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Urban K rule time-varying shortest path acquisition method considering safety and efficiency

A technology of the shortest path and acquisition method, which is applied in traffic control systems, instruments, and traffic flow detection of road vehicles. It can solve the problems that the navigation results may not be close to the actual situation, find travel costs, and cannot induce vehicles, etc., so as to alleviate urban traffic. Pressure, ensuring travel safety, and reducing traffic congestion

Active Publication Date: 2022-03-11
HEFEI UNIV OF TECH
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Problems solved by technology

[0003] However, in the existing technology, there are the following deficiencies. First, the existing navigation algorithms seldom establish a clearer connection with the real-time road conditions in the future, so that the navigation results may not be close to the actual situation; Comprehensive consideration of risk costs other than cost, etc., existing algorithms cannot induce vehicles to find the optimal route with lower travel costs and safer; third, as the scale of urban road networks continues to expand, the journey between a pair of origins and destinations Selection can have multiple different paths

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  • Urban K rule time-varying shortest path acquisition method considering safety and efficiency
  • Urban K rule time-varying shortest path acquisition method considering safety and efficiency
  • Urban K rule time-varying shortest path acquisition method considering safety and efficiency

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Embodiment Construction

[0057] In this embodiment, a time-varying shortest path acquisition method for city K considering the dual objectives of safety and efficiency, the specific flow chart is as follows figure 1 As shown, proceed as follows:

[0058] Step 1: Define parameters and initialize;

[0059] Obtain real-time road network data and obtain urban road network graph G=(V, A), the calculation example that the present invention adopts image 3 As shown, V represents the intersection node set, and V={v 1 ,v 2 ,v 3 ,...,v n ,...,v N}, v n Represents the nth intersection node, n=1,2,3...N, N represents the total number of intersection nodes; let v start Indicates the starting intersection node, v end represents the terminal intersection node, and v start , v end ∈V;

[0060] Define the nth intersection node v n The k-th short-circuit of is the path that ranks as the k-th path in ascending order of the comprehensive evaluation of travel time and travel risk value among all the paths that...

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Abstract

The invention discloses an urban K-rule time-varying shortest path acquisition method considering double targets of safety and efficiency. The method comprises the following steps: 1, acquiring a real-time urban road network map; 2, initializing a variable list label for each intersection node; 3, obtaining a Pareto optimal label set through Pareto sorting; 4, completing forward updating of the kth short path through intersection nodes in the Pareto optimal label set; and 5, finding a plurality of distance values and the shortest path from the starting point intersection node vstart to the terminal point intersection node vend, and backtracking and outputting the distance values and the shortest path. According to the method, K optimal travel paths considering efficiency and safety can be obtained, so that the personal travel safety and the stability and high efficiency of social traffic are guaranteed.

Description

technical field [0001] The invention belongs to the field of vehicle navigation path optimization, in particular to a method for obtaining the time-varying shortest path of city K in consideration of safety and efficiency. Background technique [0002] With the sharp increase in the number of residents' car ownership, navigation software has gained a large number of users and broad development space. The development of functions such as reducing travel time, avoiding congestion, and reducing tolls in the corresponding navigation algorithms provide great benefits for people's daily travel. convenience. [0003] However, in the existing technology, there are the following deficiencies. First, the existing navigation algorithms seldom establish a clearer connection with the real-time road conditions in the future, so that the navigation results may not be close to the actual situation; Considering the comprehensive consideration of risk costs other than cost, the existing algo...

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Application Information

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IPC IPC(8): G08G1/0968G08G1/01
CPCG08G1/0968G08G1/096833G08G1/0125
Inventor 丁建勋刘海生周润东江宇鹏樊银超丁卫东满忠运冯战雨徐小明龙建成
Owner HEFEI UNIV OF TECH
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