Autonomous Vehicle Shoulder Stop Selection for Minimal Risk Maneuvers
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Solution Overview
Problem
Autonomous vehicles may encounter dangerous situations during abnormal conditions, and existing systems fail to effectively manage emergency stops on road shoulders, posing a risk to safety.
Innovation Solution
The vehicle is equipped with sensors and a processor to detect the environment, generate information, and perform minimal risk maneuvers by searching for and selecting a shoulder stop position, adjusting maneuvers based on available zones and vehicle state, ensuring safe emergency stops.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle performs autonomous driving without shoulder stop search capability, then the autonomous driving operation can proceed normally, but the vehicle cannot respond effectively to abnormal conditions requiring emergency stops on road shoulders
Solution Approach 1:
The system performs preliminary actions by pre-searching for and identifying potential shoulder stop positions (MRC zones) before an emergency situation occurs. The processor continuously monitors the surrounding environment and pre-identifies safe stopping zones on road shoulders, so that when an abnormal condition requires emergency stop, the vehicle can immediately execute the maneuver without delay.
Solution Approach 2:
The system segments the autonomous driving functionality by separating the shoulder stop search and selection capability as an independent module. The processor divides the surrounding environment into different regions of interest, specifically identifying shoulder areas as potential stopping zones, while maintaining the rest of the autonomous driving system unchanged.
2Measurement precision
If the vehicle searches for shoulder stop positions using only basic sensor detection, then the system complexity remains low, but the accuracy and reliability of identifying safe stopping zones is insufficient
Solution Approach 1:
The system merges multiple information sources including map data, real-time sensor detection results, and surrounding environment information into a unified analysis. The processor combines these diverse data types to accurately identify and evaluate potential shoulder stop positions, improving detection precision through multi-source information integration.
Solution Approach 2:
The system implements feedback mechanisms where the processor continuously monitors the identified MRC zones and adjusts the selection based on updated surrounding environment information. The system provides feedback loops that re-evaluate candidate zones and can switch between different MRC zones based on changing conditions, ensuring accurate and reliable stopping position identification.
3Adaptability or versatility
If the vehicle implements comprehensive shoulder stop search and selection functionality, then the safety and adaptability of emergency stops improve, but the system complexity and computational requirements increase
Solution Approach 1:
The system implements dynamic adaptability by enabling the vehicle to switch between different types of minimal risk maneuvers based on real-time conditions. The processor can dynamically adjust the emergency response strategy, switching between different MRC zones or changing maneuver types depending on the surrounding environment and vehicle state, providing high adaptability without requiring a completely separate system for each scenario.
Data Source
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AI summary
Disclosed is a vehicle, which may include: at least one sensor configured to detect a surrounding environment associated with the vehicle; a controller configured to control one or more operations of the vehicle; and a processor. The processor may be configured to: generate, based on the surrounding environment, surrounding environment information; monitor a state of the vehicle to generate vehicle state information; set, based on at least one of the surrounding environment information or the vehicle state information during an autonomous driving operation of the vehicle, a region of interest comprising a shoulder of a road; search, within the region of interest, for one or more candidate minimum risk condition (MRC) zones; determine whether a target MRC zone is selected among the one or more candidate MRC zones; and control, based on the determination of whether the target MRC zone is selected, the vehicle to perform a minimal risk maneuver.