城市轨道交通非常态客流出行影响机制研究OA

In order to investigate the influence of multidimensional spatial attributes on the abnormal passenger flow travel mechanism of rail transit under abnormal weather conditions.Based on the gradient boosting decision tree model,we analyzed the extraordinary passenger flow travel characteristics of 143 stations in Tianjin under abnormal weather and resolved the nonlinear influence mechanism of 10 influencing factors such as economic attributes,traffic convenience and built environment on the abnormal passenger flow.The study found that:①Under abnormal weather,the average daily passenger flow of rail transit station increases significantly.97%of the average daily passenger flow at rail stations tended to increase due to weather conditions,with the largest increase of 32%at Tianjin Station.② The built environment has the most significant impact on the abnormal passenger flow of urban rail transit,reaching 86.44%,and the factor to the city center has the greatest degree of influence on the distance.③ There is a significant non-linear relationship and threshold effect between each influence factor and the abnormal passenger flow.Except for the number of bus stops,the number of intersections and the density of residential facilities,which show a fluctuating"convex"non-linear relationship with abnormal passenger flow,all other influencing factors maintain a non-linear positive or negative correlation.