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Abstract
Objective: The objective of this research is to study the feasibility of measuring behavioral indicators that reflect effects of infrastructure and interaction with other road users.
Methods: An observation study was performed using 6 cameras above a separated cycle path next to a road which included a crossing with both cyclists and cars. A learning method based on Single Shot MultiBox Detector was applied to automatically detect the cyclists, and cyclist tracks were determined. Next, kinematic parameters were calculated from the cyclists’ tracks. Amongst others, the cyclists’ intensity, speed, position on the cycle path, and the distance to each other were analyzed for a busy period as well as for a quiet period of the day.
Results: With the measurement method developed in this study it is possible to analyze the cyclists’ intensity, the space they use at the cycle path, their average velocity, waiting times, the space and velocity amongst each other, and red light negation. However, collisions were not seen in the dataset analyzed, and the data is not sufficiently accurate to analyze sudden braking actions.
Conclusion: It can be concluded that the developed measurement method provides insight of the cyclists’ behavior in such a way that it can already be used for obtaining information to make changes to the infrastructure that will improve the comfort and safety of cyclists. The method could be further developed for doing qualitative comfort and safety analyses, and for doing analyses of the interaction between various types of road participants.
Disclosure statement
No potential conflict of interest was reported by the author(s).