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Road segment correlation considering time-varying random network dynamic path search method

A road section correlation and dynamic path technology, applied in the field of intelligent transportation, can solve problems such as traveler loss, and achieve the effect of improving the possibility, solving the huge amount of calculation, and ensuring the accuracy.

Active Publication Date: 2017-09-08
BEIHANG UNIV
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Problems solved by technology

In the actual road network, the traffic state is constantly changing, and sudden traffic congestion may bring huge losses to travelers

Method used

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  • Road segment correlation considering time-varying random network dynamic path search method
  • Road segment correlation considering time-varying random network dynamic path search method
  • Road segment correlation considering time-varying random network dynamic path search method

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Embodiment Construction

[0018] The present invention will be further described in detail below in conjunction with the accompanying drawings.

[0019] The present invention is a time-varying stochastic network dynamic path search method considering road section correlation, the flow chart is as follows figure 1 shown, including the following steps:

[0020] Step 1. Collect road network status information, and establish a dynamic travel time database based on the preprocessed data

[0021] 1a) Create an abstract directed graph

[0022] Establish an abstract directed graph G=(V,L,T) of the research area according to the map information, where V={1,2,3,...,n} represents the set of all nodes in the research area, L={( i,j)|i,j∈V,i≠j} is the set of all road sections that actually exist in the research area, and Ti is a random variable representing the travel time of road section i.

[0023] 1b) Real-time collection and processing of road network status information

[0024] The status information of th...

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Abstract

The invention discloses a road segment correlation considering time-varying random network dynamic path search method, and belongs to the field of intelligent transportation. The method comprises the steps of 1, acquiring road network state information, and building a dynamic travel time database based on preprocessed data; 2, setting a current travel demand by a traveler; 3, setting parameter of a genetic algorithm, generating an initial path set, and building a fitness function to calculate the fitness of each candidate path; 4, iteratively searching an optimal path based on the genetic algorithm, wherein a vehicle drives according to the optimal path acquired by iteration; and 5, realizing real-time update of the optimal path through judging the state of the vehicle and the state of the road network so as to ensure the vehicle to continuously drive within the optimal path until arriving at the destination. The algorithm provided by the invention not only sufficiently considers a series of complex factors such as the road network time varying, travel time random distribution and road segment correlation, but also well ensures the solving speed and the solving accuracy of the genetic algorithm at the same time, thereby being more conducive to realizing the dynamic path search method.

Description

technical field [0001] The invention discloses a time-varying random network dynamic path search method considering road section correlation, which belongs to the technical field of intelligent transportation. Background technique [0002] With the continuous development and expansion of cities, people's travel needs are becoming more and more diverse and punctual. In the actual road network, traffic conditions are constantly changing, and sudden traffic congestion may bring huge losses to travelers. Therefore, how to find the optimal path from the start point to the end point in the real-time changing traffic network has become a key issue to meet the travel needs of travelers. [0003] The time-varying stochastic network can better simulate the actual road network. In a time-varying random network, the travel time of each road segment is a random variable, which obeys a certain distribution in a small enough time period, and the parameters of the distribution will also c...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06N3/12
CPCG06N3/126G06Q10/047
Inventor 陈鹏童睿王云鹏鲁光泉鹿应荣
Owner BEIHANG UNIV
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