Lane-Specific Navigation Routing for Automated Driving
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Solution Overview
Problem
Existing navigation systems for automated driving operations struggle to seamlessly integrate lane-specific information from high-definition and standard-definition street maps, leading to inefficiencies and potential safety hazards due to unsuitable lane navigation.
Innovation Solution
A method that determines a lane-specific navigation route by mapping geographical coordinates from an attribute-based street map to a sensor-based street map, identifying relevant driving sections, and optimizing lane selection using cost or bonus functions to ensure safe and efficient automated driving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a general navigation route is determined without lane-specific information, then the route determination process is simpler, but the automated driving operation may encounter unsuitable lanes leading to safety hazards and interruptions
Solution Approach 1:
The patent segments the navigation route into lane-specific driving sections by transferring the route from the attribute-based street map to the sensor-based street map, which is divided into individual lanes. This segmentation allows the system to evaluate and select appropriate lanes for automated driving, thereby improving safety without overwhelming complexity through structured analysis.
Solution Approach 2:
The patent applies local quality by evaluating different lanes along the route based on their specific characteristics. The sensor-based street map provides lane-specific information that allows the system to identify suitable lanes for automated driving at different locations, ensuring that the vehicle operates only in appropriate lanes while maintaining overall route efficiency.
2Measurement precision
If lane-specific information from sensor-based street map is integrated with attribute-based street map, then the navigation route becomes more precise and suitable for automated driving, but the data processing and mapping complexity increases
Solution Approach 1:
The patent uses the sensor-based street map as an intermediary layer between the attribute-based street map and the automated driving system. The route is first determined in the attribute-based map, then transferred to the sensor-based map for lane-specific analysis, and finally the optimal lanes are identified. This intermediary approach enables precise lane-level navigation while managing integration complexity through a structured two-map system.
3Ease of operation
If the system determines optimal lanes by evaluating all possible lanes, then the lane selection is more accurate, but the computation time and processing effort increase
Solution Approach 1:
The patent applies partial action by evaluating only the necessary lane characteristics required for automated driving suitability rather than analyzing all possible lane attributes. The system identifies key criteria for lane suitability and focuses computational resources on these essential factors, achieving accurate lane selection while reducing unnecessary processing time and effort.
Data Source
AI summary
A navigation route for the automated driving operation is determined in a lane-specific manner. A node list is produced based on a digital attribute-based street map, the node list representing the geographical coordinates of a route determined by a navigation system. The node list is transferred into a digital sensor-based street map containing a surroundings description detected by sensors. Lane-specific driving section candidates being determined in the digital sensor-based street map using the node list. Irrelevant driving section candidates are identified and eliminated. The route is segmented into subgraphs with only one possible lane and subgraphs with multiple possible lanes. Optimal lanes are identified and combined to form the lane-specific navigation route.