Research on bike-sharing Demand Forecasting and Intelligent Scheduling Method Based on Spatio-temporal Data

Abstract

Globally, the traditional public bicycle service has many disadvantages, and it has been difficult to solve the travel pain point of users in the "last kilometer". With the deepening of the development concepts of green, sharing and so on, the shared bicycle travel mode comes into being, which not only reduces the pressure and congestion of the urban road network, but also provides convenience for people's travel. Improving the informatization level and decision support ability of traffic management and services through the construction of intelligent transportation system is the fundamental way to reduce traffic accidents, solve traffic congestion, promote urban environmental protection and improve people's quality of life. The public bicycle system is a "pile type" model, which is characterized by the fact that each bicycle must be borrowed and returned in the lock column. With the infiltration and development of the concept of "sharing bicycle", the "pile free" urban public bicycle system will be more convenient for people to use and attract more user groups because it can "ride and stop at any time".Bike-sharing conforms to the development concept of innovation, coordination, green, openness and sharing, and is widely accepted by the society. The hardware update speed far exceeds expectations, and it has become one of the main components of urban transportation. However, the research on operation and management of bike-sharing lags behind the technological progress and market demand, which has become the bottleneck restricting the development of bike-sharing. In addition, due to the imbalance of traffic flow and the rush hour of commuting, the Public Bicycle System, PBS) in cities often has the embarrassing phenomenon of being unable to rent a car because there is no car at the station and being unable to return the car because the parking space at the station is full. Therefore, the method of bike-sharing demand forecasting and intelligent scheduling based on spatio-temporal data proposed in this paper plays an important role in exerting the efficiency and advantages of bike-sharing system.