Tourism route recommendation method, vehicle machine and storage medium
By receiving user requests, acquiring vehicle and attraction information, and using a pre-trained model to determine and rate travel routes, this technology solves the problem of imbalance in route recommendations in existing technologies and achieves a balance between route length, time spent, cost, and user experience.
CN122262418APending Publication Date: 2026-06-23VOYAH AUTOMOBILE TECH CO LTD
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Patent Information
- Application Number
- CN202610175264.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-02-06
- Publication Date
- 2026-06-23
AI Technical Summary
Technical Problem
Existing travel route recommendation methods cannot achieve a balance between itinerary, time spent, cost, and experience.
Method used
By receiving user input of travel route requirements, the system obtains vehicle location information, charging station information, and attraction information. It then uses a pre-trained travel route model to determine multiple travel routes, scores them using a weighted average method, and outputs recommended routes, taking into account route length, travel time, travel cost, and experience.
Benefits of technology
It achieves a balance between short route length, short travel time, low travel cost, and high experience in the recommended routes.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention provides a tourism route recommendation method, a vehicle machine and a storage medium, and relates to the technical field of vehicle-mounted tourism services. According to the method, the path length, the spent time length, the required travel cost and the experience average score of all scenic spots of each travel path can be obtained. Then, for each travel path, determining a first sub-score corresponding to the path length, a second sub-score corresponding to the spent duration, a third sub-score corresponding to the travel cost and a fourth sub-score corresponding to experience score averaging; performing weighted average on the first sub-score, the second sub-score, the third sub-score and the fourth sub-score of each travel path to obtain a recommendation score of each travel path; and sorting the first N% of travel paths based on the recommendation scores, and outputting the recommended paths, so that short path length, long consumed time, low travel cost and high experience average score can be considered, and the travel, the consumed time, the cost and the experience feeling of the user are balanced.
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