A systematic literature review on machine learning in shared mobility

J Teusch, JN Gremmel, C Koetsier… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Shared mobility has emerged as a sustainable alternative to both private transportation and
traditional public transport, promising to reduce the number of private vehicles on roads …

Resilience model and recovery strategy of transportation network based on travel OD-grid analysis

X Pan, Y Dang, H Wang, D Hong, Y Li… - Reliability Engineering & …, 2022 - Elsevier
Transportation is the key to a city's prosperity, however, there is possibility that the
development and expansion of city make the transportation system complicated, uncertain …

Synthesizing realistic trajectory data with differential privacy

X Sun, Q Ye, H Hu, Y Wang, K Huang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicle trajectory data is critical for traffic management and location-based services.
However, the released trajectories raise serious privacy concerns because they contain …

The pulse of urban transport: Exploring the co-evolving pattern for spatio-temporal forecasting

J Deng, X Chen, Z Fan, R Jiang, X Song… - ACM Transactions on …, 2021 - dl.acm.org
Transportation demand forecasting is a topic of large practical value. However, the model
that fits the demand of one transportation by only considering the historical data of its own …

Exploiting spatiotemporal correlations of arrive-stay-leave behaviors for private car flow prediction

C Liu, Z Xiao, D Wang, L Wang, H Jiang… - … on Network Science …, 2021 - ieeexplore.ieee.org
Accurate prediction of private car flows in urban regions is strategically vital for constructing
smart cities. Private car flows are essentially reflected in the arrive-stay-leave (ASL) …

Gallat: A spatiotemporal graph attention network for passenger demand prediction

Y Wang, H Yin, T Chen, C Liu, B Wang… - 2021 IEEE 37th …, 2021 - ieeexplore.ieee.org
Online ride-hailing services have become an important component of urban transportation in
recent years. As a fundamental research problem for such services, the timely prediction of …

Passenger mobility prediction via representation learning for dynamic directed and weighted graphs

Y Wang, H Yin, T Chen, C Liu, B Wang, T Wo… - ACM Transactions on …, 2021 - dl.acm.org
In recent years, ride-hailing services have been increasingly prevalent, as they provide huge
convenience for passengers. As a fundamental problem, the timely prediction of passenger …

A framework for spatial-temporal trajectory cluster analysis based on dynamic relationships

I Portugal, P Alencar, D Cowan - IEEE Access, 2020 - ieeexplore.ieee.org
In spatial-temporal data analysis, location data and its evolution through time are
investigated with the goal of uncovering important information to provide novel insights …

BM-DDPG: An integrated dispatching framework for ride-hailing systems

J Gao, X Li, C Wang, X Huang - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
This paper proposes an integrated dispatching framework for matching drivers with riders in
ride-hailing systems. The goal is to compute matching solutions that maximize social welfare …

A joint passenger flow inference and path recommender system for deploying new routes and stations of mass transit transportation

F Lin, HP Hsieh - ACM Transactions on Knowledge Discovery from Data, 2021 - dl.acm.org
In this work, a novel decision assistant system for urban transportation, called Route
Scheme Assistant (RSA), is proposed to address two crucial issues that few former …