Franziska Klügl

Decision dynamics in a traffic scenario

Information is a key commodity in many socio-economic systems like stock markets or traffic systems. In this paper the influence of dynamic information on the stability of traffic patterns is investigated using a very simple route choice scenario. The basis of the route decisions is dynamic information generated by traffic flow simulations. A correlation analysis yields that the system can be destabilized by introducing information. It is found that the overall performance of the system is reduced, although the information should help to distribute traffic more efficiently.

The impact of real-time information in a two-route scenario using agent-based simulation

Abstract Since advanced traveler information systems (ATIS) have been introduced, their potential benefits as well as their drawbacks have been discussed controversially. This will continue as long as the drivers’ reactions upon current or even predictive information about the traffic situation are not known. Thus, traffic models that also consider this feedback are necessary. In this paper, we address a basic two-route scenario with different types of information and study the impact of it using simulations. The road users are modeled as agents, a natural and promising approach to describe them. Different ways of generating current information are tested. It is pointed out that the nature of the information very much influences the potential benefits of the ATIS.

A validation methodology for agent-based simulations

Validity forms the basic prerequisite for every simulation model, therefore also for reasonable usage of the agent-based simulation paradigm. However, models based on the multi-agent system metaphor tend to need some particular approaches. In this paper, I propose a process for validating agent-based simulation models that combines face validation, sensitivity analysis, calibration and statistical validation.Validity forms the basic prerequisite for every simulation model, therefore also for reasonable usage of the agent-based simulation paradigm. However, models based on the multi-agent system metaphor tend to need some particular approaches. In this paper, I propose a process for validating agent-based simulation models that combines face validation, sensitivity analysis, calibration and statistical validation.

A review on agent-based technology for traffic and transportation

In the last few years, the number of papers devoted to applications of agent-based technologies to traffic and transportation engineering has grown enormously. Thus, it seems to be the appropriate time to shed light over the achievements of the last decade, on the questions that have been successfully addressed, as well as on remaining challenging issues. In the present paper, we review the literature related to the areas of agent-based traffic modelling and simulation, and agent-based traffic control and management. Later we discuss and summarize the main achievements and the challenges.

Agents in Traffic Modelling - From Reactive to Social Behaviour

In modern societies the demand for mobility is increasing daily. One challenge to researchers dealing with transportation is to find efficient ways to model and predict traffic flow, even if the behaviour of people in traffic is not a trivial problem. The social nature of traffic (e.g. coordinated decisions) seems to be a key question, not well explored. We aim at creating a model of drivers as social agents, thus allowing their behaviour to be predicted and considered in the simulation. This may, on its turn, improve the accuracy of the existing Advanced Travel Information Systems (ATIS).

Large-Scale Agent-Based Pedestrian Simulation

Pedestrian simulation is a challenging and fruitful application area for agent-based modeling and simulation in the traffic and transportation domain. In this paper we will present the concepts and results of a particular project study: an agent-based simulation of pedestrian traffic of the complete railway station of Bern during the most busy morning hours. Overall more than 40 000 agents are passing through during 1,5 virtual hours. Going beyond traditional approaches for microscopic pedestrian simulation, our simulated pedestrians are not only capable of moving without collisions between two pre-defined locations, but are able to flexibly plan and re-plan their way through the railway station. A short glance and some discussion about the potential of agent-based pedestrian simulation closes this contribution.

SeSAm: implementation of agent-based simulation using visual programming

In this paper, we present the most important features of SeSAm, a modeling and simulation platform for multi-agent simulations. Based on a declarative, explicit model representation and visual programming, it allows implementing models on specification level. Optimizing compilation allows efficient simulation of the explicit model representation. It was successfully applied in different areas, like biology, traffic or logistics simulation.

Anticipatory Traffic Forecast Using Multi-Agent Techniques

In this contribution, intelligent transportation systems (ITS) and their impact on traffic systems are discussed. Although traffic forecast offers the possibility to rearrange the temporal distribution of traffic patterns, it suffers from a fundamental problem because the reaction of the driver to the forecast is a priori unknown. On the other hand the behaviour of drivers can have a serious impact on the quality of a traffic forecast since it can result in a feedback - an anticipatory forecast is needed. To include such effects we propose a two-layered agent architecture for modelling drivers’ behaviour in more detail. The layers distinguish different tasks of road users.

Agent-Based Modeling and Simulation

This article gives an introduction to agent-based modeling and simulation (ABMS). After a general discussion about modeling and simulation, we address the basic concept of ABMS, focusing on its generative and bottom-up nature, its advantages as well as its pitfalls. The subsequent part of the article deals with application-oriented aspects, including selected tools and well-known applications. In order to illustrate the benefits of using ABMS, we focus on several aspects of a well-known area related to simulation of complex systems, namely traffic. At the end, a brief look into future challenges is given.

Multi-Agent Systems for Traffic and Transportation Engineering

Our increasing societal demand for mobility now challenges researchers to devise more efficient traffic and transportation systems.The Handbook of Research on Multi-Agent Systems for Traffic and Transportation Engineering provides a unique compendium of research covering topics such as transportation system designs, control devices, and techniques to optimize existing networks. Presenting a collection of approaches to issues in traffic and transportation, this authoritative reference offers a compilation of chapters with innovative methods and systems written by leading international researchers.