A Data-Driven Car-Following Model Based on the Random Forest

The car-following models are the research basis of traffic flow theory and microscopic traffic simulation. Among the previous work, the theory-driven models are dominant, while the data-driven ones are relatively rare. In recent years, the related technologies of Intelligent Transportation System (ITS) re- presented by the Vehicles to Everything (V2X) technology have been developing rapidly. Utilizing the related technologies of ITS, the large-scale vehicle microscopic trajectory data with high quality can be acquired, which provides the research foundation for modeling the car-following behavior based on the data-driven methods. According to this point, a data-driven car-following model based on the Random Forest (RF) method was constructed in this work, and the Next Generation Simulation (NGSIM) dataset was used to calibrate and train the constructed model. The Artificial Neural Network (ANN) model, GM model, and Full Velocity Difference (FVD) model are em- ployed to comparatively verify the proposed model. The research results suggest that the model proposed in this work can accurately describe the car- following behavior with better performance under multiple performance indicators.

Lithium-storage properties of SiO_(2)nanotubes@C using carbon nanotubes as templates

Silica-based anode material is the most concerned material at present,which has the advantages of good cycle stability,high theoretical specific capacity and abundant reserves.However,silica suffers from inherent low conductivity,severe volume expansion effect and low initial coulombic efficiency,which limits its application in lithium-ion batteries.Nanotubes structure can mitigate the volume expansion during lithiation/delithiation.In this article,silica nanotubes(SNTs)were prepared using carbon nanotubes(CNTs)as a template,and then the uniform carbon layer was coated on their surface by carbonization of citric acid.The hollow structure of nanotubes provides more sites for the insertion of Li+during lithiation and additional channels for Li+migration in the cycles,which improves the electrochemical performance.Conductivity can be enhanced by coating carbon layer.The specific capacity of the composite material is about 650 mAh g^(-1)at 0.1 A g^(-1)after 100 cycles.With a specific capacity of 400 mAh g^(-1)even at 1 A g^(-1)after 100 cycles.The silica-based material is a competitive anode material for lithium-ion batteries.