基于出行方式和活动交互作用的小汽车使用预测模型

Car use model based on tour mode and activity choice interdependencies

为改进我国传统小汽车出行需求预测方法,基于活动理论建立了小汽车使用预测非集计模型.从小汽车使用者活动模式的统计分析入手,对小汽车使用模式进行划分,在多项Logit(MNL)模型的基础上建立协同进化Logit小汽车使用预测模型.模型中采用协同进化方法计算确定了个体出行活动选择顺序,体现了小汽车使用者出行方式选择和活动的交互作用.模型适应性分析表明,该模型可用于城市小汽车出行需求预测和交通需求管理政策的评价.以沈阳市为例对模型进行了实例分析,结果表明模型预测正确率达88.9%,65%以上的小汽车使用者先确定小汽车使用模式再进行活动模式的选择,验证了出行活动选择顺序的个体差异性,提高了小汽车出行需求预测方法的精度.

To improve the conventional car travel forecasting method,an active-based car use model has been constructed.Firstly,the activity pattern of car user was statistically analyzed,and the car use patterns was classified,then a co-evolutionary Logit car use prediction model was built based on MNL（multinomial Logit） models.The co-evolutionary method can present the interdependence between tour mode and activity choice,and emulate the decision order of tour mode and activity choice.The adaptive analysis proves that the model can be used for travel demand forecasting and transportation demand management policy evaluation.The data from Shenyang city is taken as an example in this paper.Results indicate that 88.9% forecasting results of the new model are correct,in 65% cases the activity decisions are made after the car use choice.The model fully verifies the variation of tour mode and activity choice decision order,thus the accuracy of car travel prediction is improved.