发表机构
University College London; Buckinghamshire Council（伦敦大学学院; 白金汉郡议会）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究利用融合移动网络数据与出行调查，构建英格兰和威尔士按出行方式与目的细分的小区域OD矩阵，并开源处理流程以支持精细尺度交通规划。
AI 中文摘要
起讫点（OD）矩阵支撑着定量交通规划的诸多方面，从模型校准和可达性分析到新服务与开发项目的评估。对基于地方的解决方案日益增长的重视，要求移动性数据不仅能在战略层面，还能在更精细的空间尺度上支持决策。这需要小区域分辨率下按出行方式和目的分类的最新OD证据，而此类数据目前要么无法获取，要么不可用。在本研究中，我们提供了英格兰和威尔士的密集MSOA到MSOA OD矩阵，按七种出行方式和代表性时间段进行细分，并包含工作日早高峰的八种出行目的。这些矩阵通过将BT提供的聚合移动网络数据与国家出行调查（NTS）、人口普查和出行率证据进行校准构建而成，在保留观测到的空间移动结构的同时，将其年龄、方式和目的构成与调查数据相对照。开源数据处理流程与矩阵一同发布，以便完整检查数据集的构建过程，并可调整以适应其他年份、地区或假设。
英文摘要
Origin-destination (OD) matrices sit behind much of quantitative transport planning, from model calibration and accessibility analysis to the appraisal of new services and development. The increasing emphasis on place-based solutions requires mobility data that can support decision-making not only at the strategic level, but also at finer spatial scales. This requires up-to-date OD evidence at small-area resolution, disaggregated by travel mode and purpose, which remains either inaccessible or unavailable. In this work, we present dense MSOA-to-MSOA OD matrices for England and Wales, segmented by seven travel modes and representative time periods, with eight trip purposes for the weekday morning peak. The matrices are built by calibrating aggregate mobile network data provided by BT against National Travel Survey (NTS), census and trip-rate evidence, preserving the observed spatial structure of movement while referencing its age, mode and purpose composition to the survey. The open-source data processing pipeline is released alongside the matrices, so that the construction of the dataset can be inspected in full and adapted to other years, regions or assumptions.
Comments13 pages, 1 figure, 3 tables. Supplementary material provided as an ancillary file
