Route Section Evaluation for Landmark-Based Vehicle Localization
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Solution Overview
Problem
Existing methods for evaluating route sections for automated driving operations rely heavily on landmark density and detectability, which can lead to high uncertainty and reduced integrity of vehicle localization, especially in areas with low landmark density or adverse environmental conditions.
Innovation Solution
A method for evaluating route sections by determining the spatial density of landmarks and expected detectability under various ambient conditions, allowing for classification of route segments based on their suitability for automated driving modes and maneuvers, and storing these classifications as route attributes for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If landmark-based localization is used for automated driving, then localization accuracy is improved, but reliability deteriorates in areas with low landmark density
Solution Approach 1:
The system performs preliminary evaluation of route sections by determining spatial density of landmarks and expected detectability under various ambient conditions before automated driving operations. This advance assessment allows the system to identify areas with low landmark density or poor detectability, enabling proactive measures such as selecting alternative routes or adjusting driving parameters before entering problematic areas, thus maintaining both accuracy and reliability
Solution Approach 2:
The system changes operational parameters based on the evaluated route characteristics. When low landmark density or poor detectability is detected, the system adjusts localization strategies, such as switching between different sensor systems (lidar, camera, radar), modifying driving speed, or changing lateral positioning within lanes to optimize the use of available landmarks. This dynamic parameter adjustment maintains localization reliability across varying environmental conditions
2Duration of action of moving object
If fallback methods like odometry-based dead reckoning are used when landmarks are scarce, then continuous localization is maintained, but accuracy deteriorates quickly
Solution Approach 1:
The system prepares for potential landmark scarcity by having multiple localization methods ready and by evaluating route sections in advance. When landmark density is insufficient, the system transitions to fallback methods like odometry-based dead reckoning or inertial navigation, but does so in a controlled manner with pre-calculated compensation strategies. The system also uses map-matching techniques to periodically correct drift accumulation, cushioning the accuracy degradation that would otherwise occur rapidly during extended periods without sufficient landmarks
3Productivity
If vehicle speed is increased for efficient transportation, then productivity is improved, but safety deteriorates when localization accuracy is insufficient
Solution Approach 1:
The system dynamically adjusts vehicle operating parameters including speed, acceleration, and lateral positioning based on real-time assessment of localization quality and route characteristics. In areas with high landmark density and good detectability, the system maintains higher speeds for efficient transportation. When entering areas with low landmark density or poor environmental conditions, the system automatically reduces speed to allow more time for sensor processing and increases the frequency of localization updates, thereby maintaining safety while minimizing impact on overall transportation efficiency
Data Source
AI summary
A method for evaluating suitability route sections of a digital map storing landmarks for automated driving operation of a vehicle is provided. For each route section of the digital map a spatial density of landmarks is determined, an expected recognizability of the landmarks is determined by a vehicle sensor system under predetermined ambient conditions, a classification is performed based on the determined density and recognizability of the landmarks as to whether a vehicle can be located on the route section with a minimum accuracy required for a predetermined operating mode and/or for a predetermined driving maneuver, and a classification result is stored as a data record in a route attribute associated with the route section, the route attribute indicating for which of the predetermined operating modes and/or driving maneuvers requirements for the minimum accuracy of the landmark-based vehicle localization are met under which of the predetermined environmental conditions.