A Bicycle Navigation System for Analyzing the Comfort Level of the Cyclist

In recent years, the number of cyclists has increased and the use of bicycles has been promoted worldwide as a means of transportation in Mobility as a Service (MaaS). However, route recommendation, incorporating efficiency and comfort, is yet to be explored further. In this study, we construct a navigation system that recommends the shortest route for a cyclist. During the traversing through the recommended route, the cyclist's facial images are captured and unevenness of the route is recorded periodically; through the camera and an accelerometer of the smartphone. The system analyzes the level of comfort the cyclist experienced by estimating the facial expressions and the degree of unevenness throughout the recommended route. Finally, the information on the experienced level of comfort for the recommended route is annotated in Google Maps. We conducted real-life experiments for two consecutive days in which four subjects took part; where each of the subjects rode bicycles for about 1.5 hours per day following the route recommended by the navigation system.