# US 12,002,361 B2 · Localized artificial intelligence for intelligent road infrastructure > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,002,361 B2 - Document ID: US12002361B2 - Status: Granted - Kind: B2 - Application number: 16/917,997 - Filed: 2020-07-01 - Published: 2021-01-07 - Granted: 2024-06-04 - Earliest claimed: 2019-07-03 - Assignees: Cavh LLC - Applicants: Cavh LLC - Inventors: Yang Cheng; Bin Ran; Shen Li; Shuoxuan Dong; Tianyi Chen; Yuan Zheng; Xiaotian Li; Zhen Zhang; Yang Zhou - Web page: https://patentgrep.com/patent/US12002361B2 ## CPC - G08G 1/164: {Centralised systems, e.g. external to vehicles} - G08G 1/0116: {from roadside infrastructure, e.g. beacons} - G08G 1/012: {from other sources than vehicle or roadside beacons, e.g. mobile networks} - G08G 1/0129: {for creating historical data or processing based on historical data} - G08G 1/0141: {for traffic information dissemination} - G08G 1/096716: {where the received information does not generate an automatic action on the vehicle control} - G08G 1/096783: {where the origin of the information is a roadside individual element} - G08G 1/165: {for passive traffic, e.g. including static obstacles, trees} - G08G 1/166: {for active traffic, e.g. moving vehicles, pedestrians, bikes} - G08G 1/22: {Platooning, i.e. convoy of communicating vehicles} - G08G: TRAFFIC CONTROL SYSTEMS (guiding railway traffic, ensuring the safety of railway traffic B61L; arrangement of road signs or traffic signals E01F9/00; radar or analogous systems, sonar systems, lidar systems specially adapted for traffic control G01S13/91, G01S15/88, G01S17/88; {radar or analogous systems, sonar systems, lidar systems specially adapted for anti-collision purposes G01S13/93, G01S15/93, G01S17/93}) ## Abstract Provided herein is technology relating to connected and automated highway systems and particularly, but not exclusively, to systems and methods for providing localized self-evolving artificial intelligence for intelligent road infrastructure systems. ## Claims ### Claim 1 A roadside unit (RSU) network comprising one or more RSU, wherein said one or more RSU comprises: 1) an artificial intelligence (AI) system for automated vehicle control and traffic operations, wherein said AI system comprises: a) a database of accumulated historical data comprising background, vehicle, traffic, object, and/or environmental data for a localized area; b) sensors configured to provide real-time data comprising background, vehicle, traffic, object, and/or environmental data for said localized area; and c) a computation component configured to compare said real-time data and said accumulated historical data to provide sensing, behavior prediction and management, decision making, and vehicle control for an intelligent road infrastructure system (IRIS); wherein the AI system is configured to provide proactive safety methods by predicting incidents and estimating risk; and 2) a data processing module configured to fuse data from data sources comprising vehicle sensors and roadside sensors. ### Claim 2 (depends on 1) The RSU network of claim 1, wherein said computation component is configured to implement a self-evolving algorithm. ### Claim 3 (depends on 1) The RSU network of claim 1, wherein said localized area comprises a coverage area served by a roadside unit (RSU). ### Claim 4 (depends on 1) The RSU network of claim 1, wherein said AI system comprises an interface for communicating with a plurality of other IRIS components, smart cities, and/or other smart infrastructure. ### Claim 5 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to determine a vehicle location. ### Claim 6 (depends on 1) The RSU network of claim 1, wherein said AI system determines a vehicle location using a plurality of reference points. ### Claim 7 (depends on 1) The RSU network of claim 1, wherein said AI system determines a vehicle location using a plurality of reflective fixed structures. ### Claim 8 (depends on 1) The RSU network of claim 1, wherein said AI system further comprises a component to provide a plurality of map services. ### Claim 9 (depends on 1) The RSU network of claim 1, wherein said AI system is further configured to identify a plurality of high-risk locations, wherein a high-risk location is a location comprising an animal, a pedestrian, a traffic accident, unsafe pavement, and/or adverse weather. ### Claim 10 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to sense an environment and road in real time to acquire environmental and/or road data. ### Claim 11 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to predict a plurality of road and environmental conditions using said database of accumulated historical data and said real-time data, wherein said real-time data is provided by one or more sensors of said RSU network and/or by one or more vehicle sensors. ### Claim 12 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to detect objects on a road. ### Claim 13 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to detect objects on a roadside. ### Claim 14 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to predict object behavior. ### Claim 15 (depends on 1) The RSU network of claim 1, wherein said AI system further comprises safety hardware and safety software to reduce a crash frequency and a crash severity. ### Claim 16 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to transmit local knowledge, information, and data from an RSU to other RSUs and/or traffic control units (TCUs) to improve performance and efficiency of an IRIS. ### Claim 17 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to transfer local knowledge, information, and data of a plurality of RSUs, TCUs, and/or traffic control centers (TCCs) during hardware upgrades to the IRIS. ### Claim 18 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to provide intelligence coordination to: a) distribute intelligence among a plurality of RSUs and connected and automated vehicles to improve performance and robustness of automated vehicle control and traffic operations; b) decentralize system control with self-organized control; and c) divide labor and distribute tasks. ### Claim 19 (depends on 1) The RSU network of claim 1, wherein said AI system further comprises an interface for a) a plurality of smart cities applications managed by a city; and/or b) a plurality of third-party systems and applications. ### Claim 20 (depends on 1) The RSU network of claim 1, wherein said AI system is configured to collect and share data from a plurality of multiple sources and provide data to RSUs.