Velocity Grid Generation for Curved Object Tracking
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional velocity grids for autonomous vehicles are not precise, as they are manually generated and lack accurate representation of object movements, especially in complex scenarios like curved trajectories.
Innovation Solution
A computer-implemented method and system that simulate road scenarios with objects to generate accurate velocity grids by recording image data, identifying 3D points, and projecting velocities back into 2D frames, enabling more precise encoding of velocities for improved object tracking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If velocity grids are manually generated, then the process is simple and quick, but the precision and accuracy of object movement representation deteriorates
Solution Approach 1:
The patent creates virtual copies of real-world road scenarios in a simulated environment. These virtual scenarios include simulated objects (vehicles, pedestrians, cyclists) that replicate real traffic conditions. By copying realistic movement patterns and trajectories into the simulation, the system can generate velocity grids with high precision without manual intervention, resolving the contradiction between accuracy and complexity
Solution Approach 2:
The patent replaces the manual mechanical process of drawing velocity vectors with an automated computational system. The simulation engine automatically calculates velocity grids by tracking simulated objects through multiple image frames, computing velocity vectors mathematically rather than through manual drawing. This substitution of manual mechanical work with automated computation maintains simplicity while dramatically improving precision
2Adaptability or versatility
If velocity grids are manually drawn, then the method is easy to implement, but the representation of complex movements like curved trajectories deteriorates
Solution Approach 1:
The patent implements dynamic velocity grid generation that automatically adapts to complex movement patterns. The simulation tracks objects through multiple frames and calculates velocity vectors that naturally capture curved trajectories, acceleration, and deceleration. This dynamic computational approach replaces static manual drawing methods, enabling accurate representation of complex movements while maintaining ease of operation through automation
Solution Approach 2:
The simulation system performs self-service by automatically generating velocity grids without human intervention. The simulated objects themselves provide the movement data needed to create accurate velocity representations. The system self-corrects and self-adapts to various movement patterns including curved trajectories, eliminating the need for manual adjustment while improving both versatility and ease of use
Data Source
AI summary
A computer-implemented method is provided for creating a velocity grid using a simulated environment for use by an autonomous vehicle. The method may include simulating a road scenario with simulated objects. The method may also include recording image data collected from a camera sensor, the image data comprising a first 2D image frame comprising the simulated objects made up of a plurality of pixels. The method may also include identifying a first 3D point on the first simulated object in a 3D view of the simulated road scenario, wherein the first 3D point corresponds to the first pixel in the first 2D image frame. The method may also include generating a velocity of the first point based upon a velocity of the first simulated object, and projecting the velocity back into the first 2D image frame. The method may further include encoding the velocity for the first pixel prior to a simulated movement of the simulated object with respect to a second pixel after the simulated movement of the simulated object in a 2D velocity grid.