Vehicle Pose Determination Using Adaptive Landmark Detection
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Solution Overview
Problem
The existing methods for determining the pose of a vehicle in an at least partially automated manner require significant processing power and data handling due to the need to process multiple types of landmark data from various sensors, which can be inefficient, especially under adverse environmental conditions, and may compromise safety if not managed effectively.
Innovation Solution
Selecting and activating only the necessary detection algorithms based on environmental influences, such as weather and illumination, to process landmark data, thereby minimizing processing power and data volume, ensuring that only reliable landmark types are considered for vehicle control, allowing for efficient resource allocation and stable system behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If all detector algorithms are activated to process all types of landmark data, then the completeness of environment modeling is improved, but the processing power and hardware resources required increase significantly
Solution Approach 1:
The system dynamically adapts the set of activated detector algorithms based on current environmental conditions. Instead of a static configuration where all detectors are always active, the system adjusts which detectors are activated in real-time according to factors like weather, illumination, and detected environmental features, optimizing the balance between modeling completeness and resource consumption
Solution Approach 2:
Different detector algorithms are selectively activated based on local environmental characteristics. The system evaluates specific environmental conditions (e.g., wet road conditions, darkness, fog) and activates only the detector algorithms appropriate for those local conditions, rather than uniformly activating all detectors everywhere
2Reliability
If all detector algorithms are activated to ensure reliable vehicle control under all conditions, then the reliability of vehicle control is improved, but the data volume and processing requirements increase
Solution Approach 1:
The system dynamically adjusts the activation state of detector algorithms based on environmental conditions that affect reliability. When environmental conditions are favorable for certain landmark types (e.g., good visibility for optical markings), those detectors are activated. When conditions deteriorate (e.g., wet roads making road markings unreliable), corresponding detectors are deactivated or deprioritized, maintaining reliability while reducing data volume
Solution Approach 2:
The system changes operational parameters (activation status of detectors) based on environmental parameter assessments. By monitoring environmental parameters like illumination levels, weather conditions, and road surface state, the system adjusts which detectors are active, ensuring reliable operation under varying conditions while optimizing data processing requirements
3Productivity
If detector algorithms are deactivated to reduce processing power consumption, then the resource efficiency is improved, but the accuracy of pose determination may deteriorate under adverse environmental conditions
Solution Approach 1:
The system changes the activation parameters of detector algorithms based on environmental condition assessments. When environmental conditions are favorable, more detectors are activated to maximize accuracy. When conditions are adverse, the system selectively deactivates detectors known to perform poorly under those conditions while keeping detectors that remain reliable active, thus maintaining accuracy while optimizing resource efficiency
Solution Approach 2:
The system dynamically adjusts detector activation to match environmental conditions, creating a flexible balance between resource consumption and measurement accuracy. The activation state of each detector is dynamically determined based on real-time environmental assessments, allowing the system to optimize accuracy when resources are abundant and conserve resources when conditions warrant it
Data Source
AI summary
A method is described for determining a pose of a vehicle that is driving in an at least partially automated manner, with the aid of different landmark types, and in order to determine the pose of the vehicle, a vehicle control system processes landmark data of the detected landmark types with the aid of at least one detector algorithm. At least one detection algorithms is selected and used for processing the landmark data of certain landmark types as a function of environmental influences.