ROMANO, ANGELA (2021) Estimation/updating of origin-destination flows: recent trends and opportunities from trajectory data. [Tesi di dottorato]

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Item Type:	Tesi di dottorato
Resource language:	English
Title:	Estimation/updating of origin-destination flows: recent trends and opportunities from trajectory data
Creators:	Creators Email ROMANO, ANGELA angela.romano2@unina.it
Date:	14 July 2021
Number of Pages:	191
Institution:	Università degli Studi di Napoli Federico II
Department:	Ingegneria Civile, Edile e Ambientale
Dottorato:	Ingegneria dei sistemi civili
Ciclo di dottorato:	33
Coordinatore del Corso di dottorato:	nome email PAPOLA, ANDREA papola@unina.it
Tutor:	nome email MARZANO, VITTORIO UNSPECIFIED VITI, FRANCESCO UNSPECIFIED
Date:	14 July 2021
Number of Pages:	191
Keywords:	trajectory data, travel demand estimation, synthetic experiments, trajectory data analysis, sensing technologies, vehicle tracking, o-d flows estimation
Settori scientifico-disciplinari del MIUR:	Area 08 - Ingegneria civile e Architettura > ICAR/05 - Trasporti
Date Deposited:	19 Jul 2021 20:18
Last Modified:	07 Jun 2023 11:04
URI:	http://www.fedoa.unina.it/id/eprint/13624

Collection description

Understanding the spatial and temporal dynamics of mobility demand is essential for many applications over the entire transport domain, from planning and policy assessment to operation, control, and management. Typically, mobility demand is represented by origin-destination (o-d) flows, each representing the number of trips from one traffic zone to another, for a certain trip purpose and mode of transport, in a given time interval (Cascetta, 2009, Ortuzar and Willumsen, 2011). O-d flows have been generally unobservable for decades, thus the problem of o-d matrix estimation is still one of the most challenging in transportation studies. In recent times, unprecedented tracing and tracking capabilities have become available. The pervasive penetration of sensing devices (smartphones, black boxes, smart cards, ...) adopting a variety of tracing technologies/methods (GPS, Bluetooth, ...) could make in many cases o-d flows now observable. The increasing availability of trajectory data sources has provided new opportunities to enhance observability of human mobility and travel patterns between origins and destinations, recently explored by researchers and practitioners, bringing innovation and new research directions on origin-destination (o-d) matrix estimation. The purpose of this thesis is to develop a deep understanding of the opportunities and the limitations of trajectory data to assess its potential for ameliorating the o-d flows estimation/updating problem and for conducting o-d related analysis. The proposed work involves both real trajectory data analysis and laboratory experiments based on synthetic data to investigate the implications of the trajectory data sample distinctive features (e.g. sample representativeness and bias) on demand flows accuracy. Final considerations and results might provide useful guidelines for researchers and practitioners dealing with various types of trajectory data sample and conducting o-d related applications.

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