CN111243312B - Partially-distributed vehicle-road cooperative automatic driving system - Google Patents

Abstract

The invention discloses a partially-distributed vehicle-road cooperative automatic driving system, wherein a road network has various RSUs and TCUs/TCCs and covers various functions. Heterogeneous CAVH networks facilitate control and operation of vehicles and other road users at various levels of automation by implementing different levels of coordinated control among the CAVH system entities and providing road users with detailed customized information and time-sensitive control instructions and operation and maintenance services.

Description

Partially-distributed vehicle-road cooperative automatic driving system

Technical Field

The invention relates to the field of intelligent road side systems, in particular to a system for automatic driving of partially distributed vehicle roads in a coordinated manner.

Background

Autonomous vehicles (e.g., vehicles that can sense their environment and navigate without human manipulation or with reduced human manipulation) are under development. Currently, autodrive vehicles are undergoing experimental testing and are not widely used for commercial purposes. Existing autonomous automotive technologies require expensive and complex onboard systems, which severely hamper widespread implementation and use of autonomous vehicles.

Disclosure of Invention

The invention aims to provide a system for cooperating partially-distributed vehicle roads with automatic driving so as to solve the problems in the prior art.

In order to achieve the purpose, the invention provides the following scheme: the invention provides a system for coordinated automatic driving of partially laid vehicle roads, which comprises a vehicle road and automatic driving CAVH system, wherein the CAVH network is configured to provide a level of coordination control between system entities, provide customized information and control instructions of timeliness for road users, and provide operation and maintenance services, the CAVH system comprises a CAVH system of automatic and non-automatic vehicles and/or a CAVH system comprising roads and partial roads, and the CAVH network comprises partially laid parts and/or non-laid parts and fully laid parts according to the laying range; the part of the partial layout comprises a system part coverage area road and/or a layout with partial CAVH system functional components.

Preferably, the CAVH system comprises an intelligent roadside IRIS system, and the intelligent roadside IRIS system comprises road side unit RSU networks of different levels, a traffic control unit TCU and a traffic control center TCC network, and is used for providing various levels of coordination control among system entities, providing detailed customized information and timeliness control instructions for each road user, and providing operation and maintenance services; the RSU network includes a communication function, an environment sensing function, a traffic behavior prediction function, or a vehicle control function.

Preferably, the CAVH system is configured to provide any combination of four of the perception functions, traffic behaviour prediction and management functions, planning and decision functions and vehicle control functions, including one, or several, or all of the functions.

Preferably, when the system is configured to sense the traffic environment of a partially deployed RSU area, the data used is data from the partially deployed RSU and data from other system components transmitted using the cloud and traffic infrastructure;

when the system is configured to sense and transmit traffic environment data for an area, the traffic environment data includes vehicles, pedestrians, road geometry, road design information, road pavement conditions, traffic control infrastructure, traffic control devices, and/or animals.

Preferably, the CAVH system further comprises one or more on board units OBUs and a vehicle interface, a traffic operation centre TOC and/or a cloud platform configured to provide information and computing services for managing mixed traffic containing vehicles at an automation level, non-automated vehicles and other road users.

Preferably, the CAVH system further comprises a traffic behavior prediction and management function configured to predict vehicle trajectories for human driving of individuals, vehicle rows and/or hybrid row trajectories, vehicle routing, traffic flow on traffic segments, pedestrian behavior, general traffic environment, vehicle traffic composition, and/or vehicle and infrastructure communication connections based on information collected and or communicated by partially deployed RSUs, vehicle-to-vehicle communications, and/or clouds;

preferably, the CAVH system further comprises a planning and decision function configured to plan and/or decide a trajectory of the vehicle and/or row, a routing of the vehicle and/or row, a shift limit, a ramp control, a vehicle usage on-ramp and/or off-ramp, and/or traffic signal timing based on information collected and/or transmitted by the partially deployed RSUs.

Preferably, the CAVH system further comprises the fully deployed traffic network, partially deployed traffic network, and sub-networks comprising fully deployed, partially deployed and/or non-deployed, the non-deployed portions communicating with other components of the system.

Preferably, the CAVH system further comprises a system configured to provide vehicle control functionality configured to provide control instructions to address road infrastructure, people, vehicles and/or animals and moving obstacles; the vehicle control function comprises a coordinated control strategy, wherein the coordinated control strategy comprises a full control strategy, a partial control strategy and/or a non-control strategy; the non-control strategy includes communication of information between components of the system.

Preferably, the CAVH system further comprises a safety infrastructure and software comprising proactive methods based on event prediction and risk index estimation for use before a traffic accident occurs; an active method based on rapid event detection for identifying an impending event and deploying before a hazard occurs; and/or passive methods to mitigate hazards and losses after an accident.

The invention discloses the following technical effects: the invention provides various levels of coordination control among CAVH system entities, provides detailed customized information and timeliness control instructions for each road user, and provides operation and maintenance service, thereby improving the resource efficiency.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed to be used in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.

Fig. 1 is a schematic diagram of an embodiment of the present invention showing a CAVH system including components of the CAVH system and a road including key points, wherein 101: a traffic control center/traffic operation center (TCC/TOC), Traffic Control Units (TCUs)102 collect data, Road Side Units (RSUs) 103, stop sign key points 104, traffic signal key points 105, traffic oscillation key points 106 and traffic capacity key points 107;

FIG. 2 is a block diagram of an embodiment of the present invention showing the technology related to information flow for vehicle coordinated control, wherein an RSU 201, TCC/TCU202, cloud or other source 203, and control module unit 204;

FIG. 3 is a flow chart of the present invention;

FIG. 4 is a block diagram illustrating the present invention for spatially and/or temporally synchronizing sensor data, wherein the sensor 401, the synchronization module 402, and the control module 403;

fig. 5 is a schematic diagram of an example of the invention at a traffic signal key point, where the vehicle and RSU 501, limited function RSU502, non-CAVH vehicle 503 identified as having critical motion, CAVH vehicle 504 identified as having critical motion, non-CAVH vehicle 505 identified as having non-critical motion, CAVH vehicle 506 identified as having non-critical motion, and signal controller 507;

FIG. 6 is a schematic diagram of an example of a key point of a stop sign according to the present invention, wherein communication (e.g., wireless communication) between the RSU and the vehicle 601, a limited function RSU 602, and a vehicle travel path 603;

fig. 7 is a schematic diagram of an example of the key points of the present invention in a roundabout, wherein communication (such as wireless communication) between a CAVH component and a internet vehicle 701, a internet vehicle track 702, a common vehicle track 703 and an RSU 704 are shown.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.

Referring to fig. 1-2, the present invention provides a system for cooperative automatic driving of partially laid vehicle roads, including a vehicle road and automatic driving CAVH system including a CAVH system of automatic and non-automatic vehicles and/or a CAVH system including a road and a part of a road, the CAVH network including a partially laid part and/or a non-laid part, and a fully laid part according to a layout range; the part of the layout comprises a part of the coverage of the road and/or the layout of the CAVH system components with partial functions.

The CAVH system comprises an intelligent RSU (road side IRIS) system, the intelligent RSU system comprises RSU networks with different levels, a Traffic Control Unit (TCU) and a Traffic Control Center (TCC) network, the CAVH network comprises RSU coverage areas and functions with different levels and/or TCU/TCC coverage areas and functions with different levels and is used for providing various levels of coordination control among system entities, providing detailed customization information and control instructions with timeliness for each road user, and providing operation and maintenance service; and wherein the CAVH network is configured to provide various levels of coordinated control among system entities, detailed customized information and time-sensitive control instructions for individual road users, and operation and maintenance services.

In a further preferred embodiment, the RSU is a "limited function RSU", an RSU that includes fewer components, sensors, and/or "full function" RSU modules. The present invention provides several types of limited function RSUs and several types of full function RSUs. Several levels of RSUs, e.g., from low to high, include fewer or more components, sensors, modules, and/or functions. For example, the RSU provides real-time vehicle environmental awareness and traffic behavior prediction, and sends instantaneous control commands for individual vehicles through the OBU; the RSU provides real-time vehicle environmental awareness and traffic behavior prediction, but does not send instantaneous control commands for individual vehicles through the OBU; the RSU does not provide real-time vehicle environmental awareness and traffic behavior prediction, but sends instantaneous control commands for individual vehicles through the OBU; the RSU provides real-time vehicle context awareness but does not provide traffic behavior prediction; RSUs do not provide real-time vehicle environmental awareness but provide traffic behavior predictions; the RSU provides real-time vehicle environmental awareness based on a limited number of sensors, modules, and/or functions described herein; the RSU provides real-time vehicle environmental awareness based on 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 sensors, modules, and/or functions described herein.

A fully functional RSU or an RSU with a higher level of functionality is placed at or near the key points to monitor and collect data from the key points and manage the vehicle at the key points; the limited function RSU is placed at a non-critical point, which can save resources, efficiently use power and communication bandwidth, and reduce installation cost of the CAVH system.

The RSU comprises one or more of: a sensing module configured to measure a characteristic of a driving environment; a communication module configured to communicate with a vehicle, a TCU, and a cloud; a data processing module configured to process, fuse and compute data from the perception and/or communication module; the interface module is used for carrying out communication between the data processing module and the communication module; and the self-adaptive power supply module is used for providing electric energy and regulating the electric energy according to the condition of a local power grid. The adaptive power module is configured to provide backup redundancy. The communication module communicates using a wired or wireless medium.

The perception module comprises one or both of a radar-based sensor and a vision-based sensor; the vision-based sensor and the radar-based sensor are configured to perceive driving environment and vehicle attribute data; the radar-based sensor is a laser radar, a microwave radar, an ultrasonic radar or a millimeter radar; the vision-based sensor is a camera, an infrared camera, a thermal camera or a color camera.

The perception module further comprises a satellite-based navigation system and/or an inertial navigation system; the satellite-based navigation system is configured to receive data from the satellite-based navigation system; the inertial navigation system is configured to provide vehicle position data. The satellite based navigation system is a Differential Global Positioning System (DGPS) or a beidou navigation satellite system (BDS) system or a GLONASS global navigation satellite system. The inertial navigation system includes an inertial reference unit.

The perception module further comprises a vehicle identification device. The vehicle identification device is configured to receive vehicle identification data from an RFID component, a bluetooth component, a Wi-Fi (IEEE 802.11) component, or a cellular network radio (e.g., a 4G or 5G cellular network radio).

The system also includes one or more on-board units (OBUs) and vehicle interfaces, a Traffic Operation Center (TOC), and/or a cloud platform configured to provide information and computing services. The system is configured to manage mixed traffic including vehicles of various levels of automation, non-autonomous vehicles, and other road users.

In a further refinement, the CAVH system is configured to provide perception functions, traffic behavior prediction and management functions, planning and decision functions, and vehicle control functions.

The system provides a partially deployed RSU that provides one or more, two or more, or three or more of the following functions: a communication function, an environment perception function, a traffic behavior prediction function, or a vehicle control function.

When the system is configured to perceive the traffic environment of the area including the partially deployed RSU, the data used is data from the partially deployed RSU and data from other system components transmitted using the cloud and traffic infrastructure. The system is configured to sense and transmit traffic environment data for an area, the traffic environment data including vehicles, pedestrians, road geometry, road design information, road pavement conditions, traffic control infrastructure, traffic control devices, and/or animals; the traffic control infrastructure comprises safety barriers and/or road markings; the traffic control device includes a traffic sign and/or a traffic signal.

The CAVH system also includes traffic behavior prediction and management functions. The traffic behavior prediction and management function is configured to predict vehicle trajectories for human driving of individuals, vehicle rows and/or hybrid row trajectories, vehicle routing, traffic flow on traffic segments, pedestrian behavior, general traffic environment, vehicle traffic composition, and/or vehicle and infrastructure communication connections based on information collected and/or communicated by partially deployed RSUs, vehicle-to-vehicle communications, and/or clouds; the general traffic environment includes data describing weather, traffic conditions, traffic hazards, time, and/or location. The system integrates real-time sensor data, interpolated data, and predicted traffic behavior to provide partial or full CAVH functionality.

In a further refinement, the CAVH system further comprises a planning and decision function configured to plan and/or decide the trajectory of the vehicle and/or row, the routing of the vehicle and/or row, the shift limits, the ramp control, the use of an entrance ramp and/or an exit ramp by the vehicle, and/or the traffic signal timing based on the collection and/or transmission of the partially deployed RSUs to the partially deployed RSUs.

The TCC/TCU processes information from the partially deployed RSUs, performs planning and decision functions to plan and/or determine vehicle and/or row trajectories, vehicle and/or row routing, shift limits, ramp control, vehicle usage on-ramps and/or off-ramps, and/or traffic signal timing, and transmits instructions to the TCU and/or vehicle.

In a further refinement, the CAVH system further comprises the fully deployed traffic network, partially deployed traffic network, and sub-networks comprising fully deployed, partially deployed, and/or non-deployed portions that communicate with (e.g., transmit and receive information to and from) other components of the system.

When the system is configured to manage traffic and provide vehicle instructions to vehicles in a traffic environment that includes mixed traffic and non-traffic elements, such as human-driven vehicles, autonomous vehicles, internet vehicles, pedestrian units, non-motorized vehicles, intelligent internet vehicles, and obstacles.

When the system is configured to provide vehicle control. The vehicle control function is configured to provide control instructions to address road infrastructure, people, vehicles and/or animals and moving obstacles; the road infrastructure is a traffic sign, an IRIS component, a traffic signal or a traffic control device; the person is a pedestrian or a vehicle user; the vehicle is an automatic driving vehicle, an internet vehicle, an intelligent internet vehicle, an artificial driving vehicle or a non-motor vehicle. The vehicle control function includes a coordinated control strategy including a full control strategy, a partial control strategy and/or a non-control strategy; the non-control strategy includes communication of information (e.g., passing information) between components of the system.

In a further refinement, the vehicle control function is configured to receive information describing a CAVH configuration and information of the sensor; the information describing the CAVH configuration comprises information describing the RSU position and/or the RSU function; the sensor information includes sensed static object information and/or sensed dynamic object information from the RSU, including real-time traffic information and/or accident or special event information. The information describing the CAVH configuration includes a control plane, vehicle control functions configured to receive information including decision maker instructions and/or recommendations from the RSU, TCC/TCU, and/or cloud.

In a further refinement, the CAVH system comprises one or more keypoints, the keypoints being static keypoints or dynamic keypoints. Key points are identified as areas or points of roads having a high historical frequency of collisions, traffic control signals, traffic control signs, traffic congestion, key road geometry (e.g., curves, ramps, blind spots), junction points, entrance and exit ramps, toll booths or rotary islands), traffic oscillations and/or real-time traffic events (e.g., sustained traffic accidents). The key points are equipped with one or more IRIS components to provide partial or full control of key points identified as areas or points of roads having high priority for traffic control and management.

The key points (e.g., road areas where vehicles from different directions may collide) have more sensor deployments (e.g., increasing the number of RSUs and/or RSUs). The location of the vehicle at the critical point of conflict may vary by time and/or location. Specifically, the location and time of the vehicle conflict is a function of vehicle motion, traffic signal control, and/or intersection design and intersection signal changes. Thus, these factors will determine the type and number of sensing devices (e.g., RSUs) installed at the signalized intersection.

In a further refinement, the vehicle control function provides macro control of traffic flow or density on a road segment or road network, including determining a vehicle path. The vehicle control function also provides vehicle bank mesoscopic control. The vehicle control functions also provide microscopic control of the single vehicle, including longitudinal control of the vehicle, including controlling vehicle follow-up and/or collision avoidance, and lateral control, including controlling vehicle merge, lane change, split, and/or turn. Providing traffic awareness and control at a microscopic level (e.g., for longitudinal motion (car-following, acceleration and deceleration, stopping and leaning) and lateral motion (lane-keeping, lane-changing)), at the mesoscopic level (e.g., providing traffic awareness and control for road corridors and road segments (e.g., special event early notification, event prediction, intersection merging and splitting, rank splitting and integration, shift limit prediction and reaction, piecewise travel time prediction, and/or piecewise traffic flow prediction)), and at a macro level (e.g., to provide traffic awareness and control for a road network (e.g., potential congestion prediction, potential event prediction, network traffic demand prediction, network state prediction, and/or network travel time predictions) key points may be identified by components operating at the micro, meso, and/or macro level.

The RSU system is deployed at a fixed location near the road infrastructure (e.g., near key points, near non-key points). The RSUs are deployed at key points, for example, on highway roadsides, ramps on highways, highway ramps, interchange flyovers, bridges, tunnels, toll booths or unmanned aerial vehicles at key points. The RSUs may also be deployed on mobile components, such as on Unmanned Aerial Vehicles (UAVs) at traffic congestion locations, at traffic accident sites, at highway construction sites, or in extreme weather places, or in strategic locations (e.g., dynamic key points). The RSUs are positioned according to road geometry, heavy vehicle dimensions, heavy vehicle dynamics, heavy vehicle density and/or heavy vehicle blind spots. The RSU may also be mounted on a spreader (e.g., an overhead assembly with highway signs or signals mounted) or using a single or double cantilever support.

A single RSU (e.g., a full function RSU or a limited function RSU) provides customized traffic information and control instructions to the vehicle and/or receives information provided by the vehicle; part of the limited function RSU is in information communication with the vehicle, but does not provide control instructions to the vehicle; the partially limited function RSU provides control instructions to the vehicle but does not communicate information with the vehicle.

In a further refinement, the CAVH system further comprises safety infrastructure and software to minimize and/or eliminate impact frequency and severity. The security infrastructure and software includes an active method based on event prediction and risk index estimation for use before a traffic accident occurs; an active method based on rapid event detection for identifying an impending event and deploying before a hazard occurs; and/or passive methods to mitigate hazards and losses after an accident.

The partially deployed CAVH system. The partially deployed CAVH system is provided with IRIS components comprising: IRIS components with different functions; IRIS components having different hardware and/or software configurations; a fully configured IRIS that provides communication functionality, context awareness functionality, traffic behavior prediction functionality, and vehicle control functionality.

The partially laid CAVH system is provided with RSUs comprising: a partially configured RSU providing communication functionality; a partially deployed RSU providing context awareness functionality; a partially deployed RSU providing a traffic behavior prediction function; a partially deployed RSU providing vehicle control functions; RSUs that provide two of the following functions: a communication function, an environment perception function, a traffic behavior prediction function and a vehicle control function; RSUs that provide three of the following functions: communication function, environmental perception function, traffic behavior prediction function and vehicle control function.

The partially deployed CAVH system includes a TCC/TCU configured to make decisions, globally optimize flow and/or control flow. In some embodiments, the system includes a TCC/TCU configured to do any one or two of the three tasks of decision making, global flow optimization, and flow control.

The TCC network may be configured to provide traffic operation optimization, data processing, and data archiving. The TCC network comprises a manual operation interface, and is a macroscopic TCC, a regional TCC or a corridor TCC based on a geographical region covered by the TCC network. The TCU network may also be configured to automatically provide real-time vehicle control and data processing based on pre-installed algorithms. The TCU network includes segmented TCUs and/or point TCUs based on the geographic area covered by the TCU network.

The TCC network further comprises: a macro TCC configured to process information from a region TCC and provide a control target for the region TCC; a region TCC configured to process information from the corridor TCC and provide a control target for the corridor TCC; a corridor TCC configured to process information from both the macro and segmented TCUs and provide control targets to segment the TCUs.

The TCU network comprises: a segmented TCU configured to process information from the hallway and/or point TOC and provide a control target to point to the TCU; a point TCU configured to process information from the segment TCU and the RSU and provide vehicle-based control instructions to the RSU.

The TCC network further includes one or more TCCs, including the following modules: a connection and data exchange module, a transmission and network module, a service management module, and an application module for providing management and control of TCC network. The connection and data exchange module configured to provide data connection and exchange between TCCs, the connection and data exchange module including software components that provide data correction, data format conversion, firewalls, encryption and decryption methods; the transport and network module configured to provide a communication method for data exchange between TCCs, the transport and network module including a software component providing access functions and data conversion between different transport networks within a cloud platform; the service management module is configured to provide data storage, data search, data analysis, information security, privacy protection and network management functions; the application module providing management and control of the TCC network is configured to manage coordinated control of vehicles and roads, system monitoring, emergency services, and human and device interactions.

The TCU network further includes one or more TCUs, including the following modules: the system comprises a sensor and control module, a transmission and network module, a service management module and an application module. The sensor and control module configured to provide sensing and control functions of RSU, radar, camera, RFID and/or V2I (vehicle-to-infrastructure) devices, including DSRC, GPS, 4G, 5G and/or wifi radio; the transmission and network module configured to provide a communication network function for data exchange between the autonomous vehicle and the RSU; the service management module is configured to provide data storage, data search, data analysis, information security, privacy protection and network management; the application module is configured to provide a management and control method of the RSU including local cooperative control of vehicles and roads, system monitoring, and emergency services. The service management module provides data analysis for the application module.

In a further refinement, the TOC includes an interactive interface that provides control over the TCC network and data exchange. The interactive interface comprises an information sharing interface and a vehicle control interface. The information sharing interface includes: an interface for sharing and retrieving traffic data, an interface for sharing and retrieving traffic events, an interface for sharing and retrieving passenger demand patterns from a shared mobile system, an interface for dynamically adjusting prices according to instructions given by said vehicle operation and control system, an interface for allowing special agencies (e.g. vehicle management offices or police) to delete, change and share information, and/or an interface for allowing special agencies (e.g. vehicle management offices or police) to identify key point locations on roads. The vehicle control interface includes: an interface that allows the vehicle operation and control system to assume vehicle control, an interface that allows a vehicle to form a bank with other vehicles, and/or an interface that allows a particular authority (e.g., a vehicle management office or police) to control a vehicle. The traffic data includes vehicle density, vehicle speed, and/or vehicle trajectory. Traffic data is provided by vehicle operation and control systems and/or other shared mobile systems. The traffic events include extreme conditions, major accidents, and/or natural disasters. The keypoints are identified as locations of traffic events. The interface allows the vehicle operating and control system to assume control of the vehicle in the event of a traffic event, extreme weather or road surface malfunction, when alerted by the vehicle operating and control system and/or other shared mobile systems. The interface allows the vehicle to form a row with other vehicles traveling in the same dedicated and/or same non-dedicated lane.

Further optimizing the scheme when the system is configured to synchronize data in time or space. The system is configured to synchronize the time stamps and alignment positions of data within and between the sensors, synchronize data from the computing and communication modules in time and space, and coordinate control commands sent to the vehicle through OBU communication.

The OBU comprises: the system comprises a communication module, a data collection module and a vehicle control module. The communication module is configured to communicate with the RSU or communicate with another OBU. The data collection module is configured to collect data from external vehicle sensors and internal vehicle sensors and monitor vehicle status and driver status. The vehicle control module configured to execute control instructions for a driving task; the driving task comprises vehicle following and/or lane change; control instructions are received from the RSU.

The OBU is configured to control a vehicle using data received from an RSU, the RSU receiving data comprising: vehicle control instructions, travel path and traffic information, and/or service information; the vehicle control instructions include longitudinal acceleration, lateral acceleration, and/or vehicle orientation; the driving path and the traffic information comprise traffic conditions, event positions, intersection positions, entrance positions and/or exit positions; the service data comprises the location of the gasoline stations and/or the location of points of interest.

The OBU is further configured to transmit data to an RSU, the data transmitted to the RSU comprising: driver input data, driver status data, vehicle status data, and/or cargo status data; driver input data includes a start of a trip, an end of a trip, a desired trip time, a service request, and/or a level of hazardous material; driver state data includes driver behavior, fatigue level, and/or driver distraction; the vehicle status data includes vehicle ID, vehicle type and/or data collected by the data collection module; cargo state data includes material type, material weight, material height and/or material size.

The OBU is further configured to collect data, including: vehicle engine status, vehicle speed, cargo status, surrounding objects detected by the vehicle, and/or driver status. The OBU may also be configured to assume control of the vehicle, for example in the event of a failure of the autonomous system, when a vehicle condition and/or traffic condition prevents the autonomous system from driving the vehicle, when the vehicle condition and/or traffic condition is a bad weather condition, a traffic event, a system failure and/or a communication failure.

In a further refinement, the present system also provides a method for managing traffic control using any of the systems of one or more aspects described herein. These methods include procedures performed by individual participants in the system (e.g., drivers, public or private segments, regional or national traffic coordinators, government agencies, etc.), as well as collective activities in which one or more participants work in coordination or independently of each other.

In a further preferred embodiment, the system also provides a traffic management control method and system (for example, mixed traffic) of vehicles running on the highway, and a method and system for collecting information (for example, through a CAVH system RSU sensor and/or through a vehicle sensor). Highway RSU technology is used to collect and sense information and data communicated in upper IRIS servers (e.g., TCU/TCC) within highway segments, as well as regional traffic signaling systems. Furthermore, the highway RSU comprises a sensing device and acquires data through it. For example, in some embodiments, the RSU sensing devices may capture road conditions and/or composition of the mixed traffic flow on the highway (e.g., number and type of vehicles, including distribution of vehicles, as well as autonomous, non-autonomous, congested, queued, etc. status). The techniques provide methods that include predicting and/or managing transportation behavior (e.g., predicting traffic patterns and vehicle trajectories), making policy instructions and decisions for traffic management and vehicle control of vehicles on highways, and selecting algorithmic models for prediction and decision making. In some embodiments, techniques are applied to predictions, decision evaluation, selection algorithms and/or models based on aggregated and/or aggregated information collected on the highway (e.g., historical data, real-time data provided by the CAVH system, including data provided by RSUs, data provided by vehicles, upper IRIS servers (e.g., TCU/TCC)), and provide traffic management and/or vehicle control instructions (e.g., optimized for traffic scenarios) for vehicles within a portion of the highway. In some embodiments, systems and methods include controlling and/or distributing information related to highways. The techniques for controlling and/or distributing information related to a highway include sending a control message (e.g., from a TCU/TCC) to a vehicle configured to follow automation commands (e.g., a vehicle including an OBU); other vehicles with V2I capability may receive relevant traffic information (e.g., real-time traffic information) and/or driving instructions for the highway portion. The method applies mesoscopic (e.g., queue control and organization) and microscopic level control (e.g., steering, braking and/or acceleration commands, and/or longitude and latitude parameters to follow) techniques for individual vehicles.

In a further refinement, the present invention also provides methods and systems for traffic management (e.g., mixed traffic) and vehicle control at a stop sign or yield sign intersection. The technology provides methods that include collecting information (e.g., via RSU sensors and/or via CAVH sensors such as vehicle sensors) from a stop sign or intersection lane-giving sign (e.g., via a stop sign or intersection lane-giving sign near the RSU).

In a further refinement, the present invention also provides a system configured to collect information (e.g., via RSU sensors and/or via CAVH sensors such as vehicle sensors) at a stop sign or yield sign intersection (e.g., via a stop sign or intersection yield sign near the RSU). In addition, the intersection RSU includes a sensing device and acquires data by the sensing device. The information gathering techniques are used to gather information and data from communications with intersections, with RSUs, with vehicles within range of an upper-level IRIS server (e.g., TCU/TCC) at stop signs or intersection yield signs, such as: data generated by the regional traffic signal system, data collected via stop signs or intersection passing signs near the RSU, data collected from vehicles using RSU sensors. In some embodiments, the techniques provide for traffic flow management including predicting and/or managing transportation behavior (e.g., predicting traffic patterns and vehicle trajectories), making decisions on traffic management and vehicle control strategies and instructions, and selecting algorithms and models for predicting and making decisions for use at intersections of stop signs or yield signs. In some embodiments, techniques for signalized intersection prediction and decision-making evaluate the collected aggregated and/or integrated information, select algorithms and/or models and provide traffic management and/or vehicle control instructions (e.g., optimized for traffic conditions) for vehicles within range of the stop-sign or yielding-sign intersection; the information includes historical data, real-time data provided by the CAVH system (e.g., data provided by RSU, data provided by vehicle, data provided by upper IRIS server (e.g., TCU/TCC)). In some embodiments, systems and methods include controlling and/or distributing information related to stop signs or passing sign intersections. Techniques for controlling and/or distributing information related to stop signs or passing sign intersections include sending control information (e.g., vehicles including OBUs) to vehicles configured to follow automated instructions. Vehicles with V2I capability may receive relevant traffic information and/or driving instructions. The method applies mesoscopic (e.g. vehicle movement and organization, queue control, coordinating traffic movement with pedestrian movement across the road at the intersection of a stop sign or yield sign) and microscopic level control for individual vehicles (e.g. steering, braking and/or acceleration commands, and/or longitude and latitude parameters to be followed).

In further optimization, the present invention also provides methods and systems for managing traffic and controlling vehicles (e.g., entering, exiting, and/or traveling within a roundabout) at a roundabout. For example, the technology provides methods and systems for managing hybrid traffic and controlling vehicles at a circular intersection. The technology provides a method of collecting information at a rotary island and corresponding system infrastructure (e.g., by a CAVH sensor (e.g., by an RSU sensor and/or by a vehicle sensor)). The signalized intersection information gathering and awareness technology includes a roundabout RSU (e.g., a plurality of roundabout RSUs) that gathers information and data about the roundabout, upper IRIS servers (e.g., TCU/TCC). ) Information and data communicated to the vehicle and sensing the area proximate the roundabout (e.g., via RSU sensors or onboard sensors). Therefore, the roundabout RSU includes a sensing device and acquires data by the sensing device. The technology provides methods that include predicting and/or managing traffic behavior (e.g., predicting traffic patterns and vehicle trajectories) at a roundabout, making decisions on traffic management and vehicle control strategies and instructions, and selecting algorithms and models. The technology provides methods that deploy prediction and/or management of traffic behavior (e.g., predicting traffic patterns and vehicle trajectories), decision making for traffic management and vehicle control strategies and instructions, and selection of algorithms and models at roundabouts. The rotary island prediction and decision technology evaluates collected (e.g., aggregated and/or integrated) information (e.g., historical data, real-time data provided by a CAVH system (e.g., data provided by RSUs, data provided by vehicles, data provided by an upper-level IRIS server (e.g., TCU/TCC)), selects algorithms and/or models, and provides traffic management and/or vehicle control instructions (e.g., optimized for traffic scenarios) for vehicles on the rotary island. Other vehicles with V2I capability receive relevant traffic information and/or driving instructions. In some embodiments, mesoscopic (e.g., queuing control and organization, coordination of roundabout traffic with traffic signals) and microscopic level control (e.g., steering, braking, and/or acceleration commands, and/or longitude and latitude parameters to be followed) of the vehicle is achieved.

In a further refinement, the present invention also provides a system and method for managing traffic and controlling vehicles on a roadway system. In particular, the technology provides systems, system components, and methods for managing traffic and controlling vehicles on various road types, for road systems that include a variety of different road types (e.g., for managing traffic and controlling vehicles moving between various road types). For example, embodiments of the technology relate to managing and controlling vehicles, a range of vehicles and traffic participants (e.g., autonomous vehicles, non-autonomous vehicles, pedestrians, load-carrying vehicles, rolling stock, bicycles, etc.), different road structures (e.g., intersections, curves, straight portions, uphill slopes, downhill slopes, roundabouts, etc.), different traffic control components (e.g., traffic signals, stop signs, special traffic lanes, etc.) on roads having a range of traffic volumes (e.g., high traffic volumes, low traffic volumes, medium traffic volumes, variable traffic volumes). For roads with and without keypoints. The techniques include providing different types of RSUs for different types of roads (e.g., including different types and/or different numbers of sensors). For example, in some embodiments, the road regions that constitute the key points include RSUs with higher levels of functionality (e.g., RSUs that provide traffic control and information services, RSUs that include more sensors, etc.), provide more monitoring, more data collection, more information provision, and more control over traffic; the road region including the keypoints includes an increased number of RSUs that are provided more coverage by the CAVH system; road regions that do not include key points include lower functioning RSUs and/or a reduced number of RSUs, e.g., for conserving resources and/or allocating resources to regions that constitute key points or regions that require more traffic management and vehicle control.

In a further optimization scheme, the invention also provides a method and a system for managing traffic and controlling vehicles in a specific scene. For example, the technology provides methods and systems for managing traffic (e.g., mixed traffic of vehicles with multiple different levels of automation, non-autonomous vehicles, and other road users) and controlling vehicles at signalized intersections; the technology provides a method that includes collecting information at a signalized intersection via a CAVH sensor (e.g., RSU sensor and/or vehicle sensor); the technology provides a system configured to collect information at signalized intersections via CAVH sensors (e.g., RSU sensors and/or vehicle sensors); technologies for information collection and sensing at signalized intersections include an intersection RSU, which collects information and data from communications with vehicles within the range of the intersection, upper IRIS servers (e.g., TCU/TCC), and regional traffic signaling systems. Further, the intersection RSU includes a sensing device, and data is acquired by the sensing device. The technology provides methods that include predicting and/or managing traffic behavior (e.g., predicting traffic patterns and vehicle trajectories), making decisions regarding traffic management and vehicle control strategies and instructions, and selecting algorithms and models for prediction and making decisions at signalized intersections. The technology provides a system configured to predict and/or manage traffic behavior (e.g., predict traffic patterns and vehicle trajectories), make decisions with respect to traffic management and vehicle control strategies and instructions, and select algorithms and models for prediction and decision-making at signalized intersections. The techniques for making predictions and decisions at the signalized intersection evaluate the collected (e.g., aggregated and/or integrated) information (e.g., historical data, real-time data provided by the CAVH system (e.g., data provided by RSUs, data provided by vehicles, data provided by upper-level IRIS servers (e.g., TCU/TCC)), select algorithms and/or models, and provide traffic management and/or vehicle control instructions (e.g., traffic scenario optimization) for vehicles within the range of the signalized intersection. The method includes controlling and/or distributing information related to the signalized intersection. The system is configured to control and/or distribute information related to a signalized intersection, and techniques for controlling and/or distributing information related to a signalized intersection include sending a control message to a vehicle configured to follow an automated command (e.g., a vehicle containing an OBU). Other vehicles with the V2I function receive relevant traffic information and/or driving instructions. The system implements both macro (e.g., row control and organization, coordinating traffic at signalized intersections) and micro-level control (e.g., steering, braking, and/or acceleration commands, and/or longitude and latitude parameters to follow).

As shown in FIG. 1, the present invention provides a CAVH system comprising a TCC/TOC 101, TCU 102 and RSU103 to provide control over critical points. For each keypoint, the RSU103 collects static and/or dynamic data from the environment and sends the data to the TCU 102. The TCU 102 aggregates the data and sends the data (and/or fused (e.g., integrated) data) to the TCC/TOC 101. Based on the collected data, the TCC/TOC 101 makes decisions at the macro control level and sends information and/or control instructions to the TCU 102. Upon receiving the control instructions, the TCU 102 generates mesoscopic control policies and sends them to the RSU 103. The RSU103 controls vehicles at different key points according to policy. For the stop sign key point 104, the RSU103 calculates a vehicle gap on the primary road, and vehicles on the secondary road can pass through the gap. For traffic signal key points 105, the RSU103 adjusts vehicle speed to maintain and/or control the capacity of the road. For the traffic oscillation key point 106, the RSU103 controls the speed of the vehicle bank to reduce traffic saturation. For the capacity critical point 107, the RSU103 plans the path for the vehicles on the secondary road again to maintain high traffic volume for the primary road.

As shown in FIG. 2, the present invention provides a vehicle including components configured to manage information flow to coordinate control of the vehicle. The RSU 201 provides the control module 204 with location information and functional requirements, as well as sensed static object information and sensed dynamic object information. For example, data from the sensors describe and/or identify moving objects (e.g., dynamic objects) in the environment and non-moving objects (e.g., static objects) in the environment. The TCC/TCU202 communicates real-time traffic information, accident and special event information, instructions and recommendations of decision makers, and control levels to the control module 204 to facilitate the process of control. The control module 204 also receives information from the cloud and other sources 203 for computing control policies and/or providing control instructions.

As shown in FIG. 3, the present invention provides a system including a component configured to identify keypoints in a road system. For example, embodiments provide systems that determine whether a location on a road meets static keypoint criteria (e.g., historical collision data, traffic signs, traffic signals, road configuration, etc.) based on information and/or sensor data for the location. If the location satisfies the condition of a static keypoint, the location is identified as a keypoint. If the location does not meet the criteria for a static keypoint, the system compares the location information and/or sensor data to determine if the location meets the criteria for a dynamic keypoint (traffic oscillation, real-time traffic event, etc.). If the location satisfies the condition of a dynamic keypoint, the location is identified as a keypoint. If the location does not satisfy the dynamic keypoint condition, the location will be identified as a non-keypoint.

As shown in FIG. 4, the present invention provides a system including components configured to synchronize sensor data. The synchronization module 402 receives sensor data from the sensors 401 and synchronizes the data in time and/or based on location (e.g., spatial synchronization). The synchronization data is provided to the control module 403 for controlling the vehicles in the system. In some embodiments, the sensor frequency facilitates timely synchronization of sensor data.

As shown in fig. 5, the present invention provides a system and method for managing traffic signals including intersections. In some embodiments, the system includes a limited function RSU502 with a left-hand phase enabled at the signal intersection. At each signal phase, there is a potential conflict point between vehicles passing through the intersection. For example, a straight-ahead vehicle turning left and oncoming will have a conflict point at this stage through the intersection (fig. 5, shaded track). In some embodiments, the limited function RSU502 coordinates with the signal controller 507 to pre-identify conflict points at the intersection. When a first vehicle 503 and a second vehicle 504 approach the intersection with critical movement, the RSU502 communicates with these vehicles (e.g., via wireless communication 501) and provides information and control instructions to the vehicles to safely and efficiently guide the vehicles through the intersection. For example, in some embodiments, the system sends the launch time to a non-CAVH vehicle (e.g., vehicle 503) approaching an intersection with critical motion and sends the control strategy to a CAVH vehicle (e.g., vehicle 504) approaching an intersection with critical motion. At the same time, the limited function RSU will not communicate with and/or provide instructions to vehicles having non-critical motion (e.g., vehicles 505 and 506) approaching the intersection to reserve resources for providing instructions to vehicles having critical motion at the intersection.

As shown in fig. 6, the present invention provides a system and method for managing traffic at an intersection including a stop sign (e.g., a 4-way stop sign intersection). In some embodiments, the system includes a limited function RSU 602 at a 4-way stop sign intersection. The vehicle trajectory 603 causes a conflict point at the stop sign intersection. The limited function RSU 602 identifies a conflict point in a stop sign intersection. The RSU then communicates with nearby vehicles (e.g., via wireless communication 601) and provides information and/or control instructions to the nearby vehicles to guide the vehicles through the stop marked intersection.

As shown in fig. 7, the present invention provides a system and method for managing traffic at a circular intersection. Vehicle trajectories (e.g., vehicles 702 and 703) that approach and leave the roundabout may cause a conflict point within the roundabout. One or more RSUs 704 are located near the conflict point of the roundabout. The RSU 704 identifies and senses the region near the conflict point. The RSU then sends information about the conflict area to nearby networked vehicles (e.g., via wireless communication 701) and assists those networked vehicles in passing through the roundabout.

Throughout the specification and claims, the following terms take the meanings explicitly associated herein, unless the context clearly dictates otherwise. The phrase "in one embodiment" as used herein does not necessarily refer to the same embodiment, although it may. Moreover, the phrase "in another embodiment" as used herein does not necessarily refer to a different embodiment, although it may. Thus, as described below, various embodiments of the invention may be readily combined without departing from the scope or spirit of the invention.

The term "support" as used herein refers to providing support for one or more components of a CAVH system and/or one or more other components that support a CAVH system. For example, information and/or data is exchanged between components and/or levels of a CAVH system, instructions is sent and/or received between components and/or levels of a CAVH system, and/or other interactions between components and/or levels of a CAVH system that provide functionality such as information exchange, data transfer, messaging, and/or alerts.

The term "fully deployed" as used herein refers to a CAVH system or a portion of a CAVH system, including all IRIS system components and all IRIS system functions (e.g., all awareness functions, traffic behavior prediction and management functions, planning and decision functions, and vehicle control functions).

The term "partially deployed" as used herein refers to a CAVH system or a portion of a CAVH system, including some IRIS system components and/or some IRIS system functionality (e.g., some, but not all, awareness functionality, transportation behavior prediction and management functionality, planning and decision functionality, and vehicle control functionality), rather than all IRIS system components and/or all IRIS system functionality.

The term "non-deployed" as used herein refers to a road system or a portion of a road system (e.g., a portion of a road system or a portion that interfaces with a fully deployed and/or partially deployed CAVH system or a portion of a CAVH system) that does not include IRIS system components nor (e.g., does not serve) IRIS system functions. In some embodiments, a "non-deployed" system provides communication and information exchange.

The term "full control" as used herein refers to a control function or control strategy of a CAVH system in which all vehicles have autonomous driving capability and are configured to receive and execute control commands in a coordinated manner in which all infrastructure components (e.g., traffic signals, variable speed limits, etc.) are configured to control in a coordinated manner when necessary.

The term "partial control" as used herein refers to a control function or control strategy of a CAVH system in which all or part of the vehicles are configured to receive and execute control commands in a non-cooperative and/or cooperative manner; and/or wherein all or a portion of the infrastructure components are configured to be controlled in a non-cooperative and/or cooperative manner.

The term "uncontrolled" as used herein refers to a control function or control strategy of a CAVH system in which no vehicle is configured to be controlled, and in which no infrastructure component is configured to be controlled. In some embodiments, the non-control policies include communication and information exchange.

As used herein, the term "IRIS system components" is a generic term for one or more of OBU, RSU, TCC, TCU, TCC/TCU, TOC, and/or CAVH cloud components.

As used herein, the term "keypoint" refers to a point or area on a road that is identified as suitable for the location of a partially implemented vehicle-road cooperative driving system or a fully implemented vehicle-road cooperative driving system. In some embodiments, the keypoints are classified as "static keypoints", and in other embodiments, the keypoints are classified as "dynamic keypoints". As used herein, "static keypoints" refer to points (e.g., areas or locations) on a road that are typically based on road and/or traffic conditions that are constant or vary very slowly (e.g., over a period of one day, one week, or one month) or simply planned reconstruction infrastructure. As used herein, a "dynamic keypoint" refers to a point (e.g., an area or a location) on a certain road whose identification is based on a change in road conditions over time (e.g., predictably or unpredictably) (e.g., a time scale of one hour, one day, one week, or one month that switches on road conditions). The determination of the key points is based on historical accident data, traffic signs, traffic signals, traffic volumes, and in addition the key points of road geometry are typically static key points. The key points of real-time traffic management or real-time traffic events are typically dynamic key points based on traffic oscillation key points.

Using, for example, historical accident data (e.g., top 20% (e.g., top 15-25% (e.g., top 15,16, …,22) to identify keypoints, 23,24, or 25%)) road systems where most common collision points are determined to be keypoints, traffic signs (e.g., where certain traffic signs (e.g., areas prone to accidents) are detected) are determined to be keypoints, traffic capacity (e.g., top 20% (e.g., top 15-25% (e.g., top 15,16, …,24, or 25%)) highest traffic capacity areas are determined to be keypoints), road geometry (e.g., roads with critical road geometry (e.g., curves, blind spots, hills, intersections (e.g., signalized intersections, stop sign intersections, passing sign intersections), roundabouts) are identified as keypoints), traffic turbulence (e.g., a point with significant traffic turbulence is identified as a key point), real-time traffic management (e.g., a point with potential traffic management is identified as a key point), and/or real-time traffic accidents (e.g., a point with a traffic accident (e.g., an accident, a collision, congestion, construction or maintenance, a weather-related event, etc.) or vehicle failure is identified as a key point).

As used herein, the term "data synchronization" refers to identifying data from one or more sensors that are collected at the same time, substantially the same time, and/or effectively at the same time ("synchronized in time"), or at the same location. Substantially the same location, and/or substantially the same location ("synchronized in space")

As used herein, the term "human-driven vehicle" refers to a vehicle controlled by a human.

As used herein, the term "autonomous vehicle" or "AV" refers to an autonomous vehicle, for example, at any level of automation (e.g., as defined by SAE international standard J3016 (2014)).

As used herein, the term "networked vehicle" or "CV" refers to vehicles connected by a communication network, for example, any communication level configuration (e.g., V2V, V2I, or I2V).

As used herein, the term "walking unit" refers to any movable living being, such as a human or animal.

As used herein, the term "non-motorized vehicle" refers to a bio-propelled vehicle such as a bicycle, tricycle, scooter, carriage, cart, rickshaw, skateboard, or the like.

As used herein, the term "smart internet vehicle" or "CAV" refers to any vehicle having a level of automation (e.g., as defined by SAE international standard J3016 (2014)) and communications (e.g., V2V, V2I, or I2V).

In the description of the present invention, it is to be understood that the terms "longitudinal", "lateral", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, are merely for convenience of description of the present invention, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.

The above-described embodiments are merely illustrative of the preferred embodiments of the present invention, and do not limit the scope of the present invention, and various modifications and improvements of the technical solutions of the present invention can be made by those skilled in the art without departing from the spirit of the present invention, and the technical solutions of the present invention are within the scope of the present invention defined by the claims.

Claims (1)

1. The partially deployed vehicle road cooperative automatic driving system is characterized by comprising a vehicle road and automatic driving CAVH system, wherein a CAVH network is configured to provide a level of coordinated control between system entities, provide customized information and control instructions of timeliness for road users, and provide operation and maintenance services, the CAVH system comprises a CAVH system of automatic and non-automatic vehicles and/or a CAVH system comprising roads and partial roads, and the CAVH network comprises partially deployed parts and/or non-deployed parts and fully deployed parts according to the deployment range; the part of the partial layout comprises a part of coverage road and/or the layout of CAVH system components with partial functions; the CAVH system comprises an intelligent roadside IRIS system, the intelligent roadside IRIS system comprises road side unit RSU networks with different grades, a traffic control unit TCU and a traffic control center TCC network, and is used for providing various levels of coordination control among system entities, providing detailed customized information and timeliness control instructions for each road user, and providing operation and maintenance service; the RSU network comprises a communication function, an environment perception function, a traffic behavior prediction function or a vehicle control function; the CAVH system is configured to provide any combination of four of a perception function, a traffic behavior prediction and management function, a planning and decision function, and a vehicle control function, including one, or several, or all of the functions; when the system is configured to sense the traffic environment of a partially deployed RSU area, the data used is data from the partially deployed RSU and data from other system components transmitted using the cloud and traffic infrastructure; when the system is configured to sense and transmit traffic environment data for an area, the traffic environment data including vehicles, pedestrians, road geometry, road design information, road pavement conditions, traffic control infrastructure, traffic control devices, and/or animals; the CAVH system further comprises one or more on-board units (OBUs) and a vehicle interface, a Traffic Operation Center (TOC) and/or a cloud platform configured to provide information and computing services for managing mixed traffic containing vehicles with an automation level, non-automatic vehicles and other road users;

the CAVH system further comprises a traffic behavior prediction and management function configured to predict individual human-driven vehicle trajectories, vehicle rows and/or hybrid row trajectories, vehicle routing, traffic flow on traffic segments, pedestrian behavior, general traffic environment, vehicle traffic composition, and/or vehicle and infrastructure communication connections based on information collected and or communicated by partially deployed RSUs, vehicle-to-vehicle communications, and/or clouds;

the CAVH system further comprises a planning and decision function configured to plan and/or decide a trajectory of a vehicle and/or a bank, a routing of a vehicle and/or a bank, a shift limit, a ramp control, a vehicle using an entrance ramp and/or an exit ramp, and/or traffic signal timing based on information collected and/or transmitted by the partially deployed RSUs;

the CAVH system also comprises the fully-distributed traffic network, a partially-distributed traffic network and a fully-distributed, partially-distributed and/or non-distributed sub-network, wherein the non-distributed part is communicated with other components of the system;

the CAVH system further comprises a system configured to provide vehicle control functions configured to provide control instructions to address road infrastructure, people, vehicles and/or animals and moving obstacles; the vehicle control function comprises a coordinated control strategy, wherein the coordinated control strategy comprises a full control strategy, a partial control strategy and/or a non-control strategy; the non-control strategy includes communication of information between components of the system;

the CAVH system further comprises a safety infrastructure and software including proactive methods based on event prediction and risk index estimation for use before a traffic accident occurs; an active method based on rapid event detection for identifying an impending event and deploying before a hazard occurs; and/or passive methods to mitigate hazards and losses after an accident.

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