An integrated Computational framework for the estimation of dynamic OD trip matrices
Tipo de documentoTexto en actas de congreso
Fecha de publicación2015
Condiciones de accesoAcceso restringido por política de la editorial
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 from link flow counts, speeds, travel times and other aggregate demand data. This information is provided by an existing layout of traffic counting stations, as the traditional loop detectors. The availability of new traffic measurements provided by ICT applications offers the possibility to formulate and develop more efficient algorithms, especially suited for real-time applications. However, the efficiency strongly depends, among other factor, on the quality of the seed matrix. This paper proposes an integrated computational framework in which an off-line procedure generates the time-sliced OD matrices, which are the input to an on-line estimator. The paper also analyzes the sensitivity of the on-line estimator with respect to the available ICT traffic measurements.
CitaciónBarcelo, J., Lídia Montero. An integrated Computational framework for the estimation of dynamic OD trip matrices. A: IEEE International Conference on Intelligent Transportation Systems. "2015 IEEE 18th International Conference on Intelligent Transportation Systems". Las Palmas de Gran Canaria: 2015, p. 612-619.