Zobrazeno 1 - 10
of 58
pro vyhledávání: '"Carlos Lima Azevedo"'
Autor:
Haneen Farah, Carlos Lima Azevedo
Publikováno v:
IATSS Research, Vol 41, Iss 1, Pp 12-21 (2017)
The increased availability of detailed trajectory data sets from naturalistic, observational, and simulation-based studies, is a key source for potential improvements in the development of detailed safety models that explicitly account for vehicle co
Externí odkaz:
https://doaj.org/article/0f8e3f66d95e468187ac9ee8473a25b6
Autor:
Jimi B Oke, Youssef M Aboutaleb, Arun Akkinepally, Carlos Lima Azevedo, Yafei Han, P Christopher Zegras, Joseph Ferreira, Moshe E Ben-Akiva
Publikováno v:
Environmental Research Letters, Vol 15, Iss 9, p 099502 (2020)
Externí odkaz:
https://doaj.org/article/e1338f4c5dc84873a12d7f2d5b4adb38
Autor:
Jimi B Oke, Youssef M Aboutaleb, Arun Akkinepally, Carlos Lima Azevedo, Yafei Han, P Christopher Zegras, Joseph Ferreira, Moshe E Ben-Akiva
Publikováno v:
Environmental Research Letters, Vol 14, Iss 9, p 095006 (2019)
Urban mobility significantly contributes to global carbon dioxide emissions. Given the rapid expansion and growth in urban areas, cities thus require innovative policies to ensure efficient and sustainable mobility. Urban typologies can serve as a ve
Externí odkaz:
https://doaj.org/article/936e5acd345844a193d5eba4e8bf5ebb
Autor:
Linlin You, Mazen Danaf, Fang Zhao, Jinping Guan, Carlos Lima Azevedo, Bilge Atasoy, Moshe Ben-Akiva
Publikováno v:
IEEE Transactions on Intelligent Transportation Systems. 24:4060-4074
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bbd1f85651f50a8f46a53ef26bed728e
https://doi.org/10.1109/tits.2023.3236991
https://doi.org/10.1109/tits.2023.3236991
Publikováno v:
Transportmetrica B: Transport Dynamics. 11:434-462
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ba6f40648c6510037def8fa440f2ead1
https://doi.org/10.1080/21680566.2022.2083034
https://doi.org/10.1080/21680566.2022.2083034
Publikováno v:
Proceedings of the 12th International Scientific Conference on Mobility and Transport ISBN: 9789811983603
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7643abaa12cc28b81ccaddcfe302b8d7
https://doi.org/10.1007/978-981-19-8361-0_12
https://doi.org/10.1007/978-981-19-8361-0_12
Autor:
Christoffer Riis, Francisco Antunes, Frederik Boe Hüttel, Carlos Lima Azevedo, Francisco Camara Pereira
Publikováno v:
Technical University of Denmark Orbit
Riis, C, Antunes, F, Hüttel, F B, Lima Azevedo, C M & Pereira, F C 2022, ' Bayesian Active Learning with Fully Bayesian Gaussian Processes ', Conference on Neural Information Processing Systems, New Orleans, United States, 28/11/2022-03/12/2022 .
Riis, C, Antunes, F, Hüttel, F B, Lima Azevedo, C M & Pereira, F C 2022, ' Bayesian Active Learning with Fully Bayesian Gaussian Processes ', Conference on Neural Information Processing Systems, New Orleans, United States, 28/11/2022-03/12/2022 .
The bias-variance trade-off is a well-known problem in machine learning that only gets more pronounced the less available data there is. In active learning, where labeled data is scarce or difficult to obtain, neglecting this trade-off can cause inef
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1d684015696599a5a310bb9059cc2ab
http://arxiv.org/abs/2205.10186
http://arxiv.org/abs/2205.10186
Publikováno v:
Oh, S, Seshadri, R, Azevedo, C L, Kumar, N, Basak, K & Ben-Akiva, M 2020, ' Assessing the impacts of automated mobility-on-demand through agent-based simulation: A study of Singapore ', Transportation Research Part A: Policy and Practice, vol. 138, pp. 367-388 . https://doi.org/10.1016/j.tra.2020.06.004
The advent of autonomous vehicle technologies and the emergence of new ride-sourcing business models has spurred interest in Automated Mobility-on-Demand (AMOD) as a prospective solution to meet the challenges of urbanization. AMOD has the potential
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::92eaa32a82fcad32f46bfb790cd1c108
https://doi.org/10.1016/j.tra.2020.06.004
https://doi.org/10.1016/j.tra.2020.06.004
Publikováno v:
Fournier, N, Christofa, E, Akkinepally, A P & Lima Azevedo, C M 2021, ' Integrated population synthesis and workplace assignment using an efficient optimization-based person-household matching method ', Transportation, vol. 48, pp. 1061–1087 . https://doi.org/10.1007/s11116-020-10090-3
Large scale activity-based simulation models inform a variety of transportation and planning policies using models that often rely on fixed or flexible workplace location in a synthetic population as input to work related activity, participation, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1271bfcd0e6b83d141a8233825615aa5
https://doi.org/10.1007/s11116-020-10090-3
https://doi.org/10.1007/s11116-020-10090-3
Publikováno v:
Peled, I, Kamalakar, R, Lima Azevedo, C M & Pereira, F C 2022, ' QTIP: Quick simulation-based adaptation of traffic model per incident parameters ', Journal of Simulation, vol. 16, no. 2, pp. 111-131 . https://doi.org/10.1080/17477778.2020.1756702
Current data-driven traffic prediction models are usually trained with large datasets, e.g. several months of speeds and flows. Such models provide very good fit for ordinary road conditions, but often fail just when they are most needed: when traffi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ae6a1f79578b1e3b1c92b2adf69447b0
https://orbit.dtu.dk/en/publications/9ca69426-4fe5-4ad3-b5b5-943d71209316
https://orbit.dtu.dk/en/publications/9ca69426-4fe5-4ad3-b5b5-943d71209316