Autonomous Control Arbitration for Vehicle Failure-Grade Safety
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Solution Overview
Problem
Existing vehicle automation systems fail to safely operate when one or more devices or processes associated with autonomous vehicles are in a non-nominal or diminished state, lacking effective methods to handle device failures.
Innovation Solution
A system comprising infrastructure sensing devices, autonomous health monitors, autonomous state machines, and autonomous control planning modules that calculate failure grades and operability levels to selectively enable safe control instructions for an autonomous agent.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles operate with multiple sensors and control systems, then the ability to perceive and comprehend the environment improves, but the system complexity increases
Solution Approach 1:
The patent segments the control system into multiple independent controllers (e.g., steering controller, braking controller, acceleration controller) that can operate autonomously. Each controller manages specific vehicle functions, allowing the system to maintain reliable operation even when individual controllers or sensors fail, thus resolving the contradiction between reliability and complexity.
Solution Approach 2:
The patent implements dynamic reconfiguration of controller operations based on system health status. When sensors or controllers fail, the system changes operational parameters by adjusting which controllers are active and how they prioritize tasks, enabling safe operation with reduced system capacity without requiring complete system redesign.
2Ease of operation
If the autonomous agent assumes all devices are in nominal state, then the control logic simplifies, but the system fails when devices degrade or malfunction
Solution Approach 1:
The patent implements preliminary health monitoring and failure detection mechanisms that continuously assess the status of sensors and controllers. By detecting failures early and switching to degraded operational modes in advance, the system maintains reliability without requiring complex real-time decision-making during critical failure scenarios.
Solution Approach 2:
The autonomous vehicle system performs self-diagnosis and self-reconfiguration when failures are detected. The controllers automatically adjust their operations and prioritize critical functions based on system health status, enabling the system to maintain safe operation without external intervention while keeping control logic relatively simple.
3Adaptability or versatility
If multiple distinct autonomous controllers generate control instructions, then the system can handle diverse operational scenarios, but the complexity of managing and arbitrating control instructions increases
Solution Approach 1:
The patent introduces an intermediary arbitration layer that manages control instructions from multiple independent controllers. This intermediary system prioritizes and coordinates instructions from different controllers (steering, braking, acceleration) based on system state and failure conditions, enabling versatile operation across diverse scenarios while keeping the arbitration logic manageable through standardized protocols.
Data Source
AI summary
A system and method includes an autonomous agent having a communication interface that enables the autonomous agent to communicate with a plurality of infrastructure sensing devices; a plurality of distinct health monitors that monitor distinct operational aspects of the autonomous agent; an autonomous state machine that computes a plurality of allowed operating states of the autonomous agent based on inputs from the plurality of distinct health monitors; a plurality of distinct autonomous controllers that generate a plurality of distinct autonomous control instructions; and an arbiter of autonomous control instructions that: collects, as a first input, the plurality of autonomous control instructions generated by each of the plurality of distinct autonomous controllers; collects, as a second input, data relating to the plurality of allowed operating state of the autonomous agent; and selectively enables only a subset of the autonomous control instructions to pass to driving components of the autonomous agent.


