Main and side road identification method and system, vehicle and product

Abstract

The invention relates to the field of vehicle navigation, and provides a main and side road identification method and system, a vehicle and a product. The method comprises the following steps: acquiring a standard definition map and surrounding environment information acquired by a sensor; wherein the environment information comprises at least one of a vehicle, a traffic object and a boundary line; judging whether the environment information contains boundary lines on two sides of a road where the target moving tool is located and a vehicle; if the judgment result is that the environment information contains the boundary line and the vehicle, judging whether the target moving tool is located on the main road or the side road by utilizing the environment information; and if a judgment result is that the environment information does not contain the boundary line and the vehicle, judging whether the target moving tool is located on the main road or the side road by utilizing the standard definition map and the environment information. By identifying the boundary lines on the two sides of the road and comprehensively utilizing the environment information and / or the standard definition map, the situation that the target moving tool is located on the main road or the side road can be accurately identified.

Description

Technical Field

[0001] The present application relates to the field of vehicle navigation, and in particular to a method, system, vehicle and product for identifying main and auxiliary roads. Background Art

[0002] With the development of map navigation technology, navigation information plays an important role in autonomous driving and assisted driving scenarios.

[0003] In the existing technology, although the Standard Definition Map (SD) can meet driving needs under general circumstances. However, the accuracy of SD map data is not high and cannot meet the needs of high-precision positioning. For example, in the main and auxiliary road scenario, since the main road and the auxiliary road are adjacent, when the vehicle is driving in an environment containing the main and auxiliary roads, the SD map data cannot accurately identify whether the vehicle is driving on the main road or the auxiliary road. In the existing solution, it is usually judged whether the vehicle is about to enter the main road or the auxiliary road based on the intersection of the main and auxiliary roads. However, this method is not robust and is prone to the problem of main and auxiliary road identification errors. Summary of the invention

[0004] Embodiments of the present application provide a method, system, vehicle and product for identifying main and auxiliary roads.

[0005] According to the first aspect of the present disclosure, a method for identifying main and secondary roads is provided, the method comprising: obtaining a standard definition map and surrounding environmental information collected by sensors; wherein the environmental information comprises: at least one of vehicles, traffic objects, boundary lines and lane lines; judging whether the environmental information contains boundary lines and vehicles on both sides of the road where the target mobile tool is located; if the judgment result is that the environmental information contains boundary lines and vehicles, using the environmental information to judge whether the target mobile tool is located on the main road or the secondary road; if the judgment result is that the environmental information does not contain boundary lines and / or vehicles, using the standard definition map and environmental information to judge whether the target mobile tool is located on the main road or the secondary road.

[0006] In the above implementation, when the target mobile tool is traveling in the main and auxiliary road environment, the surrounding environmental information can be collected through sensors. When the boundary line can be accurately identified from the environmental information, the positional relationship between the vehicle, the traffic object and the boundary line can be directly used to determine whether the target mobile tool is on the main road or the auxiliary road. If the boundary line is not identified from the environmental information, it is necessary to use the standard definition map and environmental information to comprehensively determine whether the target mobile tool is on the main road or the auxiliary road. The above two methods of determining the main and auxiliary roads do not rely on the connecting intersections between the main road and the auxiliary road, nor do they rely entirely on the vehicle's own positioning. The comprehensive use of environmental information and / or standard definition maps can effectively improve the accuracy of determining the driving status of the vehicle on the main road or the auxiliary road.

[0007] According to at least one embodiment of the present disclosure, the boundary lines on both sides of the road include a left boundary line and a right boundary line. If the judgment result is that the environmental information contains the boundary line and the vehicle, the environmental information is used to determine whether the target mobile tool is located on the main road or the secondary road, including: based on the type of environmental information on the left side of the identified left boundary line, and / or the type of environmental information on the right side of the right boundary line, determining whether the target mobile tool is located on the main road or the secondary road.

[0008] In the above implementation, it is not necessary to distinguish the road that the target vehicle enters and the link mark of the corresponding road in the SD map data at the intersection of the main road and the auxiliary road. Instead, after the target vehicle completely enters the main road or the auxiliary road, it is possible to determine the road where the target vehicle is located at this time, and further determine whether the road where the current vehicle is located is consistent with the navigation route. This judgment method does not rely on the intersection of the main road and the auxiliary road, nor does it rely entirely on the positioning of the vehicle itself. Instead, it can be known whether the target vehicle is traveling on the main road or the auxiliary road by identifying the boundary line and making a comprehensive judgment on the environmental information on the corresponding sides of different boundary lines. This can effectively improve the accuracy of judging the driving status of the vehicle on the main road or the auxiliary road. In addition, most of these environmental information are conventionally collected information in intelligent driving scenarios. Without the need to add additional sensors, the existing information can be fully utilized to help accurately locate the main and auxiliary road positions of the vehicle.

[0009] According to at least one embodiment of the present disclosure, when the road traffic direction is to keep to the right, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates the presence of oncoming vehicles, and / or the environmental information on the right side of the right boundary line indicates the presence of vehicles traveling in the same direction, then it is determined that the target mobile tool is located on the main road; when the road traffic direction is to keep to the left, if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of oncoming vehicles, and / or the environmental information on the left side of the left boundary line indicates the presence of vehicles traveling in the same direction, then it is determined that the target mobile tool is located on the main road.

[0010] In the above implementation, by cleverly utilizing the different environmental information of the target vehicle's different boundary lines, it is determined that the current target vehicle is located on the main road. There is no need to determine based on the connecting intersection between the main road and the auxiliary road, which can effectively improve the accuracy of whether the target vehicle is driving or stationary on the main road.

[0011] According to at least one embodiment of the present disclosure, when the road traffic direction is to keep to the right, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the same direction, and / or the environmental information on the right side of the right boundary line indicates the presence of traffic objects, then it is determined that the target mobile tool is on the auxiliary road; when the road traffic direction is to keep to the left, if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the same direction, and / or the environmental information on the left side of the left boundary line indicates the presence of traffic objects, then it is determined that the target mobile tool is on the auxiliary road.

[0012] In the above implementation, by cleverly utilizing the different environmental information of the target vehicle's different boundary lines, it is comprehensively judged that the current location of the target vehicle is a secondary road. There is no need to judge based on the connecting intersection between the main road and the secondary road, which can effectively improve the accuracy of the target vehicle driving or stationary on the secondary road.

[0013] According to at least one embodiment of the present disclosure, standard-defined map data includes: the number of main road lanes and the number of secondary road lanes; environmental information also includes lane lines and / or lane widths; if the environmental information does not include vehicles and / or traffic objects, or the environmental information does not include road boundary lines, the number of perceived lanes on the road where the target mobile tool is located is determined from the environmental information; the number of perceived lanes is matched with the number of main road lanes and the number of secondary road lanes corresponding to the location of the target mobile tool in the standard-defined map, and it is determined whether the target mobile tool is located on the main road or the secondary road based on the matching results.

[0014] In the above implementation, the SD map data and the number of lanes sensed by the sensor are used for comparison to determine the lane the target vehicle is currently in. This allows the target mobile tool to accurately identify whether the current location of the target mobile tool is a main road or a secondary road even when the target mobile tool cannot obtain environmental information or cannot identify the boundary line.

[0015] According to at least one embodiment of the present disclosure, the number of perceived lanes on the road where the target mobile tool is located is determined from environmental information, including: determining the number of lane lines of the current road section perceived from the environmental information, and the lane line distance between adjacent lane lines; determining the number of perceived lanes based on the number of lane lines, and the relationship between the distance between adjacent lane lines and a lane width threshold, wherein if the distance between the two lane lines on both sides of each perceived lane is greater than or equal to the lane width threshold.

[0016] In the above implementation, after the lane lines are identified and the number of corresponding identified lane lines is calculated, in order to ensure the accuracy of the number of identified lane lines, the lane width is used for verification, so as to ensure that the subsequent identification results of the vehicle on the main and auxiliary roads are accurate.

[0017] According to at least one embodiment of the present disclosure, the number of perceived lanes is matched with the number of main road lanes and the number of secondary road lanes corresponding to the location of the target mobile tool in the standard definition map, and it is determined whether the target mobile tool is located on the main road or the secondary road based on the matching result, including: matching the number of perceived lanes with the number of main road lanes and the number of secondary road lanes, respectively, if the matching result is that the number of perceived lanes is the same as the number of main road lanes, then it is determined that the target mobile tool is located on the main road; if the matching result is that the number of perceived lanes is the same as the number of secondary road lanes, then it is determined that the target mobile tool is located on the secondary road.

[0018] In the above implementation, by comparing the number of lanes, it is possible to accurately identify whether the target vehicle is on the main road or the secondary road even when the environmental information is incomplete or the boundary line recognition is inaccurate, and provide the accuracy of identifying the position of the target vehicle on the main and secondary roads.

[0019] According to at least one embodiment of the present disclosure, the environmental information also includes: at least one of a curbstone, a curb, a guardrail, a green belt, a double yellow line and a lane line; judging whether the environmental information contains the boundary lines on both sides of the road where the target moving tool is located, comprising: based on the environmental information, taking at least one of the curbstone, curb, guardrail, green belt and double yellow line respectively contained on both sides of the identified target moving tool as an alternative boundary line; if curbstones, guardrails and double yellow lines are identified on both sides in multiple consecutive frames, the alternative boundary line located on the left side of the road and closest to the target moving tool is used as the left boundary line, and the alternative boundary line located on the right side of the road and closest to the target moving tool is used as the right boundary line.

[0020] In the above implementation, the boundary line of the road where the target vehicle is located can be found quickly and accurately in a complex environment, thereby obtaining a more accurate recognition result.

[0021] After obtaining the standard definition map according to at least one embodiment of the present disclosure, it also includes: determining whether there are other roads in the standard definition map data that are parallel and adjacent to the road where the target mobile tool is located; if so, triggering an identification instruction for the road where the target mobile tool is located as a main road or a secondary road.

[0022] In the above implementation, the main and auxiliary roads can be identified in time when appropriate, and in normal situations (for example, there is no auxiliary road, or the main and auxiliary roads have been accurately identified), the main and auxiliary roads do not need to be identified again, thereby improving the identification efficiency.

[0023] According to at least one embodiment of the present disclosure, after determining that the target mobile tool is located on a main road or a secondary road, it also includes: judging whether the identification result of the road where the target mobile tool is located is the same road as the road displayed in the navigation map; if it is not the same road, modifying the road display of the target mobile tool in the navigation map.

[0024] In the above implementation, the lane position of the target vehicle in the main and auxiliary road environment can be accurately identified, effectively making up for the defect of poor accuracy of SD map data. The navigation map based on SD map data is corrected using the main and auxiliary road identification results, so as to obtain a more accurate navigation effect.

[0025] According to at least one embodiment of the present disclosure, if the road is not the same, a prompt message for re-planning the navigation route is sent to the user, and the navigation route in the navigation map is re-planned based on the modified road display.

[0026] In the above implementation, it is recognized through the above embodiments that the road where the target mobile tool is located is different from the road displayed in the navigation map, and the road in the navigation map is corrected. Further, a prompt message (voice or text prompt message) can be sent to the user to remind the user that the navigation needs to be re-planned. It is convenient for the user to timely understand the current navigation status and correct the navigation route in time.

[0027] According to a second aspect of the present disclosure, a main and auxiliary road identification system is provided, including a processor and a memory, the memory storing a computer program, and when the computer program is executed by the processor, the main and auxiliary road identification system performs the following process: obtaining a standard definition map and surrounding environmental information collected by sensors; wherein the environmental information includes: at least one of vehicles, traffic objects, boundary lines and lane lines; identifying whether the environmental information contains boundary lines and vehicles on both sides of the road where the target mobile tool is located; if the boundary lines and vehicles are identified, using the environmental information to determine whether the target mobile tool is located on the main road or the auxiliary road; if the boundary lines and vehicles are not identified, using the standard definition map and environmental information to determine whether the target mobile tool is located on the main road or the auxiliary road.

[0028] The target moving tool is located on the main road or the secondary road. The target moving tool is located on the main road or the secondary road. According to the third aspect of the present disclosure, a vehicle is provided, including an on-board electronic device, which is used to implement the main and secondary road identification method as described in the first aspect.

[0029] According to a fourth aspect of the present disclosure, a computer program product is provided. The computer program product includes a computer program signal. When the computer program signal is executed by a processor, it is used to implement at least the method described in the first aspect.

[0030] In the main and auxiliary road identification method, system, vehicle and product provided by the embodiment of the present application, the target mobile tool is traveling on the road, and the road conditions are complex and diverse. Some include main and auxiliary roads. In order to accurately identify whether the target mobile tool is traveling on the main road or the auxiliary road, a standard definition map can be obtained, and environmental information collected by sensors can be obtained; the environmental information includes: at least one of a vehicle, a traffic object, a boundary line and a lane line. Then, the environmental information is identified. If the boundary line is identified, the boundary line and other environmental information can be used to determine whether the target mobile tool is located on the main road or the auxiliary road. If the boundary line is not identified, the standard definition map and environmental information can be used to determine whether the target mobile tool is located on the main road or the auxiliary road. Through the above scheme, the dependence on the identification of the intersection connecting the main and auxiliary roads is eliminated, that is, even if the intersection of the main and auxiliary roads is not identified, by identifying the boundary lines on both sides of the road, the comprehensive use of environmental information and / or standard definition maps can accurately identify whether the target mobile tool is located on the main road or the auxiliary road. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application.

[0032] Figure 1 This is a schematic diagram of a main-auxiliary road identification scenario illustrated in an embodiment of the present application.

[0033] Figure 2 A method for identifying main and auxiliary roads is provided in an embodiment of the present application.

[0034] Figure 3a This is a schematic diagram illustrating the position of a target vehicle on a main road in an embodiment of the present application.

[0035] Figure 3b This is a schematic diagram for illustrating the position of a target vehicle on a secondary road in an embodiment of the present application.

[0036] Figure 4 A flowchart of another main and auxiliary road identification method provided in an embodiment of the present application.

[0037] Figure 5 A schematic diagram of the number of lanes sensed according to an embodiment of the present application.

[0038] Figure 6a A schematic diagram of a boundary line illustrated in an embodiment of the present application.

[0039] Figure 6b A schematic diagram of another boundary line recognition method for illustrating an embodiment of the present application Figure 7aThe following is a schematic diagram of a main and auxiliary road identification system for illustrating an embodiment of the present application.

[0040] Figure 7b A schematic diagram of a main and auxiliary road identification process provided in an embodiment of the present application.

[0041] Figure 7c Another schematic diagram of the main and auxiliary road identification process provided in an embodiment of the present application.

[0042] Figure 8 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application.

[0043] Fig. 9 A schematic flow chart of an automatic driving method provided in an embodiment of the present application.

[0044] Fig.10 A flowchart of a navigation and positioning method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0046] In some processes described in the specification, claims and the above-mentioned figures of the present invention, multiple operations that appear in a specific order are included, and these operations may not be executed in the order in which they appear in this article or may be executed in parallel. The serial numbers of the operations, such as 101, 102, etc., are only used to distinguish between different operations, and the serial numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0047] Terminology explanation: Standard Definition Map (SD): is a type of map widely used in the field of navigation and autonomous driving. SD map is a map with relatively low accuracy, usually at the meter level, and is mainly used to meet daily navigation needs. Although the accuracy of SD map is not as good as that of high-precision map (HD Map), it is sufficient to meet most daily navigation and positioning needs. Since the production cost of SD map is relatively low, its coverage is usually wide and can cover most cities and roads. The update frequency of SD map is relatively low, generally once a year or every few years to adapt to road changes. The application scenarios of SD map are usually used for daily navigation and driving assistance. The data in the standard definition map is referred to as SD map data in the following text.

[0048] High Definition Map (HD Map): A digital map based on advanced surveying and mapping technology and high-precision positioning data that provides accurate and detailed road information and environmental perception data. This map not only contains the basic geographic information of traditional maps, such as road networks, topography, etc., but also provides more detailed and rich information to meet the application scenarios with extremely high requirements for map accuracy, such as autonomous driving and intelligent transportation systems.

[0049] In the application scenario of transportation tools (such as motor vehicles), high-precision maps are needed to provide data support when motor vehicles perform path planning. However, the data collection of high-precision maps requires a lot of human and material resources. Data collection is a huge and intensive task. Hundreds of data collection vehicles are responsible for collecting source data for map making to ensure that the map is quickly updated every time the road changes. The test vehicle uses a variety of sensors, such as the Global Positioning System (GPS), inertial measurement unit (IMU), lidar, and camera. By collecting various types of data, these data are integrated to finally generate a high-precision map. The data processing of high-precision maps also requires a lot of manpower and material resources. Data processing refers to how to organize, classify and simplify the collected data when the high-precision map is built offline to obtain an initial map template without any semantic information or annotations. Running high-precision maps in vehicle systems requires a lot of hardware resources, and the subsequent planning and decision-making modules are highly dependent on offline high-precision maps, which cannot meet the computing resources required for real-time computing of the vehicle system, and is not conducive to the lightweight development of the vehicle system. Therefore, in many cases, standard definition maps are required.

[0050] However, the accuracy of standard definition maps is not high, and they contain little important data. In particular, in some sections, it is impossible to accurately identify the road where the vehicle is located. For example, in the scenario of driving on the main and auxiliary roads, since the main road and the auxiliary road are very close, it is easy to deviate if the vehicle positioning is relied on alone. For example, the vehicle was originally driving on the main road, but the positioning was on the auxiliary road; or, the vehicle was originally driving on the auxiliary road, but the positioning was on the main road. In some schemes, when identifying the main and auxiliary roads, it is necessary to detect the intersection of the main and auxiliary roads and determine the direction of the intersection in order to identify whether the mobile tool has switched between the main and auxiliary roads. However, in actual applications, it is easy to make misjudgments in the process of using intersections and intersection directions to judge the main and auxiliary roads. For example, the inclination angle of the intersection where the main road and the auxiliary road are connected is relatively small, and the intersection where the target mobile tool passes through the main road and the auxiliary road may not be detected. Therefore, a solution to improve the accuracy of main and auxiliary road recognition is needed.

[0051] The target mobile tool mentioned here can be various mobile tools such as cars (including traditional fuel vehicles, new energy vehicles, hydrogen energy vehicles, etc.), bicycles, motorcycles, unmanned delivery vehicles, mobile robots, etc. The target mobile tool can travel on the road, including various lanes such as motor vehicle lanes and non-motor vehicle lanes. For ease of understanding, in the following embodiments, the technical solution of this application will be described by taking the target mobile tool as a target vehicle as an example.

[0052] Vehicles refer to all kinds of vehicles including motor vehicles, excluding non-motor vehicles such as bicycles. Traffic objects can be understood as other objects on the road besides motor vehicles, including non-motor vehicles (such as bicycles), pedestrians, etc.

[0053] like Figure 1 Schematic diagram of the main and auxiliary road identification scene illustrated in the embodiment of the present application. Figure 1 As can be seen in the figure, the target mobile tool is traveling on a road including a main road and a secondary road. The main road is a two-way four-lane road, and the secondary road is a single lane. On the main road, the two two-way lanes are separated by a double yellow line. There are secondary roads on both sides of the main road of the two-way lanes. There is a guardrail between the main road and the secondary road, and there will be an intersection connecting the main road and the secondary road where the main road and the secondary road are allowed to switch.

[0054] Figure 1The target moving tool in the image is traveling on the right main road, there is an opposite vehicle traveling in the opposite direction of the target vehicle on the left main road, there are vehicles traveling in the same direction on the right auxiliary road, and there are pedestrians in the non-motor vehicle area. According to traffic rules, during normal driving, you can change between different lanes in the main road on this side. For example, the vehicle changes from the first lane of the right main road to the left side to the second lane adjacent to the double yellow line, but the vehicle is not allowed to cross the double yellow line to travel in the opposite lane. Other vehicles on the other side of the double yellow line are traveling in the opposite direction of the vehicle. As the vehicle continues to move forward, when passing through the connecting intersection between the main road and the auxiliary road, the vehicle can change the main and auxiliary roads, that is, the vehicle can travel from the main road to the right auxiliary road through the connecting intersection. If the vehicle is traveling on the auxiliary road, the left side of the auxiliary road is the main road in the same direction, that is, the driving direction of the auxiliary road vehicle is the same as that of other vehicles on the main road in the same direction. On the right side of the auxiliary road and on the auxiliary road, there will be various motor vehicles and non-motor vehicles traveling, for example, there may be bicycles, children's cars, pedestrians, pets, etc. on the auxiliary road. There may also be other vehicles traveling on the auxiliary road at the same time. When the vehicle is driving, it can use the on-board sensors to detect the boundary lines on both sides of the road where the vehicle is located (for example, double yellow lines, green belts, guardrails, etc.). When the vehicle is driving on the main road, the sensor can also detect the environmental information of the opposite vehicles driving in the opposite direction on the other side of the double yellow line. And the same-direction vehicles and environmental information on the auxiliary road on the other side of the guardrail. When the vehicle drives from the main road to the auxiliary road through the connecting intersection, the sensor can detect the guardrail between the main road and the auxiliary road on the left side of the auxiliary road and the same-direction vehicles and environmental information on its left side, as well as the curb on the right side of the auxiliary road and pedestrians on its right side. With the above information, the vehicle can comprehensively judge whether the road it is currently traveling on is on the auxiliary road or the main road, and the judgment result is more accurate.

[0055] like Figure 2 A method for identifying main and auxiliary roads is provided in an embodiment of the present application. The method can be applied to vehicle-mounted electronic devices, or can be used in combination with vehicle-mounted electronic devices and a server (including a cloud server and a local server), or can be deployed on a user's mobile terminal. Figure 2 The specific main and auxiliary road identification method steps are as follows.

[0056] Step 201: Obtain a standard definition map and surrounding environmental information collected by sensors; wherein the environmental information includes at least one of a vehicle, a traffic object, and a boundary line.

[0057] The sensors mentioned here can be visual sensors, laser sensors and other sensors that can collect environmental information. These sensors can be installed at appropriate locations on the vehicle body (for example, the roof, vehicle rearview mirror, etc.). The specific installation location and sensor type of the sensor are not limited here, and users can choose according to their actual needs. It can also be a sensor in the roadside equipment, which shares the collected environmental information with the target vehicle within the specified range. After receiving the environmental information from at least one sensor, the target vehicle processes the information according to the needs and then performs the corresponding tasks, such as updating the lane information on the navigation, updating the road condition information, etc.

[0058] The environmental information mentioned here includes various information such as vehicle information (for example, fuel vehicles, new energy vehicles, etc.), traffic object information (for example, bicycles, pedestrians, wheelchairs, pets, etc.), environmental information, roadside information (for example, billboards, sidewalks, etc.). In practical applications, environmental information can be selected as needed, and the corresponding specific environmental information can be selected according to different detection requirements. For example, in this application scheme, vehicle information and traffic object information will be comprehensively utilized, or vehicle information, traffic object information, environmental information and roadside information will be used to determine whether the road currently traveled by the target vehicle is a main road or a secondary road.

[0059] Step 202: Determine whether the environmental information contains boundary lines and vehicles on both sides of the road where the target mobile tool is located.

[0060] After the environmental information is collected, it will be identified whether it contains boundary lines, vehicles, etc. The environmental information here can be a video image collected by an image sensor. The video image contains various environmental information, and the identification of environmental information can be the identification of the content of multiple frames in the video. In particular, it focuses on identifying whether it contains boundary lines, vehicles, traffic objects, etc.

[0061] Step 203: If the judgment result is that the environmental information contains a boundary line and a vehicle, the environmental information is used to determine whether the target mobile tool is located on a main road or a secondary road.

[0062] Step 204: If the judgment result is that the environmental information does not contain a boundary line and / or a vehicle, use the standard definition map and environmental information to determine whether the target mobile tool is located on a main road or a secondary road.

[0063] In actual applications, the method used to determine whether the target mobile tool is on a main road or a secondary road will be determined based on the recognition results of the environmental information. When the boundary lines on the left and right sides, as well as the vehicles on both sides of the boundary lines, can be accurately identified, the relative position relationship between the boundary lines and the vehicles can be used to determine whether the target mobile tool is on a main road or a secondary road. If the boundary line and the vehicle cannot be identified at the same time from the environmental information, or only the boundary line or the vehicle is identified, it is necessary to combine the standard definition map and environmental information to comprehensively determine whether the target mobile tool is on a secondary road or a main road.

[0064] It should be noted that the boundary lines on both sides of the road include a left boundary line and a right boundary line. The position of the boundary line mentioned here is determined according to the driving direction of the target moving tool. In other words, the boundary line on the left side of the target moving tool is called the left boundary line, and the boundary line on the right side of the target moving tool is called the right boundary line.

[0065] In different countries or regions, vehicles move in different ways due to different traffic rules. In simple terms, traffic rules can be divided into left-hand driving rules and right-hand driving rules. The boundary line mentioned here is only used to demarcate the scope of the main road and the scope of the secondary road, while the lane lines between different lanes in a main road with multiple lanes are not boundary lines.

[0066] In the subsequent embodiments, unless otherwise specified, the traffic rule of driving on the right will be taken as an example for explanation.

[0067] When a vehicle is driving on a main or auxiliary road, it can drive on the auxiliary road or on the main road. Therefore, when a vehicle is driving on the right side of the main road, the left boundary line is the left boundary line of the main road (that is, Figure 1 The double yellow line shown in the figure can also be considered as a green belt or guardrail between the opposite main road. The right boundary line is the right boundary line of the main road (that is, Figure 1 The first solid line shown in the figure) can also be considered as the green belt or guardrail between the auxiliary road and the side road. Similarly, when the vehicle is driving on the right side of the auxiliary road, the left side boundary line is the left side boundary line of the auxiliary road (that is, Figure 1 The first solid line shown in the figure) can also be considered as the green belt or guardrail between the auxiliary road and the main road. The right boundary line is the right boundary line of the auxiliary road (that is, Figure 1 The second solid line shown in FIG. 1 may also be considered as a traffic object road or a pedestrian path, a curb, etc. Which one should be selected as the left boundary line or the right boundary line will be described in the following embodiments, and can be referred to in subsequent embodiments, and will not be repeated here.

[0068] Based on the identified type of environmental information on the left side of the left boundary line and / or the type of environmental information on the right side of the right boundary line, it is determined that the target mobile tool is located on the main road or the secondary road. The type of environmental information mentioned here can be understood as the type of vehicle or the type of traffic object.

[0069] In actual applications, the target vehicle travels between the left boundary line and the right boundary line. In order to accurately determine the road where the target vehicle is located, it is necessary to collect environmental information on the left side of the left boundary line of the road where the target vehicle is located, and to collect environmental information on the right side of the right boundary line.

[0070] When identifying main and auxiliary roads, it is generally not necessary to obtain environmental information between the left and right boundary lines. That is to say, after collecting a lot of environmental information, the positions of the left and right boundary lines will be determined, and the positional relationship between vehicles and traffic objects and the left and right boundary lines will be distinguished. According to the positional relationship, vehicles and traffic objects between the left and right boundary lines are eliminated. Vehicles and traffic objects on the left side of the left boundary line are retained, and vehicles and traffic objects on the right side of the right boundary line are retained. Eliminate the interference of unnecessary environmental information on subsequent judgment work.

[0071] For example, Figure 3a The following is a schematic diagram of the position of a target vehicle on a main road in an embodiment of the present application. Figure 3a As can be seen from the figure, the target vehicle is driving on the main road, so the left boundary line of the target vehicle is Figure 3a The double yellow line shown in the figure, the right boundary line is Figure 3a The first solid line is shown in . Correspondingly, the environmental information that needs to be collected includes: environmental information on the left side of the left boundary line (that is, the double yellow line) (for example, vehicles traveling in the opposite direction on the opposite main road), and environmental information on the right side of the right boundary line (for example, vehicles traveling in the same direction on the auxiliary road). As for the non-motor vehicle area on the right side of the auxiliary road, since it is on the right side of the curb of the auxiliary road, the curb is another boundary line, therefore, the non-motor vehicle area is not within the scope of this environmental information recognition.

[0072] like Figure 3b The following is a schematic diagram of the position of a target vehicle on a secondary road in an embodiment of the present application. The boundary line identified when the target vehicle is driving on the secondary road is different from the boundary line identified when the target vehicle is driving on the main road. Figure 3b As shown, the left boundary line of the auxiliary road where the target vehicle is located is Figure 3b The first solid line is shown in Figure 3bCorrespondingly, the environmental information to be collected includes: environmental information on the left side of the left boundary line (i.e., the first solid line) (e.g., vehicles traveling in the same direction on the main road in the same direction), and environmental information on the right side of the right boundary line (i.e., the curb) (e.g., non-motor vehicles, pedestrians, pets, etc.).

[0073] It should be noted that the opposite roads (main roads) can be understood as two roads where vehicles are traveling in opposite directions. Vehicles traveling in opposite directions can be understood as vehicles traveling in opposite directions on a road or lane. The same-direction roads can be understood as two roads where vehicles are traveling in the same direction. Vehicles traveling in the same direction can be understood as vehicles traveling in the same direction on a road or lane.

[0074] When judging the driving state of the main and auxiliary roads (that is, judging whether the target vehicle is driving on the main road or the auxiliary road), the environmental information on the left side of the left boundary line and / or the environmental information on the right side of the right boundary line are used for comprehensive judgment. The specific implementation scheme will be described in the following embodiments, and will not be repeated here. Through the above scheme, it is not necessary to distinguish the road entered by the target vehicle and the link mark of the corresponding road in the SD map data at the intersection of the main road and the auxiliary road. Instead, after the target vehicle completely enters the main road or the auxiliary road, it can be judged that the road where the target vehicle is located at this time, and further it can be judged whether the road where the current vehicle is located is consistent with the navigation route. This judgment method does not rely on the intersection of the main road and the auxiliary road, nor does it rely entirely on the positioning of the vehicle itself, but by identifying the boundary line and comprehensively judging the environmental information on the corresponding sides of different boundary lines, it can be known that the target vehicle is driving on the main road or the auxiliary road, which can effectively improve the accuracy of judging the driving state of the vehicle on the main road or the auxiliary road. In addition, most of these environmental information are conventionally collected information in intelligent driving scenarios. Without adding additional sensors, the existing information can be fully utilized to help achieve accurate positioning of the main and auxiliary road positions of the vehicle.

[0075] In practical applications, the acquired environmental information is classified and identified to identify what information it contains and what information it is. For example, vehicles, traffic objects, boundary lines, lane lines, lane widths, etc. are identified. When collecting environmental information and identifying boundary lines, it is necessary to comprehensively consider the shooting angle of environmental information, the position of the sensor on the vehicle, and other information for identification. For example, if the sensor (such as a camera) is arranged at the front end of the vehicle, the boundary line on the left side of the captured image can be used as the left boundary line, and the boundary line on the right side of the image can be used as the right boundary line. If the sensors are respectively arranged on the left and right sides of the vehicle, for example, one on the left rearview mirror and the other on the right rearview mirror. Then the boundary line in the image captured by the camera on the left rearview mirror is the left boundary line, and the boundary line in the image captured by the camera on the right rearview mirror is the right boundary line. The field of view of the images captured by cameras of different models and cameras installed at different positions on the vehicle body is different.

[0076] After being able to accurately identify the left and right boundary lines in multiple consecutive frames of images, the environment information on both sides will be accurately judged. The order of judgment is not limited here, that is, the environment information on the left side of the left boundary line can be judged first, and then the environment information on the right side of the right boundary line can be judged; the environment information on the right side of the right boundary line can also be judged first, and then the environment information on the left side of the left boundary line can be judged; or, it can be judged at the same time.

[0077] In one or more embodiments of the present application, a main road identification solution is provided, and the identification process is as follows: When the road traffic direction is to keep to the right (and the target mobile tool complies with traffic regulations and drives on the right), if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates the presence of oncoming vehicles, and / or the environmental information on the right side of the right boundary line indicates the presence of vehicles traveling in the same direction, then it is determined that the target mobile tool is located on the main road; when the road traffic direction is to keep to the right (and the target mobile tool complies with traffic regulations and drives on the left), if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of oncoming vehicles, and / or the environmental information on the left side of the left boundary line indicates the presence of vehicles traveling in the same direction, then it is determined that the target mobile tool is located on the main road.

[0078] like Figure 3aIt shows the situation that the target vehicle is driving or stationary on the main road. Specifically, if the target vehicle is driving or stationary on the main road, the left boundary line and the right boundary line are the left and right boundary lines of the main road. The left lane of the left boundary line on the left side of the target vehicle is the opposite road, and the driving direction of other vehicles in the opposite road is opposite to the prescribed driving direction of the target vehicle. It can be known that the target vehicle is currently on the main road, or may be on the main road. The reverse driving vehicle mentioned here can be understood as identifying at least one vehicle in the environmental information, and the driving direction of the vehicle is opposite to the driving direction of the target vehicle. The right road of the right boundary line on the right side of the target vehicle is the auxiliary road, and the driving direction of other vehicles in the auxiliary road is the same as the prescribed driving direction of the target vehicle. It can be known that the target vehicle is currently on the main road, or may be on the main road. In addition, there may be vehicles such as motorcycles, as well as traffic objects such as bicycles and baby carriages in the auxiliary road. In other words, if the traffic object information (including traffic objects, pedestrians, pets, etc.) detected in the right lane of the second boundary can also be used as a basis for judging whether the lane where the target vehicle is currently located is an auxiliary road.

[0079] The prescribed driving direction here refers to the driving direction or the direction that the target vehicle is allowed to drive according to traffic rules on the road where the target vehicle is located (the current target vehicle may be stationary due to a malfunction or other reasons). The target vehicle can drive or stop on the current road, for example, if it is forced to stop due to a malfunction on the main road, it may stop temporarily on the auxiliary road.

[0080] By cleverly utilizing the different environmental information of the target vehicle's different boundary lines, it can be determined that the current target vehicle is located on the main road. There is no need to judge based on the connecting intersection between the main road and the auxiliary road, which can effectively improve the accuracy of whether the target vehicle is driving or stationary on the main road.

[0081] In one or more embodiments of the present application, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates the presence of a vehicle traveling in the opposite direction, and the environmental information on the right side of the right boundary line indicates the presence of a vehicle traveling in the same direction, then the target mobile tool is determined to be on the main road, including: if the acquired environmental information on the left side of the left boundary line includes a first vehicle, then the driving direction of the first vehicle is determined; if the driving direction of the first vehicle is opposite to the prescribed driving direction of the target mobile tool, then the first vehicle is determined to be a vehicle traveling in the opposite direction; and / or, if the acquired environmental information on the right side of the right boundary line includes a second vehicle, then the driving direction of the second vehicle is determined; if the driving direction of the second vehicle is the same as the prescribed driving direction of the target mobile tool, then the second vehicle is determined to be a vehicle traveling in the same direction; and it is determined that the target mobile tool is traveling or stationary on the main road.

[0082] When acquiring environmental information, the sensor may be able to acquire environmental information between the left boundary line and the right boundary line, and may also be able to acquire environmental information on the left side of the left boundary line and environmental information on the right side of the right boundary line. However, when determining the main and auxiliary roads, the environmental information between the left boundary line and the right boundary line is not needed. Only the environmental information on the left side of the left boundary line and the environmental information on the right side of the right boundary line is needed. Since the judgment criteria for environmental information at different locations are different, it is necessary to be able to accurately determine the positional relationship between each piece of environmental information and the corresponding boundary line.

[0083] When the environmental information on the left side of the left boundary line contains traffic object information, there may be some erroneous information. For example, the traffic object illegally enters the main road, and the signboard on the main road is mistakenly identified as a traffic object. In this case, the subsequent judgment action will be terminated. When the environmental information on the left side of the left boundary line contains a vehicle, it is necessary to further determine the driving direction of the first vehicle. The vehicle information mentioned here can be understood as the image information of a vehicle or the image information of multiple vehicles detected by the sensor. When the vehicle information of multiple vehicles is detected, one vehicle can be selected as the first vehicle and its driving direction can be further determined. If the driving direction of the first vehicle is opposite to the specified driving direction of the target moving tool (that is, the target vehicle), the first vehicle is determined to be a reverse driving vehicle, that is, the first vehicle is a reverse (some also called opposite) driving vehicle relative to the target vehicle. It can be seen that the road where the first vehicle is located is the opposite main road, then the road where the target vehicle is located is very likely to be the main road. At this time, if multiple reverse driving vehicles can be identified for a continuous period of time (that is, in a continuous multi-frame image), the recognition result can be directly output as being on the main road. If multiple vehicles traveling in the opposite direction are not identified within a continuous period of time, the right side judgment result of the right side boundary line can be combined for comprehensive identification. The environmental information judgment process of the right side boundary line is as follows.

[0084] When the environmental information on the right side of the right boundary line contains a second vehicle, it is necessary to further determine the driving direction of the second vehicle. When the driving direction judgment result is that the driving direction of the second vehicle is opposite to the specified driving direction of the target mobile tool, there may be some error information. For example, the right boundary line is recognized incorrectly, or there is a vehicle traveling in the opposite direction. In this case, the subsequent judgment action will be terminated. If the driving direction of the second vehicle is the same as the specified driving direction of the target mobile tool, the second vehicle is determined to be a vehicle traveling in the same direction. It can be seen that the road where the second vehicle is located is a secondary road in the same direction, then the road where the target vehicle is located is very likely to be the main road. At this time, if multiple vehicles in the same direction can be identified for a continuous period of time, the recognition result can be directly output as being on the main road. If multiple vehicles in the same direction are not identified for a continuous period of time, the left judgment result of the left side of the left boundary line mentioned above can be combined for comprehensive identification.

[0085] If the environmental information judgment result on the left side of the left boundary line indicates that there is a vehicle traveling in the opposite direction, and / or the environmental information judgment result on the right side of the right boundary line indicates that there is a vehicle traveling in the same direction, it means that the target vehicle is traveling on the main road or stationary. If multiple vehicles are not identified within a continuous period of time, if the environmental information judgment result on the left side of the left boundary line indicates that there is a vehicle traveling in the opposite direction, but the environmental information judgment result on the right side of the right boundary line is a traffic object, or the judgment result is a vehicle traveling in the opposite direction, then this situation has resulted in an incorrect judgment, and the subsequent judgment action will be terminated.

[0086] The target mobile vehicle can be in a moving state or a stationary state on a main road or a secondary road. The prescribed driving direction mentioned here refers to the driving direction of the target vehicle on the current road allowed by traffic regulations. The prescribed direction of the target vehicle can be determined in a variety of ways. If the target vehicle is in a moving or stationary state, the prescribed driving direction of the target vehicle can be determined based on the direction of the front of the vehicle. If the target vehicle is in a moving state, the prescribed driving direction of the target vehicle can be directly determined based on the forward gear position, the wheel rotation direction, or the vehicle speed direction.

[0087] Wherein, the specific implementation method of determining the driving direction of the first vehicle corresponding to the vehicle information is as follows: if the driving direction of the first vehicle is approaching the target mobile tool from the front of the target mobile tool, or moving away from the target mobile tool from the rear of the target mobile tool. And the relative speed between the first vehicle and the target mobile tool is greater than the target moving speed of the target mobile tool, then it is determined that the driving direction of the first vehicle is opposite to the prescribed driving direction of the target mobile tool. If the driving direction of the first vehicle is approaching the target mobile tool from the front of the target mobile tool, and the relative speed between the first vehicle and the target mobile tool is less than the target moving speed of the target mobile tool (for example, the target mobile tool is about to overtake the first vehicle), then it is determined that the driving direction of the first vehicle is the same as the prescribed driving direction of the target mobile tool. If the driving direction of the first vehicle is approaching the target mobile tool from the rear of the target mobile tool, and the relative speed between the first vehicle and the target mobile tool is less than the target moving speed of the target mobile tool (for example, the first vehicle is about to overtake the target mobile tool), then it is determined that the driving direction of the first vehicle is the same as the prescribed driving direction of the target mobile tool.

[0088] The specific implementation method of determining the driving direction of the second vehicle is as follows: if the driving direction of the second vehicle is approaching the target mobile tool from the front of the target mobile tool or moving away from the target mobile tool from the rear of the target mobile tool, and the relative speed between the second vehicle and the target mobile tool is less than the target moving speed of the target mobile tool, then it is determined that the driving direction of the second vehicle is the same as the prescribed driving direction of the target mobile tool; that is, the target vehicle is going to overtake the second vehicle. Alternatively, if the driving direction of the second vehicle is moving away from the target mobile tool from the front of the target mobile tool or moving away from the target mobile tool from the rear of the target mobile tool, and the relative speed between the second vehicle and the target mobile tool is less than the target moving speed of the target mobile tool, then it is determined that the driving direction of the second vehicle is the same as the prescribed driving direction of the target mobile tool, in which case the second vehicle is going to overtake the target vehicle.

[0089] Through the above embodiment, the environmental information on the left side of the left boundary line and / or the environmental information on the right side of the right boundary line are detected and judged. If multiple vehicles are not identified within a continuous period of time, when there is a first vehicle in the environmental information on the left side that has a driving direction opposite to the prescribed driving direction of the target vehicle, it can be known that the road on the left side of the left boundary line (that is, the left boundary line of the road where the target vehicle is currently located) is the opposite main road. In addition, there is a second vehicle in the environmental information on the right side of the right boundary line that has a driving direction that is the same as the prescribed driving direction of the target vehicle, and it can be known that the road on the right side of the right boundary line (that is, the right boundary line of the road where the target vehicle is currently located) is the auxiliary road. Therefore, it can be inferred that the road between the opposite main road and the auxiliary road can only be the main road. If multiple vehicles are identified within a continuous period of time, there are multiple first vehicles in the environmental information on the left side that have a driving direction opposite to the prescribed driving direction of the target vehicle, or if multiple vehicles are identified within a continuous period of time, there are multiple second vehicles in the environmental information on the right side of the right boundary line that have a driving direction that is the same as the prescribed driving direction of the target vehicle, and it can be inferred that the target vehicle is on the main road. By comprehensively utilizing the environmental information in the environment, it is possible to accurately determine whether the road where the target vehicle is currently located is a main road or an auxiliary road. Moreover, this judgment process can be continuous when the target vehicle is moving or stationary (this judgment can be performed multiple times until an accurate judgment result of whether it is on the main road or the secondary road is obtained). Unlike the intersection where only one judgment can be made based on the connection between the main road and the secondary road, the multiple recognition and judgment of this application can obviously effectively improve the recognition accuracy of the main and secondary roads.

[0090] In one or more embodiments of the present application, a secondary road identification scheme is also provided, and the identification process is as follows: when the road traffic direction is to drive on the right (and the target mobile tool drives on the right in compliance with traffic regulations), if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the same direction, and / or the environmental information on the right side of the right boundary line indicates the presence of traffic objects, then it is determined that the target mobile tool is on the secondary road. When the road traffic direction is to drive on the right (and the target mobile tool drives on the left in compliance with traffic regulations), if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the same direction, and / or the environmental information on the left side of the left boundary line indicates the presence of traffic objects, then it is determined that the target mobile tool is on the secondary road.

[0091] like Figure 3b It shows the situation that the target vehicle is driving or stationary on the auxiliary road. Specifically, if the target vehicle is driving or stationary on the auxiliary road, the left boundary line and the right boundary line are the left and right boundary lines of the auxiliary road. The left lane of the left boundary line on the left side of the target vehicle is the same direction lane, and the driving direction of other vehicles (including the second vehicle) in the same direction lane is the same as the specified driving direction of the target vehicle. The same direction driving vehicle mentioned here can be understood as the driving direction of the first vehicle obtained being the same as the driving direction of the target vehicle. The right side of the right boundary line on the right side of the target vehicle is the right side of the pedestrian road or green belt and other traffic objects. The environmental information contained on the right side of the right boundary line (that is, the right side) is the traffic object. In other words, after judging that the left side of the target vehicle is the same direction main road, and the right side is the road where the traffic object is located or the non-motor vehicle area where the traffic object is allowed to move, it can be judged that the road between the same direction main road and the non-motor vehicle lane (or non-motor vehicle activity area) can only be an auxiliary road.

[0092] If multiple vehicles are identified over a continuous period of time, the first vehicle on the left side of the left boundary line of the road where the target vehicle is located is traveling in the same direction as the target vehicle. Alternatively, if multiple vehicles are identified over a continuous period of time, when there is traffic object information on the right side of the right boundary line of the road where the target vehicle is located, it can be inferred that the target vehicle is on the auxiliary road. In this case, since the same and stable auxiliary road recognition result can be obtained on one side (left or right) over a continuous period of time, the recognition result on a single side can be used as the final recognition result of the auxiliary road.

[0093] By cleverly utilizing the different environmental information of the target vehicle's different boundary lines, it can be comprehensively judged that the current location of the target vehicle is a secondary road. There is no need to judge based on the connecting intersection between the main road and the secondary road, which can effectively improve the accuracy of whether the target vehicle is driving or stationary on the secondary road.

[0094] In one or more embodiments of the present application, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located is a vehicle traveling in the same direction, and the environmental information on the right side of the right boundary line is traffic object information, then it is determined that the target mobile tool is on the auxiliary road, including: if the acquired environmental information on the left side of the left boundary line indicates the presence of a first vehicle, then the driving direction of the first vehicle is determined; if the driving direction of the first vehicle is the same as the specified driving direction of the target mobile tool, then the first vehicle is determined to be a vehicle traveling in the same direction; and / or, if the acquired environmental information on the right side of the right boundary line contains a traffic object; then it is determined that the target mobile tool is on the auxiliary road.

[0095] In practical applications, when the environmental information on the left side of the left boundary line contains a traffic object, there may be some erroneous information. For example, the traffic object illegally enters the main road, and the signboard on the main road is mistakenly identified as a traffic object. In this case, the subsequent judgment action will be terminated. When the environmental information on the left side of the left boundary line contains a first vehicle, it is necessary to further determine the driving direction of the first vehicle. The vehicle mentioned here can be understood as the image information of a vehicle or multiple vehicles detected by the sensor. When multiple vehicles are detected, one vehicle can be selected as the first vehicle and its driving direction can be further judged. If the driving direction of the first vehicle is the same as the specified driving direction of the target mobile tool, it is determined that the first vehicle is a vehicle traveling in the same direction relative to the target vehicle. Therefore, it can be seen that the road where the first vehicle is located is the main road in the same direction. If multiple vehicles in the same direction can be identified for a continuous period of time, the recognition result can be directly output as the target vehicle on the auxiliary road. If multiple vehicles in the same direction are not identified for a continuous period of time, it can be comprehensively identified in combination with the right judgment result of the right side of the right boundary line below.

[0096] In the process of judging the right side environmental information of the right side boundary line, when the environmental information on the right side of the right side boundary line contains a traffic object, it can be known that the right side of the right side boundary line belongs to the activity area of ​​the traffic object. The current target vehicle may be on the auxiliary road. In this case, there is no need to judge the moving direction of the traffic object. If multiple traffic objects can be identified for a continuous period of time, the recognition result can be directly output as the target vehicle on the auxiliary road. If multiple traffic objects are not identified for a continuous period of time, a comprehensive recognition can be performed in combination with the left judgment result of the left side of the left boundary line above.

[0097] The specific implementation method of determining the driving direction of the first vehicle is as follows: if the driving direction of the first vehicle is approaching the target mobile tool from the front of the target mobile tool, and the relative speed between the first vehicle and the target mobile tool is less than the target moving speed of the target mobile tool (for example, the target mobile tool is about to overtake the first vehicle), then it is determined that the driving direction of the first vehicle is the same as the prescribed driving direction of the target mobile tool. If the driving direction of the first vehicle is approaching the target mobile tool from the rear of the target mobile tool, and the relative speed between the first vehicle and the target mobile tool is less than the target moving speed of the target mobile tool (for example, the first vehicle is about to overtake the target mobile tool), then it is determined that the driving direction of the first vehicle is the same as the prescribed driving direction of the target mobile tool.

[0098] When judging the auxiliary road, vehicles are not allowed to appear on the right side of the right boundary line, because the right side belongs to the non-motor vehicle activity area. Once a vehicle is identified, it may be an error (for example, a roadside billboard is mistakenly identified as a vehicle). There is no need to judge the movement or driving direction of traffic objects.

[0099] Through the above embodiment, the environmental information on the left side of the left boundary line and the environmental information on the right side of the right boundary line are comprehensively detected and judged at the same time. When the driving direction of the first vehicle in the environmental information on the left side is the same as the prescribed driving direction of the target vehicle, it can be known that the road on the left side of the left boundary line (that is, the left boundary line of the road where the target vehicle is currently located) is the main road in the same direction. In addition, there is a traffic object in the environmental information on the right side of the right boundary line, and it can be known that the area on the right side of the right boundary line (that is, the right boundary line of the road where the target vehicle is currently located) is the activity area of ​​the traffic object. Therefore, it can be inferred that the road between the main road in the same direction and the activity area of ​​the traffic object can only be an auxiliary road. If multiple vehicles are identified within a continuous period of time, there are multiple first vehicles in the environmental information on the left side whose driving directions are the same as the prescribed driving direction of the target vehicle, or if multiple vehicles are identified within a continuous period of time, there are multiple traffic objects in the environmental information on the right side of the right boundary line, and it can be inferred that the target vehicle is on the auxiliary road. By comprehensively utilizing the environmental information in the environment, it is possible to accurately determine whether the road where the target vehicle is currently located is a main road or an auxiliary road. Moreover, this judgment process can be continuous when the target vehicle is moving or stationary (this judgment can be performed multiple times until an accurate judgment result of whether it is on the main road or the secondary road is obtained). Unlike the intersection where only one judgment can be made based on the connection between the main road and the secondary road, the multiple recognition and judgment of this application can obviously effectively improve the recognition accuracy of the main and secondary roads.

[0100] In one or more embodiments of the present application, there are still some situations where it is impossible to use environmental information to accurately determine whether the target vehicle is on the main road or the secondary road. For example, there are no pedestrians or other non-motor vehicles on the road late at night, and there are no vehicles or traffic objects on remote roads. This will result in the inability to obtain effective environmental information. For example, due to the influence of light, the left boundary line and the right boundary line are not included or cannot be identified in the environmental information, which will directly lead to the inability to perform subsequent main and secondary road identification work. Therefore, in this case, SD map data can be combined to help realize the identification of main and secondary roads. Figure 4 A flowchart of another main and auxiliary road identification method provided in an embodiment of the present application. Figure 4 It can be seen that the specific steps include the following: Step 401: Obtain standard definition map data; wherein the standard definition map data includes: the number of main road lanes and the number of secondary road lanes; the environmental information also includes lane lines and / or lane widths. Step 402: If the environmental information does not contain vehicles and / or traffic objects, or the environmental information does not contain the boundary lines of the road, determine the number of perceived lanes on the road where the target mobile tool is located from the environmental information. Step 403: Match the number of perceived lanes with the number of main road lanes and the number of secondary road lanes corresponding to the location of the target mobile tool in the standard definition map, and determine whether the target mobile tool is located on the main road or the secondary road based on the matching results.

[0101] In practical applications, sensors can collect environmental information in real time. Environmental information also includes lane lines and lane widths. Lane lines can be identified based on images collected by sensors. Since the target vehicle often travels between two lane lines, the lane lines in the captured image are relatively clear, and such lane lines are relatively easy to identify. The lane width mentioned here can be estimated after image recognition. It can also be determined based on the road type. For example, the lane width of the main road is stipulated to be 3.5 meters.

[0102] like Figure 5 A schematic diagram of the number of lanes sensed provided by an embodiment of the present application. Figure 5 It can be seen that there is a main road with two lane lines and two boundary lines, and the target vehicle is driving in a lane on the main road. The target vehicle can collect the lane lines within the sensor's field of view through the sensor. There is a lane between two adjacent lane lines, or there is a lane between a boundary line and a lane line. Therefore, if the number of lane lines within the current field of view can be accurately identified, the number of lanes can be known. If the boundary lines cannot be identified, the number of lanes can be determined based on the lane lines alone. When all lane lines on the current road are fully identified, the number of perceived lanes = the number of lane lines + 1. Figure 5As shown in , there are two lane lines and three lanes. In this case, even if there is no way to accurately identify the road boundary line, the number of lanes on the road can be known.

[0103] After accurately identifying the number of perceived lanes N1 contained in the current road, the standard definition map data will be used to specifically identify whether the current road is a main road or a secondary road. In other words, when using the number of perceived lanes to judge the main and secondary roads, it is necessary to match the number of main road lanes and the number of secondary road lanes corresponding to the current section of the target vehicle in the standard definition map, and not to match with other sections to avoid matching errors. Generally speaking, the number of lanes on the main road will be more than the number of lanes on the secondary road. For example, if the main road has 3 lanes, the adjacent secondary road has 1 lane. Assume that the number of lanes on the main road recorded in the SD map data is N2 and the number of lanes on the secondary road is N3. Next, it is necessary to determine whether N1 is the same as N2 or N3. If the judgment result is N1=N2, it can be known that the current lane is the main road; if the judgment result is N1=N3, it can be known that the current lane is the secondary road.

[0104] Through the above embodiment, the SD map data is used in combination with the number of lanes sensed after sensor recognition to make a comparison, so as to determine the lane the target vehicle is currently in. This effectively solves the problem that in the process of lane recognition, when it is impossible to obtain vehicles, traffic objects in the environmental information, or unable to identify the boundary line, it can still accurately identify whether the target vehicle is currently located on a main road or a secondary road.

[0105] In one or more embodiments of the present application, the number of perceived lanes on the road where the target mobile tool is located is determined from environmental information, including: determining the number of lane lines of the current road section perceived from the environmental information, and the lane line distance between adjacent lane lines; determining the number of perceived lanes based on the number of lane lines, and the relationship between the distance between adjacent lane lines and a lane width threshold, wherein if the distance between the two lane lines on both sides of each perceived lane is greater than or equal to the lane width threshold.

[0106] In practical applications, the number of lane lines on the road where the target vehicle is currently located can be sensed from environmental information, as well as the lane line distance between two adjacent lane lines (that is, the lane width). The method described above can be used to calculate the number of perceived lanes based on the number of lane lines. However, in order to avoid errors, the relationship between the lane line distance and the lane width threshold can also be considered comprehensively. Generally speaking, when the lane line distance is significantly smaller than the lane width threshold, the number of perceived lane lines is wrong, and the lane lines need to be deleted and the lanes need to be merged to finally obtain the correct number of perceived lanes.

[0107] Of course, corrections can also be made during the movement of the target vehicle. For example, the number of perceived lanes of the road where the target moving tool is currently located is determined based on the number of lane lines, including: determining the lane width of each identified lane; if at least one lane width is identified to be less than a width threshold, the lane less than the width threshold is merged with the adjacent lane, and the number of perceived lanes is corrected.

[0108] After identifying the lane lines in the manner described above, it is necessary to determine whether the recognition result is correct. This is because visual sensors are easily affected by light, resulting in recognition errors, such as mistakenly identifying road surface reflections as lane lines. Since there are more recognized lane lines than actual lane lines, the lane width to which the wrong lane lines are added is directly less than the width threshold (the width threshold determined based on the road type). The addition of one lane line causes the number of lanes calculated later to be one more than the actual number of lanes. Therefore, the number of lanes obtained by subtracting 1 from the original number of perceived lanes is used as the final number of perceived lanes, and then the corrected number of perceived lanes is compared with the number of lanes on the main road and the number of lanes on the auxiliary road.

[0109] The lane width mentioned here can be determined based on image recognition provided by the sensor. For example, the lane width between two lane lines can be calculated using deep learning technology, or the lane width between two lane lines can be measured using AR technology.

[0110] Of course, there is another possibility that the width of the identified lane is significantly greater than the width threshold. If at least one lane width is greater than the width threshold, a lane line may be missed. It is necessary to reuse the sensor to collect images and identify the lane lines in the image.

[0111] If the widths of all lanes are similar to the width threshold, it can be seen that the current number of perceived lanes is accurate and can be directly used for subsequent lane number comparisons.

[0112] Through the above embodiment, after the lane lines are identified and the number of corresponding identified lane lines is calculated, in order to ensure the accuracy of the number of identified lane lines, the lane width is used for verification, so as to ensure that the subsequent identification results of the vehicle on the main and auxiliary roads are accurate.

[0113] As in step 403, the number of sensed lanes is matched with the number of main road lanes and the number of auxiliary road lanes corresponding to the location of the target mobile tool in the standard definition map, and it is determined whether the target mobile tool is located on the main road or the auxiliary road based on the matching result, including: matching the number of sensed lanes with the number of main road lanes and the number of auxiliary road lanes, if the matching result is that the number of sensed lanes is the same as the number of main road lanes, then it is determined that the target mobile tool is located on the main road; if the matching result is that the number of sensed lanes is the same as the number of auxiliary road lanes, then it is determined that the target mobile tool is located on the auxiliary road.

[0114] As mentioned above, after obtaining the accurate number of perceived lanes or the corrected number of perceived lanes, the number of perceived lanes N1 and the number of main road lanes N2, and the number of perceived lanes N1 and the number of auxiliary road lanes N3 will be compared. In actual applications, there may be a situation where N1 is not equal to N2, and N1 is not equal to N3. This situation is the case of a recognition error in a certain link. In this case, the main and auxiliary road recognition will be abandoned and the environmental information recognition will be obtained again.

[0115] By comparing the number of lanes, it is possible to accurately identify whether the target vehicle is on the main road or the secondary road even when the environmental information is incomplete or the boundary line recognition is inaccurate, and provide the accuracy of identifying the position of the target vehicle on the main and secondary roads.

[0116] In one or more embodiments of the present application, the environmental information includes: at least one of a curbstone, a curb, a guardrail, a green belt, a double yellow line, and a lane line. Determining whether the environmental information contains boundary lines on both sides of the road where the target moving tool is located includes: based on the environmental information, at least one of the curbstones, curbstones, guardrails, green belts, and double yellow lines respectively included on both sides of the identified target moving tool is used as an alternative boundary line; if multiple curbstones, guardrails, and double yellow lines are identified on both sides in multiple consecutive frames, the alternative boundary line located on the left side of the road closest to the target moving tool is used as the left boundary line, and the alternative boundary line located on the right side of the road closest to the target moving tool is used as the right boundary line.

[0117] like Figure 6a This is a schematic diagram of a boundary line for illustrating an embodiment of the present application. Figure 6a It can be seen that the boundary lines of different roads are different, and the boundary lines of different locations on the same road are different. In this application scheme, the identification of boundary lines is crucial. After the sensor provides environmental information, assuming that the environmental information is information in image format, the field of view of the sensor determines the size of the image area captured (of course, the field of view here is only for example, and the time field of view is determined by the sensor installation position and the sensor's own capabilities). To identify what is in the image, including: curbstones, curbs, guardrails, green belts and double yellow lines, etc., of course, it is also necessary to simultaneously identify the vehicles, traffic objects, lane lines, etc.

[0118] Figure 6aIn the road shown, two main roads in different directions are separated by double yellow lines. Between the main road and the secondary road, some sections are separated by green belts, and some are separated by guardrails. Here, image recognition is required to distinguish which content in the image is prohibited by traffic rules for vehicles to cross, and which content is not allowed for vehicles to cross. These prohibited and uncrossable contents are used as candidate boundary lines.

[0119] When the sensor has a good field of view, it can not only capture the environment in front of the vehicle, but also the boundary information of the opposite lane. At this time, it is necessary to identify the boundary line of the road that belongs to you. Figure 6b This is a schematic diagram of another boundary line recognition illustrated in the embodiment of the present application. Figure 6b As can be seen in the image captured by the sensor, on the left side, there are not only the double yellow lines of the target vehicle’s own lane, the right boundary line (the guardrail on the right), but also the green belt on the opposite main road ( Figure 6b The first boundary line in the middle) and the curb of the auxiliary road in the same direction ( Figure 6b In the case where the double yellow line and the green belt on the opposite main road appear on the left side of the target vehicle at the same time, it is necessary to determine the distance between the double yellow line and the green belt on the opposite main road and the target vehicle. Figure 6b It can be seen from the figure that the double yellow line is closer to the target vehicle than the guardrail of the opposite main road. Therefore, the double yellow line is marked as the left boundary line of the road where the target vehicle is located. Similarly, the guardrail and the curb appear in the field of view of the right side of the target vehicle at the same time. It is necessary to judge the distance relationship between the guardrail and the curb from the target vehicle respectively. Figure 6b As can be seen from the figure, the guardrail is closer to the target vehicle than the curb, so the guardrail is marked as the right boundary line of the road where the target vehicle is located.

[0120] Through the above solution, the boundary line of the road where the target vehicle is located can be found quickly and accurately in a complex environment, and a more accurate recognition result can be obtained.

[0121] In one or more embodiments of the present application, determining that the target mobile tool is located in front of a main road or a secondary road also includes: obtaining standard definition map data; determining whether there are other roads in the standard definition map data that are parallel to and adjacent to the road where the target mobile tool is located; if so, triggering an identification instruction for the road where the target mobile tool is located as a main road or a secondary road.

[0122] In actual applications, the main and auxiliary road identification of the road where the target vehicle is located will be initiated only when certain conditions are met. Specifically, after the SD map data is obtained, a road link identifier will be bound to the target vehicle. For example, when link1 is bound to the target vehicle, it means that the target vehicle is on the main road; when link2 is bound to the target vehicle, it means that the target vehicle is on the auxiliary road. However, due to the poor accuracy of SD map data, the binding status at this time is inaccurate, and further main and auxiliary road identification is required. After knowing the target lane link bound to the target vehicle, look for the positional relationship between the roads corresponding to other links in the SD map data and the target lane. If it is a parallel relationship, it means that there is a lane parallel to the target lane in the map, and the two lanes may be in a main and auxiliary road relationship.

[0123] If no other roads parallel to the target road are found, there is no need to identify the main and auxiliary roads. Of course, as shown in the figure, some SD map data can contain main and auxiliary road information, and the main and auxiliary road marks in the SD navigation map data can also be used as instructions to trigger the identification of the target mobile tool on the main road or auxiliary road. Alternatively, the connecting intersection between the main road and the auxiliary road is detected from the environmental information.

[0124] Through the above solution, the main and auxiliary roads can be identified in time when appropriate, and under normal circumstances (for example, there is no auxiliary road, or the main and auxiliary roads have been accurately identified), the main and auxiliary roads do not need to be identified again, thereby improving the recognition efficiency.

[0125] In one or more embodiments of the present application, after determining that the target mobile tool is located on a main road or a secondary road, it also includes: determining whether the identification result of the road where the target mobile tool is located is the same road as the road displayed in the navigation map; if it is not the same road, modifying the road display of the target mobile tool in the navigation map.

[0126] In actual applications, after accurately identifying the lane where the target vehicle is located, the display in the current navigation map is corrected according to the identification result. Specifically, if the identification result of the main and auxiliary roads of the target vehicle is consistent with the road link mark of the target road bound to the target vehicle, there is no need to correct the road display in the navigation map. If the identification result of the main and auxiliary roads of the target vehicle is inconsistent with the road link mark of the target road bound to the target vehicle, it is necessary to correct the road display in the navigation map, that is, to correct it to the identification result.

[0127] Through the above scheme, the lane position of the target vehicle in the main and auxiliary road environment can be accurately identified, effectively making up for the defect of poor accuracy of SD map data. The navigation map based on SD map data is corrected using the main and auxiliary road recognition results, so as to obtain a more accurate navigation effect.

[0128] Furthermore, if it is not the same road, a prompt message for re-planning the navigation route is sent to the user, and the navigation route in the navigation map is re-planned based on the modified road display.

[0129] Through the above embodiments, it is recognized that the road where the target mobile tool is located is different from the road displayed in the navigation map, and the road in the navigation map is corrected. Further, a prompt message (voice or text prompt message) can be sent to the user to remind the user that the navigation needs to be replanned. It is convenient for the user to understand the current navigation status in time and correct the navigation route in time.

[0130] The embodiment of the present application proposes a main and auxiliary road identification system, which can be arranged on an on-board electronic device, or can be integrated with the on-board electronic device and a server (including a cloud server and a local server), and can also be arranged on a user's mobile terminal. The main and auxiliary road identification system includes a processor and a memory, and the memory stores a computer program. When the computer program is executed by the processor, the main and auxiliary road identification system performs the following process: obtaining environmental information collected by a sensor; the environmental information includes: at least one of vehicle information, traffic object information and environmental information; according to the environmental information, identifying the left boundary line and the right boundary line on both sides of the road where the target mobile tool is located; wherein the target mobile tool drives on the right side where the right boundary line is located when driving; based on the environmental information on the left side of the left boundary line and / or the environmental information on the right side of the right boundary line, determining whether the target mobile tool is located on the main road or the auxiliary road.

[0131] The sensors mentioned here can be various sensors that can collect environmental information, such as visual sensors, laser sensors, etc. The environmental information mentioned here includes various information such as vehicles (such as fuel vehicles, new energy vehicles), traffic objects (such as bicycles, pedestrians, wheelchairs, pets, etc.), boundary lines, lane lines, etc.

[0132] It should be noted that in different countries or regions, due to different traffic rules, the vehicle movement methods are also different. Simply put, traffic rules can be divided into left-hand driving rules and right-hand driving rules.

[0133] In the subsequent embodiments, unless otherwise specified, the traffic rule of driving on the right will be taken as an example for explanation.

[0134] When a vehicle is driving in a main and auxiliary road environment, it can be driving on the auxiliary road or on the main road. Therefore, when a vehicle is driving on the right side of the main road, the left boundary line is the left boundary line of the main road, and can also be considered as the dividing line or guardrail between the opposite lane. The right boundary line is the right boundary line of the main road, and can also be considered as the dividing line or guardrail between the auxiliary road. Similarly, when a vehicle is driving on the right side of the auxiliary road, the left boundary line is the left boundary line of the auxiliary road, and can also be considered as the dividing line or guardrail between the main road. The right boundary line is the right boundary line of the auxiliary road, and can also be considered as the dividing line, curb, etc. of the traffic object road or pedestrian path.

[0135] Through the above solution, it is not necessary to distinguish the road link that the vehicle enters at the intersection of the main road and the auxiliary road. Instead, after the vehicle completely enters the main road or the auxiliary road, it is possible to determine the road the vehicle is currently on and whether the road the vehicle is currently on is consistent with the navigation route. This judgment method does not rely on the intersection of the main road and the auxiliary road, nor does it rely entirely on the vehicle's own positioning. Instead, it can effectively improve the accuracy of judging whether the vehicle is on the main road or the auxiliary road by identifying the boundary line and detecting and identifying the environmental information around the boundary line.

[0136] The specific implementation process and implementation method of the main and auxiliary road identification system can be found in the above-mentioned main and auxiliary road identification method related embodiments, which will not be repeated here.

[0137] To facilitate understanding, the implementation scheme of the present application will be described below through specific embodiments.

[0138] like Figure 7a The following is a schematic diagram of a main and auxiliary road identification system for illustrating an embodiment of the present application. Figure 7a It can be seen that when the target vehicle 71 starts navigation and drives, the SD map data will be loaded from the cloud server 72 in real time. In the SD map data, each line represents a road, each road has a unique link identifier, and each road contains at least one lane. During the driving process, the target vehicle will bind a line link in real time based on the navigation route and the current position of the target vehicle, indicating that the target vehicle is now driving on this road. There is a type field on the link here to indicate the type of road section (for example, highway, expressway, main road, and auxiliary road). Further, other road links parallel to the bound road link near the target vehicle are scanned from the SD map data. If any of the other road link types are auxiliary roads, it is recognized that this is a main and auxiliary road scene. That is, the target vehicle can drive on both the main road and the auxiliary road. In this scenario, the following strategy is enabled to comprehensively determine whether the target vehicle is driving on the main road or the auxiliary road at this time.

[0139] After collecting environmental information using sensors, the surrounding environment is perceived after being processed by the perception model. Perceived surrounding vehicles (vehicles in the same direction as the target vehicle, vehicles in the opposite direction), pedestrians, bicycles, lane lines (dashed lines, solid lines, etc.), curbs, guardrails, double yellow lines, etc. First, it is necessary to identify the left and right boundaries of the current road. This boundary may be a double yellow line, curb, guardrail, etc. The specific method for determining the boundary is as follows: extract the double yellow line (that is, the center line of the two-way lane), curb and the lower edge line of the guardrail in the current frame. The left and right lines closest to the target vehicle are the current left and right boundary lines. When the left and right boundaries can be identified in multiple frames of images continuously and stably, the position of the boundary line can be determined.

[0140] like Figure 7b A schematic diagram of a main and auxiliary road identification process provided in an embodiment of the present application. Figure 7b As can be seen in the figure, after obtaining the environmental information, the environmental information of the left and right boundary lines is recognized respectively. If there is a traffic object on the left side (corresponding to the left side in the previous text) of the left boundary line (corresponding to the left side in the previous text) for a period of time, it may be recognized incorrectly and output error feedback information. If there is an oncoming vehicle on the right side (corresponding to the right side in the previous text) of the right boundary line (corresponding to the right side in the previous text) for a period of time, it may be recognized incorrectly and output error feedback information.

[0141] If there are multiple vehicles going in the same direction on the left side of the left boundary line for a period of time, and there are traffic objects on the right side of the right boundary line, it means that the target vehicle is currently on the auxiliary road. If there are multiple vehicles going in the opposite direction on the left side of the left boundary line for a period of time, and there are multiple vehicles going in the same direction on the right side of the right boundary line for a period of time, it means that the target vehicle is currently on the main road.

[0142] If there are multiple vehicles going in the same direction on the left side of the left boundary line within a period of time, and there are also vehicles going in the same direction on the right side of the right boundary line, this situation is considered to be an error and an error feedback message is output.

[0143] If there are multiple vehicles on the opposite side of the left boundary line within a period of time, and there are traffic objects on the right side of the right boundary line (because according to traffic rules, traffic objects should not appear on the side road), this situation is considered an error and error feedback information is output. Whether there are traffic objects on the right side of the right boundary line should be based on the traffic rules of the specified area. If the traffic rules allow, no error feedback information is output.

[0144] like Figure 7c Another main and auxiliary road identification process diagram provided in an embodiment of the present application. Figure 7cAs can be seen in the figure, after obtaining the environmental information, the left and right boundary lines are respectively recognized. If there are multiple traffic objects on the left side of the left boundary line within a period of time, it may be recognized incorrectly and output error feedback information. If there are multiple oncoming vehicles on the right side of the right boundary line within a period of time, it may be recognized incorrectly and output error feedback information.

[0145] In this embodiment, only one of the conditional judgment results can be used to determine whether the target vehicle is on the main or auxiliary road. If there are multiple vehicles in the same direction on the left side of the left boundary line within a period of time, the target vehicle is considered to be on the auxiliary road. Or, if there are multiple traffic objects on the right side of the right boundary line within a period of time, the target vehicle is considered to be currently on the auxiliary road.

[0146] Similarly, if there are multiple oncoming vehicles on the left side of the left boundary for a period of time, the target vehicle is considered to be on the main road. Or, if there are multiple vehicles on the right side of the right boundary for a period of time in the same direction, the target vehicle is considered to be on the main road.

[0147] It should be noted that users can choose to use Figure 7b The corresponding main and auxiliary road identification method is still adopted Figure 7c Corresponding main and auxiliary road identification methods. For example, if Figure 7c The recognition error rate of the scheme shown is high, so you can use Figure 7b If it is not high, you can continue to use Figure 7c The scheme shown.

[0148] In addition, in some cases, it is impossible to use environmental information to identify the main road or the auxiliary road. Other auxiliary means are needed to identify whether the target vehicle is on the main road or the auxiliary road.

[0149] For example, if in a certain scene (for example, a main or secondary road in the suburbs without street lights at midnight on a rainy day), the perception effect is poor and the left and right boundaries cannot be stably recognized. There are very few pedestrians, vehicles, and bicycles on the road, so it cannot be used. Figure 7b or Figure 7cThe scheme shown determines that the target vehicle is on the main road and the secondary road. At this time, the lane number attribute on each link in the SD map data can be used. In general, the number of lanes on the main road is definitely greater than the number of lanes on the secondary road. Therefore, the number of lanes sensed by the target vehicle on the current road section and the number of lanes on the main and secondary road links can be compared; for example, if two lane lines are sensed on the current road section (excluding lane lines equivalent to boundary lines, such as double yellow lines), it means that the number of lanes is normally 3. If the distance between two adjacent lane lines is less than 2 meters (false detection or traffic object lane, etc.), the two adjacent lane lines do not constitute a lane, and the number of sensed lanes is reduced by 1. Finally, the number of sensed lanes is compared with the number of lanes on the main and secondary road links. If the number of sensed lanes is consistent with the main road, it is determined to be the main road; if it is consistent with the secondary road, it is determined to be the secondary road.

[0150] After determining whether the current target vehicle is actually on the main road or the secondary road through the above method, it is necessary to determine whether the route is consistent with the route given by the navigation. If it is found that the navigation is displayed on the main road, but the target vehicle is actually on the secondary road, the link on the navigation is switched to the secondary road in time, and the navigation replans the route to be consistent with the actual driving road, so that the user can experience a better navigation experience.

[0151] The embodiment of the present application also provides an electronic device. The electronic device includes one or more processors, memory and / or hardware modules. The processor and memory can be integrated together, or they can be connected by a bus, a communication interface or other connection medium. The processor can be a CPU, a GPU, an FPGA, or a general-purpose processor, a digital signal processor, an application-specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, etc., and multiple processors can be the same type of processors or multiple different types of processors. The processor of the embodiment of the present application can implement or execute the methods, steps and logic block diagrams disclosed in the embodiment of the present application, which will not be repeated here. The steps of the method disclosed in conjunction with the embodiment of the present application can be directly embodied as a hardware processor execution, or a combination of hardware and software modules in the processor.

[0152] Figure 8 A schematic diagram of the structure of a vehicle provided in an embodiment of the present application is shown in FIG. Figure 8 As shown, the vehicle is equipped with on-board electronic equipment, and the on-board electronic equipment includes: a memory 801 and a processor 802.

[0153] The memory 801 is used to store computer programs and can be configured to store various other data to support operations on the vehicle-mounted electronic device. Examples of such data include instructions for any application or method used to operate on the vehicle-mounted electronic device, contact data, phone book data, messages, pictures, videos, etc.

[0154] Among them, the memory 801 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable programmable read only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0155] The processor 802 is coupled to the memory 801 and is used to execute the computer program in the memory 801 to implement or execute the methods, steps and logic block diagrams disclosed in the embodiments of the present application, which will not be described in detail here.

[0156] Accordingly, the present disclosure also provides a readable storage medium, in which a computer program is stored, and the computer program is used to implement the above method when executed by a processor. "Readable storage medium" can be any device that can contain, store, communicate, propagate or transmit a program for use with an instruction execution system, device or equipment or in combination with these instruction execution systems, devices or equipment. More specific examples of readable storage media include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and editable read-only memory (EPROM or flash memory), an optical fiber device, and a portable read-only memory (CDROM), etc.

[0157] The present disclosure also provides a computer program product. The method of the present disclosure can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer programs or instructions. When the computer program or instruction is loaded and executed, the process or function of the present disclosure is executed in whole or in part.

[0158] The computer program or instructions may be stored in a readable storage medium or transmitted from one readable storage medium to another readable storage medium, for example, the computer program or instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired or wireless means. The readable storage medium may be any available medium that can be accessed or a data storage device such as a server, data center, etc. that integrates one or more available media. The available medium may be a magnetic medium, such as a floppy disk, a hard disk, or a magnetic tape; it may also be an optical medium, such as a digital video disk; it may also be a semiconductor medium, such as a solid state drive. The computer readable storage medium may be a volatile or non-volatile storage medium, or may include both volatile and non-volatile types of storage media.

[0159] In addition, the system and method of the present application can be applied not only to Figure 8 The vehicle shown can also be used in autonomous driving scenarios and navigation scenarios.

[0160] like Fig. 9 A flow chart of an automatic driving method provided for an embodiment of the present application. The method is applied to an automatic mobile tool, and the method includes the following steps: Step 901: Acquire environmental information collected by sensors during the automatic movement of the automatic mobile tool; the environmental information includes: at least one of vehicles, traffic objects and boundary lines. Step 902: According to the environmental information, identify the boundary lines on both sides of the road where the target mobile tool is located. Step 903: Determine whether the target mobile tool is located on the main road or the secondary road based on the environmental information on the left side of the left boundary line and / or the environmental information on the right side of the right boundary line. Step 904: Control the driving road of the automatic mobile tool based on the recognition result that the target mobile tool is located on the main road or the secondary road.

[0161] like Fig.10 A flowchart of a navigation positioning method provided for an embodiment of the present application. The method is applied to a mobile terminal, and the method includes the following steps: Step 1001: Determine the current position of the mobile terminal in the navigation map. Step 1002: Obtain environmental information of the location of the mobile terminal; the environmental information includes: at least one of a vehicle, a traffic object, and a boundary line. Step 1003: According to the environmental information, identify the boundary lines on both sides of the location of the mobile terminal. Step 1004: Determine whether the target mobile tool is located on the main road or the secondary road based on the environmental information on the left side of the left boundary line and / or the environmental information on the right side of the right boundary line.

[0162] In the embodiment of the present application, the target mobile tool is traveling on a road, and the road conditions are complex and diverse. Some of them include main and auxiliary roads. In order to accurately identify whether the target mobile tool is traveling on the main road or the auxiliary road, a standard definition map can be obtained, as well as environmental information collected by sensors; the environmental information includes: at least one of vehicles, traffic objects, boundary lines and lane lines. Then, the environmental information is identified. If the boundary line is identified, the boundary line and other environmental information can be used to determine whether the target mobile tool is located on the main road or the auxiliary road. If the boundary line is not identified, the standard definition map and environmental information can be used to determine whether the target mobile tool is located on the main road or the auxiliary road. Through the above scheme, the dependence on the identification of the intersection connecting the main and auxiliary roads is eliminated, that is, even if the intersection of the main and auxiliary roads is not identified, by identifying the boundary lines on both sides of the road, the comprehensive use of environmental information and / or standard definition maps can accurately identify whether the target mobile tool is located on the main road or the auxiliary road.

[0163] Those skilled in the art will appreciate that the embodiments of the present disclosure may be provided as methods, systems, or computer program products. Therefore, the present disclosure may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present disclosure may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0164] The present disclosure is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0165] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0166] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0167] In the description of this specification, the description with reference to the terms "one embodiment / method", "some embodiments / methods", "example", "specific example", or "some examples" etc. means that the specific features, structures, or characteristics described in conjunction with the embodiment / method or example are included in at least one embodiment / method or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment / method or example. Moreover, the specific features, structures, or characteristics described may be combined in any one or more embodiments / methods or examples in a suitable manner. In addition, those skilled in the art may combine and combine different embodiments / methods or examples described in this specification and features of different embodiments / methods or examples, unless they are contradictory.

[0168] Those skilled in the art should understand that the above embodiments are only for the purpose of clearly illustrating the present disclosure, and are not intended to limit the scope of the present disclosure. For those skilled in the art, other changes or modifications may be made based on the above disclosure, and these changes or modifications are still within the scope of the present disclosure.

Claims

1. A method for identifying main and auxiliary roads, characterized in that: The method comprises: Acquire a standard definition map and surrounding environmental information collected by sensors; wherein the environmental information includes at least one of a vehicle, a traffic object, and a boundary line; Determining whether the environmental information includes boundary lines on both sides of the road where the target mobile tool is located and the vehicle; If the judgment result is that the environmental information contains the boundary line and the vehicle, using the environmental information to judge whether the target mobile tool is located on a main road or a secondary road; If the judgment result is that the environmental information does not contain the boundary line and / or the vehicle, the standard definition map and the environmental information are used to judge whether the target mobile tool is located on a main road or a secondary road.

2. The method according to claim 1, characterized in that The boundary lines on both sides of the road include a left boundary line and a right boundary line. If the judgment result is that the environmental information contains the boundary lines and the vehicle, using the environmental information to judge whether the target mobile tool is located on the main road or the auxiliary road includes: Based on the type of the environmental information on the left side of the left boundary line and / or the type of the environmental information on the right side of the right boundary line, it is determined that the target moving tool is located on a main road or a secondary road.

3. The method according to claim 2, characterized in that The determining that the target mobile tool is located on a main road or a secondary road based on the identified type of the environmental information on the left side of the left boundary line and / or the type of the environmental information on the right side of the right boundary line includes: When the road traffic direction is driving on the right, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates that there is a vehicle traveling in the opposite direction, and / or the environmental information on the right side of the right boundary line indicates that there is a vehicle traveling in the same direction, then it is determined that the target mobile tool is located on the main road; When the road travel direction is to keep to the left, if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the opposite direction, and / or the environmental information on the left side of the left boundary line indicates the presence of vehicles traveling in the same direction, then it is determined that the target mobile tool is located on the main road.

4. The method according to claim 2, characterized in that: The determining that the target mobile tool is located on a main road or a secondary road based on the identified type of the environmental information on the left side of the left boundary line and / or the type of the environmental information on the right side of the right boundary line includes: When the road driving direction is driving on the right, if the environmental information on the left side of the left boundary line of the road where the target mobile tool is located indicates that there are vehicles traveling in the same direction, and / or the environmental information on the right side of the right boundary line indicates that there are traffic objects, then it is determined that the target mobile tool is on the auxiliary road; When the road driving direction is to keep to the left, if the environmental information on the right side of the right boundary line of the road where the target mobile tool is located indicates the presence of vehicles traveling in the same direction, and / or the environmental information on the left side of the left boundary line indicates the presence of traffic objects, then it is determined that the target mobile tool is on the auxiliary road.

5. The method according to any one of claims 1 to 4, characterized in that The standard defined map data includes: the number of main road lanes and the number of auxiliary road lanes; the environmental information also includes lane lines and / or lane widths; If the result of the determination is that the environmental information does not include the boundary line and / or the vehicle, determining that the target mobile tool is located on a main road or a secondary road by using the standard definition map and the environmental information includes: If the environmental information does not include the vehicle and / or the traffic object, or the environmental information does not include a boundary line of the road, determining the number of perceived lanes on the road where the target mobile tool is located from the environmental information; The number of perceived lanes is matched respectively with the number of main road lanes and the number of auxiliary road lanes corresponding to the location of the target mobile tool in the standard definition map, and it is determined whether the target mobile tool is located on the main road or the auxiliary road based on the matching result.

6. The method according to claim 5, characterized in that The step of determining the number of perceived lanes on the road where the target mobile tool is located from the environmental information includes: Determining the number of lane lines of the current road section sensed from the environmental information and the lane line distances between adjacent lane lines; The number of sensed lanes is determined according to the number of lane lines and the relationship between the distance between adjacent lane lines and the lane width threshold, wherein if the distance between two lane lines on both sides of each sensed lane is greater than or equal to the lane width threshold.

7. The method according to claim 5, characterized in that The step of matching the number of perceived lanes with the number of main road lanes and the number of auxiliary road lanes corresponding to the location of the target mobile tool in the standard definition map, and determining that the target mobile tool is located on the main road or the auxiliary road according to the matching result, includes: Matching the number of perceived lanes with the number of lanes on the main road and the number of lanes on the auxiliary road respectively, and if the matching result is that the number of perceived lanes is the same as the number of lanes on the main road, determining that the target mobile tool is located on the main road; If the matching result is that the number of the sensed lanes is the same as the number of lanes on the auxiliary road, it is determined that the target mobile tool is located on the auxiliary road.

8. The method according to claim 2, characterized in that: The environmental information also includes: at least one of a curbstone, a curb, a guardrail, a green belt, a double yellow line, and a lane line; Determining whether the environmental information includes boundary lines on both sides of the road where the target mobile tool is located includes: Based on the environmental information, at least one of the curbstone, the curb, the guardrail, the green belt and the double yellow line respectively included on both sides of the identified target moving tool is used as a candidate boundary line; If the curbstone, the guardrail and the double yellow line are identified on both sides in multiple consecutive frames, the alternative boundary line located on the left side of the road and closest to the target moving tool will be used as the left boundary line, and the alternative boundary line located on the right side of the road and closest to the target moving tool will be used as the right boundary line.

9. The method according to any one of claims 1 to 4, characterized in that After obtaining the standard definition map, it also includes: Determining whether there are other roads in the standard definition map data that are parallel to and adjacent to the road where the target mobile tool is located; If so, an instruction to identify whether the road where the target mobile tool is located is a main road or a secondary road is triggered.

10. The method according to claim 9, characterized in that After determining that the target mobile tool is located on the main road or the auxiliary road, the method further includes: Determining whether the recognition result of the road where the target mobile tool is located is the same as the road displayed in the navigation map; If it is not the same road, the road display of the target moving tool in the navigation map is modified.

11. The method according to claim 10, characterized in that Also includes: If it is not the same road, a prompt message for re-planning the navigation route is sent to the user, and the navigation route in the navigation map is re-planned based on the modified road display.

12. A main and auxiliary road identification system, characterized in that: The system comprises a processor and a memory, wherein the memory stores a computer program. When the computer program is executed by the processor, the main and auxiliary road identification system performs the following process: Acquire a standard definition map and surrounding environmental information collected by sensors; wherein the environmental information includes at least one of a vehicle, a traffic object, and a boundary line; Determining whether the environmental information includes boundary lines on both sides of the road where the target mobile tool is located and the vehicle; If the judgment result includes the boundary line and the vehicle, using the environmental information to judge whether the target mobile tool is located on a main road or a secondary road; If the judgment result is that the boundary line and the vehicle are not included, the standard definition map and the environmental information are used to judge whether the target mobile tool is located on a main road or a secondary road.

13. A vehicle, characterized in that: include: An on-vehicle electronic device, wherein the on-vehicle electronic device is used to implement the method according to any one of claims 1 to 11.

14. A computer program product, comprising a computer program signal, wherein the computer program signal is used to implement at least the method according to any one of claims 1 to 11 when being executed by a processor.

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