Rapid urbanisation has intensified the need for sustainable solutions to address challenges
in urban infrastructure, climate change, and resource constraints. This study reveals that …

Instant delivery services, such as food delivery and package delivery, have achieved
explosive growth in recent years by providing customers with daily-life convenience. An …

Rapid urbanization has significantly escalated traffic congestion, underscoring the need for
advanced congestion prediction services to bolster intelligent transportation systems. As one …

The e-commerce sector is in a constant state of growth and evolution, particularly within its
subdomain of online food delivery. As such, ensuring customer satisfaction is critical for …

With the digitization of modern cities, large data volumes and powerful computational
resources facilitate the rapid update of intelligent models deployed in smart cities. Continual …

Intelligent logistics relies on accurately predicting the service time, which is a part of time
cost in the last-mile delivery. However, service time prediction (STP) is non-trivial given …

En Route Travel Time Estimation (ER-TTE) aims to learn driving patterns from traveled
routes to achieve rapid and accurate real-time predictions. However, existing methods …

We investigate the replay buffer in rehearsal-based approaches for graph continual learning
(GCL) methods. Existing rehearsal-based GCL methods select the most representative …

Intersections are known to cause significant changes in traffic states. However, existing link-
level trajectory optimization methods often overlook intersection information, making it …

Trajectory representation learning (TRL) maps trajectories to vectors that can be used for
many downstream tasks. Existing TRL methods use either grid trajectories, capturing …