Optimized road congestion state discovery method

Abstract

The invention provides an optimized road congestion state discovery method which comprises the following steps that 1, a floating car regularly collects information of car serial numbers, positions, speeds, time and car types in a running process, and sends the information to a data center; 2, the data center filters data, obtains a road section where the floating car is located according to matching of the position information with a GIS (Geographic Information System), and stores floating car data in a position, corresponding to the road section, in a driving road section database; 3, a road section information set of road sections is extracted from the driving road section database by the data center, a weighted average of the speeds is computed by combing the car types and the weight of the speeds, and abnormal speed information is obtained; and 4, the times of the abnormal speed information of each road section are counted within a preset time, and the road section is congested if the times reach the preset value. Therefore, identification of a traffic congestion spot is achieved. The road congestion state discovery method is more efficient, reliable and dynamic, and can improve the road section congestion state discovery accuracy.

Description

【Technical field】 [0001] The invention relates to an optimized road congestion state discovery method. 【Background technique】 [0002] Floating car technology, also known as "probe car", has been widely used. Its basic principle is: based on the vehicle's position, direction and speed information regularly recorded by the floating car equipped with on-board GPS during its driving process, the application of map Matching, path estimation and other related computing models and algorithms are processed, so that the floating car position data and urban roads are associated in time and space. Which roads are often congested? At what time is there frequent congestion? How congested is it? At present, in public travel and other traffic information service systems, these information can only be based on long-term statistical data and traveler's own experience to achieve a certain degree of static information services for traffic jams, and there is no effective way to provide dyna...

AI Technical Summary

Problems solved by technology

Which roads are often congested? When is the traffic jam most common? How congested is it? At present, in public travel and other traffic information service systems, these information can only be based on long-term statistical data and traveler's own experience to achieve a certain degree of static information services for traffic jams, and there is no effective way to provide dynamic traffic jams. information service

These methods are only the accumulation of long-term data experience, and cannot realize the dynamic update of traffic jam point information on the road

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