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Special unmanned sightseeing vehicle network planning method

A technology of unmanned driving and sightseeing vehicles, applied in the direction of two-dimensional position/channel control, etc., can solve the problem of finding passenger flow density, achieve the effects of reducing time and distance, improving turnover efficiency, improving accuracy and practicality

Pending Publication Date: 2021-11-02
上海淞泓智能汽车科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In this invention, although the sightseeing car adopts unmanned driving technology, it cannot find the running path of multiple sightseeing cars with the highest passenger flow density and the smallest detour while meeting the needs of all scenic spots.

Method used

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  • Special unmanned sightseeing vehicle network planning method
  • Special unmanned sightseeing vehicle network planning method
  • Special unmanned sightseeing vehicle network planning method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0072] This embodiment introduces a network planning method for dedicated unmanned sightseeing vehicles.

[0073] Please refer to figure 1 , figure 1 A flowchart of a network planning method for dedicated unmanned sightseeing vehicles provided by the present invention, which shows a method for planning a dedicated unmanned sightseeing vehicle age network, including the following steps:

[0074] Step 1: Use the original sightseeing bus route as the initial path of the algorithm, and place a certain amount of pheromone on its path, and draw up the sightseeing bus route;

[0075] Step 2: Use the shortest path allocation method to allocate the passenger flow in the OD demand matrix to all the sightseeing bus lines in the sightseeing bus network;

[0076] Step 3: update the pheromone;

[0077] Step 4: Set up a penalty mechanism for the travel of the solution that does not meet the constraint conditions.

[0078] Furthermore, the goal of sightseeing vehicle network planning is t...

Embodiment 2

[0086] Based on the above-mentioned embodiment 1, this embodiment mainly introduces the ant colony algorithm and step 1 applied in a network planning method for a dedicated unmanned sightseeing vehicle.

[0087] The ant colony algorithm first applied, please refer to figure 2 , figure 2 A flow chart of the ant colony algorithm for a dedicated unmanned sightseeing vehicle line network planning method provided by the present invention, which shows that the ant colony algorithm includes the following steps:

[0088] S101: Initialize the ant colony size antSize and the number of iterations K;

[0089] S102: assign antSize ants to the starting point, and add the starting point to the taboo list;

[0090] S103: Each ant selects the next node according to the following probability selection formula according to the heuristic information and pheromone strength. If the end point is reached or no next node can be found, the search stops, otherwise the search continues.

[0091] ...

Embodiment 3

[0109] Based on the above-mentioned embodiment 2, this embodiment mainly introduces step 2 in a network planning method for a dedicated unmanned sightseeing vehicle.

[0110] Step 2: Use the shortest path allocation method to distribute the passenger flow in the OD demand matrix to all the sightseeing bus lines in the sightseeing bus network.

[0111] In the ant colony algorithm, each ant is trying to find a new route for a sightseeing bus route. When an ant finds a new route, it needs to use the evaluation function to calculate it. And in order to calculate the evaluation function value, must be calculated.

[0112] In order to evaluate the new route generated by ants, replace the original route that needs to be adjusted with the newly generated route, and then form a new sightseeing car route network with the new route and other sightseeing car routes in the original sightseeing car route network. Because in the process of adjusting the sightseeing car network, the perfo...

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Abstract

The invention introduces a special unmanned sightseeing vehicle network planning method, which comprises the following steps of: 1, using an original sightseeing vehicle route as an initial path of an algorithm, placing a certain amount of pheromones on the path, and drawing up the route of a sightseeing vehicle; 2, distributing passenger flow in the OD demand matrix to all sightseeing vehicle lines in the sightseeing vehicle line network by adopting a shortest path distribution method; 3, updating the pheromones; 4, setting a punishment mechanism for the travel of the solution which does not conform to the constraint condition. Compared with a sightseeing vehicle service mode adopting a fixed line and a fixed sightseeing vehicle stop point, the cost is saved by using the ant colony algorithm, and the turnover efficiency of the sightseeing vehicle is improved. Therefore, under the condition of meeting the requirements of all scenic spots, the running path of the plurality of sightseeing vehicles with the maximum passenger flow density and the minimum bypassing is found.

Description

technical field [0001] The invention relates to vehicle line planning, in particular to a line network planning method for special unmanned sightseeing vehicles. Background technique [0002] Unmanned vehicle path planning refers to planning an effective path without collision and safely reaching the target point according to the performance index after the starting point and the target point of the unmanned vehicle are given on the basis of a certain environment model. For unmanned sightseeing vehicles, it is necessary to first determine their fixed stops and driving routes according to the needs of tourists. According to the input stops, the unmanned sightseeing vehicles will quickly search for the driving path in the environment map in real time. [0003] The conventional practice is to use fixed routes and fixed sightseeing car stops, but the number of sightseeing cars in the scenic area is fixed. In order to save costs and improve the turnover efficiency of sightseeing ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G05D1/02
CPCG05D1/0221G05D1/028G05D1/0276
Inventor 林中朴周柳安康魏俊生
Owner 上海淞泓智能汽车科技有限公司