The invention discloses a
travel time fusion prediction and query method based on traffic
big data, and the method comprises the steps: carrying out the offline calculation or training of data uploaded by all online vehicles to obtain various types of prediction models and parameters, and building and dynamically updating a
data dictionary according to the prediction models and parameters; carrying out the call of the prediction models and parameters, and carrying out the prediction of the traffic state of a road network or a
single vehicle through combining the real-time
travel time data of a road segment and a path, wherein the
data dictionary comprises a vehicle
data dictionary, a road segment data dictionary and a path data dictionary, and the online vehicles are the vehicles which are registered to access to the network and automatically upload positioning and speed data. The beneficial effects of the invention are that the method solves problems that a road network or
single vehicle traffic
state prediction method in the prior art is poorer in instantaneity, universality and practicality, greatly improves the
measurement precision, greatly improves the online prediction precision, and guarantees the instantaneity, practicality and universality in
engineering application.