Chunfu Shao

TL;DR: A simulation of bi-direction pedestrian flow based on cellular automata (CA) will be presented from two aspects: direction split and pedestrians’ walking habit, and it is found that there are phase transitions at the critical density point, and the pedestrian flow shows distinctive characteristics at different phases with different relationships of velocity–density and flow–density.

TL;DR: The findings suggest that the proposed model is a superior alternative for traffic crash predictions and the average accuracy of the prediction can be improved by 84.58% and 158.27% compared to the deep learning model without the regression layer and the SVM model, respectively.

TL;DR: In this article, the authors focused on the six typical factors potentially influencing the purchase behavior of EVs in Beijing, China, namely vehicle price, vehicle usage, social influence, environmental awareness, purchase-related policies and usage related policies, and found that vehicle price and usage tend to be more influential among the six factors, accounting for 32.3% and 28.1% of the importance, respectively.

TL;DR: The results demonstrate that the proposed models are superior to ARIMA models, which ignores the spatial component of the spatial–temporal patterns, and suggest that the NSS model is a better alternative for flow rate prediction under non-congestion conditions, and the CSS model is an improved alternative for time mean speed prediction under congestion conditions.

TL;DR: The results suggest that the forecasting ability of the RLC–REP model in terms of real estate price is satisfactory, and both utility maximization theory and prospect theory were used to develop a utility function to simulate the location choice behavior of active household agents.