CN112033425B

CN112033425B - Vehicle driving assisting method, device, computer equipment and storage medium

Info

Publication number: CN112033425B
Application number: CN201910481767.3A
Authority: CN
Inventors: 马潍; 佘咸宁
Original assignee: Changsha Intelligent Driving Research Institute Co Ltd
Current assignee: Changsha Intelligent Driving Research Institute Co Ltd
Priority date: 2019-06-04
Filing date: 2019-06-04
Publication date: 2023-06-13
Anticipated expiration: 2039-06-04
Also published as: CN112033425A

Abstract

The application relates to a vehicle auxiliary driving method, a vehicle auxiliary driving device, a computer device and a storage medium, wherein the vehicle auxiliary driving device is operated on an on-board device. The method comprises the following steps: acquiring positioning information and destination information based on a vehicle, and transmitting the positioning information and the destination information to a cloud service platform; receiving global path planning information sent by a cloud service platform based on positioning information and destination information; acquiring local path planning information determined based on global path planning; and merging the local path planning information and the global path planning information to obtain the target driving plan of the vehicle. By adopting the method, the reliability of target path planning can be improved, so that the safety of vehicle running can be improved. The application relates to a vehicle driving assisting method, a device, a computer device and a storage medium for running on road side equipment, which can also improve the safety of vehicle running.

Description

Vehicle driving assisting method, device, computer equipment and storage medium

Technical Field

The present disclosure relates to the field of road traffic control technologies, and in particular, to a method and apparatus for assisting driving of a vehicle, a computer device, and a storage medium.

Background

Along with the continuous improvement of the living standard and the communication technology of people, the gradual acceleration of the urban process, the rapid increase of the possession of urban motor vehicles and other factors, the continuous increase of the number of motor vehicles, the vehicle-road cooperation technology based on the Internet of vehicles already enters the rapid development stage, and the importance of vehicle auxiliary driving is also increasing.

In the traditional vehicle auxiliary driving method, a target driving path is determined according to vehicle-mounted video data collected by vehicle-mounted equipment. Because the traditional vehicle auxiliary driving method has single considered factors when in auxiliary driving, potential safety hazards exist, and the driving safety of the vehicle is lower and needs to be further improved.

Disclosure of Invention

In view of the foregoing, it is desirable to provide a vehicle driving support method, apparatus, computer device, and storage medium that can improve the running safety of a vehicle.

A method of assisting driving of a vehicle, the method comprising:

acquiring positioning information and destination information based on a vehicle, and transmitting the positioning information and the destination information to a cloud service platform;

receiving global path planning information sent by the cloud service platform based on the positioning information and the destination information;

Acquiring local path planning information determined based on the global path planning;

and fusing the local path planning information and the global path planning information to obtain the target driving plan of the vehicle.

In one embodiment, the method further comprises:

when the vehicle is in the transmission range of the target road side equipment, receiving road side video data sent by the target road side equipment;

acquiring vehicle-mounted video data based on the vehicle;

and fusing the road side video data and the vehicle-mounted video data to obtain fused video data.

In one embodiment, the fusing the road side video data and the vehicle-mounted video data to obtain the fused video data includes:

analyzing the vehicle-mounted video data to obtain the current visual field distance of the vehicle;

determining a target visual field distance according to the braking distance of the vehicle;

and adjusting and fusing the road side video data and the vehicle-mounted video data according to the target visual field distance to obtain the visual field distance of the fused video data.

In one embodiment, when the vehicle is within the transmission range of a target roadside device, receiving the roadside video data sent by the target roadside device includes:

Transmitting a road side video request to the target road side equipment in a transmission range;

and receiving the road side video data sent by the target road side equipment according to the road side video request.

In one embodiment, after the fusing the road side video data and the vehicle-mounted video data to obtain the fused video data, the method further includes:

determining a target driving instruction according to the fused video data and the target driving plan; the target driving instruction carries steering parameters and speed parameters;

and sending the target driving instruction to a central control platform, and controlling the vehicle to run by the central control platform according to the steering parameter and the speed parameter.

In one embodiment, the obtaining local path planning information determined based on the global path planning includes:

and when the vehicle is in the transmission range of the target road side equipment, receiving local path planning information sent by the target road side equipment based on the global path planning.

A vehicle assisted driving apparatus, the apparatus comprising:

the information acquisition forwarding module is used for acquiring positioning information and destination information based on a vehicle and sending the positioning information and the destination information to the cloud service platform;

The global planning receiving module is used for receiving global path planning information sent by the cloud service platform based on the positioning information and the destination information;

the local planning receiving module is used for acquiring local path planning information determined based on the global path planning;

and the target planning fusion module is used for fusing the local path planning information and the global path planning information to obtain a target driving plan of the vehicle.

In one embodiment, the apparatus further comprises:

the road side video receiving module is used for receiving road side video data sent by the target road side equipment when the vehicle is in the transmission range of the target road side equipment;

the vehicle-mounted video acquisition module is used for acquiring vehicle-mounted video data based on the vehicle;

and the video data fusion module is used for fusing the road side video data and the vehicle-mounted video data to obtain fused video data.

In one embodiment, the video data fusion module includes:

the visual field distance analysis unit is used for analyzing the vehicle-mounted video data to obtain the current visual field distance of the vehicle;

a target visual field determining unit for determining a target visual field distance according to a braking distance of the vehicle;

And the visual field distance adjusting unit is used for adjusting and fusing the road side video data and the vehicle-mounted video data according to the target visual field distance to obtain the visual field distance of the fused video data.

In one embodiment, the roadside image receiving module includes:

a road side video request unit, configured to send a road side video request to the target road side device in the transmission range;

and the road side video receiving unit is used for receiving the road side video data sent by the target road side equipment according to the road side video request.

In one embodiment, the apparatus further comprises:

the driving instruction determining module is used for fusing the road side video data and the vehicle-mounted video data in the video data fusion module to obtain fused video data, and then determining a target driving instruction according to the fused video data and the target driving plan; the target driving instruction carries steering parameters and speed parameters;

and the driving instruction forwarding module is used for sending the target driving instruction to the central control platform, and the central control platform controls the vehicle to run according to the steering parameter and the speed parameter.

In one embodiment, the local plan obtaining module is configured to receive local path plan information sent by the target roadside device based on the global path plan when the vehicle is within a transmission range of the target roadside device.

A computer device comprising a memory storing a computer program and a processor which when executing the computer program performs the steps of:

A computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

The vehicle driving assisting method, the vehicle driving assisting device, the computer equipment and the storage medium firstly acquire positioning information and destination information based on a vehicle, and send the positioning information and the destination information to a cloud service platform; global path planning information is then received, the global path planning information being determined by the cloud service platform based on the location information and the destination information. And acquiring local path planning information determined based on the global path planning. And finally, fusing the local path planning information and the global path planning information to obtain the target driving plan of the vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the vehicle-mounted equipment fuses the global path planning information and the local path planning information, so that the vehicle-mounted equipment can comprehensively consider global path planning and local path planning when the vehicle assists driving, the reliability of target path planning is improved, and the driving safety of the vehicle can be improved.

A method of assisting driving of a vehicle, the method comprising:

acquiring road side video data and transmitting the road side video data to a cloud service platform;

receiving global path planning information sent by the cloud service platform for a target vehicle based on the road side video data;

carrying out recognition on the road side frequency data to obtain lane information and barrier information;

determining local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information;

and when the target vehicle is in the transmission range, the local path planning information is sent to the vehicle-mounted equipment of the target vehicle.

In one embodiment, the method further comprises at least one of:

when the target vehicle is in the transmission range, if a road side video request sent by the vehicle-mounted equipment of the target vehicle is received, the road side video request is sent to the vehicle-mounted equipment of the target vehicle;

and when the target vehicle is in the transmission range, if the road side data is analyzed to obtain an analysis result of the road abnormality, the road side data is sent to the vehicle-mounted equipment of the target vehicle.

In one embodiment, the sending the local path planning information to the vehicle-mounted device of the target vehicle when the target vehicle is in the transmission range includes:

calibrating the local path planning information through a high-precision map;

and when the target vehicle is in the transmission range, transmitting the calibrated local path planning information to vehicle-mounted equipment of the target vehicle.

A vehicle assisted driving apparatus, the apparatus comprising:

the video acquisition and forwarding module is used for acquiring road side video data and sending the road side video data to the cloud service platform;

the global planning receiving module is used for receiving global path planning information which is sent by the cloud service platform and aims at a target vehicle based on the road side video data;

the video data identification module is used for identifying lanes and obstacles on the road side image to obtain lane information and obstacle information;

the local path planning module is used for determining local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information;

and the local path forwarding module is used for sending the local path planning information to the vehicle-mounted equipment of the target vehicle when the target vehicle is in the transmission range.

In one embodiment, the apparatus further comprises at least one of the following two modules:

the video passive sending module is used for sending the road side video data to the vehicle-mounted equipment of the target vehicle if the road side video data request sent by the vehicle-mounted equipment of the target vehicle is received when the target vehicle is in the transmission range;

and the video active sending module is used for sending the road side frequency data to the vehicle-mounted equipment of the target vehicle if the road side frequency data are analyzed to obtain an analysis result of road abnormality when the target vehicle is in the transmission range.

In one embodiment, the apparatus further comprises a path planning calibration module;

the path planning calibration module is used for calibrating the local path planning information through a high-precision map;

and the local path forwarding module is used for sending the calibrated local path planning information to the vehicle-mounted equipment of the target vehicle when the target vehicle is in the transmission range.

The vehicle driving assisting method, the vehicle driving assisting device, the computer equipment and the storage medium acquire road side video data and send the road side video data to the cloud service platform; receiving global path planning information sent by the cloud service platform for a target vehicle based on the road side video data; carrying out recognition on the road side frequency data to obtain lane information and barrier information; determining local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information; and when the target vehicle is in the transmission range, the local path planning information is sent to the vehicle-mounted equipment of the target vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the road side equipment determines local path planning information of a target vehicle based on global path planning, and sends the local path planning information to vehicle-mounted equipment of the target vehicle when the target vehicle enters a transmission range. Thus, the global path planning and the local lane information and the obstacle information are comprehensively considered, and the local path planning is obtained, so that the reliability of the local path planning information can be improved, and the driving safety of the vehicle can be improved.

Drawings

FIG. 1 is a diagram of an application environment for a vehicle assisted driving method in one embodiment;

FIG. 2 is a flow chart of a method of assisting a vehicle in driving in one embodiment;

FIG. 3 is a flow chart of a method of assisting a vehicle in driving in another embodiment;

FIG. 4 is a block diagram of a vehicle driving assist apparatus in one embodiment;

FIG. 5 is a block diagram showing a configuration of a vehicle driving assist apparatus according to another embodiment;

fig. 6 is an internal structural diagram of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The vehicle driving assisting method provided by the application can be applied to an application environment shown in fig. 1. A road on which the vehicle 102 travels is provided with a roadside apparatus 104, and the vehicle 102 is provided with an in-vehicle apparatus communicatively connected to the roadside apparatus 104. Each roadside device 104 is communicatively connected to a cloud service platform 106. The cloud service platform 106 is in direct communication connection with the on-board devices of the vehicle 102, or the cloud service platform 106 is in indirect communication connection with the on-board devices of the vehicle 102 through forwarding by the roadside device 104. The vehicle-mounted equipment acquires positioning information and destination information based on the vehicle 102 and sends the positioning information and the destination information to the cloud service platform 106; the vehicle-mounted equipment receives global path planning information sent by the cloud service platform 106 based on the positioning information and the destination information; when the vehicle 102 is in the transmission range of the target road side equipment, the vehicle-mounted equipment receives local path planning information sent by the target road side equipment based on the global path planning; and the vehicle-mounted equipment fuses the local path planning information and the global path planning information to obtain the target driving plan of the vehicle.

The onboard devices of the vehicle 102 may be, but are not limited to, smart phones, automobile recorders, various personal computers, notebook computers, tablet computers, and portable wearable devices. The roadside device 104 includes a Road Side Unit (RSU), which may be a microwave apparatus employing DSRC (Dedicated ShortRange Communication, dedicated short-range communication) technology. The cloud service platform 106 may be a stand-alone server or a server cluster composed of a plurality of servers. In a preferred embodiment, the in-vehicle device is a smart phone. Due to the popularity of smartphones, the cost of vehicle-mounted devices for vehicle installation can be reduced by using smartphones as the vehicle-mounted devices. Further, the hardware requirements of the smart phone are the ultra-high performance graphics processor GPU (Graphics Processing Unit) and the cpu CPU (Central Processing Unit), which can process a large amount of image data; a global positioning system GPS (Global Positioning System) module is also required. The ultra-high performance graphics processor may refer to a graphics processor with a processing frequency not lower than 2500MHz (megahertz), for example, the GPU may be of the type: G. the central processing unit refers to a CPU with a processing frequency not lower than 2.6GHz (gigahertz), for example, the type of the CPU may be: intel cool Rui 7 8700. The software can support a common artificial intelligence development framework, a deep learning framework, a scientific calculation framework and an image processing framework.

In one embodiment, as shown in fig. 2, a vehicle driving assisting method is provided, which is described by taking an on-vehicle device of the vehicle 102 in fig. 1 as an example, and includes the following steps:

s202, positioning information and destination information based on the vehicle are obtained, and the positioning information and the destination information are sent to the cloud service platform.

The in-vehicle apparatus acquires positioning information and destination information of the vehicle before the trip starts. After the driver gets on the vehicle and starts the vehicle, the positioning information of the vehicle is obtained through a GPS module built in the vehicle-mounted device, and the positioning information of the vehicle can comprise the current longitude and latitude of the vehicle.

The destination information may refer to information of a destination in one trip, which may be a destination manually or phonetically input by the driver, or a destination determined after the vehicle-mounted device performs analysis based on current location information of the vehicle.

After the vehicle-mounted equipment acquires the positioning information and the destination information based on the vehicle, the positioning information and the destination information are sent to the cloud service platform for the cloud service platform to conduct global path planning on the journey of the vehicle.

S204, receiving global path planning information sent by the cloud service platform based on the positioning information and the destination information.

And the cloud service platform collects positioning information and destination information sent by the vehicle-mounted equipment. The cloud service platform can conduct global path planning according to the positioning information and the destination information and combining data sent by each road side device to obtain global path planning information.

The cloud service platform can collect road side video data sent by the road side equipment and support data for global path planning of the cloud service platform. The road side video data are video data collected by road side equipment. The cloud service platform may collect traffic data. The traffic data is data of traffic conditions obtained by analyzing the road side data, and for example, the traffic data can comprise at least one of traffic jam information and traffic flow information. Therefore, the cloud service platform can combine traffic data to determine global path planning information, so that the reliability of the global path planning information is improved. The traffic data may be obtained by analyzing the road side video data by the road side device and sent to the cloud service platform. The traffic data can also be obtained by analyzing the road side video data by the cloud service platform, so that the resource consumption of road side equipment can be reduced, and the cost of the road side equipment is reduced. It should also be noted that traffic congestion information may also be used to train a traffic congestion model. The congestion level is determined through the traffic congestion model, and the determined traffic congestion level can be stored in a database for later analysis, such as data statistical analysis of traffic congestion conditions.

The cloud service platform also collects road information data, and thus, data support is provided for global path planning of the cloud service platform. The road information data may be road information data obtained by analyzing by the road side device according to the road side video data and the position information of the road side device. The road information data may also be road information data obtained by analyzing by the cloud service platform according to road side video data sent by the road side terminal and vehicle-mounted video data sent by the vehicle-mounted device. The analysis of the road information data may be accomplished through a trained neural network model. Therefore, the cloud service platform can integrate road information data and determine global path planning information, so that the reliability of the global path planning information is improved.

The neural network model determination process comprises the following steps: collecting road side video data and vehicle-mounted video data, fusing the vehicle-mounted video data and the road side video data to obtain fused video data, inputting the fused video data into an initialized neural network model, and determining a training result; and when the loss function values of the training result and the target result reach the optimal condition of the model, obtaining the finally trained neural network model. The target result is accurate road information data determined manually. The training result is the result of road information data obtained through a neural network model in the training process.

The cloud service platform can also collect real-time traffic situation information. The traffic situation information can be sent by the road side equipment, and the traffic situation information obtained by analyzing the road side data by the road side equipment is sent to the cloud service platform. The traffic situation information can also be traffic situation information obtained by analyzing the received road side data sent by the road side equipment by the cloud service platform. The traffic situation information includes status information of each traffic participant. For example, the road side video data includes a pedestrian, and the pedestrian moves in a direction and at a certain speed. Thus, the cloud service platform can integrate historical traffic data and real-time traffic situation to determine global path planning information. Thus, the reliability of the global path planning information is improved.

S206, local path planning information determined based on the global path planning is acquired.

The local path planning information may be determined by the vehicle-mounted device. After receiving the road side data sent by the target road side equipment, the vehicle-mounted equipment carries out lane and obstacle recognition on the road side data to obtain lane information and obstacle information. The lane information comprises a road mark, a lane track and the like, and one road comprises at least one lane. The obstacle information may include information of an obstacle position, an obstacle size, and the like. And then the vehicle-mounted equipment obtains local path planning according to the lane information, the obstacle information and the global path planning information. Specifically, the information of a starting point and an ending point in a local area can be determined according to global path planning information and the local area corresponding to the target road side equipment; and determining local path planning information in the local area according to the starting point information and the ending point information and combining the barrier information and the road information.

The local path planning information may also be determined by the target roadside device or the cloud service platform and then sent to the vehicle-mounted device. The target roadside device may perform data transceiving through DSRC, LTE-V (Long Term Evolution-Vehicle) or 5G (5 th-Generation, fifth Generation mobile communication technology) technologies. The transmitting and receiving mode can adopt a C-V2X (Cellular V2X, namely V2X based on a Cellular communication technology) and DSRC compatible mode, so that handshake communication can be realized between the transmitting and receiving mode and vehicle-mounted equipment of various modules. Each road side device has a corresponding transmission range, and when the vehicle enters the transmission range of the target road side device, the target road side device sends the local path planning information of the local area corresponding to the target road side device to the vehicle-mounted device.

The target roadside device or cloud service platform may determine local path planning information based on the global path planning. For example, the target road side device may perform lane and obstacle recognition on the collected road side data to obtain lane information and obstacle information. The lane information comprises a road mark, a lane track and the like, and one road comprises at least one lane. The obstacle information may include information of an obstacle position, an obstacle size, and the like. The target road side equipment can combine the lane information, the obstacle information and the global path planning information to obtain the local path planning. Specifically, the information of a starting point and an ending point in a local area can be determined according to global path planning information and the local area corresponding to the target road side equipment; and determining local path planning information in the local area according to the starting point information and the ending point information and combining the barrier information and the road information.

In one preferred embodiment, the obtaining local path planning information determined based on the global path planning comprises: and when the vehicle is in the transmission range of the target road side equipment, receiving local path planning information sent by the target road side equipment based on the global path planning. Therefore, the road side equipment is used for planning the local path, so that the vehicles can be ensured to run continuously and efficiently.

S208, the local path planning information and the global path planning information are fused to obtain the target driving plan of the vehicle.

After receiving the local path planning information and the global path planning information, the vehicle-mounted device can fuse the local path planning and the global path planning to obtain the current driving planning of the vehicle, namely the target driving planning. The global path planning information is a path planning from a starting point to a destination, and details of the planning can be used for driving on which road, namely the global path planning information comprises road information, and the road information can be a road identifier. The starting point is the acquired positioning information of the vehicle at the start of one trip. The local path planning information is a specific path planning in a local area, and the details of the specific path planning can be specific to which lane on which road, i.e. the local path planning information comprises road information and lane information. The local area refers to an area range corresponding to the target road side equipment.

When a vehicle enters a local area corresponding to a road side device, a target driving plan of the vehicle when the vehicle is currently running can be obtained by fusing local path planning information sent by the road side device and global path planning information sent by a cloud service platform. The target driving plan comprises road information of the whole journey and lane information of the current local area.

Based on the vehicle driving assisting method of the embodiment, the vehicle-mounted device firstly acquires positioning information and destination information based on a vehicle and sends the positioning information and the destination information to the cloud service platform; global path planning information is then received, the global path planning information being determined by the cloud service platform based on the location information and the destination information. And when the vehicle is in the transmission range of the target road side equipment, the vehicle-mounted equipment receives the local path planning information sent by the target road side equipment based on the global path planning. And finally, merging the local path planning information and the global path planning information by the vehicle-mounted equipment to obtain the target driving plan of the vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the vehicle-mounted equipment fuses the global path planning information and the local path planning information, so that the vehicle-mounted equipment can comprehensively consider global path planning and local path planning when the vehicle assists driving, the reliability of target path planning is improved, and the driving safety of the vehicle can be improved.

In one embodiment, the method further comprises: when the vehicle is in the transmission range of the target road side equipment, receiving road side video data sent by the target road side equipment; acquiring vehicle-mounted video data based on a vehicle; and fusing the road side video data and the vehicle-mounted video data to obtain fused video data.

When the vehicle is required to be in the transmission range of the target road side equipment, the vehicle-mounted equipment of the vehicle can only receive the road side video data sent by the target road side equipment. The road side video data can be actively sent by the target road side equipment or passively sent by the road side equipment. The active sending of the road side device may be that the road side device analyzes the collected road side data, and when the road is found to be abnormal, the road side device actively sends the road side data to the vehicle in the transmission range corresponding to the road side device, that is, the vehicle in the local area corresponding to the road side device. Conditions of road anomalies include, but are not limited to, obstacles such as falling rocks, sprinklers; pavement potholes; the daytime visibility is lower than a preset value; flame is arranged in the tunnel. The road side equipment can preprocess the image data in the processing process, and the preprocessing flow comprises image enhancement, noise reduction, defogging, rain and snow removal and the like. After the preprocessing is completed, the road side equipment further transforms, reconstructs and synthesizes the preprocessing result to reconstruct the image.

The passive transmission of the road side device may be that when a road side video request sent by the vehicle-mounted device is received, the road side device passively transmits corresponding road side video data to the vehicle-mounted device according to the road side video request. The road side image request may be a request transmitted through the vehicle-mounted device when the driver wants to know the road condition of the forward road. The road side video request may carry current position information and preset position information in the target driving plan, where the preset position information may be position information that is a preset distance from the current position information in the target driving plan. E.g., 800 meters ahead of the current location in the target driving plan, and thus, request roadside video data within 800 meters ahead in the target driving plan. The preset position information may also be a position of a front road abnormality, and thus, road side video data at the position of the road abnormality is requested. Therefore, the driver can conveniently know the road condition, and the reliability of auxiliary driving is further improved.

The vehicle-mounted device may acquire the vehicle-mounted video data through an acquisition device of the vehicle-mounted device, such as a camera. The in-vehicle video data is video data collected on a vehicle by an in-vehicle apparatus.

And the vehicle-mounted equipment fuses the road side video data and the vehicle-mounted video data after receiving the road side video data sent by the target road side equipment and acquiring the vehicle-mounted video data based on the vehicle to obtain fused video data. The fusing the video data includes fusing the road side video data into the vehicle video data at a view angle of the vehicle-mounted device. The fused video data can also be displayed through the vehicle-mounted equipment. Thus, the visual field of the in-vehicle video data is expanded, so that a more reliable vehicle-assisted driving method can be provided.

In one embodiment, fusing road side video data and vehicle-mounted video data to obtain fused video data includes: analyzing the vehicle-mounted video data to obtain the current visual field distance of the vehicle; determining a target field of view distance according to the braking distance of the vehicle; and adjusting the fusion road side video data, the vehicle-mounted video data and the obtained visual field distance of the fusion video data according to the target visual field distance.

The current field of view distance of the vehicle is the field of view distance of the in-vehicle video data collected by the in-vehicle device of the vehicle, that is, the current field of view distance of the in-vehicle device. The current annual visual field distance of the vehicle can be obtained by analyzing the vehicle-mounted video data collected by the vehicle-mounted equipment.

The braking distance of the vehicle can be determined according to the running speed of the vehicle and the preset minimum reaction time. The vehicle running speed can be obtained from an on-board Unit (OBU) of the vehicle or can be determined by analyzing the change situation of the positioning information through map application software on the on-board device. The preset minimum reaction time is the minimum time required for emergency braking by the driver after finding an obstacle, and may be 3 seconds, 2 seconds, etc. The braking distance is obtained by multiplying the vehicle travel speed by the preset minimum reaction time.

The target field of view distance is determined from the stopping distance, and the stopping distance can be multiplied by a factor greater than or equal to 1 to obtain the target field of view distance. For example, the braking distance may be directly set as the target visual field distance, or a distance 1.5 times the braking distance may be set as the target visual field distance. And finally, adjusting the fusion road side video data and the vehicle-mounted video data according to the target visual field distance, and obtaining the visual field distance of the fusion video data. For example, the target visual field distance may be set as the visual field distance of the fusion video data, or the distance obtained by multiplying the target visual field distance by a coefficient may be set as the visual field distance of the fusion video data. The field of view distance of the fusion video data refers to the distance from the vehicle to the position of the video content which can be displayed in the fusion video data. In this way, more reliable vehicle assisted driving can be provided.

In one embodiment, when the vehicle is within the transmission range of the target roadside device, receiving the roadside video data sent by the target roadside device includes: transmitting a road side video request to target road side equipment in a transmission range; and receiving the road side video data sent by the target road side equipment according to the road side video request.

In this embodiment, an interface for actively requesting road side video data is provided for the in-vehicle apparatus. Thus, when the driver needs, such as in the case of congestion of a road ahead, the driver wants to know the road side video data at 800 meters before the current position in the target path plan, the road side video request can be sent to the target road side device in the outgoing range, and then the road side video data sent by the target road side device according to the road side video request is received. The road side video request may carry current position information and preset position information in the target driving plan, where the preset position information may be position information that is a preset distance from the current position information in the target driving plan. The preset position information may also be a position of a front road abnormality, and thus, road side video data at the position of the road abnormality is requested. Therefore, the fused video data obtained by fusing the road side video data and the vehicle-mounted video data can meet the targeted requirements of users. Therefore, the driver can know the road condition in a targeted way, and the reliability of auxiliary driving is further improved.

In one embodiment, the method for fusing road side video data and vehicle-mounted video data, after obtaining the fused video data, further includes: determining a target driving instruction according to the fused video data and the target driving plan, wherein the target driving instruction carries steering parameters and speed parameters; and sending the target driving instruction to the central control platform, and controlling the vehicle to run by the central control platform according to the steering parameter and the speed parameter.

The target driving instruction carries steering parameters and speed parameters. The steering parameter refers to a parameter that controls steering of the vehicle, such as a torque parameter for controlling steering wheel torque. The speed parameter refers to a parameter that controls the running speed of the vehicle. The vehicle-mounted device can determine the vehicle running track according to the fused video data, and can further correct the vehicle running track according to the target driving plan. For example, when the vehicle running track determined from the fused video data does not coincide with the target driving plan, the vehicle running track may be corrected to a running track that coincides with the target driving plan. The vehicle-mounted device can determine the steering parameter carried in the target driving instruction according to the vehicle running track or the corrected vehicle running track. The vehicle-mounted device can determine the safety distance between the obstacle and the vehicle according to the fusion video data, and then determine the speed parameter carried in the target driving instruction according to the safety distance and the preset minimum reaction time. When the vehicle-mounted device determines the vehicle running track according to the fused video data, the vehicle running track is determined according to the visual field distance of the fused video data. Specifically, when the field of view distance of the fusion video data is 800 meters, the vehicle running track within 800 meters can be determined according to the fusion video data. Further, the vehicle running track within 800 meters can be calibrated in combination with the target driving plan. Therefore, the running track of the vehicle can be more accurate and reasonable. For example, at 800 m, if a lane is likely to be taken in the middle according to the fused video data, but if a right turn is required at 803 m according to the target driving plan, the vehicle travel track at 800 m may be corrected to be taken in the right lane at this time according to the target driving plan.

The central control platform is a vehicle-mounted central control platform and is used for controlling the state of the vehicle, such as controlling what music is played and the volume of a player, and controlling the running direction and speed of the vehicle by sending instructions. The central control platform controls the running of the vehicle according to the steering parameters and the speed parameters, and the steering parameters can be transmitted to a steering wheel controller of the vehicle through the central control platform, and the speed parameters can be transmitted to a speed controller of the vehicle. The central control platform can also feed back the steering control and speed control results to the vehicle-mounted equipment, so that a closed-loop control system is formed.

In this embodiment, since the vehicle-mounted device determines the target driving instruction according to the fused video data and the target driving plan. In this way, the determined target driving instruction is more reliable. And hiding, sending a more reliable target driving instruction to the central control platform, and controlling the vehicle to run by the central control platform according to the steering parameter and the speed parameter, so that more reliable vehicle auxiliary driving can be provided.

In one embodiment, as shown in fig. 3, a vehicle driving assisting method is provided, which is illustrated by using the method applied to the road side device 104 in fig. 1 as an example, and includes the following steps:

s301, obtaining road side video data and sending the road side video data to a cloud service platform.

The road side video data are video data collected by road side equipment. The road side video data collected by each road side are sent to the cloud service platform, and overall management is carried out by the cloud service platform.

S303, receiving global path planning information sent by the cloud service platform aiming at the target vehicle based on the road side video data.

The target vehicle is a vehicle for global path planning of the cloud service platform. For example, it may be that a driver on a target vehicle sends positioning information and destination information based on the vehicle to a cloud service platform through an on-board device on the vehicle to request global path planning information for the vehicle. And the road side equipment receives global path planning information which is sent by the cloud service platform and aims at the target vehicle based on the road side video data.

The cloud service platform may collect traffic data based on the road side frequency data. The traffic data is data of traffic conditions obtained by analyzing the road side data, and for example, the traffic data can comprise at least one of traffic jam information and traffic flow information. Therefore, the cloud service platform can combine traffic data to determine global path planning information, so that the reliability of the global path planning information is improved. The traffic data may be obtained by analyzing the road side video data by the road side device and sent to the cloud service platform. The traffic data can also be obtained by analyzing the road side video data by the cloud service platform, so that the resource consumption of road side equipment can be reduced, and the cost of the road side equipment is reduced. It should also be noted that traffic congestion information may also be used to train a traffic congestion model. The congestion level is determined through the traffic congestion model, and the determined traffic congestion level can be stored in a database for later analysis, such as data statistical analysis of traffic congestion conditions.

The cloud service platform can also collect road information data based on the road side data, and thus, the data support is made for global path planning of the cloud service platform. The road information data may be road information data obtained by analyzing by the road side device according to the road side video data and the position information of the road side device. The road information data may also be road information data obtained by analyzing by the cloud service platform according to road side video data sent by the road side terminal and vehicle-mounted video data sent by the vehicle-mounted device. The analysis of the road information data may be accomplished through a trained neural network model. Therefore, the cloud service platform can integrate road information data and determine global path planning information, so that the reliability of the global path planning information is improved.

The cloud service platform can also collect real-time traffic situation information based on road side frequency data. The traffic situation information can be sent by the road side equipment, and the traffic situation information obtained by analyzing the road side data by the road side equipment is sent to the cloud service platform. The traffic situation information can also be traffic situation information obtained by analyzing the received road side data sent by the road side equipment by the cloud service platform. The traffic situation information includes status information of each traffic participant. For example, the road side video data includes a pedestrian, and the pedestrian moves in a direction and at a certain speed. Thus, the cloud service platform can integrate historical traffic data and real-time traffic situation to determine global path planning information. Thus, the reliability of the global path planning information is improved.

S305, identifying lanes and obstacles on the road side frequency data to obtain lane information and obstacle information.

The road side equipment can identify lanes and obstacles in each frame of image of the road side video data in an image identification mode. The lane information comprises a road mark, a lane track and the like, wherein one road comprises at least one lane. The obstacle information may include information of an obstacle position, an obstacle size, and the like.

S307, determining local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information.

The road side equipment can acquire starting point position information and end point position information of the target vehicle in the target local area according to the global path planning information; then, a local path plan of the target vehicle is determined based on the start position information, the end position information, and the lane information and the obstacle information.

Further, the road side device can also acquire the starting point direction information and the ending point direction information of the target vehicle in the target local area according to the global path planning information; and then optimizing the local path planning of the target vehicle according to the starting point direction information and the ending point direction information. Specifically, in the case where only the start point and the end point are known, the local path plan is not necessarily optimal since the direction conditions at the start point and the end point are considered. Therefore, the local path planning can still be kept to be the optimal path planning on the premise of large global path planning by adding the direction factors of the starting point and the ending point.

When the global path planning is optimally updated, the road side equipment can also optimally update the local path planning information of the target vehicle obtained before the optimization updating according to the lane information, the obstacle information and the global path planning information.

S309, when the target vehicle is within the transmission range, the local path planning information is transmitted to the in-vehicle device of the target vehicle.

Each road side device has a corresponding transmission range, and when the target vehicle enters the transmission range of the road side device, the road side device sends the local path planning information of the local area corresponding to the road side device to the vehicle-mounted device of the target vehicle. Therefore, the vehicle-mounted equipment can acquire the target driving plan by combining the local path planning information and the global path planning information.

Based on the vehicle driving assisting method of the embodiment, road side equipment acquires road side data and sends the road side data to a cloud service platform; the road side equipment receives global path planning information which is sent by the cloud service platform and is aimed at a target vehicle based on road side video data; the road side equipment recognizes a lane and an obstacle on the road side frequency data to obtain lane information and obstacle information; the road side equipment determines local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information; when the target vehicle is within the transmission range, the road side device transmits the local path planning information to the on-vehicle device of the target vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the road side equipment determines local path planning information of the target vehicle based on the global path planning, and sends the local path planning information to the vehicle-mounted equipment of the target vehicle when the target vehicle enters the transmission range. Therefore, the road side equipment comprehensively considers the global path planning, the local lane information and the obstacle information to obtain the local path planning, so that the reliability of the local path planning information can be improved, and the driving safety of the vehicle can be improved.

In one embodiment, in order to enable the vehicle-mounted device to know the road side video data collected by the road side device, the visual field range of the vehicle-mounted device is expanded, and the running safety of the vehicle is improved. The method further comprises at least one of the following two cases:

(1) And when the target vehicle is in the transmission range, if a road side video request sent by the vehicle-mounted device of the target vehicle is received, sending the road side video request to the vehicle-mounted device of the target vehicle.

In this way, a way of passively transmitting roadside video data may be provided for the roadside device. The road side device passively receives the road side video request sent by the vehicle-mounted device, and then passively sends the road side video data based on the road side device to the vehicle-mounted device according to the road side video request to the vehicle-mounted device of the target vehicle, so that the visual field range of the vehicle-mounted device can be expanded.

(2) And when the target vehicle is in the transmission range, if the road side data is analyzed to obtain an analysis result of the road abnormality, transmitting the road side data to the vehicle-mounted equipment of the target vehicle.

Thus, a way of actively transmitting the roadside video data is provided for the roadside device. And the road side equipment actively analyzes the road side frequency data to obtain an analysis result of whether the road is abnormal or not. When the analysis result is that the road is abnormal, the road side image is transmitted to the vehicle-mounted equipment of the target vehicle, so that the driver on the vehicle is reminded of the front road abnormality when the road is abnormal, namely, when the situation that threatens the driving of the driver is about to occur. When the analysis result is that the road is normal, it may not be necessary to transmit the road side image to the in-vehicle device of the target vehicle.

When the road side equipment analyzes the road side video data, the video frame image of the road side video data can be identified through an image identification algorithm of abnormal road conditions. The image recognition algorithm of the abnormal road condition mainly comprises the following steps: identifying obstacles and pavement pits, detecting daytime visibility, detecting falling rocks and casts, detecting flames in tunnels and the like. Conditions of road anomalies include, but are not limited to, obstacles such as falling rocks, sprinklers; pavement potholes; the daytime visibility is lower than a preset value; flame is arranged in the tunnel. The road side equipment can preprocess the image data in the processing process, and the preprocessing flow comprises image enhancement, noise reduction, defogging, rain and snow removal and the like. After the preprocessing is completed, the road side equipment further transforms, reconstructs and synthesizes the preprocessing result to reconstruct the image.

In one embodiment, when the target vehicle is within the transmission range, the local path planning information is transmitted to an in-vehicle device of the target vehicle, including: calibrating the local path planning information through a high-precision map; and when the target vehicle is in the transmission range, transmitting the calibrated local path planning information to the vehicle-mounted equipment of the target vehicle.

A high-precision map refers to a map that is accurate at least to each lane. Such as a hundred degree map, a high-altitude map, etc. The road side equipment can calibrate the local path planning by combining a high-precision map. For example, when the road information and the lane information related to the local route planning are obviously inconsistent with the road information in the high-precision map, the road information and the lane information in the local route planning are calibrated according to the high-precision map. In the calibration process, wrong lane information in the local path planning information can be corrected, and the reliability of the local path planning information can be further improved, so that the vehicle-mounted equipment can receive the more reliable local path planning information. Thus, the safety of the vehicle running can be further improved.

It should be understood that, although the steps in the flowcharts of fig. 2-3 are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in fig. 2-3 may include multiple sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, nor do the order in which the sub-steps or stages are performed necessarily occur sequentially, but may be performed alternately or alternately with at least a portion of the sub-steps or stages of other steps or steps.

In one embodiment, as shown in fig. 4, there is provided a vehicle-assisted driving apparatus corresponding to the above-described vehicle-assisted method operating on an in-vehicle device, including:

the information acquisition and forwarding module 402 is configured to acquire positioning information and destination information based on a vehicle, and send the positioning information and the destination information to the cloud service platform;

the global planning receiving module 404 is configured to receive global path planning information sent by the cloud service platform based on the positioning information and the destination information;

a local plan obtaining module 406, configured to obtain local path plan information determined based on the global path plan;

the target planning fusion module 408 is configured to fuse the local path planning information and the global path planning information to obtain a target driving plan of the vehicle.

The vehicle auxiliary driving device firstly acquires positioning information and destination information based on a vehicle and sends the positioning information and the destination information to a cloud service platform; global path planning information is then received, the global path planning information being determined by the cloud service platform based on the location information and the destination information. And when the vehicle is in the transmission range of the target road side equipment, receiving local path planning information sent by the target road side equipment based on the global path planning. And finally, merging the local path planning information and the global path planning information to obtain the target driving plan of the vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the vehicle-mounted equipment fuses the global path planning information and the local path planning information, so that the vehicle-mounted equipment can comprehensively consider global path planning and local path planning when the vehicle assists driving, the reliability of target path planning is improved, and the driving safety of the vehicle can be improved.

In one embodiment, the local plan obtaining module 406 is configured to receive local path plan information sent by the target roadside device based on the global path plan when the vehicle is within the transmission range of the target roadside device.

In one embodiment, the apparatus further comprises:

the road side video receiving module is used for receiving the road side video data sent by the target road side equipment when the vehicle is in the transmission range of the target road side equipment;

the vehicle-mounted video acquisition module is used for acquiring vehicle-mounted video data based on a vehicle;

In one embodiment, the video data fusion module includes:

the visual field distance adjusting unit is used for adjusting the visual field distance of the fusion road side video data, the vehicle-mounted video data and the obtained fusion video data according to the target visual field distance.

In one embodiment, the roadside image receiving module includes:

The road side video request unit is used for sending a road side video request to target road side equipment in a transmission range;

the road side video receiving unit is used for receiving the road side video data sent by the target road side equipment according to the road side video request.

In one embodiment, the apparatus further comprises:

the driving instruction determining module is used for fusing the road side video data and the vehicle-mounted video data in the video data fusion module to obtain fused video data and then determining a target driving instruction according to the fused video data and the target driving plan; the target driving instruction carries steering parameters and speed parameters;

and the driving instruction forwarding module is used for sending the target driving instruction to the central control platform, and the central control platform controls the running of the vehicle according to the steering parameters and the speed parameters.

In one embodiment, as shown in fig. 5, there is provided a vehicle auxiliary driving apparatus corresponding to the above-described vehicle auxiliary method operating on a roadside device, including:

the video acquisition and forwarding module 501 is configured to acquire road side video data and send the road side video data to the cloud service platform;

the global planning receiving module 503 is configured to receive global path planning information for a target vehicle, which is sent by the cloud service platform based on the road side video data;

The video data identification module 505 is configured to identify a lane and an obstacle on a road side to obtain lane information and obstacle information;

the local path planning module 507 is configured to determine local path planning information of the target vehicle according to the lane information, the obstacle information, and the global path planning information;

the local path forwarding module 509 is configured to send local path planning information to an on-board device of the target vehicle when the target vehicle is within the transmission range.

The vehicle auxiliary driving device acquires road side video data and sends the road side video data to the cloud service platform; receiving global path planning information sent by a cloud service platform based on road side video data and aiming at a target vehicle; carrying out lane and obstacle identification on the road side frequency data to obtain lane information and obstacle information; determining local path planning information of the target vehicle according to the lane information, the obstacle information and the global path planning information; when the target vehicle is within the transmission range, the local path planning information is transmitted to the in-vehicle device of the target vehicle. Therefore, global path planning is carried out through the cloud service platform, so that the traffic efficiency of the whole traffic network can be improved, traffic jam is reduced, and the decision making capability of vehicle auxiliary driving is improved; the road side equipment determines local path planning information of the target vehicle based on the global path planning, and sends the local path planning information to the vehicle-mounted equipment of the target vehicle when the target vehicle enters the transmission range. Thus, the global path planning and the local lane information and the obstacle information are comprehensively considered, and the local path planning is obtained, so that the reliability of the local path planning information can be improved, and the driving safety of the vehicle can be improved.

the video passive sending module is used for sending the road side video to the vehicle-mounted equipment of the target vehicle if the road side video request sent by the vehicle-mounted equipment of the target vehicle is received when the target vehicle is in the transmission range;

and the video active sending module is used for sending the road side video data to the vehicle-mounted equipment of the target vehicle if the road side video data are analyzed to obtain the analysis result of the road abnormality when the target vehicle is in the transmission range.

the path planning calibration module is used for calibrating the local path planning information through the high-precision map;

In one embodiment, a computer device is provided, which may be a terminal or a server, and the internal structure of which may be as shown in fig. 6. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a vehicle assisted driving method.

It will be appreciated by those skilled in the art that the structure shown in fig. 6 is merely a block diagram of some of the structures associated with the present application and is not limiting of the computer device to which the present application may be applied, and that a particular computer device may include more or fewer components than shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, a computer device is provided comprising a memory storing a computer program and a processor that when executing the computer program performs the steps of:

receiving global path planning information sent by a cloud service platform based on positioning information and destination information;

when the vehicle is in the transmission range of the target road side equipment, receiving local path planning information sent by the target road side equipment based on global path planning;

and merging the local path planning information and the global path planning information to obtain the target driving plan of the vehicle.

Acquiring road side video data and sending the road side video data to a cloud service platform;

receiving global path planning information sent by a cloud service platform based on road side video data and aiming at a target vehicle;

carrying out lane and obstacle identification on the road side frequency data to obtain lane information and obstacle information;

when the target vehicle is within the transmission range, the local path planning information is transmitted to the in-vehicle device of the target vehicle.

In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the various embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples merely represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the invention. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application is to be determined by the claims appended hereto.

Claims

1. A method of assisting driving of a vehicle, the method comprising:

the vehicle-mounted equipment acquires positioning information and destination information based on a vehicle and sends the positioning information and the destination information to a cloud service platform;

the vehicle-mounted equipment receives global path planning information of the vehicle, which is determined by the cloud service platform based on the positioning information, the destination information, road side video data, traffic data, road information data and traffic situation information, wherein the road side video data, the traffic data, the road information data and the traffic situation information are sent by target road side equipment; the road information data are obtained by analyzing the road side video data sent by the road side terminal and the vehicle-mounted video data sent by the vehicle-mounted equipment by the cloud service platform; the traffic situation information comprises state information of each traffic participant;

When the vehicle is in the transmission range of the target road side equipment, the vehicle-mounted equipment receives local path planning information which is sent by the target road side equipment and is determined based on lane information, barrier information and the global path planning; the lane information and the obstacle information are obtained by the target road side equipment carrying out lane and obstacle recognition on the road side frequency data; the local path planning information is information of a starting point and an ending point in a local area determined by the target road side equipment according to the global path planning information and the local area corresponding to the target road side equipment; determining according to the starting point and the ending point information and combining the obstacle information and the lane information;

the vehicle-mounted equipment fuses the local path planning information and the global path planning information to obtain a target driving plan of the vehicle;

the method further comprises the steps of:

when the vehicle is in the transmission range of the target road side equipment, the vehicle-mounted equipment receives road side video data sent by the target road side equipment; the road side video data is sent by the target road side equipment according to the road side video request when the road side video request sent by the vehicle-mounted equipment is received; the road side video request carries current position information and preset position information in the target driving plan; the preset position information is position information which is a preset distance away from the current position information in the target driving plan; or, the preset position information is the position of the front road abnormality;

The vehicle-mounted equipment acquires vehicle-mounted video data based on the vehicle;

the vehicle-mounted equipment fuses the road side video data and the vehicle-mounted video data to obtain fused video data;

the vehicle-mounted device fuses the road side video data and the vehicle-mounted video data to obtain fused video data, and then the vehicle-mounted device further comprises:

the vehicle-mounted equipment determines a vehicle running track according to the fusion video data; when the vehicle running track determined according to the fusion video data is inconsistent with the target driving plan, correcting the vehicle running track to be consistent with the target driving plan; the vehicle-mounted equipment determines steering parameters carried in the target driving instruction according to the vehicle running track or the corrected vehicle running track; the vehicle-mounted equipment determines the safety distance between the obstacle and the vehicle according to the fusion video data, and determines the speed parameter carried in the target driving instruction according to the safety distance and the preset minimum reaction time;

and the vehicle-mounted equipment sends the target driving instruction to a central control platform, and the central control platform controls the vehicle to run according to the steering parameter and the speed parameter.

2. The method of claim 1, wherein the fusing the roadside video data and the vehicle-mounted video data to obtain fused video data comprises:

3. A vehicle driving assist apparatus, characterized by comprising:

the information acquisition forwarding module is used for acquiring positioning information and destination information based on a vehicle by the vehicle-mounted equipment and sending the positioning information and the destination information to the cloud service platform;

the global planning receiving module is used for receiving global path planning information of the vehicle, which is determined by the vehicle-mounted equipment based on the positioning information, the destination information, road side video data, traffic data, road information data and traffic situation information and sent by target road side equipment; the road information data are obtained by analyzing the road side video data sent by the road side terminal and the vehicle-mounted video data sent by the vehicle-mounted equipment by the cloud service platform; the traffic situation information comprises state information of each traffic participant;

The local planning receiving module is used for receiving local path planning information which is sent by the target road side equipment and is determined based on lane information, barrier information and the global path planning when the vehicle is in the transmission range of the target road side equipment; the lane information and the obstacle information are obtained by the target road side equipment carrying out lane and obstacle recognition on the road side frequency data; the local path planning information is information of a starting point and an ending point in a local area determined by the target road side equipment according to the global path planning information and the local area corresponding to the target road side equipment; determining according to the starting point and the ending point information and combining the obstacle information and the lane information;

the target planning fusion module is used for fusing the local path planning information and the global path planning information by the vehicle-mounted equipment to obtain a target driving plan of the vehicle;

the road side video receiving module is used for receiving road side video data sent by the target road side equipment when the vehicle is in the transmission range of the target road side equipment; the road side video data is sent by the target road side equipment according to the road side video request when the road side video request sent by the vehicle-mounted equipment is received; the road side video request carries current position information and preset position information in the target driving plan; the preset position information is position information which is a preset distance away from the current position information in the target driving plan; or, the preset position information is the position of the front road abnormality;

The vehicle-mounted video acquisition module is used for acquiring vehicle-mounted video data based on the vehicle by the vehicle-mounted equipment;

the video data fusion module is used for fusing the road side video data and the vehicle-mounted video data by the vehicle-mounted equipment to obtain fused video data;

the driving instruction determining module is used for fusing the road side video data and the vehicle-mounted video data to obtain fused video data, and then determining a vehicle running track according to the fused video data by the vehicle-mounted equipment; when the vehicle running track determined according to the fusion video data is inconsistent with the target driving plan, correcting the vehicle running track to be consistent with the target driving plan; the vehicle-mounted equipment determines steering parameters carried in the target driving instruction according to the vehicle running track or the corrected vehicle running track; the vehicle-mounted equipment determines the safety distance between the obstacle and the vehicle according to the fusion video data, and determines the speed parameter carried in the target driving instruction according to the safety distance and the preset minimum reaction time;

and the driving instruction forwarding module is used for sending the target driving instruction to the central control platform by the vehicle-mounted equipment, and controlling the vehicle to run by the central control platform according to the steering parameter and the speed parameter.

4. The apparatus of claim 3, wherein the video data fusion module further comprises: the visual field distance analysis unit is used for analyzing the vehicle-mounted video data to obtain the current visual field distance of the vehicle; a target visual field determining unit for determining a target visual field distance according to a braking distance of the vehicle; and the visual field distance adjusting unit is used for adjusting and fusing the road side video data and the vehicle-mounted video data according to the target visual field distance to obtain the visual field distance of the fused video data.

5. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 2 when the computer program is executed.

6. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 2.