Methods for the Estimation of Time-dependent Origin - Destination Matrices Using Traffic Flow Data on Road Links

Methods for the Estimation of Time-dependent Origin - Destination Matrices Using Traffic Flow Data on Road Links


X Zhang and D Mustard, TRL Limited; M Maher, Napier University, UK



An origin-destination (O-D) matrix is a table containing traffic demands from each origin to each destination in a road network. It is an essential source of information in every aspect of the transport planning process. Estimating O-D matrices from traffic flow data collected on road links is a tool commonly used to produce or estimate O-D matrices when existing information is incomplete or out-of-date. It is also less labour-intensive than traditional methods for deriving O-D matrices, such as the O-D survey method using home or roadside interviews.

Estimating O-D matrices for a general network requires information on route choices in terms of the proportions of each O-D flow using each route or link in the road network. In general, route choice proportions are dependent on congestion levels, which, in turn, depend on traffic demands. They are normally obtained by a traffic assignment model given an O-D matrix. Therefore, a matrix estimation method for congested networks is normally combined with a traffic assignment model. Almost all assignment-based estimation methods developed so far are static: the input flow data consists of total traffic volumes on road links over a single (and normally long) period of time and an average O-D matrix is estimated. Time-variations in traffic are not considered. A dynamic method uses time series data of traffic flows and so it is possible to estimate time-dependent O-D matrices. To date, only non-assignment-based dynamic methods have been developed in the literature. In these methods, it is assumed that the route choice proportions are constants and are determined separately from the matrix estimation process. This assumption may be justified only in non-congested networks and may lead to inconsistencies between the results of matrix estimation and traffic assignment. The estimation method presented in this paper is developed in an on-going research project. The principle of a static estimation method will be extended so as to develop an assignment-based dynamic estimation method. The estimation problem is formulated as a mathematical programming problem based on the entropy-maximisation principle, although other formulations may also be used, such as the least squares principle. The traditional entropy-maximisation method (ME2 method) for matrix estimation assumes that traffic-flow data are error-free. This assumption will not be made in this paper. The programming problem has a hierarchical structure: at the top level an O-D matrix is estimated givenroute choice proportions; and, at the lower level, route choice proportions are determined by an assignment model given an O-D matrix defined at the top level. A heuristic solution algorithm is proposed for solving the programming problem, using the dynamic traffic assignment package CONTRAM. The algorithms will be tested using both simulated data and data collected on a real road network. It will be shown that the algorithms are efficient and are applicable to practical networks.


Association for European Transport