Road network grid matching, road status messages and introduction route information acquisition method

Abstract

The invention relates to a road network grid matching method, which comprises: obtaining GPS original point data and de-noising the GPS original point data to gain GPS point data; partitioning the road network into grids according to the GIS road network structure information to get road network grid units; and matching the GPS point data to the corresponding road network grid units to obtain grid matching data. The invention also relates to an information acquisition method for real-time road conditions, which comprises: matching road network grids to get grid matching data; integrating the grid matching data with GPS traffic flow data; and filtering the integrated data according to types of driving routes to obtain the information of real-time road conditions. The invention provides theroad network grid matching method based on the GPS road network grid partitioning technique aiming at large concurrent GPS data for achieving real-time treatment of the large concurrent GPS data; andacquires information of real-time road conditions and real-time guiding routes by using the road network grid matching method.

Description

technical field [0001] The invention relates to a road network grid matching method, a method for acquiring real-time road condition information and a method for acquiring real-time induced route information, belonging to the field of intelligent transportation. Background technique [0002] At present, the common vehicle travel guidance in China is generally based on the shortest path guidance generated by the static road network state without traffic flow in GIS. It cannot be dynamically selected according to the current road traffic conditions and driving conditions, so the understanding of the road network state is not very good. For a comprehensive traveler, they can only follow blindly. However, travel guidance based on real-time traffic and road conditions is not easy to realize due to the limitation of the source of road condition detection data. The road condition detection data generally comes from the signal light coil detector, video traffic detector, etc. of th...

AI Technical Summary

Problems solved by technology

Since these detection devices are generally installed at important traffic intersections, the data is limited, so they cannot reflect the status and changes of the entire road network

[0003] The existing traffic flow real-time detection and guidance system based on the Global Position System (GPS) floating car realizes the real-time reflection of the road network status through fusion technology, but it has the following technical difficulties: A large number of GPS data samples in the interval, the guidance system needs to process a large amount of GPS data concurrently in real time, and match it to each road section. For nearly 150,000 road sections within the Fifth Ring Road like Beijing, every second It is impossible to match the GPS points of tens of thousands of vehicles to the road using ordinary models and processing methods, and it is difficult to improve the operating efficiency of the system, and it is difficult to reach a practical level

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