Browse Topic: Visibility

Items (857)
Mining operations are important to industrial growth, but they expose the mining workers to risk including hazardous gases, elevated ambient temperatures, and dynamic structural instabilities within underground environments. Safety systems in the past, typically based on fixed sensor networks or manual patrols, fall short in accurate hazard detection amidst shifting mine conditions. The proposed project Miner's Safety Bot advanced this paradigm by leveraging an ESP 32 microcontroller as a mobile platform that integrates gas sensing, thermal monitoring, visual inspection and autonomous obstacle avoidance. The system incorporates MQ7 semiconductor gas sensor to monitor real time carbon monoxide (CO), offering detection range from 5 to 2000 ppm with accuracy of 5 ppm. Temperature and humidity are monitored through DHT11 digital sensor, calibrated to ensure reliability across the harsh microclimates in mines. Navigation and autonomous movement are enabled by Ultrasonic Sensor (HC-SR04
D, SuchitraD, AnithaMuthukumaran, BalasubramaniamMohanraj, SiddharthSubash Chandra Bose, Rohan
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, AnuragKhandekar, DhirajJahagirdar, Shweta
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, SuvidyaMakam, Sri Lalith MadhavVarghese, RixsonDesu, Harsha
The growing environmental, economic, and social challenges have spurred a demand for cleaner mobility solutions. In response to the transformative changes in the automotive sector, manufacturers must prioritize digital validation of products, manufacturing processes, and tools prior to mass production. This ensures efficiency, accuracy, and cost-effectiveness. By utilizing 3D modelling of factory layouts, factory planners can digitally validate production line changes, substantially reducing costs when introducing new products. One key innovation involves creating 3D models using point cloud data from factory scans. Traditional factory scanning processes face limitations like blind spots and periodic scanning intervals. This research proposes using drones equipped with LiDAR (Light Detection and Ranging) technology for 3D scanning, enabling real-time mapping, autonomous operation, and efficient data collection. Drones can navigate complex areas, access small spaces, and optimize
Narad, Akshay MarutiC H, AjheyasimhaVijayasekaran, VinothkumarFasge, Abhishek
With rapid advancements in Autonomous Driving (AD) & Advanced Driver Assistance Systems (ADAS), numerous sensors are integrated in vehicles to achieve higher and reliable level of autonomy. Due to the growing number of sensors and its fusion creates complex architecture which causes challenges in calibration, cost, and system reliability. Considering the need for further ADAS advancements and addressing the challenges, this paper evaluates a novel solution called One Radar - a single radar system with a wide field of view enabled by advanced antenna design. Placing the single radar at the rear of the vehicle eliminates the need for corner radars and ultrasonic sensors used for parking assistance. With rigorous real-world testing in different urban and low-speed scenarios, the single radar solution showed comparable accuracy in object detection with warning and parking assistance to the conventional combination of corner radars and ultrasonic sensors. The simple single sensor-based
Anandan, RamSharma, Akash
Ambient light reflecting off internal components of the car, specifically the Head-Up Display (HUD), creates unwanted reflections on the Windshield. These reflections can obscure the driver's field of view, potentially compromising safety and reducing visual comfort. The extent of this obscuration is influenced by geometrical factors such as the angle of the HUD and the curvature of the Windshield, which need to be analyzed and managed. The primary motivation is to improve driver safety and visual comfort. This is driven by the need to address the negative impact of ambient light reflecting off Head-Up Displays (HUDs), which can impair visibility through the Windshield. There is a need for tools and methods to address this issue proactively during the vehicle design phase. This study employs a tool-based modeling method to trace the pathways of ambient light from its source, reflecting off the HUD, and onto the Windshield using a dimensional modeling tool. It focuses on: Geometrical
Muchchandi, VinodAkula, Satya JayanthMahindrakar, PramodG S, Sharath
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, JyotiParlikar, Padmakumar
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, it could become a critical factor behind vehicle comfort and affects the brand image within the market negatively. 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 vibration and its impact on rear visibility. Through experimental analysis we identify key factors contributing to mirror instability. The findings indicate the specific frequencies of vibration, particularly those resonating with the mirror's natural frequency, significantly exacerbating
Khan, Aamir NavedSaraswat, VivekJha, KartikSingh, HemendraSeenivasan, GokulramKhan, Nafees
In today's dynamic driving environments, reliable rear wiping functionality is essential for maintaining safe rearward visibility. This study sharing the next-generation rear wiper motor assembly that seamlessly integrates the washer nozzle, delivering improved performance alongside key benefits such as better Buzz, Squeak, and Rattle (BSR) characteristics, reduced system complexity, cost savings, and enhanced perceived quality. This integrated design simplifies the hose routing which improves the compactness and the efficiency of the design. This also enhances the spray coverage and minimizes the dry wiping unlike the traditional systems that position the washer nozzle separately. A non-return valve (NRV) is incorporated to eliminate spray delays ass it maintains consistent water flow giving cleaning effectiveness. Since this makes the nonfunctional parts completely leak proof due to the advanced sealing, it increases the durability and reliability in long run. As this proposal offers
Dhage, PrashantK, NagarajanG, Sabari Rajan
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 SunilBelavadi Venkataramaiah, ShamsundaraTambolkar, Sonali Ameya
The paper aimed to improve the accurate quantification of driver drowsiness and to provide comprehensive, evidence-based validation for a Vision-Based Driver Drowsiness and Alertness Warning System. Advanced quantification of driver drowsiness is designed to enhance distinction of true positive events from False Positive and False Negative events. Methodology to pursue this included assessing inputs such as facial features, driver visibility, dynamic driving tasks, driving patterns, driving course time and vehicle speed. The system is programmed to actively learn Eye Aspect Ratio (EAR) reference and adapt personalised EAR threshold value to process EAR frames against the learnt threshold value. This method optimized the data frames to enhance the evaluation and processing of essential frames, thereby reducing delays in the processor and the Human-Machine Interface (HMI) warning module. Comprehensive validation is systematically conducted within a controlled test track environment to
Balasubrahmanyan, ChappagaddaAkbar Badusha, A
Existing ICE Mid and Heavy commercial vehicles in the Indian and international market are recording a large number of mishaps due to blind spots and non-accessibility of the driver to the opposite side mirror in real-time driving. Non-driver side rear view mirror adjustment creates the need for the driver to get down and adjust the mirror manually/get support from the co-passenger. The paper proposes a solution for a Microcontroller-based compact mirror adjustment system, which will run with minimal economy and highest efficiency. This will assist drivers in aesthetically and safely monitoring of mirror to check on specific blind spots in day conditions This will reduce the prone accidents due to non-visibility by approximately 30%, ensuring enhanced road safety and driver comfort. The Indian commercial vehicle segment needs this solution to be implemented when we look at the rate of increasing demand and also accident rates.
Jambagi, Vaibhavi VyankateshGangvekar, OnkarBhandari, Kiran Kamlakar
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, DengChen, YuhanShi, YicuiLi, JieLi, Guofa
222
Cheng, LizhiGuan, YanyanCheng, XinyuHu, JiangbiFu, YouleiYang, BiyuSong, Shousong
This SAE Standard provides test procedures, performance requirements, and guidelines for semiautomatic headlamp beam switching (SHBSD) devices.
Road Illumination Devices Standards Committee
The Operator’s Field of Vision (FOV) test, conducted in accordance with IS/ISO 5006:2017, is a vital assessment to ensure the safety and operational comfort of personnel operating Construction Equipment Vehicles (CEVs) / Earth-Moving Machinery. IS/ ISO 5006:2017 defines rigorous guidelines for evaluating the operator’s visibility from the driver's seat, with particular emphasis on the Filament Position Centre Point (FPCP), determined from the Seat Index Point (SIP) coordinates. The test includes assessment of masking areas, focusing on the Visibility Test Circle (a 24-meter diameter ground-level circle around the machine), and on the Rectangular Boundary on which a vertical test object is placed at a height specific to the machine type and its operating mass. These parameters are designed to simulate real-world operating conditions. This paper introduces a portable testing setup developed specifically for conducting the Operator’s FOV test as per IS/ISO 5006:2017. The setup facilitates
Ghodke, Dhananjay SunilTambolkar, Sonali AmeyaBelavadi Venkataramaiah, Shamsundara
This study demonstrates the application of the T-Matrix, a Total Quality Management (TQM) tool to improve thermal comfort in automotive climate control systems. Focusing on the commonly reported customer issue of insufficient cabin cooling, particularly relevant in hot and congested Indian driving conditions, the research systematically investigates 36 failure modes identified across the product lifecycle, from early design through production and post-sale customer usage. Root causes are first categorized using an Ishikawa diagram and then mapped using the T-Matrix across three critical stages: problem creation, expected detection, and actual detection. This integrated approach reveals process blind spots where existing validation and inspection systems fail to catch known risks, particularly in rear-seat airflow performance and component variability from suppliers. By applying this TQM methodology, the study identifies targeted improvement actions such as improved thermal targets
Jaiswara, PrashantKulkarni, ShridharDeshmukh, GaneshNayakawadi, UttamJoshi, GauravShah, GeetJaybhay, Sambhaji
Perception is a key component of automated vehicles (AVs). However, sensors mounted to the AVs often encounter blind spots due to obstructions from other vehicles, infrastructure, or objects in the surrounding area. While recent advancements in planning and control algorithms help AVs react to sudden object appearances from blind spots at low speeds and less complex scenarios, challenges remain at high speeds and complex intersections. Vehicle-to-infrastructure (V2I) technology promises to enhance scene representation for connected and automated vehicles (CAVs) in complex intersections, providing sufficient time and distance to react to adversary vehicles violating traffic rules. Most existing methods for infrastructure-based vehicle detection and tracking rely on LIDAR, RADAR, or sensor fusion methods, such as LIDAR–camera and RADAR–camera. Although LIDAR and RADAR provide accurate spatial information, the sparsity of point cloud data limits their ability to capture detailed object
Saravanan, Nithish KumarJammula, Varun ChandraYang, YezhouWishart, JeffreyZhao, Junfeng
This document is a tool for the certifying authority, flight deck crew station designers, instrument suppliers, lighting suppliers, and component suppliers. It is an aid to understanding and meeting relevant regulatory requirements, particularly those relating to pilot compartment view (refer to 14 CFR § 25.773[a][2]) and instrument lights (refer to 14 CFR § 25.1381[a][2]) for glare arising from visible electromagnetic radiation.
A-20A Crew Station Lighting
This document establishes the minimum curriculum requirements for training, practical assessments, and certifying composite structure repair personnel and metalbond repair personnel. It establishes criteria for the certification of personnel requiring appropriate knowledge of the technical principles underlying the composite structural repairs and/or metalbond they perform. Persons certified under this document may be eligible for licensing/certification/qualification by an appropriate authority, in addition to this industry-accepted technician certification. Teaching levels have been assigned to the curriculum to define the knowledge, skills, and abilities graduates will need to make repairs to composite or metalbond structure. Minimum hours of instruction have been provided to ensure adequate coverage of all subject matter, including lecture and laboratory. These minimums may be exceeded and may include an increase in the total number of training hours and/or increase in the teaching
AMS CACRC Commercial Aircraft Composite Repair Committee
The mobility industry is rapidly advancing towards more autonomous modes of transportation with the adoption of sophisticated self-driving technologies. However, a critical challenge, being the lack of standardized norms for defining, measuring, and ensuring vehicle visibility across various dynamic traffic environments, remains. This lack of awareness of visibility is hindering the development of new regulations for vehicle visibility and the controlled transition to a fully-integrated autonomous future. While current efforts focus on improving sensing technologies like computer vision, LiDAR systems, and sensor fusion development, two key issues remain unresolved: 1 The absence of a representative and realistic three-dimensional color visibility model for measuring and comparing the visibility of complex shapes with large but varying color coated three-dimensional surface areas. 2 The need for enhanced visibility solutions that improve visibility and vehicle detectability for all
Mijnen, Paul W.Moerenburg, Joost H.
The larger size and expanded blind spots of heavy-duty trucks in comparison to passenger cars, create unique challenges for truck drivers navigating narrow roads, such as in urban scenarios. For this reason, the detection of free space around the vehicle is of critical importance, as it has the potential to save lives and reduce operating costs due to less maintenance and downtime. Despite the existence of numerous approaches to free space detection in the literature, few of these have been applied to the trucking sector, disregarding important aspects for these kinds of vehicles such as the altitude at which obstacles are located. This paper aims to present the initial results of our research, a “Not Free Space Warner”, a driving assistance function intended for implementation in series trucks. A methodology is followed to define the characteristics that the perception component of this function shall fulfill. To this end, an analysis of the most critical accidents and common driving
Martinez, CristianPeters, Steven
Image dehazing techniques can play a vital role in object detection, surveillance, and accident prevention, especially in scenarios where visibility is compromised because of light scattering by atmospheric particles. To obtain a high-quality image or as an initial step in processing, it’s crucial to restore the scene’s information from a single image, given that this is an ill-posed inverse problem. The present approach utilized an unsupervised learning approach to predict the transmission map from a hazy image and used YOLOv8n to detect the car from a clear recovered image. The dehazing model utilized a lightweight parallel channel architecture to extract features from the input image and estimate the transmission map. The clear image is recovered using an atmospheric scattering model and given to the YOLOv8n for car detection. By incorporating dark channel prior loss during training, the model eliminates the need for a paired dataset. The proposed dehazing model with fewer
Dave, ChintanPatel, HetalKumar, Ahlad
This document recommends criteria to assure adequate visibility from the flight deck. The flight-deck windshield must provide sufficient external vision to permit the pilot to perform any maneuvers within the operating limits of the aircraft safely and, at the same time, afford an unobstructed internal view of the flight instruments and other critical components and displays from the same eye position.
S-7 Flight Deck Handling Qualities Stds for Trans Aircraft
The Science and Technology Directorate's (S&T) National Urban Security Technology Laboratory (NUSTL) recently brought together emergency responders from across the nation to test unmanned aircraft systems (UAS) from the Blue UAS Cleared List. By providing an aerial vantage point, and creating standoff distance between responders and potential threats, UAS can significantly mitigate safety risks to responders by allowing them to assess and monitor incidents remotely. U.S. Department of Homeland Security, Washington, D.C. In November 2024, the U.S. Department of Homeland Security's (DHS) National Urban Security Technology Laboratory (NUSTL) teamed up with Mississippi State University's (MSU) Raspet Flight Research Laboratory, and DAGER Technology LLC, to conduct an assessment on selected models of cybersecure “Blue UAS.” The drones, including models from Ascent AeroSystems, Freefly Systems, Parrot Drones, Skydio, and Teal Drones, are cybersecure and commercially available to assist
The proportion of pedestrian fatalities due to traffic accidents is higher at night than during the day. Drivers can more easily recognize pedestrians by setting their headlights to high beam, but use of high beam poses the issue of increasing glare for pedestrians. This study proposes a lighting technology that increases the noticeability of pedestrians for drivers and the noticeability of approaching vehicles for pedestrians while at the same time helping to reduce glare for pedestrians. The newly designed lighting enables geometric patterns projection lighting that makes use of projection technology. This geometric pattern projection lighting was compared with conventional low beam and high beam headlights to verify the effectiveness. Tests were conducted on a closed course with the participation of 20 drivers to evaluate the functionality of each headlight type. In these tests, subjects performed specific tasks such as evaluation of pedestrian visibility from the driver’s point of
Kawamura, KazuyukiOshida, Kei
India has one of the highest accident rates in the world. Quite a few accidents have been attributed to poor driver visibility. Driver visibility is an important factor that can help mitigate the risk of accidents. The optimal visibility of in-vehicle controls is also essential for improving driver experience. Optimized driver visibility improves driving comfort and gives confidence to the driver, ensuring the safety of drivers and subsequently that of pedestrians. Driver visibility is an important consideration for vehicle occupant packaging and SAE has defined various standards and regulations for the same. These guidelines are defined considering American anthropometry, helping OEMs create global vehicles with uniform checkpoints. However, due to anthropometric differences, a need was felt to capture and analyze Indian-specific eyellipse and eye points. To measure the eye point of the user in a controlled environment, the interiors of a passenger vehicle were simulated using a
P H, SalmanKalra, PreritaRawat, AshishSharma, DeepakSingh, Ashwinder
Camera matching photogrammetry is widely used in the field of accident reconstruction for mapping accident scenes, modeling vehicle damage from post collision photographs, analyzing sight lines, and video tracking. A critical aspect of camera matching photogrammetry is determining the focal length and Field of View (FOV) of the photograph being analyzed. The intent of this research is to analyze the accuracy of the metadata reported focal length and FOV. The FOV from photographs captured by over 20 different cameras of various makes, models, sensor sizes, and focal lengths will be measured using a controlled and repeatable testing methodology. The difference in measured FOV versus reported FOV will be presented and analyzed. This research will provide analysts with a dataset showing the possible error in metadata reported FOV. Analysts should consider the metadata reported FOV as a starting point for photogrammetric analysis and understand that the FOV calculated from the image
Smith, Connor A.Erickson, MichaelHashemian, Alireza
This study outlines a camera-based perspective transformation method for measuring driver direct visibility, which produces 360-degree view maps of the nearest visible ground points. This method is ideal for field data collection due to its portability and minimal space requirements. Compared with ground truth assessments using a physical grid, this method was found to have a high level of accuracy, with all points in the vehicle front varying less than 0.30 m and varying less than 0.6 m for the A- and B-pillars. Points out of the rear window varied up to 2.4 m and were highly sensitive to differences in the chosen pixel due to their greater distance from the camera. Repeatability through trials of multiple measurements per vehicle and reproducibility through measures from multiple data collectors produced highly similar results, with the greatest variations ranging from 0.19 to 1.38 m. Additionally, three different camera lenses were evaluated, resulting in comparable results within
Mueller, BeckyBragg, HadenBird, Teddy
Off-road vehicles are required to traverse a variety of pavement environments, including asphalt roads, dirt roads, sandy terrains, snowy landscapes, rocky paths, brick roads, and gravel roads, over extended periods while maintaining stable motion. Consequently, the precise identification of pavement types, road unevenness, and other environmental information is crucial for intelligent decision-making and planning, as well as for assessing traversability risks in the autonomous driving functions of off-road vehicles. Compared to traditional perception solutions such as LiDAR and monocular cameras, stereo vision offers advantages like a simple structure, wide field of view, and robust spatial perception. However, its accuracy and computational cost in estimating complex off-road terrain environments still require further optimization. To address this challenge, this paper proposes a terrain environment estimating method for off-road vehicle anticipated driving area based on stereo
Zhao, JianZhang, XutongHou, JieChen, ZhigangZheng, WenboGao, ShangZhu, BingChen, Zhicheng
In the Baja race, off-road vehicles need to run under a variety of real and complex off-road conditions such as pebble road, shell pit, stone bad road, hump, water puddle, etc. In the process of this high-intensity and high-concentration race, the unoptimized design of the cab in ergonomics will easily cause the driver's visual and handling fatigue, so that the driver's attention is not concentrated. Cause the occurrence of security accidents. Moreover, lower back pain, sciatic nerve discomfort, lumbar spine diseases and other occupational diseases are basically caused by uncomfortable driving posture and unreasonable control matching, and these have a lot to do with unreasonable ergonomic design. In order to solve these problems, firstly establish the human body model of the driver, and then build the BSC racing car model by using 3D modeling software Catia. Then use the ergonomics simulation software Jack to analyze the visibility, accessibility and comfort. Based on the simulation
Liu, YuzhouLiu, Silang
Headlight glare remains a persistent problem to the U.S. driving public. Over the past 30 years, vehicle forward lighting and signaling systems have evolved dramatically in terms of styling and lighting technologies used. Importantly, vehicles driven in the U.S. have increased in size during this time as the proportion of pickup trucks and sport-utility vehicles (SUVs) has increased relative to passenger sedans and other lower-height vehicles. Accordingly, estimates of typical driver eye height and the height of lighting and signaling equipment on vehicles from one or two decades ago are unlikely to represent the characteristics of current vehicles in the U.S. automotive market. In the present study we surveyed the most popular vehicles sold in the U.S. and carried out evaluations of the heights of lighting and signaling systems, as well as typical driver eye heights based on male and female drivers. These data may be of use to those interested in understanding how exposure to vehicle
Bullough, John D.
Videos from cameras onboard a moving vehicle are increasingly available to collision reconstructionists. The goal of this study was to evaluate the accuracy of speeds, decelerations, and brake onset times calculated from onboard dash cameras (“dashcams”) using a match-moving technique. We equipped a single test vehicle with 5 commercially available dashcams, a 5th wheel, and a brake pedal switch to synchronize the cameras and 5th wheel. The 5th wheel data served as the reference for the vehicle kinematics. We conducted 9 tests involving a constant-speed approach (mean ± standard deviation = 57.6 ± 2.0 km/h) followed by hard braking (0.989 g ± 0.021 g). For each camera and brake test, we extracted the video and calculated the camera’s position in each frame using SynthEyes, a 3D motion tracking and video analysis program. Scale and location for the analyses were based on a 3D laser scan of the test site. From each camera’s position data, we calculated its speed before braking and its
Flynn, ThomasAhrens, MatthewYoung, ColeSiegmund, Gunter P.
This paper introduces a method to solve the instantaneous speed and acceleration of a vehicle from one or more sources of video evidence by using optimization to determine the best fit speed profile that tracks the measured path of a vehicle through a scene. Mathematical optimization is the process of seeking the variables that drive an objective function to some optimal value, usually a minimum, subject to constraints on the variables. In the video analysis problem, the analyst is seeking a speed profile that tracks measured vehicle positions over time. Measured positions and observations in the video constrain the vehicle’s motion and can be used to determine the vehicle’s instantaneous speed and acceleration. The variables are the vehicle’s initial speed and an unknown number of periods of approximately constant acceleration. Optimization can be used to determine the speed profile that minimizes the total error between the vehicle’s calculated distance traveled at each measured
Snyder, SeanCallahan, MichaelWilhelm, ChristopherJohnk, ChrisLowi, AlvinBretting, Gerald
Headliners are one of the largest components inside an automobile, stretching from the front windshield to the rear windshield. Besides its aesthetic purpose, it contributes to multiple other purposes like housing different components, helps in NVH, defines the interior roominess, and plays a crucial role in defining the deployment of curtain airbag. The headliner also plays a role in meeting regulatory requirements like upward visibility and headroom requirements of the occupants. During the deployment of curtain airbag, it is important that the headliner-pillar interface aids in the easy opening of airbag, with the least hindrance. This is defined by multiple factors like the location of headliner-pillar interface, its distance from the airbag ramp bracket, the position of the inflator, the mountings of the headliner and pillar trims, to name a few. Also, during the deployment of the airbag, it is important that parts such as grabhandle, speaker grilles, etc which are fitted on the
Sabesan, Arvind KochiD., AnanthaKakani, Phani Kumar
Background. In 2022, vulnerable road user (VRU) deaths in the United States increased to their highest level in more than 40 years. At the same time, increasing vehicle size and taller front ends may contribute to larger forward blind zones, but little is known about the role that visual occlusion may play in this trend. Goal. Researchers measured the blind zones of six top-selling light-duty vehicle models (one pickup truck, three SUVs, and two passenger cars) across multiple redesign cycles (1997–2023) to determine whether the blind zones were getting larger. Method. To quantify the blind zones, the markerless method developed by the Insurance Institute for Highway Safety was used to calculate the occluded and visible areas at ground level in the forward 180° arc around the driver at ranges of 10 m and 20 m. Results. In the 10-m forward radius nearest the vehicle, outward visibility declined in all six vehicle models measured across time. The SUV models showed up to a 58% reduction
Epstein, Alexander K.Brodeur, AlyssaDrake, JuwonEnglin, EricFisher, Donald L.Zoepf, StephenMueller, Becky C.Bragg, Haden
Roadside perception technology is an essential component of traffic perception technology, primarily relying on various high-performance sensors. Among these, LiDAR stands out as one of the most effective sensors due to its high precision and wide detection range, offering extensive application prospects. This study proposes a voxel density-nearest neighbor background filtering method for roadside LiDAR point cloud data. Firstly, based on the relatively fixed nature of roadside background point clouds, a point cloud filtering method combining voxel density and nearest neighbor is proposed. This method involves voxelizing the point cloud data and using voxel grid density to filter background point clouds, then the results are processed through a neighbor point frame sequence to calculate the average distance of the specified points and compare with a distance threshold to complete accurate background filtering. Secondly, a VGG16-Pointpillars model is proposed, incorporating a CNN
Liu, ZhiyuanRui, Yikang
Secondary crashes, including struck-by incidents are a leading cause of line-of-duty deaths among emergency responders, such as firefighters, law enforcement officers, and emergency medical service providers. The introduction of light-emitting diode (LED) sources and advanced lighting control systems provides a wide range of options for emergency lighting configurations. This study investigated the impact of lighting color, intensity, modulation, and flash rate on driver behavior while traversing a traffic incident scene at night. The impact of retroreflective chevron markings in combination with lighting configurations, as well as the measurement of “moth-to-flame” effects of emergency lighting on drivers was also investigated. This human factors study recruited volunteers to drive a closed course traffic incident scene, at night under various experimental conditions. The simulated traffic incident was designed to replicate a fire apparatus in the center-block position. The incident
Bullough, John D.Parr, ScottHiebner, EmilySblendorio, Alec
Vehicle localization in enclosed environments, such as indoor parking lots, tunnels, and confined areas, presents significant challenges and has garnered considerable research interest. This paper proposes a localization technique based on an onboard binocular camera system, utilizing binocular ranging and spatial intersection algorithms to achieve active localization. The method involves pre-deploying reference points with known coordinates within the experimental space, using binocular ranging to measure the distance between the camera and the reference points, and applying the spatial intersection algorithm to calculate the camera’s center coordinates, thereby completing the localization process. Experimental results demonstrate that the proposed algorithm achieves sub-meter level localization accuracy. Localization accuracy is significantly influenced by the calibration precision of the binocular camera and the number of reference points. Higher calibration precision and a greater
Feifei, LiHaoping, QiYi, Wei
To improve the accuracy and reliability of short-term prediction of highway visibility level in key scenarios such as short duration and fast changing speed, this paper proposes a short-term prediction method for highway visibility level based on attention mechanism LSTM. Firstly, XGBoost and SHAP methods are used to analyze the factors affecting highway visibility, determine the importance ranking of different influencing factors, and select the factors that have a greater impact on visibility as inputs for the visibility level prediction model. Secondly, based on LSTM as the model foundation network and innovative coupling attention mechanism, a visibility level prediction model based on attention mechanism LSTM is constructed, which can dynamically update the correlation between meteorological feature information at each historical time point and the visibility level at the current prediction time, thereby dividing the importance of information and flexibly capturing important
Ding, ShanshanXiong, ZhuozhiHuang, XuLi, Yurong
This research explores the use of salt gradient solar ponds (SGSPs) as an environmentally friendly and efficient method for thermal energy storage. The study focuses on the design, construction, and performance evaluation of SGSP systems integrated with reflectors, comparing their effectiveness against conventional SGSP setups without reflectors. Both experimental and numerical methods are employed to thoroughly assess the thermal behavior and energy efficiency of these systems. The findings reveal that the SGSP with reflectors (SGSP-R) achieves significantly higher temperatures across all three zones—Upper Convective Zone (UCZ), Non-Convective Zone (NCZ), and Lower Convective Zone (LCZ)—with recorded temperatures of 40.56°C, 54.2°C, and 63.1°C, respectively. These values represent an increase of 6.33%, 11.12%, and 14.26% over the temperatures observed in the conventional SGSP (SGSP-C). Furthermore, the energy efficiency improvements in the UCZ, NCZ, and LCZ for the SGSP-R are
J, Vinoth Kumar
This research aimed to explore the integration of Virtual reality technology in ergonomically testing automotive interior designs. This objective was aimed at ensuring that such technology could be used to ameliorate user comfort through controlled simulations. Existing ergonomic testing methods are often limited when it comes to recreating actual driving situations and quickly repeating design improvements. VR could be used as a solution because its ergonomically tested simulation can be used to provide users with the real experience of driving. The users can be observed while they experience it and asked for their feedback. For this research, an interactive VR environment imitating a 10-minute-long trip through traffic and changing road conditions was created. It was populated by ten users, concatenated equally in men and women, both aged 20-35, representing approximate demographics of workers in the automotive production industry. Participants of the research were asked to use
Natrayan, L.Kaliappan, SeeniappanSwamy Nadh, V.Maranan, RamyaBalaji, V.
Visual perception systems for autonomous vehicles are exposed to a wide variety of complex weather conditions, among which rainfall is one of the weather conditions with high exposure. Therefore, it is necessary to construct a model that can efficiently generate a large number of images with different rainfall intensities to help test the visual perception system under rainfall conditions. However, the existing datasets either do not contain multilevel rainfall or are synthetic images. It is difficult to support the construction of the model. In this paper, the natural rainfall images of different rainfall intensities were first collected and produced a natural multilevel rain dataset. The dataset includes no rain and three levels (light, medium and heavy) of rainfall with the number of 629, 210, 248 and 193 respectively, totaling 1280 images. The dataset is open source and available online via: https://github.com/raydison/natural-multilevel-rain-dataset-NMRD. Subsequently, a
Liu, ZhenyuanJia, TongXing, XingyuWu, JianfengChen, Junyi
Letter from the Guest Editors
van Schijndel, MargrietSciarretta, AntonioOp den Camp, OlafKrosse, Bastiaan
This SAE Recommended Practice establishes three alternate methods for describing and evaluating the truck driver's viewing environment: the Target Evaluation, the Polar Plot and the Horizontal Planar Projection. The Target Evaluation describes the field of view volume around a vehicle, allowing for ray projections, or other geometrically accurate simulations, that demonstrate areas visible or non-visible to the driver. The Target Evaluation method may also be conducted manually, with appropriate physical layouts, in lieu of CAD methods. The Polar Plot presents the entire available field of view in an angular format, onto which items of interest may be plotted, whereas the Horizontal Planar Projection presents the field of view at a given elevation chosen for evaluation. These methods are based on the Three Dimensional Reference System described in SAE J182a. This document relates to the driver's exterior visibility environment and was developed for the heavy truck industry (Class B
Truck and Bus Human Factors Committee
Driving at night presents a myriad of challenges, with one of the most significant being visibility, especially on curved roads. Despite the fact that only a quarter of driving occurs at night, research indicates that over half of driving accidents happen during this period. This alarming statistic underscores the urgent need for improved illumination solutions, particularly on curved roads, to enhance driver visibility and consequently, safety. Conventional headlamp systems, while effective in many scenarios, often fall short in adequately illuminating curved roads, thereby exacerbating the risk of accidents during nighttime driving. In response to this critical issue, considerable efforts have been directed towards the development of alternative technologies, chief among them being Adaptive Front Lighting Systems (AFS). The primary objective of this endeavor is to design and construct a prototype AFS that can seamlessly integrate into existing fixed headlamp systems. Throughout the
T, KarthiG, ManikandanP C, MuruganS, SakthivelN, VinuP, Dineshkumar
Sensata Technologies' booth at this year's IAA Transportation tradeshow included two of the company's Precor radar sensors. The PreView STA79 is a heavy-duty vehicle side-monitoring system launched in May 2024 and designed to comply with Europe-wide blind spot monitoring legislation introduced in June 2024. The PreView Sentry 79 is a front- and rear-monitoring system. Both systems operate on the 79-GHz band as the nomenclature suggests. PreView STA79 can cover up to three vehicle zones: a configurable center zone, which can monitor the length of the vehicle, and two further zones that can be independently set to align with individual customer needs. The system offers a 180-degree field of view to eliminate blind spots along the vehicle sides and a built-in measurement unit that will increase the alert level when turning toward an object even when the turn indicator is not used. The system also features trailer mitigation to reduce false positive alerts on the trailer when turning. The
Kendall, John
Items per page:
1 – 50 of 857