MRT) and driver status perception mechanisms, this study designs and develops a
Chen, Ke, Li, Xinyi, Cheng, Jiahao, Guo, Gang, Li, Wenbo
Risk Identification and Accompanying Information Service Design of Long Downhill Road Section2025-99-025012/23/2025
In order to reduce traffic accidents and losses in long downhill sections of expressways, giving drivers reasonable prevention and control means of information induction can improve the safety of long downhill sections. The location of the accompanying information service of the driver's vehicle terminal and the rationality of the intervention information are worth studying. This study takes a high-speed long downhill road as an example, divides the risk level of the long downhill road based on the road safety risk index model, and verifies it with the help of driving behavior data. Secondly, three coverage schemes of sensing devices are designed according to the results of risk classification, and the HMI interface of accompanying information service is designed according to the different coverage degrees of sensing devices. Finally, a driving simulation experiment was carried out based on the driving simulator, and the speed control level, psychological comfort level, operational
Wang, Yuejia, Weng, Wenzhong, Luan, Sen, Dai, Yibo
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