The article will present the usage of AIMSUN software for modeling of urban traffic at busy intersections in Sofia. Results from a case study concerning influence of tram stops on traffic will also be presented. The case study is aimed at modeling of four connected intersections that are controlled by traffic lights along Shipchenski prohod Blvd. in Sofia, Bulgaria. The hypothesis is that tram stops will affect traffic in a negative manner. However, it is more valuable to detect the extent of this influence as this may serve for the purposes of authority for making inform decisions about time tables of trams. The possibilities of AIMSUN software suit to measure various traffic indicators as well as indicators about the fuel consumption and air pollution were utilized in this study.

A city network of crossroad sections is under consideration in order to reduce the traffic jams, the traffic queue lengths in front of the junctions, and to increase the outgoing traffic flows. The implementation of these goals is achieved by application of hierarchical approach. A bi-level optimization is applied for finding the optimal control parameters as solutions of appropriate optimization problems, hierarchically interconnected. The numerical simulations’ results show improvement of the traffic’s characteristics.

This research addresses the problem of solving the Traveling Salesman Problem (TSP) with wide distributed software suit Excel. The TSP problem has long history and it belongs to a class of optimization problems, which is under continuous attempt for finding appropriate numerical algorithms for its solution. This research does not make attempts for new solution of this problem. The added value of the research is that it gives example how this problem can be solved with wide available software suit. A real problem of transportation in Sofia town is defined. The problem belongs to the class of TSP. It is illustrated how this problem is solved in Excel environment. Appropriate programming in Excel’s sheet and in software application Solver is given. This work provides pragmatically example for the definition and solution of TSP transportation problem.

The urban traffic in city areas lead to serious problems with traffic jams, air and noise pollution, social problems, etc. A solution for improving the urban traffic is proposed. A real distribution problem is formalized by mixed integer-linear programming problem. Instead of specialized software tools for optimization, open software available for any customer or manager is proposed here. The existing problem is modelled in Excel environment and solved by its application Solver. It is shown the uniqueness of modelling by its small modification leading to substantial decision making of the modified model. Both models lead to improving the traffic flows and decreasing the traffic routes according to the formalization of the tasks and received optimization solutions.

This paper describes the formalization of the store-and-forward model in bi-level optimization problem. The study finds the optimal duration of the cycle lengths by given green splits. The queues in front of traffic lights are minimized. Thus, the network allows higher throughput and less congestion with the resulting from this less pollution and better traffic indicators such as delay, density, speed, etc. The results for traffic indicators and pollution are obtained by Aimsun suit – a specialized traffic modelling software product. The optimization is performed by a MATLAB script based on an additional toolbox called YALMIP as well as with a state-of-the-art software product TRANSYT that is compatible with Aismun suit. Results show that it is reasonable to use the script for optimization of traffic as TRANSYT optimizes only green splits and offsets but works with the cycle value form Aimsun.

This paper describes the use of bi-level optimization as well as the well-known store-and-forward model for optimization of transport network. The following software products are applied: MATLAB with an additional tool box for modeling and optimization called YALMIP and Aimsun for modeling a microsimulation. Results show that using a specially developed script based on YALMIP in MATLAB improves the performance of the transport network. The results are measured in terms of traffic indicators in the specialized traffic software product Aimsun.

Increasingly, the management of real objects is using analytical methods such as mathematical modeling, statistical analysis and mathematical optimization to identify optimal solutions to complex decision-making problems [1]. Of the mathematical modeling approaches, linear programming is the most widely used. The criterion of model efficiency is a linear objective function that must be maximized or minimized, subject to certain constraints. distribution, transportation, personnel management, marketing and more. Linear programming tasks aim to achieve optimal allocation of limited resources when defining constraints. Resources can be raw, labor, machines, time, money, and constraints can be company costs or raw materials available. For many organizations it is crucial to ensure good planning and distribution of the workforce and thus reduce costs, achieve more efficient use of resources, fairer staffing. Transport companies are no exception. Transport service operators need to properly plan the number of drivers and the number of vehicles to meet their schedules. These two problems are well described in the literature and are known as the Vehicle Scheduling Problem (VSP), the Crew Scheduling Problem (CSP). The purpose of their solution is to minimize the cost of exposure to the use of vehicles and the salaries of drivers under operational restrictions on vehicles and labor regulations for drivers and to improve the quality of the service offered [2], [3],[4]. This problem is common and solved by transport companies operating in different countries, according to media publications it exists before Bulgarian public transport operations [5],[6]. This determines the need to solve a problem using the mathematical apparatus. And thus to propose a solution to a problem of public importance. In this paper resolves two sequential problems for optimal allocation of resources in a transportation system. Both tasks are examples of demand modeling. The first task is to search the number of tram-drivers in each shift required to complete the daily tram timetable. The second task looks for the number of employees for whom the work week starts from the relevant day, so that their total number is kept to a minimum. The branch and bound approach is used, which is constructed from a series of subproblems to solve mixed-integer linear programming problem. They are addressed systematically until the best solution to the underlying problem is found. Tasks are solved with Matlab using the intlinprog function. The remainder of the paper is organized as follows. The problem specific is described in Section 1. The mathematical modeling is given in Section 2. In Section 3 Algorithm and script for optimal distribution of Tram drivers are described. The computational results are presented in Section 4 and the paper is closed by the conclusions in Section 5.

The paper applies a bi-level modeling for traffic lights optimization. The bi-level modeling allows increasing the set of control influences, the number of constraints and applies two goal functions in hierarchical order. The bi-level formalism allows integration of small optimization problems in hierarchical order to a complex interconnected and complicated optimization problem. These features have been applied for optimal control of traffic lights in urban network. The bi-level problem formulation allows to minimize the queue lengths of vehicles and to maximize the outgoing flows from arterial direction. Both control influences of the green light durations and time cycles are evaluated as optimal bi-level control influences.

Integration of two different problems for the traffic management through hierarchical organization is presented. The problems are defined according to different physical models of the transportation flows: store-and- forward model and continuity of flows. The integration of these two optimization problems is performed by bi-level optimization. The benefit of this new formalization of the traffic management comes from the extended set of control parameters: the green light duration and the cycle of the traffic lights. Numerical experiments demonstrate improvements by minimization of the vehicles queue lengths and maximization of the outflow of arterial area in Sofia.

A new optimization model for urban traffic management is presented. The model formalizes traffic control by optimization both of green light durations and traffic lights cycles. Hierarchical bi-level approach is applied for definition of the both optimization problems of the two hierarchical levels. In that manner more than one criterion is applied and the optimization control space is extended. It is shown on numerical example that the bi-level optimization determines optimal values not only of the green light duration but of the traffic light cycles as well.

The rising number of people working and living in big cities around the world, many of which own a personal car, lead to a well-known social problem, namely, traffic congestions. Congestions occur when a large number of road traffic participants aim to use the very same infrastructure, while the latter has limited capacity. This situation entails a number of negative consequences, such as slow motion, economic losses, environmental pollution, safety problems and road accidents. The implementation of appropriate transport infrastructure management can make traffic more efficient, safer and greener. Traffic management in an urban environment is mainly realized through traffic light management. It is an integral part of the intelligent transport system (ITS), which is essential for facilitating traffic congestion. Poor traffic management and inefficient settings at signalized intersections cause many problems such as excessive delays for vehicles, increased fuel consumption and CO2 emissions generated by transport means. The efficiency of signalized intersections can be significantly improved by optimizing phase duration and synchronizing traffic lights using intelligent traffic management methods. For this reason, the paper demonstrates the use of function fmincon in environment Matlab for improving the level of service (LOS) in intersection by optimizing the phase length and cycle of network of four consecutive traffic lights. The average weighted controlled vehicle delay at the intersection is the indicator for assessing the effectiveness of the objective function. The results of the study show that the calculated values for delays for passing through intersections have decreased.

С увеличаването на трафика от придвижването на автомобили, хора и стоки значително нараснаха усилията за събиране и обработка на данни от служители на заинтересованите звена, отдели и учреждения. Това налага по-засилена употреба на статистически методи, за да се улеснят и прецизират анализите, особено в градска среда. Събирането на данни е процес на набиране и измерване на информация за променливи, по установен систематичен начин, който дава възможност на изследователя да отговори на зададени въпроси на изследването, да провери хипотези и да оцени резултатите [1]. Има три различни техники за събиране на данни за интелигентен транспорт локални сензори (Site based data collection), мобилни технологии (Floating Car data) и Сателитни технологии (Wide area data collection) [2,3]. Понеже за събиране на данни в изследването не могат да се използват информационни и комуникационни технологии, то се ограничава до подхода ръчното измерване. Събираните данни за потока на трафика и изготвянето на прогнози за бъдещите му стойности са от съществено значение при планиране развитието на пътната инфраструктура и управлението на пътища. Освен това те позволяват да се опише основен отрасъл от националната икономика – транспорта, и са важни при изготвяне на ефективни политики за движението на пътници и стоки от страна на фирми и правителства [4,5,6]. Въпреки сложността на измерваните данни, те могат да се използват за изграждане на ясно дефинирани модели, които да се класифицират и анализират. Моделите позволяват да се проследят тенденции, да се направи оценка на трафика и да се реализира управление съобразено с пътната обстановка. Чрез реализиране на последното ще се увеличи ефективността на пътищата, ще се намали трафикът в даден участък, ще се увеличат приходите от използването на пътната инфраструктура, ще се прецизират мерките за пътна безопасност и др. Анализът на данните се различава значително в зависимост от обхвата и целите на проучването. Така например, най-елементарният подход е да се определи броят на превозните средства от всяка категория, а по-сложните подходи изискват да се реализира компютърен анализ на трафика, на пътувания, да се определи разпределението на натоварване на пътната мрежа или да се изготви прогноза за промяната на трафика и др. В настоящата статия се представя off-line анализ на реално измерени данни, в който се проверява тяхното разпределение и доверителен интервал. Данните касаят автомобили, преминали през пропускателен пункт в интервал от 40 минути в силно натоварен времеви интервал по време на празнични дни. Методът за преброяване на автомобилите е т. нар. ръчното измерване. Получените данни се въвеждат в програмен продукт MS Excel, след което се преобразуват, систематизират и оценяват като се извършва проверка на хипотеза за тяхното разпределение и се определя 95 % доверителен интервал на пристигането на два последователни автомобила.

The rising number of people working and living in big cities around the world, many of which own a personal car, lead to a well-known social problem, namely, traffic congestions. Congestions occur when a large number of road traffic participants aim to use the very same infrastructure, while the latter has limited capacity. This situation entails a number of negative consequences, such as slow motion, economic losses, environmental pollution, safety problems and road accidents. The implementation of appropriate transport infrastructure management can make traffic more efficient, safer and greener.Traffic management in an urban environment is mainly realized through traffic light management. It is an integral part of the intelligent transport system (ITS), which is essential for facilitating traffic congestion. Poor traffic management and inefficient settings at signalized intersections cause many problems such as excessive delays for vehicles, increased fuel consumption and CO2 emissions generated by transport means. The efficiency of signalized intersections can be significantly improved by optimizing phase duration and synchronizing traffic lights using intelligent traffic management methods. For this reason, the paper demonstrates the use of the built-in Excel GRG Nonlinear Multi-start application for improving the level of service (LOS) in intersection by optimizing the phase length and cycle of two isolated traffic lights. The average weighted controlled vehicle delay at the intersection is the indicator for assessing the effectiveness of the objective function. The results of the study show that the calculated values for delays for passing through intersections have decreased.

The research aims to make a topological synthesis through modeling and management of information flows and to offer an optimal solution for distributed connectivity of a designed network. The network can be in the field of communication, transportation or information systems. At the basis of the research is the development of model for quantitative assessment of the quality, continuity and fault tolerance of the service with a view to technological and structural optimization of the communication network. Основният проблем, обсъден в тази статия, е да се открие най-краткият път от даден възел до останалите възли в мрежата. Освен това представените графи позволяват да се анализират някои информационни модели и комуникационни потоци. Предложен е алгоритъм за изчисляване на теоретичните закъснения между възлите на допълнителните алтернативни комуникационни канали. Характеристиките на задачата за оптимизация, която трябва да бъде определена и решена, включват комуникационна мрежа с 12 възeла и структура от 2, 3 или 4 свързани елемента. За да се подобри съществуващата мрежа и да се получат непрекъснати информационни потоци, в статията са представени два модела и резултатите се оценяват количествено. За да се изведе оптималната структура на комуникационната мрежа се прилага топологичен синтез и се избира най-добрият модел със съответно параметрично състояние. Резултатите от това изследване могат да бъдат полезни за контрол на транспортните системи чрез намиране на най-интензивните трасета, следвайки моделирането на най-краткия път; за изчисляване на параметъра време за пътуване по различни маршрути, което е важен фактор при проблемите с контрола на транспорта; възможно е да се планират допълнителни маршрути между две точки в схемата за градски транспорт в случаи на социални събития като демонстрации.

This paper tackles the problem of on-street parking and the quantification of its effects for a network of four signalized intersections. The network has a key location regarding the access to the center of the city and back to the suburb neighborhoods. The intersections are situated along Shipchenski prohod Blvd. The evaluation is performed through microsimulation in the software product AIMSUN.

В монографията са дефинирани и са представени основни параметри и модели, прилагани при управление на транспортни системи. Коментирани са критерии за оптимално управление на транспротни системи, с което се постига познавателно значение за обекта „транспортна система“ и аналиттично са изследвани формалните зависимости и модели, прилагани при управление на транспортни системи. Представени са проблемите за измерване на параметри за интензивността на трафика в транспортна среда. Предпочитанията са насочени към средства за обработка на изображения, чрез които се идентифицират свойства на транспортни средства, както и за оценкка на интегрални параметри на транспортната динамикка. Направено е аналитично представяне на технически средства, които имат приложение при изграждане на устройства за следене и анализ на транспортни параметри, базирани на програмируеми матрици. Това са сложни технически компоненти, притежаващи висока функционалност, която успешно може да решава проблеми по идентификация в реално време на параметри от динамиката на транспортни системи. Представени са средства за тяхното проектиране. Експериментите по управление и симулация на транспортни системи са представени като технически решения, които имат приложение при изграждане на прибори, предназначени за идентифициране и измерване на транспортни параметри. Съобразността на проектираните прибори е илюстрирана с диаграми и оценки от тяхното функциониране. Представени са резултати от съвместно прилагане на проектираните уреди и симулационни програмни среди за сравнение и настройка на техническите средства за имерване на транспортната динамика.

The urban traffic in city areas leads to serious problems with traffic jams, air and noise pollution, social problems, etc. The chapter presents the solutions of two important transportation problems: distribution of goods and traveling salesman problems, applied in urban area. The solution of such problems leads to improvement of the management of the transportation services. The distribution problem is formalized by mixed integer-linear programming problem. The Traveling Salesman Problem (TSP) has long history for the design of appropriate numerical algorithms for its solution. It belongs to a class of combinatorial optimization problems, which insist considerable computational workload for solution. The added value of the research is that it gives examples how these two problems can be solved by wide available software suit. Real problems of transportation in Sofia city are defined. It is illustrated how these problems are solved in Excel environment. Appropriate programming of the Excel’s sheet and the software application Solver is given. This work provides pragmatically examples for the definition of transportation problem for distribution of goods and TSP one and their solutions.

The urban traffic control optimization is a complex problem because of the interconnections among the junctions and the dynamical behavior of the traffic flows. Optimization with one control variable in the literature is presented. In this research optimization model consisting of two control variables is developed. Hierarchical bi-level methodology is proposed for realization of integrated optimal control. The urban traffic management is implemented by simultaneously control of traffic light cycles and green light durations of the traffic lights of urban network of crossroads.

The control object is the urban traffic of network of eight crossroad sections as a part of density populated area in Sofia. The goal is minimization of vehicle queue lengths in front of the junctions, which leads to faster driving, better ecological picture and reducing the air and noise pollution. The paper analyzes two types of modelling and optimizations, applied for the traffic control: classical optimization (one-level) and bi-level one. The bi-level optimization has the priority to co-ordinate the two-level hierarchical problem and to take into account the interconnections between the crossroad sections. It contains two goal functions, which are considered for the control process. The bi-level and classical one-level linear-quadratic optimization are numerically applied for the traffic light control of urban network. The comparison gives preferences to the bi-level optimization, confirmed by numerical simulations.

An application of information technologies support for traffic lights control is presented. The control task is formalized as a bi-level hierarchical problem solved in MATLAB environment. The traffic lights control is applied for a network of eight crossroads in urban area in Sofia. The optimal problem is numerically tested with traffic intensity data and graphical interpretations are given. Comparison with the classical optimization control problem gives benefits for the bi-level optimization model.

Traffic congestions are a problem in large cities. They lead to many negative consequences in the fields of economic, environment and health. Proper adjustment of traffic light settings in urban environments is the main means of control over the stated problems. This paper investigates a network of crossroads situated in central Rome in the area Municipo V. The study presented in this paper offers alternative approaches to optimization of signal timings of traffic lights in the network. Comparison is made between the current settings, the Buyanov et al optimization approach, the nonlinear optimization approach and the bi-level optimization approach. Signal timings for the current settings and for the three optimization approaches are imported in the traffic simulation software suit Aimsun and the output results of the four simulations are compared. The analysis and evaluation of the output date gives advantage to the nonlinear approach followed by the bi-level optimization approach as far as different traffic indicators are concerned e.g., delay, flow, speed, queue etc. The effectiveness of the used optimization methodologies is graphically presented.

This paper presents an initial study addressing infrastructure change and its evaluation through microsimulation via the software Aimsun. The infrastructure is a T-junction that is proposed to be replaced with a roundabout. The final outcome shows that the higher the traffic demand, the bigger the difference in traffic indicators between the two cases. Although, the absolute values for Total Travel Time are in favor of the current T-junction more research will be needed.

The paper describes the design and implementation of a heuristic fuzzy controller for traffic management in urban areas. The controller uses expert knowledge for the derivation of its fuzzy rules. The proposed controller is simulated and compared to a conventional proportional controller by means of the software platform for traffic management AIMSUN.

A bi-level model for traffic signal optimization is developed. The model predictive framework is applied for traffic control in an urban traffic network. The potential of the bi-level formalization is used to increase the space of control influences with simultaneous evaluation of the green light and cycle durations. Thus, the increased control space allows more traffic parameters to be considered, such as vehicles queues and traffic flows. A particular modification of the bi-level control is applied for the synchronization of the traffic lights in the network. The model predictive approach is used for the real-time management of the traffic in the network. The control implementations are constrained by the shortest evaluated cycle. Thus, a synchronization of the traffic lights is applied for the minimization of the queues and maximization of the outgoing flows from the network. The bi-level model has been numerically tested on a set of intensive crossroads in Sofia. The numerical simulations prove the superiority of the developed bi-level control in comparison with the classical optimization of queue lengths.

The goal of this research is to improve the traffic behavior at crossroads of the urban network by decreasing the waiting vehicles in the network. This goal is achieved through bi-level optimization, which has significant advantages compared to classical optimization. The added value in this research is the analytical formalization of the optimization problem. The problem gives superiority to the values of the outgoing flows in comparison with the incoming traffic flow in each direction of the network, which results in the decrease of waiting vehicles. The research applies control rules of predictive control at each traffic light cycle by the bi-level optimization methodology. This enables additional adaptation of the green light and cycle durations to the traffic flows. The bi-level solutions are numerically evaluated and compared with the classical (one-criterion) optimization. The comparison demonstrates the advantages of bi-level optimization.

Bi-level optimization model with two control variables-green light duration and cycle durations is developed in order to decrease the queue lengths of vehicles at crossroads. A comparison of the bi-level solutions with a one-criterion optimization problem is done. An assessment of the comparison is presented giving an advantage to the bi-level optimization model.

The ship management in collision avoidance is important task, which is a prerequisite for unmanned automation of maritime transportation. The formal, quantified modeling of the needed path changes is a vitally needed to provide safe management of the ship and to provide secure policy in collision avoidance. A second criterion coming from cost reduction of the ship exploitation and environment protection matter is related with fuel consumption in path planning. This research develops a formal model which targets simultaneously goals for safe avoidance of collision in a faster way and also to minimize the fuel consumption. These both targets are formalized by bi-level optimization. The research presents this bi-level model which is implemented in optimization problem. The results from numerical simulations prove close results with the ship simulator and give evidences for efficiency of ship management and path planning.

Представена е формализация на управление на градски трафик в мрежа от четири кръстовища. Цел на изследването е намаляване на опашките от коли пред светофарите и увеличаване на изходящия поток коли от всяко кръстовище в мрежата. Методологията, използвана за формализация, е двунивовата йерархична оптимизация. Тя осъществява интегриране и координация на повече целеви функции, ограничения и променливи при оптимизацията. Това позволява по-голяма близост между разработения модел и реалността. Определени са задачите от двете йерархични нива. За синхронизиране на трафика в мрежата е използвана допълнителна техника, заложена в оптимизационния алгоритъм. Представените числени резултати от симулациите са сравнени с решенията на класическа нелинейна задача (едно-нивова задача). От сравнението следва предпочитание на двунивовата оптимизация.

The main instrument for urban traffic control is the traffic light settings, which is applied in this research in order to improve the traffic dynamics. The goal is to develop a model for urban traffic control with bigger outgoing traffic flows than ingoing ones in order to be decreased the vehicle queues at crossroads. As a difference from the usual practice of using only one control influence of the traffic light settings, here two control settings – traffic light cycles and green light durations are implemented as control influences of an arterial network of five crossroads. The implementation of this approach is on the basis of the bi-level optimization methodology. It integrates two goal functions (of both hierarchical levels), more variables and constraints in comparison with the one-level optimization. The optimization problems of the bi-level optimization have been defined. The bi-level solutions have been compared with the one-level optimization ones. The numerical simulations give preference to bi-level optimization.

A formal model of urban traffic management in a network of four intersections is developed. The aim of the study is to reduce the queues of cars in front of traffic lights and increase the outflow of cars from each intersection in the network. The methodology used for the formalization is the application of bi-level optimization. It integrates and coordinates more goal functions, constraints, and optimization variables. This allows greater closeness between the developed model and reality. For the bi-level model, the optimization problems for the two hierarchical levels are defined. An additional logical modification is applied in the optimization algorithm. It allows synchronizing the traffic control in the network. The presented numerical results of the simulations are compared with the solutions of a classical nonlinear problem (one-level problem). The comparisons give preferences to the bi-level optimization.

Appropriate on-street parking management strategies and measures can often solve the problem by shifting demand from on-street to off-street and will be much cheaper than increasing supply. Solving traffic and parking problems in the city center requires not only measures on parking but also a strategy on the future street network and the structure and use of public transport, to achieve this a mathematical model has been developed to solve an optimization problem. The results of which will show which streets are traversed to reach off-street parking and which streets are not used and parking can be allowed. In this paper a model is designed where an appropriate optimization problem is defined and solved. The solutions are optimal according to the defined and solved optimization problem.

The paper describes the design and implementation of a fuzzy controller for traffic network management in urban areas. The controller uses expert knowledge for the derivation of its fuzzy rules. The proposed controller is simulated and compared to a conventional proportional controller by means of the software platform for traffic management AIMSUN. The results show that the fuzzy controller outperforms the proportional controller.

The paper works out a mathematical model for urban traffic control on a network of five crossroads. The goal of the research is simultaneous optimization of green light and cycle duration giving priority to one direction. The bi-level hierarchical optimization is the applied formalization methodology. The optimization problems of both hierarchical levels are derived. The bi-level optimal results are compared with those from classical one-level optimization problem. The influence of the model's parameters is analyzed.

One of the major problems in modern cities is the heavy street traffic which can be a significant problem even for the emergency vehicles like ambulances and fire brigades. The present paper provides a brief description of the existing technology means for traffic management. By means of contemporary technologies, an appropriate solution for providing a priority passing of the special vehicles can be created. The paper aims to offer an algorithm for the fast movement of emergency vehicles in conditions of heavy road traffic. The presented smart traffic management system implements several nowadays technologies such as a cloud-based control center, image processing, and GPS tracking and navigation. The conceptions of data traffic management and cloud-based control center are explained, and the advantages of replacing the RFID tags with smart technologies are presented.

The control object is the urban traffic of network of eight crossroad sections as a part of density populated area in Sofia. The goal is minimization of vehicle queue lengths in front of the junctions, which leads to faster driving, reducing the air and noise pollution and better ecological picture. The paper analyzes two types of modeling and optimizations, applied for the traffic control: classical optimization (one-level) and bi-level one. The bi-level optimization has the priority to co-ordinate the two-level hierarchical problem and to take into account the interconnections between the crossroad sections. It contains two goal functions, which are considered for the control process. The bi-level and classical one-level linear-quadratic optimizations are numerically applied for the traffic light control of urban network. The comparison gives preferences to the bi-level optimization, confirmed by numerical simulations.

Evaluating future transport infrastructure projects is a challenge as it requires predicting future traffic demand and tendencies in social-economic development. It also requires monetization of factors such as road accidents, air pollution and noise. This paper aimed at presenting the role of traffic simulation software for the evaluation of future infrastructure projects as well as the role of the software in the process of cost-benefit analysis. In this regard, the role of the traffic software at each stage was presented and a conceptual model was developed as a diagram in this paper.

Traffic patterns in urban areas present a complex and dynamic system that is characterized by inherent uncertainties. The presented study is a traffic light control system with feedback. The controller of the system is designed in a fuzzy and conventional way and is applied to a network of two junctions. The verification is performed using the MATLAB fuzzy toolbox platform (for designing the fuzzy controller) and Aimsun platform for microsimulation of the two junctions using the two types of controllers. To accomplish the control of the system a fuzzy controller on heuristic rules proposed to allow adaptive traffic control on signalized junctions in urban environments. The Fuzzy Toolbox in MATLAB is used to simulate the fuzzy controller. The Aimsun traffic simulator is used to model and simulate a traffic network of two intersections. The green light duration in the Aimsun model is based on the results for the two controllers from two separated experiments. Simulations of Aimsun models with the two types of controllers, the fuzzy and the conventional one, are compared. The experiment is performed under the premise that the traffic flow is oversaturated. Findings show that in a network of two junctions both controllers perform in a similar manner for the first junction. However, for the second junction, the fuzzy controller tends to have some advantages over the conventional controller with regard to higher traffic flow. In conclusion, the overall performance of the fuzzy controller is better than the one of the conventional controller, but further research is needed for more complex traffic networks.

An optimization model for traffic light control in an urban network of intersections is derived. The model is based on store-and-forward analytic relations, which account for the length of the queue of waiting vehicles in front of the traffic light intersection. The model is complicated with probabilistic relations that formalize the requirements for maintaining short queues of vehicles. Probabilistic inequalities apply to each intersection of the city network. Approximations of probability inequalities are given in the article. Quadratic deterministic inequalities, which are part of the set of the traffic flow control optimization problem, are derived. Numerical simulations are performed, applying mean estimated data for real traffic in an urban area of Sofia. The model predictive approach is applied to traffic light optimization and control. Empirical results give advantages of the obtained model compared to the classical store-and-forward optimization model for the total number of vehicles waiting in the considered urban network.

In the presented study, a mathematical model is developed to estimate the potential for passenger transport to be implemented jointly with rail and bus transport. One of the perspective destinations of the Republican transport scheme is selected: Sofia-Varna. The mathematical model is presented with the timetable of passenger transport performed jointly by rail and road. An exploratory concept is applied to determine the maximum passenger flow in a highly interconnected network. Finding the maximum flow is accomplished with a mathematical problem that uses the law of conservation of continuity of flow. The research aims to find what is the maximum value of the flow of the transport graph between Sofia to Varna that can be transported jointly by rail and bus. The maximum flow consists of a set of individual "streams" that start from Sofia, pass through different routes in the transport graph and converge at the end point of Varna. Varna. The study aims to determine the relative value of this flow and the arcs in the transport graph through which it passes. Using the MATLAB software product, a twohierarchy problem is solved to determine the maximum flow and the arcs through which it passes, looking for a new graph structure that implements the calculated maximum flow but with a smaller number of arcs.

The aim of this experiment was to apply bi-level optimization based on constraints coming from store-and-forward model and to test the resulting values for the duration of the green lights via a microsimulation. For the aim of this study two models were designed. The first model is based on bi-level optimization and the second model is the microsimulation in the traffic simulation software Aimsun. The results of the first model were calculated through a Python-based package named PAO and a solver. The optimized values for the duration of the green light were then entered in the Aimsun microsimulation model and tested with different traffic flows. The results show that the bi-level optimization may be reliable and fast model for a small network as the investigate one. However, additional testing with simulation software reveals some weaknesses as e.g. the bi-level optimization tasks lead to zero queues in front of traffic lights, but the software simulator shows approximately 20 vehicles mean queue for the network.

The main tool for reducing queues in front of intersections in populated areas is through the appropriate setting of traffic lights. Traffic management is difficult due to the stochastic behavior of the traffic. Vehicles dynamics are formalized by the constraints of the developed traffic light control optimization model. This study applies to constraints the relations derived from the well-known “Store-and-forward” modeling, modified in the paper by adding probabilistic relations reflecting the stochastic traffic behavior. The model is validated through numerical experiments. The solutions of the modified optimization problem are compared with the solutions of the corresponding deterministic nonlinear optimization problem. The comparison gives advantage to the modified problem because it accounts for realistic constraints on the capacity of urban network sections.

The main control tool for traffic management in urban areas is traffic light settings. The goal is to decrease the queue lengths at intersections. Usually, the duration of the green light of the traffic light is used for control. The control approach is based on the so-called “store-and-forward” model. However, this model does not reflect the stochastic nature of traffic dynamics. This study presents a model with some probabilistic conditions approximating real traffic behavior. An additional contribution concerns the definition of a bi-level optimization model that simultaneously optimizes the green light and traffic light cycle duration of an urban network of four intersections. Three traffic management optimization problems are defined and solved. Their solutions are graphically illustrated and commented on. Bi-level optimization outperforms by giving lower values of queue lengths compared to classical and stochastic nonlinear optimization problems in the considered network.

The store-and-forward traffic model is widely used because of its simplicity and reasonable comprehension. Its results determine the duration of the green light according to a preset cycle. This paper builds further on the currently existing model: it expands the definitional domain of the optimization problem by adding additional probabilistic requirements regarding the number of vehicles in a street segment between intersections controlled by traffic lights. The defined optimization problem minimizes the probability of increasing the number of vehicles in the considered transport network. A further extension of the store-and-forward model allows the control domain to contain both green lights and cycle durations. Such optimal control allows the achievement of additional objective functions such as minimizing the number of vehicles in the network and minimizing the total time spent through the network. The definition of this control problem is done through a bi-level hierarchical formalization involving the store-and-forward model. The derived extended models are numerically tested and compared with real cases, giving preference to the derived extensions of the classical store-and-forward model.

This study presents design of traffic light system with feedback control that considers a crossroad in an urban area. Two types of controllers are designed – fuzzy and analytical, which have been tested separately on Aimsun platform through a simulation. The aim of the study is to compare the performance of both controllers in terms of increasing traffic flow and decreasing queue length. The controllers manage the duration of the green light according to the traffic flow. Two different formal models are designed, tested, and compared. They have produced adequate solutions in terms of developing controllers for modeling and simulation of transportation tasks.

The modeling the traffic dynamics in urban areas is mainly based on the so-called “store-and-forward” model. This model was used to model the number of vehicles on the streets of a network of four intersections. The nonlinear optimization model has variables green light duration and number of vehicles in front of the traffic light. The constraints of the optimization problem consist of a store-and-forward model that formalizes the number of vehicles in the street section. But store-and-forward modelling does not provide adequate modeling for the real traffic behavior. In this paper, the optimization model is modified to be closer to the real traffic dynamics. The solutions of the classic store-and forward model and the modified ones are compared and graphically illustrated and commented.

This paper focuses primarily on parking in the town of Sozopol, where there are major parking problems. In this regard, the parking idea offers a framework for addressing parking issues as well as guidance for particular activities to address the parking issue. An appropriate optimization problem has been defined and solved in a model that has been built to design the transport plan. According to the outlined and resolved optimization challenges, the solutions thus acquired for the transport plan are the best. The allocation of major traffic flows is shown in this paper's transportation plan. It determines parking places in the city of Sozopol while evaluating the transport plan's existing capacity. Almost all vehicle trips finish with a parking spot. Parking management typically does not involve substantial investments, such as new roads or increased public transportation, and can therefore be implemented in a very short amount of time. Additionally, almost all major cities in Europe have some type of parking management. Because of this, parking management is far more popular with the general public than innovative approaches to controlling automobile use, including congestion pricing programs.

Different approaches exist related to mitigation of traffic pollution. This research focuses on the signal timing traffic management policies and their impact on air pollution. A software simulation with the traffic software simulators AIMSUN and TRANSYT was performed. AIMSUN uses the environmental model of Panis et al., 2006. A microscopic traffic simulation model to evaluate the environmental effects of the application of different signal timing policies was used. A network of four connected junctions along Shipchenski Prohod Blvd. in Sofia was simulated. The experiments lead to the conclusion that traffic pollution can be influenced by changes in signal timing policies.

The research goal of the presented experiment was to test if the current control plan can be improved through analytical modeling of the traffic by defining a bi-level problem and dynamically simulating the existing control plan and solving the analytical model. The comparison is done by queue lengths in an urban network of crossroads. Two models were developed for this purpose – a python-based package, named PAO and a solver were used for definition and solution of a bi-level optimization model and a microsimulation model was developed to test the results in a simulation environment named Aimsun. The results showed that the bilevel optimization led to better settings for the duration of green light but it also revealed that the originally measured settings provide good performance of the investigated traffic network.