Követés
Guido Cantelmo
Guido Cantelmo
Technical University of Denmark
E-mail megerősítve itt: dtu.dk
Cím
Hivatkozott rá
Hivatkozott rá
Év
An adaptive bi-level gradient procedure for the estimation of dynamic traffic demand
G Cantelmo, E Cipriani, A Gemma, M Nigro
IEEE Transactions on Intelligent Transportation Systems 15 (3), 1348-1361, 2014
832014
Explaining demand patterns during COVID-19 using opportunistic data: a case study of the city of Munich
V Mahajan, G Cantelmo, C Antoniou
European Transport Research Review 13, 1-14, 2021
442021
Two-step approach for correction of seed matrix in dynamic demand estimation
G Cantelmo, F Viti, CMJ Tampère, E Cipriani, M Nigro
Transportation Research Record 2466 (1), 125-133, 2014
382014
Low-dimensional model for bike-sharing demand forecasting that explicitly accounts for weather data
G Cantelmo, R Kucharski, C Antoniou
Transportation research record 2674 (8), 132-144, 2020
332020
Aligning users’ and stakeholders’ needs: How incentives can reshape the carsharing market
G Cantelmo, RE Amini, MM Monteiro, A Frenkel, O Lerner, SS Tavory, ...
Transport Policy 126, 306-326, 2022
252022
Data to the people: a review of public and proprietary data for transport models
V Mahajan, N Kuehnel, A Intzevidou, G Cantelmo, R Moeckel, C Antoniou
Transport reviews 42 (4), 415-440, 2022
252022
Incorporating trip chaining within online demand estimation
G Cantelmo, M Qurashi, AA Prakash, C Antoniou, F Viti
Transportation Research Procedia 38, 462-481, 2019
232019
Incorporating activity duration and scheduling utility into equilibrium-based Dynamic Traffic Assignment
G Cantelmo, F Viti
Transportation Research Part B: Methodological 126, 365-390, 2019
222019
Crowdsensed data learning-driven prediction of local businesses attractiveness in smart cities
A Capponi, P Vitello, C Fiandrino, G Cantelmo, D Kliazovich, U Sorger, ...
2019 IEEE Symposium on Computers and Communications (ISCC), 1-6, 2019
212019
A utility-based dynamic demand estimation model that explicitly accounts for activity scheduling and duration
G Cantelmo, F Viti, E Cipriani, M Nigro
Transportation Research Part A: Policy and Practice 114, 303-320, 2018
202018
A Markov chain dynamic model for trip generation and distribution based on CDR
SA Di Donna, G Cantelmo, F Viti
2015 International Conference on Models and Technologies for Intelligent …, 2015
182015
A Utility-based Dynamic Demand Estimation Model that Explicitly Accounts for Activity Scheduling and Duration.
G Cantelmo, F Viti, E Cipriani, M Nigro
Transportation research procedia 23, 440-459, 2017
172017
A two-steps dynamic demand estimation approach sequentially adjusting generations and distributions
G Cantelmo, F Viti, E Cipriani, N Marialisa
2015 IEEE 18th International Conference on Intelligent Transportation …, 2015
172015
Dynamic demand estimation on large scale networks using principal component analysis: The case of non-existent or irrelevant historical estimates
M Qurashi, QL Lu, G Cantelmo, C Antoniou
Transportation Research Part C: Emerging Technologies 136, 103504, 2022
142022
Mobility-driven and energy-efficient deployment of edge data centers in urban environments
P Vitello, A Capponi, C Fiandrino, G Cantelmo, D Kliazovich
IEEE Transactions on Sustainable Computing 7 (4), 736-748, 2021
142021
A big data demand estimation model for urban congested networks
G Cantelmo, F Viti
Transport and Telecommunication, 2020
132020
The impact of human mobility on edge data center deployment in urban environments
P Vitello, A Capponi, C Fiandrino, G Cantelmo, D Kliazovich
2019 IEEE Global Communications Conference (GLOBECOM), 1-6, 2019
132019
A low dimensional model for bike sharing demand forecasting
C Guido, K Rafał, A Constantinos
2019 6th International Conference on Models and Technologies for Intelligent …, 2019
122019
Assignment matrix free algorithms for on-line estimation of dynamic origin-destination matrices
M Castiglione, G Cantelmo, M Qurashi, M Nigro, C Antoniou
Frontiers in Future Transportation 2, 640570, 2021
112021
Generating macroscopic, purpose-dependent trips through Monte Carlo sampling techniques
A Scheffer, G Cantelmo, F Viti
Transportation Research Procedia 27, 585-592, 2017
112017
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Cikkek 1–20