01660446

Component

Network travel time reliability can be represented by a relationship between network space-mean travel time and the standard deviation of network travel time. The primary objective of this paper is to improve estimation of the network travel time reliability with network partitioning. The authors partition a heterogeneous large-scale network into homogeneous clusters with well-defined Network Fundamental Diagrams (NFD) using directional and non-directional clustering methods. The impacts of the partitioning approaches, as well as the number of clusters, on the network travel time reliability relationship are explored. To estimate individual vehicle travel times, the authors use two distinct approaches to allocate vehicle trajectories to different time intervals, namely full trajectory and sub-trajectory approaches. The authors apply the proposed framework to a large-scale network of Chicago using a 24-hour dynamic traffic simulation. Partitioning and travel time reliability estimation are conducted for both morning and afternoon peak periods to demonstrate the impacts of travel demand pattern variations. The numerical results show that the sub-trajectory method for the travel time reliability estimation and the directional partitioning with three clusters have the highest performance among other tested methods. The analyses also demonstrate that partitioning a heterogeneous network into homogeneous clusters could improve network travel reliability estimation by assigning a separate relationship to each cluster. Also, comparing morning and afternoon peak periods suggests that the estimated parameter for the linear network travel time reliability relationship is dependent on the coefficient of variation of density.

This paper was sponsored by TRB committee AHB45 Standing Committee on Traffic Flow Theory and Characteristics.

18-06583

English

0000-0002-8443-8928

9p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Dynamic models; Networks; Reliability; Traffic simulation; Travel time

Chicago (Illinois)

Highways; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-06583

TRIS, TRB, ATRI

Jan 8 2018 11:42AM