Travel time fusion prediction and query method based on traffic big data

A technology of travel time and prediction method, which is applied in traffic flow detection, traffic control system, road vehicle traffic control system, etc., and can solve problems such as poor practicability, poor real-time performance, and poor versatility

Inactive Publication Date: 2016-06-15
CHINA MERCHANTS CHONGQING COMM RES & DESIGN INST
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Problems solved by technology

[0003] In order to solve the problems of poor real-time performance, poor versatility and poor practicability in the existing road network or

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  • Travel time fusion prediction and query method based on traffic big data
  • Travel time fusion prediction and query method based on traffic big data
  • Travel time fusion prediction and query method based on traffic big data

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Embodiment Construction

[0126] The invention uses the data uploaded by all online vehicles to obtain various prediction models and parameters through off-line calculation or training, and establishes and dynamically updates the data dictionary according to various prediction models and parameters; calls each Class prediction model and parameters combined with real-time road section and path travel time data to predict the traffic state of the road network or bicycle; the data dictionary includes vehicle data dictionary, road section data dictionary and path data dictionary; the online vehicle refers to the registered network and Vehicles that automatically upload position and velocity data. Compared with the prior art prediction method, the method of the present invention combines big data technology, each data dictionary contains multiple indexes, the data storage has better regularity, and can well meet the real-time requirements of data storage and reading and writing. It is particularly noteworth...

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Abstract

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.

Description

technical field [0001] The invention relates to road network or bicycle traffic state prediction technology, in particular to a travel time fusion prediction and query method based on traffic big data. Background technique [0002] The existing road network or bicycle traffic state prediction methods mainly use the traffic data provided by floating vehicles or roadside equipment, or even rely only on the traffic data provided by roadside equipment to predict the road network or bicycle traffic state. This type of method mainly obtains traffic information such as road network flow and average speed directly through roadside equipment, or obtains certain types of traffic information through secondary processing of floating car data, and uses model recursion to predict based on road network topology , the predicted traffic information is mainly concentrated on the three elements of traffic, resulting in a limited promotion area and low promotion value, that is, there is a gener...

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Application Information

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IPC IPC(8): G08G1/01
CPCG08G1/0112G08G1/0129
Inventor 付建胜王川久熊正荣谯志王少飞
Owner CHINA MERCHANTS CHONGQING COMM RES & DESIGN INST
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