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Data underlying the publication: Minimising missed and false alarms: a vehicle spacing based approach to conflict detection

4TU.ResearchDatavia 4TU.ResearchData (via DataCite) · bijgewerkt 6 juni 2025
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Wat erin zit

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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