WO2021164018A1 - Automatic driving control method and apparatus, information processing method and apparatus, and system - Google Patents

Abstract

An automatic driving control method and apparatus, an information processing method and apparatus, and a system. The automatic driving control method comprises: an automatic driving vehicle determines an identifier of the current lane (S1001); the automatic driving vehicle obtains status information of a traffic light associated with the lane according to the identifier of the lane (S1002); the automatic driving vehicle performs driving control according to the status information of the traffic light (S1003). The method can avoid misjudgment of information of the traffic light, thereby ensuring that the automatic driving vehicle can correctly drive according to the traffic rule.

Description

Automatic driving control method, information processing method, device and system Technical field

The embodiments of the present application relate to smart car technology, and in particular to an automatic driving control method, information processing method, device, and system.

Background technique

An autonomous vehicle (also called an unmanned vehicle) is a vehicle that is automatically controlled and operated by an autopilot system. The autopilot vehicle completes the driving through the system as the main and manual auxiliary or is completely driven by the autopilot system. Therefore, , Is an important direction for the future development of vehicles. Autonomous driving systems can use artificial intelligence, visual computing, radar, monitoring devices, and global positioning systems to coordinate and cooperate to control vehicle driving. Autonomous vehicles need to abide by traffic rules when driving. Therefore, the autopilot system first needs to recognize signs and traffic instruction information in the road environment, and then control the vehicle to drive according to the signs and traffic instruction information. Signs can include lane lines, flower beds on the side of the road, curbs, obstacles, etc. The traffic indication information may refer to the information of the traffic signal light. Among them, the information of the traffic signal light is an important basis for controlling the driving of the vehicle. Therefore, how to accurately identify the information of the traffic signal light is a problem to be solved urgently.

In the prior art, self-driving vehicles recognize the information of traffic lights based on purely visual methods. Specifically, the on-board camera installed on the self-driving vehicle collects the image in front of the vehicle, and the self-driving vehicle recognizes the image, recognizes the shape and color of the current traffic light, and controls the vehicle to run normally or stop accordingly.

However, using the method of the prior art, misjudgment of the information of the traffic signal may occur in some scenarios, which may cause the autonomous vehicle to fail to drive correctly in accordance with the traffic rules.

Summary of the invention

The embodiments of the present application provide an automatic driving control method, information processing method, device and system, which are used to solve the problem in the prior art that the automatic driving vehicle cannot drive correctly in accordance with traffic rules due to the possible misjudgment of traffic signal information. problem.

In the first aspect, an embodiment of the present application provides an automatic driving control method, which includes:

The self-driving vehicle determines the sign of the current lane, and obtains the status information of the traffic signal light associated with the lane according to the sign of the lane, and the self-driving vehicle then performs driving control according to the status information of the traffic signal.

In this method, after the self-driving vehicle determines the sign of the current lane, according to the sign of the current lane, the state information of the traffic signal associated with the current lane can be determined, and the driving control is performed according to the state information of the traffic signal. In this process, the autonomous vehicle obtains the state information of the traffic signal light that controls the vehicle on the lane based on the association relationship between the lane and the traffic light. Therefore, even in some special scenarios, for example, the head of the autonomous vehicle deviates from the lane direction. , Traffic signal lights are interfered by traffic lights in other directions, bad weather and other scenarios, autonomous vehicles can still accurately determine the status information of the traffic lights associated with the current lane, so as to avoid misjudgment of the information of the traffic lights, and then Ensure that autonomous vehicles can drive correctly in accordance with traffic regulations.

In a possible design, the self-driving vehicle may determine the identification of the traffic light associated with the lane according to the identification of the above-mentioned lane, and obtain the state information of the traffic light associated with the lane from the network device or the cloud.

In this method, the association relationship between the lane mark and the traffic light mark is used to record the association relationship between the lane and the traffic light. When the autonomous vehicle determines the lane mark, the associated traffic light can be determined according to the lane mark. , And obtain the status of traffic lights based on this. Since the lane mark and the traffic light mark can uniquely identify a lane and a traffic light within a specific range, respectively, using the lane mark to determine the traffic light mark can ensure the accuracy of the determined traffic light.

In a possible design, one way for the autonomous vehicle to obtain the state information of the traffic signal light associated with the lane from a network device or the cloud includes:

The self-driving vehicle sends request information to the network device or the cloud. The request information is used to obtain the state information of the traffic light associated with the lane, and the self-driving vehicle receives the state information of the traffic light associated with the lane from the network device or the cloud.

In this method, the self-driving vehicle obtains the status information of the traffic signal by sending request information to the network device or the cloud, so that the self-driving vehicle can send and receive messages on demand, reducing the number of processed messages.

In a possible design, the identifier of the traffic signal light associated with the lane is a part of the request information.

In a possible design, another way for the autonomous vehicle to obtain the state information of the traffic signal light associated with the lane from a network device or the cloud includes:

The autonomous vehicle receives the state information of at least one traffic signal from the network device or the cloud, and the autonomous vehicle obtains the traffic associated with the lane from the state information of the at least one traffic signal according to the identifier of the traffic signal associated with the lane. The status information of the semaphore.

In this method, the network equipment or the cloud broadcasts the status information of each traffic signal in real time, and the autonomous vehicle matches the status information of the traffic signal according to the identifier of the traffic signal associated with the current lane, thereby reducing the number of autonomous vehicles and network equipment or the cloud. The number of interactions between them improves the processing speed.

In a possible design, the automatic driving vehicle determining the current lane marking includes:

If the distance between the self-driving vehicle and the target intersection is less than a preset threshold, the self-driving vehicle determines the identity of the lane where it is currently located.

In a possible design, the automatic driving vehicle to determine the current lane markings further includes:

If the automatic driving vehicle changes lanes, the automatic driving vehicle determines the lane markings where the automatic driving vehicle is located after the lane change;

The self-driving vehicle uses the identifier of the lane where the vehicle is located after the lane change as the identifier of the lane where it is currently located.

In a possible design, the state information of the traffic signal lamp associated with the lane includes at least one of the following information:

The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.

In this method, the self-driving vehicle can obtain at least one of the above-mentioned state information. Based on the state information, the self-driving vehicle can start to control the automatic vehicle deceleration before reaching the intersection, so that the automatic driving control is consistent with the actual road conditions. More matching.

In a possible design, the driving control of the autonomous vehicle according to the state information of the traffic signal light includes:

The self-driving vehicle determines the driving action of the self-driving vehicle according to at least one of the following information:

The current time, the distance between the autonomous driving vehicle and the intersection, the current driving speed of the autonomous vehicle, the time when the traffic signal status information is issued, the current lighting color of the traffic signal, and the forecast of the traffic signal lighting time information;

The driving action includes: stopping, going straight, turning left, turning right or turning around.

In a possible design, the lane markings include at least one of the following:

The mark of the lane line of the lane, the mark of the lane stop line of the lane, the mark of the lane center line of the lane, and the mark of the lane node of the lane.

In the second aspect, an embodiment of the present application provides an information processing method, which includes:

Obtain the status information of at least one traffic signal, and send the status information of the traffic signal to the self-driving vehicle.

In this method, by acquiring the status information of the traffic signal and sending the status information to the autonomous vehicle, the autonomous vehicle can obtain accurate traffic signal status information, avoiding misjudgments of the traffic signal, and ensuring the autonomous vehicle You can drive correctly in accordance with traffic rules.

In a possible design, the sending the state information of the traffic signal light to the self-driving vehicle includes:

Receive request information sent by the target autonomous vehicle, the request information is used to obtain the status information of the traffic signal associated with the lane where the target autonomous vehicle is currently located, according to the identifier of the traffic signal associated with the lane where the target autonomous vehicle is currently located Acquire the state information of the traffic signal lamp associated with the lane where the target autonomous driving vehicle is currently located; and send the state information of the traffic signal lamp associated with the lane to the target autonomous vehicle.

In this method, the self-driving vehicle obtains the status information of the traffic signal by sending request information to the network device or the cloud, so that the self-driving vehicle can send and receive messages on demand, reducing the number of processed messages.

In a possible design, the identifier of the traffic signal light associated with the lane where the target autonomous driving vehicle is currently located is part of the request information.

In a possible design, the sending the state information of the traffic signal light to the self-driving vehicle includes:

Broadcast the status information of at least one traffic light to at least one autonomous vehicle.

In this method, the status information of each traffic signal is broadcasted in real time, so that the autonomous vehicle can match the status information of the traffic signal according to the identifier of the traffic signal associated with the current lane, thereby reducing the communication between the autonomous vehicle and the network equipment or the cloud. The number of interactions increases the processing speed.

In a possible design, the acquiring state information of at least one traffic signal light includes:

Obtain the status information of at least one traffic light from the traffic light control system.

In a possible design, the state information of the traffic signal light includes at least one of the following information:

The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.

In a third aspect, an embodiment of the present application provides an automatic driving control device, which is characterized in that it includes: a processing unit;

The processing unit is configured to determine the identifier of the current lane, obtain the state information of the traffic signal lamp associated with the lane according to the identifier of the lane, and perform driving control according to the state information of the traffic signal lamp.

In a possible design, the processing unit is specifically configured to:

The identification of the traffic signal light associated with the lane is determined according to the identification of the lane; and the state information of the traffic signal light associated with the lane is obtained from a network device or the cloud.

In a possible design, the device further includes: a transceiver unit.

The transceiver unit is configured to send request information to the network device or the cloud, where the request information is used to obtain the status information of the traffic signal lamp associated with the lane; and, to receive the lane from the network device or the cloud The status information of the associated traffic lights.

In a possible design, the identifier of the traffic signal light associated with the lane is a part of the request information.

In a possible design, the processing unit is specifically configured to:

Receiving the status information of at least one traffic signal light from the network device or the cloud; and, according to the identification of the traffic signal light associated with the lane, obtaining the status information of the traffic signal light associated with the lane from the status information of the at least one traffic light status information.

In a possible design, the processing unit is specifically configured to:

When the distance between the autonomous vehicle and the target intersection is less than the preset threshold, the identification of the current lane is determined.

In a possible design, the processing unit is specifically configured to:

When the automatic driving vehicle changes lanes, the identifier of the lane where the vehicle is located after the lane change is determined, and the identifier of the lane where it is located after the lane change is used as the identifier of the current lane.

In a possible design, the state information of the traffic signal lamp associated with the lane includes at least one of the following information:

The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.

In a possible design, the processing unit is specifically configured to:

Determine the driving action of the autonomous vehicle based on at least one of the following information:

The current time, the distance between the autonomous driving vehicle and the intersection, the current driving speed of the autonomous driving vehicle, the time when the traffic signal status information is issued, the current lighting color of the traffic signal, and the forecast of the traffic signal lighting time information;

The driving action includes: stopping, going straight, turning left, turning right or turning around.

In a possible design, the lane markings include at least one of the following:

The identification of the lane line of the lane, the identification of the lane stop line of the lane, the identification of the lane center line of the lane, and the identification of the lane node of the lane.

In a fourth aspect, an embodiment of the present application provides an information processing device, including: a processing unit and a transceiver unit.

The processing unit is used to obtain state information of at least one traffic signal light;

The transceiver unit is used to send the state information of the traffic signal light to the self-driving vehicle.

In a possible design, the transceiver unit is specifically configured to:

Receive request information sent by a target autonomous driving vehicle, where the request information is used to obtain status information of a traffic signal associated with the lane where the target autonomous driving vehicle is currently located.

The processing unit is further configured to: obtain state information of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located according to the identifier of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located;

The transceiver unit is specifically configured to send the state information of the traffic signal lamp associated with the lane to the target autonomous driving vehicle.

In a possible design, the identifier of the traffic signal light associated with the lane where the target autonomous driving vehicle is currently located is part of the request information.

In a possible design, the transceiver unit is specifically configured to:

Broadcast the status information of at least one traffic light to at least one autonomous vehicle.

In a possible design, the processing unit is specifically configured to:

Obtain the status information of at least one traffic light from the traffic light control system.

In a possible design, the state information of the traffic signal light includes at least one of the following information:

The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.

In a fifth aspect, an embodiment of the present application provides a communication device, including a processor, the processor is connected to a memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, So that the device executes the method described in the first aspect.

In a sixth aspect, an embodiment of the present application provides a communication device, including a processor, the processor is connected to a memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, So that the device executes the method described in the second aspect above.

In a seventh aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium stores a computer program, and when the computer program is executed, the method described in the first aspect is implemented.

In an eighth aspect, an embodiment of the present application provides a computer-readable storage medium that stores a computer program, and when the computer program is executed, the method described in the second aspect is implemented.

In a ninth aspect, an embodiment of the present application provides a chip including a processor and an interface.

The processor is configured to read instructions to execute the automatic driving control method described in the first aspect.

In a tenth aspect, an embodiment of the present application provides a chip including a processor and an interface.

The processor is used to read instructions in the information processing method described in the second aspect.

In an eleventh aspect, an embodiment of the present application provides a computer program product. The computer program product includes computer program code. When the computer program code is executed by a computer, the computer executes the method described in the first aspect. .

In a twelfth aspect, an embodiment of the present application provides a computer program product, the computer program product includes computer program code, when the computer program code is executed by a computer, the computer executes the method described in the second aspect above .

In a thirteenth aspect, an embodiment of the present application provides a communication system, including the communication device described in the fifth aspect, the communication device described in the sixth aspect, and a traffic signal light control system.

Description of the drawings

Fig. 1 is a schematic diagram of an automatic driving vehicle recognizing a traffic signal light in the prior art;

Figure 2 is an example diagram of misjudgment caused by the deviation of the front of the vehicle from the lane direction;

Figure 3 is an example diagram of traffic signal lights being interfered by traffic lights in other directions;

Figure 4 is an example diagram of traffic signal lights of different colors in the same direction;

Fig. 5a is an exemplary system architecture diagram of an automatic driving control method provided by an embodiment of the application;

FIG. 5b is another exemplary system architecture diagram of the automatic driving control method provided by the embodiment of the application; FIG.

Figure 6 is an example diagram of lane lines;

Figure 7 is an example diagram of the centerline of the lane;

Figure 8 is an example diagram of a lane stop line;

Figure 9 is an example diagram of lane nodes;

FIG. 10 is a schematic flowchart of an automatic driving control method provided by an embodiment of this application;

FIG. 11 is an interactive flowchart of an automatic driving control method provided by an embodiment of this application;

Figure 12a is a schematic diagram of an interaction scene between an autonomous driving vehicle and a network device;

Figure 12b is a schematic diagram of an interaction scene between an autonomous vehicle and the cloud;

FIG. 13 is another interactive flowchart of the automatic driving control method provided by the embodiment of the application;

Figure 14a is a schematic diagram of an interaction scene between an autonomous vehicle and a network device;

Figure 14b is a schematic diagram of an interaction scene between an autonomous vehicle and the cloud;

15 is a block diagram of an automatic driving control device provided by an embodiment of the application;

FIG. 16 is a module structure diagram of an information processing device provided by an embodiment of this application;

FIG. 17 is a schematic structural diagram of a communication device provided by an embodiment of this application.

Detailed ways

Fig. 1 is a schematic diagram of an automatic driving vehicle in the prior art recognizing traffic signal lights. As shown in Fig. 1, the automatic driving vehicle in the prior art recognizes traffic signal information based on a purely visual manner. Specifically, the traffic signal light information is sensed by the camera installed on the vehicle. In this way, misjudgment of traffic signal information may occur in some scenarios, which may cause the autonomous vehicle to fail to drive correctly in accordance with traffic rules. The following lists some scenarios where misjudgment of traffic signal information may occur.

1. Misjudgment may occur in rainy, hazy and other weather.

The pure visual method is easily affected by weather conditions. For example, on a rainy or hazy day, the traffic signal lights in the image collected by the camera are not clear enough, which may lead to misjudgment.

2. Misjudgment may occur under certain light.

Pure visual methods are susceptible to the influence of light. For example, at dusk, the light spots reflect the light of the setting sun, causing the light spots in the images collected by the camera to be orange-red, which leads to misjudgment.

3. When the self-driving vehicle is involved and obscured, the image of the traffic light cannot be collected.

4. When the autonomous vehicle is in the left-turn waiting area, the image of the left-turn traffic light cannot be collected.

5. Graphic recognition failure may occur when there are traffic lights of different colors in the same direction.

Figure 2 is an example diagram of traffic lights of different colors in the same direction. As shown in Figure 2, there are two traffic lights in front of the autonomous vehicle. One traffic signal is used to control the vehicle, and the other traffic signal is used to control pedestrians. Pedestrian traffic lights are provided with human-shaped signs. In some cases, the self-driving vehicle may not be able to recognize the human-shaped sign through graphic recognition, and the self-driving vehicle cannot distinguish which of the two traffic lights is used to control the vehicle, which may lead to misjudgment.

6. The traffic lights are interfered by traffic lights in other directions.

Figure 3 is an example diagram of traffic lights being interfered by traffic lights in other directions. As shown in Figure 3, in addition to the traffic lights that control the current lane, the images captured by the camera also include traffic lights in the other direction. The color of the traffic lights in the direction is inconsistent, which may cause the autonomous vehicle to be unable to accurately determine the color of the traffic lights in the current lane.

7. The front of the autonomous vehicle deviates from the lane direction.

Because some unexpected factors may cause the front of the autonomous vehicle to deviate from the lane direction, in this scenario, the traffic signal that controls the lane is not within the ideal recognition range of the camera used to collect traffic signal images in the autonomous vehicle, which may lead to misunderstandings. Misjudgment of traffic signal information. Exemplarily, Fig. 4 is an example diagram of misjudgment caused by the deviation of the vehicle head from the lane direction. As shown in Fig. 4, the autonomous vehicle is currently in a left-turning lane and the vehicle head is not facing the direction of the lane. Therefore, in the image collected by the camera, The traffic signal used to control the left turn is located at the edge of the image, which may lead to misjudgment of the traffic signal.

Taking into account the problem that the identification of traffic signal information based on purely visual methods in the prior art may lead to misjudgment of the information of the traffic signal, the embodiment of the present application associates the lane with the traffic signal that controls the lane, and the association with the lane can be directly obtained. The information of the traffic signal light and the driving control are carried out, so as to avoid the problem of misjudgment of the information of the traffic signal light.

Fig. 5a is an exemplary system architecture diagram of an automatic driving control method provided by an embodiment of the application. As shown in Fig. 5, the embodiment of the application relates to a traffic signal light control system, a network device, and an automatic driving vehicle. Among them, the traffic signal light control system can send the status information of the traffic signal light to the network device in real time, and the network device provides the self-driving vehicle. In the embodiments of the present application, the network device may refer to a vehicle to everything (V2X) device deployed on or near the road. Exemplarily, the network device may be a roadside unit (RSU), and the RSU may communicate with an autonomous vehicle, or may communicate with other roadside units.

FIG. 5b is another exemplary system architecture diagram of the automatic driving control method provided by the embodiment of the application. As shown in FIG. 5, the embodiment of the application relates to a traffic signal light control system, the cloud, and an automatic driving vehicle. Among them, the traffic signal light control system can send the status information of the traffic signal light to the cloud in real time, and the cloud provides the self-driving vehicle. In the embodiment of the present application, the cloud can process, store, and deliver data, and the data can include traffic signal information and map data. The cloud can be a map cloud, and the state information of traffic lights and regional map information are stored in the map cloud. The cloud can also be cloud resources or cloud maps.

Before describing the technical solutions of the embodiments of the present application, the technical terms involved in the embodiments of the present application are first explained. It is worth noting that the lane refers to the part on the roadway for a single column of vehicles to travel. The following terms are relative to a certain lane and can be used to identify a lane.

1. Lane line

The lane line refers to the lane dividing line on the road. Exemplarily, Fig. 6 is an example diagram of lane lines. As shown in Fig. 6, three lane lines are marked on a certain road, namely, lane line 1, lane line 2, and lane line 3. The three lane lines can be divided into two lanes, lane 1 and lane 2, respectively. In the embodiment of the present application, one lane line can be used to identify one lane. Exemplarily, lane line 2 may be used to identify lane 1, and lane line 3 may be used to identify lane 2.

2. Lane line center line

The lane line centerline refers to the virtual line in the autonomous driving map, and the lane line centerline may not exist in the actual road. The centerline of the lane line defines the trajectory of the vehicle between the sidelines of the lane. Figure 7 is an example diagram of the centerline of the lane. As shown in Figure 7, a road includes two lanes, lane 1 and lane 2, which pass through lane line 1, lane line 2, and lane line 3. segmentation. Among them, lane 1 includes lane centerline 1, and lane 2 includes lane centerline 2. In the embodiment of the present application, the lane center line may be used to identify the lane. Exemplarily, the lane centerline 1 may be used to identify the lane 1, and the lane centerline 2 may be used to identify the lane 2.

3. Lane line stop line

The lane stop line refers to the marking line at the end of a section of lane. Fig. 8 is an example diagram of a lane stop line. As shown in Fig. 8, a road ends at a certain intersection. The road includes three lanes, lane 1, lane 2, and lane 3. At the road cutoff, there are three lane stop lines 1, lane stop lines 2, and lane stop lines 3, respectively. Lane stop line 1 is the stop line of lane 1 and can be used to mark lane 1. Lane stop line 2 is the stop line of lane 2, which can be used to mark lane 2. Lane stop line 3 is the stop line of lane 3 and can be used to mark lane 3.

4. Lane node

The lane node may refer to the node of the lane line and/or the center line of the lane, and is a virtual node in the autonomous driving map. The lane node may not exist in the actual road. In the autonomous driving map, when the lane line and/or the center line of the lane change, it needs to be interrupted, and the location of the interruption can be marked by the lane node. Fig. 9 is an example diagram of lane nodes. As shown in Fig. 9, three lane lines are marked on a certain road, namely, lane line 1, lane line 2, and lane line 3. The three lane lines can be divided into two lanes, lane 1 and lane 2, respectively. Among them, lane line 1 changes at lane node 1, so lane node 1 is set here, lane line 2 changes at lane node 2, so lane node 2 is set here, and lane line 3 is at lane node 3. Change occurs, so lane node 3 is set here. Therefore, lane node 1 is associated with lane line 1, lane node 2 is associated with lane line 2, and lane node 3 is associated with lane line 3.

Taking lane line 2 as an example, since lane line 2 is associated with lane node 2 and lane line 2 can identify the lane, when associating traffic lights with lane nodes, the traffic lights can be associated with lanes. Therefore, the embodiment of the present application may be referred to as identifying the lane by the lane node.

5. Autonomous driving map

In the embodiments of this application, the autonomous driving map may be a high-precision map. In addition to storing traditional road information, the autonomous driving map also stores the nodes of roads, lanes, lane lines, lane center lines, lane stop lines, and lane lines. Information so that autonomous vehicles can achieve more precise positioning. The autonomous driving vehicle may pre-store the autonomous driving map.

For ease of description, in the embodiments of the present application, the autonomous driving map is referred to as a map for short below.

FIG. 10 is a schematic flowchart of an automatic driving control method provided by an embodiment of this application. As shown in FIG. 10, the method includes:

S1001. The self-driving vehicle determines the identification of the current lane.

Optionally, the identification of the lane where the autonomous vehicle is currently located may refer to the identification of the lane where the autonomous vehicle is currently located on the map.

During the operation of the self-driving vehicle, the lane on the map can be obtained in real time, and then the identification of the lane can be determined. Exemplarily, the self-driving vehicle first obtains the current probabilistic position according to the built-in global positioning system (GPS) module, enters the probabilistic position into the map, and uses the map for high-precision positioning, thereby obtaining the current lane , And determine the sign of the current lane.

As mentioned above, lane lines, lane center lines, lane stop lines, and lane nodes can all be used to identify lanes. Therefore, in the embodiment of the present application, the current lane identifier may refer to the lane line identifier of the current lane At least one of the identification of the lane center line of the current lane, the identification of the lane stop line of the current lane, and the identification of the lane node of the current lane.

Optionally, the above-mentioned lane line identification, lane center line identification, lane stop line identification, and lane node identification can be numbers, names, etc., so that the identified lane line can be distinguished from other lanes within a specific range The lane center line can be distinguished from other lane center lines in a specific range, the lane stop line can be distinguished from other lane stop lines in a specific range, and the lane node can be distinguished from other lane nodes in a specific range.

Optionally, the above-mentioned specific range may refer to the range of the entire map, or a part of the range in the map. Exemplarily, if the scope of the map is a province, the above-mentioned specific scope can refer to that province, or it can refer to a certain city belonging to the province.

In one example, assuming that lane lines are used to identify the lane, the autonomous vehicle can obtain the current lane on the map in real time, and obtain the lane line identification of the current lane on the map, and then determine that the current lane is the lane line. Of the logo. Taking the lane information illustrated in Figure 6 as an example, suppose that the autonomous vehicle obtains that the current lane on the map is lane 1. At the same time, in the map, the lane line corresponding to lane 1 is lane line 2, then the autonomous vehicle Determine that the current lane marking is the marking of lane line 2. Exemplarily, if the number of the lane line 2 is 2, the autonomous driving vehicle determines that the current lane identifier is 2.

In another example, assuming that the lane centerline is used to identify the lane, the autonomous vehicle can obtain the current lane on the map in real time, and obtain the lane centerline identification of the current lane on the map, and then determine that the current lane identification is The mark of the centerline of the lane. Taking the lane information illustrated in Figure 7 as an example, suppose that the autonomous vehicle has acquired the current lane on the map as lane 1. At the same time, in the map, the lane center line corresponding to lane 1 is lane center line 1, then automatically The driving vehicle determines that the current lane marking is the marking of the lane centerline 1.

In another example, assuming that the lane is marked with a lane stop line, the autonomous vehicle can obtain the current lane on the map in real time, and obtain the lane stop line identification of the current lane on the map, and then determine that the current lane identification is The mark of the stop line in this lane. Taking the lane information illustrated in Figure 8 as an example, suppose that the autonomous vehicle acquires that the current lane on the map is lane 1. At the same time, in the map, the lane stop line corresponding to lane 1 is lane stop line 1, then automatically The driving vehicle determines that the sign of the current lane is the sign of the lane stop line 1.

In another example, assuming that the lane node is used to identify the lane, the autonomous vehicle can obtain the current lane on the map in real time, and obtain the identification of the node of the current lane in the map, and then determine that the identification of the current lane is the lane in the map The identifier of the corresponding lane node.

It should be understood that in specific implementation, the autonomous vehicle may use one of the above-mentioned lane line, lane center line, lane stop line, and lane node to identify the lane, or it may use different lanes in different time periods or under different circumstances. Information to identify the lane. Exemplarily, the autonomous vehicle may use the lane line to identify the lane by default. In some cases, the autonomous vehicle may use the center line of the lane to identify the lane when it cannot accurately obtain the identification of the lane line.

Optionally, during the operation of the autonomous vehicle, the identification of the current lane can be determined when certain or certain conditions are met, and then the following steps S1002-S1003 are executed to complete the driving control. Exemplarily, the self-driving vehicle determines whether the distance between the self-driving vehicle and the target intersection is less than a preset threshold based on the current position on the self-driving map. Wherein, the target intersection may refer to an intersection on the map that is closest to the current position of the autonomous vehicle in the autonomous driving map. The intersection may be, for example, an intersection, a T-junction, and other intersections where traffic lights may be set. Alternatively, the intersection may also be a location on a road with traffic lights connected to an exit of a certain building. Exemplarily, a certain position on a certain road is connected to an exit of a certain school, and in order to ensure the safety of students, a traffic signal light is set at that position on the road. Therefore, the location where the traffic signal light is installed also belongs to the intersection. If it is determined that the distance between the self-driving vehicle and the intersection is less than the preset threshold, it indicates that the self-driving vehicle is about to arrive at the intersection. Therefore, the self-driving vehicle can determine the identification of the current lane and execute the following steps S1002-S1003 to complete the driving control.

The preset threshold may be preset by an autonomous vehicle, and for example, the threshold may be 500m, 200m, or 50m. The preset threshold value can be dynamically changed by the owner of the self-driving vehicle, for example, it can be set freely according to the traffic jam and the characteristics of the vehicle driving path.

After the self-driving vehicle has determined the sign of the current lane through the above process, it may change lanes before reaching the intersection. If the self-driving vehicle changes lanes, the self-driving vehicle can determine the sign of the lane after the lane change, and The sign of the lane where you are after changing lanes is used as the sign of the current lane.

Exemplarily, the self-driving vehicle obtains the lane in the map after the lane change, and determines that the lane line corresponding to the lane is the lane mark after the lane change, and uses the lane mark after the lane change as the new current location The identification of the lane. In the subsequent steps, the self-driving vehicle obtains the status information of the traffic lights and performs driving control based on the lane markings.

It should be understood that the operation of the self-driving vehicle described in the embodiments of the present application refers to the operation of the system of the self-driving vehicle. After the system is operated, the behavior of the vehicle is controlled, and the behavior may include driving or stopping.

S1002. The self-driving vehicle obtains state information of the traffic signal light associated with the lane according to the identification of the lane.

In the embodiment of the present application, a lane and a traffic signal light may be associated in advance, wherein a certain traffic signal light associated with a certain lane is used to control the behavior of an autonomous vehicle driving in the lane. Exemplarily, if a certain lane is a left-turn lane, the traffic signal light associated with the left-turn lane is a traffic signal light that controls the vehicle to be turned left.

Optionally, the association relationship between the lane and the traffic light can be pre-stored in the autonomous vehicle, and/or, pre-stored in the network device or cloud that provides status information of the traffic light.

The specific association between lanes and traffic signals will be described in detail in the following embodiments.

After the self-driving vehicle determines the sign of the current lane, it can obtain the state information of the traffic signal associated with the current lane based on the association relationship between the lane and the traffic light.

S1003. The autonomous vehicle performs driving control according to the state information of the above-mentioned traffic signal light.

Optionally, the above-mentioned status information of the traffic signal may indicate the lighting information of the traffic signal at the current moment and the change of the traffic signal in a certain period of time in the future, etc. The autonomous vehicle is based on the traffic signal status information combined with the speed of the autonomous vehicle And other information, you can carry out driving control. Exemplarily, the autonomous driving vehicle is controlled to pass through the intersection at a speed before reaching the intersection, or the autonomous driving vehicle is controlled to stop within the lane stop line.

The specific method for the autonomous driving vehicle to perform driving control based on the state information of the traffic signal will be described in detail in the following embodiments.

In this embodiment, after the self-driving vehicle determines the sign of the current lane, according to the sign of the current lane, the status information of the traffic signal associated with the current lane can be determined, and the driving control is performed according to the status information of the traffic signal. In this process, the autonomous vehicle obtains the state information of the traffic signal light that controls the vehicle on the lane based on the association relationship between the lane and the traffic light. Therefore, even in some special scenarios, for example, the head of the autonomous vehicle deviates from the lane direction. , Traffic signal lights are interfered by traffic lights in other directions, bad weather and other scenarios, autonomous vehicles can still accurately determine the status information of the traffic lights associated with the current lane, so as to avoid misjudgment of the information of the traffic lights, and then Ensure that autonomous vehicles can drive correctly in accordance with traffic regulations.

When associating the lanes with the traffic lights in advance, as an optional way, the lane markings can be associated with the traffic lights markings in advance. As mentioned above, the lane markings may refer to the markings of the lane lines, the markings of the center lines of the lanes, the markings of the lane stop lines, or the markings of the lane nodes. Therefore, in the specific implementation process, you can associate the lane mark with the traffic light mark in advance, or associate the lane center line mark with the traffic light mark, or link the lane stop line mark with the traffic light mark. Associate the identification of the lane node with the identification of the traffic light.

It should be understood that when the lane identifier uniquely identifies a lane within a specific range, the associated traffic signal identifier correspondingly uniquely identifies a traffic signal within the specific range or a range larger than the specific range.

The following Table 1 is an example of associating the markings of lane lines with the markings of traffic lights.

Table 1

Field Name	type	Ranges	describe
Lane_ID	int	To	Lane number
TrafficLight_ID	int	To	Number of traffic lights
…	…	…	…

The above table 1 can be a table for recording lane line elements. In this table, the Lane_ID field can be the number of the lane line, which is used to uniquely identify a lane line in the aforementioned specific range. The table can also record other lane lines. The elements of the lane line, for example, the type of the lane line is a white solid line. In addition, the above-mentioned TrafficLight_ID field can be recorded in the table, and the TrafficLight_ID field can be the number of a traffic light, and the number is used to uniquely identify a traffic light in a certain range.

Using the associations recorded in Table 1 above, after the autonomous vehicle has determined the lane markings, it can query the traffic signal lights associated with the lanes from Table 1.

The following Table 2 is an example of associating the mark of the center line of the lane with the mark of the traffic light.

Table 1

Field Name	type	Ranges	describe
MidLane_ID	int	To	Number of lane centerline
TrafficLight_ID	int	To	Number of traffic lights
…	…	…	…

The above table 2 can be a table for recording the centerline elements of the lane. In the table, the MidLane_ID field can be the number of the centerline of the lane, which is used to uniquely identify a centerline of the lane in the aforementioned specific range. The table can also Record other elements of the centerline of the lane. In addition, the above-mentioned TrafficLight_ID field can be recorded in the table, and the TrafficLight_ID field can be the number of a traffic light, and the number is used to uniquely identify a traffic light in a certain range.

Using the associations recorded in Table 2 above, after the autonomous vehicle has determined the lane markings, it can query the traffic light markings associated with the lanes from Table 1.

The following Table 3 is an example of associating the signs of the lane stop line with the signs of the traffic lights.

table 3

Field Name	type	Ranges	describe
StopLine_ID	int	To	Lane stop line number
TrafficLight_ID	int	To	Number of traffic lights
…	…	…	…

The above table 3 can be a table for recording lane stop line elements. In this table, the StopLine_ID field can be the number of the lane stop line, which is used to uniquely identify a lane stop line within the aforementioned specific range. The table can also Record other elements of the stop line of the lane. In addition, the above-mentioned TrafficLight_ID field can be recorded in the table. The TrafficLight_ID field can be the number of a traffic light, and the number is used to uniquely identify a traffic light in a certain range.

Using the associations recorded in Table 3 above, after the autonomous vehicle has determined the lane markings, it can query the traffic signal lights associated with the lanes from Table 1.

The following Table 4 is an example of associating the identification of the lane node with the identification of the traffic light.

Table 4

Field Name	type	Ranges	describe
Node_ID	int	To	The number of the lane node
TrafficLight_ID	int	To	Number of traffic lights
…	…	…	…

The above table 4 can be a table for recording lane node elements. In this table, the Node_ID field can be the number of the lane node, which is used to uniquely identify a lane node in the aforementioned specific range. The table can also record other lane nodes. Elements of lane nodes. In addition, the above-mentioned TrafficLight_ID field can be recorded in the table, and the TrafficLight_ID field can be the number of a traffic light, and the number is used to uniquely identify a traffic light in a certain range.

Using the associations recorded in Table 4 above, after the autonomous vehicle has determined the lane markings, it can query the traffic signal lights associated with the lanes from Table 1.

Based on the foregoing pre-association of the lane markings with the traffic signal lights markings, an optional implementation manner of the foregoing step S1002 includes:

The self-driving vehicle determines the identification of the traffic light associated with the lane according to the identification of the determined lane, and then obtains the state of the traffic light associated with the lane from the network device or the cloud.

The self-driving vehicle can save the above-mentioned association relationship.

Exemplarily, assuming that lane lines are used to identify the lane, the autonomous vehicle may record the information in Table 1 above in advance. After the self-driving vehicle has determined the identification of the current lane, that is, the identification of the lane line, it can query the identification of the traffic light associated with the identification of the lane line from Table 1, and then based on the identification of the traffic light, from the network equipment or The cloud obtains the identification of the traffic light.

In this embodiment, the association relationship between the lane mark and the traffic light mark is used to record the association relationship between the lane and the traffic light. After the autonomous vehicle determines the lane mark, the associated traffic light can be determined according to the lane mark. , And obtain the status of traffic lights based on this. Since the lane mark and the traffic light mark can uniquely identify a lane and a traffic light within a specific range, respectively, using the lane mark to determine the traffic light mark can ensure the accuracy of the determined traffic light.

The following describes a method for an autonomous vehicle to obtain the status information of the traffic signal light associated with the lane from the network device or the cloud after the identification of the traffic signal light associated with the lane is determined.

Optionally, the self-driving vehicle can use any of the following two optional methods to obtain traffic signal status information from a network device or the cloud.

In the first alternative, the self-driving vehicle can actively request the network device or the cloud to provide the self-driving vehicle with the status information of the traffic signal associated with the current lane. In this way, the self-driving vehicle is determining the traffic corresponding to the current lane. After the semaphore is identified, the request information is sent to the network device or the cloud.

In the second alternative, the network device or the cloud broadcasts the status information of each traffic signal, and the autonomous vehicle obtains the status information of the traffic signal associated with the current lane from the broadcast status information.

On the network device or the cloud side, the status information of at least one traffic signal can be acquired, and the status information of the traffic signal can be sent to the autonomous vehicle. Among them, the network device or the cloud can use the corresponding method of the above two optional methods to send the status information of the traffic signal to the autonomous vehicle.

The above two methods are described below respectively.

FIG. 11 is an interactive flow chart of the automatic driving control method provided by an embodiment of the application. As shown in FIG. 11, the automatic driving control interaction flow based on the above-mentioned first optional method includes:

S1101. The self-driving vehicle determines the identification of the current lane.

The specific execution process of this step is the same as the above step S1001, and you can refer to the above step S1001, which will not be repeated here.

S1102. The self-driving vehicle determines the identifier of the traffic signal light associated with the lane according to the identifier of the current lane.

For the specific execution process of this step, reference may be made to the description of the foregoing embodiment, which will not be repeated here.

S1103. The self-driving vehicle sends request information to the network device or the cloud, where the request information is used to obtain the status information of the traffic signal lamp associated with the current lane.

In an optional manner, the self-driving vehicle may carry the identifier of the traffic signal light associated with the lane in the above request information and send it to the network device or the cloud, that is, the identifier of the traffic signal light associated with the lane is part of the above request information. Correspondingly, the network device or the cloud can read the identification of the traffic light from the request information.

By carrying the identifier of the traffic light in the request information, the number of interactive signaling can be reduced, transmission resources can be saved, and transmission efficiency can be improved.

In another optional manner, the above request information may not carry the traffic signal identifier associated with the lane. After the network device or the cloud receives the request information, it instructs the autonomous vehicle to provide the traffic signal identifier, and then obtains the traffic signal identifier. Logo.

It is worth noting that the self-driving vehicle in this optional manner may be referred to as a target driving vehicle, and the target driving vehicle sends request information to the network device or the cloud.

S1104. The network device or the cloud obtains the status information of the traffic signal light according to the identifier of the traffic signal light associated with the lane where the autonomous vehicle is currently located.

As mentioned above, the traffic signal control system can provide the network equipment or the cloud with the status information of each traffic signal in real time. Therefore, the network equipment or the cloud can obtain the status information of the traffic signal according to the identification of the traffic signal.

S1105: The network device or the cloud sends the state information of the traffic signal lamp associated with the current lane to the autonomous vehicle.

Correspondingly, the self-driving vehicle receives the state information of the traffic signal light associated with the current lane from the network device or the cloud.

Figure 12a is a schematic diagram of the interaction scene between an autonomous vehicle and a network device. As shown in Figure 12a, the autonomous vehicle sends request information to the network device, and the network device obtains traffic signal status information from the traffic signal control system and sends it to the autonomous vehicle . Figure 12b is a schematic diagram of the interaction scene between the autonomous vehicle and the cloud. As shown in Figure 12b, the autonomous vehicle sends request information to the cloud, and the cloud obtains the status information of the traffic light from the traffic light control system and sends it to the self-driving vehicle.

S1106. The self-driving vehicle performs driving control according to the state information of the traffic signal light associated with the current lane.

In this embodiment, the self-driving vehicle obtains the status information of the traffic signal by sending request information to the network device or the cloud, so that the self-driving vehicle can send and receive messages on demand, reducing the number of processed messages.

FIG. 13 is another interaction flow chart of the automatic driving control method provided by the embodiment of the application. As shown in FIG. 13, the automatic driving control interaction flow based on the above-mentioned second optional method includes:

S1301. The self-driving vehicle determines the identification of the current lane.

The specific execution process of this step is the same as the above step S1001, and you can refer to the above step S1001, which will not be repeated here.

S1302. The self-driving vehicle determines the identifier of the traffic signal light associated with the lane according to the identifier of the current lane.

For the specific execution process of this step, reference may be made to the description of the foregoing embodiment, which will not be repeated here.

S1303: The network device or the cloud broadcasts the state information of at least one traffic signal light.

It is worth noting that this step is an operation actively performed by the network device or the cloud side, and this operation is independent of the operation of the self-driving vehicle. Therefore, the order of execution of the steps and the aforementioned steps S1301-S1302 is in no particular order.

Optionally, the network device or the cloud can broadcast the status information of each traffic signal to all autonomous vehicles in the area where each traffic signal is located in real time. Exemplarily, if 4 traffic lights are installed at a certain intersection, the network device or the cloud can broadcast the status information of the 4 traffic lights to all autonomous vehicles in the area where the intersection is located in real time.

Correspondingly, when the autonomous vehicle involved in the foregoing steps travels to the area, it can receive the state information of at least one traffic signal from the network device or the cloud.

S1304. The self-driving vehicle obtains the status information of the traffic signal associated with the current lane from the status information of the at least one traffic signal according to the identifier of the associated traffic signal of the current lane.

When the network device or cloud broadcasts the status information of each traffic signal light, it can broadcast the traffic signal identification and the traffic signal status information at the same time. The autonomous driving vehicle can compare the identification in the broadcast information with the traffic signal status information obtained in step S1302. The identification is matched, and the status information of the traffic signal lamp associated with the current lane can be obtained.

Figure 14a is a schematic diagram of the interactive scene between the autonomous vehicle and the network device. As shown in Figure 14a, the network device broadcasts the status information of the traffic lights installed at the intersection to the autonomous vehicles in the area where the intersection is located in real time. By matching the identifier of the traffic signal light, the status information of the traffic signal light associated with the current lane is obtained. Figure 14b is a schematic diagram of the interactive scene between autonomous vehicles and the cloud. As shown in Figure 14b, the cloud broadcasts the status information of the traffic lights installed at the intersection to the autonomous vehicles in the area where the intersection is located in real time, and the autonomous vehicles pass the matching The identification of the traffic signal light obtains the status information of the traffic signal light associated with the current lane.

S1305. The autonomous vehicle performs driving control according to the state information of the traffic signal light associated with the current lane.

In this embodiment, the network equipment or the cloud broadcasts the status information of each traffic signal in real time, and the autonomous vehicle matches the status information of the traffic signal according to the identifier of the traffic signal associated with the current lane, thereby reducing the number of autonomous vehicles and network equipment or the cloud. The number of interactions between them improves the processing speed.

The following describes the specific process of driving control according to the state information of the traffic light in the above step S1003, step S1106, and step S1305.

As mentioned above, the status information of the traffic signal indicates the lighting information of the traffic signal at the current moment and the change of the traffic signal in a certain period of time in the future.

As an optional implementation manner, the state information of the traffic signal light may include at least one of the following:

The sign of the traffic signal, the type of the traffic signal, the time when the status information of the traffic signal is issued, the current light color, and the forecast information of the light time, etc.

Among them, the time when the state information of the traffic signal lamp is issued may refer to the time when the state information is issued by the network device or the cloud. The current lighting colors can include: green, red, yellow, and off. The light-on time forecast information may include red light time forecast information, yellow light time forecast information, and green light time forecast information. Exemplarily, the red light time forecast information may refer to the time when the next red light is on.

The following Table 5 is an example of the format of the status information of traffic lights.

table 5

Based on the above-mentioned state information of the traffic signal, the autonomous vehicle can determine the driving action of the autonomous vehicle according to at least one of the following information:

The current time, the distance between the self-driving vehicle and the intersection, the current speed of the self-driving vehicle, the time when the traffic signal status information is issued, the current color of the traffic signal, and the forecast information about the time when the traffic signal is on.

Among them, the aforementioned driving actions include: stop, go straight, turn left, turn right, or turn around.

The following is a list of processing methods when an autonomous vehicle performs driving control based on at least one of the above-mentioned information.

In the first method, the self-driving vehicle can predict the light color of the self-driving vehicle when it arrives at the intersection in advance based on the current time, the distance between the self-driving vehicle and the intersection, the current speed of the self-driving vehicle, and the forecast information of the time when the traffic signal lights are on. The driving action of the vehicle is controlled according to the predicted color. When the prediction result is a green light, the prediction result needs to be dynamically updated according to the speed change of the autonomous vehicle. When the prediction result is a yellow light or a red light, the vehicle will decelerate.

In one example, the autonomous vehicle can determine the time when the autonomous vehicle arrives at the intersection based on the current time, the distance between the autonomous vehicle and the intersection, and the current driving speed of the autonomous vehicle. At the same time, the autonomous vehicle forecasts information based on the time when the traffic signal lights are on. It is determined that the green light is on when the vehicle arrives at the intersection, and the autonomous vehicle continues to monitor the vehicle speed. When the vehicle speed changes, the above method is used again to predict the color of the light when it arrives at the intersection, and the light will be lighted according to the latest prediction when it actually arrives at the intersection. The color controls the autonomous vehicle to continue driving in a certain direction or stop.

In another example, the self-driving vehicle can determine the time when the self-driving vehicle arrives at the intersection based on the current time, the distance between the self-driving vehicle and the intersection, and the current driving speed of the self-driving vehicle. At the same time, the self-driving vehicle predicts the time when the traffic signal lights are on. The information determines that the red light is on when the vehicle arrives at the intersection, and the autonomous vehicle can control the autonomous vehicle to decelerate.

In the second method, when an autonomous vehicle arrives at an intersection, it can determine the current light color of the traffic signal light and control the driving action of the vehicle based on the current time, the time when the traffic signal status information is issued, and the current light color.

Exemplarily, when an autonomous vehicle arrives at an intersection, according to the current time and the time when the status information of the traffic signal is issued, it can be known whether the light color at the current time is the current light color in the issued status information. The color of the light is controlled since the vehicle continues to drive in a certain direction or stops. For example, the current time is 2:01, and the traffic signal status information is issued at 2:05 seconds, that is, 55 seconds have elapsed since the time the status information was issued. The lighting time is 90 seconds, which means that the current time has not passed the time of the traffic signal color conversion. Therefore, the actual lighting color at the current time is the current lighting color in the status information. Therefore, the self-driving vehicle can follow the current status in the status information. The color of the lights controls the autonomous vehicle to continue driving in a certain direction or stop.

In the third method, the self-driving vehicle starts when the distance from the intersection is the preset distance, and continuously obtains the current lighting color according to the preset cycle, and controls the automatic control based on the current lighting color in the last cycle before reaching the intersection. The driving action of driving a vehicle.

Exemplarily, the current lighting color of the last cycle before the autonomous vehicle arrives at the intersection is red, and the autonomous vehicle stops when it reaches the intersection.

Exemplarily, the aforementioned period may be a period of distance, for example, every 50 meters is a period, or it may also be a period of time, for example, every 0.5 second is a period.

In the above-mentioned embodiment, at least one of the above-mentioned state information that the autonomous driving vehicle can obtain, based on the state information, the autonomous driving vehicle can start to control the automatic vehicle deceleration before reaching the intersection, so that the automatic driving control is in line with the actual The road conditions are more matched.

FIG. 15 is a block diagram of an automatic driving control device provided by an embodiment of the application. The device may be the aforementioned automatic driving vehicle, or it may be capable of enabling the automatic driving vehicle to realize the automatic driving in the method provided by the embodiment of the application. The device of the vehicle function, for example, the device may be a device or a chip system in an autonomous driving vehicle. As shown in FIG. 15, the device includes: a processing unit 1501.

The processing unit 1501 is configured to determine the identifier of the current lane, obtain state information of the traffic signal lamp associated with the lane according to the lane identifier, and perform driving control according to the state information of the traffic signal lamp.

As an optional implementation manner, the processing unit 1501 is specifically configured to:

The identification of the traffic signal light associated with the lane is determined according to the identification of the lane; and the state information of the traffic signal light associated with the lane is obtained from a network device or the cloud.

Continuing to refer to FIG. 15, as an optional implementation manner, the foregoing apparatus further includes: a transceiver unit 1502.

The transceiver unit 1502 is configured to send request information to the network device or the cloud, where the request information is used to obtain the status information of the traffic signal lamp associated with the lane; and to receive the lane association from the network device or the cloud Information about the status of traffic lights.

As an optional implementation manner, the identifier of the traffic signal lamp associated with the lane is a part of the request information.

As an optional implementation manner, the processing unit 1501 is specifically configured to:

Receiving the status information of at least one traffic signal light from the network device or the cloud; and, according to the identification of the traffic signal light associated with the lane, obtaining the status information of the traffic signal light associated with the lane from the status information of the at least one traffic light status information.

As an optional implementation manner, the processing unit 1501 is specifically configured to:

When the distance between the autonomous vehicle and the target intersection is less than the preset threshold, the identification of the current lane is determined.

As an optional implementation manner, the processing unit 1501 is specifically configured to:

When the automatic driving vehicle changes lanes, the identifier of the lane where the vehicle is located after the lane change is determined, and the identifier of the lane where it is located after the lane change is used as the identifier of the current lane.

As an optional implementation manner, the state information of the traffic signal lamp associated with the lane includes at least one of the following information:

The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.

As an optional implementation manner, the processing unit 1501 is specifically configured to:

Determine the driving action of the autonomous vehicle based on at least one of the following information:

The current time, the distance between the autonomous driving vehicle and the intersection, the current driving speed of the autonomous driving vehicle, the time when the traffic signal status information is issued, the current lighting color of the traffic signal, and the forecast of the traffic signal lighting time information.

The driving action includes: stopping, going straight, turning left, turning right or turning around.

As an optional implementation manner, the lane markings include at least one of the following:

The mark of the lane line of the lane, the mark of the lane stop line of the lane, the mark of the lane center line of the lane, and the mark of the lane node of the lane.

The automatic driving control device provided in the embodiment of the present application can execute the method steps in the above method embodiment, and its implementation principles and technical effects are similar, and will not be repeated here.

FIG. 16 is a module structure diagram of an information processing device provided by an embodiment of this application. The device can be the aforementioned network device or cloud, or it can enable the network device or cloud to implement the network in the method provided by the embodiment of this application. A device or a cloud-enabled device. For example, the device may be a network device or a device in the cloud or a chip system. As shown in FIG. 16, the device includes: a processing unit 1601 and a transceiver unit 1602.

The processing unit 1601 is configured to obtain state information of at least one traffic signal light.

The transceiver unit 1602 is used to send traffic signal status information to the autonomous vehicle.

As an optional implementation manner, the transceiver unit 1602 is specifically configured to:

Receive request information sent by a target autonomous driving vehicle, where the request information is used to obtain status information of a traffic signal associated with the lane where the target autonomous driving vehicle is currently located.

The processing unit 1601 is further configured to: obtain state information of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located according to the identifier of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located.

The transceiver unit 1602 is specifically configured to send the state information of the traffic signal lamp associated with the lane to the target autonomous driving vehicle.

As an optional implementation manner, the identifier of the traffic signal light associated with the lane where the target autonomous driving vehicle is currently located is part of the request information.

As an optional implementation manner, the transceiver unit 1602 is specifically configured to:

Broadcast the status information of at least one traffic light to at least one autonomous vehicle.

As an optional implementation manner, the processing unit 1601 is specifically configured to:

Obtain the status information of at least one traffic light from the traffic light control system.

The information processing device provided in the embodiment of the present application can execute the method steps in the above method embodiment, and its implementation principles and technical effects are similar, and will not be repeated here.

It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions, and may be fully or partially integrated into a physical entity during actual implementation, or may be physically separated. And these modules can all be implemented in the form of software called by processing elements; they can also be implemented in the form of hardware; some modules can be implemented in the form of calling software by processing elements, and some of the modules can be implemented in the form of hardware. For example, the determining module may be a separately established processing element, or it may be integrated in a certain chip of the above-mentioned device for implementation. In addition, it may also be stored in the memory of the above-mentioned device in the form of program code, which is determined by a certain processing element of the above-mentioned device. Call and execute the functions of the above-identified module. The implementation of other modules is similar. In addition, all or part of these modules can be integrated together or implemented independently. The processing element described here may be an integrated circuit with signal processing capability. In the implementation process, each step of the above method or each of the above modules can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as: one or more application specific integrated circuits (ASIC), or one or more microprocessors (digital signal processor, DSP), or, one or more field programmable gate arrays (FPGA), etc. For another example, when one of the above modules is implemented in the form of processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program codes. For another example, these modules can be integrated together and implemented in the form of a system-on-a-chip (SOC).

In the above embodiments, it may be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented by software, it can be implemented in the form of a computer program product in whole or in part. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on the computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website, computer, server, or data center. Transmission to another website, computer, server or data center via wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or a data center integrated with one or more available media. The usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, and a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).

When the automatic driving processing device is an automatic driving vehicle, and when the information processing device is a network device or the cloud, the transceiver unit 1502 and the transceiver unit 1602 can be a transmitting unit or a transmitter when sending information, and the transceiver unit 1502 and the transceiver unit 1602 are receiving The information can be a receiving unit or a receiver, the transceiver unit can be a transceiver, and the transceiver, transmitter or receiver can be a radio frequency circuit. When the automatic driving processing device and the information processing device include a storage unit, the storage unit is used to store computer instructions, and the processing unit 1501 or 1601 is in communication with the storage unit, and the processing unit 1501 or 1601 executes the computer instructions stored in the storage unit , Make the automatic driving processing device and the information processing device execute the methods involved in the embodiments of Figs. 10-13. Among them, the processing unit may be a general-purpose central processing unit (CPU), a microprocessor, or a specific ASIC.

When the automatic driving processing device or the information processing device is a chip, the transceiving unit 1502 and the transceiving unit 1602 may be input and/or output interfaces, pins, or circuits. The processing unit 1501 or the processing unit 1601 can execute the computer-executable instructions stored in the storage unit, so that the automatic driving processing device or the chip in the information processing device executes the methods involved in FIGS. 10 to 13. Optionally, the storage unit is a storage unit in the chip, such as a register, a cache, etc., and the storage unit may also be a storage unit located outside the chip in the automatic driving processing device or the information processing device , Such as read only memory (Read Only Memory, ROM) or other types of static storage devices that can store static information and instructions, random access memory (Random Access Memory, RAM), etc.

FIG. 17 is a schematic structural diagram of a communication device provided by an embodiment of this application. The communication device may be the self-driving vehicle described in the foregoing embodiment, or may be the network device or the cloud described in the foregoing embodiment. As shown in FIG. 17, the communication device 1700 may include: a processor 171 (for example, a CPU), a memory 172, and a transceiver 173; the transceiver 173 is coupled to the processor 171, and the processor 171 controls the transceiver 173 to send and receive actions. Various instructions may be stored in the memory 172 to complete various processing functions and implement method steps executed by the autonomous vehicle or network device or cloud in the embodiments of the present application.

Optionally, the communication device involved in the embodiment of the present application may further include: a power supply 174, a system bus 175, and a communication port 176. The transceiver 173 may be integrated in the transceiver of the communication device, or may be an independent transceiver antenna on the communication device. The system bus 175 is used to implement communication connections between components. The above-mentioned communication port 176 is used to realize connection and communication between the communication device and other peripherals.

In the embodiment of the present application, the above-mentioned processor 171 is configured to couple with the memory 172 to read and execute instructions in the memory 172 to implement the method steps executed by the autonomous vehicle or network device or the cloud in the above method embodiment. The transceiver 173 is coupled with the processor 171, and the processor 171 controls the transceiver 173 to send and receive messages. The implementation principles and technical effects are similar, and will not be repeated here.

The system bus mentioned in FIG. 17 may be a peripheral component interconnect standard (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The system bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus. The communication interface is used to realize the communication between the database access device and other devices (such as the client, the read-write library and the read-only library). The memory may include RAM, or may also include non-volatile memory, such as at least one disk memory.

The processor mentioned in Figure 17 may be a general-purpose processor, including a central processing unit (CPU) and a network processor.

(network processor, NP), etc.; it can also be a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

Optionally, an embodiment of the present application further provides a readable storage medium, which stores instructions in the storage medium, which when run on a computer, causes the computer to execute the method in the above-mentioned embodiments shown in FIGS. 10 to 13 .

Optionally, an embodiment of the present application further provides a chip for executing instructions, and the chip is configured to execute the method of the embodiment shown in FIG. 10 to FIG. 13.

An embodiment of the present application further provides a program product, the program product includes a computer program, the computer program is stored in a storage medium, at least one processor can read the computer program from the storage medium, and the at least one When the processor executes the computer program, the method of the embodiment shown in FIG. 10 to FIG. 13 can be implemented.

In the embodiments of the present application, "at least one" refers to one or more, and "multiple" refers to two or more. "And/or" describes the association relationship of the associated objects, indicating that there can be three relationships, for example, A and/or B, which can mean: A alone exists, A and B exist at the same time, and B exists alone, where A, B can be singular or plural. The character "/" generally indicates that the associated objects before and after are in an "or" relationship; in the formula, the character "/" indicates that the associated objects before and after are in a "division" relationship. "The following at least one item (a)" or similar expressions refers to any combination of these items, including any combination of a single item (a) or a plurality of items (a). For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple indivual.

It can be understood that the various numerical numbers involved in the embodiments of the present application are only for easy distinction for description, and are not used to limit the scope of the embodiments of the present application.

It can be understood that, in the embodiments of the present invention, the size of the sequence numbers of the above-mentioned processes does not mean the order of execution. The execution order of the processes should be determined by their functions and internal logic, and should not correspond to the embodiments of the present application. The implementation process constitutes any limitation.

Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: The technical solutions recorded in the foregoing embodiments can still be modified, or some or all of the technical features can be equivalently replaced; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the technical solutions of the embodiments of the present invention. Scope.

Claims (37)

1. An automatic driving control method, characterized in that it includes:

   The self-driving vehicle determines the sign of the current lane;

   Acquiring, by the autonomous vehicle, the state information of the traffic signal light associated with the lane according to the lane mark;

   The self-driving vehicle performs driving control according to the state information of the traffic signal light.
2. The method according to claim 1, wherein the self-driving vehicle obtains state information of traffic signal lights associated with the lane according to the lane markings, comprising:

   Determining, by the self-driving vehicle, the identifier of the traffic signal light associated with the lane according to the identifier of the lane;

   The autonomous vehicle obtains the state information of the traffic signal light associated with the lane from a network device or the cloud.
3. The method according to claim 2, wherein the self-driving vehicle obtains the state information of the traffic signal light associated with the lane from a network device or the cloud, comprising:

   Sending, by the autonomous vehicle, request information to the network device or the cloud, where the request information is used to obtain the status information of the traffic signal lamp associated with the lane;

   The self-driving vehicle receives state information of the traffic signal light associated with the lane from the network device or the cloud.
4. The method according to claim 3, wherein the identifier of the traffic signal light associated with the lane is a part of the request information.
5. The method according to claim 2, wherein the self-driving vehicle obtains the state information of the traffic signal lamp associated with the lane from a network device or the cloud, comprising:

   The autonomous vehicle receives state information of at least one traffic signal from the network device or the cloud;

   The autonomous vehicle obtains the state information of the traffic signal light associated with the lane from the state information of the at least one traffic signal light according to the identifier of the traffic light associated with the lane.
6. The method according to any one of claims 1 to 5, wherein the automatic driving vehicle determining the identifier of the current lane comprises:

   If the distance between the self-driving vehicle and the target intersection is less than a preset threshold, the self-driving vehicle determines the identity of the lane where it is currently located.
7. The method according to claim 6, wherein the automatic driving vehicle determining the identifier of the current lane further comprises:

   If the automatic driving vehicle changes lanes, the automatic driving vehicle determines the lane markings where the automatic driving vehicle is located after the lane change;

   The self-driving vehicle uses the identifier of the lane where the vehicle is located after the lane change as the identifier of the lane where it is currently located.
8. The method according to any one of claims 1-7, wherein the state information of the traffic signal lamp associated with the lane includes at least one of the following information:

   The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.
9. The method according to any one of claims 1-8, wherein the self-driving vehicle performs driving control according to the state information of the traffic signal light, comprising:

   The self-driving vehicle determines the driving action of the self-driving vehicle according to at least one of the following information:

   The current time, the distance between the autonomous driving vehicle and the intersection, the current driving speed of the autonomous vehicle, the time when the traffic signal status information is issued, the current lighting color of the traffic signal, and the forecast of the traffic signal lighting time information;

   The driving action includes: stopping, going straight, turning left, turning right or turning around.
10. The method according to any one of claims 1-9, wherein the identification of the lane includes at least one of the identifications:

    The identification of the lane line of the lane, the identification of the lane stop line of the lane, the identification of the lane center line of the lane, and the identification of the lane node of the lane.
11. An information processing method, characterized in that it comprises:

    Acquiring status information of at least one traffic signal;

    Send status information of traffic lights to autonomous vehicles.
12. The method according to claim 11, wherein the sending the state information of the traffic signal light to the self-driving vehicle comprises:

    Receiving request information sent by a target autonomous driving vehicle, where the request information is used to obtain status information of a traffic signal associated with the lane where the target autonomous driving vehicle is currently located;

    Acquiring the status information of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located according to the identifier of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located;

    Sending the state information of the traffic signal light associated with the lane to the target autonomous vehicle.
13. The method according to claim 12, wherein the identifier of the traffic signal light associated with the lane where the target autonomous driving vehicle is currently located is part of the request information.
14. The method according to claim 11, wherein the sending the state information of the traffic signal light to the self-driving vehicle comprises:

    Broadcast the status information of at least one traffic light to at least one autonomous vehicle.
15. The method according to any one of claims 11-14, wherein the acquiring state information of at least one traffic signal light comprises:

    Obtain the status information of at least one traffic light from the traffic light control system.
16. An automatic driving control device, characterized by comprising: a processing unit;

    The processing unit is configured to determine the identifier of the current lane, obtain the state information of the traffic signal lamp associated with the lane according to the identifier of the lane, and perform driving control according to the state information of the traffic signal lamp.
17. The device according to claim 16, wherein the processing unit is specifically configured to:

    Determine the identifier of the traffic signal light associated with the lane according to the identifier of the lane; and,

    Obtain the state information of the traffic signal light associated with the lane from a network device or the cloud.
18. The device according to claim 17, wherein the device further comprises: a transceiver unit;

    The transceiver unit is configured to send request information to the network device or the cloud, where the request information is used to obtain the status information of the traffic signal lamp associated with the lane; and, to receive the lane from the network device or the cloud The status information of the associated traffic lights.
19. The device according to claim 18, wherein the identifier of the traffic signal lamp associated with the lane is a part of the request information.
20. The device according to claim 17, wherein the processing unit is specifically configured to:

    Receiving the status information of at least one traffic signal light from the network device or the cloud; and, according to the identification of the traffic signal light associated with the lane, obtaining the status information of the traffic signal light associated with the lane from the status information of the at least one traffic light status information.
21. The device according to any one of claims 16-20, wherein the processing unit is specifically configured to:

    When the distance between the autonomous vehicle and the target intersection is less than the preset threshold, the identification of the current lane is determined.
22. The device according to claim 21, wherein the processing unit is specifically configured to:

    When the automatic driving vehicle changes lanes, the identifier of the lane where the vehicle is located after the lane change is determined, and the identifier of the lane where it is located after the lane change is used as the identifier of the current lane.
23. The device according to any one of claims 16-22, wherein the state information of the traffic signal lamp associated with the lane comprises at least one of the following information:

    The identifier of the traffic signal light, the type of the traffic signal light, the time when the traffic signal status information is issued, the current light color, and the light time forecast information.
24. The device according to any one of claims 16-23, wherein the processing unit is specifically configured to:

    Determine the driving action of the autonomous vehicle based on at least one of the following information:

    The current time, the distance between the autonomous driving vehicle and the intersection, the current driving speed of the autonomous driving vehicle, the time when the traffic signal status information is issued, the current lighting color of the traffic signal, and the forecast of the traffic signal lighting time information;

    The driving action includes: stopping, going straight, turning left, turning right or turning around.
25. The device according to any one of claims 16-24, wherein the lane markings comprise at least one of the following:

    The identification of the lane line of the lane, the identification of the lane stop line of the lane, the identification of the lane center line of the lane, and the identification of the lane node of the lane.
26. An information processing device, characterized by comprising: a processing unit and a transceiver unit;

    The processing unit is used to obtain state information of at least one traffic signal light;

    The transceiver unit is used to send the state information of the traffic signal light to the self-driving vehicle.
27. The device according to claim 26, wherein the transceiver unit is specifically configured to:

    Receiving request information sent by a target autonomous driving vehicle, where the request information is used to obtain status information of a traffic signal associated with the lane where the target autonomous driving vehicle is currently located;

    The processing unit is further configured to: obtain state information of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located according to the identifier of the traffic signal associated with the lane where the target autonomous driving vehicle is currently located;

    The transceiver unit is specifically configured to send the state information of the traffic signal lamp associated with the lane to the target autonomous driving vehicle.
28. The device according to claim 27, wherein the identifier of the traffic signal light associated with the lane where the target autonomous driving vehicle is currently located is part of the request information.
29. The device according to claim 26, wherein the transceiver unit is specifically configured to:

    Broadcast the status information of at least one traffic light to at least one autonomous vehicle.
30. The device according to any one of claims 26-29, wherein the processing unit is specifically configured to:

    Obtain the status information of at least one traffic light from the traffic light control system.
31. A communication device includes a processor, the processor is connected to a memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the device executes as claimed in the claims The method of any one of 1 to 10.
32. A communication device includes a processor, the processor is connected to a memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the device executes as claimed in the claims The method of any one of 11-15.
33. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 1 to 10 is implemented.
34. A computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed, the method according to any one of claims 11 to 15 is implemented.
35. A chip, characterized in that it includes a processor and an interface;

    The processor is configured to read instructions to execute the automatic driving control method according to any one of claims 1 to 10.
36. A chip, characterized in that it includes a processor and an interface;

    The processor is used to read instructions to execute the information processing method according to any one of claims 11 to 15.
37. A communication system, characterized by comprising the communication device according to claim 31, the communication device according to claim 32, and a traffic signal light control system.

Images