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Vehicle GPS data map matching method based on hidden markov model

A hidden Markov and GPS data technology, applied in the field of transportation, can solve the problem of vehicle trajectory data deviation and other problems, and achieve the effect of map matching

Inactive Publication Date: 2017-04-26
FUZHOU UNIV
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  • Claims
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Problems solved by technology

However, due to the limitations of the equipment itself and the influence of external environmental noise, the vehicle trajectory data often deviates from the actual data, and the purpose of map matching is to accurately map the observed trajectory data to the road network position

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  • Vehicle GPS data map matching method based on hidden markov model
  • Vehicle GPS data map matching method based on hidden markov model
  • Vehicle GPS data map matching method based on hidden markov model

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0042] This embodiment provides a vehicle GPS data map matching method based on a hidden Markov model, such as Figure 4 shown, including the following steps:

[0043] Step S1: Obtain road network data from the electronic map:

[0044] The electronic map is a vector map in shapefile format. The road network data is obtained from the map to construct a directed road network G(V,E), where V represents the intersection of roads, and E represents the road section between every two intersections. For the convenience of calculation, define the road section set S={s n |n=1,2,...,N}, s n is the nth road segment. The starting and ending point of the road segment is s n .start={x,y}, the end point is s n .end={x,y}, x,y represent longitude and latitude respectively.

[0045] Step S2: Preprocessing the collected real vehicle trajectory data:

[0046]The co...

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Abstract

The invention relates to a vehicle GPS data map matching method based on a hidden markov model. The method comprises the following steps: acquiring route data from a shpefile electronic map; extracting original vehicle trajectory data, and preprocessing vehicle GPS data; taking a road section with a certain distance of each GPS observation point as a candidate road section; calculating the observation probability of each GPS point and transition probability of an adjacent candidate road section on the basis of the hidden markov model; and calculating an optimal matching trajectory by using a viterbi algorithm. The vehicle GPS data map matching method is based on the hidden markov model, by consideration of the positions of the GPS points, speed and direction, topology of a road network and the associated information between trajectory points and the road network, new observation probability and new transition probability are raised, and therefore, map matching accuracy is improved further.

Description

technical field [0001] The invention relates to the traffic field, in particular to a vehicle GPS data map matching method based on a hidden Markov model. Background technique [0002] In traffic travel, on-board equipment is becoming more and more popular, and research on GPS data has become a hot topic in the field of Internet of Vehicles today. However, due to the limitations of the equipment itself and the influence of external environmental noise, the vehicle trajectory data often deviates from the actual data, and the purpose of map matching is to accurately map the observed trajectory data to the road network position. The Hidden Markov Model is a probabilistic model that describes the process of randomly generating a hidden state random sequence from a hidden Markov chain, and then generating an observed state from each hidden state to generate an observed random sequence. Hidden Markov models are widely used in pattern recognition, speech recognition, biological in...

Claims

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Application Information

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IPC IPC(8): G01C21/30G06F17/18G06Q10/04G07C5/08
CPCG01C21/30G06F17/18G06Q10/047G07C5/08
Inventor 冯心欣王彪凌献尧徐艺文郑海峰陈忠辉
Owner FUZHOU UNIV
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