Personalized Route Planning via Deviation Feedback
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Solution Overview
Problem
Conventional GPS-based route planning systems do not effectively account for user preferences and reasons for deviations from planned routes, leading to suboptimal route recommendations in subsequent trips.
Innovation Solution
A method that generates a first planned routing, detects deviations, receives user input for reasons behind the deviations, and revises the routing algorithm to create a personalized second planned routing, considering factors such as scenic routes or vehicle type, for improved route planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional GPS-based route planning systems provide recommended directions based on standard algorithms, then route planning is simple and fast, but the system does not account for user preferences and reasons for deviations, leading to suboptimal route recommendations in subsequent trips
Solution Approach 1:
The system implements feedback by detecting when users deviate from recommended routes and collecting information about their reasons for deviation. This feedback is then used to update and personalize the routing algorithm, allowing the system to learn from user behavior and improve future route recommendations. The feedback loop transforms static route planning into a dynamic, adaptive process that continuously improves based on actual user preferences.
Solution Approach 2:
The system performs preliminary action by proactively detecting deviations from planned routes and collecting user feedback about why the deviations occurred. Rather than waiting for users to manually input preferences, the system anticipates that deviations may indicate preference mismatches and automatically gathers information to prevent similar issues in future trips. This preliminary data collection enables personalized routing to be implemented in subsequent trips.
2Adaptability or versatility
If the system collects and processes user feedback about route deviations to personalize routing algorithms, then route recommendations become more personalized and relevant, but the system complexity increases
Solution Approach 1:
The system applies local quality by personalizing the routing algorithm specifically for individual users based on their deviation patterns and stated preferences, rather than attempting to create a completely new global routing system. The personalization is applied locally to each user's trip planning, allowing the core routing algorithm to remain relatively simple while adding adaptive layers that tailor recommendations to individual users without requiring complete system redesign.
3Measurement precision
If the system detects deviations and revises routing algorithms based on user input, then subsequent route planning becomes more accurate, but additional time is required for deviation detection and algorithm revision
Solution Approach 1:
The system applies partial action by focusing deviation detection and feedback processing only on trips where deviations actually occur, rather than processing every trip equally. When no deviations occur, the system uses the existing algorithm without additional processing overhead. This selective approach ensures that time is invested only when personalization can improve accuracy, avoiding unnecessary processing time for trips where the standard algorithm already provided satisfactory results.
Data Source
AI summary
Personalizing travel route planning based on past actual user travel behavior and reasons that the user deviated from planned routings. The route planning algorithm is revised based on analysis of user input related to a deviation from a planned routing. If a new trip in the planning stage entails considerations similar to those that caused the user's deviation on a previous trip, then the revised route planning algorithm can take these considerations into account when planning the route for the new trip. Changes in route planning may apply when the user: (i) plans to make a trip similar to a previous trip when the deviation occurred; (ii) plans to make a different trip, but the trip entails considerations that lead to the deviation on the prior trip; (iii) is using the same vehicle as for the previous trip with the deviation; and/or (iv) is using a different vehicle.