Autonomous Vehicle Operational Risk Monitor
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Solution Overview
Problem
Conventional autonomous vehicle control systems fail to consider changes in operational risk for previous planned paths, leading to potential hazards and violations of functional safety compliance due to underestimation of operational risks.
Innovation Solution
An operational risk monitor module assesses operational risk by using information about detected objects and their predicted behaviors, comparing current risks to previous estimations, and transmitting signals to control system modules to perform remedial actions when risks exceed thresholds, employing systematic, heuristic, or sensitivity monitoring techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional autonomous vehicle control systems rely on continuously collected sensor information to generate current understanding of the environment, then the system can make real-time control decisions, but the system fails to consider changes in operational risk for previous planned paths leading to underestimation of operational risks
Solution Approach 1:
The operational risk monitor module performs preliminary risk assessment for planned paths before the autonomous vehicle executes them. By evaluating operational risk in advance for previous planned paths and comparing it with current risk estimations, the system identifies potential hazards before they materialize, preventing underestimation of operational risks while maintaining manageable system complexity through targeted preliminary analysis.
2Measurement precision
If the operational risk monitor module compares current risks to previous estimations and transmits signals for remedial actions, then the detection of hazardous events is enhanced, but the system complexity increases due to additional monitoring and comparison mechanisms
Solution Approach 1:
The operational risk monitor module implements a feedback mechanism that continuously compares current operational risk estimations with previous risk assessments for the same planned paths. When discrepancies indicating potential hazards are detected, the system transmits signals to control system modules to perform remedial actions. This feedback loop enhances detection precision by identifying risk changes over time while managing complexity through structured comparison protocols.
3Reliability
If the system performs remedial actions to prevent autonomous vehicle from encountering events, then safety compliance is improved, but the control signal generation frequency increases
Solution Approach 1:
The operational risk monitor module performs preliminary risk assessment and identifies potential hazards before the autonomous vehicle encounters them. By comparing operational risk estimations in advance and generating remedial control signals proactively, the system prevents hazardous events rather than reacting to them. This preliminary anti-action approach improves safety compliance while reducing control signal frequency by avoiding unnecessary reactive corrections.
Data Source
AI summary
Changes in the controlling of an autonomous vehicle are caused based on an operational risk determined for the autonomous vehicle. An operational risk monitor module of the autonomous vehicle uses information about objects detected within an environment in which the autonomous vehicle is located and predicted behaviors of those objects to assess the operational risk of the autonomous vehicle along a planned path. The operational risk is used to determine whether to cause a change in the controlling of the autonomous vehicle, for example, based on a comparison between the operational risk and a previously estimated operational risk or based on a determination that the operational risk exceeds a threshold. The operational risk monitor module transmits a signal to one or more control system modules of the autonomous vehicle to indicate to change the controlling of the autonomous vehicle based on the operational risk.