18492961. METHOD FOR DETECTING LANE MARKINGS simplified abstract (Robert Bosch GmbH)
Contents
- 1 METHOD FOR DETECTING LANE MARKINGS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD FOR DETECTING LANE MARKINGS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
METHOD FOR DETECTING LANE MARKINGS
Organization Name
Inventor(s)
Maximilian Pittner of Erlangen (DE)
Alexandru Paul Condurache of Renningen (DE)
METHOD FOR DETECTING LANE MARKINGS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18492961 titled 'METHOD FOR DETECTING LANE MARKINGS
Simplified Explanation
The abstract describes a method for training a model to detect lane markings using images specific to a vehicle's recording and ground truth data for the lane markings' geometry.
- Images provided are specific to a vehicle's recording by at least one sensor.
- Ground truth data is provided for the geometry of the lane markings in the images.
- The model is trained based on the provided images and ground truth data for three-dimensional modeling of the lane markings' geometry.
Potential Applications
This technology can be applied in the development of advanced driver assistance systems (ADAS) and autonomous vehicles for accurate lane detection and tracking.
Problems Solved
1. Improved accuracy in detecting lane markings. 2. Enhancing the safety and efficiency of autonomous driving systems.
Benefits
1. Increased road safety by ensuring vehicles stay within lanes. 2. Enhanced navigation systems for better route planning. 3. Improved overall driving experience for users.
Potential Commercial Applications
Optimizing this technology for commercial applications in the automotive industry can lead to the development of more reliable and efficient autonomous vehicles, contributing to the growth of the smart transportation sector.
Possible Prior Art
Prior art in lane detection systems includes various computer vision and machine learning techniques used for lane detection in autonomous vehicles and ADAS. These methods have evolved over the years to improve accuracy and reliability in lane detection systems.
Unanswered Questions
How does this method compare to existing lane detection technologies in terms of accuracy and efficiency?
This article does not provide a direct comparison with existing lane detection technologies, leaving a gap in understanding the performance of this method relative to others in the field.
What are the potential limitations or challenges faced when implementing this method in real-world scenarios?
The article does not address potential limitations or challenges that may arise when deploying this technology in practical applications, leaving room for further exploration of its feasibility and scalability.
Original Abstract Submitted
A method for training a model to detect lane markings. The method includes: providing images that are specific to a recording by at least one sensor of a vehicle, and in which the lane markings are mapped; providing ground truth data specific to a geometry of the lane markings in the provided images; training the model on the basis of the provided images and ground truth data for a three-dimensional modeling of the geometry of the lane markings based on a parameterization of a continuous curve.
