Categorizing Bicycling Environment Quality Based on Mobile Sensor Data and Bicycle Flow Data

The bicycle is a healthy and sustainable transport mode due to its emission-free characteristics. To increase use, it fundamental provide bicycle-friendly environments. better monitor environments, this study proposed the concept of bicycling environment quality (BEQ), which was defined by perceived satisfaction conflict level. Data collection conducted at 19 road segments in five sites located Beijing, China. Then, speed-related acceleration-related behavior indicators (BBIs) were extracted from data collected using sensors on mobile phones, while (BEIs), such as flow, recorded data. Taking BBIs BEIs input attributes, two-level BEQ classification assessment model based random forest (RF) algorithm constructed. RF-based able produce approximately 77.35% overall correct classification. results demonstrate feasibility GPS evaluating BEQ. In addition, novel dockless bicycle-sharing system (DBS)-based framework for traffic monitoring discussed, great significance development bicycles. This provides theoretical method objective assessment. It can further be used planners administrators improve individual cyclists optimal route choice.