Driver Assistance Positioning Using Static Features for Lane Accuracy
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing driver assistance systems face challenges in accurately determining the lane position of a vehicle due to the uncertainty in geolocation measurements from satellite systems, which can be as large as 5-10 meters, making it difficult to perform precise driving maneuvers and maintain situational awareness.
Innovation Solution
A driver assistance system that utilizes multiple static features, such as road markings and signs, combined with camera systems and inertial measurement units, to refine geolocation accuracy by fusing GPS data with visual measurements and Kalman filtering to calculate a fine geolocation position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If satellite geolocation measurements are used for vehicle positioning, then the system can provide basic location information, but the measurement precision is insufficient (uncertainty of 5-10 meters) to determine lane position accurately
Solution Approach 1:
The patent combines multiple positioning approaches by merging satellite geolocation measurements with visual measurements from camera systems. The system integrates GPS data with images of static features (road markings, signs) to compensate for the insufficient precision of satellite alone, achieving accurate lane-level positioning without requiring complex alternative systems
Solution Approach 2:
The patent introduces static features (road markings, signs) as intermediary objects that bridge the gap between coarse satellite positioning and fine lane-level positioning. These features serve as reference points that can be measured with high precision by camera systems, translating coarse GPS coordinates into accurate lane positions through the intermediary feature measurements
2Measurement precision
If multiple sensors and processing methods are integrated to improve positioning accuracy, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent makes the camera system multi-functional by using it for both primary driving assistance tasks and secondary positioning refinement. The same camera that captures road scenes for safety monitoring also captures static features for geolocation refinement, eliminating the need for separate positioning hardware and reducing overall system complexity
Solution Approach 2:
The system uses its own existing resources (camera system, processor) to improve its positioning accuracy rather than relying on external specialized equipment. The driver assistance system refines its own geolocation data using measurements taken during normal operation, making the system self-sufficient and avoiding additional complexity
Data Source
Figure 1
Figure 2
Figure 3
AI summary
A driver assistance system for an ego vehicle, and a method for a driver assistance system is provided. The system is configured to refine a coarse geolocation method based on the detection of the static features located in the vicinity of the ego vehicle. The system performs at least one measurement of the visual appearance of each of at least one static feature located in the vicinity of the ego vehicle. Using the at least one measurement, a position of the ego vehicle relative to the static feature is calculated. The real world position of the static feature is identified. The position of the ego vehicle relative to the static feature is calculated, which is, in turn, used to calculate a static feature measurement of the vehicle location. The coarse geolocation measurement and the the static feature measurement are combined to form a fine geolocation position. By combining the measurements, a more accurate location of the ego vehicle can be determined.