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Map matching method based on conditional random fields and low-sampling-frequency floating car data

A conditional random field and floating car data technology, applied in the field of transportation, can solve the problems of high computational complexity, low matching accuracy, and low computational complexity.

Active Publication Date: 2015-12-30
ZHEJIANG UNIV OF TECH
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Problems solved by technology

[0005] In order to overcome the disadvantages of high computational complexity and low matching accuracy of existing map matching methods, the present invention provides a method based on conditional random fields and low sampling frequency floating car data with low computational complexity and high matching accuracy. map matching method

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  • Map matching method based on conditional random fields and low-sampling-frequency floating car data
  • Map matching method based on conditional random fields and low-sampling-frequency floating car data
  • Map matching method based on conditional random fields and low-sampling-frequency floating car data

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Embodiment Construction

[0038] The present invention will be further described below in conjunction with the accompanying drawings.

[0039] refer to figure 1 and figure 2 , a map matching method based on conditional random fields and low sampling frequency floating car data, including the following steps:

[0040] Step 1: Construct a directed road network G(V,E), where V is the road intersection, E is the road section between two adjacent intersections, and the attributes of each road section e include the starting latitude and longitude point e of the road section. Longitude1, e.Latitude1, end latitude and longitude point e.Longitude2, e.Latitude2 and road section type e.Type;

[0041] Step 2: Reference figure 1 , for a GPS observation point g(t) at time t, select all road sections with g(t) as the center within the radius r range, and obtain the corresponding candidate projection points by projection: if the observation point g(t) is on the road section e There is a vertical point within the ...

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Abstract

The invention discloses a map matching method based on conditional random fields and low-sampling-frequency floating car data. The map matching method includes the steps that according to the low-sampling-frequency floating car data, on the basis of a road network model, a candidate projection point set possibly matched with GPS observing points and the observing probability of the candidate projection points in the set are firstly calculated, and then a candidate route set of the adjacent GPS observing points and the transmission probability between every two adjacent candidate projection points are calculated; according to the candidate projection points and candidate routes, in a sliding window, based on a condition random field model, the optimal matched projection points of the observing points are selected through a front-and-back-direction recursive algorithm. According to the map matching method, under the condition of the low sampling frequency, the topological structure of a road network and related information between the GPS observing points are both considered so that the calculation complexity can be low, and map matching accuracy is improved.

Description

technical field [0001] The invention relates to the field of transportation, in particular to a map matching method based on conditional random fields and floating car data with low sampling frequency. Background technique [0002] In traffic travel, vehicle-mounted GPS devices have the functions of recording vehicle trajectories, routing, and navigation, and are widely used. Vehicle-mounted GPS devices can regularly and in real time transmit vehicle location information (mainly including vehicle identifiers, offset latitude and longitude, and time stamps, etc.) to the information processing center through the wireless communication system. Floating vehicles generally refer to buses and taxis that are equipped with such vehicle-mounted GPS devices and drive on urban arterial roads. In addition, GPS equipment is susceptible to environmental noise interference, the reliability of GPS equipment itself and the limitations of positioning technology itself, all of which will affe...

Claims

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Application Information

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IPC IPC(8): G01C21/30
CPCG01C21/30
Inventor 杨旭华彭朋徐恩平刘斌
Owner ZHEJIANG UNIV OF TECH
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