Multi-mode Route Selection with Confidence-Based Adaptation
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Solution Overview
Problem
Current web mapping services lack the ability to dynamically adjust multi-mode transportation routes based on real-time user data and confidence levels, potentially leading to decreased user satisfaction and safety during travel.
Innovation Solution
A method and system that utilize user and travel data to generate and modify routes by adjusting modes of transportation based on confidence scores, incorporating animation and virtual reality for guidance, and allowing for seamless transitions between different modes of transport, such as from vehicle to airplane, to enhance user confidence and route efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If web mapping services provide fixed parameter routing for single mode of transport, then routing functionality is achieved, but the system lacks dynamic adaptation to user conditions and multi-mode transitions
Solution Approach 1:
The system dynamically adjusts routing parameters and mode of transportation based on real-time user data and confidence scores. The route is not fixed but adapts continuously as the user progresses, with the ability to switch between different modes of transport (walking, driving, flying) based on changing conditions and user confidence levels.
Solution Approach 2:
The routing system serves multiple functions: it provides traditional step-by-step navigation, monitors user confidence levels, dynamically adjusts routes, and manages multi-mode transportation transitions. This multi-functional approach consolidates what would otherwise require separate systems into a unified route management platform.
2Reliability
If the system provides step-by-step guidance for a single mode of transport, then navigation accuracy is maintained, but user confidence may decrease in complex multi-mode scenarios
Solution Approach 1:
The system continuously monitors user confidence levels through user data input and provides feedback by adjusting the route and guidance accordingly. When confidence drops below a threshold, the system modifies the route to include more familiar or reliable transportation modes, creating a closed-loop feedback mechanism that maintains user confidence.
Solution Approach 2:
The system proactively monitors confidence levels and modifies routes before users experience significant discomfort or loss of direction. By detecting confidence drops early and pre-adjusting the route, the system prevents complete route failure or user disorientation rather than reacting after problems occur.
3Adaptability or versatility
If the system allows mode of transportation alterations in generated routes, then route flexibility improves, but real-time modification capability based on user data is lacking
Solution Approach 1:
The system automatically monitors user data, calculates confidence scores, and modifies routes without requiring explicit user requests. The route management system serves itself by detecting when confidence drops and autonomously generating alternative routes with different transportation modes, eliminating the need for manual route re-planning.
Solution Approach 2:
The system replaces manual route planning and modification with automated computational processes. Instead of requiring users to manually switch between transportation modes or re-plan routes, the system uses algorithms to automatically generate and switch between multi-mode transportation options based on real-time data analysis.
Data Source
AI summary
A method managing a generated route for multiple modes of transportation includes displaying guidance for a generated route based on a travel itinerary between an origin location and a destination location, wherein the generated route includes at least one mode of transportation alteration. The method receives user data associated with a user traveling at a specific point along the generated route. The method generates a confidence score for the user traveling along generated route based on the received user data. Responsive to determining the confidence score is below a confidence level threshold, the method modifies the generated route based on an analysis of the generated route at the specific point, wherein the modified route causes the confidence score to increase above the confidence level threshold. The method displays guidance for the modified route.