Accurate traffic state (ie, flow, speed, density, etc.) on an urban road network is important
information for urban traffic control and management strategies. However, due to the …

Big data have been used widely in many areas, including the transportation industry. Using
various data sources, traffic states can be well estimated and further predicted to improve the …

Smart cities and villages present a plethora of opportunities for fusing and managing multi-
source data. However, in the analysis of mobility patterns, the use of only one data source …

Understanding the spatiotemporal characteristics of traffic congestion is the cornerstone of
generating traffic management and control strategies. Based on the large-scale taxi …

Sensing network-wide traffic information is fundamental for the sustainable development of
urban planning and traffic management. However, owing to the limited budgets or device …

In response to the critical need for rapid post-disaster assessments, this paper introduces an
innovative application of artificial intelligence (AI) in Unmanned Aerial Vehicles (UAVs) for …

In modern traffic management, one of the most essential yet challenging tasks is accurately
and timely predicting traffic. It has been well investigated and examined that deep learning …

Traffic forecasting is an important prerequisite for the application of intelligent transportation
systems in urban traffic networks. The existing works adopted RNN and CNN/GCN, among …

With the continued deployment of the Internet of Things (IoT), increasing volumes of devices
are being deployed that emit massive spatially referenced data. Due in part to the dynamic …

Port plays a key role in maintaining traffic flows and the effectiveness of global maritime
logistics. However, the vulnerability of the Global Container Shipping Network (GCSN) is …