A time-space traffic (TS) 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 limitations of existing information technology and traffic infrastructure investment. 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 model to solve the problem. 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. 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. 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.

翻译：时空交通（TS）图通过颜色在时空单元格中呈现交通状态，是一种重要的交通分析与可视化工具。尽管其对交通研究和工程具有重要意义，但由于现有信息技术和交通基础设施投资的限制，大多数已存在或正在生成的TS图过于粗糙，无法展示详细的交通动态。为提高TS图的分辨率并使其呈现丰富的交通细节，本文提出了TS图精细化问题，并构建了基于多元线性回归的模型以解决该问题。通过两次测试（分别尝试将TS图分辨率提升4倍和16倍），评估了所提模型的性能。采用不同时间、地点甚至不同国家收集的数据，全面评估了模型的精确性和可迁移性。基于多样化数据的严格测试表明，所提模型尽管结构简单，但能以令人满意的精度和可靠的迁移性实现TS图的精细化。该精细化模型将“拯救”广泛存在的模糊TS图，使其能够展示更多交通细节。