Autonomous Vehicle Remote Guidance Switching for Crowd Impasses
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Solution Overview
Problem
Autonomous vehicles face challenges in navigating through unpredictable situations that fall outside their programming or training, leading to impasses where they cannot continue forward progress, such as crowded environments with unpredictable pedestrian behavior.
Innovation Solution
The system allows the autonomous robotic system to detect trigger conditions, transmit a remote guidance request to a server, and receive instructions to adjust its buffer size and speed, enabling it to proceed cautiously and overcome impasses by temporarily invoking a non-standard operating mode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the autonomous vehicle maintains standard buffer sizes and speed limits for safety, then it protects other actors in the environment, but it cannot make progress through impasses such as crowded pedestrian environments
Solution Approach 1:
The system dynamically adjusts buffer sizes and speed parameters based on operational context. When a trigger condition is detected (indicating an impasse), the vehicle transitions from standard conservative parameters to modified parameters that enable progress. This dynamic parameter adjustment resolves the contradiction by allowing the vehicle to adapt its safety margins and speed according to the situation, rather than maintaining fixed conservative values that prevent progress in all scenarios.
Solution Approach 2:
The invention changes key operational parameters (buffer size, maximum speed) when specific trigger conditions are met. The system modifies these parameters temporarily to overcome impasses, then reverts to standard values when the situation is resolved. This parameter change approach enables the vehicle to break free from situations where standard parameters would cause indefinite stalling, while maintaining safety through controlled, temporary deviations.
2Productivity
If the autonomous vehicle operates in non-standard mode with reduced buffer sizes and speeds, then it can overcome impasses and make progress, but it deviates from standard safety parameters
Solution Approach 1:
The system implements dynamic switching between standard and non-standard operational modes based on detected trigger conditions. The vehicle operates in standard mode under normal conditions, adhering to established procedures. When impasses are detected, it dynamically transitions to non-standard mode with modified parameters, then returns to standard mode when progress is achieved. This dynamic mode switching resolves the contradiction by making non-standard operation conditional and temporary rather than permanent or arbitrary.
Solution Approach 2:
The system uses feedback from sensor data and operational status to determine when to switch between standard and nonstandard modes. Trigger conditions are detected based on feedback about the vehicle's ability to progress, and this feedback controls the activation and deactivation of nonstandard parameters. The feedback mechanism ensures that deviations from standard operation are data-driven and purposeful rather than random, resolving the contradiction by providing a rational basis for parameter deviations.
3Reliability
If the autonomous vehicle maintains conservative speed limits and buffer sizes, then it ensures safety in unpredictable situations, but it ceases forward progress when encountering edge cases
Solution Approach 1:
The system changes operational parameters (speed, buffer size) in response to detected trigger conditions that indicate impasses. When standard conservative parameters cause the vehicle to stall, the system temporarily modifies these parameters to enable progress. This parameter change strategy resolves the contradiction by allowing the vehicle to adapt its safety margins dynamically rather than maintaining fixed conservative values that become counterproductive when they prevent all forward motion.
Solution Approach 2:
The invention implements dynamic parameter adjustment where buffer sizes and speed limits are not fixed but adapt based on operational context. The system transitions between conservative and less conservative parameter sets depending on whether trigger conditions are present. This dynamic approach resolves the contradiction by making safety parameters flexible rather than rigid, allowing the vehicle to maintain safety through adaptive rather than static parameter selection.
Data Source
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AI summary
A method for switching between local and remote guidance instructions (312) for autonomous vehicles (102) includes, in response to monitoring one or more actions of objects (105) detected in a scene in which the autonomous robotic system (102) is moving, causing the autonomous robotic system (102) to slow or cease movement in the scene. The method includes detecting a trigger condition based on movement of the autonomous robotic system (102) in the scene. In response to detecting the trigger condition, the method includes transmitting a remote guidance request (310) to a remote server (120) and receiving remote guidance instructions (312) from the remote server (120) and causing the autonomous robotic system (102) to begin operating according to the remote guidance instructions (312).