ITSUMO: An Agent-Based Simulator for Intelligent Transportation Systems

Bazzan, Ana L. C.; Heinen, Milton Roberto; Amarante, Maicon de Brito do

doi:10.1016/b978-0-12-397041-1.00001-7

Cited by 8 publications

(15 citation statements)

References 18 publications

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“…We have reviewed a wide range of available tra c simulators in detail (inter alia [3], [5], [19], [8], [20], [6], [7], [21], [22], [23]). In particular, the AgentPolis approach stands out as it also reflects on the shortcomings of reusability in available simulation models.…”

Section: Related Workmentioning

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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Section: Related Workmentioning

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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“…• Fully Agent-Based: MATSim [10], ITSUMO [11], MovSim [12], MASCAT [13], MATISSE [14], POLARIS [15], AgentPolis [5], OPUS [16], MOSAIIC [17], MARS [18], SimMobility [19] • Featuring Agent-Technology: ATSim [20], FastTrans [21] • Not Agent-Based: TRANSIMS [22], SUMO [23], OpenTraffic [24,25], CONTRAM [26], PTV VIS-SIM/VISUM [27], GETRAM/AIMSUN [28], PARAMICS [29], MITSIM [30], FreeSim [31], TSIS/CORSIM [32], VATSIM [33], DRACULA [34], RENAISSANCE [35], SimTraffic [36] Primary focus is put on the approaches of the first and the second category as state of the art research has shown in a growing interest in the application of agent-based simulation models. However, important applications that have laid the groundwork for the development of agent-based systems are worth mentioning and have also been included.…”

Section: Perspectives Of Comparisonmentioning

confidence: 99%

An Overview of Agent-based Traffic Simulators

Nguyen,

Powers,

Urquhart

et al. 2021

Preprint

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In most countries population in urban areas is growing, while available travel infrastructure and resources are limited. At the same time desires to minimise environmental impact and energy use have led to new requirements in the field of inner-city transportation. As a result, the portfolio of mobility services provided is developing in order to improve the use of the available resources. Computer-based simulation is an accepted means for investigating the effects of new transportation policies and services. Many researchers are faced with the question of choosing a suitable simulator for their specific research question. In this paper, we review a broad spectrum of recent and historically important applications, in order to provide an overview of available work and to help researchers make a more informed decision on the selection of a suitable simulator. We discuss strengths and weaknesses of the applications and identify gaps for which we argue that more detailed work is required.

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“…However, none of these is strictly defined as agent-based simulation systems, even though they model vehicles in an object-oriented manner. Just a few simulation tools truly support the concept of agents and multi-agent systems in traffic simulation; MATSim-T [3,4] and ITSUMO [9,6] are good examples to be mentioned.…”

Section: Related Workmentioning

confidence: 99%

“…As a motivation, just a few simulation tools truly support the concept of agents and multi-agent systems in traffic simulation; MATSim-T [3,4] and ITSUMO [9,6] are good examples to be mentioned. However, no standard of wide reach for the implementation of such tools actually exists.…”

Section: Introductionmentioning

confidence: 99%

JADE, TraSMAPI and SUMO: A tool-chain for simulating traffic light control

Azevedo,

de Araújo,

Rossetti

et al. 2016

Preprint

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Increased stress, fuel consumption, air pollution, accidents and delays are some of the consequences of traffic congestion usually incurring in tremendous economic impacts, which society aims to remedy in order to leverage a sustainable development. Recently, unconventional means for modeling and controlling such complex traffic systems relying on multiagent systems have arisen. This paper contributes to the understanding of such complex and highly dynamic systems by proposing an open-source tool-chain to implement multiagent-based solutions in traffic and transportation. The proposed approach relies on two very popular tools in both domains, with focus on traffic light control. This tool-chain consists in combining JADE (Java Agent DEvelopment Framework), for the implementation of multi-agent systems, with SUMO (Simulation of Urban MObility), for the microscopic simulation of traffic interactions. TraSMAPI (Traffic Simulation Manager Application Programming Interface) is used to combine JADE and SUMO allowing communication between them. A demonstration of the concept is presented to illustrate the main features of this tool-chain, using Q-Learning as the reinforcement learning method for each traffic light agent in a simulated network. Results demonstrate the feasibility of the proposed framework as a practical means to experiment with different agent-based designs of intelligent transportation solutions.

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ITSUMO: An Agent-Based Simulator for Intelligent Transportation Systems

Cited by 8 publications

References 18 publications

Using Semantic Technology To Model Persona For Adaptable Agents

Using Semantic Technology To Model Persona For Adaptable Agents

An Overview of Agent-based Traffic Simulators

JADE, TraSMAPI and SUMO: A tool-chain for simulating traffic light control

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