The present invention discloses an urban traffic
velocity estimation method based on multi-source crowd
sensing data. This method, based on roadside
pedestrian data and road navigation data collected by smart phones, obtains a final estimated velocity through the steps of
missing data filling, self-view velocity aggregation and multi-view velocity fusion. This fine-grained large-scale urban traffic
velocity estimation method can achieve
velocity estimation on all types of roads, including suburban road sections and paths, instead of just focusing on main roads in a city center. According to the present invention, based on data driving, the urban traffic velocity
estimation method does not need to install additional devices on roads, and is low in cost and high in universality. Compared with the prior art, the urban traffic velocity
estimation method has higher practicability, theoretical property and applicability, and is of great significance for improving
traffic management and planning.