=Paper=
{{Paper
|id=Vol-2565/paper24
|storemode=property
|title=Traffic Flows System Development for Smart City
|pdfUrl=https://ceur-ws.org/Vol-2565/paper24.pdf
|volume=Vol-2565
|authors=Iryna Krislata,Anatoliy Katrenko,Vasyl Lytvyn,Victoria Vysotska,Yevhen Burov
|dblpUrl=https://dblp.org/rec/conf/itpm/KrislataKLVB20
}}
==Traffic Flows System Development for Smart City==
https://ceur-ws.org/Vol-2565/paper24.pdf
Traffic Flows System Development for Smart City
Iryna Krislata[0000-0002-5139-2142]1, Anatoliy Katrenko[0000-0001-7142-6576]2,
Vasyl Lytvyn[0000-0002-9676-0180]3, Victoria Vysotska[0000-0001-6417-3689]4,
Yevhen Burov[0000-0001-6124-3995]5
Lviv Polytechnic National University, Lviv, Ukraine
irynakrislata@gmail.com1, Anatolii.V.Katrenko@lpnu.ua2,
Vasyl.V.Lytvyn@lpnu.ua3, Victoria.A.Vysotska@lpnu.ua4,
Yevhen.V.Burov@lpnu.ua5
Abstract. The work is devoted to the development of an information system,
where the movement of vehicles is a central element. Another key element is
research and development of theoretical and methodological foundations and
mathematical tools for performing all kinds of tasks for managing these flows,
improving the transport network and maintaining good quality of the roads. To
achieve this, the following questions were raised in this document: analysis of
existing methods of solving various problems related to the traffic of a large
city; development of a formalized approach to solving this class of problems;
development of algorithm for optimization of these tasks; implementation of
developed algorithms in the complex traffic management program. As a result,
specific practical problems regarding managing the traffic flow of a large city
were solved, the adequacy of developed models and algorithms was proved, and
the usefulness of their use was shown.
Keywords. Traffic flow management, information system, information tech-
nologies, management system, transport network, vehicles, road quality, traffic
congestion.
1 Introduction
Transport infrastructure is one of the most important infrastructures that provide the
life of cities, villages, regions, regions, and even countries [1-7]. According to the
definition, it is a collection of certain objects (enterprises) involved in the construc-
tion, repairing, as well as the maintenance of the roads, bridges etc. The transport
infrastructure ensures the availability and preservation of transport routes in proper
condition. It includes railways, railway stations and stations, highways, public
transport, streets, airlines and airports, river routes and ports, seaports, bus stations,
tram lines, etc. In recent years, many major cities have completely exhausted the po-
tential of transport networks development. That is why optimal planning of transport
Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License
Attribution 4.0 International (CC BY 4.0)
2020 ITPM Workshop.
networks, improvement of traffic organization, optimization of the public, industrial
and other route types of transport have become of particular importance [8-15].
Due to the intensive use of infrastructure, the transport sector is an important com-
ponent of the economy and a common tool used for development [16-20]. A stable,
efficient and well-supported transport infrastructure gives urban and rural residents
the opportunity to participate in economic opportunities and access to basic services.
2 System Analysis of the Research Object
A goal tree is a structured, hierarchical principle (distributed in levels) of a set of
goals of a system, program, plan, in which the general purpose ("the top of a tree") is
allocated; subordinate to her subculture of the first, second and subsequent levels
("branches of the tree") [8]. The name of the "goal tree" is due to the fact that the
schematically presented this set of goals resembles the inverted tree.
The term "tree" involves the use of a hierarchical structure (from senior to young-
er), obtained by dividing the general purpose into its subculture. The goal tree method
is oriented towards obtaining a relatively stable structure of goals, problems, and di-
rections. To achieve this, when constructing the initial version of the structure, one
should take into account the patterns of the formation of the goal and use the princi-
ples of the formation of hierarchical structures.
This method is widely used to predict possible trends in the development of sci-
ence, technology, technology, as well as for the compilation of personal, professional
or the goals of any company. A goal tree closely links prospective goals and specific
tasks at each level of the hierarchy. At the same time, the purpose of the higher order
corresponds to the top of the tree, and below several tiers are located local goals
(tasks), through which provides the achievement of the goals of the upper level.
When constructing a "goal tree" its design is based on the method "from general to
specific". The termination of the decomposition of the purpose occurs at a time when
the subsequent process is inappropriate in relation to the main goal. In general, the
structure of the objectives tree is as follows: the root of a tree is a general purpose,
formulated in the form of one or two sentences in a natural language. The following
levels are aspects of the general purpose, if need be - later examples that can be repre-
sented as a hierarchy of sub-targets, and eventually the level of "leaves" of the tree -
criteria. The criteria can be either quantitative - that is, measured directly and repre-
sented by numerical values with a certain dimension, and qualitative ones - the values
of which are obtained from experts and processed by systematic methods.
Accordingly, at the first stage we will form the main, global objective of the sys-
tem, which has a long-term, strategic nature and is aimed at the introduction and op-
eration of the system. Since the system can have only one main (general) purpose, for
this information system it has - management of traffic flows (cities) (Fig.1).
1.1. Quantitative and qualitative transport composition Data collection and monitoring
1.1.1. Number of a camera that meets the set requirements
1.2. Data collection and public transport organization
1.2.1. Optimization of public transport traffic interval
1.2.2. Prompt information on arrival of transport
2.1. Analysis and optimization of traffic lights
2.1.1. Effective functioning of traffic lights
2.2. Collection of road conditions in different weather conditions
2.2.1. The promptness of the call for equipment for clearing roads
City traffic
management
Analysis of primary Analysis and Analysis of the
information and effective constraints and
management of management of the problems
traffic flows transport network encountered
1.1 1.2 2.1 2.2 2.3 3.1 3.2 3.3
1.1.1 1.2.1 1.2.2 2.1.1 2.2.1 2.3.1 3.1.1 3.2.1 3.2.2 3.3.1 3.3.2
Fig. 1. Goal tree of the information system of traffic flows of a large city
2.3. Roads monitoring
2.3.1. Effective schedules of repair work
3.1. Data collection and raising financial capital
3.1.1. Optimization of tariffs for transport services
3.2. Reporting overview and troubleshooting
3.2.1. The promptness of informing drivers about traffic jams
3.2.2. Optimal congestion routes
3.3. Obtaining and minimizing information from police about violations
3.3.1. The optimal number of police
3.3.2. Maximizing sentencing
The main goal of the development of the main goal is the analysis of the external
and internal environment of the system, assessment of its resources and capabilities.
At the second stage we will make a decomposition of the main goal of the system for
the purpose of the second level (aspects of the general purpose). Formation of the
objectives of the second level (aspects) in the directions is in line with the main stra-
tegic goal, which should guarantee its implementation. Such aspects in this case are:
analysis of primary information and vehicle management, analysis and efficient man-
agement of the transport network, analysis of constraints and solving problems. As-
pects of general purpose characterize the specialized directions of activity and func-
tioning of the system. Each direction represents a clearly defined sphere of specialized
activity of the system. In the third stage, we decompose the objectives of the second
level (aspects of the general purpose) in accordance with the specific tasks (sub-
aspects of the general purpose). For the first aspect, when decomposing, there are new
exits: data collection and monitoring of quantitative and qualitative transport compo-
sition, data collection and optimization of public transport; for the second - analysis
and optimization of traffic lights, data collection on the condition of highway in dif-
ferent weather conditions, monitoring of the state of roads; and accordingly, for the
third, data collection and raising financial capital, an overview of reporting and solv-
ing the problem of corruption, receiving information from the police about the viola-
tion and minimizing it. At the next stage, the decompositions describe the "leaves" of
the tree, which are the criteria for achieving the goal. As shown in Fig. 1 the follow-
ing criteria for achieving the main goal of the information system of traffic flows of a
large city in accordance with the sub-aspects of the general goal are: the number of
cameras that meet the requirements, optimization of the interval of public transport,
efficiency of informing about the arrival of transport, the effective operation of traffic
lights, the speed of calling vehicles for cleaning roads , effective schedules of carrying
out of repair works, optimization of tariffs for transport services, efficiency of inform-
ing drivers about traffic jams, optimal routes of traffic collapse, optimal number of
police, maximization of penalties. The interaction of the system with elements of the
environment with sufficient completeness will be reflected within the notation of the
DFD (flowcharts) using the context diagram, and the detailing - by constructing the
DFD hierarchy of the following levels. Data Flow Diagrams (DFDs) depict the flow
of information for any process or system. They use symbols such as rectangles, circles
and arrows, as well as short text labels to show incoming and outgoing data, storage
points and routes (information transfer) between each destination [9]. These charts
can be used to analyze an existing system or create a new one.
The data flowchart may become more detailed by levels. Levels DFD are numbered
0, 1 or 2, and sometimes you can go to level 3 or go beyond its limits. The required
level of detail depends on the amount of what they are trying to achieve. The level of
DFD 0, also called the context diagram, is depicted in Fig. 2.
Elements of the Management Traffic
Department of Traffic congestion
transport information Management
fixing violations
network Department
Information about transport Management
network elements Management
Information about
traffic flows Public
Transport Ensure
Personnel
management of Public transport Transport
flows Funds information Management
Management city traffic flows
Management Department
Cars
Information about
Road status information traffic lights
Road Control Traffic lights
Department
Address and
Address and management
management
management department
Fig. 2. Context diagram of the information system of traffic flows of a large city
This is a basic overview of the entire traffic information system of a large city to be
analyzed and modeled. It is designed for clarity and in order to display the system as a
single high-level system, with its interconnections and external objects. The context
diagram is easily understood by a wide audience, including stakeholders, business
analysts and developers. This context diagram depicts only one main process "to en-
sure the management of traffic flows (cities)" and the following external entities:
"traffic flows", "elements of the transport network", "the department of fixing viola-
tions", "the department of control of traffic jams," the department of public manage-
ment transport "," traffic lights management department "and" road control depart-
ment ", which will provide stream management. Level DFD 1, shown in Fig. 3, pro-
vides a more detailed breakdown of parts of the context chart. Here are the main func-
tions performed by the system, by separating the system of high level on its subpro-
cesses.
Information about transport Results Results Traffic
6 congestion
network elements Address
Vehicle information information
Information
about traffic 1 Results 1.7
flows Cars
4 Management
1.1 Vehicle 1.8 Routes 1.3
Funds
information
Management Funds Road status Personnel
Information
information Message about traffic
1.2 lights
5 1.6
Personnel 1.4 3
Results
Results
Інформація Accident
про особу informationTraffic violation 1.5 Address
information
2 Results Management
Results
7 Management Public transport
Scoreboard information
information
Fig. 3. Flowchart of the data of the first level
Databases:
1 – Vehicle information;
2 – Reporting of violations;
3 – Traffic light information;
4 – Report on repair work;
5 – Cards;
6 – Transport service information;
7 – Information about the characteristics of the scoreboard.
Processes:
1.1 – Collect vehicle information from surveillance cameras;
1.2 – Fix violations;
1.3 – Solve congestion issues;
1.4 – Ensure proper use of traffic lights;
1.5 – Optimize public transport;
1.6 – Check the condition of the roads;
1.7 – Check the weather on the roads;
1.8 – Provide payment for transport services.
From this diagram it is clear that at this stage, according to the standard, there are
no new entities, but only duplicates those that were on the context. In addition, there
are new processes (subprocesses) and data warehouses.
The sub-processes in this chart are "collect information about vehicles", "fix viola-
tions", "solve problems with congestion", "optimize the traffic of public transport",
"ensure the proper use of traffic lights", "monitor the state of roads", "conduct road
traffic control "and" provide payment for transport services ". In addition, there are 7
data warehouses on the chart: "vehicle information", "transport service information",
"violation reporting", "traffic lights information", "table information and characteris-
tics", "maps" and "reporting on conducting repair works". At this stage, the diagram
describes in more detail the essence of the system. However, in my opinion, it can be
decomposed more in order to describe in detail some of the subprocesses. As a result
we get DFD 2 level. DFD level 2 are divides into more parts the 1st level graph. In
order to achieve the required level of detail about the functioning of the system, a
more detailed description of the system will be required. To begin with, consider the
process of "collecting information about vehicles" (Fig. 4).
Vehicle 2.1.3 2.1.2 2.1.1 Information
Recognize Video Identify locations about traffic
information Install surveillance Address
machine numbers with no surveillance flows
cameras
and other features cameras
Photo
Fig. 4. Detailing the process of collecting information on vehicles
As you can see, the diagram shows new processes: "to determine places with no ob-
servation cameras", "to install surveillance cameras", "to recognize machine numbers
and other characteristics". The results of these processes will be recorded in the data
store "vehicle information", which will be used in the future by the system in the exe-
cution of other processes.
Next we decompose the process of "fixing violations" (Fig. 5). We see that in this
second level diagram there are new processes: "fixing traffic accidents", "fixing traf-
fic offenses", "delaying the offender", "imposing a punishment", "calling police offic-
ers", "calling for ambulance if necessary". The external essence of the "Department
for fixing violations" will send information and collect all the results.
Traffic violation 2.2.1 2.2.2
information Report traffic Results Accident
Fix an accident
violations information
Person
Management information
Challenge
Results 2.2.5 Challenge
Detain the 2.2.4
Person offender Call an ambulance
Results information
if necessary
2.2.6
To impose a
Person 2.2.3 Personnel
measure of Data on the
information
punishment nature of the Call the police
Results violation Personnel
Fig. 5. Detailing the process of fixing violations
And all recorded violations and road accidents with information about place, time,
date, person and the actual violation and punishment for it will be stored in the data
warehouse "reporting of violations", which the police will also use to review the fre-
quency of relevant events committed by that or another person to determine the penal-
ties for this person. This data storage is depicted on a higher level chart. The process
of solving the problem with congestion is extremely relevant and at the same time
quite complicated. It includes several subprocesses with much entities and data stor-
age. How this issue will be solved by the information system is shown below (Fig.6).
2.3.2 2.3.1 Traffic
Personnel Results Analyze the
Send police congestion
density of
GPS officers information
congestion
information Results
2.3.5 2.3.4
Routes Send directions to Routes Consider possible Data
5 Cards
GPS detours
Results Routes
Results
2.3.7 2.3.6 Message
Management Solve congestion Send a message to
issues the radio station
2.3.3
Information
Adjust the speed about traffic
Results of the traffic light lights
Fig. 6. Detailing the process of solving problem with congestion
When the cameras observe an excessive accumulation of vehicles on one or another
section of the transport network, a signal with this information is sent to the traffic
control unit. Accordingly, the unit assigns the task of solving this problem to the fol-
lowing processes: "to send police officers", "analyze the density of the trick," "to
consider possible options for a detour", which are taken from the data warehouse
"maps", "send directions to GPS", "send message on the radio station", "adjust the
pace of work of the traffic light "and, of course, "solve the problems with traffic jams"
When fixing the camera of the observation of excessive replenishment of vehicles
in one or another department of the transport network, signal with the information is
sent to the department of traffic jam management. As a result, he refuses to solve the
problem of the following processes: "breaking the bottlenecks", "analyze the integri-
ty", "expand the possible options for exchange", which are displayed with the data
warehouses "maps", "dispatch sending to GPS", "sending messages". message on the
radio station "," prepare the pace of work of the traffic lights ", usually" solve prob-
lems with the traffic jam". If we describe in detail the process of optimizing public
transport, then several new processes will appear in the diagram (Fig. 7). Among
them: "analyze the population at stops," "determine the required amount of each
transport," "determine the required frequency of vehicles," set the scoreboard, "send
data with the arrival time on the scoreboard" and "calculate the failure." In my opin-
ion, with the help of these data, the traffic of taxis, trams, trolleybuses and other vehi-
cles people will be much more satisfied, since all possible factors for comfortable
movement of people and informed expectations will be taken into account.
2.4.2 Number of 2.4.1
Determine the
machines Analyze weather Public transport
required amount of
Results conditions information
each transport
Results
2.4.3 2.4.4
Determine the
Install the Scoreboard
desired machine
scoreboard information
speed
Arrival time Data
2.4.5 Crash 2.4.6
Results Send data with
information Calculate the Scoreboard
time of arrival on
Management the scoreboard failure information
Edited data
Fig. 7. Detailing the process of optimization of public transport
Next we consider the process of "ensuring the proper use of traffic lights", or rather its
decomposition (Fig.8).
Results Results
Information about
Management 3 Management
traffic lights
Disconnect
information New traffic light Results
2.5.2 2.5.3 2.5.4
Turn off the traffic Put in an extra Adjust the rate of
light traffic light change of light
Absence
Low density High density
2.5.1
Analyze the density
Address of the road at a Information
certain hour of the about traffic
day lights
Fig. 8. Decomposition of the process of using traffic lights
Here the managing link is the external essence of the "traffic lights management de-
partment". The diagram also shows the processes "analyze the density of the road at a
certain hour of the day", as a result of which the following processes will be per-
formed depending on the results: "turn off the traffic light", "put an additional traffic
light" or "adjust the light speed". All results of the above actions are stored in the data
store "information about traffic lights", which is also used to read current data of a
given traffic light and further work with it. Fig. 9 depicts the process of "monitoring
the state of roads". This chart is managed by the "road control department", as it pro-
vides information about a specific address and requests the processes of "constructing
a new road" and "checking the state of the roads." The funds for such actions are part-
ly received as a result of the process of "ensuring payment for transport services". The
results of the construction are recorded in the already mentioned card data repository.
After checking, if necessary, there is a process of "drawing up a schedule of repairs"
and "carrying out repairs", the results of which are reduced to "reporting on the repair
work." This data warehouse is also analyzed in the process of checking the state of
roads for a decision on the need for the start of repair. The next process, which we
will decompose, is "to provide payment for transport services" (Fig.10).
2.6.3
Results
2.6.4 Carry out repairs
Funds
Build a new road
Schedule
Results 2.6.2
Address Schedule repair
Road status work
information 2.6.1 Time
Check the Address
condition of the
Results roads
Fig. 9. Detailing the process of monitoring the state of roads
Collect 2.8.1 2.8.2
Information information about Data
Set optimal tariffs
about transport transportation
services services
Results
2.8.3
Results Funds
To raise funds
Funds
Fig. 10. Detailing the process of ensuring payment for transport services
The processes that perform the function of ensuring payment for transport services:
"to gather information about transport services", "to establish optimal tariffs", "to
raise funds". Funds are collected from drivers of vehicles, some of which are trans-
ported for the construction and reconstruction of roads. All information on tariffs and
collected funds is stored in the "transport service information" repository. The final
process that we will decompose is to "control the weather on the highways" (Fig.11).
2.7.2 2.7.1
Cars Send road cleaning Challenge Analyze weather Address
machines conditions
Fig. 11. Detailing the process of monitoring the weather on the highways
The external essence of this process is the "Department of Road Weather Monitor-
ing". The processes in this chart are "to analyze weather conditions" and "send cars to
clear roads". In general, the system can be further elaborated to 3.4 and further levels,
but going beyond Level 3 can lead to significant complexities as the model may be-
come less comparable and effective. Therefore, at this stage, we will stop.
According to the definition, description and rules, the DFD diagram of the infor-
mation system of traffic flows of a large city was built, which is a generalized intel-
lectual transport system. Let's take a closer look at what it is.
Intelligent Transport Systems (ITS) are advanced applications that, without the in-
telligence as such, are aimed at providing innovative services related to different
modes of transport and traffic management and allow different users to be more in-
formed and make transport networks safer, coordinated and "smarter" [10]. Intelligent
transport systems differ in applied technology, from basic control systems such as
automotive navigation; traffic light control systems; container management systems;
automatic speed detection for monitoring applications such as video surveillance sys-
tems; and more advanced applications that integrate real-time data and feedback sys-
tems from a number of other sources such as parking systems and other information
systems; weather information, etc. In addition, prognostic methods are developed to
make modern simulations progress in comparison with historical data.
3 Building a Hierarchy of Tasks
This information system consists of many tasks that can be represented hierarchically
(Fig.12). From the figure, we see that the main task, located at the top of the hierar-
chy, is "the task of regulating traffic flows." It breaks up into 8 sub-tasks, which, in
turn, also have several tasks at their lower levels. Including:
1) "task of collecting information on vehicles", which includes the "task of in-
stalling surveillance cameras" and "the task of recognizing the machine number";
2) "task of fixing violations", which is divided into 2 subtasks - "task of fixing vio-
lations of traffic rules" and "task of fixing an accident". For them, the lowest level of
the hierarchy will be "the task of delinquent offender";
3) the "problem of solving the problem with congestion", which includes the "task
of collecting information about the jam" and "the problem of analysis of the density of
the flood", which also branch out to "the problem of considering possible alternatives
to detour", "the task of adjusting the pace of the traffic light "And" the task of calling
police officers ";
4) "task of optimization of public transport", which includes the "task of setting the
table" and "task of determining the frequency of vehicles." The latter includes the
"task of sending data to the scoreboard" and "task of calculating failures";
5) "the task of ensuring the proper use of traffic lights", which includes the "prob-
lem of analyzing the density of the road at a certain hour of the day" and "the task of
collecting information about current traffic lights", which also branch out to the "task
of turning off the traffic light", "the task of installing additional traffic lights" and "the
task of setting the pace of change of light";
6) "task of collecting fees for transport services", which include "the task of collect-
ing information about transport services" and "the task of optimizing tariffs". They in
turn, at the lower level of the hierarchy, have a "task of raising funds";
7) "task of monitoring the state of roads", which is divided into "the task of con-
structing a new road" and "the task of checking the state of roads". The latter also has
a lower level of "the task of scheduling repair work" and "the task of repair";
8) "task of monitoring the weather on highways" includes the "task of collecting in-
formation on the availability of appropriate equipment" and "the task of weather anal-
ysis", which in turn include the "task of sending cars to clear roads".
1
1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8
1.1.1 1.1.2 1.2.1 1.2.2 1.3.1 1.3.2 1.4.1 1.4.2 1.5.1 1.5.2 1.6.1 1.6.2 1.7.1 1.7.2 1.8.1 1.8.2
A B C D E F G H I J K L M N
Fig. 12. Hierarchy of tasks of the information system of transport flows of a large city
Tasks:
1 – Management of city traffic flows;
1.1 – Information about vehicles;
1.1.1 – Installation of data collection from chamber storage;
1.1.2 – Machine number recognition;
1.2 – Commit message;
1.2.1 – Fix traffic messages;
1.2.2 – Fixing of an accident;
1.3 – Traffic congestion management;
1.3.1 – Collection of congestion information;
1.3.2 – A real congestion;
1.4 – Optimization of public transport traffic;
1.4.1 – Propose machine speeds;
1.4.2 – Installation of a simple scoreboard;
1.5 – Specially protected light of traffic lights;
1.5.1 – Analysis of the reliability of expensive at a certain hour of acquisition;
1.5.2 – Collection of information about current traffic lights;
1.6 – Complete set of payment for transport services;
1.6.1 – Information on transport services;
1.6.2 – Tariff optimization;
1.7 – Existing roads are observed;
1.7.1 – Construction of a new road;
1.7.2 – Check the condition of the roads;
1.8 – Highway advantages available;
1.8.1 – Information about the equipment that supports these people;
1.8.2 – Analysis of weather data;
A – Separate traffic monitoring;
B – Delinquency delays;
C – Adjusting the speed of the traffic light;
D – Consideration of possible detours;
E – Call the police;
F – Sending data to the scoreboard;
G – Subtraction fence;
H – Turning off the traffic light;
I – The installation of additional bright light;
J – Adjust the light change rate;
K – The collection of rights;
L – Drawing up of graphic repair of works;
M – This repair;
N – The link of road widening machines.
4 Description of the Created Software
Let's launch the program and select the required characteristics. We select the number
of cars and press the start button. Let's see how cars ride without starting a congestion
drive algorithm (Fig. 13). Next, we will switch to the mode of using the required algo-
rithm (Fig. 14). We see that the paths of some cars differ considerably in these modes,
and in the mode with the algorithm traffic is not formed. Now let's consider and com-
pare the timelines of unmanned vehicle fares with initial data and algorithm (Fig. 15).
Fig. 13. The movement of cars with the initial data
We see that taking into account the algorithm used, the time of travel of some cars has
significantly decreased, and for the rest of the cars remained almost unchanged (dif-
ference to 0.5 s). So, the program is workable and the goal is achieved. For this pur-
pose, the most active part of it was chosen, which creates the greatest discomfort for
the participants of the traffic movement. In particular, a program implementing one of
the methods for solving congestion problems was developed. Motivation of the driv-
er's actions determines the place, time and way of movement. Each driver individually
decides whether he needs to go this or that way, or whether he relies on minimizing
fuel costs or time. Therefore, to avoid the influence of the human factor on the
movement of vehicles, this program works with unmanned cars. When planning a
route to your destination, an unmanned car determines the shortest path. However,
with obstacles such as traffic jams, this path may cause significant delays. The pro-
gram is also designed to schedule commuting trains, minimizing the time for which
the vehicle will arrive at destination.
Fig. 14. Movement of cars according to the algorithm
Fig. 15. Time characteristics of travel of unmanned cars
The program works with Unity, where we set the number of vehicles that will move,
and the locations of their movement and destination will be read from the statistics
stored in the database of the traffic information system of the big city. Then the cars
are moving according to the traffic rules, and taking into account the traffic lights.
When detecting a significant number of vehicles at an intersection (intersection), the
car according to the Dijkstra algorithm is looking for a shorter route, bypassing the
overloaded road. Vehicle movement stops when the planned place is reached. The
program is called by executing executable file (with extension .exe).
The input data is the number of cars that will move on the map (the starting points
and destinations of each of the cars are indicated in Unity) and the choice of motion
algorithm or not. The starting point is the actual traffic of cars on the map, which
shows the fastest route itself.
5 Conclusion
The work of predecessors was highlighted and issues remained unpublished and those
that require further research. Then a systematic analysis of the functioning of the sys-
tem was performed, the purpose of the system was specified by constructing a goal
tree, the main variants of its achievement were given by decomposition to aspects,
sub-aspects and criteria for evaluating the quality of implementation. Next, a hierar-
chy of data flow diagrams was constructed, which, with a sufficient degree of detail,
describes the processes of the functioning of the IP, the links between them and the
information necessary for the successful operation in the context of the selected type
of IP. On the basis of DFD a task hierarchy is constructed taking into account the
sequence of their execution. The main characteristics, methods of problem solving,
methods of presentation of knowledge, software, system and auxiliaries, which are
used in work for construction of mechanisms of choice of the optimal route of a de-
tour passage, are given. The description and analysis of methods for solving the prob-
lem with congestion is presented, as well as for the implementation of the C # lan-
guage and the Unity tool for developing a graphical interface for working with the
map and unmanned cars. The composition, structure, content and functions of the
developed software and the processes of their joint operation were described. The
reference example confirms the working capacity of the development, and the results
of the system's operation correspond to the task. As a result of this work an infor-
mation system was developed, the main element of which is the traffic flows of a
large city. The theoretical and methodological provisions and mathematical tools for
performing various types of tasks for managing these flows and improving the
transport network and supporting the state of roads were also researched and devel-
oped.
References
1. Chen, N., Chen, Y., You, Y., Ling, H., Liang, P., Zimmermann, R.: Dynamic urban sur-
veillance video stream processing using fog computing. In: IEEE second international con-
ference on multimedia big data (BigMM), 105-112. IEEE. (2016).
2. Ermacora, G., Toma, A., Bona, B., Chiaberge, M., Silvagni, M., Gaspardone, M., Anto-
nini, R.: A cloud robotics architecture for an emergency management and monitoring ser-
vice in a smart city environment (Turin, Italy: Tech. Rep.) (2013).
3. Banzhaf, E., Hofer, R.: Monitoring urban structure types as spatial indicators with CIR
aerial photographs for a more effective urban environmental management. IEEE Journal of
Selected Topics in Applied Earth Observations and Remote Sensing 1(2), 129-138. (2008).
4. Dr. Henry Lieu: Revised Monograph on Traffic Flow Theory. Transportation Research
Board (TRB) Special Report 165, "Traffic Flow Theory" (2001).
5. Hoogendoorn S., Knoop V.: Traffic flow theory and modeling. Edward Eldar Publishing
(2013).
6. Georgian, M. I., Myroniuk, V. V.: Decoding the species composition of forest plantations
according to satellite imagery Sentinel-2. Forestry and landscape gardening,
http://nbuv.gov.ua/UJRN/licgoc_2017_11_6.
7. Golej, J., Adamuscin, A.: The overview of green building sector in Slovakia. In: EAI En-
dorsed Transactions on Energy Web 19(23): e8. https://eudl.eu/pdf/10.4108/eai.13-7-
2018.158874.
8. Fonstad, M. A., Dietrich, J. T., Courville, B. C., Jensen, J. L., Carbonneau, P. E.: Topo-
graphic structure from motion: a new development in photogrammetric measurement.
Earth Surface Processes and Landforms 38(4), 421-430 (2013).
9. Hahanov, V., Gharibi, W., Litvinova, E., Chumachenko, S., Ziarmand, A., Englesi, I., ...,
Khakhanova, A.: Cloud-Driven Traffic Monitoring and Control Based on Smart Virtual In-
frastructure (2017-01-0092). In: SAE Technical Paper (2017).
10. Sachenko, A., Kochan, V., Kharchenko, V., Roth, H., Yatskiv, V., Chernyshov, M., ...,
Fesenko, H.: Mobile Post-Emergency Monitoring System for Nuclear Power Plants.
In: ICTERI, 384-398 (2016).
11. Jurgen R. K.: Autonomous Vehicles for Safer Driving. In:SAE International (2013).
12. Scanning trees will help them weigh and detect carbon content:
https://ukurier.gov.ua/uk/news/skanuvannya-derev-dopomozhe-yih-zvazhuvati-ta-viya/.
13. How big data and drones can save Ukrainian forests:
http://texty.org.ua/pg/blog/nartext/read/76201/Jak_big_data_i_drony_mozhut_vratuvaty.
14. Chen, N., Chen, Y., Song, S., Huang, C. T., Ye, X.: Smart urban surveillance using fog
computing. In: 2016 IEEE/ACM Symposium on Edge Computing (SEC), 95-96 (2016).
15. Zdebskyi, P., Vysotska, V., Peleshchak, R., Peleshchak, I., Demchuk, A., Krylyshyn, M.:
An Application Development for Recognizing of View in Order to Control the Mouse
Pointer. In: CEUR Workshop Proceedings, vol 2386, pp. 55-74 (2019).
16. Lytvyn, V., Vysotska, V., Mykhailyshyn, V., Peleshchak, I., Peleshchak, R., Kohut, I.: In-
telligent system of a smart house. In: 3rd International Conference on Advanced Infor-
mation and Communications Technologies, AICT, pp. 282-287 (2019).
17. Emmerich, M., Lytvyn, V., Yevseyeva, I., Fernandes, V. B., Dosyn, D., Vysotska, V.:
Preface: Modern Machine Learning Technologies and Data Science (MoMLeT&DS-
2019). In: CEUR Workshop Proceedings, vol 2386 (2019).
18. Lytvyn, V., Sharonova, N., Hamon, T., Cherednichenko, O., Grabar, N., Kowalska-
Styczen, A., Vysotska, V.: Preface: Computational Linguistics and Intelligent Systems
(COLINS-2019). In: CEUR Workshop Proceedings, vol 2362 (2019).
19. Chyrun, L., Gozhyj, A., ,Stefanchuk, A. Oborska, O., Lozynska, O., Mykich, K., Basyuk,
T., Rzheuskyi, A.: Development of mobile application for choreographic productions crea-
tion and visualization. In: CEUR Workshop Proceedings, 2386, 340-358 (2019).
20. Lytvyn, V., Peleshchak, I., Peleshchak, R., Vysotska, V.: Information Encryption Based on
the Synthesis of a Neural Network and AES Algorithm. In: 3rd International Conference
on Advanced Information and Communications Technologies, AICT 2019, 447-450
(2019).