Map Engine Routing with Trusted Source Constraints
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Solution Overview
Problem
Current map applications do not have an easy way to incorporate user-received recommendations from friends and family into route calculations, limiting their ability to generate routes based on positive or negative areas of interest with specific constraints such as time and transportation modes.
Innovation Solution
A system and method that utilize a map engine to receive and process recommendations from trusted sources, determining applicable areas of interest with time and transportation constraints, and generate routes that either pass through or avoid these areas based on user requests, incorporating user preference and social networking data for route optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If map applications calculate routes based solely on shortest distance, then route efficiency is improved, but user preferences and trusted recommendations cannot be incorporated
Solution Approach 1:
The routing system dynamically adjusts route calculation by integrating user-specific constraints and preferences from trusted sources. The system adapts the route generation process to individual users by incorporating their unique area of interest constraints, allowing the same map application to provide personalized routing experiences while maintaining overall system efficiency
Solution Approach 2:
The patent segments the routing problem into multiple independent constraint layers (e.g., positive areas of interest, negative areas of interest, time constraints, transportation mode constraints). Each constraint type is processed separately and then integrated into the final route calculation, allowing the system to maintain efficiency while incorporating diverse user preferences
2Ease of operation
If map applications incorporate multiple user constraints and preferences, then user satisfaction is improved, but system complexity increases
Solution Approach 1:
User constraints and preferences are collected and stored in advance before actual route calculation is needed. The system pre-processes user preferences from trusted sources and maintains them as reusable constraint profiles, eliminating the need to gather this information repeatedly during each routing operation and reducing real-time computational complexity
Solution Approach 2:
The patent introduces an intermediary constraint management layer that sits between user preferences and the core routing algorithm. This intermediary layer standardizes and normalizes diverse user constraints into a unified format that the routing algorithm can efficiently process, reducing the complexity burden on the core routing system
3Adaptability or versatility
If map applications consider time and transportation mode constraints from trusted sources, then route personalization is improved, but calculation time increases
Solution Approach 1:
The system optimizes route calculation by strategically selecting and applying only the most relevant constraints from the user profile based on the specific trip context. Rather than evaluating all possible constraints uniformly, the system dynamically adjusts which parameters are actively applied, reducing calculation time while maintaining personalization quality
Data Source
AI summary
Identifications of areas of interest are received from trusted sources such as contacts in a social networking application. The areas of interest can include geographic boundaries that identify regions such as blocks or portions of streets. The areas of interest can be associated with constraints such as modes of transportation (e.g., car, bicycle, walk, etc.) or times (e.g., 9 am-5 pm, at night, in the morning, etc.), and can be positive or negative (e.g., go here or don't go here). When generating a route for a user, the map application considers the areas of interest based on the constraints associated with the areas of interest and other information such as what mode of transportation that the user is using and when the user is planning on traveling the route.