METHOD AND SYSTEM FOR PREDICTING DEMAND FOR VEHICLES

摘要

The disclosed embodiments illustrate methods and systems for predicting demand of vehicles in a transportation network. The method includes determining demand events at each of one or more locations for time intervals based on historical demand data. The demand events correspond to a demand of vehicles at one or more locations during plurality of time intervals throughout a day. The method includes creating a graph comprising nodes, and edges connecting nodes, each node being representative of a demand event from demand events. An edge is representative of dependency between two demand events from demand events. The method includes predicting demand of vehicles at a location from one or more locations during a predetermined time interval based on the graph and a real time demand of vehicles associated with other demand event. The method includes displaying demand prediction on a computing device at one or more locations of transportation network.

主权项

1. A method for predicting demand of one or more vehicles in a transportation network, said method comprising:
determining, by one or more microprocessors, one or more demand events at each of one or more locations for one or more time intervals based on a historical demand data associated with each of said one or more locations, wherein said one or more demand events correspond to a demand of said one or more vehicles at said one or more locations during plurality of time intervals throughout a day; creating, by said one or more microprocessors, a graph comprising one or more nodes, and one or more edges connecting said one or more nodes, each node being representative of a demand event from said one or more demand events, wherein an edge is representative of a dependency between two demand events from said one or more demand events; predicting, by said one or more microprocessors, said demand of said one or more vehicles at a location from said one or more locations during a predetermined time interval based on said created graph and a real time demand of said one or more vehicles associated with at least one other demand event; and displaying, by a display device, said demand prediction on a computing device at said one or more locations of said transportation network.