Landmark-Relative Obstacle Localization for Vehicle Roadway Regions
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Solution Overview
Problem
Existing methods for locating obstructing objects in vehicle roadway regions characterized by landmarks face challenges due to faulty sensor calibration, localization, and map material errors, leading to position inaccuracies, especially at long distances and high speeds.
Innovation Solution
The method involves associating sensor measurement data with stored landmark reference data to determine the position of obstructing objects on the roadway by calculating sensor-capture-specific locating distances between unassociated sensor data and landmarks, thereby correlating the obstructing objects with the roadway region.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sensor-based capture and coordinate transformation methods are used to locate obstructing objects, then collision avoidance capability is enabled, but position accuracy deteriorates at long distances due to error accumulation from faulty sensor calibration, ego-localization, and map material
Solution Approach 1:
The patent introduces landmarks as intermediary reference objects between the sensor system and the obstructing objects. Instead of directly transforming sensor coordinates to global coordinates (which accumulates errors), the system uses landmarks with known global positions as mediators. The sensor captures landmarks, determines relative positions, and uses these as reference points to locate obstructing objects, thereby reducing error propagation from calibration and localization faults.
Solution Approach 2:
The patent changes the reference frame parameter from direct global coordinate transformation to landmark-relative coordinate system. By expressing obstructing object positions relative to nearby landmarks rather than transforming from sensor coordinates directly to global coordinates, the system alters the computational parameters to avoid error-prone transformations and improve position accuracy at long distances.
2Measurement precision
If multiple sensors are used with probabilistic fusion to reduce position inaccuracies, then measurement precision improves, but device complexity increases
Solution Approach 1:
The patent extracts and utilizes naturally occurring or pre-deployed landmarks in the environment as additional reference points. Instead of adding more active sensors to the vehicle system, the solution extracts useful information from passive environmental features (landmarks) that already exist, thereby improving measurement precision without increasing device complexity.
Data Source
AI summary
The disclosed locates obstacles in vehicle roadway regions, without needing to precisely locate the obstacles or landmarks. By associating sensor measurement data, which is detected by a vehicle sensor system and belongs to sensor measurement objects and by obstacles or landmarks can be represented, with stored landmark data; and ascertaining a sensor detection-specific locating distance between a sensor measurement object based on associated and unassociated sensor measurement data in that pieces of sensor detection-specific information contained in the sensor measurement data relating to the locating distance to be ascertained are put into a relationship with one another, an obstacle in a vehicle roadway region, is located is determined on a roadway region constituting an obstacle to the vehicle if the sensor measurement object with unassociated sensor measurement data on the roadway can be correlated at least on the basis of the sensor detection-specific locating distance.