Reduzieren robuste Fahrpläne Verspätungen in Stadtbahnnetzen? - Es kommt drauf an!

Nicht in jedem Stadtbahnnetz ist Robustheit als Optimierungskriterium für Fahrpläne gleich-sam geeignet. Im Rahmen dieses Beitrags werden deshalb Faktoren für die Netzstruktur bestimmt, die die Wirksamkeit von Robustheit als verspätungsmindernden Faktor beeinflus-sen. Anhand von Optimierungs- und Simulationsexperimenten auf Basis von Modellen der Stadtbahnnetze von Köln und Montpellier werden die definierten Einflussfaktoren getestet

Applicability of rescheduling strategies in tram networks

Highly utilized tram networks, where multiple lines share tracks and stations, are inevitably affected by dis-turbances during daily operation. While consequences of small, local perturbations may be counteracted by schedule characteristics, e.g. robustness, long lasting disturbances have to be addressed by dispatchers via schedule adjustments. Several methods for the identification and assessment of different rescheduling actions have been proposed. However, most of these methods have only been applied in railway networks. Therefore, in this paper we compare different rescheduling strategies and assess their applicability in tram networks. This paper begins with a description of possible rescheduling actions and the requirements and limitations to rescheduling strategies in tram networks. Different strategies for railway networks are then described and compared in regard to their applicability in tram networks

Model-based parallelization of discrete traffic simulation models

To re-establish regular operations in a tram traffic network after a large disturbance, e.g. resulting from vehicle breakdown or station closure, the viability of several rescheduling and rerouting strategies has to be evaluated prior to their implementation. Here, a multi-modal traffic simulation system can help to enhance the decision quality. Such a system obviously faces tight time constraints, so simulation data has to be acquired fast. In this paper we propose a method for the parallel execution of discrete traffic simulation models, which would accelerate data generation in comparison to a sequential model. To assess this method's dynamic behavior in real-world applications, some experiments conducted on a software system modeling schedule based tram traffic are presented. After giving an introduction to the scope and aim, we show some background on the parallelization of discrete simulation models. The main part of the paper begins with the proposal of a method to parallelize the execution of simulation models with problem specific properties. Some estimations of the method's efficiency are shared, followed by several experiments to highlight its dynamic behavior in real-world applications. The paper ends with a short summary and some thoughts on further research

Modeling time table based tram traffic

In mid-sized cities, tram networks are major components of public service infrastructure. In those networks with their typically dense schedules, multiple lines share tracks and stations, resulting in a dynamic system behavior and mounting delays following even small disruptions. Robustness is an important factor to keep delays from spreading through the network and to minimize average delays. This paper describes part of a project on simulation and optimization of tram schedules, namely the devel-opment and application of a simulation model representing a tram network and its assigned time table. We begin by describing the components of a tram network, which consist of physical and logical entities. These concepts are then integrated into a model of time table based tram traffic. We apply the resulting simulation software to our hometown Cologne's tram network and present some experimental results

Modeling time table based tram traffic

In mid-sized cities, tram networks are major components of public service infrastructure. In those networks with their typically dense schedules, multiple lines share tracks and stations, resulting in a dynamic system behavior and mounting delays following even small disruptions. Robustness is an important factor to keep delays from spreading through the network and to minimize average delays. This paper describes part of a project on simulation and optimization of tram schedules, namely the devel-opment and application of a simulation model representing a tram network and its assigned time table. We begin by describing the components of a tram network, which consist of physical and logical entities. These concepts are then integrated into a model of time table based tram traffic. We apply the resulting simulation software to our hometown Cologne's tram network and present some experimental results

A robust schedule for Montpellier's Tramway network

The city of Montpellier in the Languedoc-Roussillon region of France features a fast growing tram network as a central part of its public service infrastructure. Here, as in many other tram networks, resources like tracks and stations are shared between different lines. Because of the resulting dependencies, small inevitable delays can spread through the network and affect its global performance. Abstract This article examines whether a robust tram schedule may help to raise punctuality in Montpellier's tram network. To accomplish this, we apply a tool set designed to generate schedules optimized for robustness, which also satisfy given sets of planning requirements. These tools allow to compare time tables with respect to their punctuality and other key indicators. Abstract After an introduction to the goals of this paper, we continue with a description of the tool set focusing on optimization and simulation modules. These software utilities are then employed to generate and simulate robust and non-robust schedules for Montpellier's tram network, which are subsequently compared for the resulting delays