Title :
Statistical Origin-destination generation with multiple sources
Author :
Morimura, Tetsuro ; Kato, Shigeo
Abstract :
Any trajectory is always generated with its origin and destination. Origin-destination (OD) generation for trips plays an important role in many applications such as trajectory mining, traffic simulation, or marketing. In previous work on traffic pattern recognition, microscopic ODs for limited areas are estimated with probe-car data, while macroscopic ODs for broad areas are usually generated by using road-traffic-census data. In this paper, we propose a microscopic OD determination method for broad areas with the same data and landmark information, which is based on an L1-regularized Poisson regression. We demonstrate performance improvements over baseline methods in numerical experiments with a massive data set from Tokyo.
Keywords :
data mining; regression analysis; road traffic; stochastic processes; traffic engineering computing; L1-regularized Poisson regression; baseline method; landmark data; microscopic OD determination method; multidata source; road traffic census; statistical origin-destination generation; trajectory mining; Data mining; Estimation; Microscopy; Rail transportation; Trajectory; Vectors;
Conference_Titel :
Pattern Recognition (ICPR), 2012 21st International Conference on
Conference_Location :
Tsukuba
Print_ISBN :
978-1-4673-2216-4