Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg

Models can provide valuable decision support in the ongoing effort to create a sustainable and effective modality mix in urban settings. Modern transportation infrastructures must meaningfully combine public transport with other mobility initiatives such as shared and on-demand systems. The increase...

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Autores principales:	Ulfia Annette Lenfers, Nima Ahmady-Moghaddam, Daniel Glake, Florian Ocker, Jonathan Ströbele, Thomas Clemen
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	multi-agent systems spatial simulation smart cities MARS decision support systems urban planning Agriculture S
Acceso en línea:	https://doaj.org/article/3ad8051374314f2abe02efd604ac9089
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spelling	oai:doaj.org-article:3ad8051374314f2abe02efd604ac90892021-11-25T18:09:29ZIncorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg10.3390/land101111792073-445Xhttps://doaj.org/article/3ad8051374314f2abe02efd604ac90892021-11-01T00:00:00Zhttps://www.mdpi.com/2073-445X/10/11/1179https://doaj.org/toc/2073-445XModels can provide valuable decision support in the ongoing effort to create a sustainable and effective modality mix in urban settings. Modern transportation infrastructures must meaningfully combine public transport with other mobility initiatives such as shared and on-demand systems. The increase of options and possibilities in multi-modal travel implies an increase in complexity when planning and implementing such an infrastructure. Multi-agent systems are well-suited for addressing questions that require an understanding of movement patterns and decision processes at the individual level. Such models should feature intelligent software agents with flexible internal logic and accurately represent the core functionalities of new modalities. We present a model in which agents can choose between owned modalities, station-based bike sharing modalities, and free-floating car sharing modalities as they exit the public transportation system and seek to finish their personal multi-modal trip. Agents move on a multi-modal road network where dynamic constraints in route planning are evaluated based on an agent’s query. Modality switch points (MSPs) along the route indicate the locations at which an agent can switch from one modality to the next (e.g., a bike rental station to return a used rental bike and continue on foot). The technical implementation of MSPs within the road network was a central focus in this work. To test their efficacy in a controlled experimental setting, agents optimized only the travel time of their multi-modal routes. However, the functionalities of the model enable the implementation of different optimization criteria (e.g., financial considerations or climate neutrality) and unique agent preferences as well. Our findings show that the implemented MSPs enable agents to switch between modalities at any time, allowing for the kind of versatile, individual, and spontaneous travel that is common in modern multi-modal settings.Ulfia Annette LenfersNima Ahmady-MoghaddamDaniel GlakeFlorian OckerJonathan StröbeleThomas ClemenMDPI AGarticlemulti-agent systemsspatial simulationsmart citiesMARSdecision support systemsurban planningAgricultureSENLand, Vol 10, Iss 1179, p 1179 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multi-agent systems spatial simulation smart cities MARS decision support systems urban planning Agriculture S
spellingShingle	multi-agent systems spatial simulation smart cities MARS decision support systems urban planning Agriculture S Ulfia Annette Lenfers Nima Ahmady-Moghaddam Daniel Glake Florian Ocker Jonathan Ströbele Thomas Clemen Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
description	Models can provide valuable decision support in the ongoing effort to create a sustainable and effective modality mix in urban settings. Modern transportation infrastructures must meaningfully combine public transport with other mobility initiatives such as shared and on-demand systems. The increase of options and possibilities in multi-modal travel implies an increase in complexity when planning and implementing such an infrastructure. Multi-agent systems are well-suited for addressing questions that require an understanding of movement patterns and decision processes at the individual level. Such models should feature intelligent software agents with flexible internal logic and accurately represent the core functionalities of new modalities. We present a model in which agents can choose between owned modalities, station-based bike sharing modalities, and free-floating car sharing modalities as they exit the public transportation system and seek to finish their personal multi-modal trip. Agents move on a multi-modal road network where dynamic constraints in route planning are evaluated based on an agent’s query. Modality switch points (MSPs) along the route indicate the locations at which an agent can switch from one modality to the next (e.g., a bike rental station to return a used rental bike and continue on foot). The technical implementation of MSPs within the road network was a central focus in this work. To test their efficacy in a controlled experimental setting, agents optimized only the travel time of their multi-modal routes. However, the functionalities of the model enable the implementation of different optimization criteria (e.g., financial considerations or climate neutrality) and unique agent preferences as well. Our findings show that the implemented MSPs enable agents to switch between modalities at any time, allowing for the kind of versatile, individual, and spontaneous travel that is common in modern multi-modal settings.
format	article
author	Ulfia Annette Lenfers Nima Ahmady-Moghaddam Daniel Glake Florian Ocker Jonathan Ströbele Thomas Clemen
author_facet	Ulfia Annette Lenfers Nima Ahmady-Moghaddam Daniel Glake Florian Ocker Jonathan Ströbele Thomas Clemen
author_sort	Ulfia Annette Lenfers
title	Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
title_short	Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
title_full	Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
title_fullStr	Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
title_full_unstemmed	Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg
title_sort	incorporating multi-modal travel planning into an agent-based model: a case study at the train station kellinghusenstraße in hamburg
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/3ad8051374314f2abe02efd604ac9089
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Incorporating Multi-Modal Travel Planning into an Agent-Based Model: A Case Study at the Train Station Kellinghusenstraße in Hamburg

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