Research on Residents' Travel Behavior Based on Multiple Logistic Regression Model

Travel mode choices are the core points of travel behaviour analysis which is conducive to discovering the mechanism of residents' travel choices. In order to study the choice of urban residents' travel mode, this paper adopts the multiple logistic regression model to analyze three travel behavior characteristics of residents during the normalization period of the virus. The collected data were used for correlation analysis and model fitting analysis by R software. The collected data were used for correlation analysis and multicollinearity test by R software. The finding indicate that female residents are more inclined to choose private modes of transportation compared to men, and residents who work as civil servants and employees of public institutions have a significant impact on the mode of transportation, and more inclined to choose public mode of transportation. The more elderly people in a family, the more they tend to choose private transportation mode. And with the gradual improvement of the virus situation, residents are starting to prioritize convenience as their primary consideration for travel. Based on the analysis results of the model, suggestions for relevant traffic management measures are proposed to meet the various transportation needs of residents and ultimately improve the overall transportation efficiency of the city.