Autonomous Vehicle Control Process Selection for Road Conditions
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Solution Overview
Problem
Autonomous vehicles face challenges in adapting their operations to function-related features of their environment, such as varying road types and conditions, which can affect their performance and safety, as existing systems lack the ability to dynamically adjust motion planning, trajectory tracking, and actuator control processes based on real-time environmental data.
Innovation Solution
The implementation of a system that uses function-related information stored in a database to select and modify software processes for motion planning, trajectory tracking, and actuator control, allowing autonomous vehicles to adjust their operations by associating specific processes with different types of road features and conditions, using parameter settings and prior information to optimize performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If autonomous vehicles use fixed software processes for motion planning, trajectory tracking, and actuator control, then system complexity is reduced, but adaptability to different road types and environmental conditions deteriorates
Solution Approach 1:
The patent implements dynamic selection of software processes based on environmental conditions. The system continuously monitors road type, weather, and geographic location, then dynamically selects appropriate motion planning, trajectory tracking, and actuator control processes from a library of specialized processes. This allows the vehicle to adapt its control strategy in real-time without requiring a completely reconfigurable system architecture.
Solution Approach 2:
The patent changes parameters of existing software processes based on environmental conditions. Different parameter sets are associated with different road types and conditions, allowing the same base process to be optimized for specific environments through parameter adjustment rather than requiring entirely different process implementations.
2Adaptability or versatility
If autonomous vehicles dynamically adjust software processes based on environmental data, then adaptability to different road types and conditions is improved, but system complexity increases
Solution Approach 1:
The patent pre-configures multiple specialized software processes and parameter sets before operation. Each process is pre-optimized for specific road types, weather conditions, or geographic regions. During operation, the system simply selects from these pre-prepared options based on current environmental sensors data, avoiding the complexity of real-time process generation or synthesis.
Solution Approach 2:
The patent introduces an intermediary layer (environmental condition monitoring and process selection system) that sits between the sensors and the control processes. This intermediary translates environmental conditions into appropriate process selections, simplifying the overall system architecture by centralizing the adaptation logic in a dedicated selection mechanism rather than distributing complexity across all control modules.
3Reliability
If autonomous vehicles use specialized processes for different road features, then navigation performance is improved, but information processing time increases
Solution Approach 1:
The patent pre-associates parameter sets and process configurations with specific road features and environmental conditions during system setup. This preliminary organization allows for rapid lookup and selection during operation, minimizing information processing time while maintaining specialized optimization for each condition.
Solution Approach 2:
The patent implements dynamic caching of environmental conditions and corresponding optimal process selections. Once a particular road type or condition is detected, the system caches the selected process configuration, allowing for rapid switching between similar conditions without re-evaluating all parameters, thus reducing processing time for sequential similar scenarios.
Data Source
AI summary
Among other things, information is received that identifies or defines a function-related feature of an environment of a vehicle. Function-related information is generated that corresponds to the function-related feature.