Automatic driving vehicle control method, device, equipment and storage medium

Abstract

Embodiments of the present application provide a kind of automatic driving vehicle control method, device, equipment and storage medium, it is related to automatic driving technical field, the method comprises: first, the positioning information and map information of target vehicle are acquired;Then, based on the positioning information and map information, path planning is carried out, and navigation information and trajectory point information are obtained;Wherein, trajectory point information is used to reflect the path information of the driving path from the high-speed main road into ramp;Finally, based on navigation information and trajectory point information, target vehicle is controlled.The above-mentioned mode will high-precision positioning information and high-precision map information as control factor together to control target vehicle, more stable navigation information and path information are obtained by path planning, and then when the method is applied to the scene when vehicle from high-speed main road into ramp, the success rate of target vehicle from high-speed main road into ramp can be improved.

Description

Technical Field

[0001] This application relates to the field of autonomous driving technology, and in particular to an autonomous vehicle control method, device, equipment and storage medium. Background Technology

[0002] With the development of autonomous driving technology, automakers and technology companies are expanding their research and development of higher-level autonomous driving functions, such as L2+, L3, and L4, as defined by the Society of Automotive Engineers (SAE). Highway scenarios, being relatively easy to implement, are a key focus of high-level autonomous driving research. While driver assistance and intelligent driving functions for highway main roads are relatively mature and widely available in commercially available vehicles, the entry point onto highway ramps presents a significant technological challenge and a major hurdle to achieving full-scale intelligent driving on highways.

[0003] Current technologies for autonomous driving on highway ramps primarily rely on forward-looking visual perception to identify lane markings and control the vehicle to change lanes and enter the ramp. However, this approach suffers from a low success rate in enabling vehicles to enter ramps from highways. Summary of the Invention

[0004] This application provides an autonomous vehicle control method, device, equipment, and storage medium to address the problem of low success rate of vehicles entering ramps from highway main roads.

[0005] According to a first aspect of this application, an autonomous vehicle control method is provided, comprising:

[0006] Obtain the location and map information of the target vehicle;

[0007] Based on the positioning information and the map information, path planning is performed to obtain navigation information and trajectory point information; wherein, the trajectory point information is used to reflect the path information of the driving route from the main highway to the ramp;

[0008] The target vehicle is controlled based on the navigation information and the trajectory point information.

[0009] This application provides an autonomous vehicle control method that uses high-precision positioning information and high-precision map information as control factors to control the target vehicle. By obtaining more stable navigation and path information through path planning, the success rate of the target vehicle entering the ramp from the highway can be improved.

[0010] In one possible implementation, controlling the target vehicle based on the navigation information and the trajectory point information includes:

[0011] Based on the navigation information, decision information is determined using a preset decision algorithm;

[0012] When the decision information indicates entering the trajectory point mode, the target vehicle is controlled based on the trajectory point information.

[0013] The embodiments of this application can accurately determine decision information through the above-mentioned decision algorithm, and provide a specific vehicle control mode, namely the trajectory point mode. Since the trajectory point information is used to reflect the path information of the driving path from the highway main road to the ramp, the trajectory point information also has high stability on the basis of the stability of the path information. Therefore, the success rate of the target vehicle entering the ramp from the highway main road can be further improved by using the trajectory point information with high stability.

[0014] In one possible implementation, the navigation information includes: the next navigation lane change sign and the distance from the target vehicle to the next navigation lane change point; the step of determining decision information based on the navigation information using a preset decision algorithm includes:

[0015] The system uses a preset decision algorithm to determine whether the next navigation lane change sign is a sign for entering the ramp from the right on the main highway, and whether the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold.

[0016] If the next navigation lane change sign is a sign indicating a right turn onto a ramp from the main highway, and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold, then entering the trajectory point mode will be determined as decision information.

[0017] This application embodiment specifically describes the process of determining the trajectory point mode as decision information. That is, the navigation information is set with conditions for entering the trajectory point mode. The navigation information that meets the conditions can reflect that the current scenario is suitable for achieving accurate control of the target vehicle in the trajectory point mode.

[0018] In one possible implementation, controlling the target vehicle based on the trajectory point information includes:

[0019] Based on the trajectory point information, corresponding control commands are output, and the target vehicle is controlled using the control commands.

[0020] The embodiments of this application realize the control of the target vehicle through control commands, which can increase the feasibility of accurately controlling the target vehicle.

[0021] In one possible implementation, the step of performing path planning based on the positioning information and the map information to obtain navigation information and trajectory point information includes:

[0022] Based on the location information, determine the current location of the target vehicle in the map information;

[0023] Based on the current location of the target vehicle and the preset destination location, determine the driving path from the main highway to the ramp.

[0024] The navigation information is determined based on the driving path and the map information, and the trajectory point information is determined based on the driving path.

[0025] This application embodiment can accurately identify the current position of the target vehicle and the preset target location based on high-precision positioning information, thereby generating a feasible and optimal driving path from the highway main road to the ramp, and obtaining stable trajectory point information and accurate navigation information, providing a data foundation for subsequent control of the target vehicle based on the trajectory point information.

[0026] In one possible implementation, determining the driving path from the highway main road to the ramp based on the current location of the target vehicle and a preset destination location includes:

[0027] Determine whether a deceleration lane exists on the ramp based on the map information;

[0028] When a deceleration lane exists on the ramp, a path planning algorithm is used to determine the driving path from the main highway into the deceleration lane based on the current position of the target vehicle and the preset destination position set on the deceleration lane.

[0029] In the absence of a deceleration lane on the highway, a path planning algorithm is used to determine the driving path from the highway main road to the ramp, based on the current position of the target vehicle and the preset destination position set on the ramp.

[0030] The embodiments of this application can intelligently identify whether there is a deceleration lane on the ramp, and if there is a deceleration lane, set the preset destination location on the deceleration lane; if there is no deceleration lane, set the preset destination location on the ramp, so that a reasonable driving route can be planned when using a path planning algorithm for path planning.

[0031] In one possible implementation, determining the trajectory point information based on the driving path includes:

[0032] Starting from the current position of the target vehicle, trajectory points are selected in the driving path according to a preset trajectory point interval strategy, and trajectory point information is generated; the preset trajectory point interval strategy is to select a first preset number of trajectory points according to a first preset interval, and select a second preset number of trajectory points according to a second preset interval.

[0033] In this embodiment, the trajectory point is a point selected after discretizing the path. There is a gap between two adjacent trajectory points. By setting the gap between two adjacent trajectory points, this embodiment can ensure that the target vehicle can successfully enter the ramp from the highway main road, while also avoiding frequent control of the target vehicle.

[0034] According to a second aspect of this application, an autonomous vehicle control device is provided, comprising:

[0035] A high-precision positioning module is used to acquire the positioning information of the target vehicle;

[0036] A high-precision map module is used to acquire map information;

[0037] The path planning module is used to perform path planning based on the positioning information and the map information to obtain navigation information and trajectory point information; wherein, the trajectory point information is used to reflect the path information of the driving path from the highway main road to the ramp.

[0038] The control module is used to control the target vehicle based on the navigation information and the trajectory point information.

[0039] According to a third aspect of this application, an electronic device is provided, comprising: at least one processor and a memory;

[0040] The memory stores computer-executed instructions;

[0041] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the autonomous vehicle control method as described in the first aspect above.

[0042] According to a fourth aspect of this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, which, when executed by a processor, are used to implement the autonomous vehicle control method described in the first aspect above.

[0043] According to a fifth aspect of this application, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the autonomous vehicle control method described in the first aspect.

[0044] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent from the following description. Attached Figure Description

[0045] Figure 1 This is a schematic diagram illustrating one of the application scenarios involved in the embodiments of this application;

[0046] Figure 2 This is a schematic diagram illustrating application scenario two involved in the embodiments of this application;

[0047] Figure 3 A flowchart illustrating an autonomous vehicle control method provided in an embodiment of this application;

[0048] Figure 4 A flowchart illustrating another autonomous vehicle control method provided in this application embodiment;

[0049] Figure 5 A flowchart illustrating another autonomous vehicle control method provided in this application embodiment;

[0050] Figure 6 This is a schematic diagram of the structure of an autonomous vehicle control device provided in an embodiment of this application;

[0051] Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0052] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application.

[0053] To facilitate understanding, the application scenarios of the embodiments of this application will be introduced first.

[0054] Figure 1 This is a schematic diagram illustrating one of the application scenarios involved in an embodiment of this application. For example... Figure 1 As shown, in this embodiment, the vehicle needs to enter the deceleration lane from the main highway. Figure 2 This is a schematic diagram illustrating application scenario two involved in the embodiments of this application. For example... Figure 2As shown, in this embodiment, the vehicle needs to enter the ramp from the main highway. Regardless of the application scenario, existing technologies rely solely on forward-looking visual perception to identify lane lines, recognizing both the main highway lane lines and the ramp lane lines, and controlling the vehicle to change lanes and enter the ramp. However, current visual perception lane line technology has poor recognition quality at ramp entrances. Not only is the recognition of lane lines on the original main highway affected by the ramp, but the recognition of lane lines on newly added ramps is also very unstable. Therefore, the success rate of vehicles entering ramps from the main highway is low, resulting in poor passenger comfort.

[0055] To address at least one of the aforementioned technical problems, this application provides an autonomous vehicle control method, apparatus, device, and storage medium, applied in the field of autonomous driving, to solve the technical problems of low success rate of vehicles entering ramps from highway main roads and poor passenger comfort.

[0056] The main idea of ​​this application is to use high-precision positioning information and high-precision map information together as control factors to control the target vehicle. By obtaining more stable navigation and path information through path planning, the success rate of the target vehicle entering the ramp from the highway can be improved.

[0057] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0058] Figure 3 This is a flowchart illustrating an autonomous vehicle control method provided in an embodiment of this application.

[0059] like Figure 3 As shown, the method in this embodiment includes:

[0060] S301: Obtain the location information and map information of the target vehicle. The map information is obtained based on a high-precision map.

[0061] In this embodiment, the target vehicle in S301 can refer to any vehicle, and the location information and map information of the target vehicle can be acquired by different acquisition modules. Figure 5As can be seen, the high-precision positioning module is used to update the target vehicle's current location in real time based on its movement, and outputs the target vehicle's positioning information to the path planning module. This positioning information includes, but is not limited to, latitude, longitude, heading angle, altitude, and speed. The high-precision map module is used to store high-precision map data and provide map information to the path planning module. This map information can refer to... Figure 1 Scene or Figure 2 Map information of a certain area of ​​the scene, or it can refer to... Figure 1 Scene or Figure 2 The map information pertains to the urban area of ​​the scene; therefore, this embodiment of the application does not specifically limit the scope of the map information.

[0062] S302: Based on the positioning information and the map information, perform path planning to obtain navigation information and trajectory point information; wherein, the trajectory point information is used to reflect the path information of the driving path from the main highway to the ramp.

[0063] This application does not specifically limit the path planning algorithm; it can be any of the following: genetic algorithm, Dijkstra's algorithm, A* algorithm, etc. The navigation information includes at least one of the following: current lane type, right lane type, next navigation lane change sign, and distance from the target vehicle to the next navigation lane change point. The trajectory point information includes: the trajectory point's heading h[N] in the target vehicle's coordinate system, the trajectory point's x-coordinate x[N] in the target vehicle's coordinate system, the trajectory point's y-coordinate y[N] in the target vehicle's coordinate system, the road's longitudinal slope slope_x[N] at the trajectory point, the road's lateral slope slope_y[N] at the trajectory point, the road curvature LaneCure[N] at the trajectory point, and the road speed limit spdlmt[N] at the trajectory point. N is the number of trajectory points, and its specific value can be adaptively adjusted according to actual needs. Furthermore, the spacing between trajectory points and the total distance between trajectory points can also be adaptively adjusted according to actual needs. This application uses N=40 as an example for explanation. The first 25 points are spaced 2m apart, and the last 15 points are spaced 20m apart, with a total distance of 350m between the trajectory points. It should be understood that the specific implementation of S302 can be found in [reference needed]. Figure 5 The detailed descriptions of S502 to S504 are not repeated here.

[0064] S303: Control the target vehicle based on the navigation information and the trajectory point information.

[0065] It should be understood that the specific implementation of S303 can be found in [reference needed]. Figure 4 The detailed descriptions of S403 to S404 are not repeated here.

[0066] As can be seen from the descriptions in S301 to S303, the embodiments of this application use high-precision positioning information and high-precision map information together as control factors to control the target vehicle. By obtaining more stable navigation information and path information through path planning, the success rate of the target vehicle entering the ramp from the highway main road can be improved.

[0067] Based on the above embodiments, the technical solution of this application will be described in more detail below with reference to several specific embodiments.

[0068] Figure 4 This is a flowchart illustrating another autonomous vehicle control method provided in an embodiment of this application. Figure 3 Based on the illustrated embodiment, this embodiment focuses on Figure 3 S303 in the text is further refined. For example... Figure 4 As shown, the method in this embodiment includes:

[0069] S401: Obtain the location and map information of the target vehicle; it should be understood that the specific implementation of S401 can be found in [reference needed]. Figure 3 The detailed description of S301 is omitted here.

[0070] S402: Based on the positioning information and the map information, perform path planning to obtain navigation information and trajectory point information; wherein, the trajectory point information is used to reflect the path information of the driving route from the main highway to the ramp; it should be understood that the specific implementation of S302 can be found in [reference needed]. Figure 5 The detailed descriptions of S502 to S504 are not repeated here.

[0071] S403: Based on the navigation information, determine decision information using a preset decision algorithm;

[0072] The decision information is whether to enter the trajectory point mode (0 / 1). The decision submodule has a built-in decision algorithm to execute the above S403. Specifically, based on the navigation information, it uses a preset decision algorithm to determine whether to enter the trajectory point mode (0 / 1) and sends the decision information of whether to enter the trajectory point mode (0 / 1) to the control submodule. The specific process is as follows in S4031 to S4032, which will not be elaborated here.

[0073] S404: When the decision information indicates entering the trajectory point mode, control the target vehicle based on the trajectory point information.

[0074] By executing the operations described in S403 to S404, the specific process of controlling the target vehicle can be determined, and the trajectory point mode can be entered. This ensures that the target vehicle can be effectively controlled to maintain lateral movement along the trajectory point based on stable path information, thereby improving the success rate of the vehicle entering the ramp from the highway main road.

[0075] In one possible implementation, the navigation information includes: the next navigation lane change sign and the distance from the target vehicle to the next navigation lane change point; step S403: based on the navigation information, determining decision information using a preset decision algorithm, including:

[0076] S4031: Use a preset decision algorithm to determine whether the next navigation lane change sign is a sign for entering the ramp from the right on the main highway, and whether the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold.

[0077] S4032: If the next navigation lane change sign is a sign indicating a right-turn ramp from a highway main road, and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold, then entering the trajectory point mode is determined as decision information. The preset threshold can be 100 or other values, and this embodiment does not limit this. When the decision submodule determines that the next navigation lane change sign is a sign indicating a right-turn ramp from a highway main road, and the distance from the target vehicle to the next navigation lane change point is less than or equal to 100, it outputs the decision information as entering the trajectory point mode.

[0078] In one possible implementation, step S404: controlling the target vehicle based on the trajectory point information includes: outputting a corresponding control command based on the trajectory point information, and using the control command to control the target vehicle.

[0079] The aforementioned control commands may include lateral control commands and longitudinal control commands. The control submodule has a built-in planning and control algorithm to execute the above S404. Specifically, based on decision information and trajectory point information, it performs target vehicle motion planning and control, and outputs lateral control information and longitudinal control information in the form of control commands to control the target vehicle. Figure 6 The vehicle's (Ego) movement is controlled by lateral control information, including steering wheel angle requests, and longitudinal control information, including acceleration torque requests and deceleration requests.

[0080] This application's embodiments use high-precision positioning and high-precision maps to replace the forward visual perception of related solutions. In the scenario of entering a ramp from a highway main road, the corresponding path planning algorithm, decision-making algorithm, and control algorithm are matched to obtain more stable path information, thereby enabling the target vehicle to enter the ramp from the highway main road according to the path information.

[0081] Figure 5 This is a flowchart illustrating another autonomous vehicle control method provided in an embodiment of this application. Figure 3 Based on the illustrated embodiment, this embodiment focuses on Figure 3S302 in the text is further refined. For example... Figure 5 As shown, the method in this embodiment includes:

[0082] S501: Obtain the location and map information of the target vehicle; it should be understood that the specific implementation of S501 can be found in [reference needed]. Figure 3 For a detailed description of S301, or see [link to S301] Figure 4 The detailed description of S401 is omitted here.

[0083] S502: Determine the current location of the target vehicle in the map information based on the positioning information;

[0084] S503: Determine the driving path from the main highway to the ramp based on the current location of the target vehicle and the preset destination location; it should be understood that the specific implementation of S503 can be found in the detailed description of S5031 to S5033 below, and will not be repeated here.

[0085] S504: Determine the navigation information based on the driving path and the map information, and determine the trajectory point information based on the driving path;

[0086] S505: Control the target vehicle based on the navigation information and the trajectory point information.

[0087] It should be understood that the specific implementation of S505 can be found in [reference needed]. Figure 4 The detailed descriptions of S403 to S404 are omitted here. The specific process of determining navigation information and trajectory point information can be described in detail by performing the operations described in S502 to S504 above.

[0088] In one possible implementation, S503: Based on the current location of the target vehicle and the preset destination location, determine the driving path from the highway main road to the ramp, including:

[0089] S5031: Determine whether a deceleration lane exists on the ramp based on the map information;

[0090] S5032: When there is a deceleration lane on the ramp, the driving path from the main highway to the deceleration lane is determined by using a path planning algorithm based on the current position of the target vehicle and the preset destination position set on the deceleration lane.

[0091] S5033: In the absence of a deceleration lane on the highway, a path planning algorithm is used to determine the driving path from the highway main road to the ramp based on the current position of the target vehicle and the preset destination position set on the ramp.

[0092] By performing the operations described in S5031 to S5033, it can be determined whether a deceleration lane exists on the ramp, thereby enabling intelligent differentiation. Figure 1 Scenes and Figure 2 The scenario described in this application enables the use of path planning algorithms to determine the driving path from the highway main road to the ramp in different scenarios, thereby effectively controlling the target vehicle. Furthermore, regardless of the context... Figure 1 In the context of the story, or in Figure 2 In all scenarios, the driving path from the main highway to the ramp is determined through the operations described in S5031 to S5033.

[0093] Specifically, in Figure 1 In this scenario, the path planning module uses the lane lines of the current highway main road and the lane lines of the ramps in the indexed high-precision map to fit a trajectory line that transforms from the center line of the highway main road lane to the center line of the deceleration lane when the width of the deceleration lane gradually increases to be greater than the width of the target vehicle. In the vehicle coordinate system (with the center of the front bumper of the target vehicle as the origin, forward is the positive x-axis, right is the positive y-axis, and upward is the positive z-axis), the trajectory point information of the trajectory line is output.

[0094] exist Figure 2 In this scenario, the path planning module uses the lane lines of the current highway main road and ramps in the indexed high-precision map to fit a trajectory line from the center line of the highway main road lane to the center line of the ramp lane, under the premise of satisfying the minimum turning radius of the target vehicle (the minimum turning radius of the target vehicle is a known value, for example, the minimum turning radius of a certain heavy truck is 30m, and the minimum turning radius is a parameter of the fitted trajectory line). In the vehicle's coordinate system (with the center of the front bumper of the heavy truck as the origin, forward is the positive x-axis direction, right is the positive y-axis direction, and upward is the positive z-axis direction), the trajectory point information of the trajectory line is output.

[0095] In an optional embodiment, since the navigation information includes at least one of the following: current lane type, right lane type, next navigation lane change sign, and distance from the target vehicle to the next navigation lane change point, the determination process of each navigation information can be described, wherein: (1) The current lane type is determined as follows: read the road topology in the map information, determine the type of the road and lane where the vehicle is currently located, and determine the type of the lane as the current lane type. The current lane type is a highway arterial road, ramp, or emergency lane. (2) The right lane type is determined as follows: read the road topology in the map information, determine the type of the road and right lane where the vehicle is currently located, and determine the type of the right lane as the right lane type, which is an arterial road, ramp, or emergency lane. (3) The method for determining the next navigation lane change sign is as follows: During the path planning process from the current location of the vehicle to the destination location, calculate the point where the road ID (Identity document) changes, and calculate the type of the lane before and after the point. If the point before the point is a ramp and the point after the point is a highway, then the next navigation lane change sign is "Ramp to the left to enter the highway driving lane". If the point before the point is a highway and the point after the point is a ramp, then the next navigation lane change sign is "Highway to the right to enter the ramp". (4) The method for determining the distance from the target vehicle to the next navigation lane change point is as follows: During the path planning process from the current location of the vehicle to the destination location, calculate the point where the road ID changes, and calculate the arc distance from the current location to the point in the Frenet coordinate system. If the arc distance is >= 5000m, then the distance of the next navigation lane change point is 5000m. If the arc distance is < 5000m, then the distance of the next navigation lane change point is the arc distance.

[0096] In one possible implementation, S504: Determining the trajectory point information based on the driving path includes: starting from the current position of the target vehicle, selecting trajectory points in the driving path according to a preset trajectory point interval strategy, and generating trajectory point information; the preset trajectory point interval strategy is to select a first preset number of trajectory points according to a first preset interval, and select a second preset number of trajectory points according to a second preset interval. For example, the first preset interval is 2m, the first preset number is 25, the second preset interval is 20m, and the second preset number is 15. This application embodiment does not impose specific limitations on the specific values ​​of the first preset interval, the first preset number, the second preset interval, and the second preset number.

[0097] The method for determining trajectory point information in this embodiment is as follows: Based on the planned driving path connecting the current position of the vehicle to the destination position, the coordinates of 40 trajectory points are calculated forward from the current position of the vehicle, and the interval between the first 25 trajectory points is set to 2m, and the interval between the last 15 trajectory points is set to 20m. The coordinates of the above trajectory points are the coordinates of the trajectory points in the vehicle coordinate system (with the center of the front bumper of the target vehicle as the origin, forward as the positive x-axis, right as the positive y-axis, and upward as the positive z-axis).

[0098] The technical solution described in this application, for two scenarios of entering a ramp from a highway main road, no longer relies on visually perceived lane lines, but instead relies on high-precision positioning and high-precision maps. A specific path planning algorithm is used to fit a suitable driving path from the highway main road to the ramp, generating navigation information and trajectory point information for 350m ahead (adjustable). Then, a decision algorithm is used to determine whether the decision submodule should enter trajectory point following mode. In trajectory point following mode, a control algorithm is used to control the target vehicle to maintain its movement along the trajectory points according to the trajectory point information.

[0099] In summary, in the scenario of entering a ramp from a highway main road, traditional methods have a lane line recognition rate of less than 50% at the ramp entrance, and the lateral deviation of the lane line parameters is greater than 0.5m. However, the embodiments of this application are based on... Figure 6 The actual vehicle in the middle ( Figure 6 Experimental data collected by the vehicle (Ego) shows that the high-precision positioning and high-precision mapping technology can achieve a success rate of over 99.9% in fitting trajectory points at the ramp entrance, with a lateral deviation of less than 0.2m. Real-vehicle test results show that the success rate of autonomous driving control of the target vehicle entering the ramp from the highway main road is less than 70% under traditional methods, while the success rate of the method in this embodiment is greater than 95%, thus improving the success rate of the target vehicle entering the ramp from the highway main road.

[0100] Figure 6 This is a schematic diagram of the structure of an autonomous vehicle control device provided in an embodiment of this application. The device in this embodiment can be in the form of software and / or hardware. Figure 6 As shown, this embodiment provides an autonomous vehicle control device, including: a high-precision positioning module 61, a high-precision map module 62, a path planning module 63, and a control module 64. Among them,

[0101] A high-precision positioning module 61 is used to acquire the positioning information of the target vehicle;

[0102] High-precision map module 62 is used to acquire map information;

[0103] The path planning module 63 is used to perform path planning based on the positioning information and the map information to obtain navigation information and trajectory point information; wherein, the trajectory point information is used to reflect the path information of the driving path from the main highway to the ramp;

[0104] The control module 64 is used to control the target vehicle based on the navigation information and the trajectory point information.

[0105] In one possible implementation, the control module 64 includes a decision submodule and a planning and control submodule, wherein:

[0106] The decision submodule 641 is used to determine decision information based on the navigation information using a preset decision algorithm;

[0107] The control submodule 642 is used to control the target vehicle based on the trajectory point information when the decision information indicates entering the trajectory point mode.

[0108] In one possible implementation, the navigation information includes: the next navigation lane change sign and the distance from the target vehicle to the next navigation lane change point; the decision submodule includes: a judgment unit and a first determination unit, wherein:

[0109] The judgment unit is used to determine whether the next navigation lane change sign is a sign for entering the ramp from the right on the main highway, and whether the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold, using a preset decision algorithm.

[0110] The first determining unit is configured to determine the entry into the trajectory point mode as decision information when the next navigation lane change sign is a sign for entering the ramp from the main highway to the right, and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold.

[0111] In one possible implementation, the planning and control submodule is also used for:

[0112] Based on the trajectory point information, corresponding control commands are output, and the target vehicle is controlled using the control commands.

[0113] In one possible implementation, the path planning module 63 includes a first determining submodule, a second determining submodule, and a third determining submodule, wherein:

[0114] The first determining submodule is used to determine the current location of the target vehicle in the map information based on the positioning information;

[0115] The second determining submodule is used to determine the driving path from the main highway to the ramp based on the current location of the target vehicle and the preset destination location.

[0116] The third determining submodule is used to determine the navigation information based on the driving path and the map information, and to determine the trajectory point information based on the driving path.

[0117] In one possible implementation, the second determining submodule includes: a second determining unit, a third determining unit, and a fourth determining unit, wherein:

[0118] The second determining unit is used to determine whether a deceleration lane exists on the ramp based on the map information;

[0119] The third determining unit is used to determine the driving path from the highway main road to the deceleration lane based on the current position of the target vehicle and the preset destination position set on the deceleration lane when there is a deceleration lane on the ramp.

[0120] The fourth determining unit is used to determine the driving path from the main highway to the ramp based on the current position of the target vehicle and the preset destination position set on the ramp, when there is no deceleration lane on the highway.

[0121] The third determination submodule is also used for:

[0122] Starting from the current position of the target vehicle, trajectory points are selected in the driving path according to a preset trajectory point interval strategy, and trajectory point information is generated; the preset trajectory point interval strategy is to select a first preset number of trajectory points according to a first preset interval, and select a second preset number of trajectory points according to a second preset interval.

[0123] The autonomous vehicle control device provided in this embodiment can be used to execute the autonomous vehicle control method provided in any of the above method embodiments. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0124] The collection, storage, use, processing, transmission, provision, and disclosure of user personal information involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0125] According to embodiments of this application, this application also provides an electronic device and a computer-readable storage medium.

[0126] Figure 7This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device includes a receiver 70, a transmitter 71, a processor 72, and a memory 73. The electronic device composed of the above components can be used to implement the above-described specific embodiments of this application, which will not be described in detail here.

[0127] This application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the steps of the methods described above.

[0128] This application also provides a computer program product, including computer instructions that, when executed by a processor, implement the various steps in the methods described above.

[0129] Various embodiments of the systems and technologies described above in this application can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0130] The program code used to implement the methods of this application may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing device, such that when executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or electronic device.

[0131] In the context of this application, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0132] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0133] The systems and technologies described herein can be implemented in computing systems that include back-end components (e.g., as data electronic devices), or computing systems that include middleware components (e.g., application electronic devices), or computing systems that include front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0134] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this application can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this application can be achieved, and this is not limited herein.

[0135] The specific embodiments described above do not constitute a limitation on the scope of protection of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this application should be included within the scope of protection of this application.

Claims

1. A method for controlling an autonomous vehicle, characterized in that, include: Obtain the target vehicle's location and map information; Based on the location information, the current location of the target vehicle is determined in the map information; Determine whether a deceleration lane exists on the ramp based on the map information; When a deceleration lane exists on the ramp, a path planning algorithm is used to determine the driving path from the main highway into the deceleration lane based on the current position of the target vehicle and the preset destination position set on the deceleration lane. Based on the lane lines of the current highway main road and the lane lines of the ramps in the indexed high-precision map, a trajectory line is fitted from the center line of the highway main road lane to the center line of the deceleration lane when the width of the deceleration lane gradually increases to be greater than the width of the target vehicle. In the absence of a deceleration lane on the ramp, a path planning algorithm is used to determine the driving path from the main highway to the ramp based on the current position of the target vehicle and the preset destination position set on the ramp. Based on the lane lines of the current main highway and the ramp in the indexed high-precision map, a trajectory line is fitted from the center line of the main highway lane to the center line of the ramp lane, while satisfying the minimum turning radius of the target vehicle. Navigation information is determined based on the driving path and map information. Starting from the current position of the target vehicle, trajectory points are selected along the driving path using a preset trajectory point interval strategy, and trajectory point information is generated. The preset trajectory point interval strategy involves selecting a first preset number of trajectory points at a first preset interval and a second preset number of trajectory points at a second preset interval. The trajectory point information reflects the path information of the driving path from the main highway to the ramp. The navigation information includes the next navigation lane change sign and the distance from the target vehicle to the next navigation lane change point. The next navigation lane change sign is determined as follows: during the path planning process connecting the current position of the vehicle to the destination, the point where the road ID changes is calculated, and the lane types before and after the point are calculated. If the point before the lane change sign is a main highway and the point after the lane change sign is a ramp, then the lane change sign is determined accordingly. If the target vehicle is located at the next navigation lane change point, the next navigation lane change sign will be the right-turn ramp on the main highway. The distance from the target vehicle to the next navigation lane change point is determined as follows: During the path planning process from the current location of the vehicle to the destination location, the points where the road ID changes are calculated, and the arc distance from the current location to that point in the Frenet coordinate system is calculated. If the arc distance is ≥ 5000m, the distance to the next navigation lane change point is equal to 5000m; if the arc distance is < 5000m, the distance to the next navigation lane change point is the arc distance. The trajectory point information includes: the heading of the trajectory point in the target vehicle coordinate system, the x-coordinate of the trajectory point in the target vehicle coordinate system, the y-coordinate of the trajectory point in the target vehicle coordinate system, the longitudinal slope of the road at the trajectory point, the lateral slope of the road at the trajectory point, the curvature of the road at the trajectory point, and the speed limit of the road at the trajectory point. The system uses a preset decision algorithm to determine whether the next navigation lane change sign is a sign for entering the ramp from the right on the main highway, and whether the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold. If the next navigation lane change sign is a sign indicating a right turn onto a ramp from the main highway, and the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold, then entering the trajectory point mode will be determined as decision information. When the decision information indicates entering the trajectory point mode, the target vehicle is controlled by outputting corresponding lateral control commands and longitudinal control commands based on the trajectory point information. The lateral control commands include steering wheel angle requests, and the longitudinal control commands include acceleration torque requests and deceleration requests.

2. An autonomous vehicle control device, characterized in that, include: A high-precision positioning module is used to acquire the positioning information of the target vehicle; A high-precision map module is used to acquire map information; The route planning module is used to determine the current position of the target vehicle from the map information; and to determine whether a deceleration lane exists on the ramp based on the map information. When a deceleration lane exists on the ramp, a path planning algorithm is used to determine the driving path from the main highway into the deceleration lane based on the current position of the target vehicle and the preset destination position set on the deceleration lane. Based on the lane lines of the current highway main road and ramps in the indexed high-precision map, a trajectory line is fitted from the center line of the highway main road lane to the center line of the deceleration lane where the width of the deceleration lane gradually increases to be greater than the width of the target vehicle. If there is no deceleration lane on the ramp, a path planning algorithm is used to determine the driving path from the highway main road to the ramp based on the current position of the target vehicle and the preset destination position set on the ramp. Based on the lane lines of the current highway main road and ramps in the indexed high-precision map, a path is fitted while satisfying the minimum turning radius of the target vehicle. A trajectory line is drawn from the center line of the highway main road lane to the center line of the ramp lane; navigation information is determined based on the driving path and the map information, and starting from the current position of the target vehicle, trajectory points are selected in the driving path according to a preset trajectory point interval strategy, and trajectory point information is generated; the preset trajectory point interval strategy is to select a first preset number of trajectory points according to a first preset interval and a second preset number of trajectory points according to a second preset interval; wherein, the trajectory point information is used to reflect the path information of the driving path from the highway main road to the ramp; the navigation information includes: the next navigation... The lane change sign and the distance from the target vehicle to the next navigation lane change point; the next navigation lane change sign is determined as follows: during the path planning process from the vehicle's current location to the destination location, the points where the road ID changes are calculated, and the types of lanes before and after that point are calculated. If the point before the point is a highway and the point after the point is a ramp, then the next navigation lane change sign is a right-turn ramp on a highway; the distance from the target vehicle to the next navigation lane change point is determined as follows: during the path planning process from the vehicle's current location to the destination location, the road ID changes are calculated... The system calculates the arc distance from the current location to that point in the Frenet coordinate system. If the arc distance is ≥ 5000m, the distance to the next navigation lane change point is 5000m; if the arc distance is < 5000m, the distance to the next navigation lane change point is the arc distance. The trajectory point information includes: the heading of the trajectory point in the target vehicle coordinate system, the x-coordinate of the trajectory point in the target vehicle coordinate system, the y-coordinate of the trajectory point in the target vehicle coordinate system, the longitudinal slope of the road at the trajectory point, the lateral slope of the road at the trajectory point, the curvature of the road at the trajectory point, and the speed limit of the road at the trajectory point. The control module is used to control the target vehicle based on the navigation information and the trajectory point information; The control module is specifically configured to: determine, using a preset decision algorithm, whether the next navigation lane change sign is a sign indicating a right-turn ramp from a highway main road, and whether the distance from the target vehicle to the next navigation lane change point is less than or equal to a preset threshold; if the next navigation lane change sign is a sign indicating a right-turn ramp from a highway main road, and the distance from the target vehicle to the next navigation lane change point is less than or equal to the preset threshold, determine entering the trajectory point mode as decision information; if the decision information is entering the trajectory point mode, output corresponding lateral control commands and longitudinal control commands to control the target vehicle based on the trajectory point information, wherein the lateral control commands include a steering wheel angle request, and the longitudinal control commands include an acceleration torque request and a deceleration request.

3. An electronic device, characterized in that, include: At least one processor and memory; The memory stores computer-executed instructions; The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the autonomous vehicle control method as described in claim 1.

4. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the autonomous vehicle control method as described in claim 1.

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