Cycling, as a mode share of urban travel, is widely desired to be increased. To support the delivery of improved infrastructure,
robust modelling is desired and modelling such agents demands real-world calibration. Data to enable this is expensive to obtain
by conventional means.
This paper presents and demonstrates a process for the analysis of video to provide such data. This analysis yields spatiotemporal
data for experimentally-observed cyclists from which velocity information (amongst other things) can be derived. With further
refinement, this process can be used in the analysis of existing and future highway video data.