Vehicle Trajectory Validation for Low-Latency Collision Avoidance
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Solution Overview
Problem
Existing vehicle safety systems face challenges in generating real-time, safe vehicle trajectories that effectively navigate dynamic environments while optimizing computational resources and reducing latency and redundancy in collision avoidance processes.
Innovation Solution
A vehicle safety system comprising a trajectory management component, perception component, filter component, and collision detection component, which work asynchronously to validate and filter trajectories, prioritize resource allocation, and reduce latency by storing data in queues, thereby optimizing computational efficiency and enhancing collision avoidance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the vehicle system processes all sensor data from multiple sources in real-time to ensure comprehensive collision detection, then the collision detection accuracy is improved, but the computational latency increases
Solution Approach 1:
The sensor data processing is divided into multiple priority levels. Critical sensor data related to potential collisions is processed immediately with high priority, while non-critical sensor data is processed with lower priority. This segmentation allows the system to maintain high collision detection accuracy by prioritizing relevant data without being blocked by less important processing tasks.
Solution Approach 2:
A priority-based scheduler acts as an intermediary between sensor data input and trajectory processing. The scheduler receives sensor data, assigns priority levels based on collision risk, and queues data for processing in priority order. This intermediary mechanism ensures that critical collision-related data is processed first, reducing latency for safety-critical operations while still processing all sensor data comprehensively.
2Reliability
If the system validates multiple trajectories using perception and collision detection components, then the safety reliability is improved, but the computational resource consumption increases
Solution Approach 1:
The system performs partial validation of trajectories by focusing computational resources on the most promising candidate trajectories first. Rather than exhaustively validating all possible trajectories with equal depth, the system validates the top candidate trajectories more thoroughly while performing lighter validation on lower-priority candidates. This approach maintains high safety reliability for critical trajectory decisions while reducing overall computational resource consumption.
Solution Approach 2:
Different validation depths are applied to different trajectories based on their priority and collision risk. High-priority trajectories that pose greater safety risks undergo more rigorous perception and collision detection validation, while lower-priority trajectories receive streamlined validation. This local differentiation of validation quality ensures safety reliability for critical paths without uniformly consuming excessive computational resources across all trajectories.
3Measurement precision
If the trajectory management component waits for all other components to complete data processing before selecting a trajectory, then the trajectory selection accuracy is improved, but the real-time responsiveness deteriorates
Solution Approach 1:
The perception and collision detection components perform preliminary processing and validation of trajectory data in advance, preparing validated trajectory information before it is needed for final selection. By pre-validating trajectory candidates and maintaining ready-to-use validated data in queues, the trajectory management component can make accurate selection decisions without waiting for complete processing cycles, thus improving real-time responsiveness while maintaining accuracy.
Solution Approach 2:
The system dynamically adjusts the waiting behavior of the trajectory management component based on processing status and time constraints. When validated data is available from other components, the trajectory management component can proceed with accurate selection. When time is critical and validated data is not yet available, the system can proceed with available data at reduced waiting time. This dynamic adjustment balances trajectory selection accuracy with real-time responsiveness based on actual system conditions.
Data Source
AI summary
Techniques for validating or determining trajectories for a vehicle are discussed herein. A trajectory management component can receive status and/or error data from other safety system components and select or otherwise determine safe and valid vehicle trajectories. A perception component of a safety system can validate a trajectory upon which the trajectory management component can wait for selecting a vehicle trajectory, validate trajectories stored in a queue, and/or utilize kinematics for validation of trajectories. A filter component of the safety system can filter out objects based on trajectories stored in a queue. A collision detection component of the safety system can determine the collision states based on trajectories stored in a queue or determine a collision state upon which the trajectory management component can wait for selecting or otherwise determining a vehicle trajectory.