Browse Topic: Optics

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Multi-Storey AI Based Parking System2026-28-0129To be published on 02/12/2026
This paper presents a comprehensive design and implementation of an AI-based parking management system tailored to address the challenges of modern parking facilities. The system is designed to enhance efficiency, reduce manual intervention, and optimize operational costs while providing a seamless experience for drivers. The core architecture of the system integrates advanced technologies, including computer vision and IR sensors, thereby minimizing reliance on conventional sensors and streamlining the parking process. By leveraging computer vision, the system continuously monitors parking areas in real-time, accurately detecting vehicle occupancy status, and dynamically updating the availability of parking spaces. This real-time monitoring capability enables efficient space utilization, allowing for the optimization of parking resources. In addition to optimizing space allocation, the proposed system prioritizes security through the integration of video surveillance. Utilizing AI
N, Kalaiarasi, Gupta, Shivansh, Hajarnis, Mihir, Anand, Vikas
ACCIDENTAL DOORING WARNING AND ASSIST SYSTEM2026-28-0053To be published on 02/12/2026
The term dooring refers to the accidents where a vehicle door is suddenly opened into the path of an oncoming cyclist or motorcyclist. These issues are serious road safety hazards, especially in congested urban areas where people may be careless. This project proposes an intelligent, computer vision based warning system designed to detect the approaching vehicles and alert the occupants in the vehicle before opening the door. The system uses the rear parking camera in vehicles with rear parking system or a USB webcam in vehicles without rear parking system to capture live video feed, which is processed by a Raspberry Pi 4 microprocessor. The system will run a lightweight deep learning model, MobileNetSSD, through TensorFlow Lite. Detected objects are classified in real time, and the relative distance of other vehicles is estimated using bounding box dimensions. If a vehicle is identified within a preset safety distance threshold, a clear visual warning is displayed to prevent door
C, Jegadheesan, T, Karthi, Gurusamy, Varun Sankar, Balraj, Tharun, Murugaiya, Tamilselvan
A Review on ‘Sensor Technologies’, its Application, Regulatory Standards & Emerging Trend Towards Safe Hydrogen Economy2026-26-011101/16/2026
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
Effect of Correlated Colour Temperature of Automotive LED Headlamps on Visibility and Safety2026-26-013001/16/2026
The objective of this study was to examine the effect of Correlated Colour Temperature (CCT) of automotive LED headlamps on driver’s visibility and comfort during night driving. The experiment was conducted on different headlamps having different correlated colour temperatures ranging from 5000K to 6500K in laboratory. Further study was conducted involving participants of different age group and genders for understanding their perception to identify objects when observed in light of different LED headlamps with different CCTs. Studies have shown that both Correlated Colour Temperature and illumination level affect driver’s alertness and performance. Further study required on headlamps with automatically varying CCT to get better solution on driver’s visibility and safety.
Patil, Mahendra G., Kirve, Jyoti, Parlikar, Padmakumar
Realistic LiDAR Data Simulation for Autonomous Systems using Physics-Informed Learning2026-26-013801/16/2026
Accurate and realistic simulation of LiDAR data is critical for the development and validation of autonomous driving systems. However, existing simulation approaches often suffer from a significant sim-to-real gap due to oversimplified modelling of physical interactions and environmental factors. In this work, we present a physics-informed deep learning framework that bridges this gap by enhancing the realism of simulated LiDAR data using generative adversarial networks guided by domain-specific physical constraints for LiDAR intensity. Our method incorporates key physical factors such as range, surface material properties, angle of incidence, and environmental conditions along with their underlying physical relationships as constraints into the Cycle-Consistent GAN architecture, enabling it to learn realistic transformations from synthetic to real-world LiDAR intensity data without requiring paired samples. We demonstrate the effectiveness of our approach across multiple datasets
Anand, Vivek, Yadav, Sourav, Limba, Mohit, Pandey, Gaurav, Lohani, Bharat
Development of a New Methodology for Measuring the Dimensions of Lighting Components in Construction Equipment Vehicles (CEVs) as per IS/ISO 12509:2004 using 3-Dimensional Planar Laser2026-26-014501/16/2026
The light and light signaling devices installation test as per as per IS/ ISO 12509:2004 & IS/ISO 12509:2023 for Earth Moving Machinery / Construction Equipment Vehicles is a mandatory test to ensure the safety and comfort of both road users and operators. Considering the shape and size of construction equipment vehicles, accurate measurement of lighting installation requirements is crucial for ensuring safety and regulatory compliance. The international standard IS/ISO 12509:2004 & IS/ISO 12509:2023 outlines specific criteria for these installation requirements of lighting components, including the precise measurement of various dimensions to ensure optimal visibility and safety. Among these dimensional requirements, the dimension 'E' i.e., the “distance between the outer edges of the machine and the illuminating surface of the lighting device” plays a critical role in the performance of vehicle lighting systems. Traditional methods of measuring this dimension, such as using a
Ghodke, Dhananjay Sunil, Belavadi Venkataramaiah, Shamsundara, Tambolkar, Sonali Ameya
Failure Prevention of Permanent Deformation in HNBR Elastomeric Diaphragms Used in CNG Valve Applications2026-26-029401/16/2026
Hydrogenated nitrile butadiene rubbers (HNBR) and their derivatives have gained significant importance in automotive compressed natural gas (CNG) valve applications. In one of the four-wheelers, CNG valve application, HNBR elastomeric diaphragms are being used for their excellent sealing and pressure regulation properties. The HNBR elastomeric diaphragm was developed to sustain CNG higher pressure However, it was found permanently deformed under lower pressures. In this research work, number of experiments was carried out to find out the primary root cause of diaphragm permanent deformation and to prevent the failure for safe usage of the CNG gas. HNBR diaphragm deformation investigation was carried out using advanced qualitative and quantitative analysis methods such as Soxhlet Extraction Column, Fourier Transform Infrared Spectroscopy (FTIR), Differential Scanning Calorimetry (DSC), Optical Microscopy (OM), Scanning Electron Microscopy (SEM), and Thermogravimetric Analysis (TGA). For
Patil, Bhushan Gulab, NAIKWADI, AMOL, Mali, Manoj, Tata, Srikanth
Assessing the Impact of Hole Piercing Edge Quality on Fatigue Samples for S550MC Steel Sheet2026-26-030601/16/2026
The exceptional strength, formability, and weldability of S550MC steel sheets make them a cornerstone material in the automotive industry. These properties translate into the creation of high-performance automotive components like chassis parts, structural reinforcements, ultimately contributing to enhanced vehicle safety and overall performance. Furthermore, S550MC steel boasts excellent fatigue resistance, a critical factor for ensuring long-term reliability in demanding automotive applications that experience repeated stress cycles. However, optimizing the performance of S550MC components depends on a fine understanding of the critical relationship between hole edge quality and fatigue failure. This study highlights the impact of hole-piercing clearance on the edge quality of the hole in modified fatigue samples manufactured from S550MC steel, and its effect on fatigue life. The surface morphology was characterized by using stereoscope for edge quality of hole piercing operation
Nahalde, Sujay, Hingalje, Abhijeet, Ughade, Vikas, Singh, Udita, More, Hemant
Adaptability Survey and Analysis of Camera Monitoring Systems (CMS) on Various Driving Population for Passenger Vehicles in Indian Driving Scenario2026-26-060101/16/2026
This paper presents a comprehensive survey and data collection study on the adaptability of Camera Monitoring Systems (CMS) for passenger vehicles. With the growing demand for enhanced safety, automation, and driver assistance technologies, Camera Monitoring Systems (CMS) has emerged as a key component in modern automotive design. This study aims to explore the current state of camera-based monitoring in passenger vehicles, focusing on their adaptability through survey data collection of various driving population and analysis. This paper evaluates the acceptance of CMS configurations in replacement to conventional rear-view mirrors through Position of Monitor, Clarity, CMS Adaptiveness to eyes, Comfort while turning, Merging into moving traffic, Monitoring Rear Traffic, while Getting Out of Car, while Overtaking, Coverage Area and Overall Acceptance. The findings offer valuable insights for manufacturers, engineers, and researchers working toward the evolution of intelligent vehicle
Sinha, Ankit, Tambolkar, Sonali Ameya, Belavadi Venkataramaiah, Shamsundara, Kauffmann, Maximilian
Simulation-Driven Load Spectrum Prediction: Virtual RLDA for Chassis and Suspension System2026-26-009501/16/2026
In the rapidly evolving and highly competitive automotive industry, manufacturers are under immense pressure to bring products to market quickly while meeting customer expectations. As a result, optimizing the product development timeline has become essential. Structural integrity analysis for chassis and suspension systems lies in the accurate acquisition of operational load spectra, conventionally executed through Road Load Data Acquisition (RLDA) on instrumented vehicles subjected to proving ground excitation. At this point, RLDA is mainly used for final validation and fine-tuning. If any performance shortfalls, such as premature component failure or durability issues, are discovered, they often trigger design revisions, prototype rework, and additional testing. This study proposes a Virtual Road Load Data Acquisition (vRLDA) methodology employing a high-fidelity full-vehicle multibody dynamic (MBD) representation developed in Adams Car. The system is parameterized and uses high
Goli, Naga Aswani Kumar, Prasad, Tej Pratap
Comparative Analysis of Pothole Depth Estimation Using LIDAR and Stereo Imaging with Polarized Lenses: A DOE Approach2026-26-026901/16/2026
Potholes are a common road hazard that significantly compromise road safety. Water filled potholes can be particularly dangerous. These hidden hazards may cause vehicles to hydroplane [1], leading to a loss of control and potential collisions. At night or in low visibility conditions, such potholes can appear deceptively shallow, increasing the risk of severe suspension damage or tire blowouts. Additionally, deep water intrusion can affect critical components such as the exhaust system, air intake, or electrical wiring, potentially leading to engine stalling or short circuits. This research proposes a novel approach for identifying and determining the depth of potholes, especially those that are filled with water. By integrating YOLO, cutting edge computer vision methods like stereo imaging and Lidar. We hope to create a system that can precisely detect and evaluate potholes' severity, reducing the risks connected to these road hazards. A structured 2k factorial Design of Experiment
Ashok, Deeksha, Kumar, Pradeep, Singh, Amandeep
Method and System of Detecting Obstacle around Vehicle Door2026-26-002601/16/2026
Vehicle door-related accidents, especially in urban environments, pose a significant safety risk to pedestrians, infrastructure and vehicle occupants. Conventional rear view systems fails to detect obstacles in blind spots directly below the Outside Rear View Mirror (ORVM), leading to unintended collisions during door opening. This paper presents a novel vision-based obstacle detection system integrated into the ORVM assembly. It utilizes the monocular camera and a projection-based reference image technique. The system captures real-time images of the ground surface near the door and compares them with calibrated reference projections to detect deviations caused by obstacles such as pavements, potholes or curbs. Once such an obstacle is detected the vehicle user is alerted in the form of a chime.
Bhuyan, Anurag, Khandekar, Dhiraj, Jahagirdar, Shweta
Vehicle Self-Soiling from Exterior Cleaning Mechanisms2026-26-042501/16/2026
The automotive industry is rapidly advancing towards autonomous vehicles, making sensors such as Cameras, LiDAR, and RADAR critical components for ensuring constant information exchange between the vehicle and its surrounding environment. However, these sensors are vulnerable to harsh environmental conditions like rain, dirt, snow, and bird droppings, which can impair their functionality and disrupt accurate vehicle maneuvers. To ensure all sensors operate effectively, dedicated cleaning is implemented, particularly for Level 3 and higher autonomous vehicles. It is important to test sensor cleaning mechanisms across different weather conditions and vehicle operating scenarios to ensure reliability and performance. One crucial aspect of testing is tracking the trajectory of the cleaning fluid to ensure it does not cause self-soiling of vehicles and affects the field of view or visibility zones of other components like the windshield. While wind tunnel tests are valuable, digitalizing
Mane, Suvidya, Makam, Sri Lalith Madhav, Varghese, Rixson, Desu, Harsha
Niobium Alloyed Brake Disc for reduced NVH and emission control2026-26-028501/16/2026
Recent regulations limiting brake dust emissions have presented many challenges to the brake engineering community. The objective of this paper is to provide a low cost, mass production solution utilizing well known existing technology to meet brake emissions requirements. The proposed process is to alloy the Gray Cast Iron with Niobium. The Niobium addition will reduce wear debris and improve NVH (Noise Vibration Harshness). The test methodology included: Manufacture of disc samples alloyed with Niobium, and Evaluation of airborne wear debris utilizing a pin-on-disc tribometer equipped with emission collection capability. The airborne emission and wear surfaces were further analyzed by Scanning Electron Microscopy, Energy Dispersive techniques (SEM-EDS), X-Ray Diffraction and Optical Microscopy. The cast iron test matrix included four groups; Unalloyed eutectic 4.3% Carbon Equivalent (CE), Unalloyed hypereutectic >4.3% CE, Niobium alloyed Eutectic and Niobium alloyed hypereutectic
Barile, Bernardo, Holly, Mike
Failure Analysis of Dissimilar Metal Weld Joint of an Air Spring Bracket within an Automotive Active Seat Suspension System2026-26-048701/16/2026
In modern four-wheelers, seat suspension systems play a crucial role in enhancing occupant comfort by mitigating the effects of road unevenness and vibrations. Among these systems, active suspension mechanisms offer advanced performance through complex assemblies involving welded, riveted, and bolted joints. This study investigates the failure of an air spring bracket - a critical component of a pneumatic active suspension system - manufactured by Gas Metal Arc Welding (GMAW) of two dissimilar ferrous materials which are likely to be SAPH440 and S355J2. These different materials were used based on mechanical properties required to perform by their particular part. System level validation tests were conducted to ensure the reliability of the seat suspension system. The one of the validation tests is continuous cyclic fatigue test which is carried out on the complete seat assembly. However, during vibration / cyclic endurance testing, premature failures were observed near the weld joints
Patale Jr, Reshma, Pinjari, Jayant Namdev, Bali, Shirish
Advanced Defect Detection Techniques Using AI, CAD Data, and Computer Vision2026-26-064401/16/2026
In area of modern manufacturing, ensuring product quality and minimizing defects are utmost important for maintaining competitive advantage and customer satisfaction. This paper presents an innovative approach to detect defect by leveraging Artificial Intelligence (AI) models trained using Computer-Aided Design (CAD) data. Traditional defect detection methods often rely on physical inspection, which can be time-consuming and prone to human error. The conventional method of developing an AI model requires a physical part data , By utilizing CAD data, the time to develop an AI model and implementing it to production line station can be saved drastically . This approach involves the use of AI algorithms trained on CAD models to detect and classify defects in real-time. The field trial results demonstrate the effectiveness of this approach in various industrial applications, highlighting its potential to revolutionize defect detection in manufacturing.
Kulkarni, Prasad Ramesh, Sahu, Dilip, Joshi, Chandrashekhar, Khatavkar, Akshay, Poddar, Shivani, Deep, Amar
Experimental Study to Investigate and Control Image Blurriness due to IRVM Vibration2026-26-032101/16/2026
Vibration is one of the prominent factors that determine the quality & comfort level of a vehicle. Moreover, if vibration occurs in areas that are almost entirely within customer touchpoints (during either city or highway driving conditions), it could become a critical factor behind the deterioration of brand image within the market. The interior rear-view mirror (IRVM) is one of the important components inside passenger cabin, providing drivers with a clear view of the rear traffic. However, vibrations induced by engine operation, road irregularities, and aerodynamic forces can cause the IRVM to oscillate, leading to image blurriness and compromised visibility and safety. This paper investigates the underlying causes of IRVM vibrations and their impact on image clarity. Through a combination of experimental analysis and computational modelling, we identify key factors contributing to mirror instability. The findings indicate the specific frequencies of vibration, particularly those
Khan, Aamir Naved, Saraswat, Vivek, Jha, Kartik, Singh, Hemendra, Seenivasan, Gokulram, Khan, Nafees
Mapless Yet Accurate: Trajectory Prediction for traffic agents using online HD Map Reconstruction for Autonomous Driving2026-26-003901/16/2026
Accurate trajectory prediction of traffic agents is vital for enabling safer and more reliable autonomous driving. High-definition (HD) and standard-definition (SD) maps play a critical role in this process by providing detailed lane topology and directional cues essential for forecasting the movement of surrounding traffic agents. However, creating HD maps is both expensive and resource-intensive, often relying on complex SLAM systems and specialized sensors, while SD maps, though more readily available, lack the precision needed for accurate navigation in autonomous driving. In this work, we present a novel framework for trajectory prediction that uses online reconstruction of HD maps using images from vehicle-mounted cameras, offering a more scalable and cost-effective solution. Our method achieves notable improvements in prediction accuracy, especially in scenarios lacking access to pre-built maps. Additionally, we propose a new evaluation metric that emphasizes safety by
Upreti, Minali, Girijal, Rahul, B A, NaveenKumar, Thontepu, Phani, Ghosh, Shankhanil, Chakraborty, Bodhisattwa
Artificial Intelligence in Passenger Cars: Unlocking Intelligent Mobility and Human-Centric Vehicle Innovation2026-26-067201/16/2026
Artificial Intelligence (AI) is fundamentally reshaping the landscape of automotive engineering, particularly in passenger vehicles where comfort, safety, and customization are paramount. This paper presents a comprehensive review of current and emerging AI-driven applications in passenger cars, including intelligent vehicle insurance, real-time traffic optimization, personalized driving experiences, emotion recognition, and advanced EV battery management. The integration of AI technologies—ranging from machine learning and computer vision to natural language processing and deep neural networks—enables predictive maintenance, adaptive driver-assist systems, and next-generation human-machine interfaces. AI’s role in vehicle insurance is also explored through behaviour-based risk scoring and claims automation. Furthermore, emotion-aware cabin systems are discussed, which aim to detect driver fatigue, stress, or distraction to improve road safety and mental wellness. The paper also
Hazra, Sandip, Tangadpalliwar, Sonali, Khan, Arkadip
Machine Learning Approach to ISO Road Class Prediction Using Multiple Linear Regression2026-26-066701/16/2026
The inertial profiler methodology is traditionally employed in RLDA (Road Load Data Acquisition) to measure road profiles and classify test routes into ISO road classes. However, this approach demands significant time and effort during instrumentation. Also, during data acquisition, laser height sensor data is affected especially during adverse conditions such as rainy seasons or on surfaces with improper reflectivity. Additionally, substantial resources are required for data processing to convert raw measurements into road classifications. To address these challenges, an initial attempt was made to establish a relationship between axle acceleration responses and road profiles, enabling axle acceleration measurements during RLDA to predict ISO road classes. However, this approach relied on a simple linear model that considered only axle acceleration responses, rendering the predictions susceptible to inaccuracies due to varying parameters such as vehicle speed. To overcome these
P, Praveen Kumar, P, Dayalan, Sriramulu, Yoganandam
Next-Gen Driver Health and Wellness Platform for Fatigue Detection and Emotional Wellbeing Monitoring2026-26-063901/16/2026
Driver fatigue and emotional distress are major contributors to traffic accidents, especially among long-haul and professional drivers, making their detection a critical area in road safety and public health. While existing research has explored various sensor-based and wearable solutions to monitor driver states, these approaches often suffer from high cost, intrusiveness, or limited scalability. Camera-based systems have recently gained attention for being less invasive and more practical for real-world deployment; however, many still depend on multiple sensors or cloud-based processing, which raise concerns around energy consumption, privacy, and integration complexity. To address these gaps, we present a sustainable, camera-only Driver Health and Wellness Platform for real-time fatigue detection and emotional wellbeing monitoring. The system leverages a single in-cabin camera and applies lightweight, edge-optimized computer vision models to analyze facial features, eye dynamics
Iqbal, Shoaib, Imteyaz, Shahma
GP-LGFusion: Deep Fusion of Infrared-Visible Driving Images Based on Gradient Preservation and Local Guidance2025-01-730512/31/2025
Infrared and visible driving image fusion represents a pivotal technology in multi-source perception for automated driving. The objective of this technology is to generate fused images that exhibit significant targets and comprehensive road information in complex traffic scenes. However, the existing image fusion algorithms demonstrate inconsistent capacity to complement information in diverse environments. Additionally, there are limitations in their ability to extract features, such as the detailed texture of traffic targets under complex lighting conditions, including low-light scenes and multi-exposure scenes. To overcome these limitations, we propose a novel gradient-preserving and locally guided fusion method (GP-LGFusion). Our primary contribution is a Multi-scale Gradient Residual Block (MGRRB), an encoder module specifically designed to capture and retain both strong and weak texture features across different scales, a capability lacking in conventional approaches. Second, we
Meng, Zhangjie, Shi, Yicui, Chen, Yuhan, Zhou, Xiaoji, Li, Jie, Li, Guofa
MAF-NET: A Multi-Scale Feature Fusion Network for Low-Light Driving Image Enhancement2025-01-730412/31/2025
In low-light driving scenarios, in-vehicle camera images encounter technical challenges, including severe brightness degradation and short exposure times. Conventional driving image enhancement algorithms are susceptible to issues such as the loss of image features and significant color distortion. The proposed solution to this problem is a multi-scale attention fusion network (MAF-NET) for the enhancement of images captured during low-light driving conditions. The network’s structural design is uncomplicated. The model incorporates a meticulously designed multi-scale attention fusion module (MAFB), along with all essential components for network connectivity. The MAF is predicated on a heavy parameter residual feature block design and incorporates a multi-scale channel attention mechanism to capture richer global/local features. A substantial body of experimental evidence has demonstrated that, in comparison with prevailing algorithms, MAF-NET exhibits superior performance in low
Pan, Deng, Chen, Yuhan, Shi, Yicui, Li, Jie, Li, Guofa
Long-Term Temporal Hierarchical Fusion Bird’s-Eye View Perception Method Based on Multiple Position Encodings2025-01-730712/31/2025
With the rapid development of autonomous driving technology, environmental perception, as its core module, has attracted much attention. Among them, the pure visual bird's-eye-view (BEV) 3D detection scheme has become a research hotspot due to its high spatial resolution and excellent semantic recognition ability in specific scenarios. Existing methods mainly utilize the Transformer encoder structure to perform position encoding in the BEV domain to achieve 3D perspective transformation, but they often fail to fully exploit the potential value of multi-perspective image information. To address this challenge, this paper proposes an improved Transformer-based visual BEV vehicle perception method that enhances perception performance by deeply fusing BEV domain and image domain information: an innovative multi-perspective position encoding mechanism is designed, which decouples camera parameters to more efficiently learn the mapping from images to 3D space; at the same time, a cyclic
Chen, Pengyu, Wei, Xiaoxu, Chen, Zhenwei
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
STO-VINS: A Robust Monocular Visual-Inertial SLAM Based on a Fusion Feature Extraction Algorithm Combining Shi-Tomasi and ORB2025-01-730612/31/2025
The VINS-Mono algorithm, which is based on a visual-inertial SLAM framework, faces challenges in extracting feature points in regions with weak or repetitive textures and struggles to achieve accurate localization under unstable lighting conditions. This paper proposes STO-VINS, a robust monocular visual-inertial SLAM algorithm that introduces several key innovations in feature extraction. Key innovations of STO-VINS include: (1) an adaptive multi-scale image preprocessing pipeline that combines image scaling, CLAHE enhancement, and Gaussian filtering, reducing computational complexity by 64% while maintaining feature quality; (2) bidirectional Lucas-Kanade optical flow consistency verification with geometric constraint validation, which significantly reduces false tracking rates by 30-40%; (3) a grid-based multi-feature fusion detection strategy combining Shi-Tomasi corner detection and ORB feature extraction, ensuring uniform spatial distribution of features and feature diversity; (4
Li, Jing, Wu, Jing, Liu, Bo, Gong, Zeyuan, Zhang, Guofang
LLS-SMGSC: A Lidar Localization System Based on Simplified Maps Integrated with Global Search Capabilities2025-01-730312/31/2025
To address the issues of large storage requirements in maps and the dependence of localization accuracy on initial pose estimation, this paper proposes a novel relocalization method named LLS-SMGSC, which is based on simplified maps integrated with Global Search capabilities. Firstly, we partition the map-based on grid size to reduce memory usage. Next, we voxelize the point cloud and map and extract surfel. Then, a coarse-to-fine hierarchical alignment module between the initial frame and maps to estimate the initial global pose. Finally, unmanned platform pose is estimated by the Normal Distribution Transform (ndt) algorithm. Experiments demonstrate that LLS-SMGSC achieves the highest localization accuracy in both unstructured and structured environments while maintaining computational efficiency.
Quan, Zhiheng
Research and Implementation of a Neural Radiance Fields-Based 3D Reconstruction Method for Autonomous Driving Scenes2025-01-731012/31/2025
This paper addresses the scarcity of training and testing data in autonomous driving scenarios. We propose a 3D reconstruction framework for autonomous driving scenes based on Neural Radiance Fields (NeRF). Compared to traditional multi-view geometry methods, NeRF offers superior scene representation and novel view synthesis capabilities but suffers from low training efficiency and limited generalization. To overcome these limitations, we integrate existing NeRF optimization techniques and introduce a scene-specific data reuse strategy tailored for autonomous driving, enabling continuous 3D reconstruction directly from 2D images without requiring elaborate calibration. This approach significantly improves reconstruction efficiency, achieving reliable reconstruction and real-time visualization in complex traffic environments. Furthermore, we develop an interactive scene editing plugin in Unreal Engine 5, supporting the addition, removal, and adjustment of static objects. This extension
Pan, Deng, Zou, Jie, Chen, Yuhan, Meng, Zhangjie, Li, Jie, Li, Guofa
Trajectory Reconstruction at Signalized Intersections in a Vehicle-to-Infrastructure Environment2025-99-021712/23/2025
Vehicle trajectories encapsulate critical spatial-temporal information essential for traffic state estimation, congestion analysis, and operational parameter optimization. In a Vehicle-to-Infrastructure (V2I) environment, connected automated vehicles (CAVs) not only continuously transmit their own real-time trajectory data but also utilize onboard sensors to perceive and estimate the motion states of surrounding regular vehicles (RVs) within a defined communication range. These multi-source data streams, when integrated with fixed infrastructure-based detectors such as speed cameras at intersections, create a robust foundation for reconstructing full-sample vehicle trajectories, thereby addressing data sparsity issues caused by incomplete CAV penetration. Building upon classical car-following (CF) theory, this study introduces a novel trajectory reconstruction framework that fuses CAV-generated trajectories and infrastructure-based speed detection data. The proposed method specifically
Bai, Wei, Fu, Chengxin, Yao, Zhihong
Impact of Tire-Ground Contact Width on Pavement Roughness Evaluation2025-99-025612/23/2025
The International Roughness Index (IRI) is a key indicator for evaluating the performance of road surfaces. However, traditional measurement methods only focus on the evaluation data of a single longitudinal section and do not consider the lateral difference between the actual contact area between the tire and the road surface, which may lead to inaccurate evaluation results. In recent years, with the advancement of 3D laser scanning and digital photogrammetry technology, full-section data acquisition has brought new possibilities for roughness evaluation. However, how to find a balance between data fineness and computing efficiency has become a core problem that needs to be solved. Based on the principle of interaction between vehicles and road surfaces, this paper proposes to include only the pavement height data within the tire width range into IRI analysis, and establishes an evaluation framework based on standard tire-ground contact width. This method not only retains the key
An, Huazhen, Wang, Rui, Han, Xiaokun, Luo, Yingchao
Analysis of Light Duty Vehicle Particulate Matter Emissions Using Scanning Electron Microscopy2025-36-007412/18/2025
Particulate matter (PM), mainly its finer fraction, is among the main atmospheric pollutants present in an urban environment. The relationship between the increase in the concentration of this pollutant and the harm to human health is well established. The main sources of particulate matter in urban areas are mobile sources, which include the exhaust emission from light duty vehicles. This work measured the emission of PM in three light duty passenger vehicles, characterizing it in terms of emitted mass in one “flex” vehicle with port fuel (indirect) injection (PFI), using ethanol and gasohol (mixture of 22% anhydrous ethanol and 78% gasoline, by volume), in another “flex” vehicle with direct fuel injection (GDI), and in a diesel vehicle. In addition to mass measurement, images of the filters used in PM sampling were produced using scanning electron microscopy. The processing of these images made it possible to determine the average PM size, as well as establish a particle size
Borsari, Vanderlei, Neto, Edson Elpídio, de Abrantes, Rui
Evaluation of Surface Integrity Aspects Induced by Different Gear Manufacturing Paths for Electric Vehicle Transmission Systems2025-36-006212/18/2025
The mobility electrification process is currently of great interest due to its environmental appeal, but it is accompanied by new technical requirements for vehicle systems, the powertrain being one of those with the most significant trade-offs to be solved. Higher power densities, higher torque efficiency and lower noise and vibration generation are simultaneously required. The literature shows that the manufacturing chain can influence the final state of surface integrity of a part, which affects the operational behavior and service life of a component. Therefore, a customized transmission system design for electric propulsion requires several analyses, from the raw material to the gear manufacturing processes, so that surface integrity plays a significative role in the required performance. From the perspective of their capability to meet the e-mobility requirements in terms of surface integrity is essential to conduct a comparative analysis of gear manufacturing processes. So, the
Gomes, Caio F. S., Gomes, Gilberto M. O., Colombo, Tiago C. A., Rego, Ronnie R., Michelotti, Alvaro C., Berto, Lucas F.
Development of Embedded Electronics with Artificial Intelligence in an Implement for Forklifts2025-36-001212/18/2025
In this article we will discuss the development and implementation of a computer vision system to be used in decision-making and control of an electro-hydraulic mechanism in order to guarantee correct functioning and efficiency during the logistics project. To achieve this, we have brought together a team of engineering students with knowledge in the area of Artificial Intelligence, Front End and mechanical, electrical and hydraulic devices. The project consists of installing a system on a forklift that moves packaged household appliances that can identify and differentiate the different types of products moved in factories and distribution centers. Therefore, the objective will be to process this identification and control an electro-hydraulic pressure control valve (normally controlled in PWM) so that it releases only the hydraulic pressure configured for each type of packaging/product, and thus correctly squeezing (compressing) the specific volume, without damaging it due to
Furquim, Bruno Bueno, Pivetta, Italo Meneguello, Ibusuki, Ugo
Fractographic Analysis after Creep Testing of Ti-6Al-4V with Yttria and Niobia Co-Doped Zirconia TBC2025-36-005312/18/2025
The application of Thermal Barrier Coatings (TBC) has been widely utilized in aerospace turbines to enhance the operational temperature and thermal efficiency of titanium alloys, while preserving their properties such as low density, creep resistance, and corrosion resistance. TBC systems typically consist of a metallic substrate, a metallic coating (Bond Coat), a thermally grown oxide (TGO), and a ceramic topcoat (TC). This study investigated the fracture surface characteristics of Ti-6Al-4V with TBC after a creep test at a constant temperature of 600 °C, under stress levels of 125, 222, and 319 MPa, in order to understand the mechanisms involved. The TBC was composed of a NiCrAlY (BC) and a zirconia co-doped with yttria and nióbia (TC). The fracture characterization of the alloy after the creep test was conducted through stereoscopy and scanning electron microscopy. The fracture mechanism at 600 °C and 222 MPa was predominantly ductile, as evidenced by the presence of dimples and
Takahashi, Renata Jesuina, de Assis, João Marcos Kruszynski, Rodrigues, Bianca Costa, de Andrade Acevedo Jimenez, Laila Ribeiro, Reis, Danieli Aparecida Pereira
Nanosilica-Based Treatments for Fabrics: Aspects of Wettability and Selective Oil/Water Separation2025-36-021312/18/2025
Nanosilica-treated fabrics have a variety of properties, such as durability, water resistance, and specific surface characteristics. Due to that, many applications of those components are highlighted in literature. Some examples include waterproofing and water repellency, stain resistance, flame retardancy, improved durability, UV protection, improved comfort, antimicrobial properties, and textile coatings for electronics. These applications demonstrate how nanosilica-based treatments can enhance the performance of fabrics, making them more suitable for various specialized uses. In this work, a technical fabric with a mesh opening of 45 μm and an open area of 29.6% was surface treated. The treatments were performed by the dip-coating method using poly(dimethylsiloxane) (PDMS) and nanosilica at different concentrations. Optical microscopy (OM) images of the fabrics’ surface and water contact angle (WCA) measurements were carried out before and after the fabrics’ treatments. The results
Kerche, Eduardo Fischer, Leal, Débora, Romano, Paulo, Oliveira, Vinícius, Polkowski, Rodrigo
The Racing & High-Performance TireR-59412/17/2025
The Racing & High-Performance Tire originally published in 2003 and continues to be a best-seller. Following up on his first two books, Inside Racing Technology and Inside Racing: A Season with the PacWest CART Team, Paul Haney presents a new book revealing the complexities of tires, how they influence vehicle dynamics, and how to use tires in the engineering of racing and high-performance cars. More than 150 photos and drawings help the reader learn the colorful history and unique characteristics that make the pneumatic tire one of the world's most complex and useful products.
Haney, Paul W.
Optimization Method for the Layout of Sponge-Like Drainage Ditches in Large Airports Based on BIM-3DGIS Coupling2025-99-035612/17/2025
The control of rainfall runoff drainage in large airports presents significant challenges, particularly in terms of real-time coupling with meteorological warnings. This paper proposes an optimization method for the layout of sponge-like drainage ditches in large airports under BIM-3DGIS coupling. A BIM water supply and drainage model is constructed, with detailed inspections conducted on the functions and connections of the pipeline system in Revit software. The flow velocity and equivalent water supply pressure within the pipelines are analyzed, and collision detection is performed on the components. Based on 3DGIS technology, an optimization model for the layout of sponge-like drainage ditches is established, taking into comprehensive consideration various factors such as airport topography, rainfall characteristics, and surrounding environment. By calculating the water level changes within the infiltration and drainage ditches under different design rainfall scenarios, the storage
Geng, Liangsui, Zhao, Zhenyu, Hu, Jing
Dynamic Graph Convolutional Recurrent Networks Based on Progressive Learning2025-99-044112/10/2025
Traffic flow prediction is the core challenge of transportation, and its key lies in effectively capturing the spatio-temporal dynamic dependencies. Aiming at the deficiencies of existing methods in modeling global temporal relations and dynamic spatial heterogeneity, this paper proposes a dynamic graph convolutional recurrent network (DGCRN) based on interactive progressive learning. First, the interactive progressive learning module (IPL) is designed to segment the input sequences through a tree structure, synchronize the extraction of spatiotemporal features using the interactive learning of parity subsequences, and adaptively capture the dynamic associations among nodes by combining with the dynamic graph convolutional recursive module (DGCRM). Secondly, a spatio-temporal embedding generator (STEG) is constructed to fuse temporal and spatial embedding to generate dynamic graph structures. Experiments validate the effectiveness of DGCRN on the PEMS04 and PEMS08 datasets with MAE
Su, Jiangfeng, Xie, Zilong, Liu, Chunya, He, Lan, Kou, Yujiao, Xue, Xue
AR-Enhanced Rescue Robot for Disaster ResponseTBMG-5428612/01/2025
Robots may soon have a new way to communicate with people. Not through words or screens, but with light and images projected directly onto the world around them.
EDITORIAL: Off-highway innovators help kick off 202625TOFHP12_0412/01/2025
As I'm wont to do come December, with work well underway on the first issue of the new year, I like to take stock of upcoming venues for innovative product reveals and thought-provoking presentations on emerging trends and technologies. Come the first week of January, that means CES in Las Vegas. Traditional equipment manufacturers have increasingly used the event to demonstrate to the broader public that they not only deal in metal but also the digital realm. For example, earlier this year at CES, John Deere revealed its second-generation tech stack featuring camera pods, Nvidia Orin purpose-built processors and Deere's VPUs (vision processing units), along with four new autonomous machines including the 9RX 640 tractor for open-field ag operations. The company is exhibiting again this coming year.
Gehm, Ryan
How Metasurfaces Can Act as Quantum UpgradesTBMG-5429212/01/2025
In the race toward practical quantum computers and networks, photons — fundamental particles of light — hold intriguing possibilities as fast carriers of information at room temperature. Photons are typically controlled and coaxed into quantum states via waveguides on extended microchips, or through bulky devices built from lenses, mirrors, and beam splitters. The photons become entangled — enabling them to encode and process quantum information in parallel — through complex networks of these optical components. But such systems are notoriously difficult to scale up due to the large numbers and imperfections of parts required to do any meaningful computation or networking.
Training Uncrewed Underwater Vehicles for Visualization of Subsurface StructuresTBMG-5429012/01/2025
Stoneridge Innovation Truck envisions a digital-vision future25TOFHP12_0512/01/2025
Stoneridge displayed its vision for the future of commercial vehicle technology on the SAE COMVEC 2025 exhibit floor. The Innovation Truck showcases the Tier 1 supplier's next-generation vision and driver-assistance technologies designed to enhance driver safety and fleet optimization. Mario Gafencu, product design and evaluation specialist at Stoneridge, gave Truck & Off-Highway Engineering a tech truck walkaround at the event. The first technology Gafencu detailed was the second-generation MirrorEye camera monitor system that's designed to replace the glass mirrors on the sides of a truck.
Gehm, Ryan
Entangled-Photon Pairs Secure Optical CommunicationsTBMG-5429412/01/2025
NASA’s Glenn Research Center has developed a method of using entangled-photon pairs to produce highly secure mobile communications that require mere milliwatts of power. Conventional gas Argon-ion laser sources are too large, expensive, and power-intensive to use in portable applications. By contrast, Glenn’s patented optical quantum communication method produces entangled-photon pairs approximately a million times more efficiently than conventional sources, in a system that is small and light enough to be portable.
Color Filtering Software Enhances Material Strain AnalysisTBMG-5429312/01/2025
Innovators at NASA Johnson Space Center have developed a technology that can isolate a single direction of tensile strain in biaxially woven material. This is accomplished using traditional digital image correlation (DIC) techniques in combination with custom red-green-blue (RGB) color filtering software. DIC is a software-based method used to measure and characterize surface deformation and strain of an object. This technology was originally developed to enable the extraction of circumferential and longitudinal webbing strain information from material comprising the primary restraint layer that encompasses inflatable space structures.
3D LiDAR for Improved Rover Traversal and ImageryTBMG-5429512/01/2025
Planetary and lunar rover exploration missions can encounter environments that do not allow for navigation by typical, stereo camera-based systems. Stereo cameras meet difficulties in areas with low ambient light (even when lit by floodlights), direct sunlight, or washed-out environments. Improved sensors are required for safe and successful rover mobility in harsh conditions. NASA Goddard Space Flight Center has developed a Space Qualified Rover LiDAR (SQRLi) system that will improve rover sensing capabilities in a small, lightweight package. The new SQRLi package is developed to survive the hazardous space environment and provide valuable image data during planetary and lunar rover exploration.
Visualization of Ammonia Engine by Pre-Chamber Igniter2025-01-053011/25/2025
Ammonia is considered more and more as a promising carbon-free fuel for internal combustion engines to contribute to the decarbonization of several sectors where replacing conventional engines with batteries or fuel cells remains unsuitable. However, ammonia properties can induce some challenges for efficient and stable combustion. This study investigates the use of an active pre-chamber ignition system fueled with hydrogen and compares it to conventional spark ignition, with a focus on lean limit operation and early flame development. Experiments were conducted on a single cylinder optical engine with a compression ratio of 9.5, equipped with a quartz window in the piston for natural flame luminosity imaging using a high-speed camera. The engine was fueled with a mixture of 95% ammonia and 5% hydrogen by volume. Ammonia was injected and mixed with air in the intake port while hydrogen was directly injected into the prechamber. As a function of the intake pressure (1.0, 0.9, 0.8, and
Rousselle, Christine Mounaim, Brequigny, Pierre, Gelé, Raphaël, Moreau, Bruno
Ultra-Lightweight, Multispectral, High-Resolution Imaging for Orbital Intelligence and Civilian MissionsTBMG-5419211/18/2025
Elbit Systems Haifa, Isreal
An AI-Powered Wearable Device to Expedite Wound HealingTBMG-5414011/12/2025
Waiting for a wound to heal is incredibly frustrating. First, it must clot; then an immune system response is needed; followed by scabbing and scarring — and that’s not even getting into the pain part.
Research on Overspeed Vehicle Detection Based on Fusion of Millimeter-Wave Radar and Visual Images2025-99-012911/11/2025
To address the limitations of conventional overspeed detection methods, this study proposes a vehicle overspeed detection approach based on the fusion of millimeter-wave radar (MWR) and vision sensors. The MWR captures target position and velocity data, while the vision sensor acquires vehicle image information. Radar-detected points are mapped onto visual images through coordinate transformation, and the Intersection over Union (IoU) method is employed to associate radar points with vision-detected vehicle bounding boxes. Subsequently, for radar-detected points exceeding the speed threshold, the corresponding vehicle images are identified, enabling real-time overspeed detection and data acquisition. This method not only facilitates prompt identification of speeding behavior but also extracts the associated vehicle images, ensuring both accuracy and informational integrity in overspeed monitoring. Experimental results demonstrate that the proposed method achieves high speed measurement
Li, Yuanchen, Wu, Zhichao, Xu, Haibo, Song, Liangliang, Huang, Hao
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