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Origin-destination matrix estimation by deep learning using maps with New York case study.

, , and . MT-ITS, page 1-6. IEEE, (2021)

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Adjusting bus timetables considering observed delays and passenger numbers., , , , and . ITSC, page 585-590. IEEE, (2017)Dynamic pricing for ride-hailing services considering relocation and mode choice., and . MT-ITS, page 1-6. IEEE, (2021)Origin-destination matrix estimation by deep learning using maps with New York case study., , and . MT-ITS, page 1-6. IEEE, (2021)Generating and Calibrating a Microscopic Traffic Flow Simulation Network of Kyoto: First Insights from Simulating Private and Public Transport., , and . SUMO, volume 1 of SUMO Conference Proceedings, page 189-195. TIB Open Publishing, (2023)Implementation of a mobility behavior change support system in Manila Philippines., , and . ITSC, page 661-666. IEEE, (2017)Route choice effects of changes from a zonal to a distance-based fare structure in a regional public transport network., and . Public Transp., 12 (3): 535-555 (2020)The demand potential of shared autonomous vehicles: a large-scale simulation using mobility survey data, , , and . Journal of Intelligent Transportation Systems, (May 2023)Traffic Control: Current Systems and Future Vision of Cities., and . Int. J. Intelligent Transportation Systems Research, 8 (1): 56-65 (2010)A Large Scale Simulation of the Electrification Effects of SAVs, , and . Smart Energy for Smart Transport, page 115--124. Cham, Springer Nature Switzerland, (2023)Investigating the Impact of Ride Sharing on the Performance of One-way Car-sharing Systems., , and . ITSC, page 1-7. IEEE, (2020)