Automated Vehicle Positioning Using Urban Light Source Patterns
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Solution Overview
Problem
Existing methods for determining the precise position of automated vehicles in urban areas with high light source density are not robust enough, especially under varying environmental conditions like different times of day, seasons, and weather, which can affect the accuracy and safety of vehicle operation.
Innovation Solution
The method involves acquiring environmental data from at least two light sources to determine a pattern based on color and brightness gradients, matching this pattern with a reference pattern stored in a digital map that accounts for time, season, and weather conditions, and using this information to accurately position the vehicle and operate it safely.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods use light sources for positioning in urban areas, then positioning can be achieved, but robustness under varying environmental conditions (time of day, season, weather) deteriorates
Solution Approach 1:
The patent applies dynamics by making the pattern recognition system adaptive to changing environmental conditions. The system dynamically adjusts to different times of day, seasons, and weather conditions by comparing observed light source patterns with stored reference patterns that account for these variations. This allows the positioning system to maintain accuracy across diverse environmental conditions rather than relying on static assumptions about light source characteristics.
Solution Approach 2:
The patent utilizes parameter changes by monitoring and utilizing variations in color and brightness of light sources as environmental conditions change. Instead of treating these variations as noise to be eliminated, the system uses them as meaningful parameters for identification and positioning. By tracking how color and brightness parameters change under different conditions and matching these against reference data, the system maintains robustness while achieving precise positioning.
2Measurement precision
If multiple light sources are used to improve positioning accuracy, then measurement precision improves, but system complexity increases
Solution Approach 1:
The patent applies universality by using a single sensor system that performs multiple functions: detecting light sources, measuring their color and brightness, determining spatial relationships, and identifying patterns. Rather than requiring separate systems for each function, the invention uses environmental sensors and pattern recognition algorithms to achieve positioning through a unified approach that leverages the multi-functionality of the sensing and processing system.
Solution Approach 2:
The patent applies copying by creating and storing reference patterns of light source arrangements, colors, and brightness values in a database. These reference copies are then compared against observed patterns to determine position. This copying approach allows the system to match observed environmental features against pre-stored templates, simplifying the real-time processing required for accurate positioning without needing complex computational models.
Data Source
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AI summary
The invention relates to a method (300) and a device (110) for determining (340) a highly precise position (210) and for operating (350) an automated vehicle (200), the method comprising: a step of detecting (310) environment data values, said environment data values representing an environment (220) of the automated vehicle (200) and the environment (220) comprising at least two environment features (221, 222); a step of determining (320) a pattern according to the at least two environment features (221, 222); a step of reading in (330) map data values, the map data values representing a map and said map representing at least the environment (220) of the automated vehicle (200) and comprising a reference pattern; a step of determining (340) the highly precise position (210) of the automated vehicle (200), starting from a comparison of the pattern with the reference pattern; and a step of operating (350) the automated vehicle (200) according to the highly precise position (210).