Vehicle Target Object Distance Estimation From User Landmark Features
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current techniques for dispatching ultra-small mobility vehicles lack an efficient method to accurately estimate the distance to a user-selected target object, such as a landmark, which is essential for precise vehicle positioning and user boarding.
Innovation Solution
A system that acquires target object data from a user via a communication device, analyzes the data for proper nouns, character strings, or colors related to the target object, and estimates the distance based on these features, with weighting given to candidate objects closer or farther based on the presence of these data types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Length of stationary object
If the system uses color data to identify target objects, then the system can recognize objects at longer distances, but the distance estimation becomes less precise compared to using proper nouns or character strings
Solution Approach 1:
The system dynamically adjusts the weighting parameter for distance estimation based on the type of feature data available. When proper nouns or character strings are detected, a higher weight is applied for precision; when only color data is available, a lower weight is applied to account for reduced accuracy at longer distances
Solution Approach 2:
The system uses multiple types of feature data (proper nouns, character strings, colors) partially, combining them with different weights. Color data alone provides partial information for distant objects, while proper nouns and character strings provide more precise information when available, creating a layered approach to distance estimation
2Measurement precision
If the system requires explicit distance designation by the user, then the distance measurement would be most accurate, but the ease of operation decreases significantly
Solution Approach 1:
The system automatically performs distance estimation by analyzing target object data extracted from user input. Instead of requiring users to manually input distances, the system self-services by inferring distance information from the presence and type of features (proper nouns, character strings, colors) in the user-provided target object description
Solution Approach 2:
The system introduces feature data (proper nouns, character strings, colors) as an intermediary between the user and the distance measurement function. Users provide natural language descriptions of target objects, and the system uses these intermediate features to indirectly derive distance information without requiring explicit numerical input
Data Source
AI summary
A system including an acquisition unit configured to acquire, from a user via a communication device associated with the user, target object data including a feature of a target object selected by the user, an analysis unit configured to analyze whether the target object data that has been acquired by the acquisition unit includes, as the feature, at least one of data of a proper noun or data of a character string related to the target object, and whether the target object data includes data of a color related to the target object, and an estimation unit configured to estimate a distance from the target object to the user, based on an analysis result of the analysis unit, wherein the estimation unit estimates the distance from the target object to the user such that the distance from the target object to the user in a case where the target object data includes at least one of the data of the proper noun or the data of the character string is shorter than the distance from the target object to the user in a case where the target object data includes the data of the color is provided.