A COMPUTATIONAL DYNAMICAL MODEL FOR TRAFFIC ACCIDENT RECONSTRUCTION.

Developed countries, especially ones with good geographic and climatic characteristics for cycling, recognized long time ago the benefits of using bicycle as a mean of transport, peculiarly by motivating passenger car users towards the wider use of bicycle. Some of the most significant advantages of cycling are health improving, emission and congestion reductions, mitigation of problems with traffic noise and parking in central urban areas etc. Traffic casualties are global world problem and cyclists are especially demoralized for resolving the above mentioned problems because they are classified as vulnerable road users. According to that, it is essential to take measures for improving the level of cyclists safety in traffic, and thus to create conditions for popularization of cycling. Besides phenomenological approach in traffic accident investigation and reconstruction (spatial distribution, time distribution, types of accidents, particular characteristics of traffic accidents, etc.), etiological approach is more significant because of more detailed causes and circumstances analyses of cyclists endangerment in traffic and results of these analyses are basis for measures in traffic safety improvement. Traffic accident reconstruction is the analysis of the occurring circumstances, but also analysis of circumstances under which could be avoided. Expertise presents investigation which is done by expert, so in traffic accident reconstruction it is necessary to realize a lot of complex procedures in order to assess traffic accident occurrence. Part of a time-distance analysis which is the most relevant for defining the causes and circumstances of traffic accidents is avoidance analysis.

Traffic accident reconstruction is a reverse dynamic problem, which requires hundreds of iterations to reconstruct the whole process of accident. However, in current pedestrian-vehicle accident reconstructions, it is difficult to quickly establish a pedestrian model based on specific cases, and it is hard to solve the contradiction between calculation accuracy and calculation time. In this paper, a personalized pedestrian customization method is proposed. First, the pedestrian structure is divided into independent modules according to obvious bony markers. For each independent module, multi-body (MB) model and finite element (FE) model are established, respectively. Then the appropriate modules are selected to form the whole hybrid pedestrian model. This method can customize the structure of pedestrian model according to the injury characteristics of pedestrians in specific accidents, and customize the parameters of pedestrian model according to the height and weight of pedestrians. The impact simulation tests are carried out on hybrid pedestrian models to verify the reliability of the models. The proposed method can effectively improve the modeling efficiency of pedestrian models and the reconstruction quality of pedestrian traffic accidents.

Reconstruction of traffic accidents has been so crucial scientific process in order to make impartial and judicious decisions. This study focuses on impact speed prediction of accident sufferers just before the collision in a comprehensive scientific way by using an accident reconstruction software called “vCrash” and Function Fitting Neural Network (FITNET) artificial intelligence method (predictor) in case of absence of skid marks or other clues about calculating impact speeds. A sample real world accident was simulated on the software several times by changing collision speeds to form different deformation on the collision regions of the vehicles in every simulation. Every single deformation amount corresponding to each impact velocity was recorded and used as teaching data for FITNET prediction model. Using 10-fold cross validation, mean squared error (MSE) and multiple correlation coefficients (R) were observed to exhibit performance of the prediction model. The model performed high R (close to 1) and acceptable MSE values. This method aims that, in a probable similar accident scene in future, it will be possible to analyze the impact speeds just by entering average deformation amounts into an application on a portable device at the accident scene without requirement of expensive reconstruction tools and it will be a guide for analysis of other accident types.

As vehicles transcend into higher levels of automation, a key factor that will determine a comfortable driving experience for the passengers will be the handling behaviour of the autonomous vehicles. Path planning will serve an important role in ensuring smooth and comfortable handling. The present study develops a well defined universal scale to define the handling behaviour of autonomous vehicles using different ergonomic path planning tools. Firstly, a reference track is designed to incorporate the worst handling. Followed by designing ergonomic roads using transition curves such as B-spline, Bezier and Hermite curves to investigate the impact of these curves on handling behaviour. Trajectory tracking of an 8 degree of freedom vehicle model is then studied using curvature dependent and curvature independent controllers to draw a comparison. Results are then compared and evaluated using a universal cost function to determine the optimal transition curve for handling. Results indicate that 3-point defined curves in general perform better handling with B-spline evaluated as the best handling transition curve for 4-point defined curves. Further research is recommended by utilising key characteristics of the transition curves like local control and non-uniformity.

Injuries After Oldtimer Accidents: Eighteen Years Experience in the Emergency Department of a Swiss University Hospital.

The objective of traffic accident reconstruction is to recreate the event, which is necessary for analyzing the collision dynamics that is used as evidence in court cases. Traffic accident reconstruction and a demonstration of the event require precise data pertaining to scene measurement. However, there are differences between the individual measuring tools and methods related to traffic accident investigation, just as there are differences between the extent of their use and measurement accuracy. The most commonly applied method is the measuring tape, followed by measurements with total stations and laser rangefinders, while photogrammetry is also becoming increasingly important. The advantages and disadvantages of individual tools and methods affect the required number of investigators, portability, measurement range, applicability depending on the amount of light and weather conditions, on the possibility of remote measurement, on data collection time, on the scope, on the option to later process, the collected data and above all on the accuracy of all gathered data. The latter is crucial for proving the guilt or innocence of traffic accident participants at court, as inaccurate data can lead to an unjust sentence. Measurement accuracy using the above mentioned tools and methods also varies depending on which ones are used, as well as on other factors.

Finite element method for reconstruction of road traffic accidents

Road traffic accidents (RTAs) pose a public health and development challenge and greatly affect the human capital development of every nation. Main causes for a significant percentage of RTAs are recklessness, fatigue or stress, inexperienced driving and driving under the influence of alcohol. Reputed automobile companies and authorities have established standards and/or proactive/reactive solutions over the years to overcome this problem but the rates continue to grow each year. Software solutions that focus on preventing RTAs are difficult to be found in economy class automobiles that are used by the majority of consumers. The limited number of successful applications are either bound to a certain brand/model and/or focus on a specific task. SmartV is smart phone based vigilance monitoring system that focuses on the majority of factors contributing to RTAs. These include DUI (driving under the influence of alcohol), health issues and vehicle defects. The mobile application communicates with a heart rate monitor and a Bluetooth OBDII Adapter. These will continuously monitor the heart rate of the driver and the status of the vehicle respectively. During the course of the drive, the system monitors the behavior of the vehicle for existence of dangerous driving patterns that are defined in Visual Detection of DWI Motorists[8] a study conducted by U.S.A. N.H.T.S.A. The final product is a versatile, non-intrusive, flexible and most importantly an affordable mobile application that captures the vehicle's behavior, the health level of the driver and the status of the vehicle. Real environment operation of SmartV has yielded significant results proving itself to be a successful and an affordable Vigilance Monitoring System for the future.

<div class="htmlview paragraph">A series of examples, involving normal mode representations of a flexible railcar and various suspension models, is presented illustrating the use of bond graph techniques for assembling a structural dynamic system model from component models. Bond graph techniques are related to other methods for achieving the same goal, and the unique features of bond graph techniques are pointed out. Not only does the bond graph provide a graphical representation of the organized system equations, but also it allows the use of ENPORT programs for automating the process of manipulating the component relations into an explicit-state space format suitable for simulation or analysis. Nonlinear and active systems which interact with structural dynamic components are readily handled using bond graph techniques.</div>

This paper presents a new concept for calculating of the bond graph observer gains based on a graphical approach that investigates the Lyapunov Second Method in order to conclude about the observer stability and to search for the adequate gains that stabilize the observer. This new observer is used in the mode identification procedure. In fact, the observer’s residues allow the differentiation between the current mode and the other system modes. In order to guarantee the efficiency of the mode identification procedure, a new bond graph approach is proposed. It concerns the discernibility between the modes in bond graph language. First, it deals with the R-discernibility that introduces the definition of the discernibility through the structural parity residual then returns to a simple calculation of some matrices’ ranks in bond graph language. Second, another bond graph technique is applied to define the discernibility throughout the equivalency between the realizations.

The frequency of road traffic accidents (RTAs) is higher in China than in other countries, and traffic safety is a more complex issue. Our study of RTA severity differences among 31 provinces in China identifies the most important traffic management issues in each province. Provinces with the highest RTA risk were identified from RTA mortality data for 31 provinces during 2004–2013. Then provinces with the highest risk according to mortality/per capita GDP, mortality/10,000 vehicles, and mortality/100,000 persons were determined to eliminate the effect of differences in economic development, vehicle numbers, and population on mortality rates. The results show that Guangdong, Zhejiang, Jiangsu, Shandong, Sichuan, Anhui, Fujian, and Hebei have the highest RTA risk in China. Tibet, Anhui, Guangxi, Qinghai, Sinkiang, Gansu, Zhejiang, and Guangdong have the highest risk trend. Thus, Anhui, Zhejiang, and Guangdong have both the highest RTA risk and the highest risk trend. We discuss environmental, road, vehicle, and human causes of RTAs for the province groups. Improving traffic management, strengthening the deterrent effect of legal penalties, and establishing a road safety culture could reduce RTAs in China.

Accurate and detailed information of traffic accident scene is important for accident investigation, and the current investigation methods (tape measuring and total station survey) always need highway closure, and their working process is time-consuming. From different angles or at different altitudes, unmanned aerial vehicle (UAV) can monitor accident site without interrupting the traffic flow, therefore, UAV is introduced for accident scene reconstruction. Firstly, the method framework of accident scene reconstruction was proposed, in which UAV was used to take pictures of accident site, and imaging system was adopted to reconstruct the 2D and 3D accident scene. Then, 3D reconstruction, point cloud generation, and model optimization were presented. Next, a UAV flight experiment was conducted for traffic accident scene reconstruction, and two evaluation indexes, signal-to-noise ratio and structural similarity, were introduced to assess the image quality of accident scene reconstruction. The case study demonstrates that compared with current methods, the proposed method is efficient; moreover, the effect of accident scene reconstruction is satisfactory.

Electric Power Steering (EPS) systems have many merits over traditional hydraulic power steering systems in fuel economy, variable assist capabilities and favorable road feeling by virtue of adjustment assist characteristic with adopting assist motor in replacement of hydraulic pump. This paper aims at modeling the mechanical parts, the assist motor and electronic control unit by bond graph technique and simulating system dynamic performance regarding vehicle maneuverability and stability and driver’s steering feel by Matlab/Simulink. The simulation results provide that the bond graph EPS model can reflect stability and dynamic steering characteristic in effect.

This article describes the investigation methodology used in road crashes in the Department of Investigation and Traffic Accident Reconstruction (DIRAT) of the Traffic School of the Spanish Guardia Civil. It has deliberately chosen to run over pedestrians for the exhibition of this methodology, given the almost unanimous scientific opinion considers this type one of the most difficult to investigate. It begins with a theoretical exposition on the subject, which sets out briefly the embodiment of Ocular Technical Inspection; the data must be obtained from the same, and the need to obtain additional information of different sources about highway, vehicles, drivers, victims and witnesses. Later, we apply software tools, specifically PC—Crash, to verify the analysis and results obtained by the analytical and sequential reconstruction of the pedestrian collision. This process has just allowing for reviewing and identifying the factors, conditions and causes that motivated the road crash. As a complement, it is shown as theoretical methodology is applied to a real case of pedestrian collision investigated and solved by the DIRAT. Finally, the conclusions reached along this work are enumerated and the lines of future work are drawn.

Road traffic accident is a massive health hazard in Egypt and all over the world. Also, Road traffic injuries (RTIs) are a major cause of global mortality and morbidity. Available funds are insufficient to solve problems in all accident locations at the same time. Consequently, accident locations need to be ranked according to its severity for best allocation of available funds to repair the most severe locations. El Minia-Beni suif east and Agriculture roads are of the roads that have a highly repetition of accidents. This study compares between accident characteristics on both roads. In addition, areas of high accident occurrence are ranked according to its severity. Accident data on both roads is abstained from General Authority of Roads, Bridges and Land transport (GARBLT) for the period from 2010-2014. Analysis proved that Agriculture road has the major part of accidents, death and injuries. The maximum number of accidents on both roads occurs at kilometers between 20 and 30. The road section length of highly accident location on both roads is divided into subsections with length 2 km. These subsections are ranked according to its severity using the accident weight methodology. Accident weight is estimated using the economic cost of death, injury and property damage. Black spots are determined using Critical Crash Rate approach. Analysis proved that two locations on the study area can be considered as black spots. One on each road at the same km (24-26) is considered as a black spot. The present study recommends starting modifications with these two black spots sites then other locations according to its rank of severity. Also, the research recommends that the methodology introduced in should be used on all Egyptian roads. © 2016. Marsland Press, Zhengzhou University Language: en