Autonomous Vehicle Path Planning in Mixed V2X Traffic
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Solution Overview
Problem
Current autonomous driving technologies focus on safe navigation of autonomous vehicles but lack effective methods for interacting with both V2X communication-capable and incapable vehicles, limiting the utilization of V2X technology for efficient and safe path planning.
Innovation Solution
A computing device integrates V2X communication and image processing to acquire recognition information, select interfering vehicles, generate potential interference prediction models, and modify optimized route information to evade potential obstacles, ensuring safe navigation in mixed V2X communication environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If V2X communication is used to acquire information from surrounding vehicles, then the safety and interaction efficiency of autonomous driving is improved, but the device complexity and information processing burden increases
Solution Approach 1:
The patent segments the information processing by dividing surrounding vehicles into different groups (V2X-capable vehicles and non-V2X vehicles) and applying different processing strategies to each group. This segmentation reduces the overall complexity by handling each segment differently rather than processing all vehicles uniformly.
Solution Approach 2:
The patent introduces an intermediary processing layer that receives V2X communication data and sensor data, then generates standardized recognition information about surrounding vehicles. This intermediary layer abstracts the complexity of handling multiple data sources and communication protocols, making the system more manageable while improving safety.
2Reliability
If image processing is used to recognize surrounding vehicles, then the ability to detect V2X incapable vehicles is improved, but the measurement precision and processing time increases
Solution Approach 1:
The patent merges V2X communication data with image processing results to create comprehensive recognition information. By combining these two data sources, the system achieves reliable detection of all surrounding vehicles including non-V2X capable ones, while the fused information reduces processing time compared to using image processing alone.
Solution Approach 2:
The patent performs preliminary processing of V2X communication data to pre-identify surrounding vehicles before image processing is applied. This preliminary action reduces the burden on image processing by pre-filtering and pre-identifying targets, thereby reducing overall processing time while maintaining detection reliability.
3Loss of information
If the system processes information from both V2X communication and image processing, then the comprehensive recognition of surrounding vehicles is improved, but the quantity of information and computational load increases
Solution Approach 1:
The patent extracts only the essential recognition information from V2X communication data and image processing results, such as vehicle position, velocity, and identification. By extracting only the necessary information rather than processing all raw data, the system achieves comprehensive recognition while reducing the quantity of information that needs to be managed.
Solution Approach 2:
The patent transforms raw V2X communication data and image processing outputs into standardized recognition information with specific parameters (position, velocity, acceleration, identification). This parameter transformation consolidates diverse data sources into a unified format, reducing information quantity while maintaining comprehensive recognition capability.
Data Source
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AI summary
A method for planning an autonomous driving by using a V2X communication and an image processing under a road circumstance where both vehicles capable of the V2X communication and vehicles incapable of the V2X communication exist is provided. And the method includes steps of: (a) a computing device, corresponding to a subject autonomous vehicle, instructing a planning module to acquire recognition information on surrounding vehicles including (i) first vehicles capable of a V2X communication and (ii) second vehicles incapable of the V2X communication; (b) the computing device instructing the planning module to select an interfering vehicle among the surrounding vehicles; and (c) the computing device instructing the planning module to generate a potential interference prediction model, and to modify current optimized route information in order to evade a potential interfering action, to thereby generate updated optimized route information of the subject autonomous vehicle.