Forecasting Rail Transit Split with Disaggregated MNL Model

The paper focuses on the urban rail transit mode division, and studies the rail transit split forecasting by two stages. At the first stage, the transfer curve method is used to forecast the traffic composition without rail transit. At the second stage, selecting the time and cost as the characteristic variables of the utility function, the study estimates the diverting ratio from all traffic modes to rail and develops the disaggregate model based on revealed preference data and stated preference data survey. In the final section, the paper takes Suzhou city as example to calibrate the model parameters and forecasts rail transit split. The results indicate that the diverting ratio from conventional transit and bike to rail is high. The model improves the accuracy and practicality of the model with consideration of more factors affecting the resident travel mode choice.

摘要以城市轨道交通方式划分为研究对象，将轨道交通方式预测分两个阶段。第一阶段采用转移曲线法预测无轨道交通条件下的各种交通方式的比例结构，第二阶段选取时间、费用作为效用函数的特征变量，以交通行为调查的RP和SP联合数据为基础，计算了各种交通方式向轨道交通转移率，建立了应用于轨道交通方式预测的非集计MNL模型。最后以苏州城市轨道交通方式划分为例，进行了模型参数估计和轨道交通分担率的预测。结果表明，常规公交和自行车交通方式向轨道交通转移比例较高，该模型能较全面地考虑居民出行选择的各方面影响因素，模型的预测实用性较好。