scholarly journals OPTIMIZATION OF MANAGEMENT OF URBAN LIGHTS WITH THE USE OF NEURAL NETWORKS

THE BULLETIN ◽  
2021 ◽  
Vol 389 (1) ◽  
pp. 14-17
Author(s):  
A.А. Suleimen ◽  
G.B. Kashaganova ◽  
G.B. Issayeva ◽  
B.R. Absatarova ◽  
M.C. Ibraev

One of the most pressing problems of large cities is the problem of traffic management of vehicles. The reason for this problem is an imperfect way to manage traffic flows. Traffic light regulation is of particular importance in traffic management. Most modern traffic light control systems operate at set time intervals and are not able to cope with the constantly changing situation on the road. A promising direction for solving this problem is to optimize the system using artificial neural networks. The advantage of neural networks is self-learning, which allows the system to adapt to the changing situation on the road. Despite numerous attempts, it has not yet been possible to obtain a high-quality mathematical model of urban traffic management. This model should determine the functional dependence of transport flow parameters on control parameters. Nowadays, traffic flows are regulated everywhere by means of traffic lights. If we can get a fairly accurate mathematical model of traffic flows, we can determine the optimal duration of the traffic signal phases to achieve the maximum capacity of the road network node. A fairly accurate mathematical model of traffic management that works in predictive mode will display an estimate of the optimal control parameters, as well as make correct decisions in emergency situations. Well-known mathematical models of road traffic take into account only the average values of traffic flows, and not the exact number of cars on each road section at a particular time.

2019 ◽  
Vol 16 (6) ◽  
pp. 680-691 ◽  
Author(s):  
A. N. Novikov ◽  
S. V. Eremin ◽  
A. G. Shevtsova

Introduction. The paper deals with traffic light regulation. This task is always relevant. Thus, even for an ordinary intersection, depending on the intensity of traffic flows, the control cycles should differ significantly. This paper discusses all kinds of systems, namely, two-phase, three-phase, four-phase and others. In addition to solving optimization problems of regulation the authors propose to use the device managed network, which allows setting the configuration of the transport network as the base graph of the managed network, and then based on the parameterization of the graph of the throughput ability of the network to solve the optimization problem of selecting the control traffic and pedestrian flow.Methods and materials. For solving the problem of traffic management on the road network, the authors proposed to use the mechanisms of managed networks. As a result, the authors presented a technique based on the calculation of saturation flows, the main characteristic of the control technique, which was activated when there were no requests from the transport detectors to turn by the green signal.Results. The authors constructed a generalized simulation model of control phases of regulation based on the usage of controlled networks, depending on the intensity of traffic flows and formed a method of selecting modes of traffic lights for different traffic situations.Discussion and conclusions. The solution of the problem of traffic light regulation significantly affects the traffic management efficiency. The authors determine the main parameters based on the analysis of traffic light control methods. As a result of the calculation of the saturation flow and information about the intensity of traffic, the authors form the method of selecting the necessary modes of the phosphor object’s operation.The authors have read and approved the final manuscript. Financial transparency: the authors have no financial interest in the presented materials or methods. There is no conflict of interest.


Author(s):  
Norlezah Hashim ◽  
Fakrulradzi Idris ◽  
Ahmad Fauzan Kadmin ◽  
Siti Suhaila Jaapar Sidek

Traffic lights play such important role in traffic management to control the traffic on the road. Situation at traffic light area is getting worse especially in the event of emergency cases. During traffic congestion, it is difficult for emergency vehicle to cross the road which involves many junctions. This situation leads to unsafe conditions which may cause accident. An Automatic Traffic Light Controller for Emergency Vehicle is designed and developed to help emergency vehicle crossing the road at traffic light junction during emergency situation. This project used Peripheral Interface Controller (PIC) to program a priority-based traffic light controller for emergency vehicle. During emergency cases, emergency vehicle like ambulance can trigger the traffic light signal to change from red to green in order to make clearance for its path automatically. Using Radio Frequency (RF) the traffic light operation will turn back to normal when the ambulance finishes crossing the road. Result showed the design is capable to response within the range of 55 meters. This project was successfully designed, implemented and tested.


2021 ◽  
Vol 2134 (1) ◽  
pp. 012002
Author(s):  
E V Kasatkina ◽  
D D Vavilova

Abstract The article presents a mathematical model for optimizing traffic flows in an urban environment based on a stochastic approach. It allows to optimize traffic flows using a genetic algorithm by changing the phases of traffic lights operation. An exponential law of distribution of the generation of cars at the input points of the transport network has been established. The relationship between the intensity of servicing the traffic flow and the time of the green signal of the traffic light is revealed. Practical calculations have confirmed the applicability of the optimization model in traffic management.


2021 ◽  
Vol 116 (1) ◽  
pp. 299-304
Author(s):  
Assel Aliyadynovna Sailau

The number of vehicles on the roads of Almaty, Kazakhstan is growing from year to year. This brings about an increasing intensity and density of traffic flows in the streets which leads to congestion, decreasing speed of the traffic flow, increasing environmental pollution caused by car emissions, and which can potentially lead to the road traffic accidents (RTA), including fatalities. While the number of injuries grows up mainly due to drivers’ non-compliance with the speed limit, the environmental pollution is caused by longer traffic jams. Therefore, to reduce the level of road traffic injuries and emissions into the environment it is necessary to ensure the uniform movement of traffic flows in cities. Currently, one of the effective ways to do it is the use of transport telematics systems, in particular, control systems for road signs, road boards and traffic lights. The paper presents an analysis of existing systems and methods of traffic light regulation. The  analyses of the systems and methods are based on the use of homogeneous data, that is the data on standard parameters of traffic flows. The need in collecting and analyzing additional semi-structured data on the factors that have a significant impact on the traffic flows parameters in cities is shown as well. The work is dedicated to solving the problem of analysis and forecast of traffic flows in the city of Almaty, Kazakhstan. GPS data on the location of individual vehicles is used as the initial data for solving this problem. By projecting the obtained information onto the graph of the city's transport network, as well as using additional filtering, it is possible to obtain an estimate of individual parameters of traffic flows. These parameters are used for short-term forecast of the changes in the city's transport network.


Author(s):  
Nouha Rida ◽  
Mohammed Ouadoud ◽  
Aberrahim Hasbi

In this paper, we present a new scheme to intelligently control the cycles and phases of traffic lights by exploiting the road traffic data collected by a wireless sensor network installed on the road. The traffic light controller determines the next phase of traffic lights by applying the Ant Colony Optimazation metaheuristics to the information collected by WSN. The objective of this system is to find an optimal solution that gives the best possible results in terms of reducing the waiting time of vehicles and maximizing the flow crossing the intersection during the green light. The results of simulations by the SUMO traffic simulator confirm the preference of the developed algorithm over the predefined time controller and other dynamic controllers.


Foristek ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Uswatun Hasanah ◽  
Mery Subito ◽  
Muhammad Aristo Indrajaya

Current road users cannot be separated from the number of violators, therefore traffic lights are made to regulate traffic on the road. At traffic lights, there is also a zebra crossing which serves as a means of crossing the road for pedestrians. To minimize violations at road intersections, researchers designed a tool to detect traffic violations. Traffic violation detection tool is made in prototype form using a control system with Arduino nano and software. This traffic light system uses LDR and laser sensors to detect these violations by cutting the laser which sends light to the LDR. This tool is also equipped with a webcam camera that functions to photograph violations that occur and a buzzer that functions as a warning to officers and riders in the event of a violation with an average response speed of the webcam of 2.37 seconds and the average response speed of the buzzer is 0.4 seconds. . The snapshot from the webcam is saved automatically on your PC / Laptop.


2019 ◽  
Vol 16 (6) ◽  
pp. 670-679 ◽  
Author(s):  
I. E. Agureev ◽  
D. A. Yurchenko

Introduction. The load models of the road network make it possible to understand a lot of the transport, social, environmental, and other city problems. Creating transport models requires knowledge of the traffic flows’ formation and functioning. The paper formulates a goal and poses tasks for the research conducting of the adjoining territories of residential areas in Tula as one of the urban traffic flows’ sources and of the identifying patterns of the parking places near houses’ influence on the road network loading.Materials and methods. The basis of the research was the development in the field of predictive simulation of automobile transport systems. The authors used complex of computer-aided design “TransNet”, which allowed adjusting the initial data in the base model by the results of the parking places’ functioning.Discussion and conclusions. As a result, the improved transport model of Tula allows making the forecast for determining the main parameters of the transport system taking into account the dynamics of vehicles’ local area departure at different time intervals. Moreover, the proposed methodological tools and algorithm for solving the problem of the road network loading in a quasi-dynamic setting helps to solve existing transport problems and to improve the traffic organization.The authors have read and approved the final manuscript. Financial transparency: the authors have no financial interest in the presented materials or methods. There is no conflict of interest.


Author(s):  
Romanika Okraszewska ◽  
Kazimierz Jamroz ◽  
Marek Bauer ◽  
Krystian Birr ◽  
Anna Gobis

The role of pedestrian and bicycle traffic in Poland has growing trend. The comprehensive traffic study, conducted in Gdansk in 2016, has confirmed the increase in the number of cyclists and their share in the modal split. Therefore, it is particularly important to ensure the safety of this group of unprotected road users. Only in 2015 on the roads of Gdansk occurred 93 accidents (excluding collisions) involving cyclists. As a result, 101 people were injured, including nine seriously and 3 people killed. The study aim was to identify risk factors for collisions involving cyclists based on data of accidents reported to the police. The following factors were analysed: the conditions for the drivers on the road (speed limits of, surface conditions), conditions for cyclists (cycling infrastructure, traffic management), external conditions (time of the year, time of the day, weather conditions), conditions organizational (type of intersection, traffic light) as well as the social aspects – the behaviour of all users.


Author(s):  
Кадасев ◽  
D. Kadasev ◽  
Коротнев ◽  
V. Korotnev

This article describes a practical method of constructing mathematical models of traffic flow, the most suitable for a particular city highway. The initial data are: instant speed, time, distance, flux density, intensity of movement of vehicles. Using the obtained data, built regression model, and conducted correlation analysis. The choice of the mathematical model that most faithfully describes the transport process was made on the basis of the correlation coefficient


2021 ◽  
Vol 2 (1) ◽  
pp. 1-24
Author(s):  
Liuwang Kang ◽  
Ankur Sarker ◽  
Haiying Shen

As Electric Vehicles (EVs) become increasingly popular, their battery-related problems (e.g., short driving range and heavy battery weight) must be resolved as soon as possible. Velocity optimization of EVs to minimize energy consumption in driving is an effective alternative to handle these problems. However, previous velocity optimization methods assume that vehicles will pass through traffic lights immediately at green traffic signals. Actually, a vehicle may still experience a delay to pass a green traffic light due to a vehicle waiting queue in front of the traffic light. Also, as velocity optimization is for individual vehicles, previous methods cannot avoid rear-end collisions. That is, a vehicle following its optimal velocity profile may experience rear-end collisions with its frontal vehicle on the road. In this article, for the first time, we propose a velocity optimization system that enables EVs to immediately pass green traffic lights without delay and to avoid rear-end collisions to ensure driving safety when EVs follow optimal velocity profiles on the road. We collected real driving data on road sections of US-25 highway (with two driving lanes in each direction and relatively low traffic volume) to conduct extensive trace-driven simulation studies. Results show that our velocity optimization system reduces energy consumption by up to 17.5% compared with real driving patterns without increasing trip time. Also, it helps EVs to avoid possible collisions compared with existing collision avoidance methods.


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