Ego Vehicle Motion Control With Nominal and Evasive Controllers
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Solution Overview
Problem
Existing automated vehicle control systems struggle to maintain safety and comfort in unexpected environmental events, often resulting in conservative actions or excessive computational time, and fail to timely react to scenarios that disrupt planned motion.
Innovation Solution
A control system comprising a nominal controller for normal vehicle motion and an evasive controller for emergency maneuvers, using distinct control theories and a feedback mechanism to determine a safe region for the vehicle state, allowing swift execution of evasive maneuvers when necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the ADS determines actions that satisfy safety, traffic rules, and comfort constraints even for unexpected events, then safety and comfort are maintained, but the control actions become overly conservative and computing time increases significantly
Solution Approach 1:
The control system is segmented into two distinct controllers: a nominal controller for normal operation that ensures comfort and traffic rule compliance, and an evasive controller for unexpected events that prioritizes safety. This segmentation allows each controller to be optimized for its specific function without the computational burden of satisfying all constraints simultaneously, resolving the contradiction between safety and maneuvering capability.
Solution Approach 2:
The system dynamically switches between nominal and evasive control modes based on the detection of unexpected events. The nominal controller operates under full constraint satisfaction for comfort and efficiency, while the evasive controller dynamically relaxes non-critical constraints (such as comfort and traffic rules) to enable rapid safety-critical maneuvers, thus maintaining maneuvering capability while ensuring safety.
2Reliability
If the ADS computes conservative actions to account for all possible unexpected events, then safety is maintained, but the vehicle loses maneuvering space and reaction time
Solution Approach 1:
The system performs preliminary classification of unexpected events into critical and non-critical categories. By pre-identifying which constraints are essential for safety versus those that can be relaxed, the system avoids the computational overhead of re-evaluating all constraints during emergency situations, thereby reducing reaction time while maintaining safety through pre-determined constraint prioritization.
Solution Approach 2:
The system changes the active constraint parameters dynamically based on the event type. For critical safety events, only safety-related parameters remain active while comfort and traffic rule parameters are temporarily deactivated. This parameter switching allows the vehicle to respond rapidly to unexpected events without the computational burden of maintaining all constraints, thus reducing loss of time while preserving safety.
3Reliability
If the ADS satisfies all constraints including comfort and traffic rules during unexpected events, then passenger comfort is maintained, but the vehicle cannot execute necessary evasive maneuvers
Solution Approach 1:
The system applies preliminary anti-action by pre-identifying and prioritizing safety constraints over comfort constraints before unexpected events occur. When an event is detected, the system has already determined which constraints must be maintained (safety) and which can be violated (comfort), allowing immediate execution of necessary evasive maneuvers without the computational delay of real-time constraint negotiation, thus ensuring safety while accepting temporary comfort degradation.
4Device complexity
If the ADS uses a single unified controller for all driving conditions, then the system structure is simple, but the computing time for handling unexpected events becomes excessive
Solution Approach 1:
The unified controller is segmented into two specialized sub-controllers: nominal and evasive. This segmentation allows each sub-controller to have a reduced constraint set and optimized computation path. The nominal controller handles normal operation with full constraints, while the evasive controller handles emergencies with relaxed constraints, significantly reducing computation time for unexpected events while maintaining manageable system complexity through modular architecture.
Data Source
AI summary
The present disclosure discloses a system and a method for controlling motion of an ego vehicle. The method includes collecting a feedback signal indicative of a current state of the ego vehicle and an environment, processing the feedback signal to determine a region of the state of the ego vehicle uplifted with admissible values of a control parameter, processing the feedback signal with a nominal controller to produce a nominal control command maintaining the state of the ego vehicle within the determined region, and evaluating a state function of an evasive controller with a value of the control parameter from the determined region to produce an evasive control command. The method further includes controlling the motion of the ego vehicle according to the nominal control command when the fault is not detected; and otherwise controlling the motion of the ego vehicle according to the evasive control command.