Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving

In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing and understanding for an increasingly complex driving environment. To incorporate the...

A Looseness Detection Method for Railway Catenary Fasteners based on Reinforcement Learning Refined Localization

Brace sleeve (BS) fasteners, i.e., nut and bolt, are small components but play essential roles in fixing BS and cantilever in railway catenary system. They are commonly inspected by onboard cameras using computer vision to ensure the safety of railway operation. However, most BS fasteners cannot be directly localized because they are too...

Action-driven Reinforcement Learning for Improving Localization of Brace Sleeve in Railway Catenary

Brace Sleeve (BS) plays an essential role in connecting and fixing cantilevers of railway catenary systems. It needs to be monitored to ensure the safety of railway operations. In the literature, image processing techniques that can localize BSs from inspection images are proposed. However, the boxes produced by existing methods can contain...

Experimental and numerical study on behaviour of square steel tube confined reinforced concrete stub columns after fire exposure

The behaviour of square steel tube confined reinforced concrete columns after fire exposure was studied experimentally and numerically in this paper. Eighteen stub columns were first heated following the ISO 834 standard fire including both heating and cooling phases, and were subsequently loaded to failure after cooling to ambient temperature....