System and method for assigning driving intelligence between vehicle and highway

Abstract

To provide a system and a method for assigning, allocating, and distributing certain functions and intelligence for facilitating the operation and control of vehicles by a connected automated vehicle highway (CAVH) system, improving the general safety of an overall transportation system, and ensuring the efficiency, intelligence, reliability, and resilience of the CAVH system, and also provide a method for defining CAVH system intelligence and levels thereof based on two dimensions, which are vehicle intelligence and infrastructure intelligence.SOLUTION: A connected automated vehicle highway (CAVH) system includes components for sensing, communicating, and controlling. The components assign, allocate, and distribute functions and intelligence that facilitate vehicle operation and control.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 62 / 669,215, filed May 9, 2018, the entire contents of which are incorporated herein by reference.

[0002] The present invention relates to a system and method for allocating, arranging, and distributing specific functions and intelligence for a Connected Automated Vehicle Highway (CAVH) system to facilitate vehicle operation and control, improve general safety of the entire transportation system, and ensure the efficiency, intelligence, reliability, and resilience of the CAVH system. The present invention also provides a method for defining CAVH system intelligence and its level based on two dimensions: vehicle intelligence and infrastructure intelligence.

Background Art

[0003] Automated vehicles that can sense the environment, detect obstacles, and drive without human labor are in the development stage. Currently, automated vehicles are undergoing field tests but have not reached widespread commercialization. Existing approaches to automated vehicles require expensive and complex in-vehicle systems and multiple sensing systems and are highly dependent on vehicle sensors and controls, presenting significant challenges for their implementation.

[0004] Alternative systems and methods for addressing these problems are described in U.S. Patent Application No. 15 / 628,331, filed Jun. 20, 2017, U.S. Provisional Patent Application No. 62 / 626,862, filed Feb. 6, 2018, U.S. Provisional Patent Application No. 62 / 627,005, filed Feb. 6, 2018, and U.S. Provisional Patent No. 62 / 655,651, filed Apr. 10, 2018, the entire disclosures of which are incorporated herein by reference (hereinafter referred to as the CAVH system).

[0005] The invention described in this specification provides a system for various combinations of intelligent road infrastructure systems (IRIS) and vehicle automation, and an intelligence allocation method to achieve the performance of transportation and vehicle systems, and facilitates the operation and control of vehicles for the optimal and reliable operation of a connected and automated vehicle highway (CAVH) system. The following description explains a general CAVH system and an intelligence allocation method for achieving specific system performance, and shows a detailed example of a method for this integrated vehicle and transportation system.

Summary of the Invention

[0006] The present invention relates to a system and method for allocating, arranging, and distributing specific functions and intelligence for a connected and automated vehicle highway (CAVH) system, facilitating the operation and control of vehicles, improving the general safety of the entire transportation system, and ensuring the efficiency, intelligence, reliability, and resilience of the CAVH system. The present invention also provides a method for defining CAVH system intelligence and its level based on two dimensions: vehicle intelligence and infrastructure intelligence.

[0007] For example, in this specification, in some embodiments, a connected and automated vehicle highway (CAVH) system is provided that includes sensing, communication, and control components connected via segments and nodes that manage the entire transportation system. In some embodiments, the vehicles managed within the CAVH system include CAVH vehicles and non-CAVH vehicles. In some embodiments, CAVH vehicles and non-CAVH vehicles include manual vehicles, automated vehicles, and connected vehicles.

[0008] In some embodiments, the segments and nodes have overlapping sensing and control regions with adjacent segments and nodes to transfer CAVH vehicles between adjacent segments and nodes.

[0009] In some embodiments, the CAVH system includes the following four control levels. a) Vehicle b) Road Side Unit (RSU) c) Traffic Control Unit (TCU) d) Traffic Control Center (TCC)

[0010] In some embodiments, to implement the on-road coordinate command from the RSU, the vehicle control level includes a vehicle equipped with an in-vehicle system or application that operates the vehicle dynamic system.

[0011] In some embodiments, the RUS level is related to segments or nodes managed by an RSU that plays a role in vehicle sensing and control. In some embodiments, sensing including information from LiDAR and / or radar, or computer vision deployed to fully capture information within a segment or node, or other related systems are sensed or used. In some embodiments, the RSU manages collision avoidance, route specification execution, lane change adjustment, and high-resolution guidance commands related to on-road coordinates in response to sensing, and the vehicle executes autonomous driving.

[0012] In some embodiments, the TCU level is related to multiple RSUs managed by the TCU. In some embodiments, the TCU is responsible for updating the dynamic map of moving objects and the control adjusted between RSUs for continuous autonomous driving. In some embodiments, multiple TCUs are connected via the TCC to cover a region or sub-network.

[0013] In some embodiments, the TCC level is responsible for managing an overall routing plan and updating a dynamic map of congestion, incidents, bad weather, and events affecting the region, including high-performance computing and cloud services. In some embodiments, the TCC level is further responsible for managing connections with other application services, which include, but are not limited to, payment and transaction systems, regional traffic management centers (TMCs), third-party applications (e.g., government applications, private enterprise applications, etc.). In some embodiments, multiple TCCs are used to facilitate CAVH operation between regions within a metropolitan area or across a metropolitan area.

[0014] For example, as described herein, in some embodiments, a Connected Automated Vehicle Highway (CAVH) system is provided that includes sensing, communication, and control components that assign, arrange, and distribute functions and intelligence to facilitate vehicle operation and control. In some embodiments, the components improve the safety of the transportation system that includes the components. In some embodiments, the components improve the efficiency, intelligence, reliability, and / or resilience of the CAVH system. In some embodiments, the functions assigned include sensing. In some embodiments, the functions assigned include predicting and managing transportation actions. In some embodiments, the functions assigned include planning and decision-making. In some embodiments, the functions assigned include vehicle control.

[0015] In some embodiments, a CAVH system that includes sensing, communication, and control components that assign, arrange, and distribute functions and intelligence to facilitate vehicle operation and control includes one or more of the following subsystems. a) An Intelligent Road Infrastructure System (IRIS) that includes one or more of a Road Side Unit (RSU), a network, a Traffic Control Unit (TCU), and a Traffic Control Center (TCC) b) Vehicle equipped with on-vehicle unit (OBU)

[0016] In some embodiments, the CAVH system is supported by one or more of the following. a) Real-time communication via wired and wireless media b) Power network c) Cyber safety and security system

[0017] In some embodiments, the assignment of functions and intelligence to facilitate vehicle operation and control is based on the following levels. a) Vehicle level b) Infrastructure level c) System level

[0018] In some embodiments, the system is configured to manage functions and intelligence in any one of various combinations of automation levels at each level. In some embodiments, the system is configured to evaluate a particular level of automation present at any level and select an appropriate assignment of functions and intelligence to optimally manage infrastructure and vehicle operation under such conditions.

[0019] In some embodiments, the vehicle level includes the following automation levels. a) A0: No automation function b) A1: Basic functions to assist the human driver in controlling the vehicle c) A2: Assist the human driver in controlling the vehicle for simple tasks and have basic sensing functions d) A3: Functions for sensing the environment in detail and in real time and capable of handling relatively complex driving tasks e) A4: Functions that enable the vehicle to drive independently under limited conditions and sometimes with the backup of a human driver, and f) A5: Functions that enable the vehicle to drive independently under all conditions without the backup of a human driver

[0020] In some embodiments, the infrastructure level includes the following automation levels. a) I0: No function b) I1: Information collection and traffic management. The infrastructure provides basic sensing functions from the perspective of collecting aggregated traffic data and basic planning and decision-making, and supports simple traffic management with low spatial and temporal resolutions. c) I2: Vehicle guidance for I2X and driving assistance. In addition to the functions provided by I1, the infrastructure realizes limited sensing functions for detecting the paving condition and the dynamic detection of vehicles, such as vertical / horizontal position / speed / acceleration, for some parts of the traffic in seconds or minutes. The infrastructure also provides traffic information and proposals and instructions for vehicle control to the vehicle via I2X communication. d) I3: Automation of dedicated lanes. The infrastructure provides the dynamics of surrounding vehicles and other objects to individual vehicles in milliseconds and supports fully automated driving in CAVH-compatible vehicle dedicated lanes. The infrastructure's traffic operation prediction ability is limited. e) I4: Scenario-specific automation. When there is mixed traffic of CAVH-compatible vehicles and CAVH-incompatible vehicles, the infrastructure provides detailed driving instructions to the vehicle to achieve fully automated driving in specific scenarios / areas, such as pre-defined geopolitical areas. Essential vehicle-based automation capabilities, such as emergency braking, are on standby as a backup system in case of infrastructure failure. f) I5: Infrastructure full automation. The infrastructure provides complete control and management to individual vehicles in all scenarios and optimizes the entire network where the infrastructure is deployed. Vehicle automation functions are not required as a backup, and fully active safety functions are available.

[0021] In some embodiments, the system level includes the following automation levels. a) S0: No function b) S1: The system maintains simple functions for individual vehicles, such as cruise control and passive safety functions. The system detects the speed and distance of the vehicle.

[0022] c) S2: The system operates with individual intelligence and detects the functional state of the vehicle, the vehicle's acceleration, traffic signs, and signals. Each individual vehicle makes decisions based on its own information and has complex functions of partial driving automation, such as the vehicle's adaptive cruise control, lane keeping, lane changing, and automatic parking assistance.

[0023] d) S3: The system integrates information among vehicle groups and operates with ad hoc intelligence with predictive capabilities. The system has intelligence for decision-making of vehicle groups and can handle complex conditional automated driving tasks such as cooperative cruise control, platooning of vehicles, passing through intersections by vehicles, merging, and diverging.

[0024] e) S4: The system optimally integrates driving behavior within a partial network. The system detects and communicates detailed information within the partial network, makes decisions based on both vehicle information and transportation information within the network, handles advanced driving automation tasks such as passing through signal corridors, and provides an optimal trajectory within a small-scale transportation network.

[0025] f) S5: Vehicle automation and system traffic automation. The system operates optimally within the entire transportation network. The system detects and transmits detailed information within a large-scale transportation network, makes decisions based on all information available within the network, handles complete driving automation tasks including individual vehicle tasks and transportation tasks, and coordinates all vehicles.

[0026] In some embodiments, the system level depends on the following two levels, namely 1) the vehicle and 2) the infrastructure, and is represented by the following equation (S = system automation, V = vehicle intelligence, I = infrastructure intelligence). S = f(V, I)

[0027] In some embodiments, the equation is a non-linear function, and system automation level 2 includes, for example, the following.

[0028] a) Sensing: The vehicle subsystem is dominant. The infrastructure subsystem helps to complete the driving environment.

[0029] b) Prediction and management of driving actions: The vehicle subsystem is dominant. The infrastructure subsystem mainly cooperates with the vehicle subsystem.

[0030] c) Planning and decision-making: The vehicle subsystem plays a major role, and the infrastructure subsystem optimizes the system from a global perspective.

[0031] d) Vehicle control: The vehicle subsystem is dominant. The infrastructure subsystem supports vehicle control commands.

[0032] The system may be implemented in various different ways according to the automation levels existing at various levels. For example, in some embodiments (Method 1), the control components assign, arrange, and distribute intelligence so that functions are assigned to the vehicle, the autonomous driving vehicle and the infrastructure do not have a communication function and function independently, and the infrastructure does not provide improvement to the vehicle intelligence, which is applicable to Scenario S1.

[0033] In another embodiment (Method 2), the control components assign, arrange, and distribute intelligence such that most of the functions are assigned to vehicle subsystems and the vehicle plays a dominant role. The roadside device subsystem plays a supplementary role only for simple tasks and assists the vehicle in maintaining a specific speed and providing collision warnings. If there is a conflict in control decisions, the vehicle makes the decision. This is applicable to Scenario S1 or S2.

[0034] In another embodiment (Method 3), the control components assign, arrange, and distribute intelligence such that the functions can be flexibly assigned to either the vehicle or the infrastructure subsystem, and either the infrastructure or the vehicle subsystem plays a major role in sensing and decision-making. Here, the roadside device subsystem proposes control for the following aspects for the vehicle to make decisions based on the local environment and operate.

[0035] a) Following strategy b) Lane keeping strategy c) Lane changing strategy d) Merging and diverging strategies e) Intersection passing

[0036] If there is a conflict in control decisions, the vehicle makes the control decision independently or makes the control decision using information from the infrastructure. This is applicable to Scenario S2 or S3.

[0037] In another embodiment (Method 4), the control components assign, arrange, and distribute intelligence such that most of the functions are distributed to the roadside device subsystem and the infrastructure plays a dominant role in control decisions. The vehicle subsystem further has basic functions such as collision avoidance, and the vehicle follows all the information provided by the infrastructure. If there is a conflict in control decisions, the vehicle takes the decision by the infrastructure as the control decision. This is applicable to Scenario S3 or S4.

[0038] In other embodiments (Method 5), the control components assign, arrange, and distribute intelligence such that all functions are dependent on the roadside subsystem and the vehicle has the ability to communicate and follow commands. Here, all vehicles are controlled by the infrastructure system, decision-making is performed by the roadside device network, and communication with the system is through the roadside device network. This is applicable to the S4 scenario or the S5 scenario.

[0039] In some embodiments, the control components manage the mixed traffic flow of vehicles with different levels of connectivity and automation. In some embodiments, the control components collect vehicle-generated data such as vehicle movement and status, transmit the collected data to the RSU, and receive input data from the IRIS. Here, the OBU facilitates vehicle control based on the input data from the IRIS. Here, in case of a failure in the vehicle control system, the OBU can take over in a short time and safely stop the vehicle.

[0040] In some embodiments, the IRIS facilitates the vehicle operation and control of the CAVH system. The IRIS provides customized detailed information and time-sensitive control commands for individual vehicles to perform driving tasks such as vehicle following, lane changing, and route guidance. It provides operation and maintenance services for vehicles on both highways and urban arterial roads.

[0041] In some embodiments, the IRIS is built and managed as an open platform. As shown below, its individual subsystems are owned and / or operated by various entities and are physically and / or logically shared among various CAVH systems including one or more or all of the following physical subsystems.

[0042] a. Roadside Unit (RSU) network, whose functions include functions such as sensing, communication, control (high-speed / simple), and calculation of the drivable range b. Traffic Control Unit (TCU) and Traffic Control Center (TCC) Network c. On-Board Unit (OBU) and Associated Vehicle Interfaces d. Traffic Operations Center, and e. Cloud-Based Platform for Information and Computing Services In some embodiments, the system implements one or more of the following functional categories.

[0043] i. Sensing ii. Prediction and Management of Travel Behavior iii. Planning and Decision Making iv. Vehicle Control

[0044] The system and method include the functions and components described in U.S. Patent Application No. 15 / 628,331, filed on June 20, 2017, U.S. Provisional Patent Application No. 62 / 626,862, filed on February 6, 2018, U.S. Provisional Patent Application No. 62 / 627,005, filed on February 6, 2018, and U.S. Provisional Patent Application No. 62 / 655,651, filed on April 10, 2018, and may be integrated with these functions and components, the content of which is hereby incorporated by reference in its entirety into this application.

[0045] Also provided herein is a method of using any of the systems described herein to manage one or more aspects of traffic control. This method includes processes initiated by individual participants in the system (e.g., drivers, public or private local, regional, or national traffic facilitators, government agencies, etc.) and collective activities of one or more participants working in coordination or independently with each other.

[0046] Some parts of this specification describe embodiments of the present invention from the perspective of algorithms and symbolic representations of operations on information. The descriptions and representations of these algorithms are commonly used by those skilled in the data processing arts and effectively convey the substance of their work to other skilled artisans. These operations are described functionally, computationally, or logically, but are understood to be implemented by a computer program or equivalent electrical circuitry, microcode, etc. Further, without loss of generality, it may sometimes be convenient to refer to the arrangement of these operations as modules. The operations described and the modules associated therewith may be embodied in software, firmware, hardware, or any combination thereof.

[0047] Certain steps, operations, or processes described herein may be performed or implemented by one or more hardware or software modules alone or in combination with other devices. In one embodiment, a software module is implemented by a computer program product comprising a computer-readable medium having computer program code thereon, the computer program code being executable by a computer processor to perform any or all of the described steps, operations, or processes.

[0048] Embodiments of the present invention may also relate to an apparatus for performing the operations of this specification. The apparatus may be specially constructed for the required purposes and / or may include a general-purpose computing device selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a non-transitory, tangible computer-readable storage medium coupled to a computer system bus or in any type of medium suitable for storing electronic instructions. Further, any computing system referred to herein may include a single processor or may be an architecture that utilizes multiple processor designs to enhance computing capabilities.

[0049] Embodiments of the present invention may also relate to products generated by the computing processes described herein. Such products may include information resulting from the computing process, which may be stored on a non-transitory and tangible computer-readable storage medium and may include any embodiment of a computer program product or other data combination described herein.

Brief Description of the Drawings

[0050]

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Modes for Carrying Out the Invention

[0051] Examples of this technology are described below. It should be understood that these are exemplary embodiments and that the present invention is not limited to these specific examples.

[0052] FIG. 1 provides a graph showing that the automation level of the system is a combination of the vehicle automation level and the infrastructure automation level. The level of the overall system is not limited to the direct combination of the degrees of the two subsystems. The functions of the overall system are distributed to the vehicle subsystem and the infrastructure subsystem.

[0053] This system realizes the following function categories. a) Sensing b) Travel behavior prediction and management c) Planning and decision-making d) Vehicle control

[0054] FIG. 2 shows a two-dimensional graph and a three-dimensional graph representing the relationship between the system automation level and the infrastructure automation level with respect to the vehicle automation level. Table 1 below represents, for further explanation, the system levels for each combination of vehicle and infrastructure automation levels by the numbers in each row and column.

[0055] Table 1: Example of system intelligence level determination JPEG2025106597000002.jpg45170

[0056] FIG. 3 shows an example of a vehicle subsystem having the following components. 301 - Vehicle 302 - OBU: An on-vehicle unit that controls the vehicle, collects and transmits data 303 - Communication module: Transfers data between the RSU and the OBU 304 - Data collection module: Collects data on the dynamic and static states of the vehicle generated by humans 305 - Vehicle control module: Executes control commands from the RSU. In case the vehicle control system is damaged, it can take over the control and safely stop the vehicle. 306 - RSU: A roadside unit that collects and transmits data

[0057] As shown in FIG. 3, the vehicle subsystem includes all vehicles 301 within the CAVH system. The OBU 302 includes, for each vehicle, a communication module 303, a data collection module 304, and a vehicle control module 305. The data collection module collects data from the vehicle and input data from a human driver, and transmits it to the RSU 306 via the communication module. Also, the OBU receives data from the RSU via the communication module. The vehicle control module assists with vehicle control based on data from the RSU.

[0058] FIG. 1 shows an embodiment of an Intelligent Road Infrastructure System (IRIS) having the following components. 401 - Macroscopic TCC / TOC: The highest level TCC / TOC that manages the Regional TCC 402 - Regional TCC: A high level TCC that manages the Corridor TCC 403 - Corridor TCC: A mid - level TCC that manages the Segment TCU 404 - Segment TCU: A low - level TCU that manages the Point TCU 405 - Point TCU: The lowest level TCU that manages the RSU

[0059] FIG. 4 shows the structure of the IRIS embodiment. The Macroscopic TCC 401 may or may not cooperate with the external TOC 401, but manages a certain number of Regional TCCs 402 within its coverage area. Similarly, the Regional TCC manages a certain number of Corridor TCCs 403, the Corridor TCC manages a certain number of Segment TCUs 404, the Segment TCU manages a certain number of Point TCUs 405, and the Point TCU manages a certain number of RSUs 306. The RSU transmits customized traffic information, controls instructions to the vehicle 301, and receives information provided by the vehicle. Further, in the embodiment, IRIS is supported by cloud services.

[0060] The three approach embodiments include the following. 1. Approach of autonomous vehicles 2. Approaches for Connected and Autonomous Vehicles Using V2I and V2V Technologies 3. CAVH-IRIS, Infrastructure-Based Approach Using Sensing, Prediction, and Decision-Making from Road-Side Systems

[0061] Approach 1 has a history of several decades. To support this approach, there are examples of several methods, such as those described in U.S. Patent No. 9,120,485 (The autonomous vehicle is configured to follow a baseline trajectory. The vehicle's computer system receives a change to the trajectory and optimizes a new trajectory for the vehicle.), U.S. Patent No. 9,665,101 (The system determines a route from the current location to the destination for the vehicle), U.S. Patent No. 9,349,055 (When attempting to sense the environment, it is used by Google's autonomous vehicles to detect other vehicles), U.S. Publication No. 20170039435 (When sensing the environment, it is used by Google's autonomous vehicles to detect traffic signals), the content of which is hereby incorporated by reference in its entirety into this application. Products and their technologies developed by vehicle manufacturers and AI research groups have been implemented so far. However, from the perspective of global optimization, this approach lacks planning and decision-making. Although autonomous driving AI can replace human drivers, human drivers cannot achieve better performance regarding the transportation system. This approach also has insufficient sensing range and vehicle computing power and is not sufficient to cope with the complexity and limitations that will be faced in the future.

[0062] Figure 5 shows an example of an AV-only approach having components. 501 On-Vehicle Sensor 502 Pedestrians on the Road 503 - Road-Side Infrastructure

[0063] Figure 5 shows the operating method of the autonomous vehicle 301 in this approach. When the AV is on the road, it continuously senses the environment with a plurality of sensors 501. The environment includes other vehicles 301, pedestrians 502, road infrastructure 503, etc. around it. In this embodiment, the AV detects two pedestrians in front of it, three vehicles around it, and a stop sign at the intersection. The AV makes decisions based on the information obtained and operates appropriately and safely on the road.

[0064] Connected autonomous vehicle approach utilizing communication. This approach has been tried for several years. Some prototypes have already been developed. For example, U.S. Patent Application Publication No. 2012 / 0059574 (When the vehicle unit is within the wireless communication range, it transmits the vehicle speed to the roadside unit. The roadside unit transmits the vehicle speed to the traffic controller. The traffic controller receives vehicle speed data from a plurality of vehicles and determines a recommended speed for each vehicle.), U.S. Patent No. 7,425,903 (In this grid system, an automobile is equipped with a selection of a transmitter, a receiver, a computer, and sensors. Other adjacent vehicles also include devices for transmitting and receiving similar signals. When a sensor in the vehicle detects a change such as hard braking (rapid deceleration) or micro speed (blockage), the vehicle automatically transmits to any other receiver in the vicinity via a transmitter on the wireless communication channel.), and other prototypes described therein, the contents of which are hereby incorporated by reference in their entirety into this application. The system can exhibit relatively better performance than individual autonomous vehicles by using V2V and V2I communication technologies. However, without system-level intervention, the system cannot achieve overall system or global optimization. Also, there are limitations to the sensing, memory, and computing capabilities of this approach.

[0065] Figure 6 shows an example of a V2V and V2I-based approach that includes component 601: roadside infrastructure that facilitates communication. Figure 6 shows the functional method of the V2V and V2I-based approach. This approach has been used for several years. Several prototypes have been developed so far. By using V2V and V2I communication technologies, the system can exhibit relatively better performance than individual autonomous vehicles. Each vehicle 301 receives information detected by the surrounding infrastructure 601 and other vehicles 301. The information includes vehicles, passengers, traffic conditions, etc. With the provided information, the vehicle enhances its surrounding awareness and makes decisions. However, without system-level intervention, the system cannot achieve overall system or global optimization. Also, there are limitations to the sensing, memory, and computing capabilities of this approach.

[0066] Figure 7 shows an example of the CAVH-IRIS approach. This system has the ability to make optimal decisions at the system level, controls the operation of individual vehicles, and is beneficial for the overall transportation system. This system is composed of more powerful computing and memory capabilities, but may have limitations in communication. The embodiment of Figure 7 includes the following components. 701 - Roadside sensor 702 - High-level IRIS 703 - Cloud: Assisting with data storage and computation

[0067] Figure 7 is a demonstration of the CAVH-IRIS approach. The RSU 306 in Figure 7 senses the road, vehicles 301, and driving environment using roadside sensors 701. This information is transmitted to a higher-level IRIS 702. The system can use the data from the sensors to make optimal decisions at the system level, control individual vehicles, and is beneficial for the overall transportation system. The system communicates with the OBU 302 to control the vehicle. As shown in Figure 7, the system can be composed of more powerful computing and memory capabilities by communicating with the cloud 703.

[0068] Figure 8 shows an example of the allocation of intelligence at system intelligence level 2 and includes the following components. 801: On-vehicle ultrasonic sensor 802: On-vehicle camera 803: On-vehicle LiDAR 804: On-vehicle long-range radar 805: Detection area of on-vehicle RSU 806: Roadside unit 807: Communication between RSU and vehicle 808: Vehicle of CAVH system

[0069] Figure 8 shows an example of the combination of intelligence distributed between vehicles and infrastructure.

[0070] a) Sensing: The vehicle subsystem plays a central role. This means that the driving environment is mainly detected by sensors such as ultrasonic sensor 801, camera 802, LiDAR 803, and long-range radar 804 mounted on vehicle 808. On the other hand, the infrastructure subsystem 806 detects the traffic in coverage area 805, continues to communicate with vehicle subsystem 807, and transmits traffic information to complete the driving environment.

[0071] b) Travel behavior prediction and management: The vehicle subsystem plays a central role. The infrastructure subsystem mainly cooperates with the vehicle subsystem. This enables the prediction of events from a macroscopic level such as long-distance traffic congestion. c) Planning and decision-making: The vehicle subsystem is a major component. However, the infrastructure subsystem can propose system optimization from a global perspective.

[0072] d) Vehicle control: The vehicle subsystem is a major component. The infrastructure subsystem only provides simple control commands determined by the vehicle subsystem. When the control commands of the two subsystems conflict, the vehicle follows the instructions sent from the vehicle subsystem. The system reports and stores conflict events.

[0073] Figure 9 shows that in the above intelligence allocation method 2, the vehicle subsystem plays a central role. In this situation, the vehicle subsystem provides a safety range to control the vehicle, and the IRIS subsystem provides control commands from a global perspective. The instructions from IRIS must meet the safety range provided by the vehicle. When the instructions from IRIS do not meet the safety range, the vehicle follows the instructions sent from the vehicle subsystem. Records of conflicts are stored and reported.

Claims

1. A Connected Automated Vehicle Highway (CAVH) system including components for sensing, communication, and control, which assign, arrange, and distribute functions and intelligence for facilitating the operation and control of a vehicle.

2. The system according to claim 1, wherein the component improves the safety of a transportation system including the component.

3. The system according to claim 1, wherein the component improves the efficiency, intelligence, reliability, and resilience of the CAVH system.

4. The system according to claim 1, wherein the assigned function includes sensing.

5. The system according to claim 1, wherein the assigned function includes transportation behavior prediction and management.

6. The system according to claim 1, wherein the assigned function includes planning and decision-making.

7. The system according to claim 1, wherein the assigned function includes vehicle control.

8. The CAVH system according to claim 1, including the following subsystems. a) An Intelligent Road Infrastructure System (IRIS) including a Road Side Unit (RSU), a network, a Traffic Control Unit (TCU), and a Traffic Control Center (TCC), and b) Vehicles equipped with an On-Board Unit (OBU)

9. The system according to claim 8, wherein the CAVH system is supported by one or more of the following. a) Real-time communication via wired and wireless media b) A power network, and c) A cyber safety and security system

10. The assignment in the system according to claim 1 is performed based on the following levels. a) Vehicle level b) Infrastructure level, and c) System level

11. The vehicle level in the system according to claim 10 includes the following automation levels. a) A0: No automation function b) A1: Basic functions assisting vehicle control performed by a human driver c) A2: Assisting vehicle control performed by a human driver for simple tasks and having basic sensing functions d) A3: Having functions for sensing the environment in detail and in real time and being able to handle relatively complex driving tasks e) A4: Having a function that enables the vehicle to drive alone under limited conditions and sometimes with the assistance of a human driver, and f) A5: Having a function that enables the vehicle to drive alone under all conditions without the assistance of a human driver.

12. The system according to claim 10, wherein the level of the infrastructure includes the following automation levels. a) I0: No function b) I1: Information collection and traffic management. The infrastructure provides primitive sensing functions from the perspective of integrated traffic data collection and basic planning and decision-making, and supports simple traffic management with low spatial and temporal resolutions. c) I2: Vehicle guidance for I2X and driving assistance. In addition to the functions provided by I1, the infrastructure realizes limited sensing functions for detecting the paved state and vehicle movement, such as longitudinal / lateral position / speed / acceleration, for some traffic in seconds or minutes. The infrastructure also provides traffic information and proposals and instructions for vehicle control to the vehicle via I2X communication. d) I3: Automation of dedicated lanes. The infrastructure provides the dynamics of surrounding vehicles and other objects to individual vehicles in milliseconds and supports fully automated driving in dedicated lanes for CAVH-compatible vehicles. The infrastructure also has limited traffic operation prediction capabilities. e) I4: Scenario-specific automation. When there is mixed traffic of CAVH-compatible vehicles and CAVH-incompatible vehicles, the infrastructure provides detailed driving instructions to the vehicle to achieve fully automated driving in a certain scenario / area, such as a pre-defined geopolitical area. Essential vehicle-based automation capabilities, such as emergency braking, are on standby as a backup system in case of a failure in the infrastructure. f) I5: Infrastructure full automation where the infrastructure provides complete control and management for all scenarios to individual vehicles and optimizes the entire network where the infrastructure is deployed. Vehicle automation functions are not required as a backup, and fully active safety functions are available.

13. The system according to claim 10, wherein the level of the system includes the following automation levels. a) S0: No function b) S1: The system maintains simple functions for individual vehicles, such as cruise control and passive safety functions. The system detects the speed and distance of the vehicle. c) S2: The system operates with individual intelligence and detects the functional state of the vehicle, the vehicle's acceleration, traffic signs, and signals. Each individual vehicle makes decisions based on its own information and has complex functions of partial driving automation, such as the vehicle's adaptive cruise control, lane keeping, lane changing, and automatic parking assistance. d) S3: The system integrates information among vehicle groups and operates with ad-hoc intelligence with predictive capabilities. The system has decision-making intelligence for vehicle groups and can handle complex conditional automated driving tasks such as cooperative cruise control, vehicle platooning, vehicle passing intersections, merging, and diverging. e) S4: The system optimally integrates driving behaviors within a partial network. The system detects and transmits detailed information within the partial network, makes decisions based on both vehicle information and transport information within the network, processes advanced driving automation tasks such as passing through signal corridors, and provides optimal trajectories within a small-scale transport network. f) S5: Vehicle automation and system traffic automation. The system operates optimally within the entire transport network. The system detects and transmits detailed information within a large-scale transport network, makes decisions based on all information available within the network. The system processes complete driving automation tasks including individual vehicle tasks and transport tasks, and coordinates all vehicles.

14. The level of the system depends on the following two levels, namely, 1) the vehicle, 2) the infrastructure, and is represented by the following equation (S = system automation, V = vehicle intelligence, I = infrastructure intelligence), the system according to claim 13. S = f(V, I)

15. The equation is a non-linear function, and the system automation level 2 includes the following, the system according to claim 14. a) Sensing: The vehicle subsystem is dominant, and the infrastructure subsystem provides assistance to complete the driving environment. b) Transportation behavior prediction and management: The vehicle subsystem is dominant, and the infrastructure subsystem mainly cooperates with the vehicle subsystem. c) Planning and decision-making: The vehicle subsystem plays a major role, and the infrastructure subsystem optimizes the system from a global perspective. d) Vehicle control: The vehicle subsystem is dominant, and the infrastructure subsystem supports vehicle control commands.

16. The components of the control allocate, arrange, and distribute intelligence so that functions are assigned to the vehicle, and the autonomous vehicle and the infrastructure have no communication function and function independently. The infrastructure does not provide improvement to vehicle intelligence and is applicable to Scenario S1. The system according to claim 13.

17. The components of the control allocate, arrange, and distribute intelligence so that most functions are assigned to the vehicle subsystem and the vehicle plays a central role. The roadside device subsystem only plays a supplementary role for simple tasks, helps the vehicle maintain a certain speed and provide collision warnings, and when control decisions conflict, the vehicle makes decisions. It is applicable to Scenario S1 or S2. The system according to claim 13.

18. The components of the control allocate, arrange, and distribute intelligence so that functions can be flexibly assigned to either the vehicle or the infrastructure subsystem. Either the infrastructure or the vehicle subsystem plays a central role in sensing and decision-making. The roadside device subsystem helps the vehicle make decisions based on the local environment, proposes control for the vehicle to operate as follows: a) Following strategy b) Lane-keeping strategy c) Lane-changing strategy d) Merging and diverging strategies, and e) Passing through intersections When control decisions conflict, the vehicle makes control decisions independently or uses information from the infrastructure to make control decisions. It is applicable to Scenario S2 or S3. The system according to claim 13.

19. Most of the functions of the control components are distributed to the roadside device subsystem. The infrastructure performs the assignment, placement, and distribution of intelligence so as to play a dominant role in control decisions. The vehicle subsystem further has basic functions such as collision avoidance. The vehicle follows all the information provided by the infrastructure. When control decisions conflict, the vehicle takes the decision by the infrastructure as the control decision, which is applicable to the S3 scenario or the S4 scenario. The system according to claim 13.

20. All the functions of the control components depend on the roadside subsystem. The assignment, placement, and distribution of intelligence are performed so that the vehicle has the ability to communicate and follow instructions. All vehicles are controlled by the infrastructure system, and the decision-making is performed by the system and transmitted via the roadside device network, which is applicable to the S4 scenario or the S5 scenario. The system according to claim 13.

21. The control component manages the mixed traffic flow of vehicles at various connectivity and automation levels. The system according to claim 8.

22. The control components collect vehicle-generated data such as the movement and state of the vehicle, transmit the collected data to the RSU, receive input data from the IRIS, and the OBU facilitates vehicle control based on the input data from the IRIS. When a failure occurs in the vehicle control system, the OBU can take over in a short time and safely stop the vehicle. The system according to claim 21.

23. The IRIS provides customized detailed information and time-sensitive control commands for individual vehicles to perform driving tasks such as vehicle following, lane changing, and route guidance, and provides operation and maintenance services for vehicles on both highways and urban arterial roads. The system according to claim 8.

24. The IRIS is built and managed as an open platform. The following unique subsystems are owned and / or operated by various entities and are physically and / or logically shared among various CAVH systems including one or more or all of the following physical subsystems. a. A roadside unit (RSU) network that includes functions such as sensing, communication, control (high-speed / simple), and calculation of the drivable range b. A traffic control unit (TCU) and traffic control center (TCC) network c. An on-board unit (OBU) and related vehicle interfaces d. A traffic operation center, and e. A cloud-based platform for information and computing services The system according to claim 23, wherein the system implements one or more of the following functional categories i. Sensing ii. Prediction and management of transportation behavior iii. Planning and decision-making, and iv. Vehicle control

25. A method including the step of using any one of the systems for managing a connected and automated vehicle according to claims 1 to 24

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