Actor-based macroscopic modeling and simulation for smart urban planning
2018 (English)In: Science of Computer Programming, ISSN 0167-6423, E-ISSN 1872-7964, Vol. 168, p. 142-164Article in journal (Refereed) Published
Abstract [en]
Assessing the impacts of a mobility initiative prior to deployment is a complex task for both urban planners and transport companies. Computational models like Tangramob offer an agent-based framework for simulating the evolution of urban traffic after the introduction of new mobility services. However, simulations can be computationally expensive to perform due to their iterative nature and the microscopic representation of traffic. To address this issue, we designed a simplified model architecture of Tangramob in Timed Rebeca (TRebeca) and we developed a tool-chain for the generation runnable instances of this model starting from the same input files of Tangramob. Running TRebeca models allows users to get an idea of how the mobility initiatives under study affect the traveling experience of commuters, in a short time and without the need to use the simulator during this first experimental step. Then, once a subset of these initiatives is identified according to user's criteria, it is reasonable to simulate them with Tangramob in order to get more detailed results. To validate this approach, we compared the output of both the simulator and the TRebeca model on a collection of mobility initiatives. The correlation between the results demonstrates the usefulness of using TRebeca models for unconventional contexts of application.
Place, publisher, year, edition, pages
Elsevier B.V. , 2018. Vol. 168, p. 142-164
Keywords [en]
Actor-based modeling languages, Distributed computer systems, Modeling languages, Urban planning, Actor-based modeling, Agent-based framework, Computational model, Macroscopic model, Mobility service, Model architecture, Transport companies, Urban planners, Urban transportation
National Category
Computer Systems Embedded Systems
Identifiers
URN: urn:nbn:se:mdh:diva-41015DOI: 10.1016/j.scico.2018.09.002ISI: 000450385200007Scopus ID: 2-s2.0-85053512327OAI: oai:DiVA.org:mdh-41015DiVA, id: diva2:1251570
2018-09-272018-09-272019-10-01Bibliographically approved