CN111071263A

CN111071263A - Control method, device, system and equipment for automatically driving vehicle

Info

Publication number: CN111071263A
Application number: CN201911247913.2A
Authority: CN
Inventors: 堵明明; 刘晨楠; 张笑枫; 李景才; 侯广大; 王秀峰; 黄淋淋
Original assignee: Suzhou Zhijia Technology Co Ltd
Current assignee: Suzhou Zhijia Technology Co Ltd; PlusAI Corp
Priority date: 2019-12-09
Filing date: 2019-12-09
Publication date: 2020-04-28
Anticipated expiration: 2039-12-09
Also published as: CN111071263B

Abstract

The specification provides a control method, a device, a system and equipment for an automatic driving vehicle, wherein the method comprises the steps of monitoring network signals at the driving position of the vehicle in real time, acquiring network state data of all road sections in a driving track of the vehicle, and determining an area with better signals in the driving process of the vehicle. Based on the collected data reported by the vehicle, the control instruction is sent to the vehicle in the area with better signal, so that the control instruction can be accurately and timely sent to the vehicle, the vehicle can be accurately controlled, and the running safety of the automatic driving vehicle is improved.

Description

Control method, device, system and equipment for automatically driving vehicle

Technical Field

The present disclosure relates to automatic driving technologies, and in particular, to a method, an apparatus, a system, and a device for controlling an automatic driving vehicle.

Background

The automatic driving technology has been developed in a rapid manner in the last decade, and the automatic driving vehicle usually collects vehicle and road condition data and sends the data to a remote control center, and the remote control center can send a control instruction to the vehicle based on the received data so as to control the vehicle to run safely. Autonomous vehicles and remote control centers require data transmission and interaction, using data transmission networks such as: 4G (fourth generation mobile communication technology), 5G (fifth generation mobile communication technology), etc., the signal stability and coverage of the data transmission network may affect the result of data transmission. The existing data transmission signal coverage strength may not be comprehensive enough, and the control of the automatic driving vehicle is influenced, so that the automatic driving vehicle has a larger danger. How to provide a safety control scheme for an automatic driving vehicle is a technical problem which needs to be solved urgently in the field.

Disclosure of Invention

An object of the embodiments of the present specification is to provide a method, an apparatus, a system, and a device for controlling an autonomous vehicle, which enable safe driving of the autonomous vehicle.

In one aspect, an embodiment of the present specification provides a control method for an autonomous vehicle, including:

receiving collected data sent by a vehicle;

acquiring position network state data and road section network state data in the vehicle driving track;

determining an area with the network signal intensity greater than a preset intensity threshold according to the position network state data and the road section network state data;

and sending a control instruction to the vehicle in the area where the network signal intensity is greater than a preset intensity threshold value according to the acquired data.

Further, in some embodiments of the present description, the method further comprises:

determining the network signal intensity of each track point in the vehicle driving track according to the collected historical position network state data and historical road section network state data;

marking the network signal intensity of each track point in the vehicle driving track at a position corresponding to the electronic map;

and updating the network signal strength marked in the electronic map according to the position network state data and the road section network state data in the vehicle running track.

determining whether the vehicle is about to run to a network coverage blind area or whether the network signal intensity is smaller than the preset intensity threshold value area according to the network signal intensity marked in the electronic map and the position data in the acquired data;

and if so, sending a control instruction for suspending data transmission to the vehicle.

determining whether the vehicle is about to run to a network coverage blind area or whether the network signal intensity is smaller than the preset intensity threshold value area according to the network signal intensity marked in the electronic map and the position data of the acquired data;

if so, determining road condition information of the vehicle according to the acquired data sent in a preset time period before the vehicle runs to the network coverage blind area or the network signal intensity is smaller than a preset intensity threshold value area;

and sending a control instruction of acceleration or deceleration to the vehicle before the vehicle runs to the network coverage blind area or the network signal intensity is smaller than the preset intensity threshold value area according to the road condition information.

Further, in some embodiments of the present specification, the sending a control command to the vehicle in an area where the network signal strength is greater than a preset strength threshold according to the collected data includes:

determining the priority of the acquired data, and if the priority of the acquired data is greater than a preset priority, judging the network signal intensity of the current position of the vehicle according to the position network state data;

and if the network signal intensity of the current position of the vehicle is smaller than a preset intensity threshold value, sending a control instruction for delaying transmission of the acquired data to the vehicle.

Further, in some embodiments of the present specification, the sending a control instruction to the vehicle to delay transmission of the collected data includes:

according to the network signal intensity marked in the electronic map, determining a target area with the network signal intensity which is closest to the current position of the vehicle and is greater than the preset intensity threshold;

and sending a control instruction to the vehicle, wherein the control instruction is transmitted when the acquired data is delayed until the vehicle runs to the target area.

after the collected data sent by the vehicle are received, determining the priority corresponding to each collected data;

determining the current position of the vehicle and the network signal strength of a front preset road section according to the position network state data and the road section network state data;

and determining a data transmission mode corresponding to each acquired data according to the priority corresponding to the acquired data and the network signal strength, and sending the data transmission mode to the vehicle, wherein the data transmission mode comprises a data transmission network, a data transmission sequence and a data transmission road section.

and according to the acquired data and the network signal strength marked in the electronic map, if the fact that the communication of the vehicle is not recovered in a specified time period after the vehicle enters a network coverage blind area is determined, remotely connecting a camera of the vehicle or sending a connection request to a security officer of the vehicle.

Further, in some embodiments of the present description, the collecting data includes: before the vehicle starts, receiving the weight of the vehicle obtained by a vehicle-mounted weighing system of the vehicle;

the method further comprises the following steps:

after the weight of the vehicle is received, determining whether the vehicle is overloaded or not according to the weight, if the vehicle is determined not to be overloaded, sending a control instruction for allowing departure to the vehicle, and if the weight is larger than the vehicle overload threshold value, sending a control instruction for forbidding starting to the vehicle.

In another aspect, the present specification provides a control apparatus of an autonomous vehicle, including:

the data receiving module is used for receiving the acquired data sent by the vehicle;

the network monitoring module is used for acquiring position network state data and road section network state data in the vehicle running track;

the signal intensity determining module is used for determining an area with the network signal intensity greater than a preset intensity threshold according to the position network state data and the road section network state data;

and the control instruction sending module is used for sending a control instruction to the vehicle in an area where the network signal intensity is greater than a preset intensity threshold value according to the acquired data.

In yet another aspect, the present description provides a control system for an autonomous vehicle, the system comprising: data acquisition device, data monitoring device, data transmission device, data receiving arrangement, control center, wherein:

the data acquisition device is used for acquiring data in the driving process of the vehicle;

the data monitoring device is used for monitoring the network state of the vehicle running track and carrying out priority judgment on the data acquired by the data acquisition device;

the data transmission device is used for transmitting data;

the data receiving device is used for receiving data;

and the control center is used for sending corresponding control instructions to the vehicles according to the data collected by the data collection device, the network state monitored by the data monitoring device and the priority of the collected data.

In still another aspect, the present specification provides a control apparatus of an autonomous vehicle, including: at least one processor and a memory for storing processor-executable instructions, which when executed by the processor implement the above-described method of controlling an autonomous vehicle.

In yet another aspect, the present specification provides an autonomous vehicle comprising: at least one processor and a memory for storing processor-executable instructions, which when executed by the processor implement the above-described method of controlling an autonomous vehicle.

The control method, device, processing equipment and system for the automatic driving vehicle and the automatic driving vehicle provided by the specification can monitor the network signals at the driving position of the vehicle in real time, acquire the network state data of each road section in the driving track of the vehicle and determine the area with better signals in the driving process of the vehicle. Based on the collected data reported by the vehicle, the control instruction is sent to the vehicle in the area with better signal, so that the control instruction can be accurately and timely sent to the vehicle, the vehicle can be accurately controlled, and the running safety of the automatic driving vehicle is improved.

Drawings

In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly introduced below, it is obvious that the drawings in the following description are only some embodiments described in the present specification, and for those skilled in the art, other drawings can be obtained according to the drawings without any creative effort.

FIG. 1 is a schematic flow chart diagram of a control method for an autonomous vehicle in one embodiment of the present description;

FIG. 2 is a block diagram of a control system for an autonomous vehicle in one embodiment of the present disclosure;

FIG. 3 is a schematic diagram of a control method for an autonomous vehicle in one embodiment of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary embodiment of a control apparatus for an autonomous vehicle provided herein;

fig. 5 is a block diagram of a hardware configuration of a control server of the vehicle autonomous driving vehicle in one embodiment of the present specification.

Detailed Description

In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step should fall within the scope of protection of the present specification.

With the development of science and technology, the number of automatic driving vehicles is increased, and the automatic driving vehicles need a control center to timely and accurately send control instructions according to data collected by the vehicles so as to control the vehicles to safely drive. The vehicle and the control center need stable data transmission network for data interaction, with the continuous progress of network technology, the 5G network has gradually come into commercial use, and the automatic driving vehicle can also apply the 5G network to vehicle control. However, the coverage area of the 5G network is relatively small at present, the probability that a network coverage blind area exists is relatively high, and a network signal may be unstable.

The embodiment of the specification provides a control method for an automatic driving vehicle, which can adjust control over the vehicle in real time based on data collected by the vehicle and monitoring of a network state in a vehicle driving track, and ensure that a control instruction can be sent to the vehicle in an area with better network signals, so as to avoid data transmission failure and ensure safe driving of the automatic driving vehicle.

The control method for automatically driving the vehicle in the specification can be applied to a client or a server, and the client can be an electronic device such as a smart phone, a tablet computer, a smart wearable device (a smart watch, virtual reality glasses, a virtual reality helmet and the like), and a smart vehicle-mounted device.

Fig. 1 is a flowchart illustrating a control method of an autonomous vehicle according to an embodiment of the present disclosure, and as shown in fig. 1, the control method of an autonomous vehicle according to an embodiment of the present disclosure may include:

and 102, receiving collected data sent by the vehicle.

In a specific implementation process, the vehicle can acquire data related to vehicle running in real time in the running process, such as: the collected data in the embodiment of the present specification may be data collected by a sensor installed in a vehicle, and may include data collected by a high definition camera, a laser radar, a millimeter wave radar, an electronic braking System, a DBW (throttle by wire, which is mainly responsible for braking, throttle and steering), a high-precision electronic map, a collision sensor, a GPS (Global Positioning System)/beidou navigation System, an inertial navigation System, a time synchronization unit, and the like, installed on the vehicle. The control method of the automatic driving vehicle in the embodiment of the description can be applied to a control center of the vehicle, such as a remote control center, after corresponding data are collected by data collection equipment in the vehicle, the data can be sent to the remote control center, and the remote control center can send a control instruction to the vehicle based on the received collected data sent by the vehicle.

In the embodiment of the present description, data transmission between the vehicle and the remote control center may use 4G, 5G or other wireless transmission methods, and may be specifically set according to actual needs, and the embodiment of the present description is not particularly limited.

And 104, acquiring position network state data and road section network state data in the vehicle running track.

In a specific implementation process, the position network state data of the vehicle driving track can represent real-time network state data of the vehicle driving position, such as the state of a data transmission network of 4G, 5G and the like in the vehicle driving track can be monitored. The network status data may include network signal strength, delay, packet loss rate, etc. data at the vehicle travel location. The road segment network status data may then represent network status data for the entire road segment traveled by the vehicle, such as: the network state data of the road section between the departure place and the destination set when the vehicle departs may specifically include data such as network signal strength, delay, packet loss rate, and the like of the whole road section.

The network state data at the vehicle running position can be monitored in real time by arranging the network monitoring equipment on the vehicle. The road section network state data of the vehicle driving track can be monitored by a network monitoring device arranged on the driving road section or obtained according to historical monitoring data.

And 106, determining an area with the network signal intensity greater than a preset intensity threshold according to the position network state data and the road section network state data.

In a specific implementation process, after the position network state data and the road section network state data in the vehicle driving process are obtained, an area in which the network signal intensity is greater than a preset intensity threshold value in the vehicle driving process can be determined. Such as: the network signal intensity of the current position where the vehicle runs can be obtained according to the position network state data, the network signal intensity of a road section where the vehicle is going to run can be predicted according to the road section network state data, and if the position network state data is not consistent with the road section network state data, the position network state data can be used as a standard. The network signal strength is greater than the preset strength threshold, which may be considered to be relatively good (e.g., strong signal strength and stable signal), and a value of the preset strength threshold may be set according to actual needs.

And step 108, sending a control instruction to the vehicle in the area where the network signal intensity is greater than the preset intensity threshold value according to the acquired data.

In a specific implementation process, after an area with relatively good network signal intensity in a vehicle running track is determined, the running state of the vehicle can be determined according to the collected data uploaded by the vehicle, and a control instruction is sent to the vehicle in the area with good signal intensity. The control instruction may include an instruction for controlling the vehicle to run, and may include: the vehicle driving instructions include vehicle starting, data transmission, vehicle steering, acceleration and deceleration, traveling path change, braking and the like. The control instruction sent to the vehicle in the embodiment of the present specification may be sent by 4G, 5G or other wireless data transmission methods.

For example: in the running process of the vehicle, the vehicle can report the position of the vehicle in real time, and when the remote control center has an instruction to be issued to the vehicle, if: the destination is changed. In order to ensure real-time and effective instructions, an area with better network signals in a vehicle running track can be determined according to the acquired position network state signals and road section network state signals in the vehicle running process, and the control instructions are sent to the vehicle on the road section with better signals after being subjected to multiple security encryption authentication. For another example: in the running process of the vehicle, according to the collected data reported by the vehicle, the data are as follows: and the road condition data is used for determining that the road condition of the front running track is congested and the running path needs to be changed, and then the updated running path can be sent to the vehicle in an area with better signal strength based on the monitored network state signal. Or, based on the road condition information reported by the vehicle, it is determined that the traffic flow of the road section ahead is less, the vehicle can run in an accelerated manner, and a control command for running in an accelerated manner is sent to the vehicle in an area with better signal strength so as to control the vehicle to run in an accelerated manner.

The control method for the automatic driving vehicle provided by the embodiment of the specification can monitor the network signals at the driving position of the vehicle in real time, acquire the network state data of each road section in the driving track of the vehicle, and determine the area with better signals in the driving process of the vehicle. Based on the collected data reported by the vehicle, the control instruction is sent to the vehicle in the area with better signal, so that the control instruction can be accurately and timely sent to the vehicle, the vehicle can be accurately controlled, and the running safety of the automatic driving vehicle is improved.

On the basis of the above embodiments, in some embodiments of the present specification, the method further includes:

In a specific implementation process, historical position network state data and historical road section network state data may be obtained based on network state data collected in a vehicle driving process before the current time, such as: and taking the network state data monitored in the process that other vehicles drive in the same driving road section before the current time as historical position network state data and historical road section network state data. The network signal intensity of each track point in the vehicle driving track is determined according to the historical position network state data and the historical road section network state data, and the network signal intensity of each track point is marked at the corresponding position in the electronic map, wherein the electronic map can be a high-precision electronic map which can be used for an electronic map for navigating the vehicle driving and comprises more detailed geographical position information, lane information, traffic sign information and the like. The embodiment of the specification can mark the acquired network signal intensity of each road section in a high-precision electronic map according to historical data so as to timely acquire the network coverage condition of the position where the vehicle is located and the front position in the driving process of the vehicle and timely adjust the sending of the control command based on the network coverage condition.

In some embodiments of the present description, network state data monitored during driving of different vehicles in different road segments may be collected, or network tests may be performed in different road segments by using a network monitoring device to obtain network state data at different positions or road segments. And marking the network signal strength of each road section or position in the electronic map according to the network state data. The network signal intensity marked in the electronic map can be updated in real time according to the position network state data and the road section network state data acquired in real time in the driving process of the vehicle, so that the accuracy of marking the network signal intensity in the electronic map is improved.

In the embodiment of the specification, in the driving process of the vehicle, the vehicle records the 4G/5G network condition of the road section and reports the condition. The network coverage condition is recorded into a high-precision map after processing, the network coverage condition of the road section can be obtained from the high-precision map when the vehicle runs the same road section next time, network evaluation is carried out on the road section to which the vehicle is about to run, pre-judgment measures are taken in advance in a blind area and an area with weak signals, and the vehicle is ensured to run safely without remote network monitoring.

On the basis of the foregoing embodiments, in some embodiments of the present specification, the method may further include:

determining whether the vehicle is about to run to a network coverage blind area or whether the network signal intensity is smaller than a preset intensity threshold value area according to the network signal intensity marked in the electronic map and the position data in the acquired data;

In a specific implementation process, the collected data reported by the vehicle may include real-time position data of the vehicle, and it may be determined whether the vehicle is about to travel to a network coverage blind area (signal coverage is 0) or whether the network signal intensity is less than a preset intensity threshold area according to the position data reported by the vehicle and the network signal intensity marked in the electronic map. When the vehicle is far from the network coverage blind area or the network signal intensity is smaller than the preset intensity threshold value area to a specified distance, the vehicle can be considered to be about to enter the network coverage blind area or the network signal intensity is smaller than the preset intensity threshold value area. Such as: when the intensity of the network information marked on the electronic map is 0 or the intensity of the network signal is smaller than or equal to a certain distance in the area with the preset intensity threshold value, the vehicle can be considered to be about to run to the area with the bad network signal. The network signal intensity is not good, the data transmission is likely to fail, a control instruction for suspending data transmission can be sent to the vehicle at the moment, the vehicle is suspended to report the collected data, the data transmission can be recovered after the vehicle exits an area with poor signals, the accuracy and the stability of the data transmission are ensured, and accurate and stable data support is provided for the safe driving of the vehicle.

determining whether the vehicle is about to run to a network coverage blind area or whether the network signal intensity is smaller than a preset intensity threshold value area according to the network signal intensity marked in the electronic map and the position data of the acquired data;

and sending a control instruction of acceleration or deceleration to the vehicle before the vehicle runs to the network coverage blind area or the network signal intensity is smaller than a preset intensity threshold value according to the road condition information.

In a specific implementation process, whether the vehicle is about to travel to a network coverage blind area or whether the network signal intensity is smaller than a preset intensity threshold value area can be determined according to position data reported by the vehicle and the network signal intensity marked in the electronic map, and if it is determined that the vehicle is about to travel to the network coverage blind area or whether the network signal intensity is smaller than the preset intensity threshold value area, data collected in a preset time period before the vehicle travels to the network coverage blind area or before the network signal intensity is smaller than the preset intensity threshold value area can be obtained, so that the road condition information about the vehicle traveling is predicted. The road condition information can represent the traffic flow, the congestion condition, the road flatness condition and the like of the running road section of the vehicle. Such as: the data collected by each sensor in the vehicle can be acquired 5 minutes before the vehicle runs to a network coverage blind area or a network signal intensity is smaller than a preset intensity threshold value area, so that the information such as the traffic flow of the current road section, the number of other vehicles around the vehicle, the speed of the vehicle, the distance between the vehicle and other vehicles and the like can be determined. Based on the data reported by the vehicle, the road condition information of the vehicle running road section can be determined, and before the vehicle runs to a network coverage blind area or a network signal intensity is smaller than a preset intensity threshold value area, a control instruction for accelerating or decelerating is sent to the vehicle. Such as: if the vehicles on the current vehicle driving road section are determined to be fewer according to the data reported by the vehicles, a control instruction for accelerating driving can be sent to the vehicles to control the vehicles to advance in an accelerated manner and to exit from a signal blind area or an area with weak signals as soon as possible. If the vehicles on the road section where the current vehicle runs are determined to be more according to the data reported by the vehicles, in order to avoid that a control instruction cannot be sent to the vehicles in a signal blind area or a region with weak signals in time and ensure the running safety of the vehicles in the signal blind area or the region with weak signals, the vehicles can be sent to run at a reduced speed to ensure that the vehicles run out of the signal blind area or the region with weak signals safely.

When determining that a vehicle is about to enter an area with a poor signal, the embodiment of the specification predicts the road condition of the current driving road section of the vehicle based on the collected data sent by the vehicle before entering the signal blind area or the signal weak area, and further sends a corresponding control instruction in time before the vehicle enters the signal blind area or the signal weak area, so that the vehicle can be ensured to safely drive in the signal blind area or the signal weak area.

On the basis of the foregoing embodiments, in some embodiments of the present specification, the sending a control instruction to the vehicle in an area where the network signal strength is greater than a preset strength threshold according to the collected data includes:

In a specific implementation process, priorities of different collected data can be preset, such as: the priority of the special data (that is, the data reported when the vehicle encounters an emergency) is the highest, the priority of the data sent by the collision sensor is higher than the priority of the data reported by the GPS, and the like, and the setting rules of the priorities of different collected data may be determined according to actual use needs, and the embodiment of the present specification is not specifically limited. After the collected data reported by the vehicle are received, the priority corresponding to each collected data can be determined according to a preset priority rule, and if the priority of the reported collected data is greater than the preset priority (the level of the preset priority is set according to actual needs), the network signal intensity of the current position can be further determined according to the monitored position network state data of the current position where the vehicle is located. If the current network signal intensity is smaller than the preset intensity threshold value, namely the current network signal is not good, a control instruction for delaying transmission of the acquired data can be sent to the vehicle. When the priority ratio of the acquired data is higher, whether the network signal at the current position is stable or not and whether the signal intensity is good or not can be determined firstly, data transmission can be carried out in time in a better signal intensity state, and if the signal intensity at the current position is not good, the data transmission can be delayed so as to ensure that the acquired data with higher priority ratio can be successfully and accurately sent to a remote control center, so that the control of a vehicle is prevented from being influenced due to the failure of data transmission.

The specific value of the preset intensity threshold may be set according to actual needs, and embodiments of the present specification are not particularly limited.

On the basis of the embodiment, when the vehicle reports the collected data with higher priority and the network signal of the position of the vehicle is not good, the target area with the network signal strength which is closest to the current position of the vehicle and is greater than the preset strength threshold value can be determined according to the network signal strength marked in the electronic map; and sending a control instruction to the vehicle, wherein the control instruction is transmitted when the acquired data is delayed until the vehicle runs to the target area.

In a specific implementation process, when data transmission delay processing is performed on data with higher priority, a target area with better network signal strength closest to a vehicle driving position can be determined according to the network signal strength marked in the electronic map and the vehicle driving position, and after the vehicle drives to the target area, data transmission of data collected with higher priority is performed, so that accuracy, stability and timeliness of data transmission are ensured.

In a specific implementation process, after the collected data sent by the vehicle is received, the priority corresponding to each collected data can be respectively determined according to the preset priority rules of different collected data. And according to the position network state data and the road section network state data in the vehicle driving process monitored in real time, determining the current position in the vehicle driving process and the network signal intensity of a preset road section in front of the vehicle in the driving process, such as: the network signal intensity of the current position can be determined according to the position network state data, and the network signal intensity of a road section in front of the vehicle in running can be predicted according to the network signal intensity marked in the electronic map and the vehicle running track which are established in advance. And determining the data transmission mode adopted by each acquired data according to the priority of each acquired data and the network coverage strength of the driving road section of the vehicle, and sending the corresponding data transmission mode to the vehicle so that the vehicle can transmit the data in the corresponding transmission mode.

The data transmission mode may include a data transmission network such as: 4G, 5G (there may be 6G in the future) or other data transmission modes, and may further include an order of data transmission (e.g., transmission first with a high priority), a data transmission path segment, and the like. For example: the data with high priority can be transmitted by selecting a data transmission mode with good signal strength and good signal stability preferentially on a road section with better network signal coverage. Such as: if the 5G network signal at the current position of the vehicle is better than the 4G network signal, the data with high priority can be transmitted by adopting the 5G network at the current position, and the 4G network can be selected for transmitting the data with low priority.

The embodiment of the specification judges the priority of the collected data reported by the vehicle, and transmits the data of different priorities by adopting different data transmission modes in combination with the network coverage condition of the vehicle driving path, so that the collected data with high priority can be successfully transmitted, and a stable data basis is provided for the safe driving of the vehicle.

On the basis of the above embodiment, the method may further include:

On the basis of the above embodiments, in some embodiments of the present specification, it can be determined whether the vehicle enters a network coverage blind area according to the position information reported by the vehicle and the network signal strength marked in the electronic map, and the vehicle cannot communicate with the control center in the network coverage blind area and is in an offline state. If the fact that the communication is not recovered in the specified time period after the vehicle enters the network coverage blind area is determined, the fact that the vehicle is possibly abnormal can be considered, and fault alarming can be conducted. Meanwhile, the vehicle monitoring system can be remotely connected with a camera installed in the vehicle in time to check the current condition of the vehicle, or can contact a security officer on the vehicle to enable the security officer to determine whether the vehicle is abnormal or not. Therefore, the vehicle can be ensured to run according to a set route in the running process, and the vehicle can be remotely and timely found out to ensure the running safety of the vehicle if the vehicle is stolen or the vehicle is in failure.

On the basis of the foregoing embodiments, in some embodiments of the present specification, the acquiring data includes: before the vehicle starts, receiving the weight of the vehicle obtained by a vehicle-mounted weighing system of the vehicle;

the method further comprises the following steps:

In a specific implementation process, before a vehicle starts, the weight of the vehicle can be obtained through a vehicle-mounted weighing system, and after the weight of the vehicle is obtained, the weight can be automatically reported through a 4G or 5G network. And after receiving the reported vehicle weight, the remote control center judges whether the vehicle is overloaded, and if not, the remote control center sends a control instruction allowing starting to the vehicle. If the vehicle is found to be seriously overloaded, an instruction for prohibiting the vehicle from starting is automatically sent to a vehicle control system. Whether the vehicle is overloaded or not can be found in time before the vehicle starts, the vehicle is prevented from running under the overload condition, and the running safety of the vehicle is ensured.

Fig. 2 is a schematic block diagram of a control system of an autonomous vehicle in an embodiment of the present disclosure, and as shown in fig. 2, the control system of the autonomous vehicle in the embodiment of the present disclosure may include: data acquisition device, data monitoring device, data transmission device, data receiving arrangement, control center, wherein:

the data acquisition device is used for acquiring data in the driving process of the vehicle; data acquisition devices include, but are not limited to: high definition camera, laser radar, millimeter wave radar, electronic braking system, DBW (drive-by-wire, mainly responsible for brake, throttle and turn to), high-precision electronic map, collision sensor, GPS/big dipper navigation system, inertial navigation system, time synchronization unit etc.. The data acquisition device is mainly responsible for recording various data of the vehicle in the driving process.

The data monitoring device is used for monitoring the network state of the vehicle running track and carrying out priority judgment on the data acquired by the data acquisition device. The data monitoring device can be divided into two parts of a network monitoring device and a system monitoring device, wherein the network monitoring device includes but is not limited to the following purposes: the network conditions of 5G and 4G on a vehicle running line are collected, and risk prejudgment basis is provided through network perception. Namely, the system can be responsible for monitoring the working states (signal strength, delay, packet loss rate and the like) of the network modules such as the 5G and the 4G in real time and monitoring the network condition of the line in real time. The system monitoring equipment is mainly responsible for judging the priority of the collected data and transmitting the data with high priority according to the signal historical data of the current position and the real-time monitored data.

The data transmission device is used for transmitting data; the data receiving device is used for receiving data. The data transmission device and the data receiving device can mainly transmit and receive data through network transmission modes such as 4G, 5G and the like, and the data transmission device and the data receiving device can transmit the received data to the rear end for processing. For example, signal coverage is marked into a high-precision electronic map.

And the control center is used for sending corresponding control instructions to the vehicles according to the data collected by the data collection device, the network state monitored by the data monitoring device and the priority of the collected data. The control center can issue a control command, and when the vehicle is abnormal, the vehicle is actively controlled. The specific content and transmission mode of the control command can refer to the description of the above embodiments.

Fig. 3 is a schematic diagram of a control method of an autonomous vehicle in an embodiment of the present disclosure, and a control process of the autonomous vehicle in the embodiment of the present disclosure is specifically described below with reference to fig. 3:

and the data is collected and then sent to a data monitoring device. The data monitoring device can judge the priority of the collected data, and can judge the mode of data transmission according to the history of the network monitoring system (for example, the data can be determined according to the network signal intensity marked in the electronic map) and the real-time monitoring network state data. Data transmission methods include, but are not limited to, 4G and 5G networks (6G may be added in the future, etc.). In the network coverage blind area and the weak signal area, the following measures can be taken in advance according to historical data (such as the network signal coverage condition marked in an electronic map):

1. and feeding back to a vehicle control system to adjust the vehicle speed. And accelerating or reducing the passing speed of the vehicle according to historical labels in the high-precision map and road condition feedback information received before the vehicle enters the blind area.

2. The data transmission is suspended.

3. For high priority emergency data, it will be transmitted in the next well-signaled area. Meanwhile, a reasonable strategy can be formulated to adjust the running state of the vehicle.

4. For the control center, the issuing of the control command can be performed in an area with good signal coverage, so that the command issuing failure or repeated sending is avoided.

The data sending/receiving system can collect and process the coverage conditions (delay, signal strength and the like) of the 4G and 5G networks provided by the acquisition system, the processed information is recorded in a high-precision electronic map, data support of the signal conditions is provided in automatic driving, and the network signal coverage conditions are provided for the command issuing of the control center.

In the embodiment of the specification, various data in the data transmission process are recorded, so that the vehicle can safely, effectively and timely receive the remote control instruction in the driving process. The problem of data transmission of the vehicle under the conditions of signal blind areas and weak signals can be solved, effective strategies are provided under the scenes, and accidents under the scenes are avoided. Meanwhile, data support is provided for safe driving of the vehicle through monitoring of transmission of vehicle data.

In the present specification, each embodiment of the method is described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. The relevant points can be obtained by referring to the partial description of the method embodiment.

Based on the control method of the autonomous vehicle, one or more embodiments of the present specification further provide a control device of the autonomous vehicle. The apparatus may include systems (including distributed systems), software (applications), modules, components, servers, clients, etc. that use the methods described in the embodiments of the present specification in conjunction with any necessary apparatus to implement the hardware. Based on the same innovative conception, embodiments of the present specification provide an apparatus as described in the following embodiments. Since the implementation scheme of the apparatus for solving the problem is similar to that of the method, the specific apparatus implementation in the embodiment of the present specification may refer to the implementation of the foregoing method, and repeated details are not repeated. As used hereinafter, the term "unit" or "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.

Specifically, fig. 4 is a schematic block diagram of an embodiment of a control device of an autonomous vehicle provided in this specification, and as shown in fig. 4, the control device of an autonomous vehicle provided in this specification may include: data receiving module 41, network monitoring module 42, signal strength determining module 43, and control instruction transmitting module 44, wherein:

the data receiving module 41 may be configured to receive collected data sent by a vehicle;

the network monitoring module 42 may be configured to obtain position network state data and road segment network state data in the vehicle driving track;

a signal strength determining module 43, configured to determine, according to the location network state data and the road segment network state data, an area where the network signal strength is greater than a preset strength threshold;

and the control instruction sending module 44 may be configured to send a control instruction to the vehicle in an area where the network signal strength is greater than a preset strength threshold according to the collected data.

The control device for the automatic driving vehicle provided by the embodiment of the specification can monitor the network signals at the driving position of the vehicle in real time, acquire the network state data of each road section in the driving track of the vehicle, and determine the area with better signals in the driving process of the vehicle. Based on the collected data reported by the vehicle, the control instruction is sent to the vehicle in the area with better signal, so that the control instruction can be accurately and timely sent to the vehicle, the vehicle can be accurately controlled, and the running safety of the automatic driving vehicle is improved.

It should be noted that the above-described apparatus may also include other embodiments according to the description of the method embodiment. The specific implementation manner may refer to the description of the above corresponding method embodiment, and is not described in detail herein.

Some embodiments of the present disclosure may further provide an autonomous vehicle, which may include the control device of the vehicle autonomous vehicle described above, and implement control of autonomous driving of the vehicle by using the control method of the autonomous vehicle described in the above embodiments.

Embodiments of the present specification may also provide a control apparatus of an autonomous vehicle, including: at least one processor and a memory for storing processor-executable instructions, which when executed by the processor implement the control method of the autonomous vehicle in the above embodiments, such as:

receiving collected data sent by a vehicle;

It should be noted that the above-mentioned processing device, the automatic driving system, the vehicle, or the like may also include other embodiments according to the description of the method embodiment. The specific implementation manner may refer to the description of the above corresponding method embodiment, and is not described in detail herein.

The control device or the processing device of the autonomous vehicle provided by the present specification can also be applied to various data analysis processing systems. The system or apparatus or processing device may comprise the control means of an autonomous vehicle of any of the embodiments described above. The system or apparatus or processing device may be a single server, or may include a server cluster, a system (including a distributed system), software (applications), an actual operation device, a logic gate device, a quantum computer, etc. using one or more of the methods or one or more of the embodiments of the present disclosure, and a terminal device incorporating necessary hardware for implementation. The system for checking for discrepancies may comprise at least one processor and a memory storing computer-executable instructions that, when executed by the processor, implement the steps of the method of any one or more of the embodiments described above.

The method embodiments provided by the embodiments of the present specification can be executed in a mobile terminal, a computer terminal, a server or a similar computing device. Taking the example of the operation on the server, fig. 5 is a hardware structure block diagram of a control server of the vehicle autonomous driving vehicle in one embodiment of the present specification, and the computer terminal may be the control device or system of the autonomous driving vehicle in the above embodiment. As shown in fig. 5, the server 10 may include one or more (only one shown) processors 100 (the processors 100 may include, but are not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 200 for storing data, and a transmission module 300 for communication functions. It will be understood by those skilled in the art that the structure shown in fig. 5 is merely illustrative and is not intended to limit the structure of the electronic device. For example, the server 10 may also include more or fewer components than shown in FIG. 5, and may also include other processing hardware, such as a database or multi-level cache, a GPU, or have a different configuration than shown in FIG. 5, for example.

The memory 200 may be used to store software programs and modules of application software, such as program instructions/modules corresponding to the control method of the autonomous vehicle in the embodiment of the present specification, and the processor 100 executes various functional applications and resource data updates by running the software programs and modules stored in the memory 200. Memory 200 may include high speed random access memory and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, memory 200 may further include memory located remotely from processor 100, which may be connected to a computer terminal through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The transmission module 300 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the computer terminal. In one example, the transmission module 300 includes a Network adapter (NIC) that can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission module 300 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The method or apparatus provided by the present specification and described in the foregoing embodiments may implement service logic through a computer program and record the service logic on a storage medium, where the storage medium may be read and executed by a computer, so as to implement the effect of the solution described in the embodiments of the present specification.

The storage medium may include a physical device for storing information, and typically, the information is digitized and then stored using an electrical, magnetic, or optical media. The storage medium may include: devices that store information using electrical energy, such as various types of memory, e.g., RAM, ROM, etc.; devices that store information using magnetic energy, such as hard disks, floppy disks, tapes, core memories, bubble memories, and usb disks; devices that store information optically, such as CDs or DVDs. Of course, there are other ways of storing media that can be read, such as quantum memory, graphene memory, and so forth.

The control method or apparatus for the autonomous vehicle provided in the embodiments of the present specification may be implemented in a computer by a processor executing corresponding program instructions, for example, implemented in a PC end using a c + + language of a windows operating system, implemented in a linux system, or implemented in an intelligent terminal using android, iOS system programming languages, implemented in processing logic based on a quantum computer, or the like.

It should be noted that descriptions of the apparatus, the computer storage medium, and the system described above according to the related method embodiments may also include other embodiments, and specific implementations may refer to descriptions of corresponding method embodiments, which are not described in detail herein.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to only the partial description of the method embodiment.

The embodiments of the present description are not limited to what must be consistent with industry communications standards, standard computer resource data updating and data storage rules, or what is described in one or more embodiments of the present description. Certain industry standards, or implementations modified slightly from those described using custom modes or examples, may also achieve the same, equivalent, or similar, or other, contemplated implementations of the above-described examples. The embodiments using the modified or transformed data acquisition, storage, judgment, processing and the like can still fall within the scope of the alternative embodiments of the embodiments in this specification.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

Although one or more embodiments of the present description provide method operational steps as described in the embodiments or flowcharts, more or fewer operational steps may be included based on conventional or non-inventive approaches. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When the device or the end product in practice executes, it can execute sequentially or in parallel according to the method shown in the embodiment or the figures (for example, in the environment of parallel processors or multi-thread processing, even in the environment of distributed resource data update). The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. The terms first, second, etc. are used to denote names, but not any particular order.

For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, when implementing one or more of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, etc. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable resource data updating apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable resource data updating apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable resource data update apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable resource data update apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage, graphene storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

One or more embodiments of the present description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more embodiments of the present specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments may be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, and the relevant points can be referred to only part of the description of the method embodiments. In the description of the specification, reference to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.

The above description is merely exemplary of one or more embodiments of the present disclosure and is not intended to limit the scope of one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of the present specification should be included in the scope of the claims.

Claims

1. A control method of an autonomous vehicle, the method comprising:

receiving collected data sent by a vehicle;

2. The method of claim 1, wherein the method further comprises:

3. The method of claim 2, wherein the method further comprises:

4. The method of claim 2, wherein the method further comprises:

5. The method of claim 2, wherein said sending control commands to said vehicle in areas where said network signal strength is greater than a preset strength threshold based on said collected data comprises:

6. The method of claim 5, wherein said sending control instructions to said vehicle to delay transmission of said collected data comprises:

7. The method of claim 1, wherein the method further comprises:

8. The method of claim 2, wherein the method further comprises:

9. The method of claim 1, wherein the acquiring data comprises: before the vehicle starts, receiving the weight of the vehicle obtained by a vehicle-mounted weighing system of the vehicle;

the method further comprises the following steps:

10. A control apparatus of an autonomous vehicle, characterized in that the apparatus comprises:

11. A control system for an autonomous vehicle, the system comprising: data acquisition device, data monitoring device, data transmission device, data receiving arrangement, control center, wherein:

the data transmission device is used for transmitting data;

the data receiving device is used for receiving data;

12. A control apparatus of an autonomous vehicle, characterized by comprising: at least one processor and a memory for storing processor-executable instructions, the processor implementing the method of any one of claims 1-9 when executing the instructions.

13. An autonomous vehicle, comprising: at least one processor and a memory for storing processor-executable instructions, the processor implementing the method of any one of claims 1-9 when executing the instructions.