Robotics & Machine Learning Daily News2024,Issue(Jun.27) :145-148.

Patent Application Titled 'Hierarchical Vehicle Action Prediction' Published Onl ine (USPTO 20240190474)

在线公布的名为“分层车辆行为预测”的专利申请(USPTO 20240190474)

Robotics & Machine Learning Daily News2024,Issue(Jun.27) :145-148.

Patent Application Titled 'Hierarchical Vehicle Action Prediction' Published Onl ine (USPTO 20240190474)

在线公布的名为“分层车辆行为预测”的专利申请(USPTO 20240190474)

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摘要

Robotics&Machine Learning Daily News的新闻记者兼新闻编辑--根据NewsRx记者从华盛顿特区发出的新闻报道,发明者王(加利福尼亚州圣何塞);杨(加利福尼亚州山景城)于2023年5月25日提交的专利申请于2024年6月13日在网上公布。本专利申请没有受让人。记者从发明者提供的背景资料中获得了以下引文:“现在车辆能够以不同程度的自主驾驶。每一个水平都以相对的人类数量和自主控制为特征。例如,汽车工程师协会(SAE)定义了从0(全手动)到5(全自动)的6个驾驶自动化级别。这些级别已被美国交通部采用。自动驾驶汽车提供了许多优点,包括:(1)减少道路上的车辆数量;(2)比人驾驶汽车更可预测和更安全的驾驶。(3)如果道路上的车辆较少,如果它们是电动的,就会减少排放,(4)如果它们由计算机控制,就会提高行驶效率、燃油经济性和交通安全,(5)增加车道容量,(6)缩短行驶时间,以及(7)增加不能潜水的用户的机动性。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News – According to news reporting originating from Wash ington, D.C., by NewsRx journalists, a patent application by the inventors Wang, Yu (San Jose, CA, US); Yang, I-Hsuan (Mountain View, CA, US), filed on May 25, 2023, was made available online on June 13, 2024. No assignee for this patent application has been made. Reporters obtained the following quote from the background information supplied by the inventors: “Vehicles are now capable of self-driving with different level s of autonomy. Each of these levels is characterized by the relative amount of h uman and autonomous control. For example, The Society of Automotive Engineers (S AE) defines 6 levels of driving automation ranging from 0 (fully manual) to 5 (f ully autonomous). These levels have been adopted by the U.S. Department of Trans portation. Autonomous vehicles provide numerous advantages including: (1) loweri ng the number of vehicles on the roads, (2) more predictable and safer driving b ehavior than human driven vehicles, (3) less emissions if there are fewer vehicl es on the road, and if they are electrically powered, (4) improved travel effici ency, fuel economy, and traffic safety if they are controlled by computers, (5) increased lane capacity, (6) shorter travel times, and (7) increased mobility fo r users who are incapable of diving.

Key words

Cyborgs/Emerging Technologies/Machine Learning/Patent Application/Self-Driving Cars/Transportation

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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