Browse Topic: Accident reconstruction

Items (827)
The Autocycle is a style of vehicle that most often utilizes a reverse-tricycle design with two front wheels and a single rear wheel. Modern autocycles in the United States are often utilized in a recreational role. This work presents physical measurements of two modern autocycles for use in accident reconstruction and pursues a deeper understanding of the unique attributes and handling associated with these vehicles. Vehicles were used to measure physical properties and subjected to cornering tests presented herein, and the data is compared to that for a conventional automobile. Observations on tire scuff marks are made from cornering tests unique to these vehicles. Strengths and challenges with this type of vehicle design are presented for various use cases as compared to conventional automobiles. Data and knowledge from this study are published to aid accident reconstruction efforts.
Warner, WyattSwensen, GrantWarner, Mark
The integration of mobile device data in accident/crash/collision reconstruction methodologies offers significant potential in analyzing collision events. This study evaluates the utility of iPhone-recorded data, specifically Global Navigation Satellite System (GNSS) position and speed data, along with Coordinated Universal Time (UTC) based time and date information associated with application usage and device activity events. By conducting controlled tests, the accuracy, precision, and reliability of iPhone GNSS data were compared against high-accuracy reference systems, including a Racelogic VBox Video HD2 25 Hz GPS data logger and VBox Sport 25 Hz GPS data logger. The synchronicity between recorded app events and device activities with physical events was also analyzed to assess the temporal resolution of the data. Results highlight the strengths and limitations of iPhone data for reconstructing crash events, including potential discrepancies in GNSS accuracy under varying
Burgess, ShanonPhy, LanceLevan, Matthew
A total of 148 tests were conducted to evaluate the Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) systems in five different Tesla Model 3 vehicles between model years 2018 and 2020 across four calendar years. These tests involved stationary vehicle targets, including a foam Stationary Vehicle Target (SVT), a Deformable Stationary Vehicle Target (DSVT), a live vehicle with brake lights, and a SoftCar360 designed for high-speed impact tests. The evaluations were conducted at speeds of 35, 50, 60, 65, 70, 75, and 80 miles per hour (mph) during both daytime and nighttime conditions and utilized early and medium FCW settings. These settings, part of Tesla's Collision Avoidance AssistTM, modify object detection alerts and the timing of visual and auditory warnings issued to drivers. The 2018 to 2020 vehicles initially utilized cameras, radar and ultrasonic sensors (USS) for object detection. Tesla updated their Autoilot software and detection algorithms to a vision
Harrington, ShawnNagarajan, Sundar Raman
Apple’s mobile phone LiDAR capabilities can be used with multiple software applications to capture the geometry of vehicles and smaller objects. The results from different software have been previously researched and compared to traditional ground-based LiDAR. However, results were inconsistent across software applications, with some software being more accurate and others being less accurate. (Technical Paper 2023-01-0614. Miller, Hashemian, Gillihan, Benes.) This paper builds upon existing research by utilizing the updated LiDAR hardware that Apple has added to its iPhone 15 smartphone lineup. This new hardware, in combination with the software application PolyCam, was used to scan a variety of crashed vehicles. These crashed vehicles were also scanned using a FARO 3D scanners and Leica RTC 360 scanners, which have been researched extensively for their accuracy. The PolyCam scans were compared to FARO and Leica scans to determine accuracy for point location and scaling. Previous
Miller, Seth HigginsStogsdill, MichaelMcWhirter, Seth
It is becoming increasingly common for bicyclists to record their rides using specialized bicycle computers and watches, the majority of which save the data they collect using the Flexible and Interoperable Data Transfer (.fit) Protocol. The contents of .fit files are stored in binary and thus not readily accessible to users, so the purpose of this paper is to demonstrate the differences induced by several common methods of analyzing .fit files. We used a Garmin Edge 830 bicycle computer with and without a wireless wheel speed sensor to record naturalistic ride data at 1 Hz. The .fit files were downloaded directly from the computer, uploaded to the chosen test platforms - Strava, Garmin Connect, and GoldenCheetah - and then exported to .gpx, .tcx and .csv formats. Those same .fit files were also parsed directly to .csv using the Garmin FIT Software Developer Kit (SDK) FitCSVTool utility. The data in those .csv files (henceforth referred to as “SDK data”) were then either directly
Sweet, DavidBretting, Gerald
Shadow positions can be useful in determining the time of day that a photograph was taken and determining the position, size, and orientation of an object casting a shadow in a scene. Astronomical equations can predict the location of the sun relative to the earth, and therefore the position of shadows cast by objects, based on the location’s latitude and longitude as well as the date and time. 3D computer software includes these calculations as a part of their built-in sun systems. In this paper, the authors examine the sun system in the 3D modeling software 3ds Max to determine its accuracy for use in accident reconstruction. A parking lot was scanned using a FARO LiDAR scanner to create a point cloud of the environment. A camera was then set up on a tripod at the environment, and photographs were taken at various times throughout the day from the same location. This environment was 3D modeled in 3ds Max based on the point cloud, and the sun system in 3ds Max was configured using the
Barreiro, EvanErickson, MichaelSmith, ConnorCarter, NealHashemian, Alireza
Toyota vehicles equipped with Toyota Safety Sense (TSS) can record detailed information surrounding various driving events, including crashes. Often, this data is employed in accident reconstruction. TSS data is comprised of three main categories: Vehicle Control History (VCH), Freeze Frame Data (FFD), and image records. Because the TSS data resides in multiple Electronic Control Units (ECUs), the data recording is susceptible to catastrophic power loss. In this paper, the effects of a sudden power loss on the VCH, FFD, and images are studied. Events are triggered on a TSS 2.5+ equipped vehicle by driving toward a stationary target. After system activation, a total power loss is induced at various delays after activation. Results show that there is a minimum time required after system initiation in order to obtain full VCH, FFD, and image records. Power losses occurring within this time frame produce incomplete records. Data accuracy is unaffected, even in partial records.
Getz, CharlesDiSogra, MatthewSpivey, HeathJohnson, TaylorPatel, Amit
When vehicle accidents occur, investigators rely on event data recorders for accident investigations. However current event data recorders do not support accident investigation involving automated or self-driving vehicles when there is state information that needs to be recorded, for example ADS modes, changes in the ODD that the vehicle operates under, and the various states of vehicle features such as intelligent cruise control, automated lane changes, autonomous emergency braking, and others. In this paper, we propose a model to design new types of event data recorders that supports accident investigations involving automated vehicles when there is state information to be recorded. The model is generic enough to be adapted to any automation level and any set of automated vehicle functional features. The model has been instantiated to a specific ADAS system.
Pimentel, Juan
Recreational Off-Highway Vehicles (ROVs) also referred to as “side-by-side” vehicles are involved in accidents / crashes due to driver error. This can often be attributed to an operator’s inexperience and failure to differentiate vehicle handling characteristics from that of a traditional automobile. Decelerating testing of ROVs on various surfaces has not been published for these types of vehicles. This work presents test data for use in accident reconstruction and examines the dynamic performance of two exemplar ROVs on various driving surfaces including asphalt, packed dirt, loose gravel and loose, deep sand. Exemplar vehicles, specifically a 4-person “pure-sport” ROV and a single bench utility ROV, are used to gather practical deceleration performance data. Deceleration data comparing tests with fully-locked brakes to tests where the operator manually modulates the brakes to achieve maximum deceleration without brake lockup are also included. The data presented herein is
Swensen, GrantWarner, WyattWarner, Mark
The braking performance of newer anti-lock braking system (ABS) equipped vehicles on roads with varying wetness levels is not well studied. Two late-model ABS-equipped vehicles were used to perform ABS-engaged braking tests on dry and wet asphalt and concrete surfaces from which vehicle speed and deceleration as a function of time were calculated. Tests were initially conducted on a dry surface before a water truck distributed water onto the road to create a wet road condition. A continuous series of tests were then performed until the road dried and the cycle was repeated multiple times. Across all tests of both vehicles on both road surfaces, deceleration levels generally decreased when the road was wet and returned to dry levels only when less than 25% of the road surface remained wet. Also, wet deceleration levels were high compared to the historical values used for wet roads. These findings provide a useful and readily identifiable boundary between what can be considered a dry and
Miller, IanKing, DavidSiegmund, Gunter
The accident reconstruction community frequently uses Terrestrial LiDAR (TLS) to capture accurate 3D images of vehicle accident sites. This paper compares the accuracy, workflow, benefits, and challenges of Unmanned Aerial Vehicle (UAV) LiDAR, or Airborne Laser Scanning (ALS), to TLS. Two roadways with features relevant to accident reconstruction were selected for testing. ALS missions were conducted at an altitude of 175 feet and a velocity of 4 miles per hour at both sites, followed by 3D scanning using TLS. Survey control points were established to minimize error during cloud-to- cloud TLS registration and to ensure accurate alignment of ALS and TLS point clouds. After data capture, the ALS point cloud was analyzed against the TLS point cloud. Approximately 80% of ALS points were within 1.8 inches of the nearest TLS point, with 64.8% at the rural site and 59.7% at the suburban site within 1.2 inches. These findings indicate that UAV-based LiDAR can achieve comparable accuracy to TLS
Foltz, StevenTerpstra, TobyClarson, Julia
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 validates the use of the pedestrian multibody model in the simulation software PC-Crash. If reasonable inputs are used, the pedestrian model will yield accurate simulations of pedestrian collisions, particularly in terms of accurately simulating the contact points between the pedestrian and the vehicle and in predicting the throw distance of the pedestrian. This study extends prior studies of the PC-Crash pedestrian multibody model by simulating additional staged collisions, by comparing the results of the model to widely utilized throw distance equations, by providing guidance on inputs for the pedestrian multibody, and by providing documentation of the characteristics of the multibody pedestrian. In addition, two new staged pedestrian collisions are discussed and simulated. This study demonstrates the following: (1) The center of gravity height of the PC-Crash pedestrian model is comparable to the center of gravity height reported for pedestrians in anthropometric data. (2
Rose, NathanSmith, ConnorCarter, NealMetanias, Andrew
Abstract 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
Snyder, SeanCallahan, MichaelWilhelm, ChristopherJohnk, ChrisLowi, AlvinBretting, Gerald
Rear impacts make up a significant portion of crashes in the United States. To date, regulations on rear impacts have focused on fuel system integrity and seat performance, while most research has focused on seat performance in relation to occupants’ injuries, with some analyses of crash severity and seat belt effects. The performance of seats and seat belts may vary depending on the size of the occupant. Understanding how occupant characteristics, as well as crash scenarios, affect injury outcomes can show opportunities for further enhancements in rear impact occupant protection. This paper presents analyses using survey weighted logistic regression models to understand the factors affecting serious injury outcomes (i.e., MAIS 3+) in rear impacts, exploring the potential for improving occupant outcomes. Three separate models are evaluated, focusing on 1) overall injury level, 2) head, neck, and cervical-spine injuries, and 3) thorax, abdomen, thoracic- and lumbar-spine injuries for
Greib, JoshuaJurkiw, ReneeKryzaniwskyj, TanjaOwen, SusanVan Rooyen, PaulWhelan, StaceyWilliamson, John
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.
Theory and principles of occupant protection for automobiles in rear-end collisions have experienced significant evolution over the decades. Performance of the seatback, specifically the stiffness of the structure, during such a collision has been a subject of particular interest and debate among design engineers, accident reconstruction experts, critics, etc. The majority of current seat designs rely on plastic deformation of the seatback structure to protect the occupant from the dynamics of the crash. In attempt to highlight and provide background information for understanding this subject, this work highlights significant events, research, and publications over the past five decades to illustrate how this subject, automobile design, government regulation and public opinion has evolved. It is observed that technology and design for improving rear-impact protection has received less attention than collisions of other principal directions of force. The different types of
Warner, Wyatt
Accurate reconstruction of vehicle collisions is essential for understanding incident dynamics and informing safety improvements. Traditionally, vehicle speed from dashcam footage has been approximated by estimating the time duration and distance traveled as the vehicle passes between reference objects. This method limits the resolution of the speed profile to an average speed over given intervals and reduces the ability to determine moments of acceleration or deceleration. A more detailed speed profile can be calculated by solving for the vehicle’s position in each video frame; however, this method is time-consuming and can introduce spatial and temporal error and is often constrained by the availability of external trackable features in the surrounding environment. Motion tracking software, widely used in the visual effects industry to track camera positions, has been adopted by some collision reconstructionists for determining vehicle speed from video. This study examines the
Perera, NishanGriffiths, HarrisonPrentice, Greg
Photogrammetry is a commonly used type of analysis in accident reconstruction. It allows the location of physical evidence, as shown in photographs and video, and the position and orientation of vehicles, other road users, and objects to be quantified. Lens distortion is an important consideration when using photogrammetry. Failure to account for lens distortion can result in inaccurate spatial measurements, particularly when elements of interest are located toward the edges and corners of images. Depending on whether the camera properties are known or unknown, various methods for removing lens distortion are commonly used in photogrammetric analysis. However, many of these methods assume that lens distortion is the result of a spherical lens or, more rarely, is solely due to distortion caused by other known lens types and has not been altered algorithmically by the camera. Today, several cameras on the market algorithmically alter images before saving them. These camera systems use
Pittman, KathleenMockensturm, EricBuckman, TaylorWhite, Kirsten
Bendix® EC-80™ and certain EC-60™ ABS control units contain an event data recorder called the Bendix® Data Recorder (BDR). Raw BDR data is obtained using commercially available software, however, the translation of the raw data into an event report has only been performed by the manufacturer. In this paper, the raw data structures of the commercially available datasets are examined. It is demonstrated that the data follows uniform and repeatable patterns. The raw BDR data is converted into a conventional report and then validated against translation reports performed by the manufacturer. The techniques outlined in this research allow investigators to access and analyze BDR records independently of the manufacturer and in a way previously not possible.
DiSogra, MatthewHirsch, JeffreyYeakley, Adam
Video analysis plays a major role in many forensic fields. Many articles, publications, and presentations have covered the importance and difficulty in properly establishing frame timing. In many cases, the analyst is given video files that do not contain native metadata. In other cases, the files contain video recordings of the surveillance playback monitor which eliminates all original metadata from the video recording. These “video of video” recordings prevent an analyst from determining frame timing using metadata from the original file. However, within many of these video files, timestamp information is visually imprinted onto each frame. Analyses that rely on timing of events captured in video may benefit from these imprinted timestamps, but for forensic purposes, it is important to establish the accuracy and reliability of these timestamps. The purpose of this research is to examine the accuracy of these timestamps and to establish if they can be used to determine the timing
Molnar, BenjaminTerpstra, TobyVoitel, Tilo
Prior research has validated a reliable method of determining vehicle speed using the audio data and a known wheelbase of a test vehicle captured by dash camera audio. However, it has been found that dash camera audio may record a frequency that varies with the test vehicle’s speed. Investigating the origin of this frequency revealed the horn effect phenomena, which has been well known in research by the tire industry. Independent research identified a frequency generated by the rotating tires when a certain speed threshold was reached by the test vehicle. The research concluded that the tread pattern of the tire in contact with the roadway surface generated a frequency that varied with vehicle speed. However, research using the audio from a dash camera to determine vehicle speed from that specific varying frequency for forensic purposes has not been investigated in prior research. The purpose of this study was to outline, test, and confirm the source of the wheel speed frequency as a
Vega, Henry V.Ngo, Long JustinHatab, ZiadCornetto, AnthonyEngleman, KrystinaHunter, Eric
This paper is a continuation of a previous effort to evaluate the post-impact motion of vehicles with high rotational velocity within various vehicle dynamic simulation softwares. To complete this goal, this paper utilizes a design of experiments (DOE) method. The previous papers analyzed four vehicle dynamic simulation software programs; HVE (SIMON and EDSMAC4), PC-Crash and VCRware, and applied the DOE to determine the most sensitive factors present in each simulation software. This paper will include Virtual Crash into this methodology to better understand the significant variables present within this simulation model. This paper will follow a similar DOE to that which was conducted in the previous paper. A total of 32 trials were conducted which analyzed ten factors. Aerodynamics, a factor included in the previous DOE, was not included within this DOE because it does not exist within Virtual Crash. The same three response variables from the previous DOE were measured to determine
Roberts, JuliusCivitanova, NicholasStegemann, JacobBuzdygon, DavidThobe, Keith
During a pitch-over event, the forward momentum of the combined bicycle and rider is suddenly arrested causing the rider and bicycle to rotate about the front wheel and also possibly propelling the rider forward. This paper examines the pitch-over of a bicycle and rider using two methods different from previous approaches. One method uses Newton’s 2nd Law directly and the other method uses the principle of impulse and momentum, the integrated form of Newton’s 2nd Law. The two methods provide useful equations, contributing to current literature on the topic of reconstructing and analyzing bicycle pitch-over incidents. The analysis is supplemented with Madymo simulations to evaluate the kinematics and kinetics of the bicycle and rider interacting with front wheel obstructions of different heights. The effect of variables such as rider weight, rider coupling to the bicycle, bicycle speed, and obstruction height on resulting kinematics were evaluated. The analysis shows that a larger
Brach, R. MatthewKelley, MireilleVan Poppel, Jon
The primary function of an Airbag Control Module (ACM), referred to as the Sensing and Diagnostic Module (SDM) by General Motors (GM), is to detect crashes, discriminate crashes, evaluate crash severities, deploy the appropriate restraints, including airbags and pretensioners, and perform system diagnostics. A secondary function of the SDM is to act as an Event Data Recorder (EDR) which records data during the time periods just prior to (pre-crash) and during a crash event. This data consists of restraint and vehicle system data which is collected, processed, and stored in the EDR. Data stored in the EDR is intended to be retrieved after a crash. This data provides operational information on the vehicle’s occupant protection system and other vehicle systems to assess system performance, aid in crash reconstruction, and support improved vehicle safety. A series of vehicle test maneuvers were conducted while injecting a non-deployment crash pulse directly into the SDM to cause the SDM to
Smyth, BrianCrosby, Charles LBickhaus, RyanSmith, JamesEdmunds, DustinFloyd, DonaldModi, VipulOutlaw, RaShawndra D.Wright, Jeff
Dash cameras (dashcams) can provide collision reconstructionists with quantifiable vehicle position and speed estimates. These estimates are achieved by tracking 2D video features with camera-tracking software to solve for the time history of camera position, and speed can then be calculated from the position-time history. Not all scenes have the same geometric features in quality or abundance. In this study, we compared the vehicle position and derived-speed estimates from dashcam video for different numbers and spatial distributions of tracked features that mimicked the continuum between barren environments and feature-rich environments. We used video from a dashcam mounted in a vehicle undergoing straight-line emergency braking. The surrounding environment had abundant trackable features on both sides of the road, including road markings, streetlights, signs, trees, and buildings. We first created a reference solution using SynthEyes, a 3D camera- and object-tracking program, and
Young, ColeAhrens, MatthewFlynn, ThomasSiegmund, Gunter P.
Bicycle computers record and store kinematic and physiologic data that can be useful for forensic investigations of crashes. The utility of speed data from bicycle computers depends on the accurate synchronization of the speed data with either the recorded time or position, and the accuracy of the reported speed. The primary goals of this study were to quantify the temporal asynchrony and the error amplitudes in speed measurements recorded by a common bicycle computer over a wide area and over a long period. We acquired 96 hours of data at 1-second intervals simultaneously from three Garmin Edge 530 computers mounted to the same bicycle during road cycling in rural and urban environments. Each computer recorded speed data using a different method: two units were paired to two different external speed sensors and a third unit was not paired to any remote sensors and calculated its speed based on GPS data. We synchronized the units based on the speed signals and used one of the paired
Booth, Gabrielle R.Siegmund, Gunter P.
Testing was conducted to evaluate the performance of the 2020 Jeep Grand Cherokee’s Forward Collision Warning (FCW) and Automatic Emergency Braking (AEB) collision mitigation systems at speeds between 35 and 70 miles per hour (mph). Two different 2020 Jeep Grand Cherokee’s were utilized under varying testing conditions in order to evaluate the performance of their collision mitigation systems. A total of 40 tests were conducted: 29 tests were conducted during daytime and 11 tests were conducted at nighttime. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning that was presented to the driver. In addition, the testing quantified the TTC response of the Automatic Emergency Braking (AEB) system including the timing and magnitude of the automatic braking response. The results of the testing add higher speed FCW and AEB testing scenarios to the database of publicly available tests for the 2020 Jeep Grand Cherokee.
Harrington, ShawnLieber, VictoriaNagarajan, Sundar Raman
Testing was conducted in daytime and nighttime conditions to evaluate the performance of the Automatic Emergency Braking and Forward Collision Warning systems present on both a 2020 and 2022 Kia Telluride. The 2022 Kia Telluride was tested during the day at speeds between 35 and 70 miles per hour, while the 2020 Kia Telluride was tested both during the day and at night at speeds between 35 and 60 miles per hour (mph). The daytime testing of both the 2020 and 2022 Kia Telluride utilized a foam stationary vehicle target. The nighttime testing of the 2020 Kia Telluride utilized a live 2006 Chevrolet Tahoe as the target with the brake lights on. Testing measured the Time to Collision (TTC) values of the visual/audible component of the Forward Collision Warning (FCW) that was presented to the driver. Further, testing also quantified the timing and magnitude of the two-phase response of the Automatic Emergency Braking (AEB) system. The results of both sets of testing add higher speed FCW and
Harrington, ShawnPatrick-Moline, PeytonNagarajan, Sundar Raman
The analysis of heterogeneous effects on traffic crashes is crucial for understanding their causal mechanisms and enhancing targeted safety management strategies. However, current methodologies for modeling crash heterogeneous effects lack smooth methods for selecting optimal controls. This study proposes an intuitive variable selection method to improve heterogeneity analysis of crash data, as well as performance evaluation and validation tests. The method utilizes causal discovery algorithms to obtain causal diagrams for selecting confounders, moderators, and neutral control factors in observational collision data. The effectiveness and performance of these methods are assessed through the quality of Heterogeneous Treatment Effects (HTE) estimation. Using a real-world highway crash data, the proposed variable selection process based on causal framework is illustrated. Results indicate that most HTE estimation models perform well in terms of goodness-of-fit and robustness when
Liang, XiaoxiLi, ShuangXu, NuoGuo, XiuchengPu, Ziyuan
Records of traffic accidents contain a wealth of information regarding accident causes and consequences. It provides a valuable data foundation for accident analysis. The diversity and complexity of textual data pose significant challenges in knowledge extracting. Previous research primarily relies on Natural Language Processing (NLP) to extract knowledge from texts and uses knowledge graphs (KGs) to store information in a structured way. However, the process based on NLP typically necessitates extensive annotated datasets for model training, which is complex and time-consuming. Moreover, the application of traffic accident knowledge graphs by direct information querying within the graph requiring complex commands, which leads to poor interaction capabilities. In this study, we adapt an innovative approach integrates Large Language Models (LLMs) for the construction and application of a traffic accident knowledge graph. Based on the defined schema layer of the traffic accident
Hou, YingqiShao, YichangHan, ZhongyiYe, Zhirui
This paper studies design parameters, selection of materials and structural analysis for an All-Terrain Vehicle (ATV) BAJA roll cage at the event site in any possible situation. SolidWorks 2022 was used for creating the prototype of the roll cage and then both static structural as well as dynamic crash analysis for the roll cage was done using Altair HyperWorks 2023 for various collisions like front, rear, side, rollover, torsional, front bump, rear bump, front roll over, side roll over and rear roll over. In addition to their corresponding deformation, Von Mises stresses were observed and a safety factor was calculated for these load cases which was found to be in the range of 1.5 to 3. Without reducing the roll cage’s strength, the roll cage designed for a four-wheel drive configuration is developed with driver comfort and safety in mind. Finding the optimal safety factor is the core objective of the analysis, as it ensures in any situation, the ATV’s roll cage will stay secure.
L, Ravi KumarSanjay P, ChiranjeevT J, Pravin ChanderMoses J, JebishD, ParthesunG, Sureshmani
Background: Road accident severity estimation is a critical aspect of road safety analysis and traffic management. Accurate severity estimation contributes to the formulation of effective road safety policies. Knowledge of the potential consequences of certain behaviors or conditions can contribute to safer driving practices. Identifying patterns of high-severity accidents allows for targeted improvements in terms of overall road safety. Objective: This study focuses on analyzing road accidents by utilizing real data, i.e., US road accidents open database called “CRSS.” It employs advanced machine learning models such as boosting algorithms such as LGBM, XGBoost, and CatBoost to predict accident severity classification based on various parameters. The study also aims to contribute to road safety by providing predictive insights for stakeholders, functional safety engineering community, and policymakers using KABCO classification systems. The article includes sections covering
Babaev, IslamMozolin, IgorGarikapati, Divya
The objectives of this study were to provide insights on how injury risk is influenced by occupant demographics such as sex, age, and size; and to quantify differences within the context of commonly-occurring real-world crashes. The analyses were confined to either single-event collisions or collisions that were judged to be well-defined based on the absence of any significant secondary impacts. These analyses, including both logistic regression and descriptive statistics, were conducted using the Crash Investigation Sampling System for calendar years 2017 to 2021. In the case of occupant sex, the findings agree with those of many recent investigations that have attempted to quantify the circumstances in which females show elevated rates of injury relative to their male counterparts given the same level bodily insult. This study, like others, provides evidence of certain female-specific injuries. The most problematic of these are AIS 2+ and AIS 3+ upper-extremity and lower-extremity
Dalmotas, DainiusChouinard, AlineComeau, Jean-LouisGerman, AlanRobbins, GlennPrasad, Priya
The accuracy of collision severity data recorded by event data recorders (EDRs) has been previously measured primarily using barrier impact data from compliance tests and experimental low-speed impacts. There has been less study of the accuracy of EDR-based collision severity data in real-world, vehicle-to-vehicle collisions. Here we used 189 real-world front-into-rear collisions from the Crash Investigating Sampling System (CISS) database where the EDR from both vehicles recorded a severity to examine the accuracy of the EDR-reported speed changes. We calculated relative error between the EDR-reported speed change of each vehicle and a speed change predicted for that same vehicle using the EDR-reported speed change of the other vehicle and conservation of momentum. We also examined the effect of vehicle-type, mass ratio, and pre-impact braking on the relative error in the speed changes. Overall, we found that the common practice of using the bullet vehicle’s EDR-reported speed change
Fix, RyanWilkinson, CraigSiegmund, Gunter P.
Video of an event recorded from a moving camera contains information not only useful for reconstructing the locations and timing of an event, but also the velocity of the camera attached to the moving object or vehicle. Determining the velocity of a video camera recording from a moving vehicle is useful for determining the vehicle’s velocity and can be compared with speeds calculated through other reconstruction methods, or to data from vehicle speed monitoring devices. After tracking the video, the positions and speeds of other objects within the video can also be determined. Video tracking analysis traditionally has required a site inspection to map the three-dimensional environment. In instances where there have been significant site changes, where there is limited or no site access, and where budgeting and timing constraints exist, a three-dimensional environment can be created using publicly available aerial imagery and aerial LiDAR. This paper presents a methodology for creating
Terpstra, TobyMcDonough, SeanHelms, EthanBeier, StevenHessell, David
Video evidence in collision reconstruction has become a common foundation for vehicle position and speed analyses. The goal of this study was to explore how the uncertainty of these position/speed analyses is affected by various camera-, scene-, and vehicle-related properties. To achieve this goal, we quantified how the size and aspect ratio of pixels in the pixel grid change as a result of correcting for lens distortion and projecting the pixel grid onto a real-world surface captured by the image. Relying on both general and case-specific examples, we used Monte Carlo analyses to explore how uncertainty can be calculated and how it varies for different measurements and different camera-, scene-, and vehicle-related properties. We found that i) the aspect ratio of image pixels projected onto a road surface can vary by multiple orders of magnitude over an entire image and generally increases rapidly as the projected pixel nears the horizon; ii) the uncertainty associated with the real
Young, ColeFlynn, ThomasMiller, IanSiegmund, Gunter P.
A and B stiffness coefficients to model the frontal stiffness of vehicles is a commonly used and accepted technique within the field of collision reconstruction. Methods for calculating stiffness coefficients rely upon examining the residual crush of a vehicle involved in a crash test. When vehicles are involved in a collision, portions of the crushed vehicle structures rebound from their maximum dynamic crush position. Once the vehicle structures have finished rebounding, the remaining damage is called the residual crush. A problem can arise when the plastic bumper cover rebounds more than the vehicle's structural components, resulting in an air gap between the structural components and the plastic bumper cover. Most modern New Car Assessment Program (NCAP) tests quantify crush in the test reports based on the deformed location of the plastic bumper cover and not the structural components behind the plastic bumper cover. This results in an underreporting of the actual residual crush
Neal, JosephLipscomb, MatthewFunk, Charles
In 2021, 412,432 road accidents were reported in India, resulting in 153,972 deaths and 384,448 injuries. India has the highest number of road fatalities, accounting for 11% of the global road fatalities. Therefore, it is important to explore the underlying causes of accidents on Indian roads. The objective of this study is to identify the factors inherent in accidents in India using clustering analysis based on self-organizing maps (SOM). It also attempts to recommend some countermeasures based on the identified factors. The study used Indian accident data collected by members of ICAT-ADAC (International Centre for Automotive Technology - Accident Data Analysis Centre) under the ICAT-RNTBCI joint project approved by the Ministry of Heavy Industries, Government of India. 210 cases were collected from the National Highway between Jaipur and Gurgaon and 239 cases from urban and semi-urban roads around Chennai were used for the analysis. Based on this study, the following results were
Vimalathithan, KulothunganRao K M, PraneshVallabhaneni, PratapnaiduSelvarathinam, VivekrajManoharan, JeyabharathPal, ChinmoyPadhy, SitikanthaJoshi, Madhusudan
Creating a 3-dimensional environment using imagery from small unmanned aerial systems (sUAS, or unmanned aerial vehicles -UAVs, or colloquially, drones) has grown in popularity recently in accident reconstruction. In this process, ground control points are placed at an accident scene and an sUAS is flown over an accident site and a series of overlapping, high resolution images are taken of the site. Those images and ground control points are then loaded onto a computer and processed using photogrammetric software to create a 3-dimensional point cloud or mesh of the site, which then can be used as a tool for recreating an accident scene. Many software packages have been created to perform these tasks, and in this paper, the authors examine RealityCapture, a newer photogrammetric software, to evaluate its accuracy for the use in accident reconstruction. It is the authors’ experience that RealityCapture may at times produce point clouds with less noise that other software packages. To do
Barreiro, EvanCarter, Neal
Testing was conducted at four speeds – 35, 50, 60, and 70 mph – to evaluate the performance of the audible and visual forward collision warning (FCW) component of the pre-collision system (PCS) in a 2020 Toyota RAV4 and a 2020 Toyota Camry. Both vehicles were tested in daytime conditions while approaching a Stationary Vehicle Target (SVT). The 2020 Toyota Camry was also tested in nighttime conditions while approaching a live stationary vehicle. Testing measured the time to collision (TTC) values at the issuance of the FCW, the distance from the test vehicles to the target at FCW, and the speed of the test vehicle at FCW utilizing Racelogic VBOX data acquisition systems. A comparison of the performance of the FCW component of two different generations of Toyota Safety Sense – P versus 2.0 – was also made. The results of the testing add higher speed scenarios to the database of publicly available tests from sources like the Insurance Institute for Highway Safety (IIHS), which currently
Harrington, ShawnAguirre, Roberto
Shadow positions can be useful in determining the time of day that a photograph was taken and determining the position, size, and orientation of an object casting a shadow in a scene. Astronomical equations can predict the location of the sun relative to the earth, and therefore the position of shadows cast by objects, based on the location’s latitude and longitude as well as the date and time. 3D computer software have begun to include these calculations as a part of their built-in sun systems. In this paper, the authors examine the sun system in the 3D modeling software Blender to determine its accuracy for use in accident reconstruction. A parking lot was scanned using Faro LiDAR scanner to create a point cloud of the environment. A camera was then set up on a tripod at the environment and photographs were taken at various times throughout the day from the same location in the environment. This environment was then 3D modeled in Blender based on the point cloud, and the sun system
Barreiro, EvanCarter, NealHashemian, Alireza
When investigating traffic accidents, it is important to determine the causes. To do so, it is necessary to reconstruct the accident situation accurately and in detail using objective and diverse information. We propose a method for reconstructing the accident situation (“reconstruction method”) which consists of rebuilding the situation immediately before the collision (“pre-crash situation”) using data collected during that time by an event data recorder (EDR) and a dashboard camera (DBC) onboard one or both of the vehicles involved. First, the vehicle’s traveling trajectory was integrally calculated using the vehicle speed and yaw rate recorded by the EDR, each point along the trajectory being linked to the EDR data. After being combined with the DBC’s video data, the trajectory was projected onto the road surface around the accident site, which allowed us not only to display on a single road map the vehicle’s traveling trajectory, but also to provide, on each point along the
Matsumura, HidekiSugiyama, MotokiIWATA, Takekazu
This paper validates the single-track vehicle driver model available in PC-Crash simulation software. The model is tested, and its limitations are described. The introduction of this model eliminated prior limitations that PC-Crash had for simulating motorcycle motion. Within PC-Crash, a user-defined path can be established for a motorcycle, and the software will generate motion consistent with the user-defined path (within the limits of friction and stability) and calculate the motorcycle lean (roll) generated by following that path at the prescribed speed, braking, or acceleration levels. In this study, the model was first examined for a simple scenario in which a motorcycle traversed a pre-defined curve at several speeds. This resulted in the conclusion that the single-track driver model in PC-Crash yielded motorcycle lean angles consistent with the standard, simple lean angle formula widely available in the literature. The PC-Crash calculations did not account for the width of the
Palmer, JacobRose, Nathan A.Smith, ConnorWalter, KevinHashemian, Alireza
The on-board emergency call system with accurate occupant injury prediction can help rescuers deliver more targeted traffic accident rescue and save more lives. We use machine learning methods to establish, train, and validate a number of classification models that can predict occupant injuries (by determining whether the MAIS (Maximum Abbreviated Injury Scale) level is greater than 2) based on crash data, and ranked the correlation of some factors affecting vehicle occupant injury levels in accidents. The optimal model was selected by the model prediction accuracy, and the Grid Search method was used to optimize the hyper-parameters for the model. The model is based on 2799 two-vehicle collision accident data from NHTSA CISS (The Crash Investigation Sampling System of NHTSA) traffic accident database.The results show that the model achieves high-precision prediction of occupant injury MAIS level (recall rate 0.8718, AUC(Area under Curve) 0.8579) without excluding vehicle model, and
Huida, ZhangLiu, YuRui, YangWu, XiaofanFan, TiqiangWan, Xinming
Reconstruction of inline crashes between vehicles with a low closing speed, so-called “low speed” crashes, continues to be a class of vehicle collisions that reconstructionists require specific methods to handle. In general, these collisions tend to be difficult to reconstruct due primarily to the lack of, or limited amount of, physical evidence available after the crash. Traditional reconstruction methods such as impulse-momentum (non-residual damage based) and CRASH3 (residual damage based) both are formulated without considering tire forces of the vehicles. These forces can be important in this class of collisions. Additionally, the CRASH3 method depends on the use of stiffness coefficients for the vehicles obtained from high-speed crash tests. The question of the applicability of these (high-speed) stiffness coefficients to collisions producing significantly less deformation than experimental crashes on which they are generated, raises questions of the applicability. An alternative
Brach, MatthewStegemann, JacobManuel, Emmanuel JayCivitanova, Nicholas
Wrap around distance (WAD) is an important index to evaluate the contact position between pedestrian head and vehicle, and is also one of the key parameters of pedestrian accident reconstruction. The purpose of this paper is to explore whether the pedestrian headform testcan reflect the distribution of head injury in the real world. Firstly, in order to study the distribution of pedestrian head WAD in road accidents in China, a head WAD prediction model was established using logistic regression based on pedestrian height and vehicle collision speed. Secondly, in order to study the distribution of the risk of severe head injuries among pedestrians in accidents, the frequency of pedestrian head impact and the proportion of pedestrian head injury were counted respectively for sedans and SUVs. Subsequently, a risk curve for severe head injuries was constructed based on the head impact frequency and the proportion of severe injuries, utilizing a method that incorporates joint probability
Ye, BinLiu, YuLong, YongchengShi, LiangliangXinming, Wan
Typical everyday driving scenarios involve acceleration ranges which are relevant to accident reconstruction. Understanding the motions and accelerations endured in common driving maneuvers can help quantify the accelerations of vehicles and occupants when reconstructing a collision. This paper evaluates various everyday driving conditions, such as traversing speed bumps and dips, and impacting parking blocks. The purpose of this paper is to quantify the accelerations experienced during everyday driving scenarios to provide a reference for impact severity analysis in the field of accident reconstruction.
Danaher, DavidDonaldson, DrewMcDonough, SeanCochran, ReeceReed, Titus
Determining occupant kinematics in a vehicle crash is essential when understanding injury mechanisms and assessing restraint performance. Identifying contact marks is key to the process. This study was conducted to assess the ability to photodocument the various fluids on different vehicle interior component types and colors with and without the use of ultraviolet (UV) lights. Biological (blood, saliva, sweat and skin), consumable and chemical fluids were applied to vehicle interior components, such as seatbelt webbing, seat and airbag fabrics, roof liner and leather steering wheel. The samples were photodocumented with natural light and UV light (365 nm) exposure immediately after surface application and again 14 days later. The review of the photos indicated that fabric type and color were important factors. The fluids deposits were better visualized on non-porous than porous materials. For example, blood was better documented on curtain airbags than side or driver airbags. Blood and
Boysen, KevinParenteau, ChantalToomey, DanielGregg, Richard H.
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