OPTIMIZING AND PREDICTING AVAILABILITY OF RESOURCES IN A SHARED VEHICLE ENVIRONMENT

摘要

An intelligent bicycle sharing system, or other vehicle sharing system, is able to provide helpful bicycle availability predictions based on historical data, including various utilization statistics. Historical data can be collected over time as users use the bicycle sharing system. For example, the historical data may include the number of available bicycles at various locations and times, as well as contextual data associated with the locations and times. Contextual data may include data regarding the weather, local events, season, day of the week or year, news events, among other environmental factors that may or may not influence bicycle utilization. In some embodiments, a model, such as a machine learning model (e.g., neural network) may be trained using the historical data as training data such that the model can predict bicycle availability for a certain future time and location.