17895330. SYSTEMS AND METHODS FOR DETECTING ROADWAY LANE BOUNDARIES simplified abstract (TOYOTA JIDOSHA KABUSHIKI KAISHA)
Contents
SYSTEMS AND METHODS FOR DETECTING ROADWAY LANE BOUNDARIES
Organization Name
TOYOTA JIDOSHA KABUSHIKI KAISHA
Inventor(s)
Kun-Hsin Chen of Mountain View CA (US)
Shunsho Kaku of Mountain View CA (US)
Jeffrey M. Walls of Ann Arbor MI (US)
Steven A. Parkison of Ann Arbor MI (US)
SYSTEMS AND METHODS FOR DETECTING ROADWAY LANE BOUNDARIES - A simplified explanation of the abstract
This abstract first appeared for US patent application 17895330 titled 'SYSTEMS AND METHODS FOR DETECTING ROADWAY LANE BOUNDARIES
Simplified Explanation
The patent application describes systems and methods for detecting roadway lane boundaries using image data and historical vehicle trajectory data. Here is a simplified explanation of the abstract:
- Image data of a roadway portion is received.
- Historical vehicle trajectory data for the same portion is received.
- A heatmap is generated from the historical vehicle trajectory data, indicating spatial coincidence with vehicle trajectories.
- The heatmap is projected onto the image data to train a neural network for detecting lane boundaries.
- The trained neural network is deployed in a vehicle to generate and save map data with detected lane boundaries.
Potential applications of this technology:
- Autonomous driving systems
- Advanced driver assistance systems
- Traffic management systems
Problems solved by this technology:
- Accurate detection of roadway lane boundaries
- Enhancing vehicle navigation and control systems
- Improving road safety by providing precise lane information
Benefits of this technology:
- Increased accuracy in lane boundary detection
- Enhanced vehicle navigation capabilities
- Improved overall road safety and traffic flow
Original Abstract Submitted
Systems and methods for detecting roadway lane boundaries are disclosed herein. One embodiment receives image data of a portion of a roadway; receives historical vehicle trajectory data for the portion of the roadway; generates, from the historical vehicle trajectory data, a heatmap indicating, for a given pixel in the heatmap, an extent to which the given pixel coincides spatially with vehicle trajectories in the historical vehicle trajectory data; and projects the heatmap onto the image data to generate a composite image that is used in training a neural network to detect roadway lane boundaries, the projected heatmap acting as supervisory data. The trained neural network is deployed in a vehicle to generate and save map data including detected roadway lane boundaries for use by other vehicles or to control operation of the vehicle itself based, at least in part, on roadway lane boundaries detected by the trained neural network.
