Data underlying the publication: Inferring vehicle spacing in urban traffic from trajectory data

This dataset includes the resulting data of the research: Inferring vehicle spacing in urban traffic from trajectory data. It contains the processed outputs generated from raw vehicle trajectory data in the pNEUMA dataset. The objective of this research is to infer average two-dimensional vehicle spacing and analyse the interactions between vehicles through empirical experiments, particularly around intersections. The study employs a combination of data preprocessing, spatial transformation, intersection detection, and statistical inference (yielding interaction Fundamental Diagrams) to capture and summarise vehicle speed, spacing, and positional data. Data are collected from real-world traffic records, then transformed and sampled into various output formats (such as CSV and HDF5) that encapsulate both the inferred interaction metrics and the underlying trajectory information. The scripts that produced these data are open-sourced at https://github.com/Yiru-Jiao/DriverSpaceInference<br>

本数据集收录了一项研究的成果数据：基于轨迹数据推断城市交通中的车辆间距。其包含从pNEUMA数据集中的原始车辆轨迹数据生成的经处理输出结果。本研究旨在推断二维平均车辆间距，并通过实证实验分析车辆间的交互行为，尤其聚焦于交叉口周边区域。该研究综合运用数据预处理、空间变换、交叉口检测及统计推断等手段（生成交互基本图），以获取并整理车辆速度、间距与位置数据。数据采集自真实世界的交通记录，经转换与采样后封装为多种输出格式（如CSV与HDF5），这些格式同时涵盖了推断得到的交互指标与原始轨迹信息。生成上述数据的脚本已在https://github.com/Yiru-Jiao/DriverSpaceInference处开源。