This research aims to address the limited consideration given to non-motorized transport facilities in current studies on shared bike travel demand forecasting. This study is the first to propose a method that applies complete citywide non-motorized facility data to predict bike-sharing demand. This study employs a multiscale geographically weighted regression (MGWR) model to examine the effects of non-motorized transport facility conditions, quantity of intersections, and land use per unit area on riding demand at various spatial scales. The results of comparison experiments reveal that riding demand is substantially affected by non-motorized transport facilities and the quantity of intersections.

Bicycle riding requires a high standard width and continuity of lanes, as an appropriate width directly improves the service level of the lanes. Therefore, the width of bicycle lanes should be designed considering the characteristics of the bicycle traffic flow and the actual conditions of an area. In order to explore the relationship between bicycle traffic flow characteristics and lane width, this study references the vehicle traffic flow model and introduces the concept of bicycle traffic flow width, defined as the average width of bicycle traffic flow over a certain distance in a unit of time. Based on measured data, this study analyzes the relationships among bicycle traffic flow, lane width, and other parameters. The research results show that when the bicycle lane width is between 2.0 and 3.4 m, there is a clear linear relationship between the speed of bicycle traffic flow and the traffic flow width, with bicycle traffic flow width increasing as speed increases. Furthermore, overly wide bicycle lanes can result in more instances of bicycle over-speeding. These findings will guide the design of bicycle lanes.