Research on the Influencing Factors of Slow Traffic on Campuses Based on Data Analysis: A Case Study of the South Campus of Henan Polytechnic University

Abstract

With the continuous development of campus construction, university faculty and students have higher requirements for the quality of the campus commuting environment. However, the supply situation of most of the campus spatial configurations in China still cannot meet the slow traffic needs. Therefore, taking the South Campus of Henan Polytechnic University as the object, this paper adopts a quantitative research method with data through field research and questionnaire distribution, and uses machine learning Apriori algorithm to analyze the data association rules. A selection model of factors affecting the slow traffic was constructed to excavate factors related to the slow traffic in campus. Meanwhile, significantly related road spatial environment factors and the specific conditions of the campus were combined to propose improvement, so as to encourage faculty and students to participate in slow traffic which is good for health.