Guest Editorial: Big Data for Driver, Vehicle, and System Control in ITS

Abstract

The papers in this special section are devoted to the topic of Big Data for intelligent vehicle systems. issue. The collection of papers included can be categorized in several ways. In terms of applications, the special section covers transit network design, taxi and bus operation, traffic flow and travel time prediction, dilemma zone management, and geometric design of roads. In terms of data sources, it covers both conventional sources of data such as bus, taxi, and individual vehicle trajectories, and also novel sources of data such as those based on the connected vehicle technology, roadside communication equipment, or onboard devices. In terms of techniques or methodologies developed for processing big data, this collection includes papers covering the data imputation technique based on the k-nearest neighbor method, data management infrastructure, the machine learning approach, and the graph-theory-based method.