AGADE Traffic 2.0 - A Knowledge-Based Approach for Multi-agent Traffic Simulations

Geyer, Jannik; Nguyen, Johannes; Farrenkopf, Thomas; Guckert, Michael

doi:10.1007/978-3-030-49778-1_38

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…Details of simulation data as well as source code of the simulation are available at GitHub. 3 Based on research activities around this scenario, we have implemented a series of analysis instruments that can also be used for other simulation scenarios. Simulation results include routing information that describe where the agents have travelled.…”

Section: Demonstrationmentioning

confidence: 99%

“…Simulation results include routing information that describe where the agents have travelled. This is visualised with a heat map that colour-codes traffic load on road sections (see [3] Figure 1). Details on global system behaviour such as temporal distribution of traveller volume, visited target locations as well as selected modes of travel are visualised using appropriate charts.…”

Section: Demonstrationmentioning

confidence: 99%

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Using AGADE Traffic to Analyse Purpose-Driven Travel Behaviour

Nguyen

Powers

Urquhart

et al. 2021

Lecture Notes in Computer Science

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AGADE Traffic is an agent-based traffic simulator that can be used to analyse purpose-driven travel behaviour of individuals that leads to the emergence of systemic patterns in mobility. The simulator uses semantic technology to model knowledge of individuals and thus is able to capture individual preferences and personal objectives as determining factors of travel decisions. This creates a deeper understanding of the individuals and allows for new analysis options. Using an example, we give an overview of analysis instruments implemented in our simulator that are particularly suitable to examine results of individual-based simulations.

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Section: Demonstrationmentioning

confidence: 99%

Section: Demonstrationmentioning

confidence: 99%

Using AGADE Traffic to Analyse Purpose-Driven Travel Behaviour

Nguyen

Powers

Urquhart

et al. 2021

Lecture Notes in Computer Science

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“…We then present a modelling method that allows for less complex customisation using the concepts of persona models and ontologies. As proof of concept, we perform simulation of two example scenarios using the AGADE Traffic simulator [14]. The scenarios fundamentally di↵er in types of mobility, which is often the case when specific research questions at hand deviate from the main focus of available simulators.…”

Section: Introductionmentioning

confidence: 99%

Using Semantic Technology To Model Persona For Adaptable Agents

Nguyen¹,

Farrenkopf²,

Guckert³

et al. 2021

ECMS 2021 Proceedings Edited by Khalid Al-Begain, Mauro Iacono, Lelio Campanile, Andrzej Bargiela

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In state of the art research a growing interest in the application of agent models for the simulation of road traffic can be observed. Software agents are particularly suitable for the representation of travellers and their goal-oriented behaviour. Although numerous applications based on these types of models are already available, the options for modelling and calibration of the agents as goal-oriented individuals are either simplified to aggregated parameters or associated with overly complex and opaque implementation details. This makes it difficult to reuse available simulation models. In this paper, we demonstrate how the combination of persona models together with semantic methods can be applied to achieve a well-structured agent model that allows for improved reusability.

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Modelling the Impact of Individual Preferences on Traffic Policies

et al. 2022

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Urban traffic is a system always prone to overload, often approaching breakdown during rush hour times. Well-adjusted modifications of traffic policies, with appropriate interventions, promise potential improvements by inducing change in both individual as well as global system behaviour. However, truly effective measures are hard to identify, and testing in vivo is at least expensive and often hardly feasible. Computer-based simulations have successfully been applied for studying effects of policies, and multi-agent systems are accepted tools for that purpose as they provide means to model individual behaviour. These simulations have primarily studied effects of policies by measuring performance indicators on social benefit, while effects on individuals are hardly considered. However, successful implementation of policies hinges on whether they are accepted by the common public. Thus, effects on individuals cannot be neglected. Evaluating effects on individuals requires a more detailed modelling that is able to capture individual preferences as determining factors of agent decisions. In this paper, we present a simulation framework that focuses on modelling of individuals and thus allows evaluation of effects of policies on both the individual as well as global system behaviour. We use semantic technology (OWL ontologies and SWRL rules) to model preferences and knowledge of agents in our simulation. Using AGADE Traffic simulator, we demonstrate modelling and simulation for a mobility scenario and discuss observed results.

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AGADE Traffic 2.0 - A Knowledge-Based Approach for Multi-agent Traffic Simulations

Cited by 3 publications

References 4 publications

Using AGADE Traffic to Analyse Purpose-Driven Travel Behaviour

Using AGADE Traffic to Analyse Purpose-Driven Travel Behaviour

Using Semantic Technology To Model Persona For Adaptable Agents

Modelling the Impact of Individual Preferences on Traffic Policies

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