ABSTRACT

This research proposes a novel single-level approach to traffic counts-based OD estimation using observed turning proportions and partial OD flows. The key idea is to relax the need for explicit assignment-based bi-level models and exploit the observations from big traffic data. The observed turning proportions are used to estimate traffic counts; and the structural knowledge of partial OD flows is used to improve the quality of OD estimates. Numerical experiments considering different spatial coverage of partial OD from Bluetooth are conducted on two networks. The study findings indicated that the quality of estimates improve with higher percentage of partial OD information. The proposed approach is computationally faster and yielded slightly better results than the traditional bi-level. The methodology is not limited to data from Bluetooth but adaptive with other sources such as GPS, mobile phone, and travel surveys that can provide turning proportions and/or partial OD flows.

摘要

本研究提出了一种新颖的单级方法，使用观察到的转向比例和部分 OD 流来进行基于交通计数的 OD 估计。关键思想是放宽对基于明确分配的双层模型的需求，并利用来自大交通数据的观察结果。观察到的转向比例用于估计交通量；部分 OD 流的结构知识用于提高 OD 估计的质量。在两个网络上进行了考虑蓝牙部分 OD 的不同空间覆盖的数值实验。研究结果表明，估计的质量随着部分 OD 信息的百分比的提高而提高。与传统的双层相比，所提出的方法计算速度更快，并且产生的结果略好。