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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Electric and hybrid vehicles are a big step towards a greener mobility, but they also open up completely new questions regarding the shortest path problem and the planning of trips. Since recharging an electric car will take much longer than refilling conventional fossil fuels, we have to balance between speed and range and we have to choose stops for charging wisely. For hybrid vehicles, a symbiosis between navigation system and power train control to choose a path with optimal phases for depleting and recharging the battery may yield much more energy-efficient paths. In this paper, we develop an appropriate model for finding shortest routes for these kinds of vehicles, which is mainly a constrained shortest path problem with convertible resources and charging stations. We study properties of solutions by classifying several types of cycles that may occur in the optimal route. We state sufficient conditions to exclude some of these cycle classes and we derive appropriate approximation schemes with provable quality and strict feasibility. We also study the related network flow problem for operating fleets of electric vehicles, e.g., shared vehicles or buses in urban areas. [ABSTRACT FROM AUTHOR]