Jörg Dallmeyer

Don't Go With the Ant Flow: Ant-Inspired Traffic Routing in Urban Environments

Traffic routing is a well-established optimization problem in traffic management. Here, we address dynamic routing problems where the load of roads is taken into account dynamically, aiming at the optimization of required travel times. We investigate ant-based algorithms that can handle dynamic routing problems, but suffer from negative emergent effects like road congestions. These negative effects are inherent in the design of ant-based algorithms. In this article we propose an inverse ant-based routing algorithm to (a) maintain the positive features of ant-based algorithms for dynamic routing problems, while (b) avoiding the occurrence of negative emerging effects, like road congestion. We evaluated the performance of the proposed algorithm by comparing its results with two alternative routing algorithms, namely, A*, which is a static routing algorithm, and an iterative approach. In particular, the iterative approach is used for providing an upper bound, as it uses routing knowledge in a number of calibration runs, to determine the actual load, before the effective routing is done. For the evaluation we used the agent-based traffic simulation system MAINSIM. The evaluation was done with one synthetic and two real-world scenarios, to outline the practical relevance of our findings. Based on these evaluations, we can conclude that the inverse ant-based routing approach is particularly suited for a scenario with a high traffic density, as it can adapt the routing of each vehicle, while avoiding the negative emerging effects of conventional ant-based routing algorithms.

Learning dynamic adaptation strategies in agent-based traffic simulation experiments

The increase of road users and traffic load has lead to the situation that in some regions road capacities appear to be exceeded regularly. Although there is natural capacity limit of roads, there exist potentials for a dynamic adaptation of road usage. Finding out about useful rules for dynamic adaptations of traffic rules is a costly and time consuming effort if performed in the real world. In this paper, we introduce an agent-based traffic simulation model and present an approach to learning dynamic adaptation rules in traffic scenarios based on supervised learning from simulation data. For evaluation, we apply our approach to synthetic traffic scenarios. Initial results show the feasibility of the approach and indicate that learned dynamic adaptation strategies can lead to an improvement w.r.t. the average velocity in our scenarios.

GIS-Based Traffic Simulation Using OSM

This chapter demonstrates how to build up a traffic simulation on the base of a Geographic Information System (GIS). Maps from the OpenStreetMap (OSM) initiative have shown to be appropriate for usage in this field. Essential steps from OSM over GIS to a graph data structure for use in traffic simulation are described. The work is done with the focus on urban scenarios. The crucial decision, which types of road users to integrate into a simulation and how to model them, is discussed. A case scenario shows the utility of data mining techniques in the field of traffic simulation. The scenario aims at predicting traffic jams in the city of Frankfurt am Main with help of a learned classifier. Our results show that taking into account simple and partial information about the traffic situation can lead to a huge gain of knowledge when using data mining techniques in the face of predicting of traffic situations.

Approximation Of Pedestrian Effects In Urban Traffic Simulation By Distribution Fitting.

For a proper simulation of urban traffic scenarios, besides cars other road users, namely bicycles and pedestrians, have to be modeled. In scenarios where a whole city is modeled, a detailed actor-based simulation of pedestrians leads to expensive extra computational load. We investigate to what extent it is possible to capture traffic effects imposed by simulated pedestrians and then perform simulations without pedestrians. We propose to collect information about pedestrian impacts in a simulation with pedestrians, estimate underlying probability distributions and finally, use a simplified model where only these effects are generated probabilistically. We investigate two approaches – a best-fit distribution fitting and a histogram-based distribution approximation – using synthetic data as well as simulated traffic scenarios. The experiments show that using the proposed approximations can lead to similar average cars’ travel times.

Wind und Wetter

Eine Emissionskarte, wie in Abbildung 14.5 gezeigt, gibt Aufschluss uber die Verteilung der Emissionsmengen, die von Autos im Messbereich ausgestosen wurden. Es ist jedoch anzunehmen, dass das Wetter einen Einfluss auf die Verteilung der Emissionen hat. MAINSIM wird daher in diesem Kapitel an die atmospharische Simulation SCIPUFF (Second-order Closure Integrated PUFF Model) [Sykes und Gabruk, 1997, Sykes et al., 1984] gekoppelt. Es werden zur Tripgenerierung QZM von Hessen Mobil genutzt. Abbildung 15.1 zeigt den Simulationsbereich. Zur Verdeutlichung der Grose des Szenarios wurden die ungefahren Umrisse der Stadte Hanau und Erlensee aufgezeigt, die im Rahmen dieser Arbeit bereits zur Simulation verwendet wurden.

Selfish road users --- case studies on rule breaking agents for traffic simulation

Many studies in the context of traffic simulation investigate effects of new regulation strategies on travel times. However, in most cases it is assumed, that these regulations are followed by all actors. This work investigates the effects of non-compliance of simulated road user agents. In particular it is analyzed to what extent rule breaking agents have advantages on the cost of the remaining road users. For evaluation we take into account three different scenarios: Overtaking prohibition for trucks on motorways, bicycles pushing to the front at traffic lights and pedestrians crossing roads in aggressive manner. In all scenarios, the fraction of rule breaking agents is varied. Simulation results show that rule breaking does not always lead to disadvantages for the remaining road users.

Coupling Traffic and Gas Dispersion Simulation for Atmospheric Pollution Estimation

A CyberGIS approach is presented in this chapter where microscopic traffic simulation and gas dispersion simulation systems are combined in order to estimate atmospheric pollution for different scenarios. The combination of these two simulation models allows for detailed investigations of different situations such as the investigation of pollution impacts of different traffic infrastructure variants, as well as for prediction of expected pollution and whether pollutant thresholds will be exceeded. For different case studies, real data about traffic movements provided by the state government, a digital terrain model of the area as well as real measurements of atmospheric data have been used. The evaluation of the approach shows that variations in the settings, regarding traffic or atmospheric conditions, lead to different patterns of observed pollution. The CyberGIS environment described is used to run multiple simulations on a distributed cyberinfrastructure, where the high-end computational resources are available on servers in Europe and in North America.

Akteursorientierte multimodale Straßenverkehrssimulation

Keines der im Stand der Forschung betrachteten Verkehrssimulationssysteme erfullt die im Abschnitt 1.4 gestellten Anforderungen vollstandig. Es muss daher gepruft werden, ob die Erweiterung eines bestehenden Systems zur Erfullung der Anforderungen oder die Entwicklung eines neuen Konzepts mit vollstandiger Implementierung eines Simulationssystems durchgefuhrt werden muss.

Approximation von Fußgängereffekten

In dieser Studie wird versucht, die Effekte nachzubilden, die Fusganger auf den Strasenverkehr haben. Dies hat zwei Ziele: Zum einen kann Simulationszeit eingespart werden, wenn Fusganger nicht mehr simuliert werden mussen. Zum anderen konnen Verkehrssimulationsysteme, die nicht uber ein Fusgangermodell verfugen, um die Effekte von Fusgangern erganzt werden. Das Kapitel basiert auf [Lattner et al., 2012] in Kooperation mit Andreas Lattner, Dimitrios Paraskevopoulos und Ingo Timm. Abschnitt 11.1 beschreibt die Protokollierung von Fusgangereffekten zur Ableitung von Wahrscheinlichkeitsverteilungen (Abschnitt 11.2), die in Abschnitt 11.3 angewendet werden. Abschnitt 11.4 gibt eine Zusammenfassung und einen Ausblick.

Ameisen-inspirierte Routingmethode

Dieses Kapitel untersucht eine Ameisen-inspirierte Routingmethode, die zu einer effizienteren Nutzung der Verkehrsinfrastruktur beitragen kann. Es basiert auf der Arbeit [Dallmeyer et al., 2012d], die in Kooperation mit Rene Schumann, Andreas Lattner und Ingo Timm entstanden ist. Die gezeigten Ergebnisse basieren jedoch auf einer neueren Version von MAINSIM, bei der die Analyse des Strasengraphen weiter verfeinert wurde. Das beschriebene Routingverfahren wurde als zusatzliche Erweiterung um die Moglichkeit des Umplanens erganzt.