TY - GEN
T1 - Door-to-door air travel time analysis in the United States using uber data
AU - Monmousseau, Philippe
AU - Delahaye, Daniel
AU - Marzuoli, Aude
AU - Feron, Eric
N1 - Generated from Scopus record by KAUST IRTS on 2021-02-18
PY - 2020/2/1
Y1 - 2020/2/1
N2 - NextGen and ACARE Flightpath 2050 set some ambitious goals for air travel, including improving the passenger travel experience using door-to-door travel times as a possible metric. Using recently released Uber data along with other online databases, a reliable estimation of door-to-door travel times is possible, which then enables a comparison of cities performance regarding the good integration of their airports as well as a per segment analysis of the full trip. This model can also be used to better evaluate where progress should and can be made with respect to air passenger travel experience.
AB - NextGen and ACARE Flightpath 2050 set some ambitious goals for air travel, including improving the passenger travel experience using door-to-door travel times as a possible metric. Using recently released Uber data along with other online databases, a reliable estimation of door-to-door travel times is possible, which then enables a comparison of cities performance regarding the good integration of their airports as well as a per segment analysis of the full trip. This model can also be used to better evaluate where progress should and can be made with respect to air passenger travel experience.
UR - https://ieeexplore.ieee.org/document/9049179/
UR - http://www.scopus.com/inward/record.url?scp=85084193105&partnerID=8YFLogxK
U2 - 10.1109/AIDA-AT48540.2020.9049179
DO - 10.1109/AIDA-AT48540.2020.9049179
M3 - Conference contribution
SN - 9781728153803
BT - 2020 International Conference on Artificial Intelligence and Data Analytics for Air Transportation, AIDA-AT 2020
PB - Institute of Electrical and Electronics Engineers Inc.
ER -