Edited by: Tecnológico Superior Corporativo

Edwards Deming

January - March Vol. 6 - 2 - 2023

https://revista-edwardsdeming.com/index.php/es

e-ISSN: 2576-0971

Received: December 08, 2022

Approved: May 22, 2023

Page 42-53

Virtual reconstruction in traffic: a review of

techniques

Reconstrucción virtual en materia de tránsito: una revisión de

técnicas

María Fernanda Padilla Ortiz

Christian Esteban Rengifo Dávila

ABSTRACT

Virtual reconstruction of traffic scenes is an increasingly

useful tool for investigators and experts in the field. It

allows investigators to obtain a clearer picture of the

events surrounding a traffic accident, allowing for a more

accurate assessment of the data and a better understanding

of accident mechanisms. This qualitative research under a

systematic review presents the techniques and methods of

virtual reconstruction in traffic that have been developed

in recent years. As a result, eight articles published

between 2020 and 2023 that are part of high impact

repositories were obtained. It is concluded that virtual

reconstruction technology for the analysis of traffic

accident situations continues to make progress.

Keywords: Virtual reconstruction, forensic techniques,

accident analysis, 3d reconstructions, reconstruction

technology.

RESUMEN

La reconstrucción virtual de escenas de tránsito es una

herramienta cada vez más útil para los investigadores y

expertos en el campo. Permite a los investigadores

obtener una imagen más clara de los hechos que rodearon

un accidente de tránsito, lo que permite una evaluación

más precisa de los datos y una mejor comprensión de los

mecanismos de accidentes. Esta investigación de corte

cualitativo bajo una revisión sistemática presenta las

* Abogada de los tribunales y juzgados de la República. Universidad Nacional

de Chimborazo. mafer201215@gmail.com

https://orcid.org/0000-0003-3290-8374

Magíster en criminalística y ciencias forenses. Universidad Nacional de

Chimborazo. christianrengifo@hotmail.com

https://orcid.org/0000-0002-3367-8796

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e-ISSN: 2576-0971

técnicas y métodos de reconstrucción virtual en materia

de tránsito que se han desarrollado en los últimos años.

Como resultado se obtuvo ocho artículos publicados entre

el 2020 y 2023 que son parte de repositorios de alto

impacto. Se concluye que la tecnología de reconstrucción

virtual para el análisis de situaciones de accidentes de

tránsito sigue teniendo avances.

Palabras clave: Reconstrucción virtual, técnicas forenses,

análisis accidentes, reconstrucciones 3d, tecnología de

reconstrucción.

INTRODUCTION

Road traffic accidents are one of the leading causes of death and injury in the world.

Recent statistics show that more than 1.35 million people die each year in road traffic

crashes, and between 20 to 50 million are injured or disabled, moreover, this figure has

increased significantly in recent years. (World Health Organization (WHO), 2018).. In

Ecuador, in the year 2021, 2131 people were killed and 17 532 injured in traffic accidents,

which represents an increase of 33, 9 % and 33.8 % respectively compared to 2020. The

number of traffic accidents in Ecuador is worrisome, especially because of the number

of human lives lost as a result of these accidents. This situation has become a social

problem for various reasons (Saltos Salgado et al., 2005).(Saltos Salgado et al., 2020).

In the report published by INEC (2022) on traffic accidents details the most common

causes, where the driver's carelessness and recklessness with 43.5% is the main cause,

followed by disrespect for traffic signs with 21%, speeding with 14.3%, drunkenness or

drug use with 8%, pedestrian recklessness with 4.6% and other causes with 8.8%.

In addition, violators of the Organic Law of Land and Roads in Ecuador receive sanctions,

but this does not prevent the occurrence of these acts. This is due to the lack of

responsibility of those involved. As an example, Article 106 of the same Law determines

that "traffic infractions are those actions or omissions that, being able and should be

foreseen, but not wanted by the cause, are verified due to negligence, imprudence, or

inexperience, or due to non-observance of the laws, regulations, resolutions and other

traffic regulations" (Asamblea Nacional Constituyente, Asamblea Nacional

Constituyente, 2001). (National Constituent Assembly, 2008).

Therefore, in any traffic accident it is important to determine the cause and responsibility

for an accident, which is possible through forensic techniques because they allow

determining the speed of the vehicles involved, the direction of travel, the location of

the impact, any damage to the vehicle, evidence of reckless driving, and any other

relevant information to determine the cause of the accident.

In addition, accidents include the collection and analysis of physical evidence, the

collection and analysis of tire tracks, pavement marks, vehicle damage, steering and

speed tests, alcohol or drug tests, and other relevant tests. Once the physical evidence

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is collected, forensic experts conduct an analysis to determine the cause of the accident.

This involves observation of the physical evidence, flight line of objects related to the

accident, accident reconstruction, and vehicle trajectory reconstruction. The analysis

also involves studies of the braking and acceleration patterns of the vehicles involved.

They also collect and analyze documentary evidence. This evidence contains police

reports, witness reports, statements, ticket tickets, vehicle maintenance records,

information on the condition of the vehicles before the accident, and other documents

related to the accident to determine cause and liability.(Montes Loaiza et al., 2013; Tian

et al., 2010).In the same sense, Rodriguez (2017), states that there are major deficiencies

in the technical documentation related to the investigation and reconstruction of traffic

accidents and other forms of violent death.

With the advancement of technology it has been possible for forensic science to take

steps for the benefit of the investigation and in order to present evidence based on

information and communication technologies. Thus, this research presents a systematic

review of ICT-based methodologies and tools in traffic forensics developed in the last

decade.

MATERIALS AND METHODS

This research was based on the report of (Kitchenham, 2004) to conduct a systematic

review of the literature on methodologies and ICT techniques used for traffic accident

reconstruction to identify, evaluate and interpret all available relevant documentation. A

source selection strategy with inclusion and exclusion criteria was carried out, as well

as a predefined search to process all research related to the research question. This

made it possible to obtain and evaluate the available evidence to arrive at a synthesized

result.

The following research question was posed: What are the methodologies or techniques

available for the reconstruction of traffic accidents based on virtual technologies?

The next step was to determine the sources of information search, considering the

importance of reliable and relevant research, the use of academic articles, academic

congress reports found in the repositories of Science direct and Scielo was determined.

In relation to the search strategy, the keywords and terms used were "traffic

reconstruction", "crash reconstruction", "virtual methods accidents", "digital techiques

accidents", "traffic accident reconstructions", "3d traffic accidents". The temporality of

the articles was delimited between publications and preprints from the year 2020, and

articles written in English, considering that this is the language in which the journals with

the greatest impact publish on the subject.

Once the documents were obtained, the abstract was reviewed for agreement with the

research objective and the title search string "accident or techniques" was applied to the

terms.

Inclusion criteria

Articles and conference reports published from 2020 to 2023.

Articles found in Scopus.

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e-ISSN: 2576-0971

Open access documents.

Research and review articles.

Exlusion criteria

Articles and short communications.

Gray literature.

An article was only selected if it was found in more than one database.

Slides and books.

Table 1: Number of studies with search criteria

filters

Refined

string/items.

Aligned to the

objective/summary

traffic

reconstruction

2214

473

crash

reconstruction

455

133

virtual methods

traffic

1755

540

TOTAL

Source: Researchers, 2023

Twenty-six articles were obtained, which were subjected to a more extensive reading

by the researchers and finally eight studies were selected that provide relevant

information for this research. The results and conclusions of the documents were read

in order to discover how these researchers have approached the topic of investigation

and the solutions or points of view that they disseminate. Table 2 presents the articles

analyzed.

Table 2: Detail of selected articles

Title

Authors

Magazine or main base

Using the scanners and drone

for comparison of point cloud

accuracy at traffic accident

analysis.

(Kamnik et al.,

2020)

Accident Analysis &

Prevention

Method for automated

generation of road accident

scene sketch based on data

from mobile device camera

(Saveliev et al.,

2020).

Proceed to

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e-ISSN: 2576-0971

Usage of Digital Evidence in

the Technical Analysis of

Traffic Collisions

(Malinová et al.,

2021).

Transportation Research

Procedia

Application of Close-Range

Photogrammetry in

Documenting the Location of

an Accident

(Stehel et al.,

2021).

14th International

scientific conference on

sustainable, modern and

safe transpor

Data-driven online traffic

reconstructions: Interactively

optimizing in virtual reality

(Wang et al., 2022)

Computers & Graphics

Using the iPhone's LiDAR

technology to capture 3D

forensic data at crime and

crash scenes

(Kottner et al., 2023).

Forensic Imaging

A feed-forwarded neural

network-based variational

Bayesian learning approach for

forensic analysis of traffic

accident.

(Xie et al., 2022).

Computer Methods in Applied

Mechanics and Engineering,

Circuits, Systems,

Communications and

Computers (CSCC),

International Conference on

(Sevcik et al., 2023).

Circuits, Systems,

Communications and

Computers (CSCC),

International Conference on

RESULTS

The eight selected papers were re-read taking into consideration how they answer the

research question. In the first paper that is part of this review it was determined that

the authors sought to test whether sketches obtained from different 3D point clouds

can be produced faster and more accurately than sketches obtained from classical police

measurements. To do so, they compared classical police work and sketching with

terrestrial laser scanners Riegl VZ-400i, Faro Focus S70, Geoslam ZebRevo 3D and data

collection from a Topcon Falcon 8 drone, all of which were used for 3D modeling and

sketching. They compared the accuracy using a graphical approach. For the subsequent

visual inspection of the traffic accident scene, the most suitable source is an orthophoto

obtained using the Surface from Motion (SfM) method, which is the result of processing

a series of georeferenced photographs taken from the UAV. They conclude that the

digital data provides the opportunity for a second look at the accident scene, whether

it is a quiet street or a busy road. The use of an accurate 3D representation of the scene,

such as a compilation of the crash data, can be helpful in addressing questions and doubts

that arise. This also provides the option to import directly into crash simulation tools,

such as PC-Crash or Analyser PR. (Kamnik et al., 2020)

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Thus, for the authors Saveliev et al. (2020) describe in their study that despite

government efforts to reduce the road fatality rate, road traffic accidents still occur

frequently and that accident scene sketches are performed manually in most countries,

which affects the quality and quantity of data collected. This poor quality of sketches

contributes to the return of cases for investigation. To improve this situation, the use

of an automatic RTA scene sketch generation system using mobile devices is proposed.

This will enable traffic officers to perform their work faster and more efficiently, increase

the accuracy and precision of traffic accident registration, and eliminate the subjectivity

of data presentation. The proposed method requires only a mobile device with a camera

to operate, which automatically generates sketches of road scenes. The process consists

of video recording vehicles and surrounding environments with a mobile device; building

maps and reconstructing the camera path using the SLAM method; reconstructing the

3D scene and classifying objects with convolutional neural networks; calibrating the scale

of the generated 3D scene and sizing the location of other objects; converting the 3D

model into a 2D RTA scene sketch. The developed system provides users with

recommendations on how to record video from different angles to capture all required

components, including the relative location of vehicles and static objects, vehicle damage

and surroundings within a 10 m radius. The video collected by the user will be

compressed on a mobile device and sent to a cloud for further processing. To generate

ATR scene sketches in an automated manner, we consider the basic stages of video

processing.

The ORB SLAM2 algorithm that is used offers faster initialization and operation, higher

model quality, and open source. It converts the video recorded by the user into a

sequence of frames, identifying features (key points) in each frame and positioning them

in a 3D space. The algorithm also generates an unoriented weighted visibility graph using

the keypoints and frames (Saveliev et al., 2020)

In the following research published by Malinová et al. (2021) they state that there are 3

ways to get data from the ECU: the first uses regular diagnostic tools, the second uses

the CDR (Crash Data Retrieval) system and the third uses the GIT Tool co. system.

Using diagnostic tools, maintenance and service related data can be read through the

OBD / OBD II socket. These records, known as freeze frame data, can be very useful

for accident analysis, although they are usually encrypted and only accessible to car

manufacturers. Thus, with this background, the authors state that the use of CDR (Crash

Data Retrieval) extracts and decodes the information stored in

The CDR system allows to extract and decode the information stored in the ACM

(Airbag Control Module). And that the data once downloaded can record up to 5

seconds before and after the accident, in addition to data on the speed difference, engine

speed, whether braking is taking place, the ignition cycle at the time of the collision, the

state of the seat belt and the state of the airbag. In addition, they specify that the data

must be stored securely to prevent tampering and be available to national authorities

for accident analysis. It must also be possible to accurately collect the model, version

and variation of the vehicle, as well as the active safety and accident prevention systems

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installed in the vehicle. The authors conclude that

15-20% of EDR (Event Data Recorder) equipped cars are on the roads of the European

Union and that these vehicles leave behind digital evidence after an accident, which can

be evaluated like any other forensic evidence. The CDR (Crash Data Recorder) system

allows the police, experts and forensic scientists to do a thorough job. This tool is

capable of recording 5 seconds before a crash, the moment of the collision and another

2 seconds of displacement, which provides an objective reconstruction of

accidents(Malinová et al., 2021)..

Another technique presented in this research is the use of short range photogrammetry

where the position of the camera is generally stationary, placed on the ground and used

for objects ranging in size from 0.5 m to 200 m. This technique is based on the creation

of a point cloud in space where one condition is

that all light rays should be at the same point on the measured object without appreciable

scattering. In addition, it is essential to evaluate the lighting conditions at the accident

site to ensure the quality of the images and documentation obtained. Direct sunlight and

lack of visibility without the use of lighting equipment can cause degraded results of the

site documentation. In so far as under the accident analyzed by (Stehel et al., 2021) which

had adverse conditions the result obtained was inaccurate due to insufficient illumination

of the scene and, consequently, difficult triangulation of the points in the captured images

because they were not identifiable in sufficient number in the individual images.

The authors of the research entitled "Data-driven online traffic reconstructions:

Interactively optimizing in virtual reality", proposed in their paper a 3D online traffic

reconstruction method based on video data and traffic simulations. The method

consisted of two parts: data preprocessing to obtain structured vehicle trajectories and

trajectory reconstruction to obtain complete and smooth vehicle trajectories.

Specifically, they first used the online MOT method to extract the vehicle trajectories

from the videos and transform them to the geodetic coordinate system using an inverse

projection transformation (IPP). Second, they introduced a traffic simulation method to

predict the vehicle trajectories and implemented the Kalman filter to optimize the

vehicle trajectories according to the extracted trajectories and the predicted

trajectories. Then, they iteratively optimized the traffic simulation parameters based on

the optimized trajectories using the Covariance Matrix Adaptive Evolutionary Strategies

of Adaptation (CMA-ES) algorithm when needed(Wang et al., 2022).

The following published paper aimed to evaluate the use of Recon-3D through example

scenarios to determine if this technology could be applied to record incident or crime

situations. The researchers used an iPhone 13 Pro along with the Recon-3D application

to record two indoor environments, a simulated crime situation and a garage, and an

external one of a parked car. Each location was captured multiple times and they

concluded that Recon-3D for iOS, which is equipped with Apple's latest LiDAR

technology, offers a simple and fast workflow for documenting in 3D with an iPhone or

iPad. Results from three test scenarios show that the imaging process is very

straightforward and allows forensic investigators or police officers to document a crime

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or accident within minutes. While more validation studies are needed, Recon-3D

appears to be a useful application for forensic pathologists(Kottner et al., 2023). A

published paper that, while not specifically describing a 3D reconstruction method or

technique, focuses on the development of an algorithm that vastly improves the

computation for 3D reconstructions. The researchers developed a computational

algorithm based on variational Bayesian learning that allowed them to inversely identify

the deformation field of a crashed car, calculate the residual deformation fields from the

final damaged structural configuration, and evaluate the strength of the crashed vehicles.

This technique allowed for greater computational efficiency by reducing the number of

iterations and improving the accuracy of the registration results, since the location of

the nodes was largely maintained during the registration process. These unique features

of the developed machine learning algorithm were found to be essential for forensic

analysis of traffic accidents and strength assessment of crashed vehicles(Xie et al., 2022)..

With respect to their perspective they state that for 3D reconstruction under a

sophisticated approach to crime scene documentation and in-depth forensic analysis the

quality of the results is strictly dependent on the source data, thus they propose an

evaluation triangle to assess the applicability of the method where they identify the

feasibility, critical requirements and individual factors for 3D reconstruction of crime

scenes. They further focus their proposal on an evaluation methodology that makes use

of the feasibility identification and evaluation triangle to address the existing dependency.

They presented a crime scene in a virtual reality workflow to show the connection

between the process and the individuals(Sevcik et al., 2023).

DISCUSSION

The first conclusion presented by this research is based on the methodology applied for

this systematic review, where the choice of the source of information allowed an

approach to everything that researchers have developed in recent years with respect to

crime scene reconstructions and provides a clear perspective on the subject and its

progress, especially in the European Union and the Asian continent, which have

published the most information. However, despite this, it is important to emphasize the

use of the resources as part of prototypes that can be used and are expected to be

adopted in research after being perfected and improved with the support of public and

private institutions.

As a second conclusion, traffic accident reconstruction technology has the potential to

significantly improve road safety. This technology has proven to be a useful tool for

recreating and analyzing the events surrounding a traffic accident, allowing traffic

authorities and investigators to better understand how accidents occurred and help

prevent future incidents. Technological advances also allow investigators to track vehicle

information, better understand impact dynamics, and obtain high-quality images for

better results. This contributes to a better understanding of traffic accidents and helps

develop better prevention methods.

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Finally, technology for traffic accident reconstruction also offers the possibility of

improving road safety through accident prevention. This is achieved through the use of

sensors, driver assistance devices and warning systems. These devices can detect

warning signs and alert the driver before an accident occurs. This helps prevent accidents

by reducing vehicle speed, providing greater road user awareness, and ensuring greater

safety for all road users. Traffic accident reconstruction technology also helps improve

road safety by collecting data for informed decision making and improved traffic signaling.

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