Autonomous vehicle cloud system

Patent metadata

Field	Value
Publication number	US-12266262-B2
Application number	US-202318227541-A
Country	US
Kind code	B2
Filing date	Jul 28, 2023
Priority date	May 17, 2017
Publication date	Apr 1, 2025
Grant date	Apr 1, 2025

Abstract

Provided herein is a technology for an Autonomous Vehicle Cloud System (AVCS). This AVCS provides sensing, data fusion, prediction, decision-making, and/or control instructions for specific vehicles at a microscopic level based on data from one or more of other vehicles, roadside unit (RSU), cloud-based platform, and traffic control center/traffic control unit (TCC/TCU). Specifically, the AVs can be effectively and efficiently operated and controlled by the AVCS. The AVCS provides individual vehicles with detailed time-sensitive control instructions for fulfilling driving tasks, including car following, lane changing, route guidance, and other related information. The AVCS is configured to predict individual vehicle behavior and provide planning and decision-making at a microscopic level. In addition, the AVCS is configured to provide one or more of virtual traffic light management, travel demand assignment, traffic state estimation, and platoon control.

First claim

We claim:

1. An autonomous vehicle cloud system (AVCS) comprising:
a) a cloud-based platform that provides information services and computing services, said cloud-based platform comprising a sensing subsystem, a prediction subsystem, a planning and decision-making subsystem, and a control subsystem; and
b) a communication module that communicates with one or more of: other autonomous vehicles (AVs), a roadside unit (RSU), or a traffic control center/traffic control unit (TCC/TCU); and that receives vehicle-specific information from the other AVs; the RSU; or the TCC/TCU,
wherein the cloud-based platform fuses multi-source data collected from vehicle sensors, roadside sensors, and the cloud; and predicts conditions of an entire transportation network for individual vehicles at a microscopic level, wherein said conditions comprise longitudinal movements and lateral movements of individual vehicles.

2. The AVCS of claim 1 , further comprising a cloud infrastructure; and an application service subsystem.

3. The AVCS of claim 2 , wherein the cloud infrastructure comprises a computation module and a storage module.

4. The AVCS of claim 2 , wherein the application service subsystem provides additional information acquisition capability as a service to the AVCS; additional storage needs as a service to the AVCS; additional control capability as a service to the AVCS; additional computing resources to the AVCS; additional sensing capability as a service to the AVCS; and/or additional operations and maintenance capability as a service to the AVCS.

5. The AVCS of claim 1 , providing functions to vehicles for performing driving tasks, wherein the functions comprise one or more of: sensing functions, prediction functions, planning and decision-making functions, and control functions; and the functions are performed using data provided by one or more of: the other AVs, the RSU, the cloud-based platform, and the TCC/TCU.

6. The AVCS of claim 1 , further comprising one or more of: a communication module, a computation module, a storage module, a sensing module, a prediction module, a decision-making module, a planning module, a control module, and a security module.

7. The AVCS of claim 1 , wherein the sensing subsystem is configured to acquire data from one or more of: the other AVs, the RSU, the cloud-based platform, and the TCC/TCU to generate comprehensive information at a microscopic level, wherein said comprehensive information comprises vehicle information, weather information, vehicle attribute data, traffic state information, road information, and/or incident information.

8. The AVCS of claim 1 , wherein the prediction subsystem is configured to predict the behavior of individual vehicles at a microscopic level and to predict a traffic state or a traffic demand using data from one or more of the other AVs, the RSU, the cloud-based platform, and the TCC/TCU.

9. The AVCS of claim 1 , wherein the planning and decision-making subsystem is configured to provide individual vehicles with decision instructions at a microscopic level using data from one or more of the other AVs, the RSU, the cloud-based platform, and the TCC/TCU, wherein the decision instructions comprise instructions for longitudinal control and for lateral control.

10. The AVCS of claim 1 , wherein the control subsystem is configured to produce or receive time-sensitive control instructions for specific vehicles to fulfill driving tasks using data from one or more of the other AVs, the RSU, the cloud-based platform, and the TCC/TCU, wherein said time-sensitive control instructions comprise instructions for vehicle longitudinal acceleration and speed, vehicle lateral acceleration and speed, and vehicle orientation and direction.

11. The AVCS of claim 1 , wherein the cloud-based platform provides individual vehicles with vehicle-specific information comprising weather information, pavement conditions, and/or estimated travel time.

12. The AVCS of claim 1 , wherein the cloud-based platform is configured to allocate computation power and storage resources and to provide one or more of sensing functions, prediction functions, planning functions, decision-making functions, and/or control functions at a microscopic level, a mesoscopic level, and a macroscopic level.

13. The AVCS of claim 1 , wherein said cloud-based platform is configured to:
a) fuse multi-source data collected from one or more of the other AVs, the RSU, the cloud-based platform, and the TCC/TCU;
b) implement learning-based models, statistical models, and empirical models; and/or
c) optimize the output of one or more of the sensing subsystem, the prediction subsystem, the planning and decision making subsystem, and the control subsystem.

14. The AVCS of claim 1 , wherein the cloud-based platform provides a virtual traffic light control function by receiving sensor information from road side sensors; analyzing the sensor information; and sending sensor information to vehicles.

15. The AVCS of claim 1 , providing a fleet maintenance function comprising remote vehicle diagnostics, intelligent fuel-saving driving, and intelligent charge/refuel.

16. The AVCS of claim 1 , wherein the cloud-based platform provides operations and maintenance services for vehicles; and/or provides security, redundancy, and resiliency measures.

17. The AVCS of claim 1 , wherein the cloud-based platform uses a weighted fusion of data and a traffic state estimation and prediction algorithm to provide an estimated traffic state.

18. The AVCS of claim 1 , wherein the cloud-based platform communicates with one or more of the other AVs, the RSU, and the TCC/TCU; and receives vehicle-specific information from one or more of the AVs, the RSU, or the TCC/TCU.

19. The AVCS of claim 1 , wherein the cloud-based platform provides safety and efficiency measures for vehicle operations and control under adverse weather conditions.

20. The AVCS of claim 1 , wherein the cloud-based platform is configured to distribute driving tasks and functions for a specific vehicle.

Assignees

• Cavh Llc

Inventors

• Ran Bin
• Zheng Yuan
• Wang Can
• Cheng Yang
• Yao Yifan
• Wu Keshu
• Chen Tianyi
• Shi Haotian
• Li Shen
• Shi Kunsong
• Zhang Zhen
• Ding Fan
• Tan Huachun
• Wu Yuankai
• Dong Shuoxuan
• Ye Linhui
• Li Xiaotian

Classifications

• G08G1/164

  Centralised systems, e.g. external to vehicles · CPC title

• G08G1/096725

  where the received information generates an automatic action on the vehicle control · CPC title

• G08G1/166

  for active traffic, e.g. moving vehicles, pedestrians, bikes · CPC title

• G08G1/0968

  Systems involving transmission of navigation instructions to the vehicle · CPC title

• G08G1/0145

  for active traffic flow control · CPC title