Automated vehicles (AVs) aim to dramatically improve traffic safety by reducing or
eliminating human error, which remains the leading cause of road crashes. However …

Crowd stampedes and incidents are critical threats to public security that have caused
countless deaths during the past few decades. To avoid crowd stampedes, real-time crowd …

Abstract In Internet of Things (IoT) applications, federated learning is commonly used for
distributedly training models in a privacy-preserving manner. Recently, federated learning is …

Accurate and efficient pedestrian detection is crucial for the intelligent transportation system
regarding pedestrian safety and mobility, eg, Advanced Driver Assistance Systems, and …

Driver attention prediction can solve the problem of 'Where should the driver pay attention?',
Most previous methods are designed to predict regional attention with redundant regions …

Understanding and representing traffic patterns are key to detecting anomalous trajectories
in the transportation domain. However, some trajectories can exhibit heterogeneous …

Short term forecasting is essential and challenging in time series data analysis for traffic flow
research. A novel deep learning architecture on short-term traffic flow prediction was …

The rapid development of urbanization has raised challenges for existing parking facilities to
serve increasing parking demand. Being constrained by the limited urban land resources for …

Over the years, the urban planning literature has focused substantial attention on walkability
research, aiming to enhance physical activity and sustainable communities through urban …

The direct yaw moment control can effectively enhance the yaw stability of the vehicle under
extreme conditions, which has become one of the essential technologies for the distributed …