Individual Travel Patterns and Rules Research Based on Campus Traffic Smart Card Data Mining
Establishing a research model based on the University of Wisconsin-Milwaukee(UWM)UPass smart card and real-time campus bus Automatic Vehicle Location(AVL)technology,collecting and comparing data.By mining UWM UPass and AVL data,con-structing passenger travel chains,and conducting corresponding analyses,a better understanding of passenger transportation characteris-tics can be achieved.Combining UWM UPass data with AVL data enables further investigation into individual travel patterns over a lar-ger time frame,facilitating rule classification through extensive travel chain computations.This analytical framework and methodology can provide technical support for transportation planning departments and operators to make scientific decisions regarding public trans-portation planning and operations.Additionally,the research methods outlined in this paper can serve as theoretical references and methodological guidance for domestic transportation planning and passenger flow analysis,thereby offering essential means for obtaining accurate and reliable public transit operation and passenger information.
万方数据
维普
