Specific Road Research Articles

Generation of traffic input for flexible pavement design

Layered elastic theory (LET) was performed by Burmister. It helped to build mechanistic – empirical (M-E) pavement design. In this study, three different approaches were used to predict Cumulative Equivalent single axle load (C-ESAL) over the design period. Two were based on M-E and one was empirical. In each of these cases, standard axle loads were used as well as weight limits and vehicle classification, according to their axle configurations (single, tandem, tridem). Traffic data came from annual traffic census campaigns over the past ten years. Gross vehicle weight (GVW) and axle weight (AW) data came from a fixed weighing station performed during 31 days in 2020. Two road axis were considered: One having a weighing station (reference road) and one under technical studies (specific road). Traffic road data were used to perform regression analyses and predictions. AW and GVW helped to calculate Axle load equivalency factors (ALEF) and Truck equivalency factors (TEF) on the reference road. These values were projected on the specific road. Frequency distribution, gross vehicle weight distribution, axle load distribution of heavy vehicles are applied on the reference road. We performed overload AW and overload GVW analyses. Comparisons were done for the three approaches and an evaluation of technical studies was proposed, including traffic and AW monitoring and management systems. This work came as a basis for the transposition of M-E calculation of traffic inputs, more accurate and used over the passed fifty years, in Higher Income countries, called AASHTO method for USA, LCPC-SETRA method for France, to Cameroon and Sub-sahara African countries, that have been using empirical generation of traffic inputs over the same period, called CEBTP method.

A Comprehensive Evaluation of Vehicle Intelligent Barrier Avoidance Function under Special Roads Based on G1-CRITIC

As one of the core functions of the autonomous driving of vehicles under special roads, the intelligent barrier avoidance function plays an important role in improving traffic efficiency and ensuring driving safety. Scientific, reasonable, and comprehensive evaluation methods can provide the basis for intelligent vehicles before their use. The comprehensive evaluation index system is constructed for the avoidance ability and avoidance mode of intelligent vehicles against different barriers. The weights of qualitative indicators that are difficult to quantify are determined based on the order relation analysis (G1) method, and the weights of quantitative indicators are determined based on the CRITIC (criteria importance though intercriteria correlation) method. The overall system is comprehensively and quantitatively evaluated through the grey correlation degree method. The correctness of the evaluation method is verified via testing. According to the comprehensive evaluation method studied, the comprehensive evaluation result of the test vehicle is obtained. The intelligent barrier avoidance function of negative barriers is superior to that of positive barriers. The integrated evaluation method can obtain evaluation results of vehicle performance in different test scenarios.

A GIS Approach to Measuring Public Transport Travel Delay on Higher Order Roads in the City of Cape Town

Abstract. On a daily basis, hundreds of thousands of people in the City of Cape Town rely on road-based public transport as a means of commuting. A major factor that influences the passengers’ experience is the travel time to reach a desired destination. Due to various physical and operational factors, some sections of the road network experience high congestion and travel time delays during the morning and afternoon peak periods. Quantifying these delays, and the number of road-based public transport passengers exposed to the delay along a specific road section during a peak period allows informed decision-making and prioritisation. GIS and spatial data analysis are powerful tools to determine where and when such delays occur. Various spatial data sets exist that were jointly analysed to quantify the delay and the passenger volumes exposed to the delay on the city’s public transport network.

A Proactive Stable Scheme for Vehicular Collaborative Edge Computing

Due to the restricted computing resources and high upgrading costs, onboard processors alone cannot meet the quality of service (QoS) requirements of the emerging and constantly upgrading vehicular applications. Computation offloading is a feasible solution to the excessive computation-intensive tasks. Meanwhile, vehicular collaborative edge computing (VCEC) is a paradigm to make the best use of surrounding vehicles' idle computing resources when the task density on a specific road segment suddenly increases. However, the high mobility of vehicles and the ad hoc nature of vehicular networks make maintaining stable task offloading performance quite challenging. Especially when the idle computing resources surrounding vehicles are insufficient, there has not been researching to achieve stable offloading performance. Based on this, we consider a proactive strategy that can decrease the events that affect performance stability. First, we propose a mobility prediction model for future network status prediction. Then we design an adaptive task offloading scheme based on proactive adjusting (PATO) to maintain stable task offloading performance. The scheme includes a state processing model and a deep reinforcement learning (DRL)-based task offloading algorithm. Finally, we conduct extensive simulations in various scenarios with insufficient resources to validate the task offloading performance of PATO. Compared with the existing DRL-based algorithm, the simulation results show that PATO can improve the mean offloading utility by 95.4% and the completion ratio by 15.8%.

Do Traffic Countermeasures Improve the Safety of Vulnerable Road Users at Signalized Intersections? A Combination of Case-Control and Cross-Sectional Studies Using Video-Based Traffic Conflicts

Driven by the vision of eliminating road fatalities, Vision Zero initiatives have been widely adopted by many cities around the world, with significant investment of resources in various safety countermeasures. However, there is still a lack of reliable quantitative evidence on the effectiveness of those countermeasures on the traffic conflict frequency at intersections. This research attempts to address this challenge with a combination of case-control and cross-sectional studies, aiming at quantifying the safety effects of three commonly applied Vision Zero countermeasures, namely, leading pedestrian interval, no right turn on red, and installation of a dedicated bicycle lane. A case study was conducted using video trajectory data from 10 signalized intersections in the City of Toronto, Canada. The traffic interactions between vehicles and vulnerable road users were extracted using a video data processing platform, and two surrogate measures of safety, including post-encroachment time and conflict speed, were obtained, and then used to classify the conflict severity into different levels. A comparative analysis using mixed-effects negative binomial regression was conducted to quantify the impacts of different treatments on the frequency of traffic conflicts under specific road weather and traffic conditions. The results show that these three types of traffic countermeasures can effectively reduce the frequency of high-risk and moderate-risk traffic conflicts, moderated by various traffic exposure and weather and environmental conditions and accessible pedestrian signals. These findings could help road safety engineers and decision makers make better informed decisions on their road safety initiatives and projects.

Evaluation of Bus Lane Layouts Based on a Bi-Level Programming Model—Using Part of the Qingshan Lake District of Nanchang City, China, as an Example

Bus lanes have gradually become an indispensable infrastructure for the development of urban public transportation networks. A bi-level programming model is used herein to compare the total travel time of social vehicles and buses before and after the bus lane is set up to judge whether the bus lane layout plan is scientific and reasonable considering the road network. The model’s effectiveness is verified using areas of Qingshan Lake in Nanchang City, and the operational efficiency of one bus lane before and after establishing the dedicated bus lane is analyzed. The case results show that the bus lane layout evaluation needs to consider the traffic benefits of a specific road and also judge whether the total travel time of the network traffic volume is improved from the macroscopic road network level. The research results provide theoretical support for the rational layout of bus lanes and are of practical significance for prioritizing the development of public transportation and promoting the sustainable development of urban transportation.

Method of calculating the influence of the suppression system on the autonomy of an armored combat vehicle

A method of calculating the effect of vibrations of the sprung body and the operation of the suspension system of an armored combat vehicle on its autonomy has been developed. One of the main indicators of autonomy is the power reserve, which depends on the specific fuel consumption. In the process of moving over bumps, a significant part of the power plant's energy, and accordingly fuel, is spent on the occurrence of vibrations of the sprung body of the machine and its unsprung masses. Then the energy of these vibrations is converted into heat in the damping devices of the chassis. In difficult road conditions, on real tracks, these losses average 10...15% of power plant power. In resonant modes, when moving along a harmonic profile of irregularities, they can reach 30%. Calculation and reduction of these costs will increase the autonomy of the armored combat vehicle.
 The methodology is based on the calculation of the energy balance of the longitudinal, angular and vertical vibrations of the sprung body of the machine and the vibrations of its unsprung masses, the deformation energies of the elastic elements of the suspension, the rubber hinges of the guide devices and tires, as well as the energies absorbed by the suspension damping devices, its rubber hinges and tires. Depending on this balance, there is either an increase in the load on the power plant and, accordingly, an increase in fuel consumption, or it decreases and the energy of the suspension system becomes the driving force. To calculate the oscillations of the sprung body and components of the energy balance, it is necessary to use a mathematical model of the movement of an armored combat vehicle over bumps. All the necessary parameters of the machine, a deterministic road profile of bumps and a high-speed driving mode are set. Amplitudes and velocities of longitudinal angular and vertical oscillations of the sprung body and oscillations of unsprung masses are calculated from these input data. For each suspension, its kinematics, twisting angles of torsions, forces in damping devices and the amount of movement of their working bodies and deformation of rubber joints and tires are calculated. Next, the magnitude and sign of the change in the total energy of the sprung body and the sprung system at each moment of time is determined. Based on the additional energy calculated using the efficiency coefficients of the engine and transmission, the additional power supplied by the power plant and, accordingly, additional fuel consumption are determined.
 Thus, it is possible to evaluate and compare with each other the reduction in the range of the armored combat vehicle, which is caused by the fluctuations of the sprung body and the operation of the suspension system, depending on the type and characteristics of the suspension, when driving in specific road conditions, at the given speed modes. With the help of the developed methodology, it is possible to carry out structural and parametric optimization of the suspension kinematics and the characteristics of its elastic elements and damping devices, in order to reduce fuel consumption and increase the autonomy of the armored combat vehicle. This technique will be useful in assessing the expediency of using the energy recovery system of the suspension system, depending on the purpose and conditions of operation of combat armored vehicles.

A Review of Surrogate Safety Measures Uses in Historical Crash Investigations

Historical road crash data are the main indicator for measuring road safety outcomes. Over the past few decades, significant efforts have been made in obtaining and exploiting Surrogate Safety Measures (SSMs). SSMs have the potential to provide excellent sustainable road safety indicators and proxy measurements which can complement traditional historical crash analyses or even substitute them. By using SSMs, crash data collection demands can be bypassed and areas can be investigated before crashes occur. Due to such advantages, the objective of the present research is to provide a review of the scientific literature regarding studies exploiting SSMs for historical crash record investigations. Specifically, 34 studies were examined, providing insights on the different types of SSMs collected under real road environment conditions, the way they are collected, their connection with specific road crash types, and the type of the developed statistical models are examined and discussed. Particular focus is also placed on the temporal dimension of the collection period of both SSMs and road crashes. Finally, the overall trends deriving from the reviewed studies are summarized and future research directions are provided.

An e-learning Course Effect on Swedish Ambulance Commanders' Decision-making in Simulated Road Tunnel incidents–Preliminary findings

Introduction:Road tunnel systems are becoming increasingly complex. Regardless of incident, the confined nature of the road tunnel impairs responding emergency services accessibility, with a risk for delay in treatment of time-sensitive injuries such as pneumothorax or internal hemorrhage. Consequently, the need for rapid decision-making by the emergency services commanders is increased. However, in Sweden ambulance commanders lack experience and training in managing road tunnel incidents. This may further delay the medical response.The aim is to investigate if the ambulance commander decision-making in simulated road tunnel incidents may be improved by a specific road tunnel incident e-learning course.Method:A web-based intervention study was performed with 20 participants; 10 participants in the intervention and control group, respectively. The control group received a pre-recorded general lecture on incident management. The intervention group received a specific road tunnel incident e-learning course, consisting of five interactive modules with learning materials (e.g. road tunnel structures, collaboration and safety). All participants participated in web-based simulations of major road tunnel incidents at one and six months post-intervention. In these simulations, participants acted as ambulance commanders and decided on the best course of action in 15 dissimilar and multiple choice-based management decisions. For each decision, time and choice of decision were recorded as outcome measurements.Results:Preliminary analysis from the one-month follow up simulation indicates that none of the participants decided to enter the road tunnel system at the early stage of the incident. The motivation for the participants decision-making was not clear.Conclusion:The cautiousness to enter the road tunnel system will impair the emergency medical services response, including delaying vital medical care. Further research into the reasoning behind this decision is needed and identified causes may be further addressed in updated educational materials and collaborative discussions.

Life cycle assessment of greenhouse gas emissions with uncertainty analysis: A case study of asphaltic pavement in China

There are a large number of complex uncertainties in the road life cycle assessment (LCA) analysis process and ignoring these uncertainties will lead to biased results and decision-making. To improve the accuracy of the quantification of carbon emissions (CEs) over the life cycle of pavements, a system for quantifying uncertainty was developed and a case study was conducted in conjunction with sensitivity analysis. The data quality index (DQI) combined with the beta distribution method was implemented to assess parameter uncertainty. The uncertainty of the model parameters was characterized using the results of slice sampling. The uncertainty in the shape of the model was described by the difference before and after the correction of the Hermite orthogonal polynomials. Various uncertainties are conveyed by the Monte Carlo simulation sampling method. To provide reliable emissions data, VISSIM and MOVES were used to calculate additional CEs from congestion. This study assesses the uncertainty of a specific road LCA case. The results show that uncertainty in model form has the greatest impact on results. The use and maintenance phases are key stages for improving the reliability of pavement life cycle CEs, with CEs and uncertainty contributions of around 90% and 94% respectively. The time-triggered conservation strategy has a 75% probability of dominance. This study provides a comprehensive theoretical basis for improving the quality of road LCA CE results, and also makes recommendations for the development of green and low-carbon road engineering.

Nomophobia, attitude and mobile phone use while riding an E-bike: Testing a dual-process model of self-control

Using a mobile phone while participating in traffic is a growing safety concern all over the world. However, mobile phone use (MPU) while riding an e-bike has not yet been given enough attention by researchers and practitioners. To fill this gap, this study conducted a preliminary online interview and a questionnaire-based survey in China to study what kinds of MPU behaviors e-bikers commonly engaged in and the prevalence of these behaviors. A conceptual dual-process framework consisting of e-bikers’ demographics, e-bike usage pattern, nomophobia, attitude and self-control was also proposed to analyze the psychological mechanism underlying this phenomenon. The preliminary online interview revealed 7 typical types of MPU behaviors performed by e-bikers on the road. Results of the questionnaire survey showed that though the overall frequencies of MPU behaviors were low, nearly 60% of the respondents reported a history of mobile phone use during riding in the last three months. E-bikers’ MPU frequencies were significantly impacted by e-bikers’ gender, attitude, self-control and information-related nomophobia. Besides, self-control also significantly moderated the predictive effects of information-related nomophobia and attitude on MPU frequencies while ring an e-bike. Fears of being unable to access information on the mobile phone only contributed to MPU at low levels of self-control. In contrast, the protective effect of unfavorable attitude against engagement in the behavior became stronger at high self-control levels. The results not only offer deeper insights into the current situation of MPU among e-bikers in China, but also could facilitate the development of intervention and safety promotion strategies targeting this specific road user group.

Cross-domain cooperative route planning for edge computing-enabled multi-connected vehicles

The safety and effectiveness of transportation systems could be improved significantly through edge computing which can be relied on to assist intelligent and connected vehicles (ICVs). However, with the rapid increase in the number of ICVs, traffic congestion worsens as a result of demand exceeding the capacity of a specific roads. To solve the issues, a cooperative route planning transportation system is proposed for edge computing-enabled multi-connected vehicles. This system is intended to achieve the cross-domain load balancing of connected vehicles and traffic flow domains. Furthermore, an iterative interior point is proposed to minimize the overall probability of traffic congestion by directing the routes of multi-connected vehicles in a coordinated way. According to the simulation results, the suggested scheme reduces the average travel time by 4.85%, 15.62%, 35.54% and 63.11% compared with others. Meanwhile, there is a significant improvement of performance in terms of traffic congestion rate and traffic load.

Influence of depressed road configuration on downwind pollutant concentrations: A CFD study under various thermal stability conditions

Outdoor air quality is a major concern worldwide, especially in urban areas. In this paper, the influence of depressed roads (specific road designs where the road's surface is lower than the surrounding ground level) on the downwind pollutant concentration was assessed using a validated Computational Fluid Dynamics (CFD) solver, for eight road depths (D) and thirteen stability conditions (Richardson numbers, Ri). Depressed roads can decrease downwind pollutant concentrations compared to classical roads, but only under neutral and unstable thermal conditions. Under neutral thermal condition, a threshold is reached for D = 0.375, leading to a maximal pollution reduction of around 10% at pedestrian level and around 5% at the first-floor level. In such stability conditions, pollutant concentrations are lower as D increases and Ri decreases. Under stable conditions, such roads lead to higher pollutant concentrations. Four equations allowing to predict the downwind pollutant concentrations are given depending on the distance from the road centerline, the road depth, and the thermal stability condition. The results of this study provide pre-construction guidance on whether a depressed road should be considered to protect human health, as well as predictive tools to assess the beneficial or adverse impact of such structures on air quality.

Studying Executive Function in Culturally Meaningful Ways

ABSTRACT Children’s development of executive function is a good candidate for studying cultural differences because it is a necessary capacity for becoming competent participants in cultural activities, and yet it is also likely to be shaped by culturally organized everyday experiences, with potential consequences for children’s development and learning. An ethnographically grounded study with Yucatec Maya children was conducted to explore cultural bias in existing theoretical constructs and methods. Yucatec Maya children autonomously organize their daily activities within a dense web of family social connections and work responsibilities. Yet small pilot samples of 4- to 8-year-olds were uninterested in and performed poorly on many traditional measures of EF due to a number of cultural assumptions inherent in the tasks’ logic and demands. Specific cultural road blocks were identified, including assumptions about motivation, task meaning, rules of social interaction, and specific cultural beliefs. Several novel tasks were then developed, comprised of contextually situated, goal-driven tasks, that children were more motivated to engage in. To check on the accuracy of our analysis we propose a design for a future comparative study consisting of a mix of traditional tasks (both culturally interpretable and culturally inappropriate for Yucatec Maya children), and novel, contextually embedded tasks that were engaging for Yucatec Maya children. We close with a cost/benefit analysis of using culturally meaningful research to study children’s development.

MDFD: A multi-source data fusion detection framework for Sybil attack detection in VANETs

Sybil attacks in Vehicular Ad-Hoc Networks (VANETs) conduct malicious behavior by falsifying and faking messages between vehicles. It poses a significant threat to the safety of vehicle movement. Meanwhile, because Sybil attacks often hide the real identity of the attacker with the help of a legitimate pseudonym, making it very difficult to detect them. Most existing detection schemes use a single data source, which is not enough to describe the specific characteristics of the attack behavior accurately, while their detection performance is also affected by real scenario factors such as traffic flow and attacker density. Therefore, we propose a multi-source data fusion detection framework for Sybil attacks based on the study of the behavior characteristics of Sybil attacks and the impact of the attacks on the traffic flow state. We get basic safety messages data, map data and sensor data and then obtain multi-dimensional data fusion features from four aspects: spatio-temporal location relationship, traffic flow state change, vehicle behavior characteristics and sensor data verification, and finally use machine learning classification model to complete the detection of attack behavior. Experimental results show that our proposed attack detection framework is able to locate the specific road section where the attack occurred in a realistic and complex traffic scenario containing different road types without using trusted vehicles as observation nodes, and has good generalization capability. the average detection accuracy of the MDFD framework for four types of compound attacks is as high as 97.69%.

Measuring accessibility to public services and infrastructure criticality for disasters risk management

Component criticality analysis of infrastructure systems has traditionally focused on physical networks rather than infrastructure services. As an example, a key objective of transport infrastructure is to ensure mobility and resilient access to public services, including for the population, service providers, and associated supply chains. We introduce a new user-centric measure for estimating infrastructure criticality and urban accessibility to critical public services - particularly healthcare facilities without loss of generality - and the effects of disaster-induced infrastructure disruptions. Accessibility measures include individuals’ choices of all services in each sector. The approach is scalable and modular while preserving detailed features necessary for local planning decisions. It relies on open data to simulate various disaster scenarios, including floods, seismic, and compound shocks. We present results for Lima, Peru, and Manila, Philippines, to illustrate how the approach identifies the most affected areas by shocks, underserved populations, and changes in accessibility and critical infrastructure components. We capture the changes in people’s choices of health service providers under each scenario. For Lima, we show that the floods of 2020 caused an increase in average access times to all health services from 33 minutes to 48 minutes. We identify specific critical road segments for ensuring access under each scenario. For Manila, we locate the 22% of the population who lost complete access to all higher health services due to flooding of over 15 cm. The approach is used to identify and prioritize targeted measures to strengthen the resilience of critical public services and their supporting infrastructure systems, while putting the population at the center of decision-making.

On the scheduling of lifecycle network-level pavement maintenance: modelling and applications

ABSTRACT Pavement maintenance is a prominent issue in road traffic systems and plays a fundamental role in ensuring the safety, mobility and comfort of road networks worldwide. This paper introduces an innovative approach for scheduling network-level pavement maintenance based on mathematical planning, guided by the principle of lifecycle cost analysis (LCCA). The primary objective is to optimise pavement performance while minimising maintenance costs, ultimately achieving cost-effectiveness. In particular, the method aims to solve the ‘2W1H’ problem (i.e. ‘Which’, ‘When’, and ‘How’), which implies identifying the specific road sections, determining an appropriate maintenance timeline, and selecting the most effective maintenance treatment for long-term pavement maintenance planning. The proposed method comprises a bi-level optimisation model. The upper layer is a multi-objective optimisation model which concurrently maximising the lifecycle pavement performance while minimising the lifecycle costs; the lower layer evaluates the impact of pavement maintenance operations on travellers' route choice behaviour by employing the user equilibrium problem to determine the change in user cost attributable to a specific maintenance scheduling scheme. A meta-heuristic algorithm is utilised to solve the model and acquire a Pareto front for multi-objective optimisation. Furthermore, we discuss the practical engineering applications under budgetary constraints and pavement performance requirements, followed by the consideration of parameter uncertainties in pavement performance prediction models. The numerical experiments demonstrate that our approach can deliver pavement maintenance scheduling outcomes across various scales of road networks, and highlight the promising potential of our approach for future pavement management endeavours.

Leveraging Infrastructure BIM for Life-Cycle-Based Sustainable Road Pavement Management.

The latest developments in the field of road asphalt materials and pavement construction/maintenance technologies, as well as the spread of life-cycle-based sustainability assessment techniques, have posed issues in the continuous and efficient management of data and relative decision-making process for the selection of appropriate road pavement design and maintenance solutions; Infrastructure Building Information Modeling (IBIM) tools may help in facing such challenges due to their data management and analysis capabilities. The present work aims to develop a road pavement life cycle sustainability assessment framework and integrate such a framework into the IBIM of a road pavement project through visual scripting to automatically provide the informatization of an appropriate pavement information model and evaluate sustainability criteria already in the design stage through life cycle assessment and life cycle cost analysis methods. The application of the proposed BIM-based tool to a real case study allowed us (a) to draw considerations about the long-term environmental and economic sustainability of alternative road construction materials and (b) to draft a maintenance plan for a specific road section that represents the best compromise solution among the analyzed ones. The IBIM tool represents a practical and dynamic way to integrate environmental considerations into road pavement design, encouraging the use of digital tools in the road industry and ultimately supporting a pavement maintenance decision-making process oriented toward a circular economy.

RESEARCH TO PROPOSE THE MAXIMUM LONGITUDINAL GRADE FOR MILITARY ROADS

In order to serve coaching and combat readiness in the new situations, in recent years, our Army has been invested and equipped with many innovative and modern weapons and armaments. Many types of them are placed on military vehicles which have peculiar sizes, loads and dynamic characteristics. Therefore, military ways whould have been designed separate geometric elements, especially in the difficult conditions: craggy terrain conditions, or on military routes that are quickly built without pavement. In this article, the authors studied the theoretical basis and applied it to build dynamic factor diagrams of some special military vehicles by analytically method as a basis of offering the maximum longitudinal grade for specific military roads of the Vietnam People’s Army.

Digital transport traseology based on Agisoft Metashape and unmanned aerial vehicle

Introduction. A vehicle and trace evidence analysis is one of the most requested types of examinations performed within the framework of criminal cases on road traffic accidents. The main methodical guidelines for traffic and trace evidence analyses were developed in the past century, while nowadays the fourth industrial revolution is on the rise. The industrial revolution is based on computer and information technologies, various software and hardware tools. Hence there is a vital necessity in update of the vehicle and trace evidence analysis methodology in order to conform to current-day realities.Materials and methods. Results of use of the unmanned aerial vehicle and Agisoft Metashape software are presented in the article in the context of specific road traffic accidents. It was made clear that application of this method has the following advantages: firstly, time of fixation of objects of the roadway network, vehicles and their traces on traffic ways is significantly reduced; secondly, fixation accuracy is improved; thirdly, use of the method makes it possible to establish all actual facts needed to perform analysis of the mechanism of a road traffic accident. Digital models obtained using this method could be used for 3D modeling, what offers an opportunity for more accurate determination of a mode and an angle of approach of vehicles before an accident with significant reduction of financial and time expenditures.Results. It was shown that digital models of road traffic accident sites and vehicles could be entered into the case file in general as well as into an expert’s statement in particular. Such entering will improve objectivity and believability of the conducted examination. Digital models of road traffic accident sites (digital twins) could be stored for an indefinitely long time and could contain the entire information on physical accident scene. Therefore such digital models are considered as valuable information while performing additional or repeated examinations.Conclusion. The proposed method for creating a digital model of a vehicle or a site of a traffic accident can be used in digital transport traceology.