Parking Vehicle Self-Localization With Selective Sensor Activation
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Solution Overview
Problem
The high energy consumption and demand for computing resources in autonomous vehicles for continuous environment sensing and self-localization in parking infrastructure, due to the need for multiple sensor systems to function simultaneously, lead to inefficiencies and reduced service life of sensor systems.
Innovation Solution
A method that consults a stored assignment instruction to activate only the most suitable environment sensor system based on the vehicle's pose and dominant landmark type, deactivating less necessary systems to reduce energy consumption and extend sensor system lifespan, by matching the vehicle's pose with preferred sensor types or dominant landmark types, thereby optimizing sensor usage for self-localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple sensor systems are activated simultaneously for continuous environment sensing, then self-localization reliability is improved, but energy consumption increases
Solution Approach 1:
The patent applies dynamics by making the sensor system configuration adaptive rather than static. The control system dynamically activates or deactivates specific sensor systems based on real-time environmental conditions detected by the pose determination system. This allows the system to maintain reliable self-localization by activating only the necessary sensors for the current environment type (e.g., activating optical sensors in well-lit areas, radar in dark or occluded areas), thereby reducing overall energy consumption while preserving localization reliability.
Solution Approach 2:
The system changes operational parameters by adjusting which sensor systems are active based on environmental parameters. The control system modifies the activation state of sensor systems according to the determined environment type (parking garage, tunnel, open area, etc.), effectively changing the system's energy consumption profile while maintaining adequate localization performance for each specific environment.
2Measurement precision
If multiple sensor systems are activated simultaneously for continuous environment sensing, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the sensor system operation into environment-specific configurations. Instead of treating all sensing operations uniformly, the system segments sensor activation based on environment types (parking garages, tunnels, open areas, etc.). The control system determines the current environment type and activates only the sensor subsystems appropriate for that environment, simplifying the overall system management while maintaining measurement precision for each specific context.
Solution Approach 2:
The control system serves multiple functions: it determines pose, classifies environment type, selects appropriate sensor configurations, and manages sensor activation. This multi-functional approach consolidates what would otherwise be separate systems into a unified control architecture, reducing device complexity while maintaining the capability to achieve precise measurements across diverse environments.
3Adaptability or versatility
If multiple sensor systems operate continuously, then adaptability to different environments is improved, but loss of energy increases
Solution Approach 1:
The system performs preliminary action by pre-determining the environment type based on initial pose determination and sensor data analysis. The control system uses the detected environment classification to proactively select and activate the appropriate sensor configuration before actual localization tasks begin, ensuring energy-efficient operation from the start while maintaining adaptability to the specific environmental conditions.
Data Source
AI summary
According to a method for self-localization of a vehicle, a first pose of the vehicle is determined in a map coordinates system, based on environment sensor data representing an environment of the vehicle, a landmark is detected in the environment, a position of the landmark is determined in the map coordinates system and a second pose of the vehicle is determined in the map coordinates system dependent on the position of the landmark. An assignment instruction is consulted, matching up the first pose with at last one preferred sensor type or at least one dominant landmark type. Depending on the assignment instruction, a first environment sensor system is activated and a second environment sensor system is deactivated, whereupon the environment sensor data are generated by means of the first environment sensor system.