Travel Demand Forecasts Improved by Using Cross-Sectional Data from Multiple Time Points
Travel Demand Forecasts Improved by Using Cross-Sectional Data from Multiple Time Points
复制标题
通过使用多个时间点的横截面数据改进旅行需求预测
DOI：
10.1007/s11116-013-9464-7
复制
发表时间：
2013
期刊：
影响因子：
4.3
通讯作者：
Sanko,N.
中科院分区：
文献类型：
--
作者：
Harada;S;Sanko,N.
对旅行需求的预测往往是基于最近时间点的数据，即使有多个时间点的横截面数据。这是因为具有相似上下文的预测模型具有更高的可移植性，并且最近时间点的上下文被认为与未来时间点的上下文最相似。在本文中，作者提出了一种方法，不仅利用最近的数据集，但也旧的数据集，以提高预测性能的非集计的出行需求模型。作者假设这些参数是时间的函数，这意味着可以预测未来的参数值。这些预测参数然后用于交通需求预测。本文介绍了一个案例研究的旅程工作模式选择分析在名古屋，日本，使用1971年，1981年，1991年和2001年收集的数据。2001年的行为预测使用的模型只有最近的1991年的数据集和模型，结合了1971年，1981年和1991年的数据集联合收割机。作者提出的模型使用三个时间点的数据可以提供更好的预测。本文还讨论了表达参数变化的函数形式和问题的时间可转移性，不仅替代特定的常数，而且水平的服务和社会经济参数。
Forecasts of travel demand are often based on data from the most recent time point, even when cross-sectional data is available from multiple time points. This is because forecasting models with similar contexts have higher transferability, and the context of the most recent time point is believed to be the most similar to the context of a future time point. In this paper, the author proposes a method for improving the forecasting performance of disaggregate travel demand models by utilising not only the most recent dataset but also an older dataset. The author assumes that the parameters are functions of time, which means that future parameter values can be forecast. These forecast parameters are then used for travel demand forecasting. This paper describes a case study of journeys to work mode choice analysis in Nagoya, Japan, using data collected in 1971, 1981, 1991, and 2001. Behaviours in 2001 are forecast using a model with only the most recent 1991 dataset and models that combine the 1971, 1981, and 1991 datasets. The models proposed by the author using data from three time points can provide better forecasts. This paper also discusses the functional forms for expressing parameter changes and questions the temporal transferability of not only alternative-specific constants but also level-of-service and socio-economic parameters.