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Path planning method based on automobile fuel consumption

A path planning and fuel consumption technology, applied in vehicle position/route/altitude control, motor vehicles, two-dimensional position/channel control, etc., can solve problems that have no practical significance, and achieve the effect of augmented reality

Pending Publication Date: 2021-12-07
JILIN UNIV
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  • Summary
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, most path planning methods use the path length as the only metric to judge the performance of the method. However, considering the economic cost and environmental cost of travel, and restricted by the current complex urban traffic environment, the method of choosing the path with the shortest path length Often too idealistic and does not have strong practical significance

Method used

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  • Path planning method based on automobile fuel consumption
  • Path planning method based on automobile fuel consumption
  • Path planning method based on automobile fuel consumption

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Embodiment Construction

[0058] The present invention will be further described below. It should be noted that this embodiment is based on the technical solution and provides detailed implementation and specific operation process, but the protection scope of the present invention is not limited to this embodiment.

[0059] This embodiment provides a route planning method based on vehicle fuel consumption, and the specific process is as follows:

[0060]S1. Use the result of the ant colony algorithm as the parameter of the A-star algorithm:

[0061] Remember the probability that the ants choose the next position j based on the current position i during the pathfinding process for:

[0062]

[0063] Among them, allow p Represents the set of all positions that the ant can choose in the next step, ε is the information heuristic factor, σ is the expected heuristic factor, ω ij (t) is the pheromone concentration of the current path, ξ ij (t) is a heuristic function, and t is time.

[0064] Consider...

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Abstract

The invention discloses a path planning method based on automobile fuel consumption. The path planning method comprises the specific steps of S1, taking the result of an ant colony algorithm as a parameter of an A star algorithm; S2, calculating driving oil consumption; S3, calculating the total idling fuel consumption; and S4, conducting path finding by the A star algorithm. According to the invention, the automobile fuel consumption serves as the judgment basis of the performance of the method, meanwhile, the idle speed time of the automobile at the traffic light and the corresponding idle speed fuel consumption are considered, the improved ant colony algorithm is used in combination with the A star algorithm to obtain the corresponding optimal path, the optimal path is used for urban traffic path planning, and then the practical significance of the selected path is enhanced.

Description

technical field [0001] The invention relates to the technical field of automobiles, in particular to a route planning method based on automobile fuel consumption. Background technique [0002] At present, most path planning methods use the path length as the only metric to judge the performance of the method. However, considering the economic cost and environmental cost of travel, and restricted by the current complex urban traffic environment, the method of choosing the path with the shortest path length It is often too idealistic and does not have strong practical significance. Contents of the invention [0003] Aiming at the deficiencies of the prior art, the present invention aims to provide a method for route planning based on vehicle fuel consumption. [0004] In order to achieve the above object, the present invention adopts the following technical solutions: [0005] A path planning method based on vehicle fuel consumption, the specific process is: [0006] S1. ...

Claims

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Application Information

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IPC IPC(8): G05D1/02
CPCG05D1/0221G05D1/0276
Inventor 张晋东刘天博
Owner JILIN UNIV
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