To enhance the testing efficiency of autonomous vehicles, it is essential to derive intelligent traffic test scenarios. Current methods face limitations such as reliance on subjective analysis and neglect of inter-element correlations. This study introduces Kalman particle filtering theory for high-dimensional traffic scenario derivation. By analyzing comprehensive energy fields in normalized scenes with various elements, we define benchmark scenes using field energy theory. Multi-level research is conducted on processing high-dimensional spatial element data, proposing a normative paradigm for weight allocation among scene elements. We perform generalized derivation by extending hierarchical elements based on offset values, meeting functional verification requirements. Simulation experiments comparing risk event detection, decision-making, and feedback behavior between the proposed method and actual driving data show a steering matching index of 0.92, a longitudinal speed matching index of 0.96, and an root mean squared error (RMSE) mean value of 0.06.

Solid-state batteries have garnered global attention due to their high energy density and safety, holding the potential to replace traditional lithium-ion batteries in the electric vehicle, alleviating "range anxiety". However, a comprehensive solid-state battery management system to complement these batteries has not yet been systematically proposed. We attempt to construct a management system for solid-state batteries based on various characteristics, considering both the demand- and supply-side. This review first introduces the advantages and disadvantages of polymer-based, oxide-based, and sulfide-based solid electrolytes, as well as anode and cathode materials with higher specific capacities and promising applications. It lists the cycling performance and safety demonstrated by assembled solid-state pouch cells. Then, we systematically analyzes the differences between all-solid-state batteries and traditional lithium-ion batteries, proposing the demands and development directions for all-solid-state battery management from multiple dimensions. Finally, we build an all-solid-state battery management system from aspects such as signal monitoring, model building, aging, and early warning of failure, which includes three parts: the electric management system, the thermal management system, and the pressure management system. This review aims to provide researchers with new insights and ideas, promoting the efficient development and industrial upgrading of battery management technology.

In real-world driving scenarios, understanding the intentions of pedestrians in real-time is critical for the built environment safety when operating intelligent vehicles on the roads. Pedestrians crossing the street is a common behavior that can easily lead to accidents. This paper presents a comprehensive review of the prediction of pedestrian crossing intentions, focusing on data, model structure, data representation, information extraction, prediction function, and associated models and challenges. The review highlights that data types, model generalization ability, and prediction uncertainty are key challenges on pedestrian crossing intention prediction. It identifies open challenges and opportunities for future research in pedestrian crossing intention prediction.

Aqueous zinc-ion batteries have emerged as a promising energy storage technology due to their intrinsic safety, cost-effectiveness, and environmental sustainability. However, practical deployment of aqueous zinc-ion batteries faces critical challenges related to zinc anode instability, including dendrite formation, hydrogen evolution, corrosion, and interfacial degradation. This review highlights recent advancements on modulating interfacial chemistry and designing robust solid electrolyte interphases (SEI) layers enriched with functional components to address these challenges. Strategies including advanced electrode/electrolyte interface engineering, functional electrolyte additives, and artificial SEI are explored for improving zinc metal anode stability and overall battery performance. Additionally, cutting-edge in-situ characterization techniques across various scales and dimensions are introduced, offering unprecedented insights into the SEI formation processes, dendrite suppression, and Zn²⁺ transport dynamics. By integrating functional interfacial designs with advanced characterization, this work outlines innovative approaches to improve zinc anode performance and realize high-efficiency, long-lifespan aqueous zinc-ion batteries.