| 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 | 78 | 2014 |
| 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 | 38 | 2021 |
| 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 | 37 | 2014 |
| 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 | 22 | 2020 |
| Incorporating trip chaining within online demand estimation G Cantelmo, M Qurashi, AA Prakash, C Antoniou, F Viti Transportation Research Procedia 38, 462-481, 2019 | 19 | 2019 |
| 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 | 18 | 2022 |
| 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 | 18 | 2019 |
| 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 | 18 | 2019 |
| 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 | 18 | 2018 |
| 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 | 17 | 2017 |
| 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 | 16 | 2015 |
| 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 | 15 | 2015 |
| 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 | 12 | 2021 |
| 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 | 11 | 2022 |
| 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 | 11 | 2019 |
| Generating macroscopic, purpose-dependent trips through Monte Carlo sampling techniques A Scheffer, G Cantelmo, F Viti Transportation Research Procedia 27, 585-592, 2017 | 10 | 2017 |
| The impact of route choice modeling on dynamic OD estimation E Cipriani, A Del Giudice, N Marialisa, F Viti, G Cantelmo 2015 IEEE 18th International Conference on Intelligent Transportation …, 2015 | 10 | 2015 |
| 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 | 9 | 2022 |
| A big data demand estimation model for urban congested networks G Cantelmo, F Viti Transport and Telecommunication Journal 21 (4), 245-254, 2020 | 9 | 2020 |
| Improving the reliability of a two-steps dynamic demand estimation approach by sequentially adjusting generations and distributions G Cantelmo, F Viti, E Cipriani, M Nigro | 9 | 2015 |
Francesco VitiUniversity of LuxembourgEmail verificata su uni.lu
