As accurate and timely traffic flow information is extremely important for traffic management,
traffic flow prediction has become a vital component of intelligent transportation systems …

In recent years, various deep learning architectures have been proposed to solve complex
challenges (eg spatial dependency, temporal dependency) in traffic domain, which have …

IoT-driven intelligent transportation systems (ITS) have great potential and capacity to make
transportation systems efficient, safe, smart, reliable, and sustainable. The IoT provides the …

Fog computing has been merged with Internet of Vehicle (IoV) systems to provide
computational resources for end users, by which low latency can be guaranteed. In this …

The concept of Connected and Automated Vehicles (CAVs) enables instant traffic
information to be shared among vehicle networks. With this newly proposed concept, a …

As one of the most promising applications in future Internet of Things, Internet of Vehicles
(IoV) has been acknowledged as a fundamental technology for developing the Intelligent …

This paper proposes a novel incremental training mode to address the problem of Deep
Reinforcement Learning (DRL) based path planning for a mobile robot. Firstly, we evaluate …

This paper capitalizes on the increasingly high relevance gained by data-intensive
technologies in the development of intelligent transportation system, which calls for the …

The present era is marked by rapid improvement and advances in technology. One of the
most essential areas that demand improvement is the traffic signal, as it constitutes the core …

As the basic system of the rescue robot, the SLAM system largely determines whether the
rescue robot can complete the rescue mission. Although the current 2D Lidar‐based SLAM …