Autonomous Vehicle Sensor Verification Using Correlated Map Instances
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Solution Overview
Problem
Autonomous vehicles face safety risks due to inaccurate sensor information caused by malicious sensor feeds, which can lead to unsafe maneuvers such as sudden stopping or changes in direction, as attackers can broadcast interfering signals that manipulate sensor data, confusing the vehicle's decision-making process.
Innovation Solution
The autonomous vehicle sensor security system generates and exchanges map instances of environmental information securely between vehicles and roadside equipment units, using Transport Layer Security (TLS) for authentication, and activates a secure sensor only when discrepancies are detected to verify the accuracy of the environment, minimizing exposure to interfering signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If the autonomous vehicle uses sensor information from the surrounding environment to navigate autonomously, then the vehicle can perform maneuvers and navigate without human input, but the vehicle becomes vulnerable to malicious sensor feeds that can cause unsafe maneuvers
Solution Approach 1:
The patent introduces map instances as an intermediary layer between raw sensor feeds and the autonomous vehicle's decision-making system. These map instances are generated by multiple vehicles and roadside equipment, then correlated to verify environmental accuracy. This intermediary structure filters out malicious sensor feeds while preserving legitimate navigation data, allowing autonomous operation without direct vulnerability to spoofed sensor information.
2Reliability
If the autonomous vehicle activates a secure sensor to verify discrepancies in environmental information, then the vehicle can detect and correct malicious sensor feeds, but the vehicle increases exposure to interfering signals and consumes additional energy
Solution Approach 1:
The patent implements periodic verification where secure sensors are activated only when map instance correlations detect discrepancies. Instead of continuous operation, the secure sensor performs intermittent validation checks triggered by anomaly detection. This periodic activation reduces energy consumption while maintaining reliability by verifying environmental information only when potential threats are identified through map instance comparison.
3Reliability
If the autonomous vehicle correlates map instances from multiple sources to verify environmental accuracy, then the vehicle can identify malicious sensor feeds, but the vehicle increases processing complexity and communication overhead
Solution Approach 1:
The patent segments the verification process into modular components: map instance generation by individual vehicles and roadside equipment, secure exchange through communication systems, correlation processing by the autonomous vehicle controller, and discrepancy identification. This segmentation distributes computational complexity across multiple independent modules rather than requiring a monolithic complex system, making the authentication process more manageable and scalable.
Data Source
AI summary
Example methods and systems are disclosed to provide autonomous vehicle sensor security. An example method may include generating, by a first autonomous vehicle, a first map instance of a physical environment using first environmental information generated by a first sensor of a first autonomous vehicle. A second map instance from at least one of a second autonomous vehicle located in the physical environment is received. The first map instance may be correlated with the second map instance. In response to a discrepancy between the first map instance and the second map instance, a secure sensor may be activated to generate a third map instance. In response to the third map instance verifying that the discrepancy accurately describes the physical environment, the first environmental information including the discrepancy is used to navigate the first autonomous vehicle.