Predicted Road Profile Sensing for Proactive Suspension Control
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Solution Overview
Problem
Current active and adaptive suspension systems for vehicles lack the ability to effectively predict and respond to road profiles ahead, which can impact ride quality and passenger comfort.
Innovation Solution
A system comprising image capture devices and processing units that acquire and analyze images to compute a road profile along predicted paths of a vehicle, allowing for proactive suspension adjustments and improved navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If reactive suspension systems are used, then the system structure remains simple, but the ride quality and passenger comfort deteriorate due to inability to predict road profiles ahead
Solution Approach 1:
The system performs preliminary action by capturing images of the road ahead and computing road profiles before the vehicle reaches them. The image capture device continuously acquires images of the area in front of the vehicle, and the processing device computes road profiles along predicted paths, enabling the suspension system to prepare for upcoming road conditions rather than merely reacting to them.
Solution Approach 2:
The patent replaces traditional mechanical road sensing methods with an optical-based system. Instead of using mechanical sensors to detect road surfaces, the system uses image capture devices (cameras) to acquire visual data of the road ahead, which is then processed computationally to determine road profiles. This substitution of mechanical detection with optical sensing and computational analysis enables predictive capabilities.
2Ease of operation
If image capture devices and processing units are added to compute road profiles, then proactive suspension adjustments are enabled, but the device complexity increases
Solution Approach 1:
The image capture device and processing system serve multiple functions: capturing road images, computing road profiles along predicted paths, determining vehicle position and orientation, and providing data to the suspension control system. This multi-functionality reduces the need for separate dedicated components for each function, thereby managing system complexity while enabling comprehensive predictive suspension control.
Solution Approach 2:
The system uses the vehicle's own image capture devices and processing units to generate the road profile data needed for suspension control. Rather than relying on external sensors or pre-existing maps, the system independently captures and processes visual data to create real-time road profiles, making the system self-sufficient and reducing dependency on additional external components.
3Reliability
If road profile computation along predicted paths is implemented, then ride quality improves through proactive adjustments, but the processing requirements and energy consumption increase
Solution Approach 1:
The system computes road profiles along predicted paths rather than analyzing the entire visible road area in detail. By focusing computational resources on the specific paths where the vehicle is predicted to travel, the system achieves sufficient accuracy for suspension control while reducing overall processing requirements and energy consumption compared to a complete road analysis approach.
Data Source
AI summary
Systems and methods are provided for navigating a host vehicle. A navigation system for the host vehicle may include at least one processor programmed to receive an image representative of an environment of a host vehicle; analyze the image to determine a predicted path of the host vehicle; determine, based on the image, an indicator of comfort associated with the predicted path; identify, based on the indicator of comfort, an alternative path of the host vehicle; and output a control signal configured to modify an operation of a component of the host vehicle to follow the alternative path of the host vehicle.