Automated Vehicle Sensor Selection via Map Data Density
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Solution Overview
Problem
Automated vehicles face uncertainty in determining location on digital maps due to misalignment between different sensor technologies and GPS, leading to potential navigation errors.
Innovation Solution
A navigation system that uses a combination of first and second sensors with different technologies to determine relative positions of navigation features, with a digital map containing data-groups characterized by each sensor's capabilities, allowing a controller to select the most reliable location based on data-density or feature-density for navigation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple sensor technologies are used to determine vehicle location, then measurement precision improves, but reliability deteriorates due to misalignment between different sensors and GPS
Solution Approach 1:
The system dynamically selects which sensor technology to use for navigation based on real-time environmental conditions and map data density. The controller switches between first sensor technology (e.g., lidar), second sensor technology (e.g., camera), and GPS depending on which provides the most reliable data in the current context, making the sensor selection adaptive rather than static
Solution Approach 2:
The system changes the operational parameters by selecting different sensor technologies based on detected feature density and map data density. When navigation features are densely populated, the system may prefer one sensor type; when sparse, it switches to another sensor type or combines with GPS, effectively changing the measurement parameters based on environmental conditions
2Measurement precision
If sensor selection is based on data-density and feature-density, then navigation accuracy improves, but device complexity increases
Solution Approach 1:
The system performs preliminary analysis by comparing map data density and detected feature density before selecting which sensor to use. This advance evaluation allows the controller to proactively choose the optimal sensor based on predicted environmental conditions, rather than reactively adjusting after navigation errors occur
Solution Approach 2:
The navigation system serves itself by automatically selecting the appropriate sensor technology based on its own detection of environmental features and comparison with map data. The system autonomously evaluates which sensor will provide the best performance and configures itself without external intervention
Data Source
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AI summary
A navigation system (10) suitable for use by an automated vehicle includes a first sensor (22), a second sensor (36), a digital-map (44), and a controller (46). The digital- map (44) includes a first data-group (48) of navigation-features (42) preferentially detected by the first sensor-technology (34), and a second data-group (50) of navigation- features (42) preferentially detected by the second sensor- technology (40). The controller (46) determines, on the digital-map (44), first and second locations of the host-vehicle (12) using the first and second sensors (20), respectively. The controller (46) selects one of the first and second locations to navigate the host-vehicle (12) based on a comparison of the first data-density (64) and the second data-density (66). Alternatively, the controller (46) determines a first feature-density (92) and a second feature-density (94) of navigation-features (42) detected by the first and second sensors (20) respectively, and selects one of the first location (52) and the second location (54) to navigate the host- vehicle (12) based on a comparison of the first feature-density (92) and the second feature-density (94).