Autonomous Vehicle Trajectory Prediction for Collision Avoidance
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Solution Overview
Problem
Real-time prediction of actions by drivers and pedestrians is challenging for semi-autonomous or autonomous vehicles, especially when they break traffic rules, leading to hesitant or unsafe vehicle behavior due to systematic worst-case assumptions or optimistic predictions.
Innovation Solution
The system generates a vehicle trajectory, detects objects within a given distance, and calculates possible object trajectories to determine collision risk, modifying the vehicle's trajectory to avoid collisions by performing emergency maneuvers if necessary, allowing for worst-case predictions while ensuring safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If systematic worst-case assumptions are used to predict object trajectories, then safety is improved, but vehicle behavior becomes overly hesitant and less efficient
Solution Approach 1:
The system dynamically adjusts the prediction approach by generating multiple object trajectories with varying degrees of conservatism (from optimistic to pessimistic). Instead of always using worst-case assumptions, the system adapts the level of conservatism based on real-time conditions, allowing the vehicle to behave efficiently when safe while maintaining safety when necessary.
Solution Approach 2:
The system changes the parameters of trajectory predictions by generating multiple possible trajectories with different speed and direction assumptions. By evaluating multiple parameter sets (optimistic, neutral, pessimistic scenarios) and selecting appropriate trajectories based on current conditions, the system avoids the limitations of fixed worst-case assumptions.
2Measurement precision
If multiple possible object trajectories are generated and evaluated, then collision detection accuracy is improved, but computational complexity increases
Solution Approach 1:
The system segments the trajectory prediction into multiple discrete scenarios (optimistic, neutral, pessimistic) rather than attempting to evaluate all possible continuous trajectories. This segmentation allows the system to achieve high detection accuracy by covering key scenario types while keeping computational complexity manageable through a finite set of evaluated possibilities.
3Reliability
If real-time trajectory prediction and modification is performed, then collision avoidance capability is improved, but response time may be insufficient for emergency situations
Solution Approach 1:
The system performs preliminary actions by continuously generating and evaluating multiple possible object trajectories in advance, before a collision actually occurs. By pre-computing potential collision scenarios and having modification strategies ready, the system reduces the critical response time needed during actual emergency situations.
Solution Approach 2:
When a potential collision is detected, the system rushes through the trajectory modification process by selecting from pre-evaluated possibilities and executing the safest option immediately. The system skips lengthy analysis in critical moments by relying on pre-computed trajectory evaluations, enabling rapid response while maintaining safety.
Data Source
AI summary
Systems and methods for operating a vehicle. The methods comprise: generating, by a computing device, a vehicle trajectory for the vehicle that is in motion; detecting an object within a given distance from the vehicle; generating, by the computing device, at least one possible object trajectory for the object which was detected; using, by the computing device, the vehicle trajectory and the at least one possible object trajectory to determine whether there is an undesirable level of risk that a collision will occur between the vehicle and the object; modifying, by the computing device, the vehicle trajectory when a determination is made that there is an undesirable level of risk that the collision will occur; and automatically causing the vehicle to move according to the modified vehicle trajectory.