AI-based bicycle type detection and factor analysis of bicycle ride location selection

Abstract

In Japan, blue lanes are being developed as part of the improvement of bicycle traffic spaces. However, investigations into the effectiveness of blue lane development conducted so far have not established widely applicable methods. Meanwhile, AI-based image analysis technology has been introduced for motor vehicle traffic volume analysis. However, research specifically focused on bicycle traffic volume surveys using image analysis technology within the country is still limited, and while its utility is recognized, research accumulation in this field has not significantly progressed.This study aims to develop a model for measuring bicycles by type using image analysis technology. Next, a visual survey of traffic volumes will be conducted on both blue lanes and sidewalks before and after blue lane implementation in Sapporo City. Using the results, an algorithm will be constructed to clarify the factors influencing bicycle users’ section selection behavior, thereby conducting an analysis of the factors affecting the positioning of bicycles within designated cycling spaces.