Autonomous Vehicle Scenario Control for Merge and Obstruction Handling
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Solution Overview
Problem
Current autonomous vehicle systems face challenges in effectively managing operational scenarios, particularly in navigating complex environments with multiple external objects and dynamic conditions, as they lack robust and adaptive control mechanisms to ensure safe and efficient traversal of vehicle transportation networks.
Innovation Solution
The implementation of an autonomous vehicle operational management system that includes scenario-specific operational control evaluation modules, such as POMDP models, to detect and respond to various operational scenarios by generating candidate vehicle control actions, enabling the vehicle to navigate safely and efficiently through diverse conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicle systems use basic navigation approaches, then device complexity is reduced, but reliability and safety deteriorate in complex environments with multiple external objects
Solution Approach 1:
The autonomous vehicle control system is segmented into multiple scenario-specific operational control evaluation modules, each dedicated to handling distinct operational scenarios (e.g., pedestrian scenarios, intersection scenarios, lane change scenarios). This segmentation allows the system to maintain high reliability for each specific scenario while managing overall complexity through modular organization.
Solution Approach 2:
The system dynamically instantiates and de-instantiates scenario-specific operational control evaluation modules based on detected operational scenarios. This dynamic adaptation allows the system to activate only the necessary control modules for current conditions, improving safety responsiveness while managing computational complexity through on-demand resource allocation.
2Adaptability or versatility
If the system implements comprehensive scenario-specific control evaluation, then adaptability to diverse conditions improves, but device complexity increases
Solution Approach 1:
The autonomous vehicle operational management controller serves as a universal platform that can instantiate multiple scenario-specific operational control evaluation modules. This multi-functional architecture allows a single controller to adapt to diverse operational scenarios by dynamically loading and executing appropriate scenario modules, thereby achieving high adaptability without proportionally increasing overall system complexity.
Solution Approach 2:
Scenario-specific operational control evaluation modules are nested within the autonomous vehicle operational management controller. This nested structure allows the system to contain specialized scenario handlers within a general-purpose controller framework, enabling adaptability to multiple scenarios while maintaining a unified and manageable system architecture.
3Productivity
If real-time scenario detection and response is implemented, then productivity and traversal efficiency improve, but measurement and detection difficulty increases
Solution Approach 1:
The system performs preliminary action by pre-defining multiple scenario-specific operational control evaluation modules that correspond to anticipated operational scenarios. When a scenario is detected, the appropriate pre-configured module is instantly instantiated and executed, enabling real-time response without the computational overhead of creating new control logic during operation, thus maintaining high traversal efficiency.
Solution Approach 2:
The autonomous vehicle operational management controller continuously monitors operational environment data and provides feedback by detecting operational scenarios and dynamically instantiating appropriate scenario-specific modules. This feedback mechanism enables real-time adaptation to changing conditions, improving traversal efficiency through responsive scenario-based control while managing detection complexity through automated scenario recognition and module selection.
Data Source
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AI summary
Traversing, by an autonomous vehicle, a vehicle transportation network, may include operating a scenario-specific operational control evaluation module instance, wherein the scenario-specific operational control evaluation module instance includes an instance of a scenario-specific operational control evaluation model of a vehicle operational scenario wherein the vehicle operational scenario is a merge vehicle operational scenario or a pass-obstruction vehicle operational scenario, receiving a candidate vehicle control action from the scenario-specific operational control evaluation module instance, and traversing a portion of the vehicle transportation network in accordance with the candidate vehicle control action.