Vehicle Control Spatial Information Generation via V2X
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Solution Overview
Problem
Current vehicle recognition technologies, particularly for autonomous driving, face limitations in accurately recognizing three-dimensional space and obstacle dimensions using cameras, which hinders effective vehicle control and path generation.
Innovation Solution
A system and method for vehicle control that utilizes a combination of image sensors, communicators, and processors to capture and process image data, receive vehicle information via V2X communication, and generate spatial information to determine a travel path based on three-dimensional space recognition, incorporating specifications of other vehicles to enhance navigation and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a camera is used to capture surrounding space, then the system can detect obstacles and their positions, but it cannot accurately obtain three-dimensional information such as length and width of obstacles
Solution Approach 1:
The patent combines multiple sensing systems (camera, radar, LIDAR, ultrasonic sensors) to create a comprehensive spatial recognition system. Each sensor type compensates for the limitations of others, with radar and LIDAR providing accurate 3D measurements that supplement the camera's visual detection capabilities, thereby resolving the contradiction between detection coverage and measurement precision
Solution Approach 2:
The patent introduces V2X communication as an intermediary to obtain specification information about other vehicles. This external information source provides accurate dimensional data about detected vehicles, which the host vehicle's sensors alone cannot determine, thus弥补ing the information loss about obstacle dimensions
2Reliability
If only camera-based recognition is used, then the system structure remains simple, but accurate 3D space recognition and vehicle control become impossible
Solution Approach 1:
The patent creates a multi-functional sensing system where each component serves multiple purposes. The camera provides both visual identification and rough positioning, while radar supplements with precise distance and velocity data. This multi-functionality approach ensures reliable vehicle control through redundant information sources without requiring completely separate systems for each function
Solution Approach 2:
The patent divides the sensing system into specialized modules (camera module, radar module, LIDAR module, ultrasonic module, V2X communication module), each optimized for specific detection tasks. This segmentation allows the complex system to be managed through modular architecture, where each module contributes specific capabilities to the overall reliable vehicle control function
3Productivity
If the system does not consider vehicle specification information, then processing is simpler, but accurate travel path generation considering other vehicles' expected travel regions is not possible
Solution Approach 1:
The patent applies preliminary action by pre-obtaining specification information about other vehicles through V2X communication before path planning begins. This advance information about vehicle dimensions and characteristics allows the path planning algorithm to pre-calculate safe travel regions and expected travel paths of other vehicles, improving overall path planning efficiency while maintaining high scenario adaptability
Data Source
AI summary
Provided are a system, apparatus, and method for vehicle control and more particularly. The apparatus includes a first spatial information generator configured to generate first spatial information at a vicinity of a host vehicle, based on at least one of image data or sensing data, a vehicle specification receiver configured to receive first vehicle information, which is vehicle information of at least one of external vehicles existing the vicinity of the host vehicle and a second spatial information generator configured to generate second spatial information of the vicinity of the host vehicle by modifying the first spatial information based on the first vehicle information.