Waymo llc (20240135727). Stop Location Change Detection simplified abstract

Stop Location Change Detection

Organization Name

waymo llc

Inventor(s)

Romain Thibaux of Fremont CA (US)

David Harrison Silver of San Carlos CA (US)

Congrui Hetang of Sunnyvale CA (US)

Stop Location Change Detection - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240135727 titled 'Stop Location Change Detection

The technology described in the patent application focuses on determining appropriate stopping locations for self-driving vehicles at intersections, even in the absence of stop lines or when map data is outdated.

• Utilizes a neural network for classification, localization, and uncertain estimation processes.
• Analyzes input training data and sensor data to evaluate distribution information for potential stop locations.
• Helps the vehicle determine an optimal stop point, which may not always align with map data.
• Updates existing map data based on the determined stop points for future reference.

1. 1. 1. Potential Applications:

This technology can be applied in autonomous vehicles, smart city infrastructure, and transportation systems to enhance safety and efficiency at intersections.

1. 1. 1. Problems Solved:

Addresses the challenge of accurately determining stopping locations for self-driving vehicles at intersections without relying solely on outdated map data or visible stop lines.

1. 1. 1. Benefits:

Improves the accuracy of stopping locations for autonomous vehicles, enhances overall safety at intersections, and enables better coordination between vehicles in traffic.

1. 1. 1. Commercial Applications:

This technology can be utilized by autonomous vehicle manufacturers, urban planners, and transportation authorities to optimize traffic flow and enhance the performance of self-driving vehicles in urban environments.

1. 1. 1. Prior Art:

Prior research has focused on mapping technologies for autonomous vehicles, but this specific approach to determining stopping locations at intersections is a novel innovation.

1. 1. 1. Frequently Updated Research:

Ongoing research in this field includes advancements in sensor technology, machine learning algorithms, and real-time data processing to further enhance the capabilities of self-driving vehicles at intersections.

1. 1. 1. 1. Questions about the Technology:

1. How does this technology improve the overall efficiency of self-driving vehicles at intersections? 2. What are the potential implications of using this technology in urban transportation systems?

Original Abstract Submitted

the technology relates to approaches for determining appropriate stopping locations at intersections for vehicles operating in a self-driving mode. while many intersections have stop lines painted on the roadway, many others have no such lines. even if a stop line is present, the physical location may not match what is in store map data, which may be out of date due to construction or line repainting. aspects of the technology employ a neural network that utilizes input training data and detected sensor data to perform classification, localization and uncertain estimation processes. based on these processes, the system is able to evaluate distribution information for possible stop locations. the vehicle uses such information to determine an optimal stop point, which may or may not correspond to a stop line in the map data. this information is also used to update the existing map data, which can be shared with other vehicles.