Driving control method, collaborative driving method, and related apparatus

Abstract

A driving control method, a collaborative driving method, and a related apparatus. The communication between a vehicle and a roadside sensing apparatus is realized by means of a cloud device, so that when the vehicle cannot sense a first object, the vehicle can acquire sensing information of the first object from the roadside sensing apparatus. The acquired sensing information is fused with sensing information acquired by a sensor of the vehicle so as to expand the sensing range, so that the driving control of the vehicle is realized on the basis of the fused sensing information, thereby effectively reducing the driving potential safety hazard of the vehicle.

Description

Driving control method, cooperative driving method and related devices

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office of China on February 28, 2024, with application number 202410225645.9, and priority to the Chinese patent application entitled “Driving Control Method, Collaborative Driving Method and Related Devices”, all contents of which are incorporated by reference into this application. Technical Field

[0002] The present application relates to the field of intelligent driving technology, and in particular to a driving control method, a collaborative driving method, and related devices. Background Art

[0003] Currently, there are two main approaches to achieving intelligent driving: single-vehicle intelligent driving and vehicle-road collaborative intelligent driving. In terms of single-vehicle intelligent driving, intelligent driving technology centered around single-vehicle intelligence has already been integrated into products with Level 2 assisted driving capabilities. However, single-vehicle intelligent driving, which relies solely on the vehicle's own sensor detection, signal feedback, and actuators to complete commands, makes it difficult for the vehicle to promptly avoid threats outside the sensor's perception range, resulting in reduced driving safety. Therefore, single-vehicle intelligent driving has significant limitations in the development of high-level intelligent driving. Achieving intelligent driving through vehicle-road collaboration can further reduce the risk and probability of accidents based on single-vehicle intelligence and can also better evolve to high-level intelligent driving.

[0004] Solutions for vehicle-infrastructure collaboration have been around for many years, and corresponding communication standards have been established. However, the current implementation cost of vehicle-infrastructure collaboration is high, and its practical application faces difficulties. Summary of the Invention

[0005] The embodiments of the present application provide a driving control method, a collaborative driving method and related devices, which can effectively reduce vehicle driving safety hazards and have low implementation costs and are easy to promote and use.

[0006] In a first aspect, the present application provides a driving control method, which includes: obtaining first information from a cloud device; the first information includes perception information of a first object by a roadside perception device; obtaining first fusion information based on the first information and the first perception information; and performing a first driving control based on the first fusion information; wherein the first perception information includes perception information obtained by sensors of the vehicle; when the vehicle perceives the first object based on second perception information, performing a second driving control based on the second perception information; the second perception information includes perception information of the first object obtained by sensors of the vehicle.

[0007] Exemplarily, the aforementioned roadside sensing device is deployed on a driving blind spot section in the forward direction of the aforementioned vehicle, and the sensing range of the aforementioned roadside sensing device covers the aforementioned driving blind spot section; the aforementioned driving blind spot section includes one or more of the following: a curved road section, a road section including an intersection, a road section including an entrance or exit, or a slope top section.

[0008] In the above solution, the roadside sensing device can sense objects outside the vehicle's perception range and transmit the object's perception information to the vehicle via a cloud device for perception fusion. If the vehicle itself can sense the object, it uses its own perception to achieve driving control, saving resources for fusion computing. The roadside sensing device is used as a perception blind spot device for the vehicle, allowing the vehicle to obtain information outside the perception range, thereby gaining a more comprehensive understanding of the driving environment and reducing safety hazards. In addition, this solution does not require direct vehicle-road communication, eliminating the need for the deployment of on-board units (OBUs) and roadside units (RSUs), thereby significantly saving costs.

[0009] In one possible implementation, the aforementioned first object includes one or more target vehicles, and the aforementioned first information includes perception information of the aforementioned one or more target vehicles by the aforementioned roadside perception device.

[0010] In the above solution, the vehicle can obtain the perception information of the target vehicle by the roadside sensing device through the cloud, thereby expanding the vehicle's perception range and facilitating blind spot filling.

[0011] In one possible implementation, the method further includes: obtaining second information from a cloud device; the second information indicates perception information of the roadside perception device on a second object; the second object includes one or more pedestrians; and discarding the second information.

[0012] In the above scheme, since the accuracy of pedestrian information perceived by the roadside sensing device is not high, discarding it can reduce interference with subsequent fusion and driving control.

[0013] In one possible implementation, the method further includes: obtaining third information from the cloud device; the third information indicates the perception information of the roadside perception device on the first object when the vehicle perceives the first object; the second driving control is performed based on the second perception information of the vehicle itself, including: fusing the third information and the second perception information according to a preset weight ratio to obtain second fused information; the weight ratio of the second perception information is greater than the weight ratio of the third information; and the second driving control is performed based on the second fused information.

[0014] In the above scheme, the roadside perception and the vehicle's own perception are integrated through the weight ratio. On the one hand, it expands the vehicle's perception range. On the other hand, the vehicle's own perception weight ratio is relatively high, which can improve the confidence of perception fusion.

[0015] In one possible implementation, the method further includes: obtaining fourth information from a cloud device; the fourth information indicates the perception information of the roadside perception device on the first object when the vehicle perceives the first object; calibrating the fourth information according to the second perception information to obtain a calibration result; and sending the calibration result, which is used to correct the perception confidence of the roadside perception device.

[0016] In the above scheme, the vehicle can calibrate the roadside perception information based on its own perception information. The calibrated roadside perception information can be used to correct the perception confidence of the roadside perception device and improve the detection accuracy of the roadside perception device.

[0017] In one possible implementation, when the aforementioned vehicle perceives the aforementioned first object, or when the aforementioned first object leaves the perception range of the aforementioned roadside perception device, the aforementioned method further includes: obtaining fifth information from the aforementioned cloud device; the aforementioned fifth information instructs the aforementioned vehicle to turn off a roadside perception fusion function, and the aforementioned roadside perception fusion function is a function of fusing the perception information of the aforementioned roadside perception device and the perception information of the aforementioned vehicle.

[0018] In the above scheme, if there is no threatening object within the perception range of the roadside perception device or the vehicle can perceive the threatening object, the vehicle can turn off the roadside fusion perception function and restore the single-vehicle perception driving mode to reduce the fusion calculation overhead.

[0019] In one possible implementation, the aforementioned obtaining of the first information from the cloud device includes: obtaining the aforementioned first information when the aforementioned vehicle cannot perceive the aforementioned first object and the aforementioned first object satisfies a first condition; the aforementioned first condition includes: the distance between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset distance, and / or the collision time between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset duration.

[0020] In the above solution, the roadside perception information is obtained only when the first object threatens the driving safety of the vehicle, which can save transmission bandwidth.

[0021] In a second aspect, the present application provides a collaborative driving method, which includes: obtaining vehicle status information from a vehicle; the aforementioned vehicle status information includes position information and speed information of the aforementioned vehicle; obtaining first information; the aforementioned first information indicates the perception information of the roadside perception device on the first object; determining that the aforementioned first object meets a first condition based on the aforementioned vehicle status information and the aforementioned first information; the aforementioned first condition includes: the distance between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset distance, and / or the collision time between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset duration; and sending the aforementioned first information to the aforementioned vehicle.

[0022] In the above solution, the cloud device can obtain the vehicle's information and the roadside device's perception information of the first object, and then determine whether the conditions for sending the perception information of the first object to the vehicle are met, and send it only if they are met. That is, in this solution, through the forwarding of the cloud device, the roadside perception device can be used as a perception blind spot device for the vehicle, allowing the vehicle to obtain information outside the perception range, thereby gaining a more comprehensive understanding of the driving environment and reducing safety hazards. In addition, this solution does not require direct vehicle-road communication, saving the deployment of the on-board unit OBU and the roadside unit RSU, thereby greatly saving costs. Furthermore, the cloud only sends information to the vehicle when the conditions are met, which can save transmission bandwidth.

[0023] In one possible implementation, the method further includes: obtaining second information from the roadside perception device; the second information indicates the perception information of the roadside perception device on the first object when the vehicle perceives the first object; sending the second information to the vehicle; obtaining third information from the vehicle; the third information is a calibration result obtained by calibrating the second information based on the perception information of the vehicle itself; sending the calibration result to the roadside perception device; the calibration result is used to correct the perception confidence of the roadside perception device.

[0024] In the above scheme, communication between the vehicle and the roadside perception device is achieved through the cloud, so that the vehicle can calibrate the roadside perception information based on its own perception information. The calibrated roadside perception information can be used to correct the perception confidence of the roadside perception device and improve the detection accuracy of the roadside perception device.

[0025] In one possible implementation, when the aforementioned vehicle perceives the aforementioned first object, or when the aforementioned first object leaves the perception range of the aforementioned roadside perception device, the aforementioned method further includes: sending fourth information to the aforementioned vehicle; the aforementioned fourth information instructs the aforementioned vehicle to turn off the roadside perception fusion function, and the aforementioned roadside perception fusion function is a function of fusing the perception information of the aforementioned roadside perception device and the perception information of the aforementioned vehicle.

[0026] Exemplarily, the aforementioned method also includes: obtaining fifth information from the aforementioned roadside perception device; the aforementioned fifth information indicates that the aforementioned first object has left the perception range of the aforementioned roadside perception device; and triggering an operation of sending the aforementioned fourth information to the aforementioned vehicle based on the aforementioned fifth information.

[0027] In the above scheme, if there is no threatening object in the perception range of the roadside perception device or the vehicle can perceive the threatening object, it can instruct the cloud device, and the cloud device can notify the vehicle to turn off the roadside fusion perception function, restore the single-vehicle perception driving mode, and reduce the fusion calculation overhead.

[0028] On the third aspect, the present application provides a collaborative driving method, which is applied to a roadside perception device, and the method includes: obtaining first perception information; the first perception information includes perception information of a first object and perception information of the vehicle; identifying whether the first object threatens the driving safety of the vehicle based on the first perception information; sending first information to a cloud device, the first information indicating the perception information of the roadside perception device on the first object, and the first information being used to send to the vehicle.

[0029] In this solution, the roadside sensing device communicates with the vehicle via the cloud, enabling the roadside sensing device to serve as a blind spot sensor for the vehicle, allowing the vehicle to obtain information beyond its sensing range, thereby providing a more comprehensive understanding of the driving environment and mitigating safety hazards. Furthermore, this solution eliminates the need for direct vehicle-road communication, eliminating the need for onboard vehicle units (OBUs) and roadside units (RSUs), significantly reducing costs. Furthermore, the roadside sensing system can automatically determine if a safety risk exists before sending information, saving data transmission bandwidth.

[0030] In one possible implementation, the method further includes: sending second information to the cloud device; the second information indicates the perception information of the roadside perception device on the first object when the vehicle perceives the first object; obtaining a calibration result from the cloud device; the calibration result is used to correct the perception confidence of the roadside perception device, and the calibration result is a calibration result obtained by the vehicle calibrating the second information based on its own perception information.

[0031] In the above scheme, communication between the vehicle and the roadside perception device is achieved through the cloud, so that the vehicle can calibrate the roadside perception information based on its own perception information. The calibrated roadside perception information can be used to correct the perception confidence of the roadside perception device and improve the detection accuracy of the roadside perception device.

[0032] In one possible implementation, the method further includes: sending a third information to the cloud device; the third information indicates that the first object has left the perception range of the roadside perception device; the third information is used to trigger the cloud device to send the fourth information to the vehicle, and the fourth information indicates that the vehicle turns off a roadside perception fusion function, and the roadside perception fusion function is a function of fusing the perception information of the roadside perception device on the first object and the perception information of the vehicle.

[0033] In the above scheme, if there is no threatening object within the perception range of the roadside perception device or the vehicle can perceive the threatening object, it can instruct the cloud, and the cloud can notify the vehicle to turn off the roadside fusion perception function, restore the single-vehicle perception driving mode, and reduce the fusion computing overhead.

[0034] In a fourth aspect, the present application provides a vehicle, comprising a unit for implementing any of the methods described in the first aspect.

[0035] In a fifth aspect, the present application provides a cloud device, which includes a unit for implementing the method described in any one of the second aspects above.

[0036] In a sixth aspect, the present application provides a roadside perception device, which includes a unit for implementing the method described in any one of the third aspects above.

[0037] In a seventh aspect, the present application provides a vehicle comprising a processor and a memory. The memory is coupled to the processor, and when the processor executes a computer program or computer instructions stored in the memory, the method described in any one of the first aspects can be implemented. The vehicle may also include a communication interface for communicating with other vehicles. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0038] In one possible implementation, the vehicle may include:

[0039] Memory for storing computer programs or computer instructions;

[0040] A processor, configured to: obtain first information from a cloud device; the first information includes perception information of a first object by a roadside perception device; obtain first fusion information based on the first information and the first perception information; and perform first driving control based on the first fusion information; wherein the first perception information includes perception information obtained by sensors of the vehicle; and perform second driving control based on the second perception information when the vehicle perceives the first object based on second perception information; the second perception information includes perception information of the first object obtained by sensors of the vehicle.

[0041] It should be noted that the computer programs or computer instructions in the memory of this application may be pre-stored or downloaded from the Internet and stored when the vehicle is used. This application does not specifically limit the source of the computer programs or computer instructions in the memory. The coupling in the embodiments of this application is an indirect coupling or connection between devices, units, or modules, which may be electrical, mechanical, or other forms, and is used for information exchange between devices, units, or modules.

[0042] In an eighth aspect, the present application provides a cloud device comprising a processor and a memory. The memory is coupled to the processor, and when the processor executes a computer program or computer instructions stored in the memory, the method described in any one of the second aspects above can be implemented. The cloud device may also include a communication interface for communicating between the cloud device and other cloud devices. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0043] In one possible implementation, the cloud device may include:

[0044] Memory for storing computer programs or computer instructions;

[0045] A processor, configured to: obtain vehicle status information from a vehicle; the aforementioned vehicle status information includes position information and speed information of the aforementioned vehicle; obtain first information; the aforementioned first information indicates perception information of a first object by a roadside perception device; determine, based on the aforementioned vehicle status information and the aforementioned first information, that the aforementioned first object satisfies a first condition; the aforementioned first condition includes: the distance between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset distance, and / or the collision time between the aforementioned first object and the aforementioned vehicle is less than or equal to a first preset duration; and send the aforementioned first information to the aforementioned vehicle via a communication interface.

[0046] It should be noted that the computer programs or computer instructions in the memory of this application can be pre-stored or downloaded from the Internet when using the cloud device. This application does not specifically limit the source of the computer programs or computer instructions in the memory. The coupling in the embodiments of this application is an indirect coupling or connection between devices, units or modules, which can be electrical, mechanical or other forms, and is used for information exchange between devices, units or modules.

[0047] In a ninth aspect, the present application provides a roadside perception device, comprising a processor and a memory. The memory is coupled to the processor, and when the processor executes a computer program or computer instructions stored in the memory, the method described in any one of the third aspects can be implemented. The roadside perception device may also include a communication interface for communicating with other roadside perception devices. Exemplarily, the communication interface may be a transceiver, circuit, bus, module, or other type of communication interface.

[0048] In one possible implementation, the roadside sensing device may include:

[0049] Memory for storing computer programs or computer instructions;

[0050] The processor is used to: obtain first perception information; the aforementioned first perception information includes perception information of a first object and perception information of the aforementioned vehicle; identify whether the aforementioned first object threatens the driving safety of the aforementioned vehicle based on the aforementioned first perception information; send first information to a cloud device through a communication interface, the aforementioned first information indicating the perception information of the aforementioned first object by the aforementioned roadside perception device, and the aforementioned first information is used to be sent to the aforementioned vehicle.

[0051] It should be noted that the computer programs or computer instructions in the memory of this application may be pre-stored or downloaded from the Internet and stored when the roadside sensing device is used. This application does not specifically limit the source of the computer programs or computer instructions in the memory. The coupling in the embodiments of this application is an indirect coupling or connection between devices, units, or modules, which may be electrical, mechanical, or other forms, and is used for information exchange between devices, units, or modules.

[0052] In a tenth aspect, the present application provides a collaborative driving system, comprising a vehicle, a cloud device, and a roadside sensing device; wherein the vehicle is the vehicle described in any one of the fourth aspect, the cloud device is the cloud device described in any one of the fifth aspect, and the roadside sensing device is the roadside sensing device described in any one of the sixth aspect.

[0053] Alternatively, the aforementioned vehicle is the vehicle described in any one of the seventh aspects, the aforementioned cloud device is the cloud device described in any one of the eighth aspects, and the aforementioned roadside sensing device is the roadside sensing device described in any one of the ninth aspects.

[0054] In an eleventh aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method described in any one of the first aspects above.

[0055] In a twelfth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method described in any one of the second aspects above.

[0056] In a thirteenth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method described in any one of the third aspects above.

[0057] In a fourteenth aspect, the present application provides a computer program product. When the aforementioned computer program product is executed by a processor, the method described in any one of the aforementioned first aspects will be implemented.

[0058] In a fifteenth aspect, the present application provides a computer program product. When the aforementioned computer program product is executed by a processor, the method described in any one of the aforementioned second aspects will be implemented.

[0059] In a sixteenth aspect, the present application provides a computer program product. When the aforementioned computer program product is executed by a processor, the method described in any one of the aforementioned third aspects will be implemented.

[0060] The solutions provided in the above-mentioned fourth to sixteenth aspects are used to implement or cooperate with the corresponding methods provided in the above-mentioned first, second or third aspects, and therefore can achieve the same or corresponding beneficial effects as the corresponding methods in the first, second or third aspects, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figures 1 and 2 are schematic diagrams of a cooperative driving system provided by an embodiment of the present application;

[0062] FIG3 and FIG3A are schematic diagrams of an application scenario architecture provided by an embodiment of the present application;

[0063] Figures 4 to 8 are schematic diagrams of application scenarios provided by embodiments of the present application;

[0064] FIG9 is a schematic diagram of a method flow chart provided in an embodiment of the present application;

[0065] 10 to 13 are schematic diagrams showing the structure of the device provided in the embodiments of the present application. DETAILED DESCRIPTION

[0066] The following describes the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. The terms "first", "second", "third" and "fourth" in the specification and claims of this application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units that are inherent to these processes, methods, products or devices. Mentioning "embodiment" in this article means that the specific features, structures or characteristics described in conjunction with the embodiment may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is understood explicitly and implicitly by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0067] The various embodiments of this application are, on the one hand, independent of each other, meaning that the embodiments do not restrict or constrain each other. On the other hand, unless otherwise specified or logically conflicting, the terms and / or descriptions of the various embodiments are consistent and can be referenced across them. Technical features from different embodiments can be combined to form new embodiments based on their inherent logical relationships.

[0068] The embodiments of the present application are exemplarily introduced below with reference to the accompanying drawings.

[0069] First, the technical problem to be solved by the embodiments of the present application is introduced. In existing implementation schemes, in order to further reduce the risk and probability of driving accidents on the basis of single-vehicle intelligence, more information on the road environment is obtained through vehicle-road collaboration to assist vehicles in driving more safely. However, in this existing solution, one implementation method is the V2X vehicle-road collaboration solution. In this solution, the vehicle's own vehicle information can be collected by deploying a V2X device (i.e., an on-board unit (OBU)) on the vehicle and broadcast through a basic safety message (BSM). After the roadside device (i.e., the road side unit (RSU)) receives the BSM message from the surrounding vehicles, it performs relevant traffic analysis on the movement status of the surrounding vehicles. At the same time, other vehicles can subscribe to relevant roadside data and select the appropriate road environment to alleviate traffic congestion and reduce the accident rate. However, in this solution, in order to achieve better traffic information release, a large number of RSU devices need to be deployed along the road. This makes deployment in the vehicle-road collaboration solution difficult and has a very high deployment cost, making it difficult to promote on a large scale.

[0070] Another existing solution combines vehicle trajectory information to determine vehicle status, generating a trajectory using vehicle information from multiple roadside RSUs. This trajectory information is then transmitted to other vehicles via the RSUs, enabling them to make more accurate driving decisions. However, this solution primarily relies on generating a trajectory using vehicle information acquired by multiple RSUs, which is then transmitted to other vehicles to ensure safe driving and avoid collisions. This implementation also requires the deployment of a large number of RSUs along the road.

[0071] According to the above description, it can be seen that the existing implementation scheme is difficult to implement in actual application. Specifically, from the perspective of the roadside, it is necessary to continuously deploy RSU on the road, which results in very high deployment costs. From the perspective of the vehicle, it is necessary to deploy OBU-related equipment on the vehicle side to achieve roadside communication, which also increases the cost of purchasing the vehicle and increases the vehicle failure points. On the other hand, since a special spectrum is required to achieve vehicle-road communication through RSU and OBU. The communication spectrum requirements are different in different countries, which also leads to different implementations of vehicle-road collaboration solutions in different countries. It also increases the deployment certification requirements of RSU and vehicles in different countries, thereby increasing the cost overhead caused by certification.

[0072] Therefore, in order to solve the above-mentioned problem that the existing solutions are high in implementation cost and difficult to implement in practical applications, the embodiments of the present application provide corresponding methods and related devices.

[0073] The following first introduces the cooperative driving system provided in the embodiment of the present application by way of example.

[0074] Please refer to Figure 1, which is a schematic diagram of the structure of a collaborative driving system 100 provided in an embodiment of the present application. The collaborative driving system 100 includes a cloud device 101, a vehicle 102, and a roadside sensing device 103. There can be one or more vehicles 102 and roadside sensing devices 103, and this embodiment of the present application does not limit this.

[0075] Exemplarily, the cloud device 101 may include, for example, a cloud server and / or a cloud virtual machine, and other devices capable of performing calculations and / or data processing. Alternatively, the cloud device 101 may include, for example, a server cluster. The cloud device 101 may communicate with the vehicle 102 and provide a variety of services for the vehicle 102. For example, it may provide the vehicle 102 with over the air (OTA) service, high-precision map service, autonomous driving or assisted driving service, and information forwarding service. In addition, the cloud device 101 may also communicate with the roadside sensing device 103 and provide a variety of services for the roadside sensing device 103. For example, it may provide the roadside sensing device 103 with information analysis and processing services, or information forwarding services.

[0076] By way of example, the vehicle 102 can be any type of vehicle traveling on the road. For example, it can be a car, a bus, a truck, a fire truck, a police car, a sanitation truck, a concrete truck, a semi-trailer, a garbage truck, or a forklift. The vehicle 102 can be driven using intelligent driving technologies such as assisted driving or autonomous driving. The vehicle 102 is equipped with a detection device for detecting and sensing the environment around the vehicle 102. By way of example, the detection device can include sensors such as a camera or a radar. The radar can include various types of radars such as ultrasonic radar, laser radar, millimeter wave radar, or microwave radar, but this embodiment of the present application does not limit this. Each detection device has its own detection range. The detection device can sense objects within the detection range. In this embodiment of the present application, if a detection device cannot sense an object, it is considered that the object is not within the detection range of the detection device. The detection range can also be referred to as the perception range. The superposition of the detection ranges of one or more detection devices installed in the vehicle 102 is the perception range of the vehicle 102.

[0077] For example, vehicle 102 can interact with cloud device 101 to enhance intelligent driving capabilities, thereby improving vehicle safety and travel efficiency. For example, vehicle 102 can collect road and surrounding vehicle information using sensors installed on the vehicle body, and upload this information, along with its own driving status information, to cloud device 101. Vehicle 102 can also receive information from cloud device 101 to assist in its own driving.

[0078] By way of example, the roadside sensing device 103 may be a sensing device deployed on both sides of the road. The roadside sensing device 103 may include, for example, a detection device such as a camera or radar. The radar may include, for example, various types of radars, such as ultrasonic radar, lidar, millimeter-wave radar, or microwave radar, though this embodiment of the present application does not limit this. By way of example, in one possible implementation, the roadside sensing device 103 may also include a perception computing unit. This perception computing unit processes and analyzes data sensed by the sensors to obtain analyzed information. The roadside sensing device 103 may interact with the cloud device 101 to transmit the obtained information to the cloud device 101. The roadside sensing device 103 also has its own detection range (actually, the detection range of a detection device such as a camera or radar). The detection device can sense objects within this detection range. In this embodiment of the present application, if a detection device cannot sense an object, it is considered to be outside the detection range of the detection device. This detection range may also be referred to as the perception range of the roadside sensing device 103. By way of example, the perception computing unit of the roadside sensing device 103 may be integrated with the sensor. Alternatively, the perception computing unit may be an independent device or module capable of communicating with the sensor.

[0079] For example, the vehicle 102 and roadside sensing device 103 can communicate with the cloud device 101 via wired or wireless communication. This embodiment of the present application uses wireless communication as an example. For an example, see Figure 2 . As shown in Figure 2 , the vehicle 102 and roadside sensing device 103 access a communication network 104 via wireless communication. The communication network 104 transmits information from the vehicle 102 and / or roadside sensing device 103 to the cloud device 101.

[0080] Exemplarily, the communication network 104 includes a wireless access device. The vehicle 102 and the roadside sensing device 103 can access the communication network 104 through the wireless access device. The wireless access device may include, for example, a macro base station, a micro base station (also known as a small station), a relay station, an access point (such as an access node in a WiFi system), a cell, etc. Exemplary base stations may be evolutionary node Bs (eNBs) and next-generation node Bs (gNBs) in 5G systems and new radio (NR) systems. In addition, the base station may also be a transmission receive point (TRP), a central unit (CU), or other network entities. In addition, in a distributed base station scenario, the wireless access device may be a baseband processing unit (BBU) and a remote radio unit (RRU), and in a cloud radio access network (CRAN) scenario, it may be a baseband pool (BBU pool) and a radio unit (RRU). Alternatively, the wireless access device may also be an access network device or a module of an access network device in an open access network (open RAN, ORAN) system. Exemplarily, the wireless access device may be a module or unit that can implement some functions of a base station. For example, the wireless access device may be a centralized unit (CU), a distributed unit (DU), a CU-control plane (CP), a CU-user plane (UP), or a radio unit (RU), etc. In the ORAN system, the CU may also be referred to as an O-CU, the DU may also be referred to as an open (open, O)-DU, the CU-CP may also be referred to as an O-CU-CP, the CU-UP may also be referred to as an O-CUP-UP, and the RU may also be referred to as an O-RU. It will be understood that this is only an example, and the embodiments of the present application do not limit the specific technology and specific device form adopted by the wireless access device.

[0081] Exemplarily, the communication network 104 further includes a network device. The network device is connected to the wireless access device and is used to forward the information received by the wireless access device from the vehicle 102 and / or the roadside sensing device 103 to the cloud device 101. In addition, it is understood that the cloud device 101 can send information to the vehicle 102 and / or the roadside sensing device 103 through the communication network 104. The network device may include, for example, a router, a switch, a wireless relay device or a wireless backhaul device, etc. It is understood that this is only an example, and the embodiments of the present application do not limit the specific technology and specific device form adopted by the network device.

[0082] In order to further understand the possible application scenario architecture of the embodiment of the present application, please refer to Figure 3 for example. In Figure 3, the cloud device 101 is deployed with software systems such as a transport operation management system (fleet management system, FMS), a high-precision map service system, a vehicle dispatching service system, a vehicle operation supervision service system, an emergency takeover service system and an intelligent driving system. For example, the transport operation management system can integrate the information provided by one or more of the high-precision map service system, the vehicle dispatching service system, the vehicle operation supervision service system, the emergency takeover service system and the intelligent driving system to achieve vehicle operation management and / or control. For example, the various service systems of the cloud device 101 can receive information from the vehicle 102 and / or the roadside sensing device 103 through the communication network 104, and integrate the received information into the transport operation management system to achieve vehicle operation management and / or control. The relevant management and / or control information is also sent to the vehicle through the communication network 104 to realize vehicle-road-cloud intelligent driving.

[0083] The above-mentioned intelligent driving system can be used to cooperate with the intelligent driving of vehicle 102. In the embodiment of the present application, it can be used to cooperate with the operation of the cloud device in the intelligent driving method provided in the embodiment of the present application. For details, please refer to the subsequent introduction and will not be described in detail here.

[0084] In FIG3 above, an on-board intelligent driving system is deployed in the vehicle 102. For example, an assisted driving system or an automatic driving system is deployed. The on-board intelligent driving system can realize functions such as perception, positioning, decision-making, planning (such as path planning) or control. These functions can be realized by sensors such as radars or cameras, hardware such as telematics boxes (T-BOX) or wire-controlled chassis, and the cooperation of on-board computing units. For example, the software of the on-board intelligent driving system can be deployed in a vehicle domain controller (VDC), a cockpit domain controller (CDC), a mobile data center (MDC) or other processing and control modules, and the embodiments of the present application are not limited to this.

[0085] In the above-mentioned FIG3 , the roadside perception device 103 includes a sensor and a perception computing unit. Please refer to the corresponding introduction in the above-mentioned FIG1 for details, which will not be repeated here.

[0086] In one possible implementation, in FIG3 above, the vehicle 102 and the roadside sensing device 103 may further include a device for communicating with the cloud device 101. For example, a communication device or module such as Customer Premise Equipment (CPE) may be included. The communication device or module may be connected to the communication network 104 to communicate with the cloud device 101. The embodiment of the present application does not limit the communication device or module. For example, take CPE as an example. CPE devices are mainly divided into two types: wired CPE and wireless CPE. Wired CPE generally uses Ethernet as the data transmission medium and supports access methods such as passive optical network (PON), very / ultra-high-bit-rate digital subscriber loop (VDSL), and asymmetric digital subscriber line (ADSL). Wireless CPE can directly access 4G or 5G networks, or access wired networks through external antennas, wireless APs, wireless base stations or routers.

[0087] In one possible implementation, an example can be seen in FIG3A . As can be seen in FIG3A , the CPE in the roadside sensing device 103 can communicate with the cloud device 101 through wired communication. For example, the CPE in the roadside sensing device 103 and the cloud device 101 can be connected via optical fiber to achieve data transmission. In addition, the CPE in the vehicle 102 can access the base station wirelessly and then communicate with the cloud device 101 via the core network. It will be understood that FIG3A is only an example and does not constitute a limitation to the embodiments of the present application.

[0088] It is understood that the above-mentioned FIG3 is merely an example and does not constitute a limitation on the embodiments of the present application. In a specific implementation, the cloud device 101, vehicle 102, or roadside sensing device 103 may include more or fewer hardware components or software units, or may be replaced with modules that can achieve the same functions, etc., and the specific configuration can be based on actual application requirements, and the embodiments of the present application do not impose any restrictions on this.

[0089] In one possible implementation, to reduce deployment costs, the roadside sensing device 103 can be deployed in blind spots on the road. These blind spots include sections that are beyond the vehicle's sensing range and are prone to accidents that threaten vehicle driving safety. For example, these blind spots can include curved sections, sections at intersections, sections at entrances or exits, or sections at the top of slopes, etc. It is understood that the size of these blind spots can be determined based on the specific circumstances of the actual application scenario, and this embodiment of the present application does not impose any restrictions on this.

[0090] Illustratively, the curved road section may be any curved road section, and the embodiment of the present application does not limit this.

[0091] Exemplarily, the above-mentioned road sections including intersections may include cross-shaped intersections, roundabout intersections, X-shaped intersections, T-shaped intersections, Y-shaped intersections, staggered intersections, multi-way intersections, etc.

[0092] For example, the road section including an entrance or exit may include a tunnel entrance or exit, a residential area entrance or exit, a garage or parking lot entrance or exit, and the like.

[0093] Exemplarily, the above-mentioned top section may include an uphill top section or a downhill top section, etc.

[0094] In order to facilitate understanding of the application scenario of the above-mentioned roadside perception device 103 being deployed in a driving blind spot section on the road, you can refer to Figures 4 to 8 for examples.

[0095] FIG4 exemplarily shows a schematic diagram of an application scenario in which the driving blind spot section is a curved road section. It can be seen that the perception range of vehicle 102 is limited, and it cannot perceive objects in the curved road section (such as vehicle A). Therefore, a roadside perception device 103 is deployed on the curved road section. The perception range of the roadside perception device 103 can cover the curved road section, so it can perceive objects in the curved road section (such as vehicle A). It can be understood that one or more roadside perception devices 103 can be deployed in the curved road section (the one shown in FIG4 is only an example), and the specific number of deployments is not limited in the embodiment of the present application. In addition, the roadside perception device 103 can be deployed on either side of the curved road section, or can be deployed on both sides of the curved road section, depending on the actual application deployment, and the embodiment of the present application does not limit this.

[0096] Figure 5 exemplarily shows a schematic diagram of an application scenario in which a driving blind spot section is a section including an intersection (referred to as the intersection section). It can be seen that the perception range of vehicle 102 is limited and it cannot perceive objects in the intersection section (such as vehicle A). Therefore, a roadside perception device 103 is deployed in the intersection section. The perception range of the roadside perception device 103 can cover the intersection section, so it can perceive objects in the intersection section (such as vehicle A). It is understandable that one or more roadside perception devices 103 can be deployed in the intersection section (the one shown in Figure 5 is only an example), and the specific number of deployments is not limited in this embodiment of the application. In addition, the roadside perception device 103 can be deployed at any position on both sides of the road in the intersection section, and the specific deployment is based on the actual application, which is not limited in this embodiment of the application.

[0097] Figure 6 exemplarily shows a schematic diagram of an application scenario in which a driving blind spot section includes a tunnel entrance section. It can be seen that the perception range of the vehicle 102 is limited and it cannot perceive objects in the tunnel entrance section (such as static obstacle A). Therefore, a roadside perception device 103 is deployed in the tunnel entrance section. The perception range of the roadside perception device 103 can cover the tunnel entrance section, so it can perceive objects in the tunnel entrance section (such as static obstacle A). It can be understood that one or more roadside perception devices 103 can be deployed in the tunnel entrance section (the one shown in Figure 6 is only an example), and the specific number of deployments is not limited in this embodiment of the application. In addition, the roadside perception device 103 can be deployed at any position on both sides of the road in the tunnel entrance section, and the specific deployment is based on the actual application, which is not limited in this embodiment of the application.

[0098] Figures 7 and 8 exemplify a schematic diagram of an application scenario in which a driving blind spot section includes a hilltop section. Figure 7 shows a schematic diagram of a scenario in which vehicle 102 is going uphill, and Figure 8 shows a schematic diagram of a scenario in which vehicle 102 is going downhill. It can be seen that the perception range of vehicle 102 is limited and it cannot perceive objects in the hilltop section (such as vehicle A). Therefore, a roadside sensing device 103 is deployed in the hilltop section. The perception range of the roadside sensing device 103 can cover the hilltop section, so it can perceive objects in the hilltop section (such as vehicle A). It is understandable that one or more roadside sensing devices 103 can be deployed in the hilltop section (the one shown in Figure 6 is only an example), and the specific number of deployments is not limited in this embodiment of the application. In addition, the roadside sensing device 103 can be deployed at any position on both sides of the road in the hilltop section, and the specific deployment is based on the actual application, and the embodiment of the application does not limit this.

[0099] While Figures 4 to 8 illustrate the vehicle 102 primarily on the blind spot, in another implementation, the vehicle 102 may be traveling on a road area outside the blind spot, such as when the vehicle 102 is traveling toward the blind spot but has not yet entered the blind spot.

[0100] It is understood that the application scenarios shown in Figures 4 to 8 are merely examples and do not constitute a limitation on the embodiments of the present application. In specific implementations, other application scenarios for driving blind spots may also be included, which are not listed one by one in the embodiments of the present application.

[0101] For example, in combination with the cooperative driving system described above, the method provided by the embodiment of the present application is described below. With reference to FIG9 , the method may include but is not limited to the following steps.

[0102] S901. A roadside sensing device obtains first information.

[0103] Exemplarily, the roadside sensing device may be, for example, the roadside sensing device 103 in the above-mentioned collaborative driving system 100. The vehicle may be, for example, the vehicle 102 in the collaborative driving system 100. The vehicle may be a vehicle traveling toward a blind spot section. The blind spot section may be, for example, any one of the blind spot sections described above, which will not be described in detail here. The roadside sensing device is deployed on the blind spot section, and the specific deployment application scenarios may be exemplified by referring to FIG. 4 or FIG. 8 above, which will not be described in detail here. For example, the roadside sensing device may include one or more sensing devices deployed on the blind spot section.

[0104] In a specific implementation, the perception range of the above-mentioned roadside perception device can cover the above-mentioned blind spot section, so that the objects in the blind spot section can be perceived (including the above-mentioned first object, which can be, for example, one or more objects in the blind spot section). Exemplarily, the objects in the blind spot section can include moving objects and stationary objects. The moving objects include, for example, vehicles, pedestrians, animals, or any objects that move in the blind spot section. The stationary objects include, for example, static obstacles such as mounds in the blind spot section, signboards temporarily blocked due to construction or other reasons, vehicles that have stopped due to accidents, or other objects placed on the road. It will be understood that the objects introduced here are only examples and do not constitute a limitation on the embodiments of the present application. Other objects may also be included in the specific implementation, and the embodiments of the present application do not impose any limitation on this.

[0105] For example, in one possible implementation, the sensor in the roadside perception device can detect objects in the blind spot section of the road and obtain detection data. For example, if the sensor is a camera, the detection data can be image data captured by the camera. Or, for example, if the sensor is a radar, the detection data can be point cloud data detected by the radar. That is, the detection data is the original perception data of the roadside perception device. It will be understood that the description of the detection data here is only an example and does not constitute a limitation to the embodiments of the present application.

[0106] In one possible implementation, after acquiring detection data, the sensor transmits the data to a perception computing unit within the roadside sensing device. The perception computing unit processes and analyzes the detection data. The detection data includes data acquired from detecting the first object within the blind spot. The following description uses this first object as an example.

[0107] After analyzing and processing the detection data, the perception computing unit may extract one or more pieces of perception information of the first object, including the position, movement speed, movement direction, type (e.g., vehicle or pedestrian), and identification. The specific analysis and processing method may be, for example, any one or more methods for extracting perception information of an object from image data or point cloud data, and this embodiment of the application is not limited thereto.

[0108] For example, in one possible implementation, the first information may include one or more of the extracted perception information. Optionally, the first information may also include the perception confidence information of the sensor. Optionally, if the first object is a vehicle, the first information may also include event information corresponding to the first object. The event information may be, for example, event information determined in vehicle to everything (V2X) technology. For the convenience of subsequent introduction, the first information may be referred to as the perception information after analysis and processing.

[0109] In another possible implementation, the first information includes detection data of the first object by the roadside perception device, that is, raw perception data of the first object. Similarly, optionally, the first information may also include perception confidence information of the sensor and / or event information corresponding to the first object. For ease of subsequent description, this first information may be referred to as unanalyzed perception information. The advantage of this implementation is that the roadside perception device does not need to perform information extraction processing, reducing the processing complexity of the roadside perception device.

[0110] It will be understood that the content of the first information listed above is merely an example and does not constitute a limitation to the embodiments of the present application.

[0111] S902. The roadside perception device sends the first information to the cloud device. The first information indicates the perception information of the roadside perception device on the first object when the vehicle cannot perceive the first object.

[0112] Exemplarily, after the roadside perception device obtains the first information, the roadside perception device may send the first information to the cloud device through a communication module or device (such as the CPE, etc.).

[0113] In one possible embodiment, when the first object is outside the vehicle's perception range (i.e., the vehicle cannot perceive the first object), the roadside perception device sends the first information to the cloud device. For example, in this case, the vehicle and the first object are both located on a blind spot, so the roadside perception device can perceive the vehicle. For ease of understanding, for example, reference can be made to any of the application scenario diagrams in Figures 4 to 8 , where the first object can be, for example, object A in the figure (e.g., vehicle A or static obstacle A in the figure), and the vehicle can be vehicle 102 in the figure. Because the vehicle is located on a blind spot, the roadside perception device can perceive the vehicle and obtain perception information about the vehicle. Then, based on the perception information about the vehicle and the first information, the distance between the vehicle and the first object can be calculated. The specific distance calculation method is not limited in this embodiment of the present application. Then, the size of the distance is determined. If the distance is greater than a preset distance, it can be determined that the first object is outside the vehicle's perception range. For example, the preset distance can be, for example, the vehicle's perception distance or a custom distance, etc. After determining that the first object is outside the sensing range of the vehicle, the roadside sensing device sends the first information to the cloud device, thereby saving unnecessary redundant data transmission and saving transmission bandwidth.

[0114] In one possible implementation, when the above-mentioned first object satisfies the first condition, the roadside perception device sends the above-mentioned first information to the above-mentioned cloud device. Exemplarily, the first condition may include that the distance between the first object and the above-mentioned vehicle is less than or equal to a first preset distance, and / or includes that the collision time (time-to-collision, TTC) between the first object and the above-mentioned vehicle is less than or equal to a first preset duration. Exemplarily, in a specific implementation, the above-mentioned first object is outside the perception range of the above-mentioned vehicle, and the roadside perception device does not necessarily send the above-mentioned first information to the cloud device. Instead, when the first object is outside the perception range of the above-mentioned vehicle and may threaten the driving safety of the vehicle (for example, when the first object satisfies the above-mentioned first condition), the above-mentioned first information is sent to the above-mentioned cloud device.

[0115] For example, the first preset distance and / or the first preset duration may be set according to actual application requirements, and the present application embodiment does not limit this. Through this implementation, unnecessary redundant data transmission can be further saved, saving transmission bandwidth.

[0116] In one possible implementation, the roadside sensing device may transmit the first information to the cloud device according to a preset format. For example, the roadside sensing device may encapsulate the first information into a message or packet and transmit it to the cloud device. For example, the first information may be encapsulated into a roadside safety message (RSM) and transmitted to the cloud device.

[0117] S903: The cloud device obtains the first information.

[0118] After the roadside sensing device sends the first information to the cloud device, the cloud device can receive the first information.

[0119] S904. The cloud device sends second information to the vehicle, where the second information is obtained based on the first information.

[0120] The cloud device receives the first information, can obtain second information based on the first information, and then can send the second information to the vehicle.

[0121] For example, in one possible implementation, if the first information is the unanalyzed perception information, the cloud device can analyze and process the raw perception data in the first information to extract one or more of the first object's location, movement speed, movement direction, type, and identification. The second information then includes the one or more pieces of perception information. Alternatively, the first information can be directly sent to the vehicle as the second information. This is not a limitation in the present embodiment.

[0122] In another possible implementation, if the first information is the perceived information after the above analysis and processing, then the cloud device can send the first information as the above second information to the vehicle. Alternatively, it can select part of the first information and send it to the vehicle. This embodiment of the present application is not limited to this.

[0123] In one possible implementation, the cloud device transmits the second information to the vehicle if the first object satisfies a second condition. The second condition includes the distance between the first object and the vehicle being less than or equal to a second preset distance, and / or the time between the collision of the first object and the vehicle being less than or equal to a second preset duration.

[0124] For example, in a specific implementation, the vehicle may send its driving status information to a cloud device. This driving status information may include one or more of the vehicle's location, driving speed, direction of movement (or driving direction), type, and identification. It should be understood that the driving status information described herein is merely illustrative and does not constitute a limitation on the embodiments of the present application. After receiving the vehicle's driving status information, the cloud device may calculate the distance between the vehicle and the first object and / or the collision time between the vehicle and the first object based on the driving status information and the received first information. For example, the cloud device may calculate the distance and / or collision time in conjunction with a high-precision map, and the embodiments of the present application do not limit the specific implementation process of this calculation. If the distance is less than or equal to the second preset distance, and / or the collision time is less than or equal to the second preset duration, the cloud device sends the second information to the vehicle. For example, the second preset distance and / or the second preset duration may be set based on actual application requirements, and the embodiments of the present application do not limit this. This implementation method can save unnecessary redundant data transmission and save transmission bandwidth.

[0125] S905. The vehicle obtains the second information and obtains first fusion information based on the second information and the first perception information; and performs first driving control based on the first fusion information; the first perception information includes perception information obtained by the vehicle's sensors; when the vehicle perceives the first object based on the second perception information, the vehicle performs second driving control based on the second perception information; the second perception information includes perception information of the first object obtained by the vehicle's sensors.

[0126] In one possible implementation, the operations performed by the vehicle described in the embodiments of the present application may be performed by a vehicle controller. For example, the operations may be performed by a VDC, CDC, MDC, or other controller that deploys the software of the vehicle-mounted intelligent driving system shown in FIG. 3 .

[0127] For example, the vehicle's own sensors are also constantly detecting the surrounding road conditions to obtain its own perception information. After the vehicle receives the second information from the cloud device, it can achieve information fusion based on the second information and the vehicle's own perception information.

[0128] In one possible implementation, the vehicle can fuse the second information and its own perception information into a high-precision map. For example, any perception information fusion method can be used to achieve the fusion of the second information and the vehicle's own perception information, and the embodiment of the present application does not limit the method of perception information fusion. After obtaining the fused high-precision map, intelligent driving control of the vehicle is implemented based on the fused high-precision map. For example, the vehicle can perceive the existence of the first object based on the fused high-precision map, and thus can calculate the distance and / or collision time between itself and the first object. Then, based on the distance and / or collision time, operational controls such as deceleration or lane changing are performed to achieve safe driving.

[0129] In another specific implementation, the vehicle may integrate the second information and its own perception information into a customized map. Based on the integrated map, the vehicle may also sense the presence of the first object and, based on the distance to the first object and / or collision time, perform maneuvers such as deceleration or lane change to achieve safe driving.

[0130] In one possible implementation, if the first object enters the vehicle's perception range, meaning the vehicle can sense the first object, driving control can be performed based on the vehicle's own perception information. In this case, the vehicle's own perception information includes the perception information of the first object. This eliminates the need to fuse roadside perception data with the vehicle's own perception data. While conserving computing resources, the vehicle's own perception data offers a higher degree of confidence, enabling more accurate and rational driving control and reducing the risk of accidents.

[0131] In another possible implementation, after the vehicle can perceive the first object, it can still receive perception information (referred to as third information) from the roadside perception device regarding the first object from the cloud device. This third information can then be fused with the vehicle's own perception information according to a weight ratio, and corresponding driving control can be performed based on the fused perception information. For example, the weight of the vehicle's own perception information is greater than the weight of the third information. For example, the weight can be expressed as a percentage or a score, which is not limited in this embodiment of the present application. For example, in a specific implementation, the fusion of the vehicle's own perception information and the third information can be achieved using a perception fusion model, such as a machine learning model or a deep learning model. For example, the input of the perception fusion model can include the vehicle's own perception information (including the perception information regarding the first object), the third information, and the weight (or weight ratio) of the two information, and the output is the fused perception information. Driving control can then be performed based on the fused perception information. In this implementation, on the one hand, the roadside perception information is utilized to expand the vehicle's perception range, and on the other hand, the higher weight ratio of the vehicle's own perception can increase the confidence level of the perception fusion.

[0132] In one possible implementation, the roadside perception device has a higher confidence level in sensing vehicles and a lower confidence level in sensing pedestrians. Therefore, if the roadside perception information forwarded by the cloud device to the vehicle includes perception information about the vehicle, the vehicle can fuse the perception information of the vehicle with its own perception information. For example, the first object includes one or more target vehicles, and the second information includes the perception information of the roadside perception device on the one or more target vehicles. If the roadside perception information forwarded by the cloud device to the vehicle includes perception information about pedestrians, the perception information about pedestrians can be discarded and not used. This is to reduce interference with subsequent fusion and driving control. Exemplarily, for example, it is possible to determine whether it is the perception information of pedestrians or the perception information of vehicles by the type in the second information.

[0133] In one possible implementation, after the first object enters the perception range of the vehicle, the vehicle may detect the first object and obtain perception information of the first object (referred to as second perception information). For example, the second perception information may include one or more of the following: the location, movement speed, movement direction, type, and identification of the first object.

[0134] In addition, after the above-mentioned first object enters the perception range of the above-mentioned vehicle, the vehicle can still receive the perception information of the first object detected by the above-mentioned roadside perception device (referred to as the fourth information) from the cloud device. Then, the vehicle can calibrate the fourth information based on its own perception information of the first object to obtain a calibration result. Exemplarily, the fourth information also indicates one or more of the position, moving speed, moving direction, type and identification of the first object. The vehicle can also obtain one or more of the position, moving speed, moving direction, type and identification of the first object by analyzing and processing the perception information of the first object.

[0135] Exemplarily, in one possible implementation, data association can be performed using a Euclidean distance algorithm or a Mahalanobis distance algorithm to achieve a match between the first object perceived by the roadside device and the first object perceived by the vehicle. The vehicle can then compare the fourth information with the vehicle's perception information of the first object to obtain deviation information of the perception information. For example, the fourth information can be compared with the position information in the vehicle's perception information of the first object to obtain a position deviation. Optionally, the fourth information can also be compared with the moving speed in the vehicle's perception information of the first object to obtain a speed deviation, and so on. The one or more deviations constitute the deviation information of the perception information, and the deviation information is the above-mentioned calibration result.

[0136] Or, illustratively, in another possible implementation, the vehicle may first fuse the above-mentioned vehicle's perception information of the first object and the fourth information into the vehicle's map (such as a high-precision map or a custom map). Then, the vehicle can obtain one or more of the position, moving speed, moving direction, type and identification of the first object based on the fused map. This information is referred to as fused perception information. The vehicle can then compare the fourth information with the fused perception information to obtain deviation information of the perception information. For example, the fourth information can be compared with the position information in the fused perception information to obtain a position deviation. Optionally, the fourth information can also be compared with the moving speed in the fused perception information to obtain a speed deviation, and so on. The one or more deviations constitute the deviation information of the perception information, and the deviation information is the above-mentioned calibration result.

[0137] After obtaining the calibration results, the vehicle can send them to the cloud device. The cloud device then sends them to the roadside perception device. After receiving the calibration results, the roadside perception device calibrates its perception confidence level based on them. For example, the roadside perception device can use these calibration results as calibration parameters to input the perception model of its own perception computing unit to calibrate the parameters of the perception model, thereby calibrating the perception confidence level of the roadside perception device.

[0138] In one possible implementation, if the roadside sensing device senses that the first object has left the blind spot or enters the sensing range of the vehicle, the roadside sensing device may send fifth information to the cloud device.

[0139] For example, if the roadside sensing device fails to detect the presence of the first object in the detection information detected by the sensor, for example, if it fails to extract the sensing information of the first object, it can be determined that the first object has left the aforementioned blind spot section. In this case, the fifth information is used to indicate that the first object has left the aforementioned blind spot section. For example, the fifth information can be empty data or can be preset first indicator information, etc., which is not limited in this embodiment of the present application.

[0140] Exemplarily, the roadside perception device extracts the perception information of the first object and the vehicle from the detection information detected by the sensor, and then calculates the distance between the two. If the distance is less than a preset distance, it can be determined that the first object has entered the perception range of the vehicle. In this case, the fifth information is used to indicate that the first object has entered the perception range of the vehicle. Exemplarily, the fifth information can be a preset second indicator mark information, etc., which is not limited in this embodiment of the present application. Exemplarily, the second indicator mark information and the first indicator mark information can be the same or different.

[0141] After receiving the fifth information, the cloud device can learn that the first object has left the blind spot section, or the first object has entered the perception range of the vehicle. If the first object leaves the blind spot section, it indicates that the first object will not (or will not temporarily) pose a threat to the driving safety of the vehicle. If the first object enters the perception range of the vehicle, the vehicle can handle it based on its own perception information. Therefore, the cloud device can generate perception fusion shutdown information based on the fifth information and send the perception fusion shutdown information to the vehicle. After the vehicle receives the perception fusion shutdown information, it restores the single-vehicle perception driving mode according to the instructions of the information and turns off the function of fusing the perception information of the first object detected by the roadside perception device.

[0142] Exemplarily, in one possible implementation, the first object is the last object to leave the blind spot section. Only in this case will the fusion shutdown operation be triggered. That is, there are no objects in the blind spot section that threaten the driving safety of the vehicle. At this time, the roadside detection device can send empty data to the cloud device. For example, the data in the message or message sent to the cloud device is empty. After receiving the empty data, the cloud device can send the perception fusion shutdown information to the vehicle. If there are other objects in the blind spot section after the first object leaves the blind spot section, especially objects that threaten the driving safety of the vehicle, the fusion shutdown operation will not be triggered.

[0143] In one possible implementation, if the blind spot includes a traffic light, the roadside sensing device may also obtain the traffic light's traffic indication information and send it to the cloud device. This traffic indication information may be, for example, traffic light phase information. After receiving this traffic indication information, the cloud device may dynamically calculate the optimal path and / or speed for the vehicle based on the vehicle's location information and send this information to the vehicle. After receiving this information, the vehicle may perform corresponding driving control based on this information, for example, driving according to the optimal path and / or speed.

[0144] In one possible implementation, the cloud device may only send the calculated optimal path and / or speed information to the vehicle if the information is different from the information reported by the vehicle, thereby saving transmission bandwidth.

[0145] In summary, in the embodiment of the present application, roadside sensing devices are deployed in blind spots on the road instead of continuously deploying a large number of sensing devices on the road; and the vehicle does not communicate with the roadside sensing device, but realizes information interaction between the vehicle and the road through the cloud, so that there is no need to deploy OBU in the vehicle and no need to use expensive RSU on the roadside, thereby greatly reducing costs. In addition, the roadside sensing device is regarded as an extension of the vehicle's sensing device, that is, the information perceived by the roadside sensing device is directly sent to the vehicle via the cloud, and the vehicle integrates the received sensing information with the information perceived by its own sensing device to expand the vehicle's sensing range and reduce driving safety hazards. That is, this solution provides a vehicle-road collaboration solution that can effectively reduce vehicle driving safety hazards, has low implementation costs, and is easy to promote and use.

[0146] The above mainly introduces the method provided by the embodiment of the present application. It is understandable that, in order to realize the corresponding functions mentioned above, each control unit or device includes a hardware structure and / or software module corresponding to the execution of each function. In combination with the units and steps of each example described in the embodiments disclosed herein, the present application can be implemented in the form of hardware or a combination of hardware and computer software. Whether a function is executed in the form of hardware or computer software driving hardware depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0147] The embodiment of the present application can divide the functional modules of the device according to the above method example. For example, each functional module can be divided according to each function, or two or more functions can be integrated into one module. The above integrated modules can be implemented in the form of hardware or in the form of software functional modules. It should be noted that the division of modules in the embodiment of the present application is schematic and is only a logical function division. In actual implementation, there may be other division methods.

[0148] In the case of dividing each functional module according to each function, the embodiment of the present application also provides an apparatus for implementing any of the above methods. For example, the provided apparatus includes units (or means) for implementing each step in any of the above methods.

[0149] For example, please refer to Figure 10, which is a schematic diagram of the structure of a driving control system 1000 provided in an embodiment of the present application. The driving control system 1000 shown in Figure 10 can be a driving control system in a vehicle in any embodiment of the above method. The driving control system 1000 can include an acquisition unit 1001 and a processing unit 1002. Among them:

[0150] An acquiring unit 1001 is configured to acquire first information from a cloud device; the first information includes perception information of a first object by a roadside perception device;

[0151] The processing unit 1002 is configured to obtain first fusion information based on the first information and the first perception information; and perform first driving control based on the first fusion information; wherein the first perception information includes perception information obtained by a sensor of the vehicle;

[0152] The processing unit 1002 is further configured to execute a second driving control according to the second perception information when the vehicle perceives the first object according to the second perception information; the second perception information includes perception information of the first object obtained by the sensor of the vehicle.

[0153] In one possible implementation, the first object includes one or more target vehicles, and the first information includes perception information of the roadside perception device on the one or more target vehicles.

[0154] In a possible implementation, the acquiring unit 1001 is further configured to acquire second information from a cloud device; the second information indicates perception information of the roadside perception device on the second object; the second object includes one or more pedestrians;

[0155] The processing unit 1002 is further configured to discard the second information.

[0156] In a possible implementation, the acquiring unit 1001 is further configured to acquire third information from the cloud device; the third information indicates perception information of the roadside perception device on the first object when the vehicle perceives the first object;

[0157] The processing unit 1002 is specifically configured to:

[0158] fusing the third information and the second perception information according to a preset weight ratio to obtain second fused information; wherein the weight ratio of the second perception information is greater than the weight ratio of the third information;

[0159] The second driving control is performed according to the second fusion information.

[0160] In a possible implementation, the acquiring unit 1001 is further configured to acquire fourth information from a cloud device; the fourth information indicates perception information of the roadside perception device on the first object when the vehicle perceives the first object;

[0161] The processing unit 1002 is further configured to calibrate the fourth information according to the second perception information to obtain a calibration result;

[0162] The vehicle also includes a sending unit for sending the calibration result, which is used to correct the perception confidence of the roadside perception device.

[0163] In a possible implementation, the acquiring unit 1001 is further configured to, when the vehicle senses the first object, or when the first object leaves the sensing range of the roadside sensing device,

[0164] Obtain fifth information from the cloud device; the fifth information instructs the vehicle to turn off a roadside perception fusion function, where the roadside perception fusion function is a function of fusing perception information of the roadside perception device with perception information of the vehicle.

[0165] In a possible implementation, the acquiring unit 1001 is specifically configured to:

[0166] When the vehicle cannot perceive the first object and the first object satisfies a first condition, obtaining the first information;

[0167] The first condition includes: a distance between the first object and the vehicle is less than or equal to a first preset distance, and / or a collision time between the first object and the vehicle is less than or equal to a first preset duration.

[0168] The specific operations and beneficial effects of each unit in the driving control system 1000 shown in FIG10 can be found in the corresponding descriptions in FIG9 and its possible embodiments, and will not be repeated here.

[0169] For example, please refer to Figure 11, which is a schematic diagram of the structure of a cloud device 1100 provided in an embodiment of the present application. The cloud device 1100 shown in Figure 11 can be a cloud device for implementing any embodiment of the above method. The cloud device 1100 may include an acquisition unit 1101, a processing unit 1102, and a sending unit 1103. Among them:

[0170] The acquisition unit 1101 is configured to acquire vehicle status information from a vehicle; the vehicle status information includes location information and speed information of the vehicle;

[0171] The acquiring unit 1101 is further configured to acquire first information; the first information indicates perception information of the roadside perception device on the first object;

[0172] The processing unit 1102 is configured to determine, based on the vehicle state information and the first information, that the first object satisfies a first condition; the first condition comprising: a distance between the first object and the vehicle is less than or equal to a first preset distance, and / or a collision time between the first object and the vehicle is less than or equal to a first preset duration;

[0173] The sending unit 1103 is configured to send the first information to the vehicle.

[0174] In a possible implementation, the acquiring unit 1101 is further configured to acquire second information from the roadside sensing device; the second information indicates perception information of the roadside sensing device regarding the first object when the vehicle perceives the first object;

[0175] The sending unit 1103 is further configured to send the second information to the vehicle;

[0176] The acquiring unit 1101 is further configured to acquire third information from the vehicle; the third information is a calibration result obtained by calibrating the second information based on the vehicle's own perception information;

[0177] The sending unit 1103 is further configured to send the calibration result to the roadside perception device; the calibration result is used to correct the perception confidence of the roadside perception device.

[0178] In a possible implementation, the sending unit 1103 is further configured to, when the vehicle senses the first object, or when the first object leaves the sensing range of the roadside sensing device,

[0179] A fourth message is sent to the vehicle; the fourth message instructs the vehicle to turn off a roadside perception fusion function, where the roadside perception fusion function is a function of fusing perception information of the roadside perception device with perception information of the vehicle.

[0180] In a possible implementation, the acquiring unit 1101 is further configured to acquire fifth information from the roadside sensing device; the fifth information indicates that the first object has left a sensing range of the roadside sensing device;

[0181] The processing unit 1102 is further configured to trigger an operation of sending the fourth information to the vehicle according to the fifth information.

[0182] The specific operations and beneficial effects of each unit in the cloud device 1100 shown in Figure 11 can be found in the corresponding descriptions in Figure 9 and its possible embodiments, and will not be repeated here.

[0183] For example, please refer to Figure 12, which is a schematic diagram of the structure of a roadside sensing device 1200 provided in an embodiment of the present application. The roadside sensing device 1200 shown in Figure 12 can be a roadside sensing device for implementing any embodiment of the above method. The roadside sensing device 1200 may include an acquisition unit 1201, a processing unit 1202, and a sending unit 1203. Among them:

[0184] An acquiring unit 1201 is configured to acquire first perception information, wherein the first perception information includes perception information of the first object and perception information of the vehicle;

[0185] The processing unit 1202 is configured to identify, based on the first perception information, whether the first object threatens the driving safety of the vehicle;

[0186] The sending unit 1203 is used to send first information to the cloud device, where the first information indicates the perception information of the roadside perception device on the first object, and the first information is used to be sent to the vehicle.

[0187] In a possible implementation, the sending unit 1203 is further configured to send second information to the cloud device; the second information indicates perception information of the roadside perception device on the first object when the vehicle perceives the first object;

[0188] The roadside perception device also includes an acquisition unit for obtaining a calibration result from the cloud device; the calibration result is used to correct the perception confidence of the roadside perception device, and the calibration result is a calibration result obtained by the vehicle calibrating the second information based on its own perception information.

[0189] In a possible implementation, the sending unit 1203 is further configured to

[0190] A third message is sent to the cloud device; the third message indicates that the first object has left the perception range of the roadside perception device; the third message is used to trigger the cloud device to send the fourth message to the vehicle, and the fourth message instructs the vehicle to turn off the roadside perception fusion function, which is a function of fusing the perception information of the roadside perception device on the first object and the perception information of the vehicle.

[0191] The specific operations and beneficial effects of each unit in the roadside perception device 1200 shown in Figure 12 can be found in the corresponding descriptions in Figure 9 and its possible embodiments, and will not be repeated here.

[0192] It should be understood that the division of the various units in the above vehicle, cloud device or roadside sensing device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. In addition, the units in the device can be implemented in the form of a processor calling software; for example, the device includes a processor, the processor is connected to a memory, and the memory stores instructions. The processor calls the instructions stored in the memory to implement any of the above methods or realize the functions of the various units of the device, wherein the processor is, for example, a general-purpose processor, such as a central processing unit (CPU) or a microprocessor, and the memory is a memory within the device or a memory outside the device. Alternatively, the units in the device can be implemented in the form of hardware circuits, and the functions of some or all of the units can be realized by designing the hardware circuits. The hardware circuit can be understood as one or more processors. For example, in one implementation, the hardware circuit is an application-specific integrated circuit (ASIC), which realizes the functions of some or all of the above units by designing the logical relationship of the components in the circuit. For another example, in another implementation, the hardware circuit can be implemented by a programmable logic device (PLD). Taking a field programmable gate array (FPGA) as an example, it can include a large number of logic gate circuits, and the connection relationship between the logic gate circuits is configured by configuring the configuration file, thereby realizing the functions of some or all of the above units. All units of the above devices can be implemented in the form of software called by the processor, or in the form of hardware circuits, or in part by software called by the processor, and the rest by hardware circuits.

[0193] In an embodiment of the present application, a processor is a circuit with data processing capabilities. In one implementation, the processor can be a circuit with instruction reading and execution capabilities, such as a CPU, a microprocessor, a graphics processing unit (GPU) (which can be understood as a microprocessor), or a digital signal processor (DSP); in another implementation, the processor can implement certain functions through the logical relationship of a hardware circuit, and the logical relationship of the hardware circuit is fixed or reconfigurable, such as a hardware circuit implemented by an ASIC or PLD, such as an FPGA. In a reconfigurable hardware circuit, the process of the processor loading a configuration document and implementing the hardware circuit configuration can be understood as the process of the processor loading instructions to implement the functions of some or all of the above units. In addition, it can also be a hardware circuit designed for artificial intelligence, which can be understood as an ASIC, such as a neural network processing unit (NPU), a tensor processing unit (TPU), a deep learning processing unit (DPU), etc.

[0194] It can be seen that each unit in the above device can be one or more processors (or processing circuits) configured to implement the above method, such as: CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of these processor forms.

[0195] In addition, the various units in the above devices can be fully or partially integrated together, or can be implemented independently. In one implementation, these units are integrated together and implemented in the form of a system-on-a-chip (SOC). The SOC may include at least one processor for implementing any of the above methods or implementing the functions of the various units of the device. The type of the at least one processor can be different, for example, including a CPU and FPGA, a CPU and an artificial intelligence processor, a CPU and a GPU, etc.

[0196] For example, see Figure 13 , which is a schematic diagram of a possible physical structure of the device provided herein. The device 1300 shown in Figure 13 can be a vehicle, cloud device, or roadside sensing device in the methods described in the above embodiments. The device 1300 includes a processor 1301 , a memory 1302 , and a communication interface 1303 . The processor 1301 , the communication interface 1303 , and the memory 1302 can be interconnected or connected via a bus 1304 .

[0197] Exemplarily, the memory 1302 is used to store computer programs and data of the device 1300. The memory 1302 may include, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), or portable read-only memory (CD-ROM).

[0198] The software or program codes required for all or part of the functions of the device in the above method embodiment are stored in the memory 1302 .

[0199] In one possible implementation, if the software or program code required for some functions is stored in the memory 1302, the processor 1301, in addition to calling the program code in the memory 1302 to implement some functions, can also cooperate with other components (such as the communication interface 1303) to jointly complete other functions described in the method embodiment (such as the function of receiving or sending data).

[0200] There may be multiple communication interfaces 1303 , which are used to support the device 1300 to communicate, such as receiving or sending data or signals.

[0201] Exemplarily, the processor 1301 may be a CPU, GPU, NPU, TPU, DPU, microprocessor, DSP, ASIC, FPGA, or a combination of at least two of the aforementioned processor types. The processor 1301 may be configured to read programs stored in the memory 1302 and execute the operations performed by the corresponding device in the method described in FIG. 9 and its possible embodiments.

[0202] The specific operations and beneficial effects of each unit in the device 1300 shown in Figure 13 can be found in the corresponding descriptions in Figure 9 and its possible embodiments, and will not be repeated here.

[0203] The present application also provides a chip including a processor and a memory, wherein the memory is configured to store computer programs or computer instructions, and the processor is configured to execute the computer programs or computer instructions stored in the memory, so that the chip performs the operations performed by the vehicle in FIG. 9 and its possible embodiments.

[0204] The present application also provides a chip including a processor and a memory, wherein the memory is configured to store computer programs or computer instructions, and the processor is configured to execute the computer programs or computer instructions stored in the memory, so that the chip performs the operations performed by the cloud device in FIG. 9 and its possible embodiments.

[0205] The present application also provides a chip comprising a processor and a memory, wherein the memory is configured to store computer programs or computer instructions, and the processor is configured to execute the computer programs or computer instructions stored in the memory, so that the chip performs the operations performed by the roadside sensing device in FIG. 9 and its possible embodiments.

[0206] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method implemented by the vehicle in Figure 9 and its possible embodiments.

[0207] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method implemented by the cloud device in Figure 9 and its possible embodiments.

[0208] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method implemented by the roadside perception device in Figure 9 and its possible embodiments.

[0209] An embodiment of the present application also provides a computer program product. When the computer program product is read and executed by a computer, the operations implemented by the vehicle in the method described in any one of Figure 9 and its possible embodiments will be executed.

[0210] An embodiment of the present application also provides a computer program product. When the computer program product is read and executed by a computer, the operations implemented by the cloud device in the method described in any one of Figure 9 and its possible embodiments will be executed.

[0211] An embodiment of the present application also provides a computer program product. When the computer program product is read and executed by a computer, the operations implemented by the roadside perception device in the method described in any one of Figure 9 and its possible embodiments will be executed.

[0212] It should be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0213] It will also be understood that the term “comprise” (also known as “includes,” “including,” “comprises,” and / or “comprising”) when used in this specification specifies the presence of stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0214] It should also be understood that references throughout this specification to "one embodiment," "an embodiment," or "one possible implementation" mean that specific features, structures, or characteristics associated with that embodiment or implementation are included in at least one embodiment of the present application. Therefore, the appearance of "in one embodiment," "in an embodiment," or "one possible implementation" throughout this specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0215] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present application.

Claims

1. A driving control method, characterized in that: The method comprises: Obtaining first information from a cloud device; the first information includes perception information of a first object by a roadside perception device; Acquire first fusion information based on the first information and the first perception information; and perform first driving control based on the first fusion information; wherein the first perception information includes perception information obtained by a sensor of the vehicle; When the vehicle perceives the first object according to second perception information, a second driving control is performed according to the second perception information; the second perception information includes perception information of the first object obtained by a sensor of the vehicle.

2. The method according to claim 1, characterized in that The first object includes one or more target vehicles, and the first information includes perception information of the one or more target vehicles by the roadside perception device.

3. The method according to claim 1 or 2, characterized in that The method further comprises: Obtaining second information from a cloud device; the second information indicates perception information of a second object by the roadside perception device; the second object includes one or more pedestrians; The second information is discarded.

4. The method according to any one of claims 1 to 3, characterized in that The method further includes: acquiring third information from the cloud device; the third information indicating perception information of the first object by the roadside perception device when the vehicle perceives the first object; The performing the second driving control according to the second perception information of the vehicle itself includes: fusing the third information and the second perception information according to a preset weight ratio to obtain second fused information; wherein the weight ratio of the second perception information is greater than the weight ratio of the third information; The second driving control is performed according to the second fusion information.

5. The method according to any one of claims 1 to 4, characterized in that The method further comprises: Obtaining fourth information from the cloud device; the fourth information indicating perception information of the first object by the roadside perception device when the vehicle perceives the first object; calibrating the fourth information according to the second perception information to obtain a calibration result; The calibration result is sent, where the calibration result is used to correct the perception confidence of the roadside perception device.

6. The method according to any one of claims 1 to 5, characterized in that When the vehicle senses the first object, or when the first object leaves a sensing range of the roadside sensing device, the method further includes: Obtain fifth information from the cloud device; the fifth information instructs the vehicle to turn off a roadside perception fusion function, where the roadside perception fusion function is a function of fusing perception information of the roadside perception device with perception information of the vehicle.

7. The method according to any one of claims 1 to 6, characterized in that The obtaining of the first information from the cloud device includes: When the vehicle cannot perceive the first object and the first object satisfies a first condition, acquiring the first information; The first condition includes: a distance between the first object and the vehicle is less than or equal to a first preset distance, and / or a collision time between the first object and the vehicle is less than or equal to a first preset duration.

8. The method according to any one of claims 1 to 7, characterized in that The roadside sensing device is deployed on a blind spot section in the forward direction of the vehicle, and the sensing range of the roadside sensing device covers the blind spot section; The driving blind spot section includes one or more of the following: a curved road section, a road section including an intersection, a road section including an entrance or exit, or a slope top section.

9. A cooperative driving method, characterized in that: The method comprises: Acquiring vehicle status information from a vehicle; the vehicle status information includes position information and speed information of the vehicle; Acquire first information; the first information indicates perception information of the first object by the roadside perception device; determining, based on the vehicle state information and the first information, that the first object satisfies a first condition; the first condition comprising: a distance between the first object and the vehicle being less than or equal to a first preset distance, and / or a collision time between the first object and the vehicle being less than or equal to a first preset duration; The first information is sent to the vehicle.

10. The method according to claim 9, characterized in that The method further comprises: Acquiring second information from the roadside perception device; the second information indicating perception information of the first object by the roadside perception device when the vehicle perceives the first object; sending the second information to the vehicle; Acquiring third information from the vehicle; the third information being a calibration result obtained by calibrating the second information based on the perception information of the vehicle itself; The calibration result is sent to the roadside perception device; the calibration result is used to correct the perception confidence of the roadside perception device.

11. The method according to claim 9 or 10, characterized in that When the vehicle senses the first object, or when the first object leaves a sensing range of the roadside sensing device, the method further includes: A fourth message is sent to the vehicle; the fourth message instructs the vehicle to turn off a roadside perception fusion function, where the roadside perception fusion function is a function of fusing perception information of the roadside perception device with perception information of the vehicle.

12. The method according to claim 11, characterized in that The method further comprises: Acquiring fifth information from the roadside perception device; the fifth information indicating that the first object has left the perception range of the roadside perception device; An operation of sending the fourth information to the vehicle is triggered according to the fifth information.

13. A driving control system, characterized in that: include: an acquiring unit, configured to acquire first information from a cloud device; The first information includes perception information of the first object by the roadside perception device; a processing unit, configured to obtain first fusion information based on the first information and the first perception information; and perform first driving control based on the first fusion information; wherein the first perception information includes perception information obtained by a sensor of the vehicle; The processing unit is further configured to, when the vehicle perceives the first object based on second perception information, perform a second driving control based on the second perception information; the second perception information includes perception information of the first object obtained by the sensor of the vehicle.

14. The driving control system according to claim 13, characterized in that: The acquisition unit is further configured to acquire second information from the cloud device; the second information indicates perception information of the roadside perception device on the second object; the second object includes one or more pedestrians; The processing unit is further configured to discard the second information.

15. The driving control system according to claim 13 or 14, characterized in that: The acquisition unit is further configured to acquire third information from the cloud device; the third information indicating perception information of the first object by the roadside perception device when the vehicle perceives the first object; The processing unit is specifically configured to: fusing the third information and the second perception information according to a preset weight ratio to obtain second fused information; wherein the weight ratio of the second perception information is greater than the weight ratio of the third information; The second driving control is performed according to the second fusion information.

16. The driving control system according to any one of claims 13 to 15, characterized in that: The acquiring unit is further configured to acquire fourth information from the cloud device; the fourth information indicating perception information of the first object by the roadside perception device when the vehicle perceives the first object; The processing unit is further configured to calibrate the fourth information according to the second perception information to obtain a calibration result; The vehicle further includes a sending unit for sending the calibration result, where the calibration result is used to correct the perception confidence of the roadside perception device.

17. A cloud device, characterized in that: The cloud device includes: an acquiring unit, configured to acquire vehicle status information from a vehicle; the vehicle status information including position information and speed information of the vehicle; The acquiring unit is further configured to acquire first information, wherein the first information indicates perception information of the roadside perception device on the first object; a processing unit, configured to determine, based on the vehicle state information and the first information, that the first object satisfies a first condition; the first condition comprising: a distance between the first object and the vehicle is less than or equal to a first preset distance, and / or a collision time between the first object and the vehicle is less than or equal to a first preset duration; A sending unit is used to send the first information to the vehicle.

18. A vehicle, characterized in that: The vehicle includes a processor and a memory, wherein the memory is used to store a computer program or computer instructions, and the processor is used to execute the computer program or computer instructions stored in the memory, so that the vehicle performs the method according to any one of claims 1 to 8.

19. A cloud device, characterized in that: The cloud device includes a processor and a memory, wherein the memory is used to store computer programs or computer instructions, and the processor is used to execute the computer programs or computer instructions stored in the memory, so that the cloud device executes the method according to any one of claims 9 to 12.

20. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program or computer instructions, and the computer program or computer instructions are executed by a processor to implement the method according to any one of claims 1 to 8; Alternatively, the computer program or computer instructions are executed by a processor to implement the method according to any one of claims 9 to 12.

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