Modelling time-of-travel preferences capturing correlations between departure times and activity durations
提出一种新的多项式函数形式来刻画出行者出发时间与活动持续时间之间的相关性，并用孟加拉国达卡的通勤数据验证，相比现有三角函数模型能更真实地预测出行时间，有助于设计高峰疏导政策。
Departure time choice models quantify the relative impacts of the factors affecting travellers' departure time selection and help design targeted peak-spreading policies. The departure time preference of travellers is traditionally captured using parameters associated with different alternatives along three aspects – outbound, return, and duration. In reality, departure time decisions for outbound and return legs, and the corresponding activity durations, are interrelated in most cases. However, none of the previous departure time choice models has explicitly investigated the impact of this potential correlation on model outputs. To address this gap in the existing literature, we proposed a model structure with a novel polynomial functional form of alternative specific constants (ASCs) that captures this correlation in a joint (outbound and return) departure time choice model. A revealed preference (RP) dataset from Dhaka, Bangladesh, was used to model the joint departure time preferences of the car commuters. The proposed model was then compared with a state-of-the-art model that uses a trigonometric formulation of the ASCs. Results indicate that the proposed formulation yields more behaviourally realistic outputs compared to the trigonometric model by explicitly capturing the correlation between departure time and duration. While the specific outputs are applicable to car commuters residing in Dhaka, Bangladesh, the framework can be applied to better predict departure times and improve the formulations of the peak spreading policies in other contexts as well.