Refining Time-Space Traffic Diagrams: A Simple Multiple Linear Regression Model

A time-space (TS) traffic diagram, which presents traffic states in time-space cells with color, is an important traffic analysis and visualization tool. Despite its importance for transportation research and engineering, most TS diagrams that have already existed or are being produced are too coarse to exhibit detailed traffic dynamics due to the difficulty of collecting high-fidelity traffic data. To increase the resolution of a TS diagram and enable it to present ample traffic details, this paper introduces the TS diagram refinement problem and proposes a multiple linear regression-based solution. Data collected at different times, in different locations and even in different countries are employed to thoroughly evaluate the accuracy and transferability of the proposed model. Two tests, which attempt to increase the resolution of a TS diagram 4 and 16 times, are carried out to evaluate the performance of the proposed model. In the increase-4-times test, the errors represented by Mean Absolute Percentage Error are all less than 0.1, and in the increase-16-times test all less than 0.17. Model comparison demonstrates that the proposed model outperforms the classic adaptive smoothing method in refining TS diagrams. All the strict tests with diverse data show that the proposed model, despite its simplicity, is able to refine a TS diagram with promising accuracy and reliable transferability. The proposed refinement model will “save” widely existing TS diagrams from their blurry “faces” and enable TS diagrams to show more traffic details.