Vehicle Intersection Attribute Detection Using Lane Graph Analysis
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Solution Overview
Problem
Existing vehicle control systems struggle to accurately determine intersection attributes, leading to increased accident risks during autonomous driving.
Innovation Solution
A vehicle control device and method that utilize lane attributes, map information, and vehicle sensors to accurately identify intersection types, including three-way, four-way, five-way intersections, roundabouts, overpasses, and underpasses, by analyzing lane segments and their directional graphs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If vehicle control systems use basic intersection detection methods, then the system complexity is low, but the measurement precision of intersection attributes is insufficient leading to increased accident risks
Solution Approach 1:
The patent segments the intersection detection process into multiple distinct steps: detecting the vehicle's current lane, determining the type of intersection based on lane configuration, identifying the specific traffic lane within the intersection, and finally determining the precise intersection attribute. This segmentation allows each step to be handled with appropriate complexity, improving overall measurement precision without requiring the entire system to be overly complex.
Solution Approach 2:
The patent performs preliminary actions by first detecting the current lane and determining the intersection type before proceeding to identify the specific traffic lane and intersection attribute. This preliminary classification enables the system to prepare appropriate detection strategies in advance, improving measurement precision while managing system complexity through structured preprocessing.
2Reliability
If the system comprehensively analyzes lane attributes and map information to determine intersection attributes, then the reliability of vehicle control decisions is improved, but the loss of time for processing increases
Solution Approach 1:
The system performs preliminary detection of lane attributes and classification of intersection types before making final control decisions. By preparing this information in advance through structured analysis of map data and sensor inputs, the system ensures reliable decision-making while reducing the time required for final processing through pre-organized data structures.
Solution Approach 2:
The system uses the vehicle's own sensor data and onboard map information to determine intersection attributes, rather than relying on external real-time services. This self-service approach improves reliability by using trusted onboard data while minimizing time loss by avoiding external communication delays.
3Measurement precision
If the system uses detailed lane attribute analysis including vector calculations and cross products, then the measurement precision of path direction is improved, but the device complexity increases
Solution Approach 1:
The patent segments the directional analysis into distinct mathematical operations: calculating vectors from lane geometry, computing cross products to determine turn direction, and comparing angles to threshold values. This segmentation allows each calculation to be optimized independently, improving measurement precision while managing device complexity through modular computation.
Solution Approach 2:
The system changes parameters by using vector mathematics and cross product calculations to transform geometric lane data into directional information. By changing from raw coordinate data to vector representations and then to directional classifications, the system achieves high measurement precision while the computational complexity remains manageable through parameter transformation.
Data Source
AI summary
A vehicle control device may include memory that stores map information, a sensor that determines at least a location or a heading of a vehicle, and a processor. The processor may determine, based on at least one of the location of the vehicle or the heading of the vehicle, an intersection on a path of the vehicle, determine, based on the map information, a region of interest that comprises the intersection, determine, based on at least one of a traffic lane in the region of interest or a lane attribute of the traffic lane, an intersection attribute of the intersection, and control, based on the intersection attribute, an operation of the vehicle.