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Intelligent road infrastructure system (IRIS): systems and methods

專利號(hào)
US10867512B2
公開日期
2020-12-15
申請人
CAVH LLC(US WI Fitchburg)
發(fā)明人
Bin Ran; Yang Cheng; Shen Li; Zhen Zhang; Fan Ding; Huachun Tan; Yuankai Wu; Shuoxuan Dong; Linhui Ye; Xiaotian Li; Tianyi Chen; Kunsong Shi
IPC分類
G08G1/09; G08G1/0967; B60W30/165; G08G1/16
技術(shù)領(lǐng)域
rsu,rsus,module,vehicle,lane,iris,tcu,tcc,data,traffic
地域: WI WI Fitchburg

摘要

The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. In some embodiments, the IRIS comprises or consists of one of more of the following physical subsystems: (1) Roadside unit (RSU) network, (2) Traffic Control Unit (TCU) and Traffic Control Center (TCC) network, (3) vehicle onboard unit (OBU), (4) traffic operations centers (TOCs), and (5) cloud information and computing services. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.

說明書

FIG. 1 shows an exemplary OBU containing a communication module 101, a data collection module 102, and a vehicle control module 103. The data collection module 102 collects data related to a vehicle and a human 104 and then sends it 104 to an RSU through communication module 101. Also, OBU can receive data of RSU 105 through communication module 101. Based on the data of RSU 105, the vehicle control module 103 helps control the vehicle.

FIG. 2 illustrates an exemplary framework of a lane management sensing system and its data flow.

The RSU exchanges information between the vehicles and the road and communicates with TCUs, the information including weather information, road condition information, lane traffic information, vehicle information, and incident information.

FIG. 3 illustrates exemplary workflow of a basic prediction process of a lane management sensing system and its data flow. In some embodiments, fused multi-source data collected from vehicle sensors, roadside sensors and the cloud is processed through models including but not limited to learning based models, statistical models, and empirical models. Then predictions are made at different levels including microscopic, mesoscopic, and macroscopic levels using emerging models including learning based, statistic based, and empirical models.

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