HaTTC: An urban traffic sensing method based on tensor completion technique

It has been proved that the adoption of traffic sensing data can reduce traffic jam, and improve traffic volume. However, traffic sensing by both vehicles and road monitoring infrastructures faces the problem of data missing on dimensions of time and space, which makes data reconstruction a challenge for full-time and wide-area traffic sensing. Exploiting the hidden structure of the traffic data, we raise a tensor-completion-based algorithm, HaTTC, to tackle the problem in this paper. We testify the high efficiency of the algorithm based on highway traffic data from static sensors. Employing our algorithm, we achieve full-time urban traffic sensing on some road segments of Shanghai via a probe-vehicle-based Vehicular Sensor Network (VSN) system.