Traffic semantic analysis based on mobile phone base station data

As traffic sensors gradually increase, traffic managers obtain more and more detection data, and the data volume has jumped to the Big Data magnitude. Recently, the cell detail record data are used as an emerging traffic detection data source. Using mobile phone as a probe, its detection data is able to well reflect user's travel behavior. Meanwhile, cell phone base stations can be treated as fixed sensor and used to detect people flows in the base station area, reflect the distribution of traffic source, and provide supports for the division of the commuting traffic zone. In this article, the traffic semantic framework is proposed. We analyze the data of cell detail record data in Beijing, and extract four features of base stations: real-time user stock, inflow, outflow and increments, to tag the traffic semantic attribute of the base stations.