Autonomous Vehicle Maneuver Selection for Highway Merge Safe Stops
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Autonomous vehicles face challenges in minimizing collision risks during unexpected events on highways, as existing systems lack effective methods to rapidly assess and respond to critical situations by selecting optimal safety zones for maneuvers.
Innovation Solution
The vehicle is equipped with sensors and a processor that detect abnormalities, select from various minimal risk maneuver types, and perform maneuvers such as stopping in safety zones, including completely or partially on shoulders, road merge points, and highway entrance merge points, based on environmental and vehicle state data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle performs autonomous driving on a highway, then driving convenience is improved, but collision risk increases when unexpected events occur
Solution Approach 1:
The system performs preliminary actions by pre-identifying multiple potential safety zones (shoulders, merge points, entrance points) along the highway route before critical events occur. When an abnormality is detected, the system can immediately execute a maneuver to the pre-identified safety zone without delay, thus resolving the contradiction between autonomous driving convenience and collision risk mitigation.
2Reliability
If the vehicle selects from multiple minimal risk maneuver types, then maneuver effectiveness is improved, but system complexity increases
Solution Approach 1:
The system dynamically selects from multiple minimal risk maneuver types (stopping in safety zone, emergency stopping, in-lane stopping) based on real-time assessment of vehicle state and environmental conditions. This dynamic adaptation allows the system to maintain high maneuver effectiveness while managing complexity through context-dependent selection rather than fixed complex protocols.
Solution Approach 2:
The system employs feedback mechanisms by continuously monitoring vehicle state abnormalities and environmental conditions, then selecting appropriate maneuver types based on this feedback. The multi-type maneuver system uses feedback from sensor data to determine the most effective maneuver, resolving the contradiction between maneuver effectiveness and system complexity through intelligent decision-making rather than brute-force complexity.
3Reliability
If the vehicle stops in a safety zone, then collision risk is minimized, but driving time increases
Solution Approach 1:
The system performs preliminary identification of multiple safety zones (shoulders, merge points, entrance points) along the highway before critical events occur. By pre-mapping these zones, the system can quickly select and execute the nearest or most appropriate safety zone when an abnormality is detected, minimizing the time lost while still achieving collision risk minimization.
Data Source
AI summary
An embodiment method of operating a vehicle includes generating a minimal risk maneuver request of the vehicle in response to a determination that there is an abnormality in a state of the vehicle, in response to the minimal risk maneuver request being generated, selecting a minimal risk maneuver type from among a plurality of minimal risk maneuver types based on the state of the vehicle, and performing a minimal risk maneuver based on the selected minimal risk maneuver type.