Dynamic Demand Forecast and Assignment Model for Bike-and-Ride System

Bike-and-Ride (B&R) has long been considered as an effective way to deal with urbanization-related issues such as traffic congestion, emissions, equality, etc. Although there are some studies focused on the B&R demand forecast, the influencing factors from previous studies have been excluded from those forecasting methods. To fill this gap, this paper proposes a new B&R demand forecast model considering the influencing factors as dynamic rather than fixed ones to reach higher forecasting accuracy. This model is tested in a theoretical network to validate the feasibility and effectiveness and the results show that the generalised cost does have an effect on the demand for the B&R system.</p

Traffic Risk Assessment Based on Warning Data

To address the issues of insufficient danger excavation and long data collection period in traditional traffic risk assessment methods, this paper proposes a risk assessment method based on driver’s improper driving behavior and abnormal vehicle state warning data. Meanwhile, this paper analyses the built environment’s impact on traffic risk using the spatial econometric model. Firstly, a risk assessment system with the relative incidence of driver’s improper driving behavior (eye closure, yawn, and looking away) and abnormal vehicle state (rapid acceleration, rapid deceleration, and lane departure) warnings as assessment indicators is constructed. Then, the risk responsibility weights of each warning type were determined using the entropy weight method. The risk classification thresholds were determined based on the Gaussian Mixture Model algorithm. Finally, a spatial econometric model was used to quantify the impact of built environment factors characterized by Point of Interest (POI) data on regional traffic risk, with the results of risk class classification as the dependent variable. The data of bus vehicle warnings in Zhenjiang, Jiangsu Province, are employed as an example for validation. The geographic cell of 1 km × 1 km scale is applied as the basic risk assessment unit. The results show that the optimal risk classification threshold for road traffic risk levels I and II is 1.92, the accuracy rate of class classification is 79.3%; the optimal risk classification threshold for levels II and III is 0.75, and the accuracy rate of class classification is 83.4%. The number of residential areas, Point of Interest (POI) mixing degree, and bus stops were significantly and positively correlated with transit traffic risk. The study results provide references for developing customized accident prevention measures and the appropriate setting of urban supporting facilities

Facile spray drying synthesis of porous structured ZnFe2O4 as high-performance anode material for lithium-ion batteries

Porous ZnFe2O4 nanorods have been successfully prepared by a simple spray-drying process followed by sintering. The structure and morphology of the samples were characterized by X-ray diffraction, field emission scanning electron microscopy and transmission electron microscopy. The porous structured ZnFe2O4 materials are successfully used as potential anode material for lithium-ion batteries. Electrochemical results show that the anodes exhibit good cycling performance and rate capability. The anode exhibits initial discharge capacity of approximately 1459 mAh g−1 with an initial coulombic efficiency of 77.8% at a constant density of 100 mA g−1. The discharge capacity of the ZnFe2O4 retained 1458 mA h g−1 after 120 cycles at the current rate of 100 mA g−1 and 456 mA h g−1 could be obtained at the current density of 5000 mA g−1 after 200 cycles. The discharge capacities can still be as high as 778 mAh g−1 at a high rate of 3000 mA g−1. Such remarkable electrochemical properties could be ascribed to the unique porous morphology with large surface area and porosity that were beneficial to facilitate the diffusion of Li ions and electrolyte into the electrodes, meanwhile prevent volume expansion/contraction during lithiation/dislithiation processes