Autonomous Vehicle Stuck Detection and Trajectory Assistance
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Solution Overview
Problem
Autonomous vehicles face challenges in efficiently detecting when they are stuck and requesting assistance, leading to potential over-allocation of resources or delayed assistance due to excessive false positives or negatives in determining stuck conditions.
Innovation Solution
An autonomous vehicle system that includes a stuck condition detection component and a communications component, which detects impediments to navigation and sends assistance signals with low-level sensor data and high-level object representations to an assistance center, receiving a revised trajectory that ignores obstructing objects, allowing the vehicle to navigate around obstacles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle sends assistance signals frequently to ensure accurate stuck condition detection, then the reliability of navigation assistance improves, but the loss of time and communication resources increases due to excessive signals
Solution Approach 1:
The system performs preliminary analysis of sensor data locally before sending assistance signals. The autonomous vehicle evaluates whether conditions truly indicate a stuck state using pre-defined criteria, filtering out false positives before communication occurs. This preliminary action ensures that only genuine stuck conditions trigger assistance signals, improving reliability while reducing unnecessary communication overhead and time loss.
2Loss of energy
If the autonomous vehicle waits longer before sending assistance signals to reduce false positives, then the loss of communication resources decreases, but the productivity is reduced due to delayed assistance when actually stuck
Solution Approach 1:
The system dynamically adjusts the waiting period before sending assistance signals based on the confidence level of stuck condition detection. When sensor data strongly indicates a stuck condition (high confidence), the system sends signals immediately without extended waiting. When confidence is lower, the system waits longer to confirm the condition. This dynamic approach optimizes both communication resource usage and assistance speed, preventing both false positives and delayed help.
3Measurement precision
If the autonomous vehicle includes detailed sensor information in assistance signals to improve trajectory calculation accuracy, then the measurement precision of obstacle detection improves, but the device complexity and data transmission requirements increase
Solution Approach 1:
The system extracts only the most relevant and critical sensor data for inclusion in assistance signals. Rather than transmitting all raw sensor information, the system identifies and extracts key features such as obstacle positions, trajectories, and critical sensor readings that are essential for trajectory calculation. This extraction approach maintains measurement precision for obstacle detection while significantly reducing data transmission requirements and processing complexity at both the vehicle and assistance center.
Data Source
AI summary
An autonomous vehicle may determine to seek assistance navigating using a first trajectory. The autonomous vehicle may be configured to receive and store data about a plurality of obstacles. A particular obstacle in the plurality of obstacles may partially or wholly obstruct the first trajectory. The autonomous vehicle may select a portion of the stored data that includes data representing the particular obstacle. The selected portion of the stored data may be provided to an assistance center. A second trajectory may be received from the assistance center, where the second trajectory is not obstructed by the particular obstacle.