Route Selection System with Multi-Criteria Customization
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Solution Overview
Problem
Current map systems do not effectively allow users to select routes based on a variety of preferences, such as lighting, travel surface, population density, weather, distance, speed, and calorie burn, making it difficult for users to plan and navigate routes that meet their specific needs.
Innovation Solution
A system that receives user input for route preferences and provides customizable route options on a map, allowing users to select routes based on multiple criteria, including lighting, travel surface, population density, weather, distance, speed, and calorie burn, using a combination of modules for route generation, retrieval, and display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple route criteria (lighting, surface, population density, weather, distance, speed, calorie burn) are integrated into the route selection system, then route customization and user preference matching are improved, but system complexity and computational requirements increase
Solution Approach 1:
The route selection system is divided into multiple independent modules, each responsible for a specific criterion (lighting conditions, surface type, population density, weather, distance, speed, calorie burn). Each module processes its specific criterion separately and contributes to the overall route evaluation, allowing the system to handle multiple criteria without becoming unmanageably complex.
Solution Approach 2:
The system employs a universal route evaluation framework that can accommodate multiple different criteria through a common scoring and ranking mechanism. This multi-functional approach allows the same core system to handle various route selection needs by simply adjusting which criteria are active and their respective weights, rather than requiring separate systems for each criterion.
2Measurement precision
If real-time route calculation and multiple criterion evaluation are performed, then route planning accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
The system pre-calculates and stores route data based on various criteria combinations before user requests arrive. When a user submits a route request, the system retrieves and combines pre-computed results rather than calculating everything from scratch, significantly reducing response time while maintaining accuracy.
Solution Approach 2:
The system implements incremental route evaluation, where routes are scored and ranked based on available criteria without requiring all criteria to be fully processed. This allows the system to provide satisfactory route recommendations even when some criteria cannot be fully evaluated, reducing overall processing time while maintaining sufficient accuracy for user needs.
Data Source
AI summary
In one embodiment, a method of selecting a route for a user is disclosed. The method includes a routing computer presenting a map on a display operably coupled to the routing computer. The routing computer receives a start location and distance criteria via user input, and a plurality of routing criteria. The routing computer determines a plurality of routes that start and end at the start location based on the distance criteria and the routing criteria, and displays at least one of the plurality of routes on the map. Further, the routing computer receives route editing instructions via user input, and modifies at least one of the plurality of routes based on the editing instructions to create one or more modified routes.