Robust SPSA algorithms for dynamic OD matrix estimation

Dynamic OD Matrix Estimation Exploiting Bluetooth Data in Urban Networks

Time-Dependent Origin-Destination (OD) matrices are a key input to Dynamic Traffic Models. Microscopic and Mesoscopic traffic simulators are relevant examples of such models, traditionally used to assist in the design and evaluation of Traffic Management and Information Systems (ATMS/ATIS). Dynamic traffic models can also be used to support real-time traffic management decisions. The typical ap...

Dynamic OD transit matrix estimation: formulation and model-building environment

The aim of this paper is to provide a detailed description of a framework for the estimation of time-sliced origin-destination (OD) trip matrices in a transit network using counts and travel time data of Bluetooth Smartphone devices carried by passengers at equipped transit-stops. A Kalman filtering formulation defined by the authors has been included in the application. The definition of the i...

An EM Approach to OD Matrix Estimation

Consider a \black box" having I input channels and J output channels. Each arrival on an input channel gets routed through the black box and appears on an output channel. The system is monitored for a xed time period and a record is made of the number of arrivals on each input channel and the number of departures on each output channel. The OD (origination-destination) matrix estimation problem...

A robust framework for the estimation of dynamic OD trip matrices for reliable traffic management

Origin-Destination (OD) trip matrices describe the patterns of traffic behavior across the network and play a key role as primary data input to many traffic models. OD matrices are a critical requirement, either in static or dynamic models for traffic assignment. However, OD matrices are not yet directly observable; thus, the current practice consists of adjusting an initial or a priori matrix ...

Dynamic Estimation of OD Matrices for Freeways and Arterials