Real Accidents Research Articles

Optimal distribution of emergency resources to accidents for pre-rescue in chemical industrial parks

Medical and fire resources are scheduled to chemical industrial parks which have caused mass casualties due to accidents. However, most of models of emergency logistics do not account for pre-rescue before large-scale rescue which may increase the casualty rate because of the long emergency response time and distance. This paper presents a mathematical model proposed for optimal distribution of emergency resources for rescuing the trapped victims who are highly likely to be seriously injured or even killed before the arrival of ambulances and fire engines. Due to the different types and risks of accidents at various locations have different impacts on people, we consider the detailed characteristics of accident scenarios and maximum tolerance time for the trapped victims to determine the priority of rescue sites. In addition, this paper proposes two indices of pavement resistance coefficient and obstacle to reflect the environment after accidents, which are not involved in other models of emergency resources distribution. Based on these, a penalty cost objective function is established to maximize the rescue rate. The optimal delivery route which reflects the distribution process is planned for the robot that will save more casualties. Two simulations and a real accident case study were conducted by minimizing the objective function, and the numerical results showed the reliability and effectiveness of the presented model for making optimal decisions for emergency distribution to accidents in chemical industrial parks.

Robust and transferable end-to-end navigation against disturbances and external attacks: an adversarial training approach

Purpose This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments. Design/methodology/approach In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models. Findings Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world. Originality/value The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.

Incorporation of a global perspective into data-driven analysis of maritime collision accident risk

Ship collision accidents are one of the most frequent accident types in global maritime transportation. Nevertheless, conducting an in-depth analysis of collision prevention poses a formidable challenge due to the constraints of limited Risk Influential Factors (RIFs) and available datasets. This paper aims to incorporate a global perspective into a new data-driven risk model, scrutinize the root causes of collision accidents, and advance measures for their mitigation. Additionally, it seeks to analyze the spatial distribution and conduct a comprehensive comparative study on collision characteristics for both pre- and post-COVID-19, utilizing the real accident dataset collected from two reputable organizations: Global Integrated Shipping Information System (GISIS) and Lloyd's Register Fairplay (LRF). The research findings and implications encompass several crucial aspects: 1) the constructed model demonstrates its reliability and accuracy in predicting collision accidents, as evident from its prediction performance and various scenario analysis; 2) the most hazardous voyage segment for collision accidents is identified to provide valuable guidance to different stakeholders; and 3) the hierarchical significance of various ship types in the context of collision accident is highlighted regarding the most probable scenario for collision occurrences; 4) During the pandemic, the rise in collision probabilities, particularly involving older vessels and bulk carriers, implies heightened operational challenges or maintenance issues for these ship types; (5) The prominence of favorable and adverse sea conditions in collision reports underscores the significant influence of weather on accidents during the pandemic. These findings and implications help enhance safety protocols, ultimately reducing the frequency of collision accidents in the global maritime domain.

Interobserver variability in preclinical assessment of collision variables following traffic accidents

PurposeTraffic accidents persist as a leading cause of death. European law mandates the integration of automatic emergency call systems (eCall). Our project focuses on an automated injury prediction device for car accidents, correlating technical and epidemiological input data, such as age, gender, seating position, impact on the passenger compartment, seatbelt usage, impact direction, EES, vehicle class, and airbag deployment. This study aims to explore interobserver variability in data collection quality in real accident scenarios. The assessment will evaluate the impact of user training and measure the time needed for data collection to inform user recommendations for the prehospital assessment.Insights from this study can aid in evaluating the ability of different professional groups to identify potential accident-independent parameters at accident scenes. This includes, among other things, relaying information to dispatchers at rescue control centers, also within the context of telemedicine approaches.MethodsDuring group sessions, real accident scenarios were presented both before and after a training presentation. Participants, including laypersons, accident research staff, emergency services, hospital physicians, and emergency physicians, visually assessed injury prediction parameters within a time limit. Training involved defining and explaining parameters using accident images. The study analyzed participant demographics, prediction accuracy, and time required, comparing assessment quality between professional groups and before and after training.ResultsIn summary, the study demonstrates that training had a significantly positive impact on the quality of assessment for technical accident parameters. The processing time decreased significantly after training. A notable training effect was observed, particularly for the parameters of rigid collision object, affected passenger compartment, energy equivalent speed (EES), and front and side airbags. It was recommended that individuals without prior knowledge should receive training on assessing EES. Overall, it was evident that technical parameters following a traffic accident can be well assessed through training, irrespective of the professional group.ConclusionSignificant differences in the assessment quality of technical accident parameters were observed based on technical and medical expertise. After user training, interdisciplinary differences were reconciled, and all professional groups yielded comparable results, indicating that training can enhance the assessment abilities of all participants in the rescue chain, while the time required for assessing accident parameters was significantly reduced with training.

The identification of minor impact collisions in a long video for detecting property damages caused by fleeing vehicles using three-dimensional convolutional neural network

Abstract A parked vehicle damaged by a hit-and-run can only be repaired at the expense of the owner, unless the fleeing vehicle is identified and the driver apprehended. Identifying the fleeing vehicle involves using a video investigation method that searches for perpetrators through CCTV footage of the crime scene. When the length of the recorded video is long, the investigation may require an extended amount of time from the investigator, resulting in an added burden on their daily work. Some commercial companies are using object recognition and tracking technology to detect hit-and-run incidents; however, detecting small movements of a vehicle during a minor collision still remains a challenge. Therefore, there is a need for a system that can detect small movement in a vehicle in a lengthy video. Automatic recognition and tracking require a sufficient amount of training dataset. However, such a dataset for hit-and-run incidents is not publicly available. One of the reasons behind this scarcity is that it may violate personal information protection acts. On the other hand, instead of using real accident videos, we could use actors to simulate such accident scenes. Although this may be feasible, creating such a dataset would require substantial costs. In this paper, we describe a new dataset for hit-and-run incidents. We collected 833 hit-and-run videos by recreating a parking lot using miniaturized cars. This dataset has been made publicly available through Kaggle. We used three-dimensional convolution neural network, which is frequently used in the field of action recognition, to detect small movements of vehicles during hit-and-run incidents. In addition, the proportion of the area that surrounds the target vehicle to the min-max box of the vehicle itself and the length of the input frame are varied to compare the accuracy. As a result, we were able to achieve better accuracy by using the lowest proportion and the shortest input frame.

The role of traffic conflicts in roundabout safety evaluation: A review

The roundabout is one type of at-grade intersection commonly seen in many countries. The evaluation of roundabout safety is usually counted on conflict analysis of the roundabout traffic due to random and limited records of real accidents. This paper surveyed published papers and reports that investigate the role of traffic conflicts in roundabout safety evaluation. It summarized the definitions and observation methods of roundabout conflicts and classified the attributing factors of roundabout conflicts and the countermeasures to control the conflicts. This study found that although unique traffic flow movements at roundabouts create special patterns of roundabout conflicts, the methods of roundabout conflict analysis used in most existing studies were inherited from the studies of highway or cross-intersection conflicts, including conflict definitions, conflict measurements, and thresholds of conflict severity. Special or improper designs of roundabout configurations or basic geometry elements could arouse roundabout conflicts. The most common vehicle-to-vehicle conflicts were entering-circulating conflicts, sideswipe conflicts, and exiting-circulating conflicts. The conflicts among vehicles and vulnerable road users (VRUs) easily evolved into serious collisions, but these conflicts did not get deserved attention in previous studies. Drivers’ familiarity with roundabouts also affected road users’ safety. Traffic signs and pavement markings were commonly used to control roundabout conflicts, while traffic signals were more effective methods for the roundabouts with uneven distribution of approaching traffic or high traffic volume. Based on the analysis of existing studies, this paper pointed out seven future directions of further research in term of conflict measurement, data collection, infrastructure and access management, geometry, drivers and VRUs, signal control, and vehicle control.

The Baby on the Track: A Newspaper Legend with Roots in the 19th Century

Abstract In a novel by a Chinese author, Yu Hua, the birth of the main character takes place in a train toilet. He falls down on the track and survives. During the last 30 years news stories with this content have been reported several times. The event is generally said to have taken place in China or India. From a folkloristic perspective the story can be defined as a newspaper legend. Like contemporary legends in oral tradition newspaper legends often are about accidents where babies are involved. As opposed to the orally transmitted legends they generally have a happy ending; they are published as a counterbalance to all the real accidents that daily papers have to report. The oldest version of “The Baby on the Track” was published in 1888 in a medical journal. The author, the famous physician William Osler, had a reputation for being a practical joker, and today it is difficult to judge if his story is based on a real case or if Osler invented it.

Estimating the effectiveness of electric vehicles braking when determining the circumstances of a traffic accident

In the vast majority of cases, the braking process is used to prevent traffic accidents. The effectiveness of this process depends on the design and functionality of vehicle braking systems (presence of anti-lock braking system, emergency braking system, preventive safety systems, etc.) and is limited by the amount of frictional forces in contact of tires with the road. The improvement of methodical approaches to evaluating the effectiveness of braking of cars contributes to increasing the accuracy and objectivity of establishing the circumstances of the occurrence of emergency situations. The paper analyses existing methods of evaluating the braking parameters of vehicles (including those with an electric drive) and modern methods of evaluating electric vehicle braking parameters and conducting auto-technical investigations of traffic accidents, which relate to using different methodological approaches and digital technologies at all stages of expert research. In contrast to existing models, the proposed mathematical model for estimating the trajectory of two-axle cars during braking allows for considering various types of input parameter uncertainty, reducing the range of possible modeling errors by 39%. Comparing simulation results and experimental data showed that the average relative error is 4.58%, and the maximum error did not exceed 7.82%. The performed study of the stability of the electric vehicles' movement during emergency braking with the help of developed mathematical models in the Mathcad software environment reveals the content of the algorithm of a similar calculation in specialized computer programs of auto technical examination. Conducting such calculations is relevant in the analysis of real accident situations, where specific circumstances and features that cannot be considered during modeling in specialized software must be taken into account. Simultaneously, the probability of type I errors is reduced by 2–19%, and type II errors are reduced by 43–68%.

Maritime risk assessment using a non-linear spatial multi-criteria decision method: A case study in the Bohai Sea and Yellow Sea, China

The risk caused by different environmental factors in the navigation of ships is not uniform. The univariant (e.g., sea fog), covariant (e.g., wind and waves), and spatially restricted (e.g., offshore distance) risk factors present a complex non-linearity impact on the navigation of ships. This means that a comprehensive evaluation of the environmental risk for navigation should consider the risk characteristics of different factors. In this paper, a non-linear spatial multi-criteria decision (SMCD) method-based evaluation framework was developed to evaluate the potential environmental risk of navigating ships. (1) Non-linear weight adjustment and risk decision functions were proposed to spatially evaluate the comprehensive risk and avoid diluting the critical impact of high-risk factors. (2) The double thresholds standardization approach was developed to construct the risk association between different tonnage ships and environmental factors. (3) The developed methods were used in the Bohai and Yellow Seas as a case study to verify the validity and practicability. The quantitative analysis, historical accident matching (82% accident matching rate), and a real accident case proved the validity of the developed model.

Dynamic prediction of spatial dose rate distribution during nuclear severe accidents by means of active machine learning and mobile sensors

The prediction of atmospheric dispersion of nuclear material is crucial to support emergency response during nuclear accidents, due to the potential severity and far-reaching consequences of such accidents. This importance is particularly evident in the context of severe accidents, like the incident that occurred at the Fukushima Daiichi Nuclear Power Plant (NPP). NPP are commonly supported by atmospheric dispersion systems (ADS), which estimate the spatial dose rates distribution, referred to as the dose rate map (DRM), by means of physical model simulations, including source term (ST), wind fields, atmospheric transport and diffusion, and dose calculations. However, it is well-known that a real accident scenario may differ from those modeled especially under severe conditions, and this fact may lead to erroneous predictions resulting in poor or catastrophic decision making. Aiming to minimize this problem, several efforts have been made to improve predictions based on field measurements, such as inverse problems and other methods to correct/adjust ST parameters. Such methods, however, complement the physical model calculations. This paper proposes a novel approach to predict DRM at ground level, based only upon field measurements (avoiding execution of physical model simulations). The idea is to dynamically adapt a set of mobile sensors (for example monitoring drones swarm) to follow the radioactive plume. To achieve this, an active machine learning (AML) approach was developed based on Gaussian process regression (GRP) and swarm intelligence. To test the approach, computational experiments using realistic simulated data (generated on the ADS simulator of a Brazilian NPP) has been used. As result, DRMs have been reproduced with good qualitative (visual) representation and satisfactory quantitative metrics. The average correlation coefficient between predicted and real DRMs was approximately 0.72 (ranging from 0.64 to 0.97 during plume evolution), demonstrating to be a promising approach to predict DRMs.

A methodology for crash investigation of motorcycle-cars collisions combining accident reconstruction, finite elements, and experimental tests

Motorcycle and in general motorized 2–3 wheelers accidents are a major concern of road safety worldwide representing about 28% of the overall fatalities. Speed is a central factor in the increase of injury severity of the accident’s intervenients. The main factors and causes of an accident can be determined with accident reconstruction being the reason for its popularity in accident safety research. A methodology of three different and complementary accident reconstruction methods is proposed and applied to a real accident where a motorcycle impacts the front side door of a passenger car. No other study in the literature presents a similar methodology for motorcycle accident reconstruction. With PC-Crash all accident dynamics were determined in the first place with a complete accident reconstruction. Afterwards, a finite element simulation of the impact between the motorcycle tire and the car’s door was conducted in Ansys LS-DYNA using all the results extracted from PC-Crash. The results of both these analyses correlated well with reality. To validate the finite element model, a pendulum experimental impact test was performed. It was achieved a good correlation from a kinematic point of view. An accurate accident reconstruction and a correct validation of the kinematics are possible with the proposed methodology. A good correlation of results between the three different methods was achieved. The proposed methodology enables for a more accurate estimation of the speed of motorcycles involved in accidents which is of extreme importance in accident investigation.

경미사고 사례분석을 통한 공학적 상해위험 분석의 유효성

In the case of minor injury patients, they usually feel stiffness in the neck or waist. However, it is not detected through image diagnosis techniques such as CT or MRI. Therefore, doctors rely on the victim's subjective arguments for treatment. Some victims exploit these blind spots and receive excessive insurance payments. According to data from the Korea Insurance Research Institute, It was announced that the scale of over-treatment for minor injury patients is serious, which leads to the effect of raising insurance premium for good insurers. In the engineering field, an analysis method through simulation was attempted to analyze the judgement of the minor injury. However, there were many limitations to the reliability of the simulation model. Therefore, in this paper, based on the empirical research results and car to car collision data, the risk of passenger injury was judged based on two real accident cases. As a result, it was difficult to judgement the risk of injury to passengers in the two real accident cases. These results are used as reference materials by the court, and the injury claimed by the victim was not recognized.

The Effects of Including Blood in First Aid Training on Confidence in Bleeding Control Ability and Intent to Aid

Introduction:Educational initiatives such as Stop the Bleed continue to educate medical laypeople in first aid for massive bleedings. The effect of including realistic blood early in Stop the Bleed-type training remains unknown. The aim of this study was to investigate the effects of including realistic blood early in a Stop the Bleed-type training on medical laypeople's intent to provide future aid and self-perceived ability to provide aid.Method:In total, 46 medical laypeople participated in this study. Two bleeding control tasks, wound packing and tourniquet application, were performed in a simulated scenario on a manikin with a wound. Participants received brief Stop the Bleed-type training and were divided into two groups: with (Blood) or without (Control) blood present during the tasks. After the experiment, two surveys were administered, one on confidence in their ability to perform each task, and a previously established survey on their intent to aid a bleeding victim in real-life situations.Results:The post-trial survey showed that the participants in the Blood group had lower confidence than the Control group in their wound packing ability (MBlood = 2.09, SDBlood = 0.85; MControl = 3.04, SDControl = 0.86), t(43) = 3.725, p < .001, but not regarding their tourniquet application ability, t(43) = 0.019, p = 0.985. Further, there was no difference between the groups in their intent to aid in future real accidents (MBlood = 91.00, SDBlood = 6.10: MControl = 90.39, SDControl = 8.30), t(43) = 0.282, p = .782.Conclusion:This study shows that introducing realistic blood early in Stop the bleed-type training of laypeople results in decreased confidence in their wound packing ability. However, it does not decrease their intent to aid in future emergencies. Future studies should investigate when and how complicating factors such as blood should be introduced in laypeople hemorrhage control training.

Subjective individuals' perception during evacuation in road tunnels: Post-experiment survey results.

The aim of the research was to analyse the process of evacuation from the point of view of the individual's perception, behaviour and decision making. The study used a survey method that was conducted during two real-scale evacuation experiments in real road tunnels under smoky conditions. All experiments, with fire scenarios and procedures were very similar to real accident. Respondents' observations and important aspects affecting the evacuation process were verified, including decision-making during evacuation, loss of bearing in smoky conditions and group evacuation. The results indicate that participants in the experiments had started the evacuation due to smoke in the tunnel and fire drill. The evacuees observed decreased visibility on the escape route as well as a loss of bearing in the tunnel when smoke levels were high (extinction coefficient Cs > 0,7 m-1). The participants in the experiment evacuated in a group (when the tunnel infrastructure was unknown and there was no instruction as to what to do) and in twos under the smokiest conditions (extinction coefficient Cs~1.0-1.1m-1). During the experiments, the large impact of herding behaviour and following the group was noticed. The results of such studies based on real-scale evacuation experiments in road tunnels are essential to improve the level of safety in the road tunnel. In the surveys, the participants pointed to important issues related to evacuation, which require particular attention during the design, implementation and acceptance of this type of construction. The results of the study provide a better understanding of the behaviour of evacuees and indicate areas where tunnel infrastructure needs to be improved.

Spinoza and the Hybrid Distinction of Attributes

Abstract In this paper, I address the issue of what kind of distinction separates the attributes of Spinoza’s substance. I propose to consider the distinction between attributes neither as a real distinction nor as a pure distinction of reason. Instead, I ventilate the alternative of understanding attributes as distinguished by a hybrid distinction, of which I trace the development during the Medieval and Early Modern eras. With the term hybrid, I capture distinctions which are neither a real distinction between substances or real accidents; nor a pure distinction of reason, produced or fabricated by the intellect. I shall argue that Spinoza’s notion of attribute falls under the scope of a hybrid distinction, thus sidestepping the longstanding debate between objectivism and subjectivism.

Nonlinear analysis and processing of software development data under Internet of things monitoring system

Abstract The most important and core technology of the Internet of things (IoT) is still the internet, and it also includes many other technical fields and is applied to many fields. The various processes of IoT data are the guarantee that the IoT can meet the management and management requirements in a certain application field, so that each application field can better meet the requirements of people’s lives. In order to study the nonlinear analysis and processing of software development data under the IoT monitoring system, this work uses QT software and socket programming to build the detection, control, and transmission module of the system, and uses multiple processes to classify and process the data. The user interface technology is used to display the data in real time. The system can control the type of transmitted data through interface operation. The classified transmission of data is realized, and the transmission speed is guaranteed to be about 50 MB/s. The experimental results show that after the functional design of each module is completed, the whole system is finally tested to determine whether the system can meet the requirements of data transmission, control, and processing. Since these data are simulated data, video playback is used to simulate the occurrence of a real accident. When an abnormal situation occurs, the whole system starts to work. If an accident occurs, a signal is sent after the accident. The system not only ensures the intellectualization of control, but also ensures the rapidity of data transmission.

Work environment risk management at petrol stations

Work environment risk factors have a big influence in the daily life of employees at every company and work environment. In this study, a wide-ranging work environment risk assessment was carried out, using qualitative, quantitative, and semi-quantitative risk assessment methods, comparing the obtained results, and influencing factors, as well as evaluating the work environment management system and recommending possible improvements in its future development. The importance of the topic is justified by the fact that petrol stations are sites of heightened danger, where employees must pay greater attention to ensuring and maintaining a safe and secure environment to prevent the transformation of potential risks into real accidents or incidents. The work was developed at a company in Riga, Latvia, and station surveys were conducted in March 2021. As part of the work environment risk assessment process, four petrol stations in Pardaugava, Riga, were chosen for the risk assessment and measurements. In addition to station evaluations, an employee survey was conducted at 66 petrol stations throughout Latvia.

Lagrange tracking-based long-term drift trajectory prediction method for Autonomous Underwater Vehicle.

Autonomous Underwater Vehicle (AUV) works autonomously in complex marine environments. After a severe accident, an AUV will lose its power and rely on its small buoyancy to ascend at a slow speed. If the reserved buoyancy is insufficient, when reaching the thermocline, the buoyancy will rapidly decrease to zero. Consequently, the AUV will experience prolonged lateral drift within the thermocline. This study focuses on developing a prediction method for the drift trajectory of an AUV after a long-term power loss accident. The aim is to forecast the potential resurfacing location, providing technical support for surface search and salvage operations of the disabled AUV. To the best of our knowledge, currently, there is no mature and effective method for predicting long-term AUV underwater drift trajectories. In response to this issue, based on real AUV catastrophes, this paper studies the prediction of long-term AUV underwater drift trajectories in the cases of power loss. We propose a three-dimensional trajectory prediction method based on the Lagrange tracking approach. This method takes the AUV's longitudinal velocity, the time taken to reach different depths, and ocean current data at various depths into account. The reason for the AUV's failure to ascend to sea surface lies that the remaining buoyancy is too small to overcome the thermocline. As a result, AUV drifts long time within the thermocline. To address this issue, a method for estimating thermocline currents is proposed, which can be used to predict the lateral drift trajectory of the AUV within the thermocline. Simulation is conducted to compare the results obtained by the proposed method and that in a real accident. The results demonstrate that the proposed approach exhibits small directional and positional errors. This validates the effectiveness of the proposed method.

Неопределённости расчёта параметров взрыва газовоздушного облака при аварийном выбросе сжиженного природного газа в открытом пространстве

Purpose. Increasing production of liquefied natural gas (LNG) in the Russian Federation raise the risk of the accidental LNG releases. To prevent the negative consequences of a possible gas-air cloud explosion during LNG release, it is necessary to predict probable emergency scenarios. Regulatory documents for determining fire risk make it possible to define the likely consequences of an explosion of liquefied hydrocarbon gases (LPG) vapor clouds, however the application of calculation methods for LNG requires additional analysis. Methods. The analysis of methods for calculating the parameters of a gas-air cloud explosion in an open space is carried out, the consequences of real gas-air clouds explosions during the emergency LNG release are analyzed. Findings. The analysis of the methods has showed the main uncertainties in predicting the parameters of LNG vapor cloud explosion. Propagation features of LNG vapor cloud, the influence of various gases that are part of LNG are not taken into account. Research application field. The results obtained will allow improving the method for calculating the pressure of the gas-air clouds explosion during the emergency LNG release. Conclusions. The analysis of the real accident with LNG release has showed that the calculated pressures obtained on the basis of the methods are incomparable with the explosion consequences. The further direction for improving the methodology of calculating the explosion pressure of gas-air clouds during the emergency LNG release is determined. To improve the methodology it is necessary to determine the effect of combustible gases, which are part of LNG, on the parameters of the explosion, and also take into account the effect of low temperatures of LNG vapor cloud.

Construction of a mathematical model of vehicles tangent collision during reconstruction of the circumstances of a road accident

This paper considers the task to clarify the circumstances of a traffic accident (TA) involving two vehicles as a result of their lateral tangential collision at low angles. The aim of the study is to construct a mathematical model of a tangential collision of vehicles for the reconstruction of TA circumstances. Owing to the combination of the law of conservation of momentum and the theory of impact using the coefficient of recovery, it was possible to construct a mathematical model that describes the development of such an accident and makes it possible to determine the main parameters of the movement of vehicles after and before the collision. An answer is given regarding the possibility of losing the directional stability of the vehicle and its movement in the lateral direction because of a collision. Based on the mathematical model, the basic parameters of vehicles motion after their side collision at angles of 5–15° were analytically determined, when there are no slip marks on the road surface. A numerical experiment was conducted on the example of a specific accident. The findings make it possible to argue about the possibility of losing the directional stability of vehicles and shifting them to the oncoming lane or curb as a result of collision. A comparison of the results of the numerical calculation with the results of software modeling of accidents and the circumstances that were established in the process of studying a real accident was carried out. It was concluded that the results obtained are consistent and make it possible to more accurately assess the parameters of the movement of vehicles after their lateral tangential collision. In general, this produces more objective results of the reconstruction of TA mechanism in cases where there are no traces of slipping and braking on the road surface. The proposed mathematical model could be used in collisions accompanied by minor deformations or damage to vehicles