VIRTUAL Lisbon Livable Cities
Abstract
This paper presents a methodology for generating an origin-destination matrix (ODM) that integrates trip generation, attraction, and distribution—an approach rarely found in the literature. It leverages secondary data, such as population and housing censuses and databases on job, education, commercial, and recreational facilities (Points of Interest, POI). Trip generation is calculated based on the a-posteriori probability of an individual undertaking a trip to fulfill a specific need, considering the socio-demographic characteristics of each individual in a Traffic Analysis Zone (TAZ). The model determines trip attraction based on the Points of Interest (POIs) within each TAZ and models trip distribution using Gravity, Regression, and Logit Models, factoring in generalized cost between origin-destination pairs. This versatile methodology estimates ODMs for motorized and non-motorized transport, many trip purposes, and at different frame times. Its flexibility and applicability to diverse scenarios set it apart from existing studies, which typically only address some of these dimensions simultaneously. Moreover, the approach does not require an initial ODM, making it particularly useful in regions needing more detailed travel data, such as urban zones in developing countries. Only a few household surveys are needed for calibration and validation, underscoring the method’s cost- and time. The ODM reveals the spatial distribution of population groups and facilities, providing essential data for urban planning. It helps decision-makers balance service supply with mobility demand, reduce inter-TAZ travel, enhance zone autonomy, and promote sustainable urban environments.
Patricia Cazorla Vanegas: I am a Civil Engineer from the University of Cuenca with a Master’s in Traffic, Logistics, and Intelligent Transportation Systems from KU Leuven. I am a PhD candidate in Applied Computer Science at the University of Cuenca, where I focus on the Origin-Destination Matrix Estimation Problem. Additionally, I serve as a tenured professor at the University of Cuenca and am co-director of the MAS Research Group (Models, Analysis, and Simulations). My work spans various areas, including analyzing land use and sociodemographic characteristics related to mobility systems, optimization, data analytics.
Elina Avila-Ordoñez: A Systems Engineer who graduated from the University of Cuenca, she earned her Master’s degree in Software Engineering from the National University of La Plata in Argentina and her PhD in Transportation Engineering from KU Leuven in Belgium. Currently a tenured professor and researcher at the University of Cuenca, she previously led the School of Informatics and has served as a director for research and mobility consulting projects. Her areas of interest include mathematical modeling, software, and mobility.
Victor Saquicela Galarza: Victor is an Associate Professor at the University of Cuenca and a member of the Knowledge Management Group in its Computer Science Department. He previously worked as a programming analyst, network administrator, and researcher in the Artificial Intelligence Department at the Polytechnic University of Madrid within the Ontological Engineering Group. He holds a Systems Engineering degree (University of Cuenca, 2001), a Master’s in Software Engineering (2004), and a PhD in Computer Science and Artificial Intelligence (Polytechnic University of Madrid). His research focuses on Semantic e-Science, IoT, and the Semantic Web, with expertise in scalable applications, information integration, and business intelligence.
5:00 pm - 6:30 pm
Wednesday 9th July, 2025