3D Object Data Complementation for Vehicle Surroundings View
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Solution Overview
Problem
Existing vehicle driving assistance systems fail to provide accurate and comprehensive information about objects around a vehicle, leading to insufficient driving assistance due to incomplete detection data, which can cause discomfort and safety concerns for drivers.
Innovation Solution
An information processing device that obtains three-dimensional detection data of objects outside the vehicle, complements it with pre-stored three-dimensional object data using data complementation, and synthesizes it with vehicle data to generate comprehensive three-dimensional synthesized data, providing a bird's-eye view or objective representation of the vehicle and its surroundings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If detection data is obtained using existing detection devices, then basic object detection is achieved, but the detection data is incomplete and lacks comprehensive information about objects around the vehicle
Solution Approach 1:
The system performs preliminary action by storing three-dimensional data of multiple objects in advance in a database. When detection data is obtained, the system can quickly retrieve and complement missing information from the pre-stored data, avoiding the need for complex real-time detection of all object details and reducing information loss.
Solution Approach 2:
The system introduces an intermediary component (the data complementation module) that bridges the gap between incomplete detection data and comprehensive object information. This intermediary retrieves supplementary data from pre-stored three-dimensional object models and integrates it with detection data, effectively reducing information loss without significantly increasing device complexity.
2Measurement precision
If only detection data from detection devices is used, then the system remains simple, but the driving assistance information is insufficient and inaccurate
Solution Approach 1:
The system merges detection data with pre-stored three-dimensional object data and vehicle data to create comprehensive synthesized data. This combination integrates multiple data sources to improve measurement precision and accuracy of driving assistance information, while the automated synthesis process manages the complexity of handling multiple data types.
Solution Approach 2:
The synthesized data serves multiple functions: it provides accurate object information for collision avoidance, comprehensive environmental awareness for navigation, and detailed vehicle-surroundings relationships for various driving assistance features. This multi-functionality justifies the increased system complexity by delivering high-precision information across multiple application areas.
3Loss of information
If comprehensive three-dimensional data synthesis is performed, then complete view of vehicle environment is achieved, but processing time and computational resources increase
Solution Approach 1:
By performing preliminary action of storing three-dimensional object data in advance, the system prepares comprehensive environmental information beforehand. During actual operation, the system only needs to retrieve and integrate this pre-prepared data with detection data, significantly reducing processing time while maintaining complete environmental information.
Solution Approach 2:
The system applies local quality by focusing computational resources on synthesizing data for specific regions or objects that require detailed information, rather than uniformly processing all data at maximum detail. This selective approach reduces overall processing time while maintaining completeness of environmental information where most critical.
Data Source
AI summary
The information processing device is an information processing device for generating driving assistance information for a vehicle. An information processing device includes: a detection data obtainer that obtains detection data, the detection data being three-dimensional data obtained by detecting an object located outside the vehicle; a data complementation that extracts object data from a plurality of pieces of three-dimensional data of objects stored in advance, the object data being three-dimensional data of the object corresponding to the detection data, and complements the detection data with the object data to generate complementary data that is three-dimensional data; and a data synthesizer that synthesizes the complementary data and vehicle data, the vehicle data being three-dimensional data of the vehicle, to generate synthesized data that is three-dimensional data including the vehicle and an external area of the vehicle.