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
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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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