Driving Assistance Control for Map Feature Error Suspension Timing
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Solution Overview
Problem
Existing driving assistance systems face challenges in determining appropriate timing for suspending autonomous driving due to feature errors in maps, leading to potential safety issues and discomfort for passengers, especially during turns where map accuracy is low.
Innovation Solution
A driving assistance device and method that set a determination point on the travel track considering vehicle motion allowable amounts and feature errors, using external sensors to measure target feature positions and estimate the vehicle's self-position, allowing for controlled transitions from automatic driving to manual driving.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If autonomous driving continues based on scheduled travel route and self-position estimation, then productivity is improved, but reliability deteriorates due to map feature errors causing inappropriate timing for suspension of autonomous driving
Solution Approach 1:
The system performs preliminary actions by setting a determination point before the vehicle reaches the actual feature position on the map. At this determination point, the system checks whether the map feature position and actual feature position coincide within a predetermined distance. This advance check allows the system to prepare for potential suspension of autonomous driving before it becomes necessary, ensuring safety while maintaining productivity by avoiding unnecessary suspensions.
Solution Approach 2:
The determination point acts as an intermediary between the scheduled travel route and the actual feature position. Instead of directly comparing the vehicle's current position with the map feature position, the system introduces a determination point as an intermediate reference. This intermediary allows for a buffer zone that accounts for map errors, enabling the system to maintain autonomous driving when appropriate and suspend it only when truly necessary, thus resolving the contradiction between productivity and reliability.
2Device complexity
If map feature position is used for determining autonomous driving allowability, then device complexity is reduced, but measurement precision deteriorates due to map errors
Solution Approach 1:
The system applies local quality by making the evaluation criterion location-dependent. Instead of using a uniform accuracy threshold throughout the travel route, the system sets a determination point at a specific location where the map feature position and actual feature position are compared. This localized approach allows the system to maintain simple device architecture while improving measurement precision at the critical decision point, as the comparison is made at a predetermined distance buffer that accounts for local map errors.
3Reliability
If determination point is set considering feature error, then reliability is improved, but device complexity increases due to additional calculation requirements
Solution Approach 1:
The system applies parameter changes by transforming the determination criterion from a fixed distance threshold to a dynamic determination point that incorporates feature error. Instead of using a constant distance value for comparing map and actual positions, the system calculates a determination point that adjusts for the predetermined distance buffer based on feature error characteristics. This parameter change improves reliability by accurately accounting for map errors while managing device complexity through a systematic calculation approach that can be pre-computed and stored.
Data Source
AI summary
Provided are a driving assistance device and a driving assistance method that are capable of determining, at an appropriate timing, suspension of driving assistance and automatic driving due to a feature error of a map. The driving assistance device includes: a determination point setting unit that sets a determination point in which an assumed self-position of own vehicle that is assumed on a map, a position of a measurement target feature on the map, and an error predicted as a difference between the position on the map and an actual position of the measurement target feature are associated with each other, the measurement target feature being measurable from the assumed self-position; a target feature measurement unit that obtains a measurement position of the measurement target feature based on external information acquired by an external sensor mounted on the own vehicle; a self-position estimation unit that estimates a self-position of the own vehicle on the map based on the external information; and a driving assistance state setting unit that sets a control mode of a driving assistance system of the own vehicle based on the determination point, the measurement position of the measurement target feature measured by the target feature measurement unit, and the self-position of the own vehicle estimated by the self-position estimation unit.