Vehicle Trajectory Search for Degraded Visual Navigation
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Solution Overview
Problem
Existing systems and methods for operating vehicles, particularly in autonomous modes, face difficulties in navigating through degraded visual environments due to lacking or unreliable sensor data, which impairs obstacle identification and vehicle orientation, affecting both autonomous and manual operators.
Innovation Solution
A method and system that identify a degraded visual environment and determine adaptive trajectories for vehicles to search for improved navigation environments, involving first and second segments of trajectories based on the vehicle's phase of operation, using sensor data and decision prompts to adjust navigation strategies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle operates in a degraded visual environment using traditional navigation methods, then the vehicle can maintain its route, but the navigation reliability deteriorates due to impaired obstacle identification and vehicle orientation
Solution Approach 1:
The patent replaces visual-based mechanical navigation with sensor-based detection systems. Sensors detect environmental conditions and provide data to the controller, which then determines alternative trajectories. This substitution of visual mechanics with sensor-electronic-mechanical systems enables reliable navigation in degraded visual environments by eliminating dependence on human visual capabilities.
Solution Approach 2:
The controller acts as an intermediary between the degraded visual environment and the vehicle navigation system. It receives sensor data about the degraded environment, processes this information, and generates alternative trajectories that bypass the problematic visual conditions. This intermediary processing layer translates environmental challenges into actionable navigation solutions.
2Reliability
If the vehicle searches for improved navigation environments by deviating from the predetermined route, then navigation reliability improves, but the loss of time increases due to trajectory adjustments
Solution Approach 1:
The navigation system dynamically adjusts trajectories based on real-time sensor feedback about visual environment quality. The controller evaluates whether to maintain the predetermined route or deviate to alternative trajectories depending on current conditions. This dynamic adaptation allows the system to minimize time loss by only deviating when necessary, while maintaining reliability by continuously monitoring and adjusting to environmental conditions.
Solution Approach 2:
The system uses sensor feedback about visual environment conditions to determine when and where to adjust trajectories. The controller continuously monitors environmental quality and uses this feedback to make informed decisions about route deviations. This feedback mechanism ensures that time loss is minimized by only implementing trajectory adjustments when the degraded visual environment actually impacts navigation reliability.
3Measurement precision
If the system uses multiple sensors to detect degraded visual environments, then the measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent combines multiple sensor types (cameras, LIDAR, radar, infrared sensors) into an integrated sensor system that operates under unified control. The controller receives and processes data from all sensors simultaneously, merging their capabilities to detect degraded visual environments with high precision. This merging approach manages complexity by providing a single point of control while leveraging the complementary strengths of multiple sensor technologies.
Solution Approach 2:
The sensor system is designed with multi-functionality to detect various types of degraded visual environments (fog, rain, snow, dust, smoke) using the same hardware platform. The controller universally processes sensor data regardless of the specific environmental condition, making the system adaptable to different degradation types without requiring separate specialized systems for each condition.
Data Source
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AI summary
In an example, a method for controlling a vehicle in a degraded visual environment is provided. The method includes identifying a degraded visual environment corresponding to a phase of a route followed by the vehicle. The method includes determining, based on the phase of the route, a first segment of a trajectory of the vehicle along which to search for a location with an improved navigation environment. The method includes causing the vehicle to follow the first segment until: (i) identifying the improved navigation environment, or (ii) reaching an end of the first segment without identifying the improved navigation environment. The method includes determining a second segment of the trajectory based on whether the improved navigation environment has been identified. The method includes causing the vehicle to follow the second segment.