Route Selection Using Road Nonlinearity Values
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Solution Overview
Problem
Current route-determining systems do not effectively account for user preferences in road nonlinearity characteristics, such as horizontal curvature, twistiness, gradient, hilliness, and exhilaration, when recommending travel routes, leading to routes that may not align with user desires for excitement or comfort.
Innovation Solution
A processor-implemented method that stores and calculates road nonlinearity values for each road section, allowing users to input desired route-specific values, and selects a candidate route based on comparison with user preferences, including options to maximize or minimize road nonlinearity, while providing navigational guidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If route-determining systems minimize travel time or travel distance, then efficiency is improved, but user preferences for road nonlinearity characteristics (excitement or comfort) are not accounted for
Solution Approach 1:
The system changes the parameters used for route evaluation by incorporating road nonlinearity characteristics (horizontal curvature, twistiness, gradient, hilliness, exhilaration) as additional evaluation criteria. Instead of minimizing only time or distance, the system evaluates routes based on multiple parameters including user-preferred nonlinearity characteristics, allowing flexible adjustment of route selection criteria to match user desires for excitement or comfort.
Solution Approach 2:
The system dynamically adjusts route recommendations based on user inputs regarding desired road nonlinearity characteristics. The evaluation criteria are not fixed but can be modified according to user preferences, enabling the system to adapt between efficiency-oriented routes and excitement-oriented routes by adjusting the weighting and selection of nonlinearity parameters.
2Ease of operation
If route-determining systems provide standard efficiency routes, then simplicity is maintained, but user desires for specific road characteristics are not met
Solution Approach 1:
The system performs preliminary evaluation of road sections to calculate nonlinearity characteristics (horizontal curvature, twistiness, gradient, hilliness, exhilaration) and stores this data in advance. This preliminary action enables the system to quickly compare and evaluate multiple candidate routes against user preferences without requiring complex real-time calculations, maintaining simplicity while enabling customization.
Solution Approach 2:
The system evaluates and selects routes based on local road characteristics at different segments. By analyzing specific nonlinearity characteristics at local levels (horizontal curvature at certain points, twistiness in specific areas, gradient and hilliness in particular zones), the system can customize routes to match user preferences for excitement or comfort while maintaining overall route efficiency.
3Adaptability or versatility
If routes maximize road nonlinearity for excitement, then user preference for excitement is met, but fuel consumption and vehicle wear increase
Solution Approach 1:
The system dynamically balances route selection between excitement and efficiency by adjusting the weighting of nonlinearity characteristics. Users can specify desired levels of road nonlinearity, and the system optimizes routes accordingly, allowing flexible adjustment between excitement-oriented routes (higher nonlinearity) and efficiency-oriented routes (lower nonlinearity, reducing fuel consumption and vehicle wear).
Solution Approach 2:
The system changes the evaluation parameters to include trade-off considerations between nonlinearity characteristics and energy consumption. By incorporating factors like horizontal curvature, twistiness, gradient, and hilliness into the evaluation while considering their impact on fuel consumption and vehicle wear, the system can optimize routes that balance user excitement preferences with energy efficiency.
Data Source
AI summary
A processor-implemented method includes storing, for each of multiple road sections, section-specific road-nonlinearity values relating to road-nonlinearity characteristics of the respective road section. The method includes receiving, from a user, user-desired route-specific road-nonlinearity values relating to the road-nonlinearity characteristics. The method further includes calculating, from the stored section-specific road-nonlinearity values, for a candidate route, one or one route-specific road-nonlinearity values relating to the road-nonlinearity characteristics. The candidate route's route-specific road-nonlinearity values are compared to the user-desired route-specific road-nonlinearity values. Based on results of the comparison, the candidate route is select to be a recommended route. The recommended route is communicated to the user.


