Google llc (20240202490). Lane Selection Using Machine Learning simplified abstract
Contents
Lane Selection Using Machine Learning
Organization Name
Inventor(s)
Thomas Deselaers of Zurich (CH)
Lane Selection Using Machine Learning - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202490 titled 'Lane Selection Using Machine Learning
The abstract of the patent application describes a system that helps a vehicle choose a lane in a multi-lane road segment by identifying another vehicle in a region ahead, tracking its movement using optical flow, estimating traffic speed, and using machine learning to recommend the best lane.
- The system identifies another vehicle in a region ahead of the vehicle.
- It tracks the movement of the identified vehicle using optical flow.
- The system estimates the speed of traffic based on the tracked movement.
- Machine learning is applied to generate a recommendation on which lane the vehicle should choose.
- The recommendation is based on the estimated traffic speed and other factors.
Potential Applications: - Autonomous vehicles navigation systems - Traffic management systems - Fleet management systems
Problems Solved: - Helps vehicles make informed decisions on lane selection - Improves traffic flow and reduces congestion - Enhances overall road safety
Benefits: - Increased efficiency in lane selection - Improved traffic flow - Enhanced safety for drivers and passengers
Commercial Applications: Title: "Smart Lane Selection System for Autonomous Vehicles" This technology can be used in autonomous vehicles to improve navigation and optimize lane selection, leading to safer and more efficient transportation systems. It can also be integrated into traffic management solutions for cities to enhance overall traffic flow and reduce congestion.
Questions about Smart Lane Selection System for Autonomous Vehicles:
1. How does the system track the movement of other vehicles in the region ahead? The system uses optical flow techniques to track the movement of other vehicles in the region ahead, allowing it to estimate traffic speed accurately.
2. What are the potential benefits of using machine learning in lane selection for vehicles? Machine learning helps vehicles make data-driven decisions on lane selection, leading to improved efficiency, safety, and overall traffic flow.
Original Abstract Submitted
to select a lane in a multi-lane road segment for a vehicle travelling on the road segment, a system identifies, in multiple lanes and in a region ahead of the vehicle, another vehicle defining a target; the system applies an optical flow technique to track the target during a period of time, to generate an estimate of how fast traffic moves; and the system applies the estimate to machine learning (ml) model to generate a recommendation which one of the plurality of lanes the vehicle is to choose
