Static origin-destination (OD) matrices, specifying the number of trips from each O to each D, are usually needed for several transportation planning and operations decisions. One approach to estimate an OD matrix is to use data from traditional counting sensors on links in conjunction with models or assumptions on how vehicular traffic uses the network. A closely related problem is to locate a given number of counting sensors to obtain good estimates of OD flows. In this paper, a new linear integer programming model for locating sensors to maximize the reduction in the uncertainties in route flows estimates is presented. The model assumes a general underlying traffic loading model as long as the route choice set from each O to each D are known and priors route flows and their reliabilities for each OD route are given. Extensive computational experiments and comparisons with some existing sensor location models indicate that the proposed model consistently gives good estimate of OD flows
A Model to Locate Sensors for Estimating Static OD Volumes given Prior Flow Information
GENTILI, Monica;
2012-01-01
Abstract
Static origin-destination (OD) matrices, specifying the number of trips from each O to each D, are usually needed for several transportation planning and operations decisions. One approach to estimate an OD matrix is to use data from traditional counting sensors on links in conjunction with models or assumptions on how vehicular traffic uses the network. A closely related problem is to locate a given number of counting sensors to obtain good estimates of OD flows. In this paper, a new linear integer programming model for locating sensors to maximize the reduction in the uncertainties in route flows estimates is presented. The model assumes a general underlying traffic loading model as long as the route choice set from each O to each D are known and priors route flows and their reliabilities for each OD route are given. Extensive computational experiments and comparisons with some existing sensor location models indicate that the proposed model consistently gives good estimate of OD flowsI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.