TY - DATA T1 - Data underlying the publication: Minimising missed and false alarms: a vehicle spacing based approach to conflict detection PY - 2025/06/06 AU - Yiru Jiao AU - Simeon Calvert AU - Hans van Lint UR - DO - 10.4121/252a79e7-d9ff-4181-a9e4-842ea7845a77.v1 KW - Advanced Driving Assistance System KW - Forward Collision Warning KW - Collision avoidance KW - Conflict detection KW - Vehicle spacing patterns N2 -

This dataset includes the resulting data of the research: Minimising missed and false alarms: a vehicle spacing based approach to conflict detection. It contains processed data from the 100Car NDS, organised data from the CitySim FreewayB subset, as well as output files generated by conflict detection analyses. The research objective is to minimise missed and false alarms in vehicle conflict detection by optimising critical spacing thresholds. This study combines simulated traffic scenarios and real-world near-crashes to evaluate conflict detection strategies. Systematic data collection methods are used to compile vehicle trajectories, conflict events, and spacing distributions for comprehensive analysis. The scripts that produced these data are open-sourced at https://github.com/Yiru-Jiao/Conflict-detection-MFaM

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