Classification of Methods for Estimating the Origin-Destination Matrix with Link Volume Counts Data in the Congested and Uncongested

Form of the source-destination matrix Conventional approaches to accessing this matrix An essential input to the transportation planning process is the amount of travel demand in the directly, based on interviews and surveys in specific locations, are costly and time consuming. Hence, for the sake of mathematical methods based on intuitive statistics such as the volume of traffic in the network passages are becoming more and more popular in transportation studies. These methods are defined by having a source-primary-destination matrix as well as the current traffic flow information observed in a number of network paths, resulting in matrix estimation with the least distance from the primary matrix. , When allocated to the network, reproduce the observed volumes. Because conventional methods of obtaining this matrix that are based on interviewing and surveying are expensive, time consuming and annoying to people, the mathematical methods based on the observed statistics (such as the volume of network passage counts) ) Are expanding day by day. In this research, the source-destination matrix estimation methods can be divided into crowded and backbone networks in terms of network performance and the characteristics of each are presented.