Self-Driving Vehicle Mode Switching for Adaptive Sensor Range
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Solution Overview
Problem
Self-driving vehicles face challenges in navigating environments with obstacles and changing navigation modes based on trigger conditions, such as transitioning between following guiding infrastructure and electronic maps, while ensuring collision avoidance and efficient operation.
Innovation Solution
The system and method involve a vehicle processor that monitors for trigger conditions, adjusts vehicle attributes, and switches between navigation modes (fixed path and free form) by controlling sensors and drive systems, using detection sensors to manage detection ranges and speed, and updating electronic maps with sensor data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the vehicle operates in free form mode with wide detection range, then collision avoidance capability is improved, but energy consumption increases and speed is reduced
Solution Approach 1:
The system dynamically adjusts the detection range of sensors based on the current navigation mode. In fixed path mode, the detection range is reduced to conserve energy, while in free form mode, the detection range is expanded to improve collision avoidance. This dynamic adaptation resolves the contradiction by making the detection range variable rather than static.
Solution Approach 2:
The system changes the operational parameters of detection sensors based on navigation mode. By adjusting parameters such as detection range and sensor activation levels, the system optimizes the balance between collision avoidance capability and energy consumption for each specific navigation scenario.
2Adaptability or versatility
If the vehicle operates in free form mode, then navigation flexibility is improved, but detection range must be increased which reduces speed
Solution Approach 1:
The system implements dynamic adjustment of detection range based on navigation mode. In fixed path mode, the detection range is minimized to maintain high speed, while in free form mode, the detection range is expanded to enable navigation flexibility. This resolves the contradiction by adapting detection range to the specific navigation requirements.
Solution Approach 2:
The system applies different detection range qualities to different navigation modes. Rather than using a uniform detection range, the system tailors the detection characteristics to the specific needs of each navigation mode, providing local optimization for both speed and flexibility.
3Productivity
If the vehicle reduces detection range to increase speed, then productivity is improved, but collision avoidance capability deteriorates
Solution Approach 1:
The system dynamically adjusts detection range based on navigation mode requirements. In fixed path mode where the path is predetermined, the detection range is reduced to increase speed and productivity. In free form mode, the detection range is expanded to maintain collision avoidance capability. This dynamic adaptation resolves the contradiction.
Solution Approach 2:
The system changes detection parameters adaptively based on the navigation mode. By modifying detection range and sensor activation levels according to whether the vehicle is in fixed path or free form mode, the system optimizes the trade-off between productivity and safety for each operational context.
4Adaptability or versatility
If the vehicle continuously monitors for trigger conditions and adjusts navigation mode, then adaptability is improved, but device complexity increases
Solution Approach 1:
The system performs preliminary classification of trigger conditions into categories (fixed path triggers vs. free form triggers). By pre-defining trigger types and their corresponding navigation modes, the system reduces the complexity of real-time decision-making while maintaining high adaptability to environmental changes.
Solution Approach 2:
The system segments trigger conditions into distinct categories with predetermined responses. By dividing the complex monitoring task into discrete trigger types (e.g., detecting guiding infrastructure, receiving fleet management commands, detecting proximity indicators), the system manages complexity through structured classification while maintaining adaptability.
Data Source
AI summary
The various embodiments described herein generally relate to systems and methods for operating one or more self-driving vehicles. In some embodiments, the self-driving vehicles may include a vehicle processor being operable to: control the vehicle to navigate an operating environment in an initial vehicle navigation mode; monitor for one or more trigger conditions indicating a possible change for the vehicle navigation mode; detect a trigger condition; determine a prospective vehicle navigation mode associated with the detected trigger condition; determine whether to change from the initial vehicle navigation mode to the prospective vehicle navigation mode; and in response to determining to change from the initial vehicle navigation mode to the prospective vehicle navigation mode, adjust one or more vehicle attributes corresponding to the prospective vehicle navigation mode, otherwise continue to operate the vehicle in the initial vehicle navigation mode.