Vehicle Steering Limiters for Lateral Acceleration and Jerk Control
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Solution Overview
Problem
Autonomous vehicle systems face challenges in ensuring safety and scalability, particularly in navigating complex environments while adhering to safety constraints and liability rules, and in reducing jerk during steering operations.
Innovation Solution
The system employs cameras to analyze environmental images, combining this data with GPS and sensor information to determine navigational actions, including steering limits, and implements these actions through actuators, ensuring safe and scalable navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the autonomous vehicle system implements strict safety constraints and liability rules for navigation decisions, then safety assurance is improved, but the complexity of the navigation system increases
Solution Approach 1:
The navigation system is divided into separate functional modules: an image capture device for environmental sensing, a processor for analyzing images and determining navigational actions, and actuators for executing steering commands. This segmentation allows each module to be independently optimized and tested, improving safety assurance while managing system complexity through modular architecture.
Solution Approach 2:
The processor acts as an intermediary between the image capture device and the actuators, translating environmental perceptions into safe navigational decisions. This intermediary layer implements safety constraints and liability rules by evaluating multiple possible actions against predefined safety criteria before executing steering commands, thereby ensuring safety assurance while maintaining manageable system complexity.
2Adaptability or versatility
If the system uses multiple sensors and complex image analysis to navigate complex environments, then navigation capability is improved, but device complexity increases
Solution Approach 1:
The image capture device serves multiple functions: capturing environmental images for navigation decisions, identifying characteristics of the environment, and providing input for determining navigational actions. This multi-functionality improves navigation capability in complex environments while avoiding the need for separate specialized sensors for each function, thereby managing system complexity.
Solution Approach 2:
The system combines image capture, image analysis, and navigational decision-making into an integrated processing pipeline. The processor simultaneously performs multiple tasks including analyzing images to identify environmental characteristics, determining navigational actions based on safety constraints, and controlling actuators. This merging of functions improves navigation capability while reducing overall system complexity compared to having separate independent systems for each function.
3Ease of operation
If the vehicle implements smooth steering operations with limited jerk, then passenger comfort is improved, but the responsiveness to environmental changes may be reduced
Solution Approach 1:
The steering limiter dynamically adjusts the maximum allowable steering rate based on current vehicle conditions and environmental context. When rapid environmental changes are detected, the system can temporarily increase steering responsiveness while still maintaining jerk limits for passenger comfort. This dynamic adjustment allows the system to balance passenger comfort with responsive navigation in complex environments.
Solution Approach 2:
The system continuously monitors environmental conditions through image capture and analysis, providing feedback to the processor which adjusts steering commands in real-time. This feedback loop allows the system to respond to environmental changes while maintaining smooth steering operations by modulating the steering rate based on the urgency of the situation and current vehicle state, thereby balancing comfort and responsiveness.
Data Source
AI summary
Systems and methods are provided for navigating a host vehicle. In one implementation, a system may include at least one processor configured to receive at least one image acquired by an image capture device, the at least one image being representative of an environment of the host vehicle; analyze the at least one image to identify at least one characteristic associated with the environment of the host vehicle; determine a navigational action for the host vehicle based on: the at least one characteristic associated with the environment of the host vehicle, and a steering limit corresponding to a maximum allowable lateral acceleration for the host vehicle; and cause one or more actuators associated with the host vehicle to implement the determined navigational action.