Traffic Signal Optimization Using Cyclically Expanded Networks

Traditionally, the coordination of multiple traffic signals and the traffic assignment problem in an urban street network are considered as two separate optimization problems. However, it is easy to see that the traffic assignment has an influence on the optimal signal coordination and, vice versa, a change in the signal coordination changes the optimal traffic assignment. In this paper we present a cyclically time-expanded network and a corresponding mixed integer linear programming formulation for simultaneously optimizing both the coordination of traffic signals and the traffic assignment in an urban street network. Although the new cyclically time-expanded network provides a model of both traffic and signals close to reality, it still has the advantage of a linear objective function. Using this model we compute optimized signal coordinations and traffic assignment on real-world street networks. To evaluate the practical relevance of the computed solutions we conduct extensive simulation experiments using two established traffic simulation tools that reveal the advantages of our model

Optimization and simulation of fixed-time traffic signal control in real-world applications

This paper contributes to the question how to optimize fixed-time traffic signal coordinations for real-world applications. Therefore, two models are combined: An analytically model that optimizes fixed-time plans based on a cyclically time-expanded network formulation, and a coevolutionary transport simulation that is able to evaluate the optimized fixed-time plans for large-scale realistic traffic situations. The coupling process of both models is discussed and applied to a real-world scenario. Steps that were necessary to align the models and improve the results are presented. The optimized fixed-time signals are compared to other signal approaches in the application. It is found, that they also help to improve the performance of actuated signal control

Adaptive traffic signal control for real-world scenarios in agent-based transport simulations

This study provides an open-source implementation of a decentralized, adaptive signal control algorithm in the agent-based transport simulation MATSim, which is applicable for large-scale real-world scenarios. The implementation is based on the algorithm proposed by Lämmer and Helbing (2008), which had promising results, but was not applicable to real-world scenarios in its published form. The algorithm is extended in this paper to cope with realistic situations like different lanes per signal, small periods of overload, phase combination of non-conflicting traffic, and minimum green times. Impacts and limitations of the adaptive signal control are analyzed for a real-world scenario and compared to a fixed-time and traffic-actuated signal control. It can be shown that delays significantly reduce and queue lengths are lower and more stable than with fixed-time signals. Another finding is that the adaptive signal control behaves like a fixed-time control in overload situations and, therefore, ensures system-wide stability

СОВРЕМЕННЫЕ МЕТОДЫ ОРГАНИЗАЦИИ ДОРОЖНОГО ДВИЖЕНИЯ В ГОРОДАХ

Optimum synchronization of traffic signals is an effective and efficient way to reduce traffic jam. The introduction of an automatic traffic light system creates a number of advantages compared to individual regulation at every crossroad. The Green Way System was developed to ensure continuous and safe movement of vehicles on motorways. In this paper, we present a comprehensive overview of the studies on various methods for calculating and optimizing “Green Waves”. The main goal of these methods is to reduce the number of stops and minimize travel time. The analyzed works were divided into several groups: the classical model, the use of cyclically expanded networks, modeling based on the MATLAB program, multi-agent systems.Оптимальная синхронизация сигналов светофора является эффективным и действенным способом уменьшения заторов на дорогах. Внедрение автоматической системы светофорного регулирования создает ряд преимуществ по сравнению с индивидуальным регулированием на каждом перекрестке. Система «Зеленая волна» была разработана с целью обеспечения непрерывного и безопасного перемещения транспортных средств на магистральных дорогах. В статье представлен всесторонний обзор исследований, посвященных различным методам расчета и оптимизации «зеленых волн». Основная цель этих методов заключается в уменьшении количества остановок и минимизации времени в пути. Проанализированные работы были разделены на несколько групп: классическая модель, использование циклически расширенных сетей, моделирование на основе программы MATLAB, многоагентные системы

The structure of user equilibria: Dynamic coevolutionary simulations vs. cyclically expanded networks

A variety of approaches exist that model traffic time-dependently. While all approaches have their advantages and disadvantages but have to find a balance between modeling traffic as realistic as possible and being still manageable in combinational terms. While transport simulations are efficient in evaluating user equilibria in large scale scenarios, their potential to be used for optimization is limited. On the other hand, analytical formulations like models based on cyclically time-expanded networks can be used to optimize traffic flow, but are not suitable for large scale scenarios. By optimizing the network structure in a mathematical model and evaluating its effect in a more realistic transport simulation, two models can benefit from each other. Detailed knowledge about model properties and differences in traffic flow behavior help to understand results and potential difficulties of such a model combination. In this paper, properties of two such models are compared regarding traffic flow modeling. It is shown that the set of user equilibria in both models and, therefore, the resulting route distributions can be structurally different