累积logistic模型在出行强度预测中的应用

传统的出行生成预测模型使用集计的方法预测交通小区的平均出行次数,并未考虑出行者的个人属性及家庭属性,容易产生集计误差.通过乌鲁木齐居民出行调查数据建立了一个预测居民出行次数的累积logistic模型.结果表明,家庭年收入、公交服务水平、拥有交通工具状况和职业等因素对居民的出行次数有显著影响.通过分析得出,家庭年收入较高的群体、家中拥有摩托车或者自行车的群体、学生和公务员等出行强度较高.

Cumulative Logistic Model in the Forecast of the Trip Intensity

Traditional trip generation forecasting model uses the aggregated method to forecast the average trip times in trip zones,but seldom considers the traveler's individual and the family characteristic,this is easier to cause the aggregated error.This paper,through a survey data of the residents trip in Urumchi City,establishes a cumulative logistic model to forecast the residents trip times.The result of the model shows that the family annual income,the level of transit service,the condition of transportation means and the vocations have significant ffect on residents trip times.A conclusion is drawn from this analysis that the higher family annual income,the higher possission rate of bicycle or motorcycle,the higher trip intensity especially the groups like students and civil servants.