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The average speed and density of road transport are used as indicators of the congestion situation, but do not allow tracking the evolution (stages of formatting, progressing, and vanishing) of traffic congestion. The authors proposed and justified a quantitative indicator of traffic congestion, which allows in an automated mode to identify the congestion situation on the urban road network using hardware and software video recording systems. The purpose of this study is due to the need to study the quantitative characteristics of the proposed indicator at characteristic intersections of urban roads, which will allow us to develop scientifically based recommendations for predicting congestion situations, substantiating, and making optimal decisions on measures to promptly eliminate traffic congestion. The object of study is the traffic flow at three types of intersections of the Perm city road network, equipped with a photo and video recording software and hardware complex. The subject of the study is the regularities of the evolution of the listed deterministic indicators of traffic flows, which can be used for operational forecasting of the formation, development, and elimination of traffic congestion. The theoretical and methodological approach is based on the methods of mathematical statistics used to process the results of observations of traffic flows at different types of intersections using a «sliding window», calculating the average daily value and standard deviation. The initial data were obtained with the help of hardware and software complexes for fixing violations of traffic rules installed on the street and road network of the Perm city. As a result of the study, the rational parameters of the «sliding window» were determined, ensuring the structuring of the traffic congestion indicator; the facts of the congestion situations formation were revealed; the features of the congestion evolution and the presence of problematic traffic directions for which it is advisable to change the traffic light regulation mode were determined. The theoretical and practical significance of the work consists in checking the operability of the proposed indicator and criterion of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, adjusting the operating modes of traffic lights, etc. It is also possible to use the proposed traffic congestion indicator to assess the effectiveness of traffic light regulation on the Perm city road network. The direction of further research is to study the patterns of traffic congestion at intersections of the urban road network, of various types that are not included in this study.

In the context of the formation of heterogeneous data that differ significantly in nature, even of a small volume, it becomes necessary to analyze them for decision-making. This is typical for many high-tech industrial fields of human activity. The problem can be solved by bringing heterogeneous data to a single view and then dividing it into clusters. Instead of searching for a solution for each data element, it is proposed to use the division of the entire set of normalized data into clusters, and thereby simplify the process of isolating the cluster and making a decision on it. The essence of the proposed solution is the automatic grouping of objects with similar data into clusters. This allows you to reduce the amount of analyzed information by combining a lot of data and perform mathematical operations already for the cluster. When splitting, it is proposed to use the theory of fuzzy logic. The possibility of such an approach is due to the fact that different objects always have several characteristics by which they can be combined. These signs are often not obvious and are poorly formalized. A hierarchical modification of the AFC fuzzy clustering method based on the operation (maxmin) of the fuzzy similarity ratio is proposed. The basic concepts and definitions of the proposed method of automatic partitioning of a set of input data, a step-by-step scheme of the corresponding cluster procedure are considered. The efficiency of the proposed method is demonstrated by the example of solving the problem of forming a traffic flow. A numerical experiment has shown that the developed algorithm allows you to automatically analyze heterogeneous data and stably divide them into classes. The application of the proposed modification allows for the preliminary partitioning of data into clusters and allows reducing the volume of analyzed data in the future. There is no need to consider the objects in each case separately.

The movement of vehicles in the places of separation of traffic flows is analyzed. The high-speed mode of movement of vehicles along traffic lanes at a regulated intersection in the places of traffic flow separation has been determined. It is recorded that the number of formed “bundles” increases in the places of separation of transport flows. The movement of the formed “packs” of moving cars determines the speed mode of vehicles. The experiment showed that the speed of movement along the lanes is different. In a lane with a large number of formed “bundles”, the speed of cars is less than in a lane with a smaller number of “bundles”. It is established that the presence of “bundles”, especially in the areas of separation of traffic flows, leads to a large variation in the range of changes in the speed of vehicles at the intersection. The highest value of the speed mode of vehicles when driving on the experimental section is within 15-20 km/h, and the lowest is less than 5 km/h. Purpose – determination of the factors influencing the change in the speed regime of vehicles in the places of separation of traffic flows. Methodology statistical methods of processing a full-scale experiment were used in the work. Results: the ranges of changes in the speed of vehicles in places where traffic flows are separated by lanes and the reasons for their changes are determined. Practical implications: the obtained results should be used in the development of measures to ensure road safety in places of separation of traffic flows and the organization of traffic at intersections.

The relevance of the present paper is justified by the need to search for a scientifically based criterion for the formation, development and elimination of traffic congestion using modern highly efficient mathematical methods of information processing. It seems necessary to study the results of using the rescaled range, statistical, fractal, harmonic, and wavelet analysis of time series formed by the time (duration) of the movement of cars in a stream along a road section in the absence and presence of traffic congestion. The object of study is a section of the road network equipped with a software and hardware complex that allows measuring the characteristics of any car in the flow of transport. The subject of the study is the patterns of changes in the duration of movement of individual cars in the absence and presence of a congestion situation. The purpose of this study is a quantitative indicator of the formation, evolution, and elimination of traffic congestion. The basis of the theoretical and methodological approach is the use of modern highly efficient mathematical methods for processing information about traffic flows received from stationary complexes of photo and video recording of traffic violations. As a result of the study of time series, decompositions of the analyzed time series by harmonics and wavelets are constructed, statistical and fractal characteristics of the time series under consideration are determined. The analysis of the obtained results is carried out, the features of the obtained dependencies are revealed. The theoretical and practical significance of the work lies in the scientific substantiation of the quantitative characteristics of traffic congestion, which is of practical interest from the point of view of predicting anomalies in the movement of vehicles on the road network, making decisions on managing the operation of traffic lights, etc. The direction of further research is an in-depth analysis of the identified indicator and determination on its basis of a criterion for determining the stages of formation, evolution, and elimination of traffic congestion at intersections of the street and road network of a large industrial city.

Full-scale studies of the movement of vehicles on the street and road network of large cities have been carried out. It is revealed that a large number of realignments are observed during the movement of vehicles, as factors affecting the capacity of the road network. The quantitative characteristics of car rebuilds before relocations are determined. The dependence of the number of vehicle realignments on the number of traffic lanes and the location of the vehicle in a particular lane has been established. The obtained research results should be taken into account when determining the duration of traffic light regulation cycles at intersections. Purpose – determination of the number of realignments as factors affecting the capacity of the road network. Methodology statistical methods of processing a full-scale experiment were used in the work. Results: quantitative characteristics of realignments depending on the number of lanes and the composition of traffic flows are obtained. Practical implications it is advisable to apply the obtained results in the regulation of road traffic by technical means of traffic management.

The active development of the fleet of vehicles contributes to an increase in the congestion of transport networks and requires the construction of new systems for determining the places of congestion, as well as the development of ways to solve the existing problems. A special place in this area is occupied by an early assessment of the condition of transport networks, which allows timely measures to be taken to modify them. In this regard, research in the field of forecasting the main indicators of traffic flow in order to identify congestion of transport networks has become highly relevant. The use of data mining technologies, including methods of multidimensional linear regression, will make it possible to build predictive models for studying the characteristics of traffic flow. Aim. To build a model for predicting traffic intensity at an intersection using machine learning methods for effective decision-making when managing traffic flow. The scientific novelty of this study lies in the development of a multidimensional regression model for predicting traffic intensity, considering the control of retraining based on open data on observations of the number of vehicles at four different sections of the intersection. Methods. A multidimensional linear regression model was used to predict the intensity of traffic flow. Ridge, Lasso and ElasticNet regularization approaches were used as methods to improve the forecasting efficiency. Results. A model for predicting the intensity of traffic flow is constructed. As part of the experimental study, an assessment of the effectiveness of the use of regularization methods was carried out, as well as a comparative analysis of the accuracy of forecasting the model based on the initial and normalized data. Conclusion. The smallest root-mean-square error on the test data was shown by the multidimensional linear regression model with Ridge regularization. The developed model makes it possible to predict the number of vehicles passing per unit of time with an average quadratic error equal to 0.638. The obtained results of the study will allow early diagnostics of the occurrence of congestion of transport networks to optimize the movement of vehicles at various intersections of the UDS. The results of the study are of high practical importance, as they can be implemented into existing traffic management systems for effective decision-making in traffic flow management. The direction of future research includes the practical testing of the predictive model in real conditions, as well as the consideration of ensemble methods of machine learning to improve the accuracy in predicting the main indicators of the traffic flow.

A method is proposed for determining the fuel consumption of a wheeled vehicle depending on its speed, road surface flatness and road slope in the longitudinal direction. The purpose of the research is to derive mathematical relationships for calculating the fuel consumption of vehicles, which is one of the transport cost factors during the construction/reconstruction or overhaul of a highway. The proposed polynomial dependencies for calculating fuel in addition to vehicle speed, road surface flatness and its longitudinal slope take into account the mass-dimensional parameters of vehicles involved in road traffic. New mathematical relationships between the speed of wheeled vehicles, road surface flatness and longitudinal road slope allow to simulate the change in the value of fuel consumption of a wheeled vehicle when the speed of traffic flow or the slope of the road surface changes in the forward or reverse direction of the vehicle. In a graphic way, the influence of the pavement slope on the value of fuel consumption, both loaded and unloaded wheeled vehicle is presented. When determining transport costs associated with the highway construction, reconstruction or overhaul it is proposed to use empirical mathematical relationships, which make it possible to obtain fuel consumption with an accuracy of 5 % and save up to 15 % of budget (private) investments. The analysis of scientific publications of the existing approach determine the transport costs associated with highway construction, reconstruction or overhaul. The presented method for determining the fuel consumption of wheeled vehicles with small and large loading capacity increases the accuracy of determining transportation costs and reduces the level of financial costs for highway construction, reconstruction or overhaul.

The relevance of the manuscript is due to the need to process and analyze the information accumulated by the complexes of photo-video recording of traffic violations, which will further develop mathematical, computational and simulation models of road transport, solve problems of optimization and management of traffic flows, make management decisions to reduce the number of congestion and reduce the anthropogenic load on the environment. The object of the study is a part of a three-lane road with heavy one-way traffic, equipped with a software and technical complex that allows measuring the main characteristics of the traffic flow (vehicle speeds, including the average values on the controlled road part, driving time, etc.). The subject of the study is the traffic flow intensity during a 7-day time (from Monday to Sunday). The analysis of the obtained dependences allowed us to formulate a hypothesis about the presence of determin- istic and stochastic components in the traffic flow intensity, which is a random function of time, and the verification of which is the purpose of this study. Statistical processing of the obtained data is used as a theoretical and methodological approach, as well as the assumption that the traffic flow intensity can be represented by the sum of deterministic and stochastic components. The developed approach using the smoothing procedure allowed us to select both components, and this is a scientific novelty of the analysis performed. As a result of the study, it is shown that the deterministic component of the traffic flow intensity for working days is qualitatively different from the deterministic component for weekends. Statistical indicators of probabilistic distributions of traffic flow intensities and random components selected from them are determined. Estimates of the correspondence of the selected curves to the normal law of probability distribution are obtained using the Kolmogorov and Pearson criteria, which contradict each other. Practical significance consists in the use of a deterministic component for predicting traffic flows, controlling the operation of traffic lights, monitoring the operation of equipment, as well as in the reconstruction, design and construction of roads and road objects. The direction of further research is to obtain, statistically process and generalize data on the traffic flows intensity in other parts of the road network.

Copyright of Cybernetics & Systems Analysis / Kibernetiki i Sistemnyj Analiz is the property of V.M. Glushkov Institute of Cybernetics of NAS of Ukraine and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The capacity of a road (street) is the maximum number of cars that a section of a road (street) can pass per unit of time in one or two directions in the considered road and weather and climatic conditions. In science, there are several approaches to determine the capacity: models based on dynamic models of traffic flow, the model of Birul A. K., Silyanov V. V., Tribunsky V. M., Khomyak Ya. V., Bilyatinsky A. A. and etc. In a practical way, they divide: theoretical, practical and maximum throughput. In the Russian Federation, there are a large number of guidelines for its determination. However, for a circular intersection with traffic light regulation and a cut-through central island (hereinafter referred to as KPSRPTSO), no such recommendations have been presented. After analyzing this traffic organization scheme, it was for the first time proposed to determine the capacity of the traffic lane of the KPSRPTSO half-ring. The purpose of the study is to improve the efficiency of the KPSRPTSO by determining the theoretical bandwidth of the traffic lane of a semi-ring of a traffic intersection. The article hypothesizes that the investigated theoretical throughput depends on two factors: the diameter of the traffic junction ring and the effective duration of regulation for the main road. To substantiate the adequacy of the calculations, the simulation method was used in the Aimsun software package (micromodeling). On the basis of data from field surveys of sections of the road network, a simulation model was created with a high degree of reliability, reflecting the current situation at regulated intersections, and the effectiveness of design solutions when organizing the KPSRPTSO was assessed. The relationship between the theoretical bandwidth of the KPSRPTSO half-ring and the diameter of the ring and the effective duration of regulation for the main road has been established. Comparison of the experimental data with the calculated values performed according to the recommendations of the methodological literature shows a discrepancy from 1% to 13%, which shows the qualitative convergence of the data. Further research involves the development of a methodology for calculating the parameters of the KPSRPTSO.

Today, one of the most powerful trends in innovative change in the modern world is the Internet of Things IoT. And although this trend is essentially only at an early stage, it already plays a significant role in the modern world, in modern civilization. It is safe to predict that further expansion of its scope. However, the emergence of this phenomenon is also accompanied by the emergence of related problems. This is especially true of cyber threats, which can cause significant harm to both the Internet of Things itself and the people who use those networks. Accordingly, there is a need for means to combat these threats. This is a rather complex problem, which primarily requires the development of methods and technologies for detecting such threats. At the same time, there are no clear concepts of relevant solutions for cyber security of various IoT applications, especially where financial resources are limited. Therefore, research is currently relevant to find solutions that may be acceptable for relatively low-budget facilities. The aim of the work is to obtain a method for detecting intrusions into the IoT network by detecting anomalies in the network traffic flow of AAA protocols. This problem is complicated by the fact that the solution found must comply with basic security policies. The study conducted in this paper showed that such a solution is possible in principle by using the capabilities of the AAA RADIUS protocol and the use of machine learning. Machine learning methods were tested on the UNSW_NB15 dataset. For machine learning, pre-processing was performed to normalize and standardize the data. Computer experiments have tested the suitability of detecting a set of cyberattacks for different models of machine learning. It was shown that the formulated approach has the potential to be used in practical developments to detect intrusions in the IoT network. [ABSTRACT FROM AUTHOR]

Problem. Existing methods to determine travel time on the road network links are based on the estimation of link saturation. Different formulas are used during the estimation but the ratio of traffic volume to link capacity is always the base for calculations. The main problem of such an approach is an insufficient justification of the lane capacity value which defines link capacity. It causes doubts about the background of the approach application regarding urban traffic flows. At the same time, authoritative traffic management guidelines declare that when there are signal-controlled intersections on the link then the link capacity is restricted by the intersection with minimal capacity. Thus, the alternative to the known traffic assignment approach based on link capacity can be created and then used to make the assignment on the base of delays at intersections. Evaluation of such an alternative is the actual task as the new approach to traffic assignment opens the scope for improving the accuracy of modelling the traffic flows in cities. Goal. The new approach to traffic assignment on the base of intersection delays needs to be tested for the usefulness for transport modelling practice. Methodology. The alternative approaches to traffic assignment were experimentally compared based on the parameters of the transport model, which provide the compliance of the calculated average vehicles’ speed with the factual one. Results. The new approach to traffic assignment based on intersection delays allows a more accurate calcu-lation of traffic volumes. Originality. The new ap-proach to traffic assignment based on intersection delays allows avoiding the need to set restrictions on road network links’ capacity. Practical value. Re-ceived results clarify the way to set the free-flow travel time of network objects in VISUM and allow increasing accuracy of urban traffic flows modelling.

The formation of traffic congestion remains a significant problem in the organization of road traffic in cities and is a serious challenge for engineering and science. Domestic and foreign practical experience, as well as scientific research have shown that the most rational approach to solve this problem is the use of intelligent transport systems, the subsystem of which, in terms of traffic management on the road network of cities, are automated traffic management systems. However, in the case of implementation of traffic flow control in the automated mode on the basis of values of the number of passing vehicles, there is uncertainty: the value of the traffic flow intensity can be equal to or close to zero both in the case of traffic congestion and in the case of complete absence of the vehicle. In modern foreign scientific research it is offered to solve this situation by means of comparison of data of intensity of traffic flow with its concentration in time (lane occupancy). Unfortunately, this process is not fully for understanding. Therefore, the purpose of this article is to improve the previously developed by the authors of the model of the influence of lane occupancy on the intensity of traffic flow, taking into account a wider range of experimental data. Achieving this goal required theoretical studies, which were based on the theory of transport flows, the theory of pulses, mathematical modeling. To confirm the results of theoretical studies, experimental studies were conducted, which were based on the theory of experimental planning, mathematical statistics. The initial data for the experiment were collected and processed with the help of software and equipment STATISTICA 10, SPECTRUM 2.0, Traficam, etc.in the end, the initial model of the influence of band occupation on the intensity of traffic flow was corrected. The scientific novelty of the research results lies in the fact that the corrected model reliably displays the physical meaning of the process of changing the intensity of traffic under the influence of the concentration of traffic flow in time, taking into account the different modes of operation of the adjustable cross-section. the obtained results can be used to improve the algo-rhythms of controlled intersections in the automated traffic management systems, calibration of simulation models of traffic flow movement, operational control of traffic flow.

For thousands of years in major cities one of the main problems was the possibility of movement. The need for movement is based on the opportunities provided by transport, and encourages society to further develop. The article considers the historical aspects of the study of the mobility of the population and the study of its mobility in terms of digital technology.The application of various methods of mobility research is a common practice in many countries, cities, regions, which provides the collection of important information for the development of transport systems. Financial and organizational constraints affect the quantity and quality of the data collected. Existing techniques need to be constantly adapted to rapidly developing technologies and the rapidly changing nature of population mobility, which is becoming more intermodal. A qualitative model based on an appropriate data set creates a qualitative set of input data for the concept, design, and evaluation results. This in turn will allow for a more reasonable design and evaluation of transport projects.Transport modeling varies from developing relatively simple models in the form of tables to models of transport networks, which consider transport demand as a function of the state of the transport network. For each stage of modeling, there is a need to include feedback in the modeling process. They reveal the interrelation of the various steps of the modeling process and the need to use iterative methods of calculation. The functionality of the model is determined by the presence of feedbacks, which increase the ability of the model to predict actual results. Before carrying out any actions on transport modeling, it is necessary fully understand the requirements for the function of this model. This will ensure, that the model is a result, which is important for the project and provides it with a qualitative assessment.

Subject. Assessment of the level of environmental hazard of vehicles in the urbanized area. Goals. Theoretical and practical rationale for the use of an integrated approach to assessing the parameters of the system “Motor transport flow-urbanized territory”. Methodology. Modeling the process of functioning of motor transport flows in the conditions of an urbanized territory due to a more complete account of the negative environmental effect of the collectively acting chemical and energy pollution. Results. Comparative analysis of the organization of the movement of vehicles in urbanized areas according to environmental criteria using the classical and integrated approaches. Findings. The revealed contradictions allowed to prove the adequacy of the proposed provisions concerning the development and application of a new criterion - a complex environmental load index, which complements the model understanding of the “Motor transport flow-urbanized territory” system.

Accurate and timely information on the current and predicted traffic flows is important for the successful deployment of intelligent transport systems. These data play an essential role in traffic management and control. Using traffic flow information, travelers could plan their routes to avoid traffic congestion, reduce travel time and environmental pollution, as well as improving traffic operation efficiency in general. In this paper, we propose a distributed model for short-term traffic flow prediction based on a k nearest neighbors method, that takes into account spatial and temporal traffic flow distributions. The proposed model is implemented as a MapReduce based algorithm in an Apache Spark framework. An experimental study of the proposed model is carried out on a traffic flow data in the transportation network of Samara, Russia. The results demonstrate that the proposed model has high predictive accuracy and an execution time sufficient for real-time prediction.

When modelling traffic flows through intersections of the network of streets, the most difficult task is to model driver's behavior, since it defies precise mathematical description, it depends on almost unlimited number of factors and can significantly change even for the same driver over a fairly short period of time, for example, one trip. Goal. The goal is to obtain the values of Cd and to build the histogram of distribution of these values probabilities for the chosen type of maneuver. Methodology. The method of modeling driver's behavior at uncontrolled intersections in cross traffic flows has been investigated in the paper. The analysis and processing of video recording of cross traffic flows at the four-way intersection chosen on the network of streets of the city of Kharkiv has been performed. An improved method of «boundary intervals» as a «sliding boundary interval» has been proposed for modeling the driver's behavior. Results. As a result of processing the video recording of the flow motion at uncontrolled intersections, the histogram of the distribution of probabilities of the determination coefficient values at cross traffic flows has been built [11, 12]. With the help of such histograms, the Cd values for each car in the flow can be specified using any known random number generator. Originality. The method stated will take into account both the individual characteristics of drivers and the impact of objective factors on their behavior; the proposed method of recording drivers when modeling the movement of traffic flows will increase the accuracy of modeling, which in turn will allow us to specify a number of results that we obtain by modeling, for example, the calculation of the traffic lane capacity. Practical value. The proposed method of simulating the driver's behavior in the models of traffic flows makes it possible to approximate the accuracy of simulation to the real variety of behavior of drivers, and, consequently, to increase the adequacy of models.

Crowd forecasting is a relatively new task in predicting the future. Today, the crowd studied by classical social psychology has undergone significant changes, which has led to the emergence of such a concept as "Internet crowd". Internet crowd technology is now used to create "dead souls", i.e. fake accounts, using fake names and addresses to form, disseminate opinions and/or impose opinions on real users. The aim of the work is to develop a mathematical model of a virtual crowd to predict its behavior and calculate the probability of transition of a virtual crowd to a real one. The paper highlights the most important factors influencing the emergence of protest movements through the formation of a virtual crowd. It is shown that a person living in a country with a high level of economic development, it is easier to decide to participate in the protest because of confidence in the further stable development of the state. The importance of Internet censorship in the modern world and the possibility of the influence of this factor on the formation of primary groups of protesters in a virtual environment are demonstrated. The methods of mathematical modeling used in the work make it possible to obtain scientifically substantiated variants of development and the probability of changes that the virtual crowd undergoes in time, until its rebirth into real motion. Thus, the assessment of the probability of the transition of the crowd from the virtual to the real state, is important and relevant both in terms of security of the individual citizen and society, and in terms of security of the state as a whole. The proposed model will allow to develop recommendations for specialists who help to ensure a high level of safety in ordinary and extreme situations, to optimize urban development in terms of efficiency of human traffic flow, as well as to effectively manage traffic flow. [ABSTRACT FROM AUTHOR]

The short-term prediction of road traffic condition is one of the main tasks of transportation modelling. The main purpose of which are traffic control, reporting of accidents, avoiding traffic jams due to knowledge of traffic flow and subsequent transportation planning. A number of solutions exist - both model-driven and data driven had proven to be successful in capturing the dynamics of traffic flow. Nevertheless, most space-time models suffer from high mathematical complexity and low efficiency. Artificial Neural Networks, one of the prominent datadriven approaches, show promising performance in modelling the complexity of traffic flow. We present a neural network architecture for traffic flow prediction on a real-world road network graph. The model is based on the combination of a recurrent neural network and graph convolutional neural network. Where a recurrent neural network is used to model temporal dependencies, and a convolutional neural network is responsible for extracting spatial features from traffic. To make multiple few steps ahead predictions, the encoder-decoder architecture is used, which allows to reduce noise propagation due to inexact predictions. To model the complexity of traffic flow, we employ multilayered architecture. Deeper neural networks are more difficult to train. To speed up the training process, we use skip-connections between each layer, so that each layer teaches only the residual function with respect to the previous layer outputs. The resulting neural network was trained on raw data from traffic flow detectors from the US highway system with a resolution of 5 minutes. 3 metrics: mean absolute error, mean relative error, mean-square error were used to estimate the quality of the prediction. It was found that for all metrics the proposed model achieved lower prediction error than previously published models, such as Vector Auto Regression, LSTM and Graph Convolution GRU.

The paper presents results of demand research for “park and ride” parking lots in the city of Kharkiv. The analysis of the previous research pertaining to demand for “park and ride” parking lots has been carried out in the paper. Disadvantages of the existing methods have been identified as well. A methodology in research on demand for “park and ride” demand for “park and ride” parking lots in the city of Kharkiv according to various characteristics. Distribution of traffic parking lots in the city of Kharkiv has been developed and it is based on modelling of transportation correspondence distribution on traffic networks and a questionnaire survey of car drivers. The obtained data have made it possible to segment the demand for drivers representing suburban areas according to frequency of visits to the city by private cars has been determined in the paper. Drivers’ satisfaction with their efficient movement through the city has been assessed in the paper. Segmentation of traffic demand in the places of possible locations for “park and ride” parking lots has been made according to urban transportation distance and on the basis of modelling distribution of transport correspondences. Quantity demanded for “park and ride” parking lots in the Kharkiv city in dependence to conditions for services has been calculated according to a questionnaire survey of car drivers. It has been established that conditions for parking services significantly determine the demand for “park and ride” parking lots. Analysis of segmentation results concerning the demand for “park and ride” parking lots has shown that under current condions demand for this type of parkings in Kharkiv is at rather low level and they are practically absent in case of 5 km urban transportation distance. Parameters demonstrating dependence of demand for “park and ride” parking lots on transportation distance through the city have beendetermined in the paper. The obtained results of the research are considered as initial data to study demand for “park and ride” parking lots.

The features of applying the theory of chaotic electrical impulse flows in mathematical modelling of traffic flows have been considered. Both the moments of appearance of vehicles on the traffic lane and the moments of appearance of electrical impulse on the time axis are supposed to obey the Poisson law. It is assumed that the duration of an impulse is equivalent to the length of a vehicle, and the intervals between the impulses are equivalent to the intervals between the vehicles in the spatial-temporal axis.

Study results of the human settlement influence on the traffic flow density in suburban service of international, national and regional roads of Ukraine are presented. The possibility of an adequate description of suburban traffic flows in the vicinity of large cities is established, depending on the city population and link remoteness from the city center. The possibility is determined on the basis of obtained models to define the prognosis value of the intensity and specific maintenance of freight and passenger transport flows.

The goal of this work is to generalize second order mathematical models for automotive flow using algorithm for building state equation - the dependency of pressure on traffic density - which is adequate with regard to real world data. The form of state equation, which closes the system of model equations, is obtained from experimental form of fundamental diagram - the dependency of traffic flow intensity on its density, and completely defines all properties of any phenomenological model. The proposed approach was verified using numerical experiments on typical traffic data, obtained from PeMS system (http://pems.dot.ca.gov/), using segment of I-507 highway in California, USA as model system.

The current systems and methods for automated traffic management in cities are analyzed. The management in cities is analyzed. The management levels are specified. There were fermulated the general requirements, objectives and funnctions of the automated sistems for traffic management with regard to the modern transport problems as well as proposed their aditional managemrnt and infor-maton functions. A phased approach to the implementation of projects on creation of automated sys-tems of traffic management is offered.

An analytical model for estimation of the bus departure delax from the bus stopping point after passenger loading is presented. The model allows to take into account the traffic density on a particular road section of the transport network, as well as the bus parameters.

The problem of application of miscroscopic traffic models for the analysis of large network segments is discussed with an example of discrete flow with safe distance. A concept of integral charasteristics of network segments is introduced, a method for obtaining such characteristics via microscopic traffic flow models is presented. Said method is applied to a circular unidirectional interchange, obtained characteristics analysed.

The technique and results of vehicles parking density law determination by the roadside that allowed to determine the rate of congestion in the central part of Kharkiv are presented.

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The assigned tasks of formalizing the process of forming additional sealings of traffic flows on approaches to the adjustable crossroads by the corresponding traffic light object operation in the adjustment mode, as well as by the corresponding traffic light object operation in the yellow blinking mode or at switched-off object are solved in the paper. Formulas for general corrected value of the amount of sealings on the approaches to the crossroads with traffic light adjustment during the day by the relevant traffic light operation modes and adjustment phases are obtained. The above allows quantitatively assess negative effects of sealings of traffic flows as a result of traffic light object operation. The results of the work allow further development of theoretical principals concerning evaluation and corresponding reduction of adverse effects during traffic light operation at the crossroads. Synthesis of kinematic criteria for evaluating traffic safety at respective crossroads is proposed. The criterion will allow to substantiate appropriate measures on improving traffic safety within the traffic light adjustment at the crossroads. [ABSTRACT FROM AUTHOR]

Based on the analysis of statistics of road traffic accidents in Ukraine at unregulated crossroads, the task on improving the methods for assessing the safety of unregulated crossroads taking into account qualitative accident rate indicators that characterize the severity of road traffic accidents was set in the paper. According to the analysis of the interaction between vehicles and pedestrians, the concepts of conflict area of interaction between traffic and pedestrian flows in the crossroad territory were introduced. Five specific interaction areas were identified. For the corresponding conflict areas in the crossroad territory, formalization of the specified interaction between vehicles and pedestrians at the level of the characteristics of the interaction process in time within the day was held. It was proposed to reflect the interaction using the law of conservation of energy. In this regard, energy characteristics of interaction between vehicles and pedestrians in the corresponding conflict areas were synthesized by the proposed five types of interaction between traffic and pedestrian flows. [ABSTRACT FROM AUTHOR]

An intensive increase in road transport, particularly individual, in recent years has led to such consequences as increased time spent on travel, the number of forced stops, traffic accidents, the occurrence of traffic jams on the road network, reducing traffic speed and a deteriorated urban road network in cities. The most effective method for solving these problems is the use of graph theory, the main characteristics of which is reliability, durability and accessibility of a free as well as loaded network. Based on their analysis the methods for network optimization are proposed. [ABSTRACT FROM AUTHOR]

General data on the network of Ukrainian highways are presented. The analysis of design methods of highway reconstruction based on the theory of traffic flows and economic calculations of its repay time is made. The relationship between traffic intensity and speed is shown by considering the theory of traffic flows. The methods, taking into account the principle of effectiveness of highway reconstruction based on its repay time, are discussed. [ABSTRACT FROM AUTHOR]

Recently, negative trends towards the environment where the system of Mass Passenger Public Transport (MPPT) operates continue to grow. Mobility and citizens' standard of living are constantly increasing. A significant increase in using private cars (level of motorization) along with all negative consequences faced under such circumstances as an increase in traffic volume, congestions, a decrease in travelling speed, a higher number of traffic accidents, greater negative influence on the environment etc. can be noticed. Th e city of Belgrade has recognized the significance of continuous research and has monitored the quality of Mass Passenger Public Transport service as well as changes that are taking place in order to influence some specific parts of transport and traffic policy in the city. Th is paper contains the benchmarking of results obtained in research and a trend towards changes in the expected and perceived quality of service (QoS) within the system of Mass Passenger Public Transport in Belgrade within the period from 2005 to 2007. [ABSTRACT FROM AUTHOR]

Traffic circles have been used in many countries all over the world. Traffic circles can be defined as intersections where traffic circulates around a center island where priority is given to the vehicles entering from branches and are designed considering weaving movements as the basic goal. Th ere are two most common capacity analysis methods for traffic circles: the method of critical gap acceptance and the method of regression analysis. Th is study explains the methods of gap acceptance and regression analysis. Ashworth and Field method is investigated and the applicability of these capacity models in Turkey is discussed. Th e obtained results have shown that both methodologies give satisfactory results; however, the existing methods should be improved (modified) considering conditions. [ABSTRACT FROM AUTHOR]

Intersections are the key components of road networks considerably aff ecting capacity. As fl ow levels and experience have increased over the years, methods and means have been developed to cope with growing demand for traffic at road junctions. Among various traffic control devices and techniques developed to cope with conflicting movements, traffic signals create artificial gaps to accommodate the impeded traffic streams. Th e majority of parameters that govern signalised intersection control and operations such as a degree of saturation, delays, queue lengths, the level of service etc. are very sensitive to saturation fl ow. Th erefore, it is essential to reliably evaluate saturation fl ow for correctly setting traffic signals to avoid unnecessary delays and conflicts. Generally, almost all guidelines support the constancy of saturation fl ow irrespective of green time duration. Th is paper presents the results of fi eld studies carried out to enable the performance of signalised intersections to be compared at diff erent green time durations. It was found that saturation fl ow decreased slightly with growing green time. Reduction corresponded to between 2 and 5 pcus/gh per second of green time. However, the analyses of the discharge rate during the successive time intervals of 6-seconds showed a substantial reduction of 10% to 13% in saturation fl ow levels aft er 36 seconds of green time compared to those relating to 6-36 seconds range. No reduction in saturation fl ow levels was detected at the sites where only green periods of 44 seconds or less were implemented. [ABSTRACT FROM AUTHOR]