Route Evaluation Using Satellite Images and Driver Preferences
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Solution Overview
Problem
Existing navigation devices provide insufficient added value to drivers by relying solely on landscape information for route selection.
Innovation Solution
An information processing device that acquires satellite images and driver preference information to evaluate and propose highly relevant travel routes, incorporating real-time data to enhance route selection based on driver preferences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If route selection is based only on landscape information, then the navigation device can provide basic route guidance, but it cannot provide sufficient added value to the driver
Solution Approach 1:
The system performs preliminary actions by acquiring and storing driver preference information in advance, including preferences for landscape types (mountain, sea, river, forest), specific plants (flowers, trees), and events (festivals, fireworks). This pre-acquisition of preference data enables the route evaluation function to quickly match driver preferences with satellite image data without requiring complex real-time processing during navigation.
Solution Approach 2:
The patent introduces satellite images as an intermediary element that bridges the gap between driver preferences and route evaluation. The satellite images provide real-time visual information about landscapes, plants, and events along potential routes, serving as a mediator that translates abstract preference data into concrete route recommendations without requiring direct complex interactions between all preference parameters.
2Adaptability or versatility
If the system uses satellite images to evaluate routes based on driver preferences, then added value is provided to the driver, but more information processing is required
Solution Approach 1:
The route evaluation function is segmented into distinct processing stages: acquiring satellite images of the route area, extracting feature information (landscapes, plants, events) from the images, comparing extracted features with driver preferences, and generating evaluation results. This segmentation allows each stage to be optimized independently, improving overall evaluation efficiency while maintaining high adaptability to different driver preferences.
Solution Approach 2:
The system dynamically changes evaluation parameters based on driver preferences. When a driver expresses preference for specific landscapes, plants, or events, the system adjusts the weight and criteria of corresponding parameters in the route evaluation algorithm. This parameter adaptation enables versatile route evaluation tailored to individual drivers while maintaining computational efficiency through focused processing on relevant parameters.
3Ease of operation
If the system proposes multiple highly evaluated routes, then driver choice is enhanced, but information processing time increases
Solution Approach 1:
The system applies partial action by generating a limited number of highly evaluated routes (e.g., top 3-5 routes) rather than evaluating and presenting all possible routes. This approach provides sufficient choice for drivers to make informed decisions while avoiding the excessive processing time that would result from evaluating every possible route combination. The system focuses computational resources on identifying and presenting the most relevant route options.
Data Source
AI summary
The information processing device acquires a satellite image captured by an artificial satellite in a range from a current position of the vehicle to a destination, acquires preference information regarding a preference of the driver, evaluates a traveling route to the destination based on the satellite image and the preference information, and outputs an evaluation result of the traveling route.