Revista
de la
Universidad
del Zulia
Fundada en 1947
por el Dr. Jesús Enrique Lossada
DEPÓSITO LEGAL ZU2020000153
ISSN 0041-8811
E-ISSN 2665-0428
Ciencias del
Agro,
Ingeniería
y Tecnología
Año 13 N° 36
Enero - Abril 2022
Tercera Época
Maracaibo-Venezuela
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339
Legal analysis of implementation of the traffic accident monitoring
system
Yuliia Y. Atamanenko *
Olga M. Merdova **
Yurii I. Martsenyshyn ***
Oleksii P. Tsurkan ****
Stanislav O. Chebotar *****
ABSTRACT
Purpose. The study aims to establish positive changes after the introduction of traffic
accident monitoring systems implemented by government agencies in China, India,
Germany, the United States, the United Kingdom, Finland, Beijing and Sweden. Methods.
The research was carried out in stages, based on the logical presentation of the material. The
following methods were implemented in the study: direct observation, comparison and
analysis of the content and the form of advanced traffic accident monitoring systems. Results.
The study of international best practices and experiments about the implementation of
various options for traffic accident monitoring systems gave preference to an intelligent
system. A study conducted in the United States, India and Portugal shows the effectiveness
of different approaches to use mobile applications on smartphones to transmit reliable
information to the traffic accident registration system. Accident data collection should be
standardized and structured, and police officers should benefit from the statistical reports
they complete for each traffic accident.
KEYWORDS: Education; transport policy; justice; dignity; responsibility; schoolchildren.
Candidate of Technical Sciences, Senior Researcher of the Research Laboratory on Problematic Issues of Law
Enforcement Activities, Krivorizhskii scientific-research institute of Donetsk State University of Internal
Affairs, Mariupol, Ukraine. ORCID: https://orcid.org/0000-0001-7423-9880. E-mail: yuliiaatam@gmail.com
Candidate of Law Sciences, Head of the Department of Administrative and Legal Disciplines, Faculty №2,
Donetsk State University of Internal Affairs, Mariupol, Ukraine. ORCID: https://orcid.org/0000-0003-0769-
2364. E-mail: olhamerd@ukr.net
Candidate of Law Sciences, The superviser (chief) of Patrol Police Department in the Transcarpathian
Region, Uzhhorod, Ukraine. ORCID: https://orcid.org/0000-0002-4462-9885. E-mail:
Marc.police.new750@gmail.com
Candidate of Law Sciences, Head of Department of special disciplines and professional training, 1st
Faculty, Krivorizhskii scientific-research institute of Donetsk State University of Internal Affairs., Mariupol,
Ukraine. ORCID: https://orcid.org/0000-0002-0273-1902. E-mail: oleksiitsurkan34234@gmail.com
Graduate student, Donetsk State University of Internal Affairs, Mariupol, Ukraine. ORCID:
https://orcid.org/0000-0003-1983-3152.
Recibido: 11/12/2021 Aceptado: 08/12/2021
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Análisis legal de la implementación del sistema de monitoreo de
accidentes de tránsito
RESUMEN
Propósito. El estudio tiene como objetivo establecer cambios positivos después de la
introducción de sistemas de monitoreo de accidentes de tránsito implementados por agencias
gubernamentales en China, India, Alemania, Estados Unidos, Reino Unido, Finlandia y
Suecia. Métodos. La investigación se llevó a cabo por etapas, en base a la presentación lógica
del material. En el estudio se implementaron los siguientes métodos: observación directa,
comparación y análisis del contenido y la forma de los sistemas avanzados de seguimiento de
accidentes de tráfico. Resultados. El estudio de las mejores prácticas y experimentos
internacionales sobre la implementación de varias opciones para los sistemas de monitoreo
de accidentes de tránsito dio preferencia a un sistema inteligente. Un estudio realizado en
Estados Unidos, India y Portugal muestra la efectividad de diferentes enfoques para usar
aplicaciones móviles en teléfonos inteligentes para transmitir información confiable al
sistema de registro de accidentes de tránsito. La obtención de datos sobre accidentes debe
estar estandarizada y estructurada, y los agentes de policía deben beneficiarse de los informes
estadísticos que completan para cada accidente de tráfico.
PALABRAS CLAVE: educación; política de transporte; justicia; dignidad; responsabilidad;
escolares.
Introduction
Every year, almost 1.3 million people in the world die as a result of road accidents, and
another several million are injured or disabled. At the same time, most road accidents (90
percent) occur in low- and middle-income countries (Kitamura et al., 2018). The fact that the
death rate in high-income countries decreased between 2000 and 2015, but increased in low-
income countries, indicates the seriousness of transport problems in developing countries. If
government action is not taken, the number of people injured in road accidents in most parts
of the world will increase exponentially over the next two decades.
The fact that the death rate in high-income countries decreased between 2000 and 2015,
but increased in low-income countries, indicates the seriousness of transport problems in
developing countries (World Health Organization, 2009). If governments take no action, the
number of people injured in road accidents in most parts of the world will increase
exponentially over the next two decades (Government of Nepal, 2015).
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In 2004, the World Health Organization and the World Bank identified the importance
of collecting accurate and reliable data that determine the extent and problems of road
accidents. In particular, the need to create data systems to collect information on the state of
traffic on the roads and implement them primarily in countries with a large number of
accidents was emphasized. Based on the accumulated data on the monitoring of accidents, it
is proposed to implement appropriate road safety practices for.
An automated monitoring system is created to mitigate the consequences and reduce
the number of accidents. Such a system can be useful for the timely provision of emergency
care, which can increase the chances of immediate treatment to save the victims of a road
accident.
The introduction of the road accident monitoring system is urgent at the national level
as well, it corresponds to the 2024 State Strategy for Improving Road Safety (Cabinet of
Ministers of Ukraine, 2020). According to the statistics of the National Police for 2019 and
2020, there were approximately 450 accidents on the roads every day (Patrol police, 2021).
In this regard, by 2023 it is planned to introduce and improve the analytical system of
registration and analysis of accident data based on the European Common Accident Data
Sets (CADAs) (Ministry of Infrastructure of Ukraine, 2020).
The correct scientific approach to the registration of accidents and their analysis is
important for the implementation of effective countermeasures for road safety. Information
about the accident location is important for engineering improvements to road
infrastructure. Accident monitoring reports can provide the information not only about the
total number of accidents, but what accidents, where and when they occur, objective
circumstances about the condition and cause of people’s behaviour in a particular place and
on all roads, their injuries and deaths. Besides, road accident data can help develop
generalized road safety theories (Abdulhafedh, 2017).
Data collection at the accident scene is crucial (Wach, 2013), because the subsequent
stages of the accident rely on these data: investigation (reproduction of the circumstances of
the event), insurance, compensation for material damage and other legal aspects (Padua et
al., 2020). In the event of an accident, the driver is obliged to stop (Cabinet of Ministers of
Ukraine, 2001) and provide his/her data (or information identifying the vehicle) to another
driver who is involved in an accident to compensate for material damage (Legal Services
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Commission, 2021). However, irresponsible drivers do not always do as required by law and
leave the scene arbitrarily.
Therefore, further research on the implementation of road accident monitoring systems
is necessary and relevant to take into account and reduce the factors and consequences
arising from road accidents.
The aim of this study is to conduct a legal analysis of international experience and the
results of the introduction of road accident registration and monitoring systems in China,
India, Germany, USA, UK, Finland, Beijing, and Sweden.
The aim of the study involves a number of objectives that will help to understand the
features and difficulties that exist in the implementation of road accident registration
systems, in particular: study the international practice and best practices on technical and
legal significance of road accident monitoring system; identify problems that arise during the
interpretation and use of data accumulated in the database of the accident monitoring
system; try to develop a functional diagram of a modern accident monitoring system; outline
the advantages and disadvantages of different types of accident monitoring systems.
1. Literature review
At the national level, the Centre for Road Safety and Automated Systems at the
Ministry of Internal Affairs (2008) analyses the causes and state of road accidents in the
country based on statistics or accident databases, monitors and proposes measures to control
the road traffic situation, prevent accidents and mitigate the severity of their consequences.
The results of studying such statistics of Ukraine allow identifying the shortcomings that
exist in road traffic conditions. By studying the causes of road accidents, it is possible to
identify dangerous areas of their location and reasonably develop a strategy to eliminate such
shortcomings (Oznyuk, et al., 2019).
In 2018, India ranked 1st in the number of fatalities in road accidents among 199
countries, which is 11 deaths per million people, that is less than in Iran (20), the Russian
Federation (14) and the United States (12) (Ministry of Road Transport and Highways of
India, 2018). A study conducted in India showed that the country’s rating is the worst in the
world, each year about 150 thousand people die as a result of road accidents, and 80% of
victims of accidents in India do not receive timely emergency care. In this regard, it is
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proposed to introduce a smart accident registration system. However, the peculiarity of this
system is that it consists of a database and a module that is installed on the car. Such a module
includes GPS, GSM transmitters and an impact sensor that can be activated during an
impact, vibration or the airbag deployment. Bluetooth technology is used to activate the
module. In the event of an accident, the information contained in this module (full name of
the driver, blood type, telephone number, e-mail, medical history, date of birth) is
automatically sent to the appropriate telephone number and downloaded to the database of
the main monitoring system (Sharma et al., 2020). In this case, the experimental work and
suggestions of experts were taken into account in this system in terms of troubleshooting. It
has been found that the proposed system will work well in a variety of situations. The
detection hardware can detect an accident and a collision and accurately send a message to
the rescue service with the help of three sensors and a software application (Parmar et al.,
2019). With the development of wireless technologies in their mobile applications, motor
transport is being transformed into smart vehicles that can be accessed through intelligent
traffic applications (Rath, 2018). Another group of Indian researchers proposed an algorithm
for registering accidents only for cases in which there are any victims (Sharma & Shoney,
2019).
Research conducted in Beijing is worth mentioning. The spatial analysis of road
accident data based on the WaveCluster system showed that the entire road accident area in
Beijing is divided into 5 categories: hotspot space (high traffic area), space with different
quality of drivers or intersection of urban and rural roads, and information system about
vehicles. It has been found that accidents usually change in stages as they are dealt with.
However, the adoption of laws and establishment of mechanisms for accidents can improve
the ability to anticipate new cases (Zhang & Shi, 2019).
Modelling the number of road accident data is of particular importance for road safety
analysis, and over the past few decades a significant number of tools have been proposed for
the analysis of road accident data (Abdulhafedh, 2016), but the choice of the necessary
monitoring system depends on the specifics and financial capabilities of the country.
The CADaS system is considered as a recommendation for the collection of road
accident data for the police of the EU countries in a common database. The list of variables
for CADaS should be comprehensive and concise, and the level of their detail is chosen by
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each EU country. The list of CADaS variables is divided into four main categories: A — for
accident-related variables, R — for the road-related variables, U — for variables related to
the traffic unit, P — for variables related to a person (for example, A-2 Date of the accident)
(Petros Evgenikos National Technical University of Athens, 2009).
2. Methods
The research involved the following methods: direct observation helped established the
opinion of modern scientists and researchers on the implementation of accident monitoring
systems; the method of comparison was used to identify the difficulties faced by public
authorities of different countries during the implementation of the accident monitoring
system; the main international trends and advanced technical experience on this issue were
identified using the content analysis.
So, the main sources of input data generation are established, which are transmitted to
the accident monitoring system, and the main parameters of accident data in all types of road
accidents are outlined through the direct observation.
The method of comparison helped reveal common trends among developing countries
(Ukraine, India, China) and developed countries (USA, Germany, UK) in the use of devices
and software to transmit statistics and receive them from the accident monitoring system.
The experience of the implementation of the accident monitoring systems in Europe
and the world was studied: RADMS (in India), WaveCluster (in Beijing), CADaS (for
European countries), TARS (in the UK), NASS (in the US), STRADA in Finland and
Sweden), CrashMape (in Germany), CVIS (in China).
A total of 50 sources and references were used: statistical reports on the state of road
accidents.
3. Results
Since 1979, the United States has implemented a National Automotive Sampling System
(NASS) for collecting data about road accidents which occurred during the year. NASS
provides an effective and useful resource to collect data necessary for society. Over the past
10 years, the basic set of NASS components on road accidents has created a reliable resource
for a number of departments and agencies. Personal information about individuals, names,
addresses, driver’s licenses, vehicle registration certificate and even specific places of the
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accident are not contained in publicly available NASS files. The NASS consists of two parts:
the Crashworthiness Data System (CDS) and the General Estimates System (GES). Both
systems collect information from police accident reports in randomly selected regions of the
country (National Highway Traffic Safety Administration, 2020). One of the disadvantages
of NASS-GES data is that they use an aggregate data element that provides overall national
estimates that may differ from true values at the state level because they are based on the
probable choice of accident in the country and cannot provide accurate estimates at the state
level, which reduces the reliability of the data. Another disadvantage is that NASS-GES data
is obtained either directly from the police accident report (PAR), or by interpreting the
information presented in the PAR, by viewing the accident diagram or a combination of data
elements in the PAR (National Highway Traffic Safety Administration, 2021).
An empirical study conducted in the United States shows the effectiveness of different
approaches to the use of mobile applications on smartphones to transmit reliable information
to the accident registration system. So, built-in accident reporting systems are not available
in all vehicles, and they are expensive to upgrade for older vehicles. Alternatively,
smartphones can automatically detect accidents using accelerometers and acoustic data,
immediately notify the central emergency server after an accident, and provide situational
awareness through photos, GPS coordinates, VOIP communication channels, etc. (White et
al., 2011). The results of the experiments show that the microphones in smartphones are not
able to distinguish sounds such as screaming from the airbag deployment (White et al., 2011).
Therefore, the use of various sensors can help in more accurate detection of accidents (Bhatti
et al., 2019).
In the UK, the TARS system is used to assist in the management, review, analysis and
display of accident information. Anyone can request TARS for information about the
accident and, using the TARS2 software, see the accident sites on the map, as well as a
detailed report on accidents. The information obtained from TARS is useful for policy
development, monitoring and evaluation of road safety efforts in the country (CDR Group,
2020).
The Indian state of Himachal Pradesh has launched its first Road Accident Data
Management System (RADMS) for data management, analysis and evaluation. This system
was developed by a research laboratory in the UK. RADMS optimizes and centralizes
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accident data management, making it easier to detect and take action to reduce the number
and severity of accidents (ITS International, 2021). In Greece, a web geographic information
system (webGIS) has been introduced since 2004 to register, store, visualize and analyse
road accidents (Vaitis et al., 2019).
The German Statistics Office has also solved the problem of accident registration using
a web application, which is public and shows only accidents in which people were injured
and the police arrived on call. Assessment of the condition of the motor road for the absence
of accidents is calculated by the number of accidents on one section of the road. It is planned
that the map will have information on accident statistics from all 16 federal states of
Germany, not from 9 as it is currently the case, as not all states register geographical data on
accidents (European Transport Safety Council, 2018). In the Czech Republic, there is a
website created in collaboration with the Transport Research Centre and the police. The
CrashMape map shows accidents from 2007 to date and is updated monthly. Compared to
England and Germany, it has the widest filtering of accidents by identification number or
criteria. Criteria that have not been indicated in previous versions are: blood alcohol content,
substance use, visibility during the accident, the cause of the accident, information about the
road (highway) and many others (Kmet & Kvet, 2021).
A group of German researchers also proposed a different and inexpensive accident
monitoring system. This system uses a multi-level IoT-based automotive environment
through V2X and Edge/Cloud Computing. A video camera is built into the vehicle for reliable
detection of accidents together with the GPS module. As soon as an accident occurs, the
vehicle sends a notification to the receiving device. The receiving device, in turn, finds the
nearest hospital and immediately makes a request to send an ambulance to the scene of the
accident. A dynamic interface visualization, which is hosted on the server, is also proposed
in order to assist the relevant authorities in conducting a full analysis of the road accident.
The generated charts help the police officers to make the corresponding legal decisions on
their basis. Besides, when an accident occurs and the accident monitoring system registers
it, it can ensure that relevant data is passed to rescuers and doctors, which can improve the
likelihood of survivors. Accumulated accident data is sent to a central database for long-term
storage. These data can later be obtained for analysis. Data stored in the cloud can allow
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relevant authorities to develop policies and take effective measures to reduce the number of
injuries and deaths caused by road accidents (Abdul Khali et al., 2019).
A smartphone that contains inertial sensors can be used as an additional data source to
better understand the events of the accident. These are the results of a study using sensors in
smartphones to detect the acceleration of the torso associated with the risk of falling in the
elderly who have suffered a stroke (Isho et al., 2015).
The comparative analysis of accident statistics in the system of Finland and Sweden
(STRADA, Swedish Traffic Accident Data Acquisition) for 2009-2013 is also noteworthy. A
study of the causes of fatal accidents has shown that the use of detailed data provides more
opportunities for analysis than computer programmes on accidents across Europe (Peltola
& Luoma, 2017).
That is, the main parameters of all types of accidents can be reduced to the following
categories (Table 1).
Table 1. The main parameters of all types of accidents (author’s development).
General information
Date, week, hour, working day or day off, etc.
Accident location
Street number, intersection number, geographical (GPS)
coordinate, number of kilometres from the settlement, name of
the district, etc.
Participants in the
accident
Age, sex, type of road user, signs of alcohol consumption, use of
seat belts, placement of passengers inside the car, category of
driver’s license, date of issue, driver’s medical data, etc.
Details of injuries
Volume, number of injured, data on injured, ambulances and
evacuations, etc.
Traffic conditions at
the time of the accident
Road type, road category, weather conditions, lighting
conditions, type and condition of the road surface, availability
of means of control and video recording of traffic, etc.
Vehicle
Vehicle type, age of the vehicle, etc.
Information about the
mechanism of the
accident
Accident type, type of manoeuvre, causes, etc.
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Video surveillance systems that receive data through video mining can provide
additional information about the causes of accidents. In this way, it is possible to better
understand which sections and infrastructure of the road are dangerous or those that cause
accidents (Battiato et al., 2018). At the same time, it is proved that the use of unmanned aerial
vehicles (hereinafter — UAVs) as a video surveillance camera for traffic condition provides
accuracy of 80%, and the use of stationary video cameras for traffic control has 50-75%
accuracy. Besides, UAVs combine the capabilities of both stationary and mobile traffic
detectors (Shan et al., 2021). With good visibility from above (without clouds, high-voltage
cables and good lighting), UAVs provide the ability to collect more data, with greater
accuracy and speed in relation to traditional approaches to recording/registering accidents.
Therefore, in real conditions, a group of Portuguese researchers proposed to use a full set of
tools to obtain data on the accident. In particular, they include: UAVs, terrestrial video
cameras, tacheometers, artificial lighting units and photogrammetry, measuring tape,
receivers of the Global Navigation Satellite System (GNSS).
However, CVIS methods were the most effective in collecting data on road accidents.
The CVIS system is not cheap, it consists of a set of intelligent devices of road infrastructure,
which showed the shortest time of detection of a car accident, namely, 0.0461 seconds with
a probability of 90.02%. The accident detection model is based on the use of a deep neural
network (YOLO-CA) based on a set of auto image data (CAD-CVIS) and self-learning
algorithms (Tian et al., 2021). Given the high cost of intelligent road devices, it is proposed
to use them on the most dangerous intersections of smart streets of the city (Iqbal and Khan,
2018). Taking into account the above, the author proposes to use the following functional
diagram of a smart accident monitoring system for analysis (Figure 1).
At the same time, the collection of data on road accidents should be standardized and
structured in practice. For completeness and objectivity, the procedure for obtaining data on
an accident should be synchronized with the process of its investigation, reconstruction and
simulation of the circumstances of the events. It is advisable to fully computerize and
automate the data accumulation procedure in the monitoring system. It is also proposed to
conduct a survey of victims about their health in 1 month. In turn, police officers who receive
primary accident data should benefit from reporting work (European Commission, 2019).
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Figure 1. Functional diagram of a smart accident monitoring system (author’s
development).
Road safety analysis, based only on registered accidents, often suffers from
underestimation of data, which can lead to biased conclusions and an ineffective accident
prevention strategy. An additional method of obtaining information about the accident is to
send accident reports yourself. The combination of the two methods can provide a more
accurate idea of how safe a driving should be (Kamaluddin et al., 2018). Common problems
in the use of consolidated statistics obtained from the database of accident monitoring
systems are given in Table 2.
4. Discussion
An overview of the current situation and practice in Abu Dhabi, as well as in the
Kingdom of Bahrain, UAE, UK, Sweden, Australia, New Zealand, USA contains other
information that is worth noting. With the exception of the Persian Gulf, most countries
require only the presence of the police when injuries or serious material damage are caused
Video recording
system of road
accidents and
their
consequences
(cameras,
system (compliance
with traffic rules),
police patrol
Peripheral road
devices of
"smart" roads for
recording/egisteri
ng road accidents
GPS and GSM
modules, sensors
on the vehicle,
subscriber mobile
applications on
smartphones
Primary data sources
SMART ACCIDENT MONITORING SYSTEM
Adjustment of
traffic and
movement of
ambulances,
rescue service
evidence of an
accident for the
administration,
courts, insurance
Application
Analysis and
forecast of the
traffic condition
in the region over
time
Adoption of legal
mechanisms
aimed at reducing
the number of
accidents
Operational data
Long-term storage database
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at the scene of an accident, whereas all accidents in the Persian Gulf must be reported to the
police.
Table 2. The main problems in the use of consolidated statistics obtained from the
accident monitoring system (author’s development).
Excessive or
insufficient
variance
When the data is excessively scattered (excessive variance), the estimation
of the accident model may lead to a bias in the estimation of the
parameters. As a result, there will be incorrect conclusions about the
factors that determine the frequency of accidents. When there is a lack of
data (insufficient variance), the accident forecast will be incorrect.
Small
sample size
Given the fact that the process of collecting data and collecting a sample of
accidents can be financially costly, the calculation and forecast of accidents
is often not comprehensive and incomplete.
Changing
the time
interval
The period for collecting data on accidents is usually one, three and five
years. Instability of the time interval can lead to incorrect estimation of
parameters and forecast of road accidents. The accuracy of the forecast
directly depends on the duration of the time interval: the longer the time
interval of the obtained sample, the more accurate the forecast.
Temporal
and spatial
dependences
Roadway objects may be mistakenly taken into account several times in a
few years or not taken into account at all because they were near the scene
of the accident.
Skipping
variables in
the forecast
Modelling of accident forecasts according to the methodology with
insufficient number of variables can lead to simplification of models and
incorrect conclusions.
Not
complete
reporting
Because of minor accidents, police reporting is incomplete.
One of the priority areas for reducing the number and severity of accidents is to improve
road infrastructure. To this end, it is necessary to improve the organization of road traffic and
develop measures to improve road safety. Statistics on accidents should be used to eliminate
the shortcomings of traffic condition. Therefore, the introduction of a modern and intelligent
system of accounting and monitoring of accidents remains more relevant than ever.
The smart monitoring technology includes the processing of streaming data (photos,
videos, telemetry data, user information), data mining, machine learning, processing and
forecasting, and the implementation of existing traffic models in practice. At the same time,
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a comparison of time characteristics showed that changes in traffic conditions and the
concentration of accidents in controlled areas are highly dependent on weather conditions
(Finogeev et al., 2018).
Given the constant growth of the number of road vehicles owned by citizens, the
existing system is difficult to ensure road safety for all its participants. Therefore, a long-term
strategy to improve road safety must be implemented (Gurzhiy, 2012). One of the directions
of such a strategy should be traffic optimization. The proposition of alternative routes to
avoid accidents significantly increases the overall efficiency of traffic. However, the main
problem is how to do it in the shortest time and with the least financial cost (Souza et al.,
2017).
Monitoring of traffic violations significantly affects the drivers’ behaviour in the control
area. Monitoring traffic violations can effectively reduce the likelihood of accidents.
Therefore, monitoring of traffic violations has a positive effect on road safety (Zhu et al.,
2012). In order to maintain order on the roads and reduce the number of accidents on high-
risk roads (for example, on school and main road sections), it is advisable to install traffic
violation monitoring systems (Pan et al., 2020).
Besides, the ability to use artificial intelligence to analyse and provide information
about the situation in the event of a road accident significantly increases the efficiency of
road accident response operations. The analysis and reporting module should be further
improved to adjust the information and images obtained from other possible sources about
the accident site and to create one final agreed report (El Barachia et al., 2020). When
analysing statistical data from the database of accident monitoring systems, it is necessary to
take into account the problems in their use.
Conclusion
The introduction of accident monitoring systems is an urgent need for middle- and
low-income countries. The best option is a smart monitoring system with a focus on smart
city, smart street and so on. Such a system can increase the chances of the necessary
treatment of persons injured in an accident, to adjust traffic. Besides, data from the long-term
storage database can be used to generate video evidence of an accident for the administration,
courts, insurance companies, analysis and forecast of accidents on a particular section of road
and the adoption of legal mechanisms to reduce the number of accidents.
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There is no doubt that a promising area for the development of monitoring systems
are systems based on artificial intelligence with the possibility of machine learning.
Experiments conducted in India, Germany, USA, Sweden, Finland, Portugal and
China have shown high efficiency from the use of databases of long-term and operational
storage of accident data based on data obtained from various sources: GPS and GSM
modules, sensors on the vehicle, mobile subscriber applications on smartphones, UAVs,
radars, photo and video recording systems. The most effective accident data collection
system was CVIS (proposed in China), which consists of a set of smart road infrastructure
devices.
Based on the results of evaluation and analysis of statistical data, it is logically correct
to implement an adequate policy and strategy to reduce the number of accidents and mitigate
their consequences.
Although the CADaS system is part of the 2024 State Strategy for Improving Road
Safety, CADaS is seen only as a recommendation to collect accident data for the police of the
European Union into a common database. Therefore, taking into account international best
practices on this issue will not be superfluous. However, the question of time and financial
costs for the implementation of a smart accident monitoring system arises in such a case.
It will be useful to further study the features of the introduction of a smart monitoring
system for road accidents into the legislation of Ukraine.
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