Route Guidance Apparatus for Multi-Point Transit with Charging Integration
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional navigation systems fail to efficiently guide users to visit multiple transit points, such as tourist spots and charging stations, while considering user preferences and battery charging needs.
Innovation Solution
A route guidance apparatus that acquires user request information and event information for each transit point, calculates a matching degree based on user priorities, and decides a go-around route that includes transit points with higher matching degrees and charging stations, optimizing travel distance and time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional navigation systems guide users to a single destination, then the route is simple and easy to follow, but the user cannot efficiently visit multiple transit points such as tourist spots and charging stations
Solution Approach 1:
The patent segments the route guidance function into multiple specialized units: an acquisition unit that collects user requests and event information, a selection unit that identifies transit points based on matching degrees, and a decision unit that determines the optimal go-around route. This segmentation allows the system to handle multiple transit points efficiently while maintaining manageable complexity through modular design.
Solution Approach 2:
The system dynamically adjusts route guidance based on real-time inputs including user preferences, event information at transit points, and battery status. The selection unit calculates matching degrees dynamically, and the decision unit optimizes the go-around route considering changing conditions such as charging needs and visit priorities, making the system adaptable rather than static.
2Adaptability or versatility
If the system prioritizes visiting multiple transit points, then user preferences and event participation improve, but travel time and distance increase
Solution Approach 1:
The acquisition unit collects user requests and sets priorities in advance before route calculation. The selection unit pre-identifies suitable transit points by calculating matching degrees between user preferences and event information. This preliminary preparation allows the decision unit to optimize the go-around route efficiently, balancing transit point visits with reasonable travel time by having all necessary information ready before route determination.
Solution Approach 2:
The system changes key parameters including the matching degree calculation (which incorporates user priority settings), the route optimization criteria (which considers both distance/time and transit point visits), and the battery status threshold for including charging stations. By adjusting these parameters based on user preferences and real-time conditions, the system achieves adaptability while controlling travel time through intelligent parameter selection.
3Reliability
If the system includes charging stations in the route, then battery depletion risk is reduced, but the route complexity and decision-making process increase
Solution Approach 1:
The selection unit pre-identifies charging stations among candidate transit points by checking their charging capabilities before the decision unit finalizes the route. The decision unit then simply includes or excludes these pre-identified charging stations based on battery status thresholds, rather than performing complex real-time optimization. This preliminary identification reduces the decision-making complexity while ensuring reliable battery charge availability.
4Measurement precision
If the system calculates matching degrees for all candidate transit points, then transit point selection accuracy improves, but computational load increases
Solution Approach 1:
The selection unit calculates matching degrees for all candidate transit points to ensure comprehensive and accurate selection, even though this requires significant computational power. The system accepts the excessive action of calculating all matching degrees rather than using approximation methods, prioritizing selection accuracy over computational efficiency. This approach ensures that no potentially suitable transit point is missed due to incomplete evaluation.
Data Source
AI summary
The present invention provides a route guidance apparatus for guiding a go-around route of a plurality of transit points, the apparatus comprising: an acquisition unit configured to acquire request information of a user and event information for each of candidates of the plurality of transit points; a selection unit configured to select possible round transit points among the candidates of the plurality of transit points in accordance with a matching degree between the request information and the event information; and a decision unit configured to decide a go-around route of the transit points selected by the selection unit.