Expanding the applicability of large-scale transportation models for the assessment of disruptive mobility technologies

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School of Engineering | Doctoral thesis (article-based) | Defence date: 2024-09-27
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Author
Date
2024
Department
Rakennetun ympäristön laitos
Department of Built Environment
Major/Subject
Mcode
Degree programme
Language
en
Pages
65 + app. 101
Series
Aalto University publication series DOCTORAL THESES, 176/2024
Abstract
As the world grows more complex and most aspects of daily life become fluid and more subject to change, transportation is no exception. Urbanization, sprawling, inequalities, and climate change are only a few of the challenges currently facing transportation planners, institutions, and public bodies. Moreover, historical patterns become less reliable as disruptions that once were counted in decades are now happening every few years. To address all these challenges, it is of utmost importance to adapt our approaches to be more flexible and to frame changes in attitudes, utilities, and goals in the urban population.The work presented in this thesis focuses on developing and providing multiple solutions with a specific focus on large-scale urban models. The main objective is to draw a road map of the major issues hindering modeling solutions able to tackle the challenges described above. Once that is accomplished, different methods are designed, developed, and tested on a real case study (Tallinn, the capital city of Estonia).  First, we approach the problem of defining a synthetic population detailed enough to carry out large-scale behavioral studies, without infringing privacy constraints. We then use the resulting dataset to build an activity-based behavioral model for the whole city. We harness machine learning techniques to automate the calibration of the hundreds of behavioral parameters involved, a quantity not yet achieved in the state of the art. We then focus on integrating the behavioral model with state-of-the-art traffic assignment solutions, trying to forge a blueprint for any modeler wanting to expand an existing model (a problem quite common, as many urban traffic assignment models have been developed through the years and are not easily replaceable). An iterative approach is developed and tested, first to frame a baseline situation and then to forecast the impact of disruptive mobility services on both the demand and the supply. Finally, the large-scale urban architecture built by integrating behavioral and traffic assignment models is exploited to test, for the first time with the presented degree of detail, the impacts of both an optimization algorithm and a fairness pricing scheme on an (automated) on-demand system.
Description
Supervising professor
Roncoli, Claudio, Prof., Aalto University, Department of Built Environment, Finland
Thesis advisor
Nahmias-Biran, Bat-hen, Senior Lecturer, Tel-Aviv University, Israel
Keywords
transport modeling, activity-based modeling, calibration, land use, behavioral modeling, automated driving, traffic simulation
Other note
Parts
  • [Publication 1]: Agriesti, Serio; Roncoli, Claudio; Nahmias-Biran, Bathen. Assignment of a Synthetic Population for Activity-Based Modeling Employing Publicly Available Data. International J 10.3390/ijgi11020148 ournal of Geo-Information, 11, 2, 2022.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202203152253
    DOI: 10.3390/ijgi11020148 View at publisher
  • [Publication 2]: Agriesti, Serio; Kuzmanovski, Vladimir; Hollmén, Jaakko; Roncoli, Claudio; Nahmias-Biran, Bat-hen. A Bayesian Optimization Approach for Calibrating Large-Scale Activity-Based Transport Models. IEEE Open Journal of Intelligent Transportation Systems, 4, 740 - 754, 2023.
    Full text in Acris/Aaltodoc: https://urn.fi/URN:NBN:fi:aalto-202310116240
    DOI: 10.1109/OJITS.2023.3321110 View at publisher
  • [Publication 3]: Agriesti, Serio; Roncoli, Claudio; Nahmias-Biran, Bathen. An Equilibrium-seeking Search Algorithm for Modeling the Integration of Supply and Demand. In 12th Symposium of the European Association for Research in Transportation hEART 2024, Espoo, Finland, 18th of June, 2024, Available [Online] https://transp-or.epfl.ch/heart/2024/abstracts/hEART_2024_paper_2936.pdf.
    DOI: 10.48550/arXiv.2404.07789 View at publisher
  • [Publication 4]: Agriesti, Serio; Roncoli, Claudio; Nahmias-Biran, Bathen. A simulation-based framework for quantifying potential AMoD demand loss due to operational constraints in mobility services. Transportation Research Part A, Under review.
    DOI: 10.1109/ITSC.2018.8569961 View at publisher
  • [Publication 5]: Zhou, Ze; Agriesti, Serio; Roncoli, Claudio; Yfantis, Lampros; Nahmias-Biran, Bat-hen; Casas, Jordi. Assessing the Operational Performance of Ridesharing-Enabled Shared Autonomous Vehicles Fleets. In 12th Symposium of the European Association for Research in Transportation hEART 2024, Espoo, Finland, 20th of June, 2024, Available [Online] https://transp-or.epfl.ch/heart/2024/abstracts/ hEART_2024_paper_0695.pdf
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Permanent link to this item
https://urn.fi/URN:ISBN:978-952-64-1989-3
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