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\section{Conclusion}  This paper demonstrates the theoretical and practical application of a large-scale, automated, video data collection system using computer vision for highly detailed traffic studies, particularly proactive road safety analysis using surrogate safety analysis. The reader is led step-by-step through the process of collecting, processing, and analysing video data, presenting examples and discussing challenges along the way. It demonstrates an early implementation in the form of a cross-sectional analysis of driver behaviour in a large set of roundabout video data . data.  Several technical challenges and their solutions were outlined, notably tracking error (accuracy optimised up to $94\%$ and no less than $85\%$ using the comprehensive MOTA methodology), analysis of TTC distributions, and aggregation and sampling considerations. It is expected that these issues will be further addressed as processing and analysis tools become more accessible, more collaborators contribute solutions to the open-source software stack, and as techniques applied to transportation issues become more sophisticated.