Route Prioritization Control for Low-Certainty Autonomous Maps
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Solution Overview
Problem
Existing autonomous driving systems face challenges in accurately calculating routes due to insufficient map information, leading to potential inaccuracies in navigation and route planning.
Innovation Solution
An assistance control system that utilizes an electronic control unit to generate and update map information based on sensor inputs, evaluates the accuracy of route candidates, and prioritizes routes with lower map information accuracy to increase data collection, thereby enhancing map information accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a route candidate with high map information accuracy is selected, then navigation reliability is improved, but map information accuracy improvement is limited
Solution Approach 1:
The patent inverts the conventional route selection logic by prioritizing routes with lower map information accuracy instead of higher accuracy. The electronic control unit calculates map information evaluation values for multiple route candidates and selects the route with the lowest evaluation value, thereby transforming the selection criterion from 'highest accuracy' to 'lowest accuracy' to achieve the dual objective of maintaining navigation reliability while improving map information coverage.
Solution Approach 2:
The system implements a feedback mechanism where the electronic control unit continuously updates map information based on sensor data collected during vehicle traversal. After the vehicle completes a route, the system calculates new map information evaluation values and adjusts future route selections accordingly, creating a closed-loop system that progressively improves map information accuracy while maintaining reliable navigation.
2Loss of information
If multiple route candidates are evaluated and prioritized based on map information evaluation values, then map information accuracy is improved, but calculation complexity increases
Solution Approach 1:
The electronic control unit performs self-service by automatically calculating map information evaluation values for multiple route candidates, comparing them, and selecting the optimal route without requiring external intervention. The system uses its own sensor data and existing map information to autonomously evaluate and prioritize routes, reducing the need for complex external processing while improving map information accuracy.
Solution Approach 2:
The system changes the evaluation parameter from traditional route selection criteria (such as distance or time) to map information evaluation values that reflect data completeness and accuracy. By calculating and comparing these specialized parameters across multiple route candidates, the system achieves improved map information coverage while managing calculation complexity through focused parameter optimization.
Data Source
AI summary
An assistance control system performs assistance control for causing a moving object to move to a destination based on map information. The assistance control system includes an electronic control unit. The electronic control unit is configured to generate or update the map information based on input from a sensor mounted on the moving object, acquire a plurality of route candidates to the destination, evaluate certainty of the map information for each location or each section, and calculate a map information evaluation value, evaluate accuracy of the assistance control in the acquired route candidates based on the calculated map information evaluation value, and present a route candidate having the highest priority among the route candidates to an occupant of the moving object, or control the moving object along the route candidate having the highest priority.