Building a Large-Scale Micro-Simulation Transport Scenario Using Big Data

Dados Bibliográficos

ID22034985
AutoresJoerg Schweizer (0000-0003-2289-6111, University of Bologna, autor correspondente), Cristian Poliziani (0000-0002-7646-1394, University of Bologna), Federico Rupi (0000-0001-8404-5684, University of Bologna), Davide Morgano (University of Bologna), Mattia Magi (Eni (Italy))
Ano2021
Volume10
Fascículo3
Páginas165
Data de publicação2021-03-14
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoISPRS International Journal of Geo-Information (JOURNAL)
Identificadores do periódicoISSN: 2220-9964 • E-ISSN: 2220-9964
EditoraMDPI AG (PUBLISHER • IT)
DOI10.3390/ijgi10030165
OpenAlexW3138785323
IdiomaEN
Citações recebidas7
Referências citadas43

A large-scale agent-based microsimulation scenario including the transport modes car, bus, bicycle, scooter, and pedestrian, is built and validated for the city of Bologna (Italy) during the morning peak hour. Large-scale microsimulations enable the evaluation of city-wide effects of novel and complex transport technologies and services, such as intelligent traffic lights or shared autonomous vehicles. Large-scale microsimulations can be seen as an interdisciplinary project where transport planners and technology developers can work together on the same scenario; big data from OpenStreetMap, traffic surveys, GPS traces, traffic counts and transit details are merged into a unique transport scenario. The employed activity-based demand model is able to simulate and evaluate door-to-door trip times while testing different mobility strategies. Indeed, a utility-based mode choice model is calibrated that matches the official modal split. The scenario is implemented and analyzed with the software SUMOPy/SUMO which is an open source software, available on GitHub. The simulated traffic flows are compared with flows from traffic counters using different indicators. The determination coefficient has been 0.7 for larger roads (width greater than seven meters). The present work shows that it is possible to build realistic microsimulation scenarios for larger urban areas. A higher precision of the results could be achieved by using more coherent data and by merging different data sources

Big data · Data mining · Geography · Global Positioning System · Microsimulation · Pedestrian · Simulation · Telecommunications · Traffic simulation · Transport engineering · Computer Science · Engineering · Traffic control and management · Transportation and Mobility Innovations · Transportation Planning and Optimization · Software