WO2020258276A1

WO2020258276A1 - Yielding method and apparatus for intelligent driving vehicle, and vehicle-mounted device

Info

Publication number: WO2020258276A1
Application number: PCT/CN2019/093808
Authority: WO
Inventors: 马万里; 赵世杰; 周小成
Original assignee: 驭势科技（北京）有限公司
Priority date: 2019-06-28
Filing date: 2019-06-28
Publication date: 2020-12-30
Also published as: CN110494341A

Abstract

A yielding method and apparatus for an intelligent driving vehicle, and a vehicle-mounted device. An intelligent driving vehicle (003) runs on a special road configured with a plurality of road monitoring units (002). The method comprises: determining, on the basis of monitoring information of road monitoring units (002), whether a passing vehicle (004) that an intelligent driving vehicle (003) needs to yield exists; if yes, determining a yielding area according to state information of the intelligent driving vehicle (003); planning and generating a yielding path of the intelligent driving vehicle (003) on the basis of the state information of the intelligent driving vehicle (003) and the yielding area; and controlling the intelligent driving vehicle (003) to run according to the yielding path. The present invention implements yielding to a passing vehicle, and by means of effective coordination between a vehicle and a road, improves passing efficiency and ensures traffic safety.

Description

Method, device and vehicle-mounted equipment for intelligent driving vehicle to yield

Technical field

The embodiments of the present disclosure relate to the field of intelligent driving, and in particular to a method, device and vehicle-mounted equipment for an intelligent driving vehicle to yield.

Background technique

With the development of vehicle intelligence and network technology, autonomous vehicle autonomous driving technology based on vehicle-road collaboration has gradually become a hot spot in the field of intelligent transportation research.

Vehicle-road collaboration technology uses advanced wireless network technology (including cellular network communication, wireless communication, 4G and 5G and other communication technologies) for data transmission to realize real-time data exchange between road-cloud-vehicles, thereby realizing active safety control of vehicles , To fully realize effective coordination between vehicles and vehicles, and between vehicles and roads, thereby improving traffic efficiency and ensuring traffic safety.

In some special scenarios, due to the characteristics of the road itself, for example, the road is a single lane, but it can drive in two directions. If the planning is unreasonable, there will be congestion or congestion. Therefore, special planning is required for this special road condition. However, the existing autonomous driving technology does not provide any solutions for this special road condition.

The above description of the discovery process of the problem is only used to assist the understanding of the technical solution of the present invention, and does not mean that the above content is recognized as prior art.

Summary of the invention

In order to solve at least one problem in the prior art, at least one embodiment of the present application provides a method, device and vehicle-mounted device for an intelligent driving vehicle to yield.

In a first aspect, an embodiment of the present disclosure proposes a method for giving way to a smart driving vehicle, wherein the smart driving vehicle is driving on a special road, and the special road is configured with multiple road monitoring units, including:

Judging whether there is a passing vehicle on the special road that requires intelligent driving vehicles to give way;

Based on the existence of passing vehicles that need to yield, determine the yieldable area according to the state information of the intelligent driving vehicle;

Planning and generating a yield path of the smart driving vehicle based on the state information of the smart driving vehicle and the yieldable area;

Control the intelligent driving vehicle to follow the yield path.

In the second aspect, the embodiments of the present disclosure also propose a vehicle-mounted device, including:

Processor and memory;

The processor is used to execute the steps of the method described in the first aspect by calling the program or instruction stored in the memory.

In the third aspect, the embodiments of the present disclosure also propose a non-transitory computer-readable storage medium, the non-transitory computer-readable storage medium stores a program or instruction, and the program or instruction causes a computer to execute as described in the first aspect Method steps.

In a fourth aspect, an embodiment of the present disclosure also proposes an intelligent driving vehicle yielding device. The intelligent driving vehicle to which the intelligent driving vehicle yielding device belongs runs on a special road, and the special road is configured with multiple road monitoring units, so The smart driving vehicle yielding device includes:

The yield determination unit is used to determine whether there is a passing vehicle that requires an intelligent driving vehicle to yield on the special road;

A yield path generation unit is used to determine a yieldable area based on the state information of the intelligent driving vehicle based on the existence of a passing vehicle that needs to yield; planning based on the state information of the smart driving vehicle and the yieldable area Generating a yield path of the intelligent driving vehicle;

The yield path driving unit is used to control the intelligent driving vehicle to follow the yield path.

In a fifth aspect, an embodiment of the present disclosure also proposes a vehicle yielding system, including: a server, the smart driving vehicle yielding device as described in any embodiment of the fourth aspect, and multiple road monitoring units configured on the road ；

The road monitoring unit interacts with the server, and the server interacts with the intelligent driving vehicle yielding device.

It can be seen that in at least one of the embodiments of the present disclosure, it is determined whether there is a passing vehicle that needs to yield on a special road, and when it is determined that there is a passing vehicle that needs to yield, the yield path is planned and generated, and then the intelligent driving vehicle is The yield path is driven to achieve yield, and then active yield actions can be taken in advance, which improves traffic efficiency and ensures traffic safety.

In the embodiments of the present disclosure, the decision is made based on the monitoring information of the road monitoring unit, that is, through effective coordination between the vehicle and the road, not only the sensor of the intelligent driving vehicle is used for sensing, thereby improving the traffic efficiency and ensuring traffic safety.

Description of the drawings

In order to explain the technical solutions of the embodiments of the present disclosure more clearly, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some of the present application. For the embodiments, those of ordinary skill in the art can also obtain other drawings based on these drawings.

FIG. 1 is a scene diagram of an intelligent driving vehicle driving provided by an embodiment of the present disclosure;

Figure 2 is an overall architecture diagram of an intelligent driving vehicle provided by an embodiment of the present disclosure;

3A is a block diagram of an intelligent driving system provided by an embodiment of the present disclosure;

3B is a block diagram of a yield module provided by an embodiment of the present disclosure;

FIG. 4 is a block diagram of a vehicle-mounted device provided by an embodiment of the present disclosure;

FIG. 5 is a flowchart of a method for giving way for an intelligent driving vehicle provided by an embodiment of the present disclosure;

FIG. 6 is a flowchart of yet another method for giving way for a smart driving vehicle provided by an embodiment of the present disclosure;

FIG. 7 is a signaling diagram of a method for giving way for an intelligent driving vehicle provided by an embodiment of the present disclosure;

FIG. 8A is a scene diagram of another intelligent driving vehicle driving provided by an embodiment of the present disclosure;

8B to 8E are schematic diagrams of giving way according to the intelligent driving vehicle in the scene shown in FIG. 8A;

FIG. 9 is a schematic diagram of a yield point used in another method for yielding a smart driving vehicle provided by an embodiment of the present disclosure.

Detailed ways

In order to be able to understand the above objectives, features and advantages of the application more clearly, the application will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the described embodiments are part of the embodiments of the present application, rather than all of the embodiments. The specific embodiments described here are only used to explain the application, but not to limit the application. Based on the described embodiments of the present application, all other embodiments obtained by a person of ordinary skill in the art fall within the protection scope of the present application.

It should be noted that in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply these There is any such actual relationship or sequence between entities or operations.

In view of the unreasonable planning of some roads in the prior art, resulting in frequent congestion or congestion of passing vehicles, resulting in low traffic efficiency, embodiments of the present disclosure provide a solution for intelligently driving vehicles to give way to driving on special roads. When it is determined based on the monitoring information of the road monitoring unit that it is necessary to give way to passing vehicles, the give way area on the special road is determined, and the give way path of the intelligent driving vehicle is generated according to the allowable area plan, and the intelligent driving vehicle is controlled to follow Driving on the yield path can then take active yield actions in advance to improve traffic efficiency and ensure traffic safety.

The embodiments of the present disclosure provide an intelligent driving vehicle yielding solution, which can be applied to intelligent driving vehicles and various scenarios. For example, when a smart driving vehicle and some emergency vehicles (for example, an ambulance, a fire engine, etc.) are driving head-on, the smart driving vehicle needs to give way to the emergency vehicle. In some embodiments, when the intelligent driving vehicle is driving on a special road, it will also encounter a situation where it needs to give way. For example, when the special road is a two-way single-lane road, it is necessary to give way to passing vehicles (such as fire trucks) that are driving in the same direction and located behind the driving direction of the intelligent driving vehicle, or it is necessary to give way to oncoming vehicles (such as rescue vehicles). ) Make a concession. In addition, in the above scenario, multiple road monitoring units may be configured. In some embodiments, the road monitoring unit may be a device configured on both sides of the road to collect monitoring information within the monitoring range. In some embodiments, the road monitoring unit may also be embedded in other devices, such as on a traffic light device, a camera, or other road signs.

Figure 1 is a scene of a smart driving vehicle driving in some embodiments of the present disclosure. As shown in Figure 1, the scene includes a cloud server 001, a road side unit (RSU: Road Side Unit) 002, and a smart driving vehicle 003 And traffic vehicles 004. In some embodiments, the cloud server 001 may be used to obtain information about the road monitoring unit 002 and the intelligent driving vehicle 003, and may send information to the intelligent driving vehicle 003. In some embodiments, the cloud server 001 may send the monitoring information corresponding to the smart driving vehicle 003 in the road monitoring unit 002 to the smart driving vehicle 003 according to the information of the smart driving vehicle 003. In some embodiments, the cloud server 001 may be an independent background server or a server group. The server group can be centralized or distributed. The server can be local or remote.

The road monitoring unit 002 can be used to collect road monitoring information. In some embodiments, the road monitoring unit 002 may be an environmental sensor, such as a camera, a lidar, etc., or a road device, such as a V2X device, a roadside traffic light device, and the like. In some embodiments, the road monitoring unit 002 may monitor the road conditions subordinate to the corresponding road monitoring unit 002, for example, the type, speed, priority level, etc. of passing vehicles. After collecting the road monitoring information, the road monitoring unit 002 may send the road monitoring information to the cloud server, or may also send the road monitoring information to the intelligent driving vehicles passing the road.

The intelligent driving vehicle 003 is used to generate control information according to the surrounding environment and control the driving of the vehicle. In some embodiments, the intelligent driving vehicle 003 may send request information to a cloud server for obtaining relevant information of the cloud server. In some embodiments, the requested information includes, but is not limited to, the current vehicle identifier, the current vehicle pose, and corresponding road monitoring unit information corresponding to the vehicle. In some embodiments, the intelligent driving vehicle 003 may receive feedback information from the cloud server 001, where the feedback information includes, but is not limited to, road monitoring information of a corresponding road monitoring unit. In some embodiments, the intelligent driving vehicle 003 can realize the planning control information of the intelligent driving vehicle 003 according to the road monitoring information of the corresponding road monitoring unit. For example, giving way to some vehicles on special roads, thereby improving the efficiency of vehicles on special roads while ensuring traffic safety.

Traffic vehicles 004 are various vehicles that travel on the road. In some embodiments, the traffic vehicle 004 may be a smart driving vehicle, a manual driving vehicle, or an autonomous driving vehicle of different levels. The traffic vehicle 004 may also be a vehicle including but not limited to a small car, a medium-sized car, a large-sized car, a cargo car, an ambulance, a fire engine, etc. In some embodiments, different vehicles have different priorities. For example, the priority of an ambulance or a fire truck is higher than that of a normal vehicle.

FIG. 2 is an overall architecture diagram of an intelligent driving vehicle in some embodiments of the present disclosure. As shown in FIG. 2, the intelligent driving vehicle includes: a sensor group, an intelligent driving system 100, a vehicle bottom-level execution system, and others that can be used to drive intelligent driving Vehicles and components that control the operation of intelligent driving vehicles.

The sensor group is used to collect the data of the external environment of the intelligent driving vehicle and to detect the position data of the intelligent driving vehicle. The sensor group includes, but is not limited to, at least one of a camera, a lidar, a millimeter wave radar, a GPS (Global Positioning System, global positioning system), and an IMU (Inertial Measurement Unit), for example.

In some embodiments, the sensor group is also used to collect dynamics data of the vehicle. The sensor group includes, but is not limited to, at least one of a wheel speed sensor, a speed sensor, an acceleration sensor, a steering wheel angle sensor, and a front wheel angle sensor.

The intelligent driving system 100 is used to obtain data of a sensor group, and all sensors in the sensor group transmit data at a higher frequency during the driving of the intelligent driving vehicle. The intelligent driving system is also used for wireless communication with the cloud server to exchange various information. The intelligent driving system is also used for wireless communication with the road monitoring unit to exchange various information.

The intelligent driving system 100 is also used for environmental perception and vehicle positioning based on the data of the sensor group, path planning and decision-making based on environmental perception information and vehicle positioning information, and generating vehicle control instructions based on the planned path, thereby controlling the vehicle according to the plan Route driving.

The intelligent driving system 100 is also used to determine whether there is a passing vehicle that requires an intelligent driving vehicle to give way on the special road; based on the existence of a passing vehicle that needs to give way, determine the allowable area according to the state information of the intelligent driving vehicle; Based on the state information of the smart driving vehicle and the yieldable area, planning and generating a yield path of the smart driving vehicle; controlling the smart driving vehicle to drive along the yield path.

In some embodiments, the intelligent driving system 100 may be a software system, a hardware system, or a combination of software and hardware. For example, the intelligent driving system 100 is a software system running on an operating system, and the on-board hardware system is a hardware system supporting the operation of the operating system. The intelligent driving system of the present disclosure may be a component in an in-vehicle device or an in-vehicle control device of an intelligently driving vehicle, or an in-vehicle device or an in-vehicle control device of an intelligently driving vehicle.

The bottom-level execution system of the vehicle is used to receive vehicle control instructions and realize the control of the intelligent driving vehicle. The bottom-level execution system of the vehicle includes but is not limited to: steering system, braking system and drive system. The steering system, braking system, and driving system are mature structures in the vehicle field, and will not be repeated here.

In some embodiments, the intelligent driving vehicle may further include a vehicle CAN bus not shown in FIG. 2, and the vehicle CAN bus is connected to the underlying execution system of the vehicle. The information interaction between the intelligent driving system 100 and the underlying execution system of the vehicle is transmitted through the vehicle CAN bus.

In some embodiments, the intelligent driving vehicle can be controlled by the driver and the intelligent driving system 100 to control the vehicle. In the manual driving mode, the driver drives the vehicle by operating a device that controls the travel of the vehicle. The devices that control the travel of the vehicle include, but are not limited to, a brake pedal, a steering wheel, and an accelerator pedal. The device for controlling the driving of the vehicle can directly operate the execution system at the bottom of the vehicle to control the driving of the vehicle.

In some embodiments, the intelligent driving vehicle may also be an unmanned vehicle, and the driving control of the intelligent driving vehicle is executed by the intelligent driving system.

FIG. 3A is a block diagram of an intelligent driving system 200 provided by an embodiment of the disclosure. In some embodiments, the smart driving system 200 may be implemented as the smart driving system 100 or a part of the smart driving system 100 in FIG. 2 for controlling the driving of the vehicle.

As shown in FIG. 3A, the intelligent driving system 200 includes, but is not limited to: a perception module 201, a planning module 202, a control module 203, a yield module 204, and other modules that can be used for intelligent driving.

In some embodiments, the sensing module 201 is used for acquired sensor data, V2X (Vehicle to X) data, high-precision maps and other data.

In some embodiments, the sensing module 201 is configured to perform environment perception and positioning based on at least one of acquired sensor data, V2X (Vehicle to X, vehicle wireless communication) data, and high-precision maps.

In some embodiments, the perception module 201 is used to generate perception positioning information to realize obstacle perception, recognition of the drivable area of camera images, and vehicle positioning.

Environmental perception (Environmental Perception) can be understood as the ability to understand the scene of the environment, such as the location of obstacles, the detection of road signs/marks, the detection of pedestrians/vehicles, and the semantic classification of data.

In some embodiments, environment perception can be realized by fusing data from multiple sensors such as cameras, lidars, millimeter wave radars, etc.

Localization is a part of perception, which is the ability to determine the position of the intelligent driving vehicle relative to the environment.

Positioning can be: GPS positioning, GPS positioning accuracy is tens of meters to centimeters, high positioning accuracy; positioning can also use GPS and inertial navigation system (Inertial Navigation System) positioning method. Positioning can also use SLAM (Simultaneous Localization And Mapping, simultaneous positioning and map construction). The goal of SLAM is to construct a map while using the map for positioning. SLAM uses the observed environmental features to determine the current vehicle's position and current observation features s position.

V2X is the key technology of the intelligent transportation system, which enables the communication between vehicles, vehicles and base stations, base stations and base stations, so as to obtain a series of traffic information such as real-time road conditions, road information, pedestrian information, and improve the safety of intelligent driving. Congestion, improve traffic efficiency, provide on-board entertainment information, etc.

High-precision maps are geographic maps used in the field of intelligent driving. Compared with traditional maps, the differences are: 1) High-precision maps include a large amount of driving assistance information, for example, relying on the accurate three-dimensional representation of the road network: including intersections and The location of road signs, etc.; 2) The high-precision map also includes a lot of semantic information, such as reporting the meaning of different colors on traffic lights, and for example indicating the speed limit of the road, and the position of the left turn lane; 3) The high-precision map can reach centimeters Class accuracy ensures the safe driving of intelligent driving vehicles.

The planning module 202 is configured to perform path planning and decision-making based on the sensing positioning information generated by the sensing positioning module.

In some embodiments, the planning module 202 is used to perform a route based on the perception positioning information generated by the perception positioning module, combined with at least one of V2X data, high-precision maps and other data, road monitoring unit information, and cloud server information. Planning and decision-making.

In some embodiments, the planning module 202 is used to plan routes and make decisions: behaviors (for example, including but not limited to following, overtaking, stopping, detouring, etc.), vehicle heading, vehicle speed, desired acceleration of the vehicle, desired steering wheel angle And so on, generate planning decision information.

The control module 203 is configured to perform path tracking, trajectory tracking, or path yield based on the planning decision information generated by the planning module.

In some embodiments, the control module 203 is used to generate control instructions for the bottom-level execution system of the vehicle, and issue control instructions so that the bottom-level execution system of the vehicle controls the vehicle to travel along a desired path, for example, by controlling the steering wheel, brakes, and accelerator to control the vehicle. Horizontal and vertical control.

In some embodiments, the control module 203 is also used to calculate the front wheel angle based on the path tracking algorithm.

In some embodiments, the yield module 204 is used to determine whether there is a passing vehicle that requires a smart driving vehicle to yield on the special road; based on the existence of a passing vehicle that needs to yield, it is determined according to the state information of the smart driving vehicle. Giving way area; based on the state information of the smart driving vehicle and the giving way area, planning and generating the giving way path of the smart driving vehicle; controlling the smart driving vehicle to drive according to the giving way path. In some embodiments, the yield module 204 is also used to obtain monitoring information of the corresponding road monitoring unit, and determine whether there is a passing vehicle that needs to yield based on the acquired monitoring information.

In some embodiments, the function of the yield module 204 can be integrated into the perception module 201, the planning module 202 or the control module 203, or it can be configured as a module independent of the intelligent driving system. The yield module 204 can be a software module, Hardware module or a combination of software and hardware. For example, the yield module 204 is a software module running on an operating system, and the vehicle-mounted hardware system is a hardware system that supports the running of the operating system.

FIG. 3B is a block diagram of an intelligent driving vehicle yielding device 300 provided by an embodiment of the disclosure. In some embodiments, the smart driving vehicle yielding device 300 may be implemented as the yielding module 204 or a part of the yielding module 204 in FIG. 3A.

As shown in FIG. 3B, the smart driving vehicle yielding device 300 includes a yield determining unit 301, a yield path generating unit 302, a yield path driving unit 303, and other units that can be used to perform yield operations.

The yield determination unit 301 is used to determine whether there is a passing vehicle that needs to yield on the road on which the intelligent driving vehicle is currently traveling. In some embodiments, the intelligent driving vehicle determines whether there is a passing vehicle that needs to yield based on the monitoring information of the road monitoring unit. The intelligent driving vehicle determines the corresponding road monitoring unit based on the state information of the intelligent driving vehicle, and sends the corresponding road monitoring unit information to the cloud server, thereby receiving the monitoring information of the corresponding road monitoring unit. Among them, the state information of the intelligent driving vehicle includes, but is not limited to: position information, speed, and heading. In some embodiments, the yield determination unit 301 determines the corresponding road monitoring unit based on one or more of the position information, speed, and heading of the intelligent driving vehicle.

The yield determination unit 301 obtains corresponding road monitoring unit information based on one or more of the position information, heading, and high-precision map of the intelligent driving vehicle. The high-precision map includes one or more of the location and the monitoring range of the road monitoring unit in the road network. In some embodiments, the yield determination unit 301 may send an acquisition request to the server to acquire the monitoring information of the corresponding road monitoring unit, wherein the acquisition request includes at least the corresponding road monitoring unit information. In some embodiments, the smart driving vehicle yielding device can interact with the cloud server to obtain the monitoring information of the road monitoring unit. Of course, in some embodiments, the smart driving vehicle yielding device of the embodiment of the present disclosure can directly interact with the road monitoring unit to obtain monitoring information of the road monitoring unit. In some embodiments, the monitoring information of the road monitoring unit includes but is not limited to at least one of passing vehicle information, passing vehicle priority, passing vehicle location, passing vehicle heading, passing vehicle type, and passing vehicle speed.

The yield determination unit 301 may determine whether there is a passing vehicle that needs to yield based on at least one of the passing vehicle priority, the passing vehicle position, and the passing vehicle heading. In some embodiments, the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, and the intelligent driving vehicle needs to yield. In some embodiments, when the direction of the passing vehicle and the intelligent driving vehicle are opposite, and the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, the intelligent driving vehicle needs to give way. In some embodiments, when the direction of the passing vehicle and the intelligent driving vehicle are the same, the speed of the passing vehicle is greater than the speed of the intelligent driving vehicle, and the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, The intelligent driving vehicle needs to give way.

The yield path generating unit 302 is configured to plan and generate a yield path when there are vehicles that need to yield. In some embodiments, the yielding path generation unit 302 obtains the yieldable area of the special road based on the state information of the intelligent driving vehicle. Wherein, the state information of the intelligent driving vehicle includes, but is not limited to: position information, speed, and heading. In some embodiments, the yield path generating unit 301 determines a yield area based on the position, heading, and/or high-precision map of the vehicle, and determines a yield point based on the yield area. Wherein, the giving way area and the giving way point can be marked on the high-precision map, that is, whether there are any give-away areas on the road recorded in the high-precision map used by the intelligent driving system, and any The yield point information in the row area. In some embodiments, the yield point in the yield area is determined according to the yield area and the road network topology. At this time, the road network topology may include road network information corresponding to the yieldable area, where the road network topology and road network information are included in the high-precision map.

In some embodiments, the yield path generation unit 302 determines a yield point based on the yield area, and uses the yield point as a yield destination during path planning in the intelligent driving vehicle, thereby planning and generating Yield path. In some embodiments, if there are multiple yield points, the yield path generating unit 302 can select one of the yield points as the target yield point to reach the yield point and plan the yield path, for example, the target yield point/ The reachable yield point may be the yield point closest to the intelligent driving vehicle as the target yield point, or the target yield point may be any yield point in the yield area.

In some embodiments, the yield path generating unit 302 is also used to adjust the priority of the smart driving vehicle when there is no yield point, so that the smart driving vehicle becomes another passing vehicle on a special road and needs to yield. Vehicles. The adjustment of the priority of the intelligent driving vehicle may adjust the priority of the intelligent driving vehicle to a higher priority on the current traffic road to ensure passage, or it may be adjusted to the highest priority. In some embodiments, the intelligent driving system may send the adjusted priority to the cloud server or road monitoring unit, and the cloud server or road monitoring unit may notify other vehicles, or it may use vehicle-to-vehicle communication to notify other vehicles on the current road. Passing vehicles, so that other passing vehicles give way to the current intelligent driving vehicle.

The yield path driving unit 303 is used to generate a control instruction to control the intelligent driving vehicle to follow the yield path. In some embodiments, the yield path driving unit 303 generates a control instruction based on the yield path, converts the control instruction into a control execution instruction, and issues it to the vehicle bottom-level execution system. The vehicle bottom-level execution system controls the intelligent driving vehicle to follow the yield path based on the control execution instruction.

In some embodiments, the smart-driving vehicle yielding device 300 further includes a path planning unit not shown in the figure, which is used to generate the original destination and the current position of the smart-driving vehicle after the yield is completed based on the yielding path. Plan the path. In some embodiments, the original destination may be understood as the destination where the intelligent driving vehicle travels before giving way. In some embodiments, the current position of the intelligent driving vehicle may be the reachable yield point in the foregoing yieldable area. The reachable yield point is used as location information when planning a route.

In the embodiments of the present disclosure, through the effective collaboration between the vehicle and the road, the sensor data of the intelligent driving vehicle is not only relied on, thereby improving the traffic efficiency and ensuring traffic safety.

In some embodiments, the division of each unit in the way of intelligent driving vehicle yielding device 300 is only a logical function division. In actual implementation, there may be other ways of dividing, for example, yield determining unit 301, yield path generating unit 302, and The yield path driving unit 303 may be implemented as a unit; the yield determination unit 301, the yield path generation unit 302, and the yield path driving unit 303 may also be divided into multiple sub-units. It can be understood that each unit or sub-unit can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed by hardware or software depends on the specific application and design constraint conditions of the technical solution. Professional technicians can use different methods for each specific application to achieve the described functions.

Fig. 4 is a schematic structural diagram of a vehicle-mounted device provided by an embodiment of the present disclosure. On-board equipment can support the operation of the intelligent driving system.

As shown in FIG. 4, the vehicle-mounted device includes: at least one processor 401, at least one memory 402, and at least one communication interface 403. The various components in the vehicle-mounted device are coupled together through the bus system 404. The communication interface 403 is used for information transmission with external devices. It can be understood that the bus system 404 is used to implement connection and communication between these components. In addition to the data bus, the bus system 404 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, various buses are marked as the bus system 404 in FIG. 4.

It can be understood that the memory 402 in this embodiment may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.

In some embodiments, the memory 402 stores the following elements, executable units or data structures, or a subset of them, or an extended set of them: operating systems and applications.

Among them, the operating system includes various system programs, such as a framework layer, a core library layer, and a driver layer, which are used to implement various basic services and process hardware-based tasks. Application programs, including various application programs, such as Media Player, Browser, etc., are used to implement various application services. A program that implements the method of giving way for an intelligent driving vehicle provided by an embodiment of the present disclosure may be included in an application program.

In the embodiments of the present disclosure, the processor 401 calls a program or instruction stored in the memory 402, specifically, it may be a program or instruction stored in an application program. The processor 401 is used for the steps of the various embodiments of the method for giving way to a smart driving vehicle. .

The smart driving vehicle yielding method provided by the embodiment of the present disclosure may be applied to the processor 401 or implemented by the processor 401. The processor 401 may be an integrated circuit chip with signal processing capability. In the implementation process, the steps of the foregoing method can be completed by hardware integrated logic circuits in the processor 401 or instructions in the form of software. The aforementioned processor 401 may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a ready-made programmable gate array (Field Programmable Gate Array, FPGA) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor or the like.

The steps of the intelligent driving vehicle yield method provided by the embodiments of the present disclosure can be directly embodied as execution and completion by a hardware decoding processor, or by a combination of hardware and software units in the decoding processor. The software unit may be located in a mature storage medium in the field such as random access memory, flash memory, read-only memory, programmable read-only memory or electrically erasable programmable memory, registers. The storage medium is located in the memory 402, and the processor 401 reads the information in the memory 402 and completes the steps of the method in combination with its hardware.

Fig. 5 is an exemplary flow chart of a method for giving way for an intelligent driving vehicle shown in some embodiments of the present application. The execution body of the method is a vehicle-mounted device. In some embodiments, the execution body of the method is an intelligent driving system supported by the vehicle-mounted device.

In some embodiments, the method for giving way for a smart driving vehicle can be applied to a vehicle giving way scheme for a smart driving vehicle on a special road during the driving process. In some embodiments, the special reasoning includes, but is not limited to, a two-way single lane. In some embodiments, multiple road monitoring units obtain monitoring information of the special road. In some embodiments, multiple road monitoring units are arranged on special roads at intervals. In some embodiments, each road monitoring unit can be installed separately, or embedded in other equipment such as traffic light equipment or road signs. The embodiments of the present disclosure do not limit the specific equipment structure of the road monitoring unit. Devices with unit functions are within the scope of this application.

As shown in FIG. 5, in step 510, the intelligent driving vehicle (for example, the vehicle-mounted equipment or vehicle control device of the intelligent-driving vehicle, or the intelligent driving system supported by the vehicle-mounted equipment) determines the intelligence based on the monitoring information of the road monitoring unit. Whether there is a passing vehicle that needs to yield on the road on which the vehicle is driving. In some embodiments, the road monitoring unit is determined based on the state information of the intelligent driving vehicle. In some embodiments, the state information of the intelligent driving vehicle includes, but is not limited to: position, speed, and heading. In some embodiments, the intelligent driving system determines the corresponding road monitoring unit in real time or periodically based on the status information of the intelligent driving vehicle, and then determines whether there is a passing vehicle that needs to yield on the current road based on the monitoring information of the corresponding road monitoring unit. In some embodiments, the monitoring information of each road monitoring unit includes but is not limited to: at least one of passing vehicle information, passing vehicle priority, passing vehicle location, passing vehicle heading, and passing vehicle type. Furthermore, in a specific implementation process, it is determined whether there is a passing vehicle that needs to yield according to at least one of the priority of the passing vehicle, the location information of the passing vehicle, and the heading of the passing vehicle. For example, if there is at least one passing vehicle in the monitoring information of the corresponding road monitoring unit that has a priority higher than that of a smart driving vehicle, it is determined that there is a passing vehicle that needs to yield on the current road. In some embodiments, in the monitoring information of the corresponding road monitoring unit, there is at least one passing vehicle whose priority is higher than the priority of the intelligent driving vehicle, and the heading is the same, and the position information of all passing vehicles is located in front of the driving direction of the intelligent driving vehicle , It is determined that there is no passing vehicle that needs to give way on the current road, and intelligent driving vehicles do not need to give way to high-priority passing vehicles. In some embodiments, in the monitoring information of the corresponding road monitoring unit, there is at least one passing vehicle whose priority is higher than the priority of the intelligent driving vehicle, and the heading is the same, and there is a high priority passing vehicle in the driving direction of the intelligent driving vehicle Behind the road, it is determined that there are passing vehicles that need to give way on the current road, that is, the intelligent driving vehicle needs to give way to the high-priority passing vehicles.

In step 520, when the intelligent driving system determines that it is necessary to give way, it obtains the yieldable area on the current driving road. In some embodiments, the row area may be marked on the high-precision map. In some embodiments, the allowable area is understood to be an area on the road where temporary parking is possible. In some embodiments, the smart driving system determines the yieldable area according to the state information of the smart driving vehicle. In some embodiments, the state information of the intelligent driving vehicle includes, but is not limited to: position, heading, and speed. In some embodiments, based on the location, speed, and high-precision map of the intelligent driving vehicle, the yieldable area on the driving road is determined. In some embodiments, the allowable area on the driving road is determined according to the position, heading and high-precision map of the intelligent driving vehicle.

In step 530, the smart driving system plans a yield path based on the yieldable area and the state information of the smart driving vehicle. In some embodiments, the intelligent driving system determines whether there is a yield point in the yield area, and if there is a yield point, the yield point is used as the destination of the planned yield path, and the path planning is performed to obtain the yield path . In some embodiments, the intelligent driving system determines that there is a yield point in the yieldable area, and there are multiple yield points, the smart driving system may select a yield point as the reachable yield point according to the yield point screening rule At this time, the selected reachable yield point is the destination used for planning the yield path. In some embodiments, the reachable yield point may be the yield point closest to the position information of the intelligent driving vehicle. In some embodiments, based on the position of the passing vehicle, the position, speed and heading of the intelligent driving vehicle, a yield point is selected as the reachable yield point according to the yield point screening rule. At this time, the intelligent driving system plans the yield path based on the status information of the intelligent driving vehicle and the reachable yield point. In some embodiments, whether there is a yield point in the yield area is determined by the yield area and the road network topology in the high-resolution map. The topological structure of the road network includes road network information of the concession area. In some embodiments, if there is no yield point in the yieldable area, the smart driving system adjusts the priority of the smart driving vehicle by adjusting the priority of the vehicle, so that the smart driving vehicle after the adjusted priority becomes the current road Vehicles that board other passing vehicles to give way.

In step 540, the intelligent driving system controls the intelligent driving vehicle to drive along the yield path. In some embodiments, when the intelligent driving vehicle of the intelligent driving system is an unmanned vehicle, the intelligent driving system can generate and issue control instructions for the underlying vehicle execution system based on the yield path, and the vehicle underlying execution system controls the intelligent driving vehicle according to the control execution Follow the yield path. In some embodiments, the intelligent driving system controls the intelligent driving vehicle to drive according to the yielding path based on the perception information of the sensor group and the underlying execution system of the vehicle.

In the embodiment of the present disclosure, when it is determined that there is a passing vehicle that needs to give way through the monitoring information of the road monitoring unit, the give way area of the intelligent driving vehicle is obtained, and then the give way path is generated based on the give way area planning, thereby controlling the intelligent driving Vehicles follow the concession path to achieve concession, thereby improving the efficiency of traffic and ensuring traffic safety.

In some embodiments, as shown in FIG. 6, step 510 may include sub-step 5101 to sub-step 5103; specifically, in step 5101, the corresponding road monitoring unit is determined based on the state information of the intelligent driving vehicle. In some embodiments, the state information of the intelligent driving vehicle includes, but is not limited to, position information, speed, driving state, and heading of the intelligent driving vehicle. In some embodiments, the location information of the intelligent driving vehicle may be obtained through the sensing module of the intelligent driving system. In some embodiments, the intelligent driving vehicle obtains corresponding road monitoring unit information based on the location information and high-precision map of the intelligent driving vehicle. In some embodiments, the intelligent driving vehicle obtains corresponding road monitoring unit information based on the position information, speed, heading, and high-precision map of the intelligent driving vehicle. In some embodiments, the high-precision map includes, but is not limited to, location information, road network information, and road network identification information of the road monitoring unit. In some embodiments, the high-precision map of this embodiment may be the high-precision map used in the intelligent driving field described in the foregoing content. Through the use of high-precision maps, the corresponding road monitoring unit information can be obtained accurately and in real time.

In some embodiments, the determination of the corresponding road monitoring unit by the intelligent driving vehicle can be understood as acquiring the identification and location information of the required road monitoring unit.

In step 5102, the intelligent driving system receives the monitoring information of the corresponding road monitoring unit. In some embodiments, the intelligent driving system may send an acquisition request to the server, where the acquisition request includes at least the corresponding road monitoring unit information. In some embodiments, the intelligent driving system may receive a response from the server, wherein the response includes at least monitoring information of each road monitoring unit in the corresponding road monitoring unit. In some embodiments, the server receives the monitoring information reported by the road monitoring unit periodically or in real time. After receiving the acquisition request, the server screens the latest monitoring information of the corresponding road monitoring unit according to the corresponding road monitoring unit information in the acquisition request. In some embodiments, the server may be a cloud server. In some embodiments, the acquisition request includes at least the location information of the corresponding road monitoring unit or the identification of the corresponding road monitoring unit. The response includes but is not limited to: the monitoring information of the corresponding road monitoring unit, the location information of the corresponding road monitoring unit, the identification of the corresponding road monitoring unit, the status information of the corresponding road monitoring unit, the priority of the vehicle in the monitoring information of the road monitoring unit, etc. . In some embodiments, the state information of the road monitoring unit may include, but is not limited to, the normal state of the road monitoring unit and the off state of the road monitoring unit.

In some embodiments, the monitoring information includes, but is not limited to, at least one of passing vehicle information, passing vehicle priority, passing vehicle location, passing vehicle heading, and passing vehicle type.

In some embodiments, the server may receive the information reported by the road monitoring unit in real time, and send the monitoring information of the road monitoring unit to intelligent driving vehicles within the road range in real time or periodically. In some embodiments, the intelligent driving vehicle can obtain the monitoring information of the road monitoring unit through the server without omission, so as to ensure the accuracy and real-time nature of the monitoring information obtained by the intelligent driving vehicle.

In some embodiments, the monitoring information obtained by the intelligent driving vehicle may be the monitoring information recognized and processed by a server such as a cloud server, or it may be the monitoring information of a road monitoring unit directly forwarded by a server such as a cloud server. Embodiments of the present disclosure Do not limit it, choose according to actual needs. In some embodiments, the priority of the passing vehicles in the monitoring information may be that the road monitoring unit marks the priority of the passing vehicles according to the pre-priority judgment rules after monitoring the passing vehicles, so as to obtain the vehicles of the passing vehicles within the monitoring range of the road monitoring unit. priority. In some embodiments, the priority of the passing vehicle in the monitoring information can be understood as the server marking the priority of the passing vehicle according to the priority judgment rule in advance, so that the monitoring information sent to the intelligent driving system carries the monitoring range of the road monitoring unit Vehicle priority of vehicles passing inside.

In step 5103, the intelligent driving system determines whether there is a passing vehicle that needs to yield on the current road based on the monitoring information. In some embodiments, it is determined whether there is a passing vehicle that needs to yield based on at least one of the passing vehicle priority, the passing vehicle location, and the passing vehicle heading. In some embodiments, the intelligent driving system determines whether there is a passing vehicle that needs to yield based on the priority of passing vehicles in the monitoring information. In some embodiments, the intelligent driving system determines whether there is a passing vehicle that needs to yield based on the priority of the passing vehicle and the heading of the passing vehicle in the monitoring information.

In some embodiments, when the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, the intelligent driving vehicle needs to yield. In some embodiments, the heading of the intelligent driving vehicle is opposite to the heading of the passing vehicle, and the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, and the intelligent driving vehicle needs to give way. In some embodiments, the heading of the intelligent driving vehicle is the same as the heading of the passing vehicle, and the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle. When the passing vehicle is located behind the intelligent driving vehicle, the intelligent driving vehicle Need to make concessions.

In the embodiments of the present disclosure, during the driving of the intelligent driving vehicle, the intelligent driving system can periodically or in real time determine the corresponding road monitoring unit, and receive the monitoring information of the corresponding road monitoring unit, and then according to the monitoring information of the road monitoring unit, Determine whether there is a passing vehicle that needs to give way. When it exists, determine the yield area, and plan the yield path according to the yield area to control the intelligent driving vehicle to yield according to the yield path, and then take the initiative to yield in advance Action to improve traffic efficiency and ensure traffic safety.

Fig. 7 is a signaling diagram of yet another method for giving way for an intelligent driving vehicle according to some embodiments of the present application. The execution body of the method shown in FIG. 7 is the vehicle-mounted device. In some embodiments, the execution body of the method may be the intelligent driving system supported by the vehicle-mounted device. In some embodiments, the execution body of the method may be the vehicle-mounted device. Supported smart driving vehicle yield device.

In step 701, the intelligent driving system obtains corresponding road monitoring unit information based on the position information of the intelligent driving vehicle and the high-precision map. In some embodiments, the corresponding road monitoring unit information includes: a device for collecting road information on the road where the intelligent driving vehicle is traveling, for example, cameras periodically installed on both sides of the road, or periodically installed Lidar. In some embodiments, the road information collected by the road monitoring unit includes, but is not limited to, the type of the passing vehicle, the state of the passing vehicle, the direction of the passing vehicle, and other information of the passing vehicle such as color, license plate number, and so on. In some embodiments, the intelligent driving system directly wirelessly communicates with the obtained corresponding road monitoring unit to obtain the monitoring information of the corresponding road monitoring unit.

The embodiment of the present disclosure provides a way to obtain the monitoring information of the corresponding road monitoring unit by means of a cloud server. In step 702 and step 703, the intelligent driving system sends an acquisition request including corresponding road monitoring unit information to the cloud server, and receives a response of the road monitoring unit monitoring information returned by the cloud server. In some embodiments, the corresponding road monitoring unit information in the acquisition request includes, but is not limited to: the identification of the road monitoring unit, the name of the road monitoring unit, the location information of the road monitoring unit, and the like. In some embodiments, the response includes the monitoring information of the corresponding road monitoring unit forwarded by the cloud server, or the monitoring information after the cloud server processes the monitoring information of the corresponding road monitoring unit. In some embodiments, the monitoring information includes but is not limited to at least one of passing vehicle information, passing vehicle priority, passing vehicle location, passing vehicle heading, and passing vehicle type. In some embodiments, the corresponding road monitoring unit may include all road monitoring units within a preset range in front of the driving direction of the smart driving vehicle, and all road monitoring units within a preset range behind the driving direction of the smart driving vehicle. In the embodiment of the present disclosure, each road monitoring unit periodically or in real time uploads the monitoring information within the monitoring range to the cloud server.

In step 704, the intelligent driving system determines whether there is a passing vehicle that needs to yield on the current road based on the monitoring information. In some embodiments, the passing vehicles may be fire trucks, ambulances, and other vehicles with higher priority than smart driving vehicles. In some embodiments, if there is a passing vehicle based on special circumstances (such as loss of control, taking a life-threatening person, etc.), the priority of the vehicle is increased and the corresponding road monitoring unit is notified. At this time, the passing vehicle may be another vehicle, such as a large truck, Or unmanned vehicles and so on. If there is a priority of a passing vehicle in the monitoring information that is higher than the priority of an intelligent driving vehicle of the current intelligent driving system, a yield needs to be made, and step 705 is executed. If the priority of the passing vehicles in the monitoring information of all the corresponding road monitoring units is not higher than the priority of the smart driving vehicles of the current smart driving system, there is no need to give way and repeat the process of obtaining the corresponding road monitoring unit in step 701 above .

In step 705, the intelligent driving system obtains the yieldable area of the current road based on the state information of the intelligent driving vehicle. In some embodiments, the intelligent driving system obtains the concessionable area of the special road based on the state information and the high-precision map sensed by the sensing module in the intelligent driving vehicle. In some embodiments, the yieldable area is an area displayed on a high-precision map that allows temporary parking. The concession area as described in Fig. 9 shows a polygonal concession area. On an actual road, the shape of the concession area may not be limited to a polygonal shape, but any other shape is acceptable. In some embodiments, the yieldable area acquired by the smart driving system is usually the area closest to the smart driving vehicle of the current smart driving system, and the yieldable area is located in front of the driving direction of the smart driving vehicle.

In step 706, the intelligent driving system determines whether there is a yield point based on the yield area. In some embodiments, it is determined whether there is a yield point based on the yield area and the road network topology. In some embodiments, both the yieldable area and the road network topology are information included in the high-precision map. The road network topology includes road network information corresponding to the yieldable area. Based on the description of the aforementioned high-precision map, the road network information belongs to the information included in the high-precision map. In some embodiments, if there is no yield point in the yield area, step 710 is executed to adjust the priority of the intelligent driving vehicle. If there is a yield point, step 707 is executed.

In step 707, if there is a yield point, the intelligent driving system plans to generate the yield path based on the state information and the yield point. In some embodiments, if there is a yield point, and there is one yield point (as shown in FIG. 9), the yield point is regarded as the reachable yield point. If there are yield points and there are multiple yield points, the yield point closest to the intelligent driving vehicle is selected as the reachable yield point; or if there are multiple yield points, it is based on the passing vehicle and For the position, speed and heading of the intelligent driving vehicle, select a yield point as the reachable yield point. In some embodiments, the intelligent driving system plans to generate the yield path based on the state information and the reachable yield point. At this time, the reachable yield point is used as the destination when planning the yield path. In some embodiments, the reachable yield point is terminal point information used to locate when generating the yield path in the yield area. In some embodiments, the end point in the yield path is the location information of the reachable yield point. In some embodiments, the yield point may be a preset position in the yield area, which belongs to information in a high-precision map or is manually set in advance.

In step 708, the intelligent driving system controls the intelligent driving vehicle to drive along the yield path. In some embodiments, the intelligent driving system controls the intelligent driving vehicle to drive quickly based on the constraints (such as the maximum speed limit) on the current driving road. In some embodiments, the yield path planned by the intelligent driving system is the path with the shortest distance from the current position. In some embodiments, if the smart driving vehicle is driving on a two-way single-lane lane, the yield path is the path that is consistent with the current driving direction of the smart driving vehicle and has the shortest distance from the current position of the smart driving vehicle.

In step 709, the intelligent driving system generates a planned route based on the destination and the current position of the intelligent driving vehicle after completing the yield based on the yield path. In some embodiments, the yield path is the previously planned yield path, and the destination can be understood as the destination before the planned yield path.

In step 710, if there is no yield point in the yieldable area, the smart driving system adjusts the priority of the smart driving vehicle so that the smart driving vehicle becomes a vehicle that other passing vehicles on the current road give way. In some embodiments, after adjusting the priority of the smart driving vehicle, the smart driving system informs other vehicles on the current road of the current priority of the smart driving vehicle through a vehicle-to-vehicle communication method. In some embodiments, after the priority of the intelligent driving vehicle is adjusted, the vehicle-server-vehicle communication method may be used to notify other vehicles on the current special road, such as the reverse vehicle, to give way. For example, after the smart driving system adjusts the priority of the smart driving vehicle, it sends the adjusted priority of the current smart driving vehicle to the server, so that the server will send the adjusted priority to other vehicles on the current road so that other vehicles can pass. The vehicle gives way. In some embodiments, after adjusting the priority of the intelligent driving vehicle, the intelligent driving system sends the adjusted priority of the current intelligent driving vehicle to the corresponding road monitoring unit, so that the corresponding road monitoring unit transfers the adjusted priority to the current It is sent by other vehicles on the road, or the corresponding road monitoring unit reports to the server, so that the server sends the adjusted priority to other vehicles on the current road, so that other vehicles give way.

In the embodiment of the present disclosure, the yield point is determined through the yield area in advance, and then the yield path is planned and generated according to the state information of the smart car and the yield point, so as to better realize the yield path to the smart car Plan to ensure traffic safety and improve traffic efficiency.

Further, for a better understanding, description will be given below with reference to the examples in FIGS. 8A to 8E.

In the embodiment of the present disclosure, the two sides in FIGS. 8A to 8E are two-way two-lane lanes, and the middle section is a two-way single-lane lane. Different yield points are set on the two-way two-lane and the two-way single-lane.

The following is an example of a scenario where vehicles need to be allowed to pass on a special road in advance. In the embodiment of the present disclosure, the passing vehicle is a fire truck with a higher priority than a smart driving vehicle. As shown in FIG. 8A, the smart driving vehicle is in A and B Runs back and forth between points, where,

Section I is a two-way two-lane, Section II is a one-way two-lane, and Section III is a two-way two-lane.

The three RSU-A, RSU-B, and RSU-C are respectively installed in the positions shown in Fig. 8A, and RSU-A, RSU-B, and RSU-C respectively monitor the traffic conditions of vehicles within a certain range of their respective positions. Here RSU can be a camera, lidar or other device that can sense the position, speed, heading, and type of vehicles in the monitoring range.

S1 to S5 in Fig. 8A to Fig. 8E are temporary stop points respectively.

Since Section II is a two-way single-lane, when RSU detects that a high-priority vehicle (take a fire truck as an example) is in this area, the intelligent driving vehicle needs to give way. The specific concession scenarios can be divided into the following four:

1) When the intelligent driving vehicle is in the Section I area and driving toward point B, if the RSU-C detects that the fire truck enters Section I, the intelligent driving vehicle must give way to stop point S1, as shown in Figure 8B.

2) When the intelligent driving vehicle is driving toward point B in Section I area, if there is a fire truck driving toward point A in the Section II area, the intelligent driving vehicle must give way to stop point S1, as shown in Figure 8C.

3) When the intelligent driving vehicle is driving to point B in the Section II area, if there is a fire truck driving to point A or point B in the Section II area, the intelligent driving vehicle must give way to the nearest stop point S2～S5 , If you have left the nearest yield point (ie leave the Section II area immediately), you do not need to yield again, as shown in Figure 8D.

4) When the intelligent driving vehicle is driving to point A in Section II area, if there is a fire truck driving to point A or point B in the section II area, the intelligent driving vehicle must also go to the nearest stop point S2~S5 If you have left the nearest yield point (that is, immediately leave the Section II area), you do not need to yield again, as shown in Figure 8E.

The yield requirement for the above four situations is that the smart driving system of the smart driving vehicle makes decisions based on the monitoring information of the road monitoring unit and plans the yield path to realize the yield operation to the high-priority vehicles and ensure traffic safety.

In the embodiments of the present disclosure, the intelligent driving system makes decisions based on the monitoring information of the road monitoring unit, that is, through effective collaboration between vehicles and roads, not only the sensor of the intelligent driving vehicle is used for sensing, thereby improving traffic efficiency and ensuring traffic safety.

The embodiments of the present disclosure provide a vehicle yielding system, including: a server, the vehicle control device/intelligent driving system/vehicle equipment/smart driving vehicle yielding device mentioned in any of the above disclosed embodiments, and multiple Road monitoring unit.

The road monitoring unit interacts with the server, and the server interacts with the on-board control device/intelligent driving system/on-board equipment/intelligent driving vehicle yielding device. Refer to the descriptions in the foregoing method embodiments. In some embodiments, the smart driving system is a system supported by the on-board equipment, the smart driving vehicle yield device is a component/module in the smart driving system, and the smart driving system is a component/module in the on-board control device.

In some embodiments, the road monitoring unit is used to monitor the passing vehicles within the monitoring range of the road on which the monitoring results include, but are not limited to, the location, speed, heading, type of passing vehicles, etc., and the monitoring results, The location information of the road monitoring unit and the status information of the road monitoring unit (whether it works normally) are uploaded to the server/cloud server in a fixed time period. In some embodiments, the road monitoring unit may be a camera, a lidar, a traffic light, or other equipment capable of acquiring monitoring information within a monitoring range on the road.

The server is used to receive the monitoring information reported by the road monitoring unit in each location, and filter the monitoring information of the corresponding road monitoring unit and send it to the on-board equipment/smart driving system according to the corresponding road monitoring unit reported by the smart driving system.

The intelligent driving system is used to obtain the information of the corresponding road monitoring unit required by the current position and the position information of each road monitoring unit recorded in the high-precision map, and report it to the server.

The intelligent driving system updates whether there are high-priority vehicles in the corresponding area according to the acquired monitoring information, so as to make the corresponding yield decision and generate the corresponding yield path. In some embodiments, the priority of the passing vehicle may be adjusted or set by the intelligent driving system of the passing vehicle, or the priority of the passing vehicle is determined by the road monitoring unit according to the type of the passing vehicle. In some embodiments, the intelligent driving system may be a program running in an in-vehicle device/vehicle control device or a component in an in-vehicle device/vehicle control device. The server is a background server or a control platform or a cloud server.

The embodiments of the present disclosure are applied to special roads. Due to the limited sensing distance of the internal sensors of the vehicle, with the help of the monitoring information provided by the road monitoring unit, a yield action is taken in advance for the high-priority vehicles. Traffic efficiency ensures traffic safety.

In the application, the vehicle yielding system of the embodiment of the present disclosure can improve the traffic efficiency on the road where the intelligent driving vehicle is located, while ensuring the safety of the vehicle.

It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should know that the embodiments of the present disclosure are not affected by the described sequence of actions. Limitation, because according to the embodiments of the present disclosure, some steps can be performed in other order or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the involved actions and modules are not necessarily required by this application.

The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium, which stores a program or instruction, and the program or instruction causes a computer to execute, for example, various embodiments of the intelligent driving vehicle yield method To avoid repeating the description, I won’t repeat them here.

Through the description of the above embodiments, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus the necessary general hardware platform, of course, it can also be implemented by hardware, but in many cases the former is Better implementation. Based on this understanding, the technical solutions of the embodiments of the present disclosure can be embodied in the form of software products in essence or the parts that contribute to the prior art. The computer software products are stored in a storage medium (such as ROM/RAM, magnetic A disc or an optical disc) includes several instructions to make a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) execute the methods described in the various embodiments of the present application.

It should be noted that in this article, the terms "include", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, It also includes other elements not explicitly listed, or elements inherent to the process, method, article, or device. If there are no more restrictions, the element defined by the sentence "including a..." does not exclude the existence of other identical elements in the process, method, article or device that includes the element.

Those skilled in the art can understand that although some embodiments described herein include certain features included in other embodiments but not other features, the combination of features of different embodiments means that they fall within the scope of the present invention And form different embodiments.

Those skilled in the art can understand that the description of each embodiment has its own focus, and for a part that is not described in detail in an embodiment, reference may be made to related descriptions of other embodiments.

Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall under the appended rights. Within the scope defined by the requirements.

Industrial applicability

In the embodiments of the present disclosure, based on the monitoring information of the road monitoring unit, when it is determined that a passing vehicle needs to be yielded, the yield path is planned in advance to realize the yield to the passing vehicle, and the effective coordination between the vehicle and the road improves the passing efficiency and ensures Traffic safety and industrial applicability.

Claims

A method for giving way to an intelligent driving vehicle, wherein the intelligent driving vehicle is traveling on a special road, and the special road is configured with a plurality of road monitoring units, which is characterized in that it comprises:

Judging whether there is a passing vehicle on the special road that requires intelligent driving vehicles to give way;

Based on the existence of passing vehicles that need to yield, determine the yieldable area according to the state information of the intelligent driving vehicle;

Planning and generating a yield path of the smart driving vehicle based on the state information of the smart driving vehicle and the yieldable area;

Control the intelligent driving vehicle to follow the yield path.
The method according to claim 1, wherein the special road includes a two-way single-lane road.
The method according to claim 1, wherein the state information of the intelligent driving vehicle includes position information and heading.
The method according to claim 1, wherein the determining whether there is a passing vehicle that requires an intelligent driving vehicle to yield on the special road comprises:

Determining a corresponding road monitoring unit based on the state information of the intelligent driving vehicle;

Receiving the monitoring information of the corresponding road monitoring unit;

Based on the monitoring information, it is determined whether there is a passing vehicle on the special road that requires an intelligent driving vehicle to give way.
The method according to claim 4, wherein the monitoring information includes at least one of passing vehicle information, passing vehicle priority, passing vehicle location, passing vehicle heading, and passing vehicle type.
The method according to claim 5, characterized in that, based on the monitoring information, judging whether there is a passing vehicle on the special road that requires an intelligent driving vehicle to give way, comprising:

Based on at least one of the priority of the passing vehicle, the location of the passing vehicle, and the heading of the passing vehicle, it is determined whether there is a passing vehicle that requires a smart driving vehicle to yield.
The method according to claim 6, further comprising:

When the priority of the passing vehicle is higher than the priority of the intelligent driving vehicle, the intelligent driving vehicle needs to yield.
The method according to claim 3, wherein the determining the yieldable area according to the state information of the intelligent driving vehicle comprises:

Determining the yieldable area based on the position information of the intelligent driving vehicle and a high-precision map;

Wherein, the high-precision map includes information about a yieldable area.
The method according to claim 1, wherein the planning and generating a yield path of the smart driving vehicle based on the state information of the smart driving vehicle and the yieldable area comprises:

Determine whether there is a yield point based on the yield area;

If there is a yield point, based on the state information and the yield point, plan to generate the yield path.
The method according to claim 9, wherein the determining whether there is a yield point based on the yield area comprises:

Based on the concession area and the road network topology, determine whether there is a concession point;

The road network topology includes road network information corresponding to the yieldable area.
The method according to claim 9 or 10, wherein, if there is a yield point, planning and generating the yield path based on the status information and the yield point includes:

If there are multiple yield points, the yield point closest to the position information of the intelligent driving vehicle is selected as the reachable yield point; or, if there are multiple yield points, it is based on the passing vehicle and the intelligent driving vehicle Select a yield point as the reachable yield point;

Based on the status information and the reachable yield point, plan to generate the yield path.
The method according to claim 9, further comprising:

If there is no yield point, the priority of the smart driving vehicle is adjusted so that the smart driving vehicle becomes a vehicle that other passing vehicles on the special road give way.
The method of claim 1, further comprising:

After the yield is completed based on the yield path, a planned path is generated according to the destination and the current position of the intelligent driving vehicle.
An in-vehicle device, characterized by comprising: a processor and a memory;

The processor is configured to execute the steps of the method according to any one of claims 1 to 13 by calling a program or instruction stored in the memory.
A non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores a program or instruction, and the program or instruction causes a computer to execute the method according to any one of claims 1 to 13 A step of.
An intelligent driving vehicle yielding device, characterized in that the intelligent driving vehicle to which the intelligent driving vehicle yielding device belongs runs on a special road, the special road is configured with a plurality of road monitoring units, and the intelligent driving vehicle yields The device includes:

The yield determination unit is used to determine whether there is a passing vehicle that requires an intelligent driving vehicle to yield on the special road;

A yield path generation unit is used to determine a yieldable area based on the state information of the intelligent driving vehicle based on the existence of a passing vehicle that needs to yield; planning based on the state information of the smart driving vehicle and the yieldable area Generating a yield path of the intelligent driving vehicle;

The yield path driving unit is used to control the intelligent driving vehicle to follow the yield path.
A vehicle giving way system is characterized in that it comprises:

A server, multiple road monitoring units configured on the road, and the intelligent driving vehicle yielding device in claim 16;

The road monitoring unit interacts with the server, and the server interacts with an intelligent driving vehicle yielding device.