3D Geospatial modeling of accident scene using Laser Scanner data

The aim of traffic reconstruction is to recreate motor vehicle collision scenes in order to analyze the dynamics of the collision events, to provide evidence in court cases and allow the manufacturers to evaluate the vehicle’s design. However, at the scene of the accident it is not known exactly the amount of information that will be required for the analysis and often relevant data are missing. The emergence of terrestrial laser scanning has enabled the 3D documentation of accident events in a safer way, as information can be collected without any lane closures or traffic interruptions, and in a more flexible and faster way, as a single user can operate the instrument in complete darkness or direct sunlight. The notion of this paper is to model accident scene using terrestrial laser scanning data. With the intersection-related crashes making up a high proportion of total fatal crashes, there is a need for recording their current status in order to improve the design and operation of road intersections. Terrestrial laser scanning provides the capability of recording such infrastructures in a fast and reliable way, where a number of different information, including traffic control features, volumes, accident characteristics and detailed spatial data, can be easily obtained. This information can then be integrated within traffic management integrated systems and be used for accident prevention purposes. Keywords: Terrestrial laser scanner (TLS), Momentum, speed, Accuracy

Automatic segmentation and reconstruction of traffic accident scenarios from mobile laser scanning data

Virtual reconstruction of historic sites, planning of restorations and attachments of new building parts, as well as forest inventory are few examples of fields that benefit from the application of 3D surveying data. Originally using 2D photo based documentation and manual distance measurements, the 3D information obtained from multi camera and laser scanning systems realizes a noticeable improvement regarding the surveying times and the amount of generated 3D information. The 3D data allows a detailed post processing and better visualization of all relevant spatial information. Yet, for the extraction of the required information from the raw scan data and for the generation of useable visual output, time-consuming, complex user-based data processing is still required, using the commercially available 3D software tools. In this context, the automatic object recognition from 3D point cloud and depth data has been discussed in many different works. The developed tools and methods however, usually only focus on a certain kind of object or the detection of learned invariant surface shapes. Although the resulting methods are applicable for certain practices of data segmentation, they are not necessarily suitable for arbitrary tasks due to the varying requirements of the different fields of research. This thesis presents a more widespread solution for automatic scene reconstruction from 3D point clouds, targeting street scenarios, specifically for the task of traffic accident scene analysis and documentation. The data, obtained by sampling the scene using a mobile scanning system is evaluated, segmented, and finally used to generate detailed 3D information of the scanned environment. To realize this aim, this work adapts and validates various existing approaches on laser scan segmentation regarding the application on accident relevant scene information, including road surfaces and markings, vehicles, walls, trees and other salient objects. The approaches are therefore evaluated regarding their suitability and limitations for the given tasks, as well as for possibilities concerning the combined application together with other procedures. The obtained knowledge is used for the development of new algorithms and procedures to allow a satisfying segmentation and reconstruction of the scene, corresponding to the available sampling densities and precisions. Besides the segmentation of the point cloud data, this thesis presents different visualization and reconstruction methods to achieve a wider range of possible applications of the developed system for data export and utilization in different third party software tools

Vehicle and Traffic Safety

The book is devoted to contemporary issues regarding the safety of motor vehicles and road traffic. It presents the achievements of scientists, specialists, and industry representatives in the following selected areas of road transport safety and automotive engineering: active and passive vehicle safety, vehicle dynamics and stability, testing of vehicles (and their assemblies), including electric cars as well as autonomous vehicles. Selected issues from the area of accident analysis and reconstruction are discussed. The impact on road safety of aspects such as traffic control systems, road infrastructure, and human factors is also considered

An exploratory study toward the contribution of 3D surface scanning for association of an injury with its causing instrument.

3D surface scanning is a technique brought forward for wound documentation and analysis in order to identify injury-causing tools in legal medicine and forensic science. Although many case reports have been published, little is known about the methodology employed by the authors. The study reported here is exploratory in nature, and its main purpose was to get a first evaluation of the ability of an operator, by means of 3D surface scanning and following a simple methodology, to correctly exclude or associate an incriminated tool as the source of a mock wound. Based on these results, an assessment of the possibility to define a structured methodology that could be suitable for this use was proposed. Blunt tools were used to produce 'wounds' on watermelons. Both wounds and tools were scanned with a non-contact optical surface 3D digitising system. Analysis of the obtained 3D models of wounds and tools was undertaken separately. This analytical phase was followed by a qualitative and a quantitative comparison. Results showed that in more than half of the cases, we obtained a correct association but the prevalence of wrong association was still high due to mark deformation and other limitations. Even if the findings of this exploratory study cannot be generalised, they suggest that the simple and direct comparison process is not reliable enough for a systematic routine application. The article highlights the importance of an analysis phase preceding the comparison step. Limitations of the technique, ensuring needs and possible paths for improvement are also expounded

Road Accident Reconstruction and Simulation With and Without EDR Data

Indiana University-Purdue University Indianapolis (IUPUI)Road accident reconstruction and simulation investigates the accident causes, suggests improvements in vehicle design and investigates failures in vehicle control and safety systems such as the anti-lock brake system (ABS) and air-bag deployment. This thesis focuses on analysis of crash data from vehicles not equipped with collision warning systems. Vehicle parameters before and during an accident can be recorded using an Event Data Recorder (EDR) which helps in reconstructing an accident. This tool, installed in the vehicle, records different crash parameters like vehicle speed, lateral and longitudinal acceleration, seat-belt status, and air-bag deployment over a period that spens the accident. This thesis focuses on accident reconstruction with and without EDR data. A simulation software tool called HVE is used to visually recreate the reconstructed accidents. HVE is a platform to execute different accident simulation methods which are used for specific types of simulations. Two such simulation methods, EDSMAC4 and EDHIS, are discussed in this thesis. The former is an important method for vehicle-to-vehicle collisions and the latter is used for analysis of human behavior involved in the accident. Three real-life accidents were chosen for reconstruction and simulation. They were Bus and Car accident, Three Vehicle accident and Intersection accident. These particular accidents were chosen to represent a diverse selection of accidents based on the following parameters: the locations of the accidents, the vehicles involved in each accident, and the data available. A qualitative analysis of vehicle occupant's behavior is also presented for one of the three accidents. The thesis discusses in detail the reconstruction of these three accidents. Throughout these simulations, the thesis illustrates the advantages and limitations of the EDR and HVE simulation software for accident reconstruction and simulation

Multivariate Modelling of Pedestrian Fatality Risk Through on the Spot Accident Investigation

Pedestrians are the most vulnerable users of public roads and represent one of the largest groups of road casualties; their death rate around the world due to vehicle-pedestrian collisions is high and tending to rise. In Spain, as in other countries of the European Union, steps have been taken to reduce the number and consequences of such accidents, with encouraging results in recent years. A key to countering this concern is the accident research activity that has obtained remarkable achievements in different fields, especially when multidisciplinary approaches are taken. This paper describes the development of a multivariate model that is able to detect the most influential parameters on the consequences of vehicle-pedestrian collision and to quantify their impact on pedestrian fatality risk. First, an accident database containing detailed information and parameters of vehicle-pedestrian collisions in Madrid has been developed. The accidents were investigated on the spot by INSIA accident investigation teams and analyzed using advanced reconstruction techniques. The model was then developed with two components: (1) a classification tree that characterizes and selects the explanatory variables, identifying their interactions, and (2) a binary logistic regression to quantify the influence of each variable and interaction resulting from the classification tree. The whole model represents an important tool for identifying, quantifying and predicting the potential impact of measures aimed at reducing injuries in vehicle-pedestrian collisions

Imaging in forensic science: Five years on

The Journal of Forensic Radiology and Imaging was launched in 2013 with the aim to collate the literature and demonstrate high-quality case studies on image-based modalities across the forensic sciences. Largely, the focus of this journal has been on the transmissive aspect of forensic imaging, and therefore a significant number of high-quality case studies have been published focusing on computed tomography and magnetic resonance imaging. As a result, the ‘and imaging’ aspect is often neglected. Since 2013, technology has fundamentally evolved, and a number of new techniques have become accessible or have been demonstrated as particularly useful within many sub-disciplines of forensic science. These include active and passive surface scanning techniques, and the availability of three-dimensional printing. Therefore, this article discusses non-contact techniques, their applications, advantages, and considerations on the current state of play of imaging in forensic science

Predicting Safety Benefits of Automated Emergency Braking at Intersections - Virtual simulations based on real-world accident data

Introduction: Intersections are a global traffic safety concern. In the United States, around half of all fatal road traffic accidents take place at intersections or were related to them. In the European Union, about one fifth of road traffic fatalities occur at intersections.Intersection Automated Emergency Braking (AEB) seems to be a promising technology with which to address intersection accidents, as information retrieval by on-board sensing is operational on its own, and, in critical situations, braking is initiated independent of driver reaction. This is not the case for Vehicle-to-Everything (V2X) communication, which requires all conflict-involved vehicles to be equipped with this technology and drivers to respond to an initiated warning. The objective of this thesis is to evaluate the effectiveness of a theoretical Intersection AEB system in avoiding accidents and mitigating injuries. As it will take several decades for a new safety technology to penetrate the vehicle fleet and full coverage of all vehicles may never be achieved, the technology benefit is here analyzed as a function of market penetration. Finally, this research assesses whether a set of test scenarios can be derived without compromising the variance of real-world accidents.Methods: Data from the United States National Automotive Sampling System / General Estimates System and the Fatality Analysis Reporting System was used to compare the capacity of on-board sensing and V2X communication to save lives. To investigate Intersection AEB in detail, the German In-Depth Accident Study (GIDAS) data and the related Pre-Crash Matrix (PCM) were utilized to re-simulate accidents with and without Intersection AEB using different parameter settings of technical aspects and driver comfort boundaries. Machine learning techniques were used to identify opportunities for data clustering.Result: On-board sensing has a substantially higher capability to save lives than V2X communication during the period before full market penetration of both is reached. The analysis of GIDAS and PCM data indicate that about two thirds of left-turn across path accidents with oncoming traffic (LTAP/OD) and about 80 percent of straight crossing path (SCP) accidents can be avoid by an idealized Intersection AEB. Moderate to fatal injuries could be avoided to an even higher extent. Key parameters impacting effectiveness are vehicle speed and potential path choice; to increase effectiveness, these should be limited and narrowed down, respectively.Conclusion and Limitations: Intersection AEB is effective in reducing LTAP/OD and SCP accidents and mitigating injuries However, intersection accidents are highly diverse and accurate performance evaluation requires taking variations into account. The simulations were conducted using ideal sensing without processing delays and an ideal coefficient of friction estimation

Study and validation of data recorded in the vehicles’ EDR in order to perform a road accident’s dynamic reconstruction

Road accident reconstruction is an issue which involves multiple and differentiated subjects. A collision contours’ determination requires the investigation and the analysis of all the evidence provided from highly distinct sources and remaining from uncertain and, sometimes, chaotic scenarios. People are vastly involved in traffic accident situations, either being drivers, victims, injured or witnesses. Therefore, accident investigation is a sensitive matter which requires objectiveness, accuracy, efficiency, and effectiveness, to draw faithful and factual conclusions about the collisions’ contours. The accidents reconstruction science’s main objective is to determine and describe the involved vehicles dynamics, which is accomplished by collecting and interconnect all the available evidence extracted from the impacts’ scenarios, from the vehicles, and from the involved people. In the past, many authors developed mathematical models which describe, approximately, the vehicles’ dynamics involved in a road traffic collision. Over the years, with the technology evolution and the advances on the area, multiple solutions have been created and enhanced to provide to accident reconstructionists better and more reliable evidence, allowing them to perform crash reconstructions with higher accuracy. These solutions include numerical methods, simulation and evaluation software, and tools for evidence collection. However, the introduction of the Event Data Recorder (EDR) on the vehicles consists of a great progression concerning the availability of valid and meaningful clues which can be used as inputs for the scientific crash reconstruction, since the EDR stores data that was unavailable and was difficult to deduce from the accident’s remaining evidence, previously. On the scope of this project, a vehicle data logging device was developed and tested regarding the validation of the EDR’s recorded data. The device’s purpose is to acquire the most relevant variables for crash reconstruction, which are also stored by the EDR, and provide a source of information for comparison and validation. This device was integrated with the respective sensors, programmed with a developed software, and tested on a vehicle. The tests for dynamic data acquisition consisted of travelling a defined path around the school campus, since there was not the opportunity to perform a real crash test with an EDR equipped vehicle