Autonomous Navigation Liability Rules for Safer Driving Decisions
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Solution Overview
Problem
Current autonomous vehicle navigation systems lack a scalable and interpretable mathematical model for safety assurance, making it challenging to ensure safety and widespread adoption of autonomous vehicles.
Innovation Solution
The system uses cameras to monitor the environment and processes images to determine navigational actions, incorporating GPS data, sensor data, and accident liability rules to ensure safe navigation while avoiding potential liability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicle navigation systems incorporate comprehensive safety assurance models and liability rule testing, then safety and reliability are improved, but device complexity increases
Solution Approach 1:
The navigation system is divided into distinct functional modules: image capture device for environmental sensing, processing device for analyzing images and testing navigational actions against liability rules, and control mechanisms for executing approved actions. This segmentation allows each component to be optimized independently while maintaining overall system reliability without excessive complexity
Solution Approach 2:
The system performs preliminary testing of planned navigational actions against accident liability rules before execution. By evaluating potential actions in advance and filtering out those that may create liability, the system ensures safety and reliability are maintained while the complexity is confined to the planning stage rather than affecting the entire operational system
2Reliability
If the system tests multiple potential navigational actions against accident liability rules, then safety assurance is improved, but loss of time increases
Solution Approach 1:
The system generates a plurality of potential navigational actions and tests them against liability rules, but does not require exhaustive testing of every possible action. By evaluating a sufficient subset of reasonable alternatives and selecting the first action that satisfies safety requirements, the system achieves adequate safety assurance without excessive time loss
Solution Approach 2:
The system implements a feedback loop where navigational actions are tested against liability rules, and results are used to refine and adjust the selection of actions. This iterative process allows the system to learn from previous evaluations and improve decision efficiency over time, reducing the time required for safety assessments while maintaining reliability
Data Source
AI summary
Systems and methods are provided for navigating a host vehicle. In some embodiments, the system may include at least one processing device programmed to: receive, from an image capture device, at least one image representative of an environment of the host vehicle; determine, based on at least one driving policy, a planned navigational action for accomplishing a navigational goal of the host vehicle; analyze the at least one image to identify a target vehicle in the environment of the host vehicle; test the planned navigational action against at least one accident liability rule for determining potential accident liability for the host vehicle relative to the identified target vehicle; if the test of the planned navigational action against the at least one accident liability rule indicates that potential accident liability exists for the host vehicle if the planned navigational action is taken, then cause the host vehicle not to implement the planned navigational action; and if the test of the planned navigational action against the at least one accident liability rule indicates that no accident liability would result for the host vehicle if the planned navigational action is taken, then cause the host vehicle to implement the planned navigational action.