Waymo llc (20240262393). Automated Cut-In Identification and Classification simplified abstract
Contents
Automated Cut-In Identification and Classification
Organization Name
Inventor(s)
Pablo Abad of Mountain View CA (US)
Aman Ved Kalia of Mountain View CA (US)
Juan Gomez-ramos of Mountain View CA (US)
Jiayi Chen of Mountain View CA (US)
Jasman Singh Malik of Mountain View CA (US)
Joe Riggs of Mountain View CA (US)
Automated Cut-In Identification and Classification - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240262393 titled 'Automated Cut-In Identification and Classification
The patent application relates to a method for identifying and classifying cut-ins in operational data of vehicles, with a focus on training a model for controlling autonomous vehicles based on this data.
- Obtaining operational data about vehicles
- Identifying the presence of cut-ins within the data
- Extracting cut-in data from the operational data
- Training a model for autonomous vehicle control based on the extracted cut-in data
Potential Applications: - Autonomous driving systems - Traffic management systems - Vehicle safety technologies
Problems Solved: - Improving the ability of autonomous vehicles to react to cut-ins - Enhancing overall road safety and efficiency
Benefits: - Increased accuracy in identifying and reacting to cut-ins - Enhanced control and decision-making capabilities for autonomous vehicles
Commercial Applications: "Cut-in Identification and Classification Technology for Autonomous Vehicles: Enhancing Safety and Efficiency in Transportation Systems"
Questions about the technology: 1. How does this technology improve the safety of autonomous vehicles on the road? 2. What are the potential implications of this technology for traffic management systems?
Original Abstract Submitted
example embodiments relate to a method for cut-in identification and classification. an example embodiment includes a obtaining operational data about one or more vehicles; based on the operational data, identifying the presence of one or more cut-ins within the operational data; extracting, from the operational data, cut-in data that depicts one or more of the cut-ins identified within the operational data; and, based on the extracted cut-in data, training a model for controlling an autonomous vehicle. identifying the presence of a given cut-in includes: determining that at least one vertex of a bounding box surrounding a vehicle was located more than a threshold distance within a lane being navigated by a given vehicle; and determining that the ability of the given vehicle to maintain its course and speed was impeded by the presence of the particular additional vehicle within the lane.
