Autonomous Vehicle Safe Stop Motion Planning by Severity Level
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Solution Overview
Problem
Existing autonomous vehicle systems face challenges in effectively modifying planned paths in response to changing vehicle and environmental states, particularly in ensuring safe and efficient vehicle stoppage.
Innovation Solution
A computer-implemented method for autonomous vehicle operation that involves receiving state data, determining vehicle stoppage conditions, selecting a severity level for the conditions from a plurality of levels, and generating a motion plan that complies with the constraints associated with the selected severity level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle rapidly changes its path in response to environmental changes, then operational safety is improved, but the complexity of the motion planning system increases
Solution Approach 1:
The motion planning system is segmented into multiple severity levels (e.g., Level 1 for minor obstacles, Level 2 for moderate risks, Level 3 for critical threats). Each severity level has pre-defined response protocols and path modification rules, breaking down the complex decision-making process into manageable segments that can be executed rapidly without overwhelming the system.
Solution Approach 2:
The system dynamically changes planning parameters such as deceleration rates, path deviation angles, and stopping distances based on the detected severity level. For example, at Level 3 severity, the system automatically switches to emergency braking parameters with maximum deceleration, while at Level 1, it uses gentle path adjustments. This parameter-based approach simplifies real-time decision-making while maintaining high safety standards.
2Manufacturing precision
If the autonomous vehicle generates optimized motion plans considering multiple severity levels and constraints, then stopping precision is improved, but the computation time increases
Solution Approach 1:
The system pre-calculates and stores optimal motion plans for various severity levels and constraint combinations before real-time operation. When an obstacle is detected, the system simply retrieves and executes the pre-computed plan corresponding to the detected severity level, rather than calculating a new plan from scratch. This dramatically reduces computation time while maintaining high stopping precision.
Solution Approach 2:
The motion planning system applies different levels of computational precision to different aspects of the stopping maneuver based on severity. For critical Level 3 situations, the system uses full precision calculations for safety-critical parameters like braking force and steering angle. For less critical parameters in lower severity situations, it uses simplified calculations, optimizing the balance between precision and computation time.
Data Source
AI summary
Systems, methods, tangible non-transitory computer-readable media, and devices for operating an autonomous vehicle are provided. For example, the disclosed technology can include receiving state data that includes information associated with states of an autonomous vehicle and an environment external to the autonomous vehicle. Responsive to the state data satisfying vehicle stoppage criteria, vehicle stoppage conditions can be determined to have occurred. A severity level of the vehicle stoppage conditions can be selected from a plurality of available severity levels respectively associated with a plurality of different sets of constraints. A motion plan can be generated based on the state data. The motion plan can include information associated with locations for the autonomous vehicle to traverse at time intervals corresponding to the locations. Further, the locations can include a current location of the autonomous vehicle and a destination location at which the autonomous vehicle stops traveling.