Future directions in human mobility science
We provide a brief review of human mobility science and present three key areas where we
expect to see substantial advancements. We start from the mind and discuss the need to …
expect to see substantial advancements. We start from the mind and discuss the need to …
A survey on trajectory data management, analytics, and learning
Recent advances in sensor and mobile devices have enabled an unprecedented increase
in the availability and collection of urban trajectory data, thus increasing the demand for …
in the availability and collection of urban trajectory data, thus increasing the demand for …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Outlier detection for multidimensional time series using deep neural networks
Due to the continued digitization of industrial and societal processes, including the
deployment of networked sensors, we are witnessing a rapid proliferation of time-ordered …
deployment of networked sensors, we are witnessing a rapid proliferation of time-ordered …
A survey on trajectory data mining: Techniques and applications
Rapid advance of location acquisition technologies boosts the generation of trajectory data,
which track the traces of moving objects. A trajectory is typically represented by a sequence …
which track the traces of moving objects. A trajectory is typically represented by a sequence …
Learning effective road network representation with hierarchical graph neural networks
Road network is the core component of urban transportation, and it is widely useful in
various traffic-related systems and applications. Due to its important role, it is essential to …
various traffic-related systems and applications. Due to its important role, it is essential to …
Controltraj: Controllable trajectory generation with topology-constrained diffusion model
Generating trajectory data is among promising solutions to addressing privacy concerns,
collection costs, and proprietary restrictions usually associated with human mobility …
collection costs, and proprietary restrictions usually associated with human mobility …
A big data-as-a-service framework: State-of-the-art and perspectives
Due to the rapid advances of information technologies, Big Data, recognized with 4Vs
characteristics (volume, variety, veracity, and velocity), bring significant benefits as well as …
characteristics (volume, variety, veracity, and velocity), bring significant benefits as well as …
Integrating Dijkstra's algorithm into deep inverse reinforcement learning for food delivery route planning
In China, rapid development of online food delivery brings massive orders, which relies
heavily on deliverymen riding e-bikes. In practice, actual delivery routes of most orders are …
heavily on deliverymen riding e-bikes. In practice, actual delivery routes of most orders are …
Finding top-k shortest paths with diversity
The classical K Shortest Paths (KSP) problem, which identifies the k shortest paths in a
directed graph, plays an important role in many application domains, such as providing …
directed graph, plays an important role in many application domains, such as providing …