Minimum Risk Maneuver Control for Highway Lane-Change Stopping
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Advanced driver assistance systems (ADAS) face challenges in managing unexpected events during automated driving, particularly in minimizing collision risks and safely changing lanes to avoid hazards on highways.
Innovation Solution
A vehicle system that includes sensors, processors, and controllers to monitor the vehicle's state and environment, determine a minimum risk maneuver type, and execute strategies such as straight-ahead stopping, one-lane change stopping, or shoulder stopping to mitigate collision risks, using artificial intelligence for decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the vehicle performs automated driving on a highway, then driving convenience is improved, but collision risk increases when unexpected events occur
Solution Approach 1:
The system performs preliminary detection of neighboring vehicles and pre-calculates multiple lane change strategies before an emergency occurs. When a minimum risk maneuver is triggered, the vehicle can immediately execute a pre-planned safe lane change without delay, resolving the contradiction by preparing safety measures in advance while maintaining automated driving convenience.
Solution Approach 2:
The system dynamically selects from multiple lane change strategies (one-lane change, two-lane change, shoulder stopping) based on real-time detection of neighboring vehicles and road conditions. This dynamic adaptation allows the vehicle to maintain automated driving convenience while adjusting safety responses to specific situations, reducing collision risk without sacrificing operational ease.
2Reliability
If the vehicle changes lanes to avoid hazards, then collision risk is reduced, but system complexity increases due to multiple decision factors
Solution Approach 1:
The complex decision-making process is segmented into distinct modules: detection unit for identifying neighboring vehicles, determination unit for selecting lane change strategies, and execution unit for performing the maneuver. Each module handles a specific aspect of the decision process, reducing overall system complexity while maintaining comprehensive collision risk reduction capabilities.
Solution Approach 2:
The system uses quantifiable parameters such as longitudinal distances to neighboring vehicles and lane change feasibility flags to make deterministic decisions. By converting complex safety assessments into parameter comparisons against predefined thresholds, the system reduces decision complexity while ensuring reliable collision avoidance through objective criteria.
3Reliability
If the vehicle performs straight-ahead stopping, then collision risk is reduced, but loss of time increases due to stopping on the current lane
Solution Approach 1:
The system dynamically determines whether to perform straight-ahead stopping or lane change stopping based on real-time detection of neighboring vehicles in the current lane and adjacent lanes. When the current lane is clear, the vehicle stops in place minimizing time loss; when other lanes are available and safer, the vehicle changes lanes before stopping, resolving the contradiction by adapting the stopping strategy to current traffic conditions.
Data Source
AI summary
An embodiment method for operating a vehicle includes monitoring a state of the vehicle, determining a type of a minimum risk maneuver based on the state of the vehicle, wherein the type of the minimum risk maneuver comprises a straight-ahead stopping type in which the vehicle stops after driving straight ahead only and a lane change stopping type in which the vehicle stops after changing a lane, and executing the determined type of the minimum risk maneuver.