Risk assessment is a crucial component of collision warning and avoidance systems for intelligent vehicles. Reachability-based formal approaches have been developed to ensure driving safety to accurately detect potential vehicle collisions. However, they suffer from over-conservatism, potentially resulting in false–positive risk events in complicated real-world applications. In this paper, we combine two reachability analysis techniques, a backward reachable set (BRS) and a stochastic forward reachable set (FRS), and propose an integrated probabilistic collision–detection framework for highway driving. Within this framework, we can first use a BRS to formally check whether a two-vehicle interaction is safe; otherwise, a prediction-based stochastic FRS is employed to estimate the collision probability at each future time step. Thus, the framework can not only identify non-risky events with guaranteed safety but also provide accurate collision risk estimation in safety–critical events. To construct the stochastic FRS, we develop a neural network-based acceleration model for surrounding vehicles and further incorporate a confidence-aware dynamic belief to improve the prediction accuracy. Extensive experiments were conducted to validate the performance of the acceleration prediction model based on naturalistic highway driving data. The efficiency and effectiveness of the framework with infused confidence beliefs were tested in both naturalistic and simulated highway scenarios. The proposed risk assessment framework is promising for real-world applications.

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The energy matching of PV driven air conditioners is influenced by building load demand and PV generation. Merely increasing energy performance of building or PV capacity separately may improve the energy balance on a large time resolution, the real-time energy mismatching problem is still serious. In this study, a coordinated optimization method of PV capacity, building design, and load flexibility is proposed for improving the real-time energy matching of PVAC system. Then, a methodology integrating data mining method (XG Boost) and parametric simulation was developed to identify the determinant parameters of PV system and building design, exploring feature importance and correlations. The results of XG Boost indicate that the PV capacity, shape factor, and SHGC are the most critical factors. Finally, based on the optimized building design, the PCM layer was applied to improve the real time energy matching. To achieve a goal of 90 % ZEP, the PCM capacity can be decreased by 50.4 % and 62.8 % in Guangzhou and Shanghai in the optimized building. Moreover, the PV capacity can be reduced by 23 % in Guangzhou. The findings of this study provide practical guidance for designing PVAC system coupling with building design and energy storage devices.@en

Iodine vacancies and uncoordinated iodide ions of CsPbI₃ films are mainly responsible for nonradiative recombination. Here, we report a composition-engineering passivation method that through guanidium (GA⁺) and I⁻ forms strong hydrogen bonds to passivate iodine vacancies and reduce defects. Both experimental and theoretical results confirmed strong chemical interactions between GA⁺ and uncoordinated I⁻ in the GA_xCs_1−xPbI₃ bulk or at the grain boundary. Moreover, GA⁺ doping could slow down the crystallization speed of perovskite films during the deposition process. As a result, we observed GA⁺ modified films with much lower defect density, larger grain size, and better carrier extraction and transportation. Upon GA⁺ passivation, the power conversion efficiency (PCE) is boosted from 18.01% to 19.05%, with open-circuit voltage (V_OC) enhancement from 1.08 V to 1.14 V.

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Due to the limitation of the geological environment, many railways around the world are built in desert areas. The intrusion of sand particles can increase the stiffness of ballast beds and cause corrosion and fracture of fasteners, turnout blockage, etc., even affecting the service safety of railways. In the paper, based on the results of field and laboratory tests, a three-dimensional discrete element model of the sandy ballast bed is developed to study the effect of sand intrusion on the load sharing ratio of sleepers, contact forces between ballast particles, displacements of ballast particles, and energy dissipation in ballast beds. The results show that the axle load in sandy tracks is mainly shared by three sleepers under the single-axle load and six sleepers under the dual-axle load. The maximum contact force under the sleeper in the sandy ballast bed is about 80% larger than that in the clean ballast bed and its normal and tangential contact forces are also larger than that in the clean ballast bed. The ballast particles at the ballast shoulder of the clean ballast bed move downward in the direction of less than 45°, while those in the sandy ballast bed move outward at the direction of 90°. The sand intrusion inhibits the movement of ballast particles and may cause a rheological phenomenon of ballast particles at the ballast shoulder. The intrusion of sand particles mainly affects the elastic strain energy and damping energy in ballast beds but has less effect on friction energy and kinetic energy.@en