MaaS in Bike-Sharing: Smart Phone GPS Data Based Layout Optimization and Emission Reduction Potential Analysis

摘要

As a representation of smart and green city development,bike-sharing system is one of the hottest topic in the fields of transportation,public health,urban planning,and so on.With the development of Mobility as a Service(MaaS),emerging technologies such as mobile data mining give some new solutions for optimizing bike-sharing system and predicting the emission reduction.Here,we propose a bike-sharing layout optimization and emission reduction potential analysis structure under the concept of MaaS.A human travel mode detection method and a geometry-based probability model are proposed to support the particle swarm optimization process.We implement a comparison study to analyze the computational efficiency.Taking Setagaya ward,Tokyo as the study case with about 3 million GPS trajectories,the result shows that with the increase of station number from 30 to 90,the adoption of bike-sharing system can reduce about 3.1-3.8 thousand tonnes of C02 emission.