Trajectory Constraints for Autonomous Collision Avoidance in Adjacent Lanes
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Solution Overview
Problem
Conventional vehicle traffic management using V2X communication struggles to provide autonomous driving strategies that account for trajectory constraints, especially in complex urban environments, and fails to effectively manage collisions involving various traffic participants like bicycles and pedestrians.
Innovation Solution
An infrastructure cooperative autonomous driving system generates trajectory constraints for collision avoidance by comparing target vehicle trajectories with predicted object trajectories, calculating a time to collision and collision point, and defining safety points to avoid lane obstructions, using a processor-based system that incorporates edge infrastructure and V2X communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicle stops for collision avoidance based on conventional V2X communication, then collision avoidance is achieved, but traffic flow in adjacent lanes is obstructed
Solution Approach 1:
The patent introduces a temporal dimension by calculating time-to-collision (TTC) and defining trajectory constraints in the time-space domain rather than just spatial domain. This allows the system to predict future collision points and generate avoidance strategies that consider both position and time, enabling smoother deceleration profiles that maintain traffic flow while ensuring collision avoidance.
Solution Approach 2:
The system performs preliminary calculation of collision points and trajectory constraints before actual collision occurs. By using V2X communication to share trajectory information with adjacent lanes in advance, the system enables proactive traffic management where vehicles in adjacent lanes can be notified and adjust their trajectories beforehand, preventing traffic obstruction while maintaining safety.
2Adaptability or versatility
If conventional V2X communication is used for traffic management, then nearby vehicle communication is achieved, but various traffic participants like bicycles and pedestrians are not covered
Solution Approach 1:
The patent extends V2X communication functionality to be universal across all traffic participants including vehicles, bicycles, and pedestrians. The system defines a unified trajectory constraint model that can accommodate different types of traffic participants by predicting their future trajectories and calculating collision risks using the same mathematical framework, thereby achieving multi-functionality without losing information about diverse participant types.
3Reliability
If simple collision-based braking is used, then collision avoidance is achieved, but smooth vehicle traffic management in complex urban environment is difficult
Solution Approach 1:
The patent dynamically adjusts braking strategies based on real-time trajectory predictions and TTC calculations. Instead of fixed collision-based braking, the system continuously updates trajectory constraints using V2X communication data and adjusts deceleration profiles dynamically. This allows smooth traffic management in complex urban environments by adapting to changing conditions while maintaining collision avoidance reliability.
Data Source
AI summary
According to the present invention, autonomous driving may be performed according to an autonomous driving strategy defined in trajectory constraints generated based on object recognition information about a road map and various traffic participants, and thus, because collision avoidance does not obstruct traffic of an adjacent lane despite a situation where an autonomous vehicle stops for avoiding a collision, the stability of autonomous driving may increase and vehicle traffic management may be easily performed.