Vehicle speed setting method and device and vehicle

Abstract

The invention relates to the field of vehicle control, in particular to a vehicle speed setting method and device and a vehicle. According to the method provided by the embodiment of the invention, the map speed limit and the speed limit identification detection result are integrated, so that the road speed limit can be clearer; secondly, the average speed of a target vehicle is detected, and actual traffic flow speed reference is provided for speed setting; in addition, the problem of inconsistent speed limit is solved, multi-source speed limit data are obtained, and different speed limit information can be comprehensively collected. And when the map speed limit does not accord with the recognized road section speed limit, the target driving speed is set according to a set rule by comprehensively analyzing the map speed limit, the speed limit detection result and the average speed. Therefore, the set speed of the vehicle can be intelligently and reasonably selected, the traffic rate is effectively prevented from being influenced by overspeed or unreasonable speed, and the driving safety and the road traffic efficiency are improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle control, and in particular, to a method and device for setting vehicle speed and a vehicle. Background Art

[0002] In the currently mass-produced intelligent driving high-speed pilot assist system solutions on the market, the main ways to set the speed of the vehicle are through the speed limit of the high-precision map and through the camera to identify the road speed limit signs. However, in some specific scenarios on the highway, such as the speed limit signs for highway construction, the replacement of old signs with new speed limit signs, and the inconsistency between the high-precision map speed limit of the ramp and the road speed limit identified by the camera, the system cannot intelligently and reasonably set the vehicle speed. This results in an obvious speed difference between the speed at which the vehicle travels according to the speed limit obtained from the high-precision map or road signs and other surrounding vehicles, and further leads to the vehicle speeding or seriously driving at a low speed. Summary of the Invention

[0003] In view of this, embodiments of the present invention provide a method and device for setting vehicle speed and a vehicle, so as to solve the problem that the speed limit of the high-precision map does not match the road speed limit identified by the camera, and it is impossible to intelligently and reasonably select the set speed of the vehicle, resulting in the vehicle speeding or affecting the traffic efficiency.

[0004] In a first aspect, an embodiment of the present invention provides a method for setting vehicle speed, the method including:

[0005] Obtain the map speed limit corresponding to the section where the vehicle is located, and detect the speed limit signs of the section to obtain a speed limit detection result;

[0006] Detect the average speed of the target vehicle of the vehicle in the section;

[0007] Analyze the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and set the target driving speed of the vehicle in the section according to the analysis result.

[0008] Further, before detecting the average speed of the target vehicle of the vehicle in the section, the method further includes:

[0009] Obtain at least one lane line in the section where the vehicle is located, and extract the lane line features of the lane line;

[0010] Match the lane line features with preset features to obtain a matching result, where the preset features are the features of the guide line;

[0011] Determine the section type of the section where the vehicle is located according to the matching result.

[0012] Further, detecting the average speed of the target vehicle of the vehicle on the road section includes:

[0013] Obtain the search range corresponding to the road section type of the road section where the vehicle is located;

[0014] Select target vehicles in the road section according to the search range, and detect the vehicle speed corresponding to the target vehicles;

[0015] Calculate the average speed of the target vehicle according to the vehicle speed of the target vehicle.

[0016] Further, analyzing the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and setting the target driving speed of the vehicle on the road section according to the analysis result includes:

[0017] If there is a road section speed limit shown in the speed limit detection result, analyze the relative magnitude relationship between the road section speed limit and the map speed limit;

[0018] Select a control speed from the road section speed limit and the map speed limit based on the relative magnitude relationship, and control the vehicle to travel at the control speed;

[0019] Compare the road section speed limit with the average speed of each target vehicle to obtain a first comparison result;

[0020] Update the control speed to the target driving speed based on the first comparison result.

[0021] Further, selecting a control speed from the road section speed limit and the map speed limit based on the relative magnitude relationship includes:

[0022] If the relative magnitude relationship is that the road section speed limit is less than the map speed limit, and the map speed limit is less than or equal to the first speed threshold, then use the map speed limit as the control speed, where the first speed threshold is calculated from the road section speed limit and a first coefficient greater than 1; or,

[0023] If the relative magnitude relationship is that the second speed threshold is less than or equal to the map speed limit, and the map speed limit is less than the road section speed limit, then use the road section speed limit as the control speed, where the second speed threshold is calculated from the road section speed limit and a second coefficient less than 1.

[0024] Further, updating the control speed to the target driving speed based on the first comparison result includes:

[0025] If the first comparison result is that the average speed is less than the speed limit of the road section, then use the speed limit of the road section as the target driving speed; or,

[0026] If the first comparison result is that the average speed of only one target vehicle is greater than the speed limit of the road section, then use the product of the speed limit of the road section and the third coefficient as the target driving speed; or,

[0027] If the first comparison result is that the average speeds of at least two target vehicles are greater than the speed limit of the road section, then use the average speed of the target vehicles as the target driving speed.

[0028] Further, analyzing the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and setting the target driving speed of the vehicle on the road section according to the analysis result includes:

[0029] If the speed limit detection result does not show the speed limit of the road section, then compare the map speed limit with the average speed of each target vehicle to obtain a second comparison result;

[0030] Set the target driving speed of the vehicle on the road section based on the second comparison result.

[0031] Further, setting the target driving speed of the vehicle on the road section based on the second comparison result includes:

[0032] If the second comparison result is that the average speed is less than the map speed limit, then use the map speed limit as the target driving speed; or,

[0033] If the second comparison result is that the average speed of only one target vehicle is greater than the map speed limit, then use the product of the map speed limit and the third coefficient as the target driving speed; or,

[0034] If the second comparison result is that the average speeds of at least two target vehicles are greater than the map speed limit, then use the average speed of the target vehicles as the target driving speed.

[0035] In a second aspect, an embodiment of the present invention provides a device for setting a vehicle speed, and the device includes:

[0036] An acquisition module, configured to acquire the map speed limit of a vehicle on a road section and identify the speed limit of the road section to obtain a speed limit detection result;

[0037] A detection module, configured to detect the average speed of a target vehicle of the vehicle on the road section;

[0038] An analysis module is configured to analyze the map speed limit, the speed limit detection result, and the average speed, obtain an analysis result, and set a target driving speed of the vehicle on the section according to the analysis result.

[0039] In a third aspect, an embodiment of the present invention provides a vehicle, including: a vehicle body and a controller. Control instructions are stored in the controller, and the controller executes the above method by executing the control instructions.

[0040] In a fourth aspect, an embodiment of the present invention provides a computer device, including: a memory and a processor. The memory and the processor are communicatively connected to each other. Computer instructions are stored in the memory, and the processor executes the above method according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0041] In a fifth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which computer instructions are stored, and the computer instructions are used to cause a computer to execute the above method according to the first aspect or any corresponding embodiment thereof.

[0042] The method provided by the embodiments of the present application first comprehensively combines the map speed limit and the speed limit sign detection result, which can make the road speed limit clearer; secondly, it detects the average speed of the target vehicle, providing a reference for the actual speed of the traffic flow for speed setting. In addition, in solving the problem of inconsistent speed limits, multi-source speed limit data is obtained, which can comprehensively collect different speed limit information. When the map speed limit does not match the speed limit of the identified section, by comprehensively analyzing the map speed limit, the speed limit detection result, and the average speed, the target driving speed is set according to the established rules. In this way, the set speed of the vehicle can be intelligently and reasonably selected, effectively avoiding speeding or affecting the traffic efficiency due to unreasonable speed, and improving driving safety and road traffic efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0044] Figure 1 is a flowchart of a method for setting a vehicle speed according to some embodiments of the present invention;

[0045] Figure 2 is a schematic diagram of a guide line according to some embodiments of the present invention;

[0046] Figure 3 is an analysis schematic diagram of a section type according to some embodiments of the present invention;

[0047] Figure 4 is a schematic flowchart of a method for setting vehicle speed according to some embodiments of the present invention;

[0048] Figure 5 is a schematic flowchart of a method for setting vehicle speed according to some embodiments of the present invention;

[0049] Figure 6 is a structural block diagram of a device for setting vehicle speed according to an embodiment of the present invention;

[0050] Figure 7 is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed implementation manners

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Apparently, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0052] According to an embodiment of the present invention, there is provided a method, a device, and a vehicle for setting vehicle speed. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0053] In this embodiment, a method for setting vehicle speed is provided, which can be used in the above-mentioned mobile terminals, such as mobile phones, tablets, etc. Figure 1 is a flowchart of a method for setting vehicle speed according to an embodiment of the present invention, as Figure 1 shown, and the process includes the following steps:

[0054] Step S101, obtain the map speed limit corresponding to the road section where the vehicle is located, and detect the speed limit signs on the road section to obtain a speed limit detection result.

[0055] In the embodiment of the present application, after the high-precision map system carried by the vehicle is started, it will immediately cooperate with the vehicle positioning module. The positioning module, relying on high-precision satellite positioning technology and inertial navigation system, can accurately and real-time measure the geographical location of the vehicle, including key information such as longitude, latitude, and altitude, and transmit it to the high-precision map system.

[0056] Meanwhile, the high-precision map system establishes a stable network connection with the cloud server. Based on the vehicle's current location information, it sends a specific request instruction to the cloud server, indicating that it needs to obtain the map speed limit data of the area where the vehicle is currently located. After receiving the request, the cloud server retrieves the road segment information corresponding to the vehicle's current location from the map database and extracts the corresponding speed limit values. Subsequently, these speed limit data are encapsulated and transmitted back to the high-precision map system on the vehicle side.

[0057] Step S102, detect the average speed of the target vehicle on the road segment.

[0058] In the embodiment of the present application, before detecting the average speed of the target vehicle on the road segment, the method further includes the following steps A1 - A3:

[0059] Step A1, obtain at least one lane line in the road segment where the vehicle is located and extract the lane line features.

[0060] Specifically, the vehicle continuously collects image information of the road segment where it is located through a camera installed at a specific position on the vehicle body (such as the front, rear, or side). These images cover the road scene within a certain range in front of or around the vehicle, including lane lines. After the image is collected, it is transmitted to the image processing unit. In the image processing unit, first, an algorithm based on instance segmentation is used to process the image. This algorithm classifies each pixel in the image and accurately identifies and segments the pixel points belonging to the lane lines, thereby obtaining at least one lane line in the road segment where the vehicle is located. For the segmented lane lines, their lane line features are further extracted. These features include, but are not limited to, the geometric shape features of the lane lines, such as length, curvature, straightness, etc.; position features, that is, the coordinate position of the lane lines in the image and their relative relationship with the vehicle's own position; and direction features, such as the inclination angle of the lane lines, whether they are horizontal, vertical, or have a certain slope, etc.

[0061] Step A2, match the lane line features with preset features to obtain a matching result, where the preset features are the features of the guide line.

[0062] Specifically, after obtaining the lane line features, they are matched with the preset guide line features. The preset features are a set of representative features obtained through analysis and summary based on a large number of guide line sample data. These features include unique shape features. The guide line usually presents a triangular or other specific irregular shape; position features such as Figure 2As shown, the guide line is generally set at specific locations such as near intersections and ramps; and the direction feature has a specific angular relationship with the normal driving direction of the vehicle. During the matching process, using the similarity algorithm, the extracted lane line features are compared with the preset guide line features one by one, and the similarity scores between them are calculated. The matching result is determined according to the similarity score and the preset threshold. If the similarity score is higher than the threshold, it is considered that the lane line feature matches the preset feature successfully, that is, the lane line is identified as a guide line; if the similarity score is lower than the threshold, the matching fails, indicating that the lane line does not conform to the characteristics of the guide line. The final obtained matching result will determine whether to return to the lane line detection based on instance segmentation or enter the position judgment link.

[0063] Step A3, determine the road section type where the vehicle is located according to the matching result.

[0064] Specifically, if the matching result is that the lane line features of each lane line do not match the preset features, determine that the road section type is the main road type;

[0065] It should be noted that after performing the matching operation on the lane line features and the preset guide line features, if the obtained matching result shows that the lane line features of each lane line do not match the preset features, it means that the currently detected lane lines do not have the typical features of the guide line. Based on the established judgment rules, in this case, it can be determined that the road section type where the vehicle is located is the main road type.

[0066] Or, if the matching result is that the lane line features of the lane line match the preset features, determine the lane line corresponding to the lane line features that match the preset features as the guide line. If the guide line is on the left side of the driving direction of the vehicle, determine that the road section type is the ramp type, or, if the guide line is on the right side of the driving direction of the vehicle, determine that the road section type is the main road type.

[0067] If the matching result shows that there are lane line features of the lane line that match the preset features, then the system will determine the lane lines corresponding to these lane line features that match the preset features as the guide lines. Next, the system will further judge the position of the guide line relative to the driving direction of the vehicle. If it is determined that this guide line is on the left side of the driving direction of the vehicle, according to the preset rules, at this time, it will be determined that the road section type where the vehicle is located is the ramp type; on the contrary, if the guide line is on the right side of the driving direction of the vehicle, the system will determine that the road section type is the main road type.

[0068] Finally, based on the judgment of the guide line, determine the position of the vehicle itself. If it is not determined as the guide line, it is considered that the position of the vehicle itself is on the main road; if it is confirmed as the guide line, if it is on the left side of the vehicle itself, it is considered as the ramp, and if it is on the right side of the vehicle itself, it is considered as the main road, and output this result. Then, asFigure 3 As shown, the result is matched with the high-precision map (EHP). If the EHP gives a ramp, and the camera gives ramp guiding lines and it is considered that the current position is a ramp, and the position of the vehicle itself is successfully matched, the ramp is output; if the EHP outputs the main road, the camera gives ramp guiding lines and it is considered that the current position is a ramp, but the position of the vehicle itself is not successfully matched, the process loops again; if the EHP outputs a ramp, the camera does not give ramp guiding lines and it is considered that the current position is the main road, and the position of the vehicle itself is not successfully matched, the process loops again; if the EHP outputs the main road, the camera does not give ramp guiding lines and it is considered that the current position is the main road, and the position of the vehicle itself is successfully matched, the main road is output.

[0069] In the embodiment of the present application, detecting the average speed of a target vehicle on a road section includes the following steps B1 - B3:

[0070] Step B1, obtaining the search range corresponding to the road section type of the road where the vehicle is located.

[0071] Specifically, the vehicle determines the road section type of the road where it is located through an in - built positioning system and by identifying and judging lane lines and guiding lines. If it is determined that the current road section is a high - speed main road (2 - 4 lanes), according to the set rules, its search range is determined to be Lane 1 on the left, Lane 2 on the left, and the lane where the vehicle itself is located. This is set based on the distribution characteristics and driving rules of vehicles on the main road. The principle of giving priority to the left can more comprehensively pay attention to the target vehicles affecting the vehicle's driving. If it is determined to be a ramp, considering the lane layout and vehicle driving direction characteristics of the ramp, the search range is set to the lane where the vehicle itself is located and the right - hand lane. This range selection can effectively cover the target vehicles on the ramp that affect the vehicle's driving.

[0072] Step B2, selecting target vehicles on the road section according to the search range and detecting the vehicle speeds corresponding to the target vehicles.

[0073] Specifically, after determining the search range, the vehicle uses the front - facing camera to identify the vehicles within this range. When on the main road, in the order of giving priority to the left, first judge the vehicles in Lane 1 on the left. If there are vehicles in this lane, target screening is carried out on them. The vehicles that do not pass the screening return to target sampling and are re - identified and selected; for the target vehicles that pass the screening, their driving speeds are obtained using sensors and dot - marking is carried out. After processing the vehicles in Lane 1 on the left, the vehicles in Lane 2 on the left and the lane where the vehicle itself is located are processed in the same way. When on the ramp, target screening is carried out on the vehicles in the lane where the vehicle itself is located and the right - hand lane. For the vehicles that do not pass the screening, they return to target sampling for re - identification, and for the vehicles that pass the screening, dot - marking is carried out. If necessary, the driving speeds of these vehicles are also obtained using sensors.

[0074] Understandably, if the road segment type is the main road type, the lane on the left side of the driving direction of the vehicle is taken as the first search range; it is detected whether there is a first candidate vehicle passing through in the first search range; if there is a first candidate vehicle in the first search range, the first candidate vehicle is taken as the target vehicle; or, if there is no first candidate vehicle in the first search range, the lane where the vehicle is located is taken as the second search range, and it is detected whether there is a second candidate vehicle in the second search range, and if there is a second candidate vehicle, the second candidate vehicle is taken as the target vehicle.

[0075] When the vehicle determines that the road segment type it is in is the main road type, it will determine the search range for the target vehicle and select the target vehicle according to a specific strategy. First, the lane on the left side of the vehicle's driving direction is set as the first search range, and then the vehicles within this range are detected to see if there is a first candidate vehicle that meets the passing conditions. Once a first candidate vehicle is found within the first search range, it is directly selected as the target vehicle. This reflects the principle of giving priority to paying attention to the vehicles in the left lane because when driving on the main road, the dynamics of the vehicles in the left lane have a greater impact on the driving of the vehicle itself. If there is no first candidate vehicle within the first search range, at this time, the lane where the vehicle itself is located is taken as the second search range, and it continues to be detected whether there is a second candidate vehicle within this range. If there is, the second candidate vehicle is determined as the target vehicle, so as to ensure that in the main road driving scenario, the target vehicle that has important reference significance for the driving of the vehicle itself can be comprehensively and orderly selected.

[0076] In addition, if the road segment type is the ramp type, the third search range is determined according to the number of lanes in the ramp; it is detected whether there is a third candidate vehicle passing through in the third search range; if there is a third candidate vehicle in the third search range, the third candidate vehicle is taken as the target vehicle.

[0077] When the vehicle determines that the current road segment type it is in is the ramp type, it will delimit the third search range according to the specific situation of the number of lanes in the ramp. Because different numbers of lanes in the ramp (such as single-lane or double-lane) will affect the driving environment of the vehicle and potential interference factors, it is necessary to reasonably determine the search range according to the actual number of lanes. After determining the third search range, the vehicle detects the vehicles within this range to see if there is a third candidate vehicle that meets the passing conditions. Once a third candidate vehicle is found within the third search range, it will be selected as the target vehicle. This process reflects that in the ramp driving scenario, the vehicle determines the search range and selects the target vehicle in a targeted manner according to its own special road environment, so as to better adapt to the driving characteristics of the ramp and provide a reference basis for subsequent driving decisions.

[0078] Step B3: Calculate the average speed of the target vehicle based on the vehicle speed of the target vehicle.

[0079] Specifically, with the help of various sensors equipped on the vehicle, such as radar, cameras, etc., accurately identify the target vehicle. After the identification is completed, obtain the driving speeds of these target vehicles, and record the speed values of each target vehicle. Add up all the recorded speed values of the target vehicles to get the total speed. Then count the number of target vehicles, and divide the total speed by the number of target vehicles. The result obtained is the average speed of the current batch of target vehicles. Output the calculated average speed, and this output can be displayed on the vehicle's dashboard or transmitted to the relevant control system of the vehicle. At the same time, save this average speed as the "average speed output at the previous dotting" for the next calculation.

[0080] When 5 seconds have passed since the last calculation, start the sensor again to re-identify the target vehicle. After identifying the target vehicle, obtain their driving speeds and record these new speed values. Add the "average speed output at the previous dotting" saved last time to all the newly recorded speed values of the target vehicles to get a new total speed. Count the number of newly identified target vehicles this time, and then add 1 (representing this one data of the previous average speed), and divide the new total speed by this total number to obtain a new average speed. Output the newly calculated average speed in the same way as the first calculation. Then, overwrite the previously saved "average speed output at the previous dotting" with this new average speed to prepare for the calculation after the next 5 seconds.

[0081] By continuously repeating the operations in the calculation loop and taking the previous average speed into account each time, the calculated average speed can be made closer to the current traffic flow speed.

[0082] In addition, after selecting the target vehicle, the sensor obtains the driving speeds of these target vehicles and simultaneously measures the distance between the target vehicle and the vehicle itself to calculate the relative speed. Then, assign weights according to the distance between the target vehicle and the vehicle itself and the stability of the relative speed. Higher weights are assigned to target vehicles that are closer to the vehicle itself and have stable relative speeds, and lower weights are assigned otherwise. After that, add up the speeds of each target vehicle multiplied by the corresponding weights and divide by the total weight to calculate the target average value, which can more accurately reflect the traffic flow speed that has a direct impact on the vehicle's driving.

[0083] As an example, assume that the vehicle is traveling on a certain section of the road, and three target vehicles in front are selected and marked as target vehicles A, B, and C respectively. The sensor obtains that the traveling speed of target vehicle A is 80 km / h, the distance from the vehicle is 50 meters, and the relative speed is stable at 10 km / h; the traveling speed of target vehicle B is 75 km / h, the distance from the vehicle is 80 meters, the relative speed has certain fluctuations and is stable at about 5 km / h; the traveling speed of target vehicle C is 85 km / h, the distance from the vehicle is 120 meters, the relative speed changes greatly, and the average relative speed is 15 km / h.

[0084] Weights are assigned according to the distance and the stability of the relative speed: Since target vehicle A is relatively close to the vehicle and the relative speed is stable, the weight assigned is 0.5. Target vehicle B is at a moderate distance and the relative speed has a certain degree of stability, so the weight assigned is 0.3. Target vehicle C is relatively far away and the relative speed changes greatly, so the weight assigned is 0.2.

[0085] Calculate the target average value: (80×0.5 + 75×0.3 + 85×0.2)÷(0.5 + 0.3 + 0.2) = 79.5. Therefore, the calculated target average value is 79.5 km / h, which can more accurately reflect the traffic flow speed that has a direct impact on the vehicle's driving, so that the vehicle can set its own driving speed more reasonably.

[0086] Step S103: Analyze the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and set the target driving speed of the vehicle on the section according to the analysis result.

[0087] In the embodiment of the present application, the map speed limit, the speed limit detection result, and the average speed are analyzed to obtain an analysis result, and the target driving speed of the vehicle on the section is set according to the analysis result. As Figure 4 shown, it includes the following steps C1 - C4:

[0088] Step C1: If the speed limit detection result shows that there is a section speed limit, analyze the relative magnitude relationship between the section speed limit and the map speed limit.

[0089] Specifically, if the speed limit detection result indicates that there is a section speed limit, first, it is necessary to obtain the section speed limit recognized by the camera and the map speed limit obtained from the high-precision map. These two speed limit values are compared and analyzed according to a predetermined comparison method (such as comparing the difference, comparing the magnitudes, etc.) to clarify the relative magnitude relationship between the section speed limit and the map speed limit.

[0090] Step C2: Select the control speed from the section speed limit and the map speed limit based on the relative magnitude relationship, and control the vehicle to travel at the control speed.

[0091] In the embodiment of the present application, selecting a control speed from the section speed limit and the map speed limit based on the relative size relationship includes: if the relative size relationship is that the section speed limit is less than the map speed limit, and the map speed limit is less than or equal to the first speed threshold, the map speed limit is used as the control speed. The first speed threshold is calculated from the section speed limit and the first coefficient, and the first coefficient is greater than 1.

[0092] It should be noted that when it is obtained through comparative analysis that the section speed limit is less than the map speed limit, and the map speed limit is less than or equal to the first speed threshold calculated from the section speed limit and the first coefficient (the coefficient can be 1.1), in order to set the vehicle speed more reasonably under the condition of conforming to certain speed limit rules, the system will determine the map speed limit as the control speed. This not only refers to the section speed limit recognized by the actual road camera, but also combines the map speed limit information provided by the high-precision map. Under the condition of meeting the requirement of not exceeding the first speed threshold calculated based on the section speed limit, using the map speed limit as the control speed to guide the vehicle to travel helps to balance the actual speed limit requirement of the road and the speed setting in the overall traffic environment.

[0093] In addition, the first coefficient can be set in the following way: First, determine the initial value of the first coefficient according to the design standard and type of the road. For example, for a highway with a relatively high design speed, a relatively large initial value can be given; while for a rural road with a relatively low design speed, a smaller initial value is given. Second, adjust the initial value using the real-time traffic flow data. If a certain section is severely congested during the peak period and the vehicle driving speed is slow, in order to ensure driving safety and traffic flow, the first coefficient should be appropriately reduced; if the traffic flow is small and the traffic is smooth during the non-peak period, the first coefficient is appropriately increased. Then, adjust it using the weather and road condition information. Under bad weather conditions such as rain, snow, and fog, or when there are many complex road conditions such as sharp turns and steep slopes on the road, reduce the first coefficient to limit the vehicle speed and enhance safety; when the weather is good and the road condition is flat, the first coefficient can be appropriately increased. Finally, comprehensively consider all the above adjustment factors, combine relevant data such as the type and performance of the vehicle, and fine-tune the first coefficient to output the finally determined first coefficient for calculating the first speed threshold.

[0094] Or, if the relative size relationship is that the second speed threshold is less than or equal to the map speed limit, and the map speed limit is less than the section speed limit, the section speed limit is used as the control speed. The second speed threshold is calculated from the section speed limit and the second coefficient, and the second coefficient is less than 1.

[0095] It should be noted that after analyzing the relative magnitude relationship between the speed limit of a road section and the speed limit on the map, if it is found that the second speed threshold is less than or equal to the speed limit on the map, and at the same time the speed limit on the map is less than the speed limit of the road section (where the second speed threshold is calculated from the speed limit of the road section and a second coefficient less than 1), in order to ensure that the vehicle driving speed can take into account both map information and meet the speed limit requirements of the actual road, the system will determine the speed limit of the road section as the control speed. This decision comprehensively considers the theoretical speed limit (the second speed threshold) adjusted by the coefficient, the speed limit on the map, and the speed limit of the road section recognized by the camera on the actual road. Under this specific speed limit relationship, choosing the speed limit of the road section as the control speed can enable the vehicle to better adapt to the actual road conditions.

[0096] In addition, the second coefficient can be set in the following way: First, determine the initial value of the second coefficient according to the environmental conditions around the road. If there are areas such as schools, hospitals, and residential areas with strict speed limit requirements around the road, set a relatively small initial value; if it is an empty industrial area or a rural road, a relatively large initial value can be set. Second, adjust the initial value using the special regulations and policies of the traffic management department. For example, if there are special speed limit regulations on certain road sections, or traffic control is implemented during specific time periods, adjust the second coefficient accordingly according to these regulations and policies. Then, adjust it using the historical traffic accident data of this road section. If there have been many accidents caused by excessive speed in a certain road section in the past, reduce the second coefficient to more strictly limit the speed; if the number of accidents is small and has little to do with the speed, the second coefficient can be appropriately increased. Finally, comprehensively consider factors such as the degree of improvement of the road traffic facilities and the average driving speed of the vehicles, and perform fine-tuning on the second coefficient and then output the final second coefficient for calculating the second speed threshold.

[0097] Step C3: Compare the speed limit of the road section with the average speed of each target vehicle to obtain the first comparison result.

[0098] Specifically, compare the speed limit value of the road section with the average speed calculated for each target vehicle in turn. For example, if the current speed limit of the road section is 60 km / h and there are 3 target vehicles with average speeds of 55 km / h, 62 km / h, and 65 km / h respectively, then the system will compare 60 km / h with these three speed values respectively. Through such comparison operations, the first comparison result reflecting the relationship between the two is finally obtained. This result is situations such as the average speed being less than the speed limit of the road section, the average speed being greater than the speed limit of the road section, etc., providing a key basis for subsequent decisions.

[0099] Step C4: Update the control speed to the target driving speed based on the first comparison result.

[0100] Specifically, updating the control speed to the target driving speed based on the first comparison result includes: if the first comparison result is that the average speed is less than the section speed limit, then taking the section speed limit as the target driving speed; or, if the first comparison result is that only the average speed of one target vehicle is greater than the section speed limit, then taking the product of the section speed limit and the third coefficient as the target driving speed; or, if the first comparison result is that the average speeds of at least two target vehicles are greater than the section speed limit, then taking the average speed of the target vehicles as the target driving speed.

[0101] It should be noted that: ① When the first comparison result shows that the average speed of the target vehicle is less than the section speed limit, in order to make the vehicle driving meet the road speed limit requirements and ensure a certain traffic efficiency, the system will directly take the section speed limit as the target driving speed. For example, the section speed limit is 80 km / h, and the average speed of the target vehicle is 75 km / h. At this time, the target driving speed is set to 80 km / h.

[0102] ② If the first comparison result indicates that only the average speed of one target vehicle is greater than the section speed limit, the system will multiply the section speed limit by the third coefficient and take the obtained product as the target driving speed. The third coefficient is set to reasonably adjust the target driving speed when there are individual vehicles with relatively high speeds, neither being overly affected by individual high-speed vehicles nor completely ignoring this situation. Suppose the section speed limit is 70 km / h and the third coefficient is 1.05. When only one target vehicle has an average speed greater than 70 km / h, the target driving speed is 70×1.05 = 73.5 km / h.

[0103] ③ If the first comparison result shows that the average speeds of at least two target vehicles are greater than the section speed limit, this means that the overall speed of the current traffic flow is relatively fast. At this time, the system will take the average speed of the target vehicles as the target driving speed. For example, the section speed limit is 65 km / h, and there are 3 target vehicles with average speeds of 68 km / h, 70 km / h, and 72 km / h respectively. After calculation, the average speed of the target vehicles is about 70 km / h. Then the target driving speed is set to 70 km / h to better adapt to the actual speed situation of the traffic flow.

[0104] In the embodiment of the present application, when there is a speed limit on a section of the road, by analyzing the relative magnitude relationship between the section speed limit and the map speed limit, and selecting a control speed according to specific rules (such as considering the first speed threshold, the second speed threshold, and the corresponding coefficients), it is possible to comprehensively consider the actual road sign speed limit and the map speed limit information, reasonably determine the preliminary control speed, and avoid the deviation caused by simply relying on a single speed limit data. Then, by comparing the section speed limit with the average speed of the target vehicle, according to different comparison results (the average speed is less than the section speed limit, only one vehicle speed is greater than the section speed limit, at least two vehicle speeds are greater than the section speed limit), the control speed is updated to the target driving speed using the corresponding rules, fully considering the actual speed conditions of the traffic flow, enabling the vehicle driving speed to not only comply with the speed limit regulations but also adapt to the traffic flow, effectively avoiding speeding or low traffic efficiency caused by unreasonable speeds, ensuring driving safety, and improving the smoothness of road traffic.

[0105] The method provided by the embodiment of the present application first comprehensively considers the map speed limit and the speed limit sign detection result, which can make the road speed limit clearer; secondly, it detects the average speed of the target vehicle to provide a reference for the actual speed of the traffic flow for speed setting. In addition, when solving the problem of inconsistent speed limits, by obtaining multi-source speed limit data, different speed limit information can be comprehensively collected. When the map speed limit does not match the identified section speed limit, by comprehensively analyzing the map speed limit, the speed limit detection result, and the average speed, the target driving speed is set according to the established rules. In this way, the set speed of the vehicle can be intelligently and reasonably selected, effectively avoiding speeding or affecting the traffic flow rate due to unreasonable speeds, and improving driving safety and road traffic efficiency.

[0106] In another embodiment of the present application, the map speed limit, the speed limit detection result, and the average speed are analyzed to obtain an analysis result, and the target driving speed of the vehicle on the section is set according to the analysis result, such as Figure 5 shown, including the following steps D1 - D2:

[0107] Step D1, if no section speed limit is shown in the speed limit detection result, then compare the map speed limit with the average speed of each target vehicle to obtain a second comparison result.

[0108] Specifically, when the speed limit detection result shows that no speed limit of the current road section recognized by the camera is detected (i.e., there is no clear actual road speed limit sign information), the system will compare the speed limit obtained from the high-precision map with the average speed of each target vehicle. Specifically, the system will compare the map speed limit value with the average speed calculated for each target vehicle in turn. For example, if the high-precision map shows that the speed limit of the current road section is 80 km / h, and there are 4 target vehicles with average speeds of 70 km / h, 75 km / h, 82 km / h, and 85 km / h respectively, the system will compare 80 km / h with these four speed values respectively. Through such a comparison process, a second comparison result that can reflect the relationship between the map speed limit and the average speed of the target vehicle is finally obtained.

[0109] Step D2, set the target driving speed of the vehicle on the road section based on the second comparison result.

[0110] Specifically, setting the target driving speed of the vehicle on the road section based on the second comparison result includes: if the second comparison result is that the average speed is less than the map speed limit, then set the map speed limit as the target driving speed; or, if the second comparison result is that only the average speed of one target vehicle is greater than the map speed limit, then take the product of the map speed limit and the third coefficient as the target driving speed; or, if the second comparison result is that the average speeds of at least two target vehicles are greater than the map speed limit, then take the average speed of the target vehicles as the target driving speed.

[0111] It should be noted that ① if the second comparison result shows that the average speed of the target vehicle is less than the speed limit value provided by the high-precision map, in order to make the vehicle driving speed meet the speed limit requirements indicated by the map in the case of no actual road section speed limit sign, the system will directly set the map speed limit as the target driving speed. For example, if the map speed limit is 90 km / h and the average speed of the target vehicle is 85 km / h, then the target driving speed is determined to be 90 km / h.

[0112] ② When the second comparison result shows that only the average speed of one target vehicle is greater than the map speed limit, the system will multiply the map speed limit by the third coefficient and take the obtained product as the target driving speed. The third coefficient is set to reasonably adjust the target driving speed in the case of individual target vehicles with relatively high speeds, so as not to be overly affected by individual high-speed vehicles and to appropriately consider this speed difference. Suppose the map speed limit is 100 km / h and the third coefficient is 1.03. When only one target vehicle has an average speed greater than 100 km / h, the target driving speed is 100×1.03 = 103 km / h.

[0113] ③ If the second comparison result shows that the average speed of at least two target vehicles is greater than the map speed limit, it indicates that the overall speed of the traffic flow on the current road section is relatively high. At this time, the system will use the average speed of the target vehicles as the target driving speed. For example, the map speed limit is 110 km / h, and there are 3 target vehicles with average speeds of 112 km / h, 115 km / h, and 118 km / h respectively. After calculation, the average speed of the target vehicles is about 115 km / h, then the target driving speed is set to 115 km / h. This setting can better adapt to the actual traffic flow speed condition and make the vehicle driving smoother.

[0114] In the embodiment of the present application, when the speed limit detection result does not show the road section speed limit, the second comparison result is obtained by comparing the map speed limit with the average speed of the target vehicles, and the target driving speed is set accordingly, which has significant beneficial effects. On the one hand, it comprehensively considers the map speed limit and the actual speed of the traffic flow. When the average speed is less than the map speed limit, the map speed limit is adopted to ensure that the vehicle driving complies with the regulations. On the other hand, for different speed comparison situations, such as when only one vehicle speed is greater than the map speed limit, the product of the map speed limit and the third coefficient is used as the target driving speed. When at least two vehicle speeds are greater than the map speed limit, the average speed of the target vehicles is directly adopted, which can make the vehicle speed setting more in line with the actual traffic flow condition, avoid the low traffic efficiency or safety hazards caused by unreasonable speed settings, effectively improve the driving safety and road traffic efficiency, and ensure that the vehicle can drive reasonably without a clear road section speed limit sign.

[0115] The following is a complete example provided by the embodiment of the present application, which is illustrated by a highway section:

[0116] Step 1, the vehicle activates the highway navigation pilot (NOA) function. The perception sensor identifies the speed limit sign, and the high-precision map obtains the speed limit value of the current area of the vehicle through the cloud, and outputs both to the ECU for speed limit value comparison. After difference calculation, the result is output. If the map speed limit Vm is greater than the road section speed limit Vt and does not exceed 10%, it is controlled according to the high-precision map speed limit. If the map speed limit Vm is less than the road section speed limit Vt and does not exceed 10%, it is controlled according to the speed limit identified by the camera. Otherwise, if it exceeds 10%, the control logic continues to be executed.

[0117] Step 2: Obtain the vehicle's position information through the cloud and input it into the position matching and judgment module. Use the lane line detection method based on instance segmentation to label each lane line as a unique instance, and determine whether it is a guide line according to the shape, position, and direction of the lane lines after segmentation and labeling. If it is detected that it is not a guide line, return to the lane line detection based on instance segmentation; if it is recognized as a guide line, enter the position judgment. If it is not determined to be a guide line, the vehicle's position is considered to be the main road. If it is confirmed to be a guide line and on the left side of the vehicle itself, it is considered to be a ramp. If it is confirmed to be a guide line and on the right side of the vehicle itself, it is considered to be the main road. Output the currently obtained result and match it with the high-precision map.

[0118] Step 3: Conduct target sampling, take all vehicle targets that can be recognized by the front camera, and re-recognize the vehicles that do not pass the target screening and new vehicles every 5s. When on the main road, judge the target vehicles in the left 1 and left 2 lanes and the vehicle's own lane, with the left taking precedence. For those that do not pass, return to the target sampling for re-identification and selection. For the target vehicles that pass, the sensor measures the driving speed and makes dot markings (applicable to lanes 2-4 on the highway); when on the ramp, select targets based on the current position. When entering the ramp, for dual / single-lane targets, measure the vehicle driving speed. The target selection strategy is the target vehicles in the vehicle's own lane and the right lane. For those that do not pass, return to the target sampling for re-identification and selection. For those that pass, make dot markings. Calculate the average speed of the dot-marked target vehicles, output the calculated average speed, and calculate and output the average speed by participating the average speed output in the previous dot marking in the average speed output of the dot-marked target vehicles for re-identifying the target vehicles after the next 5s (in a loop).

[0119] Step 4: Compare the speed limit of the high-precision map, the average target speed, and the speed limit recognized by the camera for the road. When there is a speed limit recognized by the camera for the road, compare the average speed with the speed limit value recognized by the camera. When it is less, the set speed of the vehicle uses the speed limit indicated by the speed limit sign. When it is greater and there is a single target, use the average speed not exceeding 10% of the speed limit recognized by the camera. When it is greater and there are multiple targets (2 or more target vehicles), directly use the average speed; when there is no speed limit recognized by the camera for the road, compare the average speed with the speed limit of the high-precision map. When it is less, the set vehicle speed uses the speed limit of the high-precision map. When it is greater and there is a single target, use the average speed not exceeding 10% of the map speed limit. When it is greater and there are multiple targets (2 or more target vehicles), directly use the average speed, and adjust the set vehicle speed according to the comparison result.

[0120] In this embodiment, a device for setting the vehicle speed is also provided. This device is used to implement the above-mentioned embodiments and preferred implementation manners, and those that have been described will not be repeated. As used hereinafter, the term "module" can be a combination of software and / or hardware that can achieve a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation in hardware, or a combination of software and hardware is also contemplated.

[0121] This embodiment provides a device for setting the vehicle speed, as Figure 6 shown, including:

[0122] An acquisition module 501, configured to acquire the map speed limit of the vehicle on the road section and identify the road section speed limit of the road section, so as to obtain a speed limit detection result;

[0123] A detection module 502, configured to detect the average speed of the target vehicle of the vehicle on the road section;

[0124] An analysis module 503, configured to analyze the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and set the target driving speed of the vehicle on the road section according to the analysis result.

[0125] In the embodiment of the present application, the device further includes: a matching module, configured to acquire at least one lane line in the road section where the vehicle is located, and extract the lane line features of the lane line; match the lane line features with preset features to obtain a matching result, where the preset features are the features of the diversion line; determine the road section type of the road section where the vehicle is located according to the matching result.

[0126] In the embodiment of the present application, the detection module 502 is configured to acquire the search range corresponding to the road section type of the road section where the vehicle is located; select a target vehicle in the road section according to the search range, and detect the vehicle speed corresponding to the target vehicle; calculate the average speed of the target vehicle according to the vehicle speed of the target vehicle.

[0127] In the embodiment of the present application, the analysis module 503 includes:

[0128] A first analysis sub-module, configured to analyze the relative magnitude relationship between the road section speed limit and the map speed limit if the road section speed limit is shown in the speed limit detection result;

[0129] A selection sub-module, configured to select a control speed from the road section speed limit and the map speed limit based on the relative magnitude relationship, and control the vehicle to travel at the control speed;

[0130] A comparison sub-module, configured to compare the road section speed limit with the average speed of each target vehicle to obtain a first comparison result;

[0131] An update sub-module, configured to update the control speed to the target driving speed based on the first comparison result.

[0132] In an embodiment of the present application, a sub-module is selected. If the relative magnitude relationship is that the section speed limit is less than the map speed limit and the map speed limit is less than or equal to the first speed threshold, the map speed limit is used as the control speed. The first speed threshold is calculated from the section speed limit and a first coefficient, and the first coefficient is greater than 1. Or, if the relative magnitude relationship is that the second speed threshold is less than or equal to the map speed limit and the map speed limit is less than the section speed limit, the section speed limit is used as the control speed. The second speed threshold is calculated from the section speed limit and a second coefficient, and the second coefficient is less than 1.

[0133] In an embodiment of the present application, an update sub-module is used. If the first comparison result is that the average speed is less than the section speed limit, the section speed limit is used as the target driving speed. Or, if the first comparison result is that the average speed of only one target vehicle is greater than the section speed limit, the product of the section speed limit and a third coefficient is used as the target driving speed. Or, if the first comparison result is that the average speeds of at least two target vehicles are greater than the section speed limit, the average speed of the target vehicles is used as the target driving speed.

[0134] In an embodiment of the present application, the analysis module 503 includes:

[0135] A second analysis sub-module is used to compare the map speed limit with the average speed of each target vehicle to obtain a second comparison result if no section speed limit is shown in the speed limit detection result.

[0136] A setting sub-module is used to set the target driving speed of the vehicle on the section based on the second comparison result.

[0137] In an embodiment of the present application, the setting sub-module is used. If the second comparison result is that the average speed is less than the map speed limit, the map speed limit is used as the target driving speed. Or, if the second comparison result is that the average speed of only one target vehicle is greater than the map speed limit, the product of the map speed limit and a third coefficient is used as the target driving speed. Or, if the second comparison result is that the average speeds of at least two target vehicles are greater than the map speed limit, the average speed of the target vehicles is used as the target driving speed.

[0138] An embodiment of the present invention provides a vehicle, including: a vehicle body and a controller. Control instructions are stored in the controller, and the controller executes the above method by executing the control instructions.

[0139] Please refer to Figure 7 , Figure 7 which is a schematic structural diagram of a computer device provided by an alternative embodiment of the present invention, as Figure 7As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting the components, including a high-speed interface and a low-speed interface. Each component communicates with each other using different buses and can be installed on a common motherboard or installed in other ways as needed. The processor can process instructions executed within the computer device, including instructions stored in the memory or on the memory to display graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some alternative embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (such as an array of servers, a set of blade servers, or a multi-processor system). Figure 7 In [the figure], a processor 10 is taken as an example.

[0140] The processor 10 can be a central processing unit, a network processor, or a combination thereof. Among them, the processor 10 can further include a hardware chip. The above-mentioned hardware chip can be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The above-mentioned programmable logic device can be a complex programmable logic device, a field programmable gate array, a generic array logic, or any combination thereof.

[0141] Among them, the memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiments.

[0142] The memory 20 can include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the computer device presented by a kind of landing page of a small program, etc. In addition, the memory 20 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one disk storage device, a flash memory device, or other non-transitory solid-state storage devices. In some alternative embodiments, the memory 20 can optionally include a memory remotely set relative to the processor 10, and these remote memories can be connected to the computer device through a network. Examples of the above-mentioned network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and a combination thereof.

[0143] The memory 20 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid-state drive; the memory 20 can also include a combination of the above types of memories.

[0144] The computer device further includes a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0145] Embodiments of the present invention also provide a computer-readable storage medium. The method according to the embodiments of the present invention can be implemented in hardware, firmware, or be implemented as computer code that can be recorded on a storage medium, or be implemented as computer code that is originally stored in a remote storage medium or a non-transitory machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk, or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code, and when the software or computer code is accessed and executed by the computer, the processor, or the hardware, the method shown in the above embodiments is implemented.

[0146] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for setting vehicle speed, characterized in that: The method comprises: Obtain the map speed limit corresponding to the road section where the vehicle is located, and detect the speed limit sign of the road section to obtain the speed limit detection result; Detecting an average speed of a target vehicle of the vehicle on the road section; The map speed limit, the speed limit detection result and the average speed are analyzed to obtain an analysis result, and a target driving speed of the vehicle on the road section is set according to the analysis result.

2. The method according to claim 1, characterized in that Before detecting the average speed of the target vehicle on the road section, the method further includes: Acquire at least one lane line in the road section where the vehicle is located, and extract lane line features of the lane line; Matching the lane line feature with a preset feature to obtain a matching result, wherein the preset feature is a feature of a guide line; The road section type of the road section where the vehicle is located is determined according to the matching result.

3. The method according to claim 2, characterized in that The detecting an average speed of the target vehicle on the road section includes: Obtaining a search range corresponding to the road section type of the road section where the vehicle is located; Selecting a target vehicle on the road section according to the search range, and detecting a vehicle speed corresponding to the target vehicle; An average speed of the target vehicle is calculated based on the vehicle speed of the target vehicle.

4. The method according to claim 1, characterized in that: The analyzing the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and setting a target driving speed of the vehicle on the road section according to the analysis result, includes: If the speed limit detection result shows a road section speed limit, analyzing the relative size relationship between the road section speed limit and the map speed limit; Selecting a control speed from the road section speed limit and the map speed limit based on the relative size relationship, and controlling the vehicle to travel at the control speed; Comparing the speed limit of the road section with the average speed of each of the target vehicles to obtain a first comparison result; The control speed is updated to a target travel speed based on the first comparison result.

5. The method according to claim 4, characterized in that The selecting a control speed from the road section speed limit and the map speed limit based on the relative size relationship includes: If the relative size relationship is that the speed limit of the road section is less than the speed limit on the map, and the speed limit on the map is less than or equal to a first speed threshold, the speed limit on the map is used as the control speed, and the first speed threshold is calculated by the speed limit of the road section and a first coefficient, and the first coefficient is greater than 1; or, If the relative size relationship is that the second speed threshold is less than or equal to the map speed limit, and the map speed limit is less than the road section speed limit, the road section speed limit is used as the control speed, and the second speed threshold is calculated by the road section speed limit and a second coefficient, and the second coefficient is less than 1.

6. The method according to claim 4, characterized in that The updating of the control speed to the target driving speed based on the first comparison result includes: If the first comparison result is that the average speed is less than the speed limit of the road section, the speed limit of the road section is used as the target driving speed; or, If the first comparison result is that only one target vehicle has an average speed greater than the speed limit of the road section, the product of the speed limit of the road section and the third coefficient is used as the target driving speed; or, If the first comparison result is that the average speed of at least two target vehicles is greater than the speed limit of the road section, the average speed of the target vehicles is used as the target driving speed.

7. The method according to claim 1, characterized in that The analyzing the map speed limit, the speed limit detection result, and the average speed to obtain an analysis result, and setting a target driving speed of the vehicle on the road section according to the analysis result, includes: If the speed limit detection result does not show a road section speed limit, compare the map speed limit with the average speed of each target vehicle to obtain a second comparison result; A target driving speed of the vehicle on the road section is set based on the second comparison result.

8. The method according to claim 7, characterized in that The step of setting a target driving speed of the vehicle on the road section based on the second comparison result includes: If the second comparison result is that the average speed is less than the map speed limit, the map speed limit is used as the target driving speed; or, If the second comparison result is that only one target vehicle has an average speed greater than the map speed limit, then the product of the map speed limit and the third coefficient is used as the target driving speed; or, If the second comparison result is that the average speed of at least two target vehicles is greater than the map speed limit, the average speed of the target vehicles is used as the target driving speed.

9. A vehicle speed setting device, characterized in that: The device comprises: An acquisition module is used to acquire a map speed limit of a vehicle on a road section, identify the speed limit of the road section, and obtain a speed limit detection result; A detection module, used for detecting an average speed of a target vehicle of the vehicle on the road section; The analysis module is used to analyze the map speed limit, the speed limit detection result and the average speed to obtain an analysis result, and set a target driving speed of the vehicle on the road section according to the analysis result.

10. A vehicle, characterized in that: include: A vehicle body and a controller, wherein control instructions are stored in the controller, and the controller executes the method according to any one of claims 1 to 8 by executing the control instructions.

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