Cities worldwide are trying to increase the modal share of bicycle traffic to address traffic and carbon emission problems. Aside from safety, a key factor for this is the cycling comfort, including the surface quality of cycle paths. In this paper, we propose a novel edge-based crowdsensing method for analyzing the surface quality of bicycle paths using smartphone sensor data: Cyclists record their rides which after preprocessed on their phones before being uploaded to a private cloud backend. There, additional analysis modules aggregate data from all available rides to derive surface quality information which can then used for surface quality-aware routing and planning of infrastructure maintenance.

翻译：全球各城市正努力提升自行车交通的出行分担率，以应对交通拥堵和碳排放问题。除安全性外，骑行舒适度（包括自行车道路面质量）是关键因素。本文提出一种基于边缘计算的创新众感知方法，利用智能手机传感器数据分析自行车道路面质量：骑行者在手机端对骑行数据进行预处理后，上传至私有云后端系统。该系统通过附加分析模块整合所有骑行数据，推导出路面质量信息，进而支持基于路面质量的路径规划及基础设施维护决策。