Driver Behavior Modeling with Subjective Risk‐Driven Inverse Reinforcement Learning
A subjective risk‐driven inverse reinforcement learning framework is proposed to model driver decision‐making. It infers drivers' risk perception and risk tolerance from driving data. A learnable risk threshold is used to regulate decisions, enabling interpretable and human‐like driving behavior decisions.
Yang Liang +6 more
wiley +1 more source
Research on Robot Collision Response Based on Human-Robot Collaboration. [PDF]
Zhong S, Xu C, Chen G, Xu Y, Wang Z.
europepmc +1 more source
Beyond PEGylation: Archaeal Lipids for Long‐Circulating Liposomes
Archaeal lipid‐based liposomes, particularly those containing caldarchaeol (GDGT), were found to significantly prolong the circulation time of vancomycin in rats, matching the pharmacokinetic properties of PEGylated systems. These findings suggest archaeal lipids as promising non‐PEG excipients for parenteral applications to minimize drug clearance ...
Viktor Sedlmayr +9 more
wiley +1 more source
Concrete multi-agent path planning enabling kinodynamically aggressive maneuvers. [PDF]
Okumura K +4 more
europepmc +1 more source
ECE-VDTDA: A robust and computationally efficient collision avoidance system for driver assistance in foggy weather. [PDF]
Raza N +7 more
europepmc +1 more source
Deep Reinforcement Learning for Autonomous Underwater Navigation: A Comparative Study with DWA and Digital Twin Validation. [PDF]
Mari Z, Nawaf MM, Drap P.
europepmc +1 more source
Bio-Inspired Reactive Approaches for Automated Guided Vehicle Path Planning: A Review. [PDF]
Lin S, Wang J, Kong X.
europepmc +1 more source
ABSTRACT Drilling fluids used in high‐performance well operations often struggle to maintain rheological stability, colloidal dispersion, and filtration control under harsh downhole conditions. This study engineered a multifunctional Fe3O4@Saponin/Cu(II) nanocomposite to address these challenges.
Kassem Al Attabi +9 more
wiley +1 more source
Harnessing multi-modal deep learning for multi-drone navigation-based trajectory prediction system. [PDF]
Alzahrani A.
europepmc +1 more source
Complexity Analysis of Bubble Plumes in Power Law Fluids Based on Chaos Theory
ABSTRACT In order to reveal the complexity of the internal flow of bubble plume in power law fluid, the flow characteristics and chaotic characteristics of plume are studied by experiment and theory. The chaotic characteristic parameters (correlation dimension D, K entropy, and Lyapunov exponent λ) of gas velocity under different superficial gas ...
Xin Dong +6 more
wiley +1 more source

