Using Passive Data Collection Methods to Learn Complex Mobility Patterns: An Exploratory Analysis; ; ;
Communication orale (in press)
Using Passive Data Collection Methods to Learn Complex Mobility Patterns: An Exploratory AnalysisCommunication orale (in press)
Mobility-Driven and Energy-Efficient Deployment of Edge Data Centers in Urban Environmentsin IEEE Transactions on Sustainable Computing (2021)
Multi-access Edge Computing (MEC) brings storage and computational capabilities at the edge of the ...
A Big Data Demand Estimation Model for Urban Congested Networksin Transport and Telecommunication (2020)
Incorporating trip chaining within online demand estimationin Transportation Research. Part B, Methodological (2020), 132
Inferring Urban Mobility and Habits from User Location Historyin Transportation Research Procedia (2020, January), 47
The Impact of Human Mobility on Edge Data Center Deployment in Urban Environmentsin IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 2019 (2019, December)
Multi-access Edge Computing (MEC) brings storage and computational capabilities at the edge of the ...
Crowdsensed Data Learning-Driven Prediction of Local Businesses Attractiveness in Smart Citiesin IEEE Symposium on Computers and Communications (ISCC), Barcelona, Spain, 2019 (2019, July)
Urban planning typically relies on experience-based solutions and traditional methodologies to face ...
Leveraging GIS Data and Topological Information to Infer Trip Chaining Behaviour at Macroscopic LevelCommunication orale (2019, June)
One of the open challenges in transport modelling is to estimate within-day demand flows that ...
Incorporating trip chaining within online demand estimationin Transportation Research. Part B, Methodological (2019)
Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dy- namic Traffic ...
A Big Data Demand Estimation Framework for Modelling of Urban Congested Networksin CSUM 2018, AISC 879 proceedings (2019)
A Markov Chain Monte Carlo Approach for Estimating Daily Activity PatternsPoster (2019, January)
Determining the purpose of trips brings is a fundamental information to evaluate travel demand ...
Incorporating trip chaining within online demand estimationin Transportation Research Procedia (2019), 38
Time-dependent Origin–Destination (OD) demand flows are fundamental inputs for Dynamic Traffic ...
Incorporating activity duration and scheduling utility into equilibrium-based Dynamic Traffic Assignmentin Transportation Research. Part B, Methodological (2018)
This paper deals with the problem of jointly modelling activity scheduling and duration within a ...
A utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and durationin Transportation Research. Part A, Policy and Practice (2018)
This paper proposes a Dynamic Demand Estimation (DODE) framework that explicitly accounts for ...
Dynamic Origin-Destination Matrix Estimation with Interacting Demand PatternsThèse de doctorat (2018)
It has become very fashionable to talk about Mobility as a Service, multimodal transport networks ...
Evaluating the reliability of the Utility-Based Dynamic OD Estimation on Large NetworksCommunication orale (2018, January)
Utility-Based Kalman Filtering for real-time estimation of daily demand flowsCommunication orale (2018)
Time-dependent Origin-Destination (OD) demand flows are fundamental inputs for Dynamic Traffic ...
Demo: MAMBA: A Platform for Personalised Multimodal Trip PlanningLogiciel (2017)
In recent years, multimodal transportation has become a challenging approach to route planning ...
Effectiveness of the Two-Step Dynamic Demand Estimation model on large networksin Proceedings of 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS) (2017, June 28)
In this paper, the authors present a Two-Step approach that sequentially adjusts generation and ...
Generating purpose-dependent production factors through Monte Carlo sampling techniques.Communication orale (2017, May)
Generating Macroscopic, Purpose-Dependent Production Factors Through Monte Carlo Sampling Techniquesin Transportation Research Procedia (2017)
A network-wide assessment of local signal control policies’ performance in practical implementationsin Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International Conference on (2016, November)
Effects of incorporating activity duration and scheduling utility on the equilibrium-based dynamic traffic assignmentCommunication orale (2016, July)
A Markov chain dynamic model for trip generation and distribution based on CDRin Periodica Polytechnica (2015)
On the link between activity patterns and traffic within-day demand profiles: empirical analysis and application to demand estimationCommunication orale (2015, September)
A two-steps dynamic demand estimation approach sequentially adjusting generations and distributionsin Proceedings of IEEE-ITS Conference (2015, September)
The Impact of Route Choice Modeling on Dynamic OD Estimationin Proceedings of IEEE-ITS Conference (2015, September)
Improving the reliability of demand estimation using traffic counts by including information on link flow observabilityCommunication orale (2015, August)
Systematic assessment of local & global control policies: A methodological perspectivein Proceedings of the MT-ITS Conference (2015, June)
A Markov Chain dynamic model for trip generation and distribution based on CDRin Proceedings of the MT-ITS Conference (2015, June)
Assessing the consistency between observed and modelled route choices through GPS datain Proceedings of the MT-ITS Conference (2015, June)
Systematic assessment of local & global signal control policies: A methodological perspectivein Proceedings of 2015 International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2015 (2015)
Traffic control performance on networks depends on the flow response to the policy adopted, which ...
A TWO-STEP APPROACH FOR THE CORRECTION OF THE SEED MATRIX IN THE DYNAMIC DEMAND ESTIMATIONin Transportation Research Record: Journal of the Transportation Research Board (2014), 2466
In this work deterministic and stochastic optimization methods are tested for solving the Dynamic ...
Exploiting the relation between Activity Data and Traffic Data within the Dynamic Demand Estimation ProblemCommunication orale (2014)
