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Global voting map matching method based on low-sampling-rate floating vehicle data

A technology of floating car data and low sampling rate, applied in the field of transportation, can solve the problem of low accuracy rate of the voting map matching method in the whole district

Active Publication Date: 2014-12-10
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the shortcomings of the existing voting map matching method for the whole region, the accuracy rate is low, the present invention provides a global voting map matching method based on low sampling rate floating car data, based on the model of the road network, first calculate The candidate set that the current GPS track point may match, consider the proximity probability and connectivity probability of the candidate points in the set, and obtain the static analysis matrix

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  • Global voting map matching method based on low-sampling-rate floating vehicle data
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  • Global voting map matching method based on low-sampling-rate floating vehicle data

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[0034] The present invention will be further described below in conjunction with the drawings.

[0035] reference figure 1 with figure 2 , A global voting map matching method based on low sampling rate floating car data, including the following steps:

[0036] Step 1: Construct a directed road network G(V, E), where V is the intersection, starting point or end of the road, and E is the road section separated by two adjacent intersections. Define a path as: In the road network, select two nodes V i ,V j , Find a set of interconnected road sections s 1 →s 2 →s 3 ...→s n And s 1 .start=V i ,s n .end=V j . On the basis of the road network, process the floating car GPS data to obtain the floating car GPS track data T;

[0037] Step 2: Reference figure 2 , For trajectory T:p 1 →p 2 →p 3 ...→p n Trajectory point p in i , 1≤i≤n, select all road sections within the radius r as candidate road sections k means point p i The kth candidate road segment of. Get the corresponding candidate ...

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Abstract

The invention relates to a global voting map matching method based on low-sampling-rate floating vehicle data. On the basis of floating vehicle GPS (Global Positioning System) trajectory data, influence of a topological structure of a road network and the GPS trajectory data of the adjacent spatial positions in different distances on the map matching process is considered; new map matching function indexes are defined; influence of the geometrical property and the topological structure of the road network on matching is comprehensively considered, so that a static matching matrix (SMM) as an initial map matching result is obtained; on the basis, the SMM is corrected by a distance weighing function defining influence of distance among reflected nodes, so that a dynamic matching matrix (DMM) is obtained; and finally, an optimal trajectory as the map matching result is found out by performing global voting on the DMM. According to the invention, relatively good map matching effect can be realized with low computing time complexity at low sampling rate.

Description

Technical field [0001] The invention relates to the field of transportation, in particular to a global voting map matching method based on low sampling rate floating car data. Background technique [0002] Floating vehicles generally refer to buses or taxis that are equipped with on-board GPS positioning devices and drive on urban main roads. Floating car technology is a dynamic traffic information detection technology that has emerged in recent years. It is one of the advanced technical means to obtain road traffic information used in intelligent transportation systems in recent years. The floating car can periodically transmit the vehicle number, time, direction, latitude and longitude coordinates and other data to the dispatch center. After information processing, it can easily obtain the real-time traffic information of the entire city road network. The map matching method is one of the key technologies of floating car data processing. It can correct the errors caused by GPS...

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Application Information

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IPC IPC(8): G01C21/30
CPCG01C21/30
Inventor 杨旭华赵久强汪向飞
Owner ZHEJIANG UNIV OF TECH
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