[HTML][HTML] How machine learning informs ride-hailing services: A survey
In recent years, online ride-hailing services have emerged as an important component of
urban transportation system, which not only provide significant ease for residents' travel …
urban transportation system, which not only provide significant ease for residents' travel …
[HTML][HTML] A/B testing: A systematic literature review
A/B testing, also referred to as online controlled experimentation or continuous
experimentation, is a form of hypothesis testing where two variants of a piece of software are …
experimentation, is a form of hypothesis testing where two variants of a piece of software are …
Spatio-temporal graph neural networks for predictive learning in urban computing: A survey
With recent advances in sensing technologies, a myriad of spatio-temporal data has been
generated and recorded in smart cities. Forecasting the evolution patterns of spatio-temporal …
generated and recorded in smart cities. Forecasting the evolution patterns of spatio-temporal …
Machine learning for next‐generation intelligent transportation systems: A survey
T Yuan, W da Rocha Neto… - Transactions on …, 2022 - Wiley Online Library
Intelligent transportation systems, or ITS for short, includes a variety of services and
applications such as road traffic management, traveler information systems, public transit …
applications such as road traffic management, traveler information systems, public transit …
Multi-attention graph neural networks for city-wide bus travel time estimation using limited data
An important factor that discourages patrons from using bus systems is the long and
uncertain waiting times. Therefore, accurate bus travel time prediction is important to …
uncertain waiting times. Therefore, accurate bus travel time prediction is important to …
Cross-area travel time uncertainty estimation from trajectory data: a federated learning approach
Along with urbanization and the deployment of GPS sensors in vehicles and mobile phones,
massive amounts of trajectory data have been generated for city areas. The analysis of …
massive amounts of trajectory data have been generated for city areas. The analysis of …
Lightpath: Lightweight and scalable path representation learning
Movement paths are used widely in intelligent transportation and smart city applications. To
serve such applications, path representation learning aims to provide compact …
serve such applications, path representation learning aims to provide compact …
A survey on graph neural network acceleration: Algorithms, systems, and customized hardware
Graph neural networks (GNNs) are emerging for machine learning research on graph-
structured data. GNNs achieve state-of-the-art performance on many tasks, but they face …
structured data. GNNs achieve state-of-the-art performance on many tasks, but they face …
Interpreting trajectories from multiple views: A hierarchical self-attention network for estimating the time of arrival
Z Chen, X Xiao, YJ Gong, J Fang, N Ma… - Proceedings of the 28th …, 2022 - dl.acm.org
Estimating the time of arrival is a crucial task in intelligent transportation systems. Although
considerable efforts have been made to solve this problem, most of them decompose a …
considerable efforts have been made to solve this problem, most of them decompose a …
Software escalation prediction based on deep learning in the cognitive internet of vehicles
In the Cognitive Internet of Vehicles (CIoV), vehicles, road side units (RSU) and other key
nodes have been equipped with more and more software to support intelligent …
nodes have been equipped with more and more software to support intelligent …