Meta-learning over time for destination prediction tasks

M Tenzer, Z Rasheed, K Shafique… - Proceedings of the 30th …, 2022 - dl.acm.org
A need to understand and predict vehicles' behavior underlies both public and private goals
in the transportation domain, including urban planning and management, ride-sharing …

Forecasting taxi demands using generative adversarial networks with multi-source data

HAH Naji, Q Xue, H Zhu, T Li - Applied Sciences, 2021 - mdpi.com
As a popular transportation mode in urban regions, taxis play an essential role in providing
comfortable and convenient services for travelers. For the sake of tackling the imbalance …

Taxi demand prediction using an LSTM-based deep sequence model and points of interest

B Askari, T Le Quy, E Ntoutsi - 2020 IEEE 44th Annual …, 2020 - ieeexplore.ieee.org
Nowadays, urban mobility plays an important role in modern cities for city planning,
navigation, and other mobility services. Taxicabs are vital public services in large cities that …

[HTML][HTML] Supply level planning for shared e-scooters considering spatiotemporal heteroscedastic demand

N Saum, M Piantanakulchai, S Sugiura - Transportation research …, 2024 - Elsevier
Accurate demand forecasting is a key success for mobility service businesses, especially
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …

Taxi‐demand forecasting using dynamic spatiotemporal analysis

A Gangrade, P Pratyush, G Hajela - ETRI Journal, 2022 - Wiley Online Library
Taxi‐demand forecasting and hotspot prediction can be critical in reducing response times
and designing a cost effective online taxi‐booking model. Taxi demand in a region can be …

Learning citywide patterns of life from trajectory monitoring

M Tenzer, Z Rasheed, K Shafique - Proceedings of the 30th International …, 2022 - dl.acm.org
The recent proliferation of real-world human mobility datasets has catalyzed geospatial and
transportation research in trajectory prediction, demand forecasting, travel time estimation …

An Ensemble Machine Learning Model To Predictive Analysis of End to End Uber Data

S Tanniru, H Tummala, K Kodali… - 2024 Asia Pacific …, 2024 - ieeexplore.ieee.org
Accurately predicting both daily and monthly transactions is crucial for businesses, providing
invaluable insights to analyze fluctuations and formulate strategic plans effectively. This …

[PDF][PDF] Transportation Research Interdisciplinary Perspectives

N Saum, M Piantanakulchai, S Sugiura - researchgate.net
Accurate demand forecasting is a key success for mobility service businesses, especially
shared electric (e-) scooters, for their volatile demand, high operational costs, and strict …