摘要
对智能公交系统IC卡数据、GPS数据挖掘与应用问题进行了研究,构建了基于公交站点下车概率的乘客下车站点推算模型.该模型提取公交乘客通勤、随机出行等行为链,考虑站点吸引权及当次乘车方向下游站点数等影响因素,判断随机出行下车站点.针对该模型提出了乘客下车站点判断算法,并设计了模型的检验方法.以青岛市11路公交为例验证算法,检验回归方程系数值为1.0211.结果表明,该算法能实现乘客下车站点有效推算,具有良好可靠性.
This paper studies the IC card data,GPS data mining and application of the intelligent public transportation system.A bus passenger alighting stop model based on the probabilities of alighting stops was constructed.The model fully analyzed bus passenger commuting,random travel and other travel behaviors,and estimated the alighting stops of random-travelling passengers,considering the influencing factors such as alighting attraction weighting of stops and the number of downstream stops in the current direction.Then we proposed an algorithm to estimate the alighting stops and design a method to test this mode.The Line 11 in Qingdao was taken as an example to test the algorithm.and the regression coefficient was 1.0211.The results show that this algorithm model is reliable and can effectively identify the alighting stops.
作者
张志熙
陈玲娟
ZHANG Zhixi;CHEN Lingjuan(School of Automobile and Traffic Engineering,Wuhan University of Science and Technology,Wuhan 430081,China)
出处
《昆明理工大学学报（自然科学版）》
CAS
北大核心
2021年第1期142-149,共8页
Journal of Kunming University of Science and Technology(Natural Science)
基金
教育部人文社会科学研究青年基金项目(19YJCZH007)
武汉科技大学2018年国家级大学生创新创业训练计划项目(201810488027)。
关键词
智能交通
数据挖掘
出行行为
下车站点
数据分析
intelligent transportation
data mining
travel behavior
alighting stop
data analysis
