Autonomous Vehicle Motion Planning via Decision Point Engine
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Solution Overview
Problem
Autonomous vehicles lack effective systems to dynamically manage speed and trajectory to preserve stopping opportunities and ensure safety, particularly in scenarios where object interaction probabilities are high, leading to potential collisions and reduced safety.
Innovation Solution
A decision point engine within a motion planning system that determines a stopping profile and decision point based on object interaction probabilities, generating a trajectory that incorporates speed zone constraints to maintain the ability to stop before interaction points, thereby optimizing vehicle motion and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous vehicle maintains high speed to improve productivity, then the travel time is reduced, but the ability to stop before interaction points is compromised, reducing safety
Solution Approach 1:
The system dynamically adjusts the vehicle's speed profile based on real-time interaction probabilities with detected objects. The motion planning system continuously modifies velocity commands to maintain a protective stopping buffer, allowing the vehicle to operate at high speeds when safe and reduce speed when objects are detected, thus resolving the contradiction between productivity and safety
Solution Approach 2:
The system performs preliminary calculations of stopping distances and protective buffers before reaching interaction points. By pre-computing the maximum safe speed that still allows stopping before potential hazards, the system ensures safety is maintained without unnecessarily reducing overall travel efficiency
2Reliability
If the autonomous vehicle reduces speed to improve safety by preserving stopping opportunities, then the ability to stop before interaction points is improved, but travel time increases, reducing productivity
Solution Approach 1:
The system changes the speed parameter dynamically based on detected objects and their interaction probabilities. Rather than maintaining a constantly reduced speed, the vehicle adjusts velocity in response to specific conditions, maintaining high speeds when safe and reducing only when necessary to preserve stopping buffers, thus minimizing impact on productivity while ensuring safety
3Reliability
If the motion planning system implements complex speed zone constraints to improve safety, then the ability to manage stopping opportunities is improved, but the computational complexity increases
Solution Approach 1:
The motion planning system segments the operational space into speed zones based on interaction probabilities with detected objects. By dividing the planning problem into discrete velocity ranges (e.g., high speed zones, reduced speed zones, stopping zones), the system manages complexity while maintaining comprehensive safety constraints through structured, modular decision-making
Data Source
AI summary
Generally, the present disclosure is directed to systems and methods that include or otherwise leverage a decision point engine as part of determining a motion plan for an autonomous vehicle. In particular, a motion planning system that includes a decision point engine can be configured to obtain object data associated with one or more objects identified near one or more travel paths of an autonomous vehicle. The system can determine a stopping profile based at least in part on the object data, wherein the stopping profile identifies a set of candidate states for the autonomous vehicle that preserves an ability of the autonomous vehicle to stop before the interaction point. The system can determine a decision point corresponding to a selected state from the set of candidate states identified by the stopping profile, and determine a trajectory for the autonomous vehicle based at least in part on the decision point.