Location-Based Map Rules for Real-Time Automated Vehicle Actions
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Solution Overview
Problem
Current digital maps lack the ability to dynamically adjust vehicle behavior based on real-time environmental conditions and traffic rules, limiting the efficiency and safety of automated vehicle navigation.
Innovation Solution
Incorporating high-definition digital maps that associate rules with specific segments of the road, using sensors to determine dynamic states, and utilizing these states to evaluate rules and adjust vehicle actions, such as stopping or yielding, for automated control systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If digital maps store only basic mapping information, then the map data structure remains simple, but the system cannot dynamically adjust vehicle behavior based on real-time environmental conditions and traffic rules
Solution Approach 1:
The patent transforms static digital maps into dynamic systems by introducing real-time state determination through sensors. The map system continuously updates its representation of environmental conditions, traffic rules, and vehicle states, enabling dynamic adjustment of vehicle behavior while maintaining adaptability to changing conditions.
Solution Approach 2:
The system implements feedback loops where sensors continuously monitor environmental conditions and feed this information back to the map system. This feedback mechanism enables the system to evaluate current states against stored rules and dynamically adjust vehicle behavior, resolving the contradiction between information completeness and adaptability.
2Reliability
If digital maps include detailed rules and real-time state information, then vehicle navigation safety and efficiency improve, but the system complexity increases
Solution Approach 1:
The patent segments the complex navigation system into distinct functional modules: map data storage, sensor input processing, state determination, rule evaluation, and action generation. This segmentation allows each component to handle specific tasks independently, improving reliability through modular design while managing overall system complexity through clear separation of concerns.
Solution Approach 2:
The system employs a universal rule evaluation framework that can process multiple types of traffic rules and environmental conditions through a single integrated architecture. This multi-functional approach enhances navigation safety by comprehensively evaluating various scenarios while avoiding the need for separate specialized systems for each rule type.
3Measurement precision
If the map system processes multiple observables and rules simultaneously, then decision-making accuracy improves, but the processing time and computational load increase
Solution Approach 1:
The patent pre-processes and stores traffic rules and map segments in an optimized format before they are needed for decision-making. By preparing rule structures and spatial indices in advance, the system reduces computational load during real-time evaluation, maintaining high decision-making accuracy while minimizing processing time delays.
Solution Approach 2:
The system applies local quality optimization by focusing computational resources on evaluating rules and observables relevant to the vehicle's current location and immediate surroundings. Rather than processing all possible rules uniformly, the system prioritizes locally applicable rules, improving decision-making accuracy for critical situations while reducing overall processing time.
Data Source
AI summary
A method includes obtaining a rule that is associated with a segment of a map, determining a state for use in evaluation of the rule, evaluating the rule using the state, identifying an action to be performed based on a result of evaluating the rule using the state, and utilizing the action to be performed as an input to an automated control system of a vehicle.