A vehicle travel road selection method and system, a vehicle-mounted control device, and a vehicle

Abstract

This application provides a vehicle driving route selection method and system, on-board control equipment, and vehicle, including: identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road; when the current road is congested, synchronous positioning and map construction are performed through sensor data to generate perception information of the target vehicle; then, the driving speed of the target vehicle is calculated based on the driving data, and the perception information of the target vehicle and the number of lanes on the current road are correlated to generate a road selection strategy for the target vehicle; simultaneously, the target vehicle is controlled to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change. This application can quickly obtain lanes with relatively short travel times on the current road by using the driving data of the current vehicle and the map data of the current road, thereby reducing the travel time of the target vehicle on the current road.

Description

Technical Field

[0001] This application relates to the field of vehicle control technology, and in particular to a method and system for selecting a vehicle driving route, on-board control equipment, and a vehicle. Background Technology

[0002] With the continuous updating and improvement of intelligent driving system technology, many models are now equipped with intelligent driving functions. These functions use devices such as LiDAR and cameras to update perception information in a timely manner and help drivers navigate the vehicle on the road, thereby improving the driver's driving experience.

[0003] However, currently available intelligent driving functions can only assist drivers on a single road. When there is congestion ahead, they will only follow the vehicle in front at a slow speed and cannot change lanes in time or prompt the driver to move to a lane with faster traffic flow when approaching a congested section. Furthermore, manual driving may also be unable to make quick judgments due to unfamiliarity with the road ahead. Therefore, how to help drivers identify the lane with the fastest traffic flow in congested roads in advance and quickly pass through congested sections is a problem that urgently needs to be solved. Summary of the Invention

[0004] In view of the shortcomings of the prior art described above, the purpose of this application is to provide a vehicle driving road selection method and system, on-board control equipment and vehicle, to solve the technical problems in the prior art.

[0005] To achieve the above and other related objectives, this application provides a method for selecting a vehicle driving route, comprising the following steps:

[0006] The traffic status of the current road is identified based on the map data of the current road and the driving data of the target vehicle on the current road. The traffic status includes: congestion status and normal traffic status; wherein, the current road includes at least one lane.

[0007] When the road is congested, the system uses sensor data to perform synchronous positioning and map construction to generate perception information for the target vehicle; wherein, the sensor data is generated by sensors pre-configured on the target vehicle.

[0008] The driving speed of the target vehicle is calculated based on the driving data of the target vehicle on the current road, and the perception information of the target vehicle and the number of lanes on the current road are associated to generate the road selection strategy of the target vehicle.

[0009] The target vehicle is controlled to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change.

[0010] In one embodiment of this application, the process of identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road includes:

[0011] Based on the map data of the current road, acquire the speed and geographical location data of multiple vehicles. If the real-time speed of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed, or the geographical location change distance of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset distance, then the corresponding road segment is recorded as a target road segment, and the traffic status of the target road segment is marked as congested; and,

[0012] Based on the driving data of the target vehicle on the target road segment, the distance between the target vehicle and the vehicle in front is obtained, and the average driving speed of the vehicle in front is calculated through the distance between the two vehicles within a preset time period; and, based on the speed limit of the target road segment and the average driving speed of the vehicle in front within the preset time period, the traffic status of the target vehicle on the target road segment is determined; wherein, the vehicle in front is located in front of the target vehicle.

[0013] The current road traffic status is determined based on the traffic status of the target road segment and the traffic status of the target vehicle on the target road segment.

[0014] In one embodiment of this application, the process of generating perception information for the target vehicle by synchronously locating and mapping using sensor data includes:

[0015] The sensor data is generated by acquiring laser point cloud data of the surrounding environment of the target vehicle through a pre-configured lidar on the target vehicle, and by collecting view data through an image capturing device pre-configured on the target vehicle.

[0016] Using the sensor data, synchronous positioning and map construction are performed to generate the motion equation and observation equation of the target vehicle; wherein, the motion equation is used to characterize the pose change of the target vehicle at different times, and the observation equation is used to characterize the surrounding environmental features observed by the target vehicle at different poses.

[0017] The perception information of the target vehicle is generated based on the motion equation and observation equation of the target vehicle.

[0018] In one embodiment of this application, if the current road includes only one lane, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes:

[0019] The system acquires the real-time speed of the vehicle ahead and the deceleration of the target vehicle; wherein the vehicle ahead is located in front of the target vehicle.

[0020] Based on the real-time speed of the vehicle in front and the deceleration of the target vehicle, calculate the minimum safe distance between the target vehicle and the vehicle in front.

[0021] The road selection strategy is set to follow without changing lanes; and the target vehicle is controlled to follow the vehicle in front at the minimum safe distance for normal driving.

[0022] In one embodiment of this application, if the current road includes only two lanes, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes:

[0023] Based on the perception information of the target vehicle, identify whether there is a vehicle in front of the target vehicle in the current lane and the adjacent lane, and compare the speeds of the vehicle in front of the target vehicle in the current lane and the vehicle in front of the adjacent lane when there is a vehicle in front of the target vehicle in the current lane and the vehicle in front of the adjacent lane.

[0024] If the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to change to the adjacent lane, and the target vehicle is controlled to change from the current lane to the adjacent lane based on the perception information of the target vehicle.

[0025] If the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the adjacent lane, the road selection strategy is set to follow without changing lanes; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

[0026] In one embodiment of this application, if the current road includes only three or more lanes, a road selection strategy for the target vehicle is generated, and the process of controlling the target vehicle to change lanes according to the road selection strategy includes:

[0027] The lane position of the target vehicle is identified based on the perception information of the target vehicle;

[0028] When the target vehicle is in the middle lane of the current road, the system identifies whether there are vehicles in front of the target vehicle in the current lane, the left lane, and the right lane based on the target vehicle's perception information; and when there is a vehicle in front in the current lane, a vehicle in front in the left lane, and a vehicle in front in the right lane, the system compares the speeds of the vehicle in front in the current lane with those of the vehicles in front in the left lane and the vehicles in front in the right lane, respectively.

[0029] If the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane or the speed of the vehicle in front of the right lane, the road selection strategy is determined to change to the lane with the fastest speed, and the target vehicle is controlled to change from the current lane to the corresponding lane based on the perception information of the target vehicle.

[0030] If the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the left lane, and greater than or equal to the speed of the vehicle ahead in the right lane, then the road selection strategy is determined to be following, and no lane change is performed; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

[0031] In one embodiment of this application, when identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road, the method further includes:

[0032] The traffic status obtained based on the map data of the current road is recorded as the map traffic status, and the traffic status obtained based on the driving data of the target vehicle on the current road is recorded as the driving traffic status.

[0033] Determine whether the map traffic status is consistent with the driving traffic status;

[0034] If the map traffic status is consistent with the driving traffic status, then the map traffic status or the driving traffic status shall be taken as the current road traffic status;

[0035] If the map traffic status is inconsistent with the driving traffic status, the driving traffic status is taken as the current road traffic status; and the current road traffic status is uploaded to the cloud and pushed to other vehicles connected to the cloud.

[0036] This application also provides a vehicle driving route selection system, the system comprising:

[0037] The traffic status module is used to identify the traffic status of the current road based on the map data of the current road and the driving data of the target vehicle on the current road. The traffic status includes: congestion status and normal traffic status; wherein, the current road includes at least one lane.

[0038] The perception information module is used to generate perception information of the target vehicle by synchronously locating and building a map using sensor data when the current road is congested; wherein, the sensor data is generated by sensors pre-configured on the target vehicle.

[0039] The road selection strategy module is used to calculate the driving speed of the target vehicle based on the driving data of the target vehicle on the current road, and associate the perception information of the target vehicle with the number of lanes on the current road to generate the road selection strategy of the target vehicle.

[0040] The lane change module is used to control the target vehicle to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change.

[0041] This application also provides an on-board control device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the vehicle driving road selection method described in any one of the above.

[0042] This application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the vehicle driving road selection method described in any one of the above.

[0043] As described above, this application provides a vehicle driving road selection method and system, an on-board control device, and a vehicle, which has the following beneficial effects: This application first identifies the traffic status of the current road based on the map data of the current road and the driving data of the target vehicle on the current road. When the current road is congested, synchronous positioning and map construction are performed through sensor data to generate the perception information of the target vehicle. Then, the driving speed of the target vehicle is calculated based on the driving data of the target vehicle on the current road, and the perception information of the target vehicle and the number of lanes of the current road are associated to generate the road selection strategy of the target vehicle. At the same time, the target vehicle is controlled to change lanes according to the road selection strategy so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change. Therefore, this application addresses the challenges of choosing the fastest route in congested traffic conditions due to the current limitations of intelligent driving technology, and the inability of manual driving to select the optimal route due to uncertainty about road conditions. By combining current vehicle driving data with map data of the current road, it can quickly identify lanes with relatively short travel times. When a target vehicle is controlled to move to a lane with a shorter travel time, its travel time on the current road can be reduced. Furthermore, by uploading the current road traffic status to the cloud, it can push the traffic status to other vehicles connected to the cloud, helping their drivers identify the lanes with the fastest traffic flow in congested areas and allowing them to change lanes in advance to the optimal route and quickly pass through congested sections. If other vehicles are using intelligent driving mode, they can also change lanes in advance based on the cloud-push traffic status, greatly improving the driver's experience, enhancing human-computer interaction, and reducing driver fatigue. Attached Figure Description

[0044] Figure 1 This is a schematic flowchart of a vehicle driving road selection method provided in one embodiment of this application;

[0045] Figure 2 This is a schematic diagram of a target vehicle traveling on a road segment, as provided in one embodiment of this application.

[0046] Figure 3 This is a schematic diagram illustrating the principle of a vehicle driving road selection method provided in one embodiment of this application;

[0047] Figure 4 This is a schematic diagram of the hardware structure of a vehicle driving route selection system provided in an embodiment of this application;

[0048] Figure 5 This is a schematic diagram of the hardware structure of an in-vehicle control device suitable for implementing one or more embodiments of this application. Detailed Implementation

[0049] The following specific examples illustrate the implementation of this application. Those skilled in the art can easily understand other advantages and effects of this application from the content disclosed in this specification. This application can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of this application. It should be noted that, unless otherwise specified, the following embodiments and features in the embodiments can be combined with each other.

[0050] It should be noted that the illustrations provided in this embodiment are only schematic representations of the basic concept of this application. Therefore, the illustrations only show the components related to this application and are not drawn according to the actual number, shape and size of the components in the actual implementation. In the actual implementation, the form, quantity and proportion of each component can be arbitrarily changed, and the layout of the components may also be more complex.

[0051] Figure 1 A schematic flowchart of a vehicle driving route selection method according to an embodiment of this application is shown. Specifically, in an exemplary embodiment, as follows... Figure 1 As shown, this embodiment provides a method for selecting a vehicle's driving route, which includes the following steps:

[0052] S110, the traffic status of the current road is identified based on the map data of the current road and the driving data of the target vehicle on the current road. The traffic status includes: congestion status and normal traffic status; wherein, the current road includes at least one lane. In this embodiment or other embodiments, the target vehicle can be a vehicle determined in advance or in real time, such as a vehicle with both intelligent driving and manual driving functions, or a vehicle with only manual driving functions, or a vehicle with only intelligent driving functions. In this embodiment or other embodiments, the target vehicle can also be referred to as a self-driving vehicle. In this embodiment or other embodiments, the traffic status of the current road identified based on the map data of the current road and the driving data of the target vehicle on the current road can be stored in the vehicle controller (Electronic Control Unit, abbreviated as ECU).

[0053] S120, when the current road is congested, synchronous positioning and map construction are performed using sensor data to generate perception information of the target vehicle; wherein, the sensor data is generated by sensors pre-configured on the target vehicle. As an example, in this embodiment or other embodiments, the sensors pre-configured on the target vehicle include, but are not limited to, LiDAR, millimeter-wave radar, ultrasonic radar, and image capturing devices (e.g., cameras).

[0054] S130: Calculate the target vehicle's speed based on the target vehicle's driving data on the current road, and associate the target vehicle's perception information with the number of lanes on the current road to generate the target vehicle's road selection strategy.

[0055] S140 controls the target vehicle to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change.

[0056] Therefore, this embodiment addresses the challenges of choosing the fastest route in congested traffic conditions due to the limitations of current intelligent driving technology, and the inability of manual driving to select the optimal route due to uncertainty about the road ahead. By utilizing the vehicle's current driving data and the map data of the current road, it can quickly identify the lane with the shortest travel time within a short period. When the target vehicle is controlled and moved to the lane with the shorter travel time, its travel time on the current road can be reduced. Thus, this embodiment can help drivers identify the lane with the fastest traffic flow in congested roads in advance and quickly pass through congested sections.

[0057] In an exemplary embodiment, the process of identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road includes: acquiring vehicle speed data and geographical location data of multiple vehicles based on map data of the current road; if the real-time speed of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed, or the geographical location change distance of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset distance, then the corresponding road segment is recorded as a target road segment, and the traffic status of the target road segment is marked as congested; and, based on the driving data of the target vehicle on the target road segment, acquiring the distance between the target vehicle and the vehicle in front, and calculating the average driving speed of the vehicle in front within a preset time period using the distance between the two vehicles; and, based on the speed limit of the target road segment and the average driving speed of the vehicle in front within the preset time period, determining the traffic status of the target vehicle on the target road segment; wherein the vehicle in front is located in front of the target vehicle; and determining the traffic status of the current road based on the traffic status of the target road segment and the traffic status of the target vehicle on the target road segment. As an example, in this embodiment or other embodiments, the preset quantity and preset speed can be set according to the actual situation, and this embodiment does not limit the specific values.

[0058] Specifically, such as Figure 2 As shown, Figure 2 This diagram illustrates the target vehicle traveling on a certain road segment. Figure 2In the diagram, A represents the target vehicle, B and C represent vehicles ahead of target vehicle A, P is the camera position of target vehicle A, image plane I is generated by projecting the points of vehicles B and C through point P, f is the camera focal length, H is the camera height, y1 and y2 are the distances of vehicles B and C projected onto the zero point of image plane I, and z1 and z2 are the distances of vehicles B and C from target vehicle A. Therefore, the process of determining the traffic status of the target vehicle on the target road segment in this embodiment can be as follows: Using the formula for similar triangles, we know that... At the same time from Figure 2 As can be seen, the farther the vehicle is from the horizontal, the smaller the distance y between the bottom of the vehicle and the horizontal line in image plane I. The distance y from the zero point of the projected vehicle onto image plane I can be obtained by transforming the coordinate system after the camera P takes a picture of the vehicle in front. Therefore, the average speed v of the vehicle in front during the time period Δt can be expressed as: This allows us to calculate the average speed of the vehicle ahead within a time period Δt. Then, by using map data from map software, we can obtain the speed limit for the current road segment. If the average speed v of the vehicle ahead within time period Δt is less than 30% of the speed limit, then the lane containing the target vehicle can be considered congested; the same applies to other lanes. If the target vehicle uploads the congestion information to the cloud, other vehicles connected to the cloud in the current road segment can also receive this congestion information. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, it can do so through the vehicle controller within the target vehicle.

[0059] In an exemplary embodiment, identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road may further include: recording the traffic status obtained based on the map data of the current road as the map traffic status, and recording the traffic status obtained based on the driving data of the target vehicle on the current road as the driving traffic status; determining whether the map traffic status and the driving traffic status are consistent; if the map traffic status and the driving traffic status are consistent, then using either the map traffic status or the driving traffic status as the traffic status of the current road; if the map traffic status and the driving traffic status are inconsistent, then using the driving traffic status as the traffic status of the current road; and uploading the traffic status of the current road to the cloud and pushing the traffic status of the current road to other vehicles connected to the cloud. Therefore, this embodiment, in identifying the traffic status of the current road, also determines the priority of map data and driving data. Since driving data is real-time and accurate, this embodiment can avoid the delay error caused by map data by using the driving traffic status as the traffic status of the current road when the map traffic status and the driving traffic status are inconsistent. Meanwhile, this embodiment uploads the current road traffic status to the cloud, which can then push the current road traffic status to other vehicles connected to the cloud. This helps drivers of other vehicles identify the lane with the fastest traffic flow in congested roads in advance, allowing them to change lanes to the optimal route and quickly pass through congested sections. If other vehicles are using intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed from the cloud, greatly improving the driver's driving experience, enhancing the stickiness of human-computer interaction, and helping to reduce driver fatigue.

[0060] In an exemplary embodiment, the process of generating perception information of a target vehicle through simultaneous localization and mapping (SLAM) using sensor data includes: acquiring laser point cloud data of the surrounding environment of the target vehicle using a pre-configured LiDAR on the target vehicle, and constructing sensor data using view data collected by an image capturing device pre-configured on the target vehicle; using the sensor data for SLAM to construct and generate motion equations and observation equations for the target vehicle; wherein the motion equations characterize the pose changes of the target vehicle at different times, and the observation equations characterize the surrounding environment features observed by the target vehicle at different poses; and generating perception information of the target vehicle based on the motion equations and observation equations. Specifically, in this embodiment, when the current road is congested, the lane information of the target vehicle can be fed back through the Simultaneous Localization and Mapping (SLAM) method. For example, laser point cloud data of the surrounding environment of the target vehicle can be acquired through LiDAR. LiDAR can measure the angle and distance of objects around the car with high accuracy. Visually, data collected by a camera is used for SLAM. At the same time, the perception information of the target vehicle can be regarded as a mathematical modeling process, thus having the motion equation x k =f(x) k-1 )+u k-1 and observation equation y k =h(x k )+v k In the equations of motion, x k Let f(x) represent the pose of the target vehicle at time k, which is derived from the pose at time k-1. k-1 The actual environment may have errors, therefore a noise factor u is added. k-1 This imposes certain constraints on pose changes. In the observation equation, y k The sensor observation at time k represents the current target vehicle pose h(x). k ) decided, v k This is to account for errors caused by the actual environmental conditions. In this embodiment, the equation of motion describes the pose x at time k-1. k-1 How does the pose x change to time k? k The observation equation describes how to obtain the pose x at time k. k Obtain observation data y k Therefore, by using motion equations and observation equations, we can more realistically reflect the actual position and orientation of the target vehicle in relation to the current environment.

[0061] In an exemplary embodiment, if the current road includes only one lane, generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: obtaining the real-time speed of the vehicle in front and the deceleration of the target vehicle; wherein the vehicle in front is located in front of the target vehicle; calculating the minimum safe distance between the target vehicle and the vehicle in front based on the real-time speed of the vehicle in front and the deceleration of the target vehicle; determining the road selection strategy as following without changing lanes; and controlling the target vehicle to follow the vehicle in front normally according to the minimum safe distance. In this embodiment or other embodiments, the process of calculating the minimum safe distance between the target vehicle and the vehicle in front may be: In the formula, MSFD represents the minimum safe distance between the target vehicle and the vehicle in front, s p This indicates the real-time speed of the vehicle ahead, and de indicates the deceleration of the target vehicle.

[0062] In an exemplary embodiment, if the current road includes only two lanes, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: identifying whether there are vehicles in front of the target vehicle in the current lane and the adjacent lane based on the target vehicle's perception information; comparing the speeds of the vehicles in front of the target vehicle in the current lane and the adjacent lane when there are vehicles in front of both lanes; if the speed of the vehicle in front of the target vehicle in the current lane is less than the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to change to the adjacent lane, and the target vehicle is controlled to change from the current lane to the adjacent lane based on the target vehicle's perception information; if the speed of the vehicle in front of the target vehicle in the current lane is greater than or equal to the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to follow without changing lanes; and controlling the target vehicle to follow the vehicle in front of the target vehicle in the current lane at a minimum safe distance for normal driving.

[0063] In an exemplary embodiment, if the current road includes only three or more lanes, a road selection strategy for the target vehicle is generated. The process of controlling the target vehicle to change lanes according to the road selection strategy includes: identifying the lane position of the target vehicle based on the target vehicle's perception information; when the target vehicle is in the middle lane of the current road, identifying whether there are vehicles in front of the target vehicle in the current lane, the left lane, and the right lane based on the target vehicle's perception information; and, when there are vehicles in front in the current lane, the left lane, and the right lane, respectively, controlling the vehicles in front in the current lane, the vehicles in front in the left lane, and the vehicles in front in the right lane. A speed comparison is performed; if the speed of the vehicle ahead in the current lane is less than the speed of the vehicle ahead in the left lane or the speed of the vehicle ahead in the right lane, the road selection strategy is determined to change to the lane with the fastest speed, and the target vehicle is controlled to change from the current lane to the corresponding lane based on the target vehicle's perception information; if the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the left lane, and greater than or equal to the speed of the vehicle ahead in the right lane, the road selection strategy is determined to follow, and no lane change is performed; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

[0064] Specifically, as an example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the left lane is less than the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the right lane, and the target vehicle is controlled to change from the current lane to the right lane based on the target vehicle's perception information.

[0065] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, while the speed of the vehicle in front of the left lane is greater than the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the left lane, and the target vehicle is controlled to change from the current lane to the left lane based on the target vehicle's perception information.

[0066] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, while the speed of the vehicle in front of the left lane is equal to the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed. That is, the road selection strategy is determined to change to the left lane or the right lane, and the target vehicle is controlled to change from the current lane to the left lane or the right lane based on the target vehicle's perception information.

[0067] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the right lane is less than the speed of the vehicle in front of the left lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the left lane, and the target vehicle is controlled to change from the current lane to the left lane based on the target vehicle's perception information.

[0068] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, while the speed of the vehicle in front of the right lane is greater than the speed of the vehicle in front of the left lane, then the road selection strategy is determined to change to the lane with the fastest speed. That is, the road selection strategy is determined to change to the right lane, and the target vehicle is controlled to change from the current lane to the right lane based on the target vehicle's perception information.

[0069] In another exemplary embodiment of this application, the embodiment also provides a method for selecting a driving route during road congestion, the principle of which is illustrated in the following diagram. Figure 3 As shown. Specifically, as Figure 3 As shown, the method includes the following steps:

[0070] Step S1: The vehicle is driving normally along the navigation. The map software can provide feedback on the current traffic information. The map software can determine whether there is congestion by collecting and analyzing user-generated content (UGC) data. This method uploads information such as vehicle speed and GPS (Global Positioning System) location during the user's use of the map software to the background for analysis. The analysis updates the traffic conditions in real time. If multiple users are traveling slowly on the same road segment, it will be considered congested. When the target vehicle reaches the congested road segment, the map software actively interacts with the vehicle controller ECU to proceed to step S2.

[0071] Step S2: With navigation disabled, if the driver encounters traffic congestion while driving, the congestion information will be reported to the vehicle's ECU. For example... Figure 2 As shown, in Figure 2 In the diagram, A represents the target vehicle, B and C represent vehicles ahead of target vehicle A, P is the camera position of target vehicle A, image plane I is generated by projecting the points of vehicles B and C through point P, f is the camera focal length, H is the camera height, y1 and y2 are the distances of vehicles B and C projected onto the zero point of image plane I, and z1 and z2 are the distances of vehicles B and C from the target vehicle A. Therefore, this embodiment can determine whether there is congestion based on vehicle driving data using the following process: The formula for similar triangles shows that... At the same time from Figure 2 As can be seen, the farther the vehicle is from the horizontal, the smaller the distance y between the bottom of the vehicle and the horizontal line in image plane I. The distance y from the zero point of the projected vehicle onto image plane I can be obtained by transforming the coordinate system after the camera P takes a picture of the vehicle in front. Therefore, the average speed v of the vehicle in front during the time period Δt can be expressed as: This allows us to calculate the average speed of the vehicle ahead within a time period Δt. Then, by using map data from map software, we can obtain the speed limit for the current road segment. If the average speed v of the vehicle ahead within time period Δt is less than 30% of the speed limit, then the lane containing the target vehicle can be considered congested; the same applies to other lanes. If the target vehicle uploads the congestion information to the cloud, other vehicles connected to the cloud in the current road segment can also receive this congestion information. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, it can do so through the vehicle controller within the target vehicle.

[0072] Step S3: After the vehicle controller (ECU) receives the reported road congestion information, the control perception system acquires road information. It can feed back the lane information of the target vehicle using Simultaneous Localization and Mapping (SLAM) methods. For example, it can acquire laser point cloud data of the surrounding environment of the target vehicle using LiDAR. LiDAR can measure the angle and distance of objects around the car with high accuracy. Visually, data collected by cameras is used for SLAM. Simultaneously, the perception information of the target vehicle can be considered as a mathematical modeling process, resulting in the motion equation x. k =f(x) k-1 )+u k-1 and observation equation y k =h(x k )+v k In the equations of motion, x kLet f(x) represent the pose of the target vehicle at time k, which is derived from the pose at time k-1. k-1 The actual environment may have errors, therefore a noise factor u is added. k-1 This imposes certain constraints on pose changes. In the observation equation, yk represents the sensor observation value at time k, which is determined by the current target vehicle pose h(xk), and v k This is to account for errors caused by the actual environmental conditions. In this embodiment, the equation of motion describes the pose x at time k-1. k-1 How does the pose x change to time k? k The observation equation describes how to obtain the pose x at time k. k Obtain observation data y k Therefore, by using motion equations and observation equations, we can more realistically reflect the actual position and orientation of the target vehicle in relation to the current environment.

[0073] Step S4: Calculate the target vehicle's position using the speed calculation in step S2 and the perception information in step S3. This will give you the relative position of the target vehicle to other vehicles. Processing can be performed on single-lane, two-lane, and three-lane or higher vehicles respectively.

[0074] Specifically, in the first scenario, a single lane. If there is only a single lane or the lane is a solid line, the real-time speed of the vehicle ahead and the deceleration of the target vehicle are obtained; wherein, the vehicle ahead is located in front of the target vehicle; based on the real-time speed of the vehicle ahead and the deceleration of the target vehicle, the minimum safe distance between the target vehicle and the vehicle ahead is calculated; the road selection strategy is determined to follow, without lane changing; and the target vehicle is controlled to follow the vehicle ahead normally at the minimum safe distance. The process of calculating the minimum safe distance between the target vehicle and the vehicle ahead can be as follows: In the formula, MSFD represents the minimum safe distance between the target vehicle and the vehicle in front, s p This indicates the real-time speed of the vehicle ahead, and de indicates the deceleration of the target vehicle.

[0075] The second scenario involves two lanes. Based on the target vehicle's perception information, it identifies whether there are vehicles in front of the target vehicle in the current lane and the adjacent lane. If there are vehicles in front in both the current lane and the adjacent lane, their speeds are compared. If the speed of the vehicle in front in the current lane is less than the speed of the vehicle in front in the adjacent lane, the road selection strategy is determined to change to the adjacent lane, and the target vehicle is controlled to change from the current lane to the adjacent lane based on the target vehicle's perception information from step S3. If the speed of the vehicle in front in the current lane is greater than or equal to the speed of the vehicle in front in the adjacent lane, the road selection strategy is determined to follow, and no lane change is performed. The target vehicle is then controlled to follow the vehicle in front in the current lane at the minimum safe distance.

[0076] In the third scenario, with three or more lanes, the target vehicle's lane position is identified based on its perception information from step S3. When the target vehicle is in the middle lane of the current road, the system identifies whether there are vehicles in front of the target vehicle in the current lane, the left lane, and the right lane, based on the target vehicle's perception information. Furthermore, if there is a vehicle in front in the current lane, the left lane, or the right lane, the speeds of the vehicles in front in the current lane, the left lane, and the right lane are compared. If the speed of the vehicle in front in the current lane is less than the speed of the vehicle in front in the left lane or the right lane, the road selection strategy is determined to change to the lane with the fastest speed, and the target vehicle is controlled to change from the current lane to the corresponding lane based on its perception information. If the speed of the vehicle in front in the current lane is greater than or equal to the speed of the vehicle in front in the left lane, and also greater than or equal to the speed of the vehicle in front in the right lane, the road selection strategy is determined to follow, without changing lanes. Finally, the target vehicle is controlled to follow the vehicle in front in the current lane at the minimum safe distance.

[0077] Step S5: After receiving the information from the vehicle controller ECU, the cockpit control system provides voice and text pop-up prompts. If the driver is in manual driving mode, only text and voice prompts are provided for one-way communication without driver feedback. If the driver is in intelligent driving mode, they can ask whether to change lanes to the adjacent lane. After receiving the user's feedback, the cockpit control system sends the information back to the vehicle controller ECU. If the user indicates that they do not need to change lanes, the vehicle continues to drive in the current lane. If the user indicates that they need to change lanes, the vehicle controller ECU then sends the information to the intelligent driving control system, which controls the vehicle to change lanes.

[0078] Step S6: When the vehicle controller ECU receives a congestion signal, it calculates the lane with the fastest traffic flow as in step S4 and simultaneously synchronizes this information to the vehicle cloud system. The vehicle cloud system is a large cloud system, and all vehicles of the same model driven by the driver are in the same vehicle cloud environment. If the vehicle cloud system receives congestion information reported by the vehicle controller ECU, it will record the specific road segment, time, and the optimal lane information processed by the vehicle controller ECU in the driver's target vehicle. At the same time, if other vehicles under the same vehicle cloud system, whether in intelligent driving or manual driving, are about to enter or have already entered the current congested road segment within a similar time period, they will receive the optimal lane information from the vehicle cloud system and receive voice and text prompts. Through human-machine interaction, they can also automatically enter the optimal lane in intelligent driving mode. If the vehicle controller ECU in the target vehicle has already uploaded congestion information, lane information, and time information to the vehicle cloud system, it will no longer receive information from the vehicle cloud system to avoid blocking the channel between the vehicle controller ECU and the vehicle cloud system.

[0079] Therefore, this embodiment addresses the current limitations of intelligent driving technology in selecting the fastest route through congested traffic, and the potential inability to choose the optimal route in manual driving mode due to uncertainty about road conditions. This embodiment utilizes navigation, target vehicle driving information, and vehicle-to-cloud (V2X) system interaction to accurately identify current road congestion. In congested situations, the vehicle's ECU (Electronic Control Unit) can quickly coordinate with related components to identify the optimal route. After identifying the optimal route, the ECU uploads the information to the V2X system, which then distributes the road information to vehicles about to enter the congested area. This cloud-based distribution helps drivers identify and select the optimal lane before entering the congested section, resulting in a better driving experience. Therefore, this embodiment, through interaction between the target vehicle and the V2X system, significantly improves the time for rapid passage through congested areas. Regardless of whether the driver is in intelligent or manual driving mode, they can quickly obtain lane information and the fastest route information, enabling them to quickly navigate congested areas and achieve a better driving experience. Furthermore, by incorporating the interaction of the vehicle-cloud system, this embodiment greatly optimizes the system response time, allowing drivers to perceive information about current traffic congestion in advance and quickly helping them choose the optimal route. In manual driving mode, it can prompt the driver to enter the optimal route in advance, and in intelligent driving mode, it can also change lanes to the optimal route in advance, greatly improving the driver's driving experience, enhancing the stickiness of human-computer interaction, and helping drivers reduce driving fatigue.

[0080] In summary, this application provides a vehicle driving route selection method. First, it identifies the traffic status of the current road based on map data and the target vehicle's driving data. When the current road is congested, it uses sensor data for synchronous positioning and map construction to generate the target vehicle's perception information. Then, it calculates the target vehicle's speed based on its driving data and correlates the target vehicle's perception information with the number of lanes on the current road to generate a route selection strategy. Simultaneously, it controls the target vehicle to change lanes according to the route selection strategy, ensuring that the travel time after the lane change is less than or equal to the travel time before the lane change. Therefore, this method addresses the challenges of current intelligent driving technology's limitations in selecting fast routes in congested conditions, and the inability of manual driving to choose the optimal route due to uncertainty about the road ahead. It can quickly identify lanes with relatively shorter travel times on the current road using the vehicle's driving data and the current road map data. When the target vehicle is controlled to change to a lane with a relatively shorter travel time, its travel time on the current road can be reduced. Furthermore, by uploading the current road traffic status to the cloud, this information can be pushed to other vehicles connected to the cloud. This helps drivers of other vehicles identify the lanes with the fastest traffic flow in congested areas in advance, allowing them to change lanes to the optimal route and quickly pass through congested sections. If other vehicles are using intelligent driving mode, they can also change lanes to the optimal route in advance based on the cloud-push traffic status, greatly improving the driver's driving experience, enhancing human-computer interaction, and reducing driver fatigue.

[0081] In another exemplary embodiment of this application, such as Figure 4 As shown, this embodiment also provides a vehicle driving route selection system, including:

[0082] The traffic status module 410 is used to identify the traffic status of the current road based on the map data of the current road and the driving data of the target vehicle on the current road. The traffic status includes: congestion status and normal traffic status; wherein, the current road includes at least one lane. In this embodiment or other embodiments, the target vehicle can be a vehicle determined in advance or in real time, such as a vehicle with both intelligent driving and manual driving functions, or a vehicle with only manual driving functions, or a vehicle with only intelligent driving functions. In this embodiment or other embodiments, the target vehicle can also be referred to as a self-driving vehicle. In this embodiment or other embodiments, the traffic status of the current road identified based on the map data of the current road and the driving data of the target vehicle on the current road can be stored in the vehicle controller (Electronic Control Unit, abbreviated as ECU).

[0083] The perception information module 420 is used to generate perception information of the target vehicle by synchronously locating and building a map using sensor data when the current road is congested; wherein, the sensor data is generated by sensors pre-configured on the target vehicle. As an example, in this embodiment or other embodiments, the sensors pre-configured on the target vehicle include, but are not limited to, lidar, millimeter-wave radar, ultrasonic radar, and image capturing devices (such as cameras).

[0084] The road selection strategy module 430 is used to calculate the driving speed of the target vehicle based on the driving data of the target vehicle on the current road, and associate the perception information of the target vehicle with the number of lanes on the current road to generate the road selection strategy of the target vehicle.

[0085] The lane change module 440 is used to control the target vehicle to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change.

[0086] Therefore, this embodiment addresses the challenges of choosing the fastest route in congested traffic conditions due to the limitations of current intelligent driving technology, and the inability of manual driving to select the optimal route due to uncertainty about the road ahead. By utilizing the vehicle's current driving data and the map data of the current road, it can quickly identify the lane with the shortest travel time within a short period. When the target vehicle is controlled and moved to the lane with the shorter travel time, its travel time on the current road can be reduced. Thus, this embodiment can help drivers identify the lane with the fastest traffic flow in congested roads in advance and quickly pass through congested sections.

[0087] In an exemplary embodiment, the process of identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road includes: acquiring vehicle speed data and geographical location data of multiple vehicles based on map data of the current road; if the real-time speed of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed, or the geographical location change distance of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset distance, then the corresponding road segment is recorded as a target road segment, and the traffic status of the target road segment is marked as congested; and, based on the driving data of the target vehicle on the target road segment, acquiring the distance between the target vehicle and the vehicle in front, and calculating the average driving speed of the vehicle in front within a preset time period using the distance between the two vehicles; and, based on the speed limit of the target road segment and the average driving speed of the vehicle in front within the preset time period, determining the traffic status of the target vehicle on the target road segment; wherein the vehicle in front is located in front of the target vehicle; and determining the traffic status of the current road based on the traffic status of the target road segment and the traffic status of the target vehicle on the target road segment. As an example, in this embodiment or other embodiments, the preset quantity and preset speed can be set according to the actual situation, and this embodiment does not limit the specific values.

[0088] Specifically, such as Figure 2 As shown, Figure 2 This diagram illustrates the target vehicle traveling on a certain road segment. Figure 2 In the diagram, A represents the target vehicle, B and C represent vehicles ahead of target vehicle A, P is the camera position of target vehicle A, image plane I is generated by projecting the points of vehicles B and C through point P, f is the camera focal length, H is the camera height, y1 and y2 are the distances of vehicles B and C projected onto the zero point of image plane I, and z1 and z2 are the distances of vehicles B and C from target vehicle A. Therefore, the process of determining the traffic status of the target vehicle on the target road segment in this embodiment can be as follows: Using the formula for similar triangles, we know that... At the same time from Figure 2 As can be seen, the farther the vehicle is from the horizontal, the smaller the distance y between the bottom of the vehicle and the horizontal line in image plane I. The distance y from the zero point of the projected vehicle onto image plane I can be obtained by transforming the coordinate system after the camera P takes a picture of the vehicle in front. Therefore, the average speed v of the vehicle in front during the time period Δt can be expressed as: This allows us to calculate the average speed of the vehicle ahead within a time period Δt. Then, by using map data from map software, we can obtain the speed limit for the current road segment. If the average speed v of the vehicle ahead within time period Δt is less than 30% of the speed limit, then the lane containing the target vehicle can be considered congested; the same applies to other lanes. If the target vehicle uploads the congestion information to the cloud, other vehicles connected to the cloud in the current road segment can also receive this congestion information. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, it can do so through the vehicle controller within the target vehicle.

[0089] In an exemplary embodiment, identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road may further include: recording the traffic status obtained based on the map data of the current road as the map traffic status, and recording the traffic status obtained based on the driving data of the target vehicle on the current road as the driving traffic status; determining whether the map traffic status and the driving traffic status are consistent; if the map traffic status and the driving traffic status are consistent, then using either the map traffic status or the driving traffic status as the traffic status of the current road; if the map traffic status and the driving traffic status are inconsistent, then using the driving traffic status as the traffic status of the current road; and uploading the traffic status of the current road to the cloud and pushing the traffic status of the current road to other vehicles connected to the cloud. Therefore, this embodiment, in identifying the traffic status of the current road, also determines the priority of map data and driving data. Since driving data is real-time and accurate, this embodiment can avoid the delay error caused by map data by using the driving traffic status as the traffic status of the current road when the map traffic status and the driving traffic status are inconsistent. Meanwhile, this embodiment uploads the current road traffic status to the cloud, which can then push the current road traffic status to other vehicles connected to the cloud. This helps drivers of other vehicles identify the lane with the fastest traffic flow in congested roads in advance, allowing them to change lanes to the optimal route and quickly pass through congested sections. If other vehicles are using intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed from the cloud, greatly improving the driver's driving experience, enhancing the stickiness of human-computer interaction, and helping to reduce driver fatigue.

[0090] In an exemplary embodiment, the process of generating perception information of a target vehicle through simultaneous localization and mapping (SLAM) using sensor data includes: acquiring laser point cloud data of the surrounding environment of the target vehicle using a pre-configured LiDAR on the target vehicle, and constructing sensor data using view data collected by an image capturing device pre-configured on the target vehicle; using the sensor data for simultaneous localization and mapping to construct and generate motion equations and observation equations for the target vehicle; wherein the motion equations characterize the pose changes of the target vehicle at different times, and the observation equations characterize the surrounding environment features observed by the target vehicle at different poses; and generating perception information of the target vehicle based on the motion equations and observation equations. Specifically, in this embodiment, when the current road is congested, the lane information of the target vehicle can be fed back through the Simultaneous Localization and Mapping (SLAM) method. For example, laser point cloud data of the surrounding environment of the target vehicle can be acquired through LiDAR. LiDAR can measure the angle and distance of objects around the car with high accuracy. Visually, simultaneous localization and mapping are performed using data collected by a camera. At the same time, the perception information of the target vehicle can be regarded as a mathematical modeling process, thus having the motion equation x k =f(x) k-1 )+u k-1 and observation equation y k =h(x k )+v k In the equations of motion, x k Let f(x) represent the pose of the target vehicle at time k, which is derived from the pose at time k-1. k-1 The actual environment may have errors, therefore a noise factor u is added. k-1 This imposes certain constraints on pose changes. In the observation equation, y k The sensor observation at time k represents the current target vehicle pose h(x). k ) decided, v k This is to account for errors caused by the actual environmental conditions. In this embodiment, the equation of motion describes the pose x at time k-1. k-1 How does the pose x change to time k? k The observation equation describes how to obtain the pose x at time k. k Obtain observation data y k Therefore, by using motion equations and observation equations, we can more realistically reflect the actual position and orientation of the target vehicle in relation to the current environment.

[0091] In an exemplary embodiment, if the current road includes only one lane, generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: obtaining the real-time speed of the vehicle in front and the deceleration of the target vehicle; wherein the vehicle in front is located in front of the target vehicle; calculating the minimum safe distance between the target vehicle and the vehicle in front based on the real-time speed of the vehicle in front and the deceleration of the target vehicle; determining the road selection strategy as following without changing lanes; and controlling the target vehicle to follow the vehicle in front normally according to the minimum safe distance. In this embodiment or other embodiments, the process of calculating the minimum safe distance between the target vehicle and the vehicle in front may be: In the formula, MSFD represents the minimum safe distance between the target vehicle and the vehicle in front, s p This indicates the real-time speed of the vehicle ahead, and de indicates the deceleration of the target vehicle.

[0092] In an exemplary embodiment, if the current road includes only two lanes, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: identifying whether there are vehicles in front of the target vehicle in the current lane and the adjacent lane based on the target vehicle's perception information; comparing the speeds of the vehicles in front of the target vehicle in the current lane and the adjacent lane when there are vehicles in front of both lanes; if the speed of the vehicle in front of the target vehicle in the current lane is less than the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to change to the adjacent lane, and the target vehicle is controlled to change from the current lane to the adjacent lane based on the target vehicle's perception information; if the speed of the vehicle in front of the target vehicle in the current lane is greater than or equal to the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to follow without changing lanes; and controlling the target vehicle to follow the vehicle in front of the target vehicle in the current lane at a minimum safe distance for normal driving.

[0093] In an exemplary embodiment, if the current road includes only three or more lanes, a road selection strategy for the target vehicle is generated. The process of controlling the target vehicle to change lanes according to the road selection strategy includes: identifying the lane position of the target vehicle based on the target vehicle's perception information; when the target vehicle is in the middle lane of the current road, identifying whether there are vehicles in front of the target vehicle in the current lane, the left lane, and the right lane based on the target vehicle's perception information; and, when there are vehicles in front in the current lane, the left lane, and the right lane, respectively, controlling the vehicles in front in the current lane, the vehicles in front in the left lane, and the vehicles in front in the right lane. A speed comparison is performed; if the speed of the vehicle ahead in the current lane is less than the speed of the vehicle ahead in the left lane or the speed of the vehicle ahead in the right lane, the road selection strategy is determined to change to the lane with the fastest speed, and the target vehicle is controlled to change from the current lane to the corresponding lane based on the target vehicle's perception information; if the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the left lane, and greater than or equal to the speed of the vehicle ahead in the right lane, the road selection strategy is determined to follow, and no lane change is performed; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

[0094] Specifically, as an example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the left lane is less than the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the right lane, and the target vehicle is controlled to change from the current lane to the right lane based on the target vehicle's perception information.

[0095] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, while the speed of the vehicle in front of the left lane is greater than the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the left lane, and the target vehicle is controlled to change from the current lane to the left lane based on the target vehicle's perception information.

[0096] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, while the speed of the vehicle in front of the left lane is equal to the speed of the vehicle in front of the right lane, then the road selection strategy is determined to change to the lane with the fastest speed. That is, the road selection strategy is determined to change to the left lane or the right lane, and the target vehicle is controlled to change from the current lane to the left lane or the right lane based on the target vehicle's perception information.

[0097] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the right lane is less than the speed of the vehicle in front of the left lane, then the road selection strategy is determined to change to the lane with the fastest speed, that is, the road selection strategy is determined to change to the left lane, and the target vehicle is controlled to change from the current lane to the left lane based on the target vehicle's perception information.

[0098] As another example, if the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane, while the speed of the vehicle in front of the right lane is greater than the speed of the vehicle in front of the left lane, then the road selection strategy is determined to change to the lane with the fastest speed. That is, the road selection strategy is determined to change to the right lane, and the target vehicle is controlled to change from the current lane to the right lane based on the target vehicle's perception information.

[0099] In summary, this application provides a vehicle driving route selection system. First, it identifies the traffic status of the current road based on map data and the target vehicle's driving data. When the current road is congested, it uses sensor data for synchronous positioning and map construction to generate the target vehicle's perception information. Then, it calculates the target vehicle's speed based on its driving data and correlates the target vehicle's perception information with the number of lanes on the current road to generate a route selection strategy. Simultaneously, it controls the target vehicle to change lanes according to the route selection strategy, ensuring that the travel time after the lane change is less than or equal to the travel time before the lane change. Therefore, this system addresses the challenges of choosing a fast route in congested traffic conditions due to the limitations of current intelligent driving technology, and the inability of manual driving to choose the optimal route due to uncertainty about the road ahead. It can quickly identify lanes with relatively shorter travel times on the current road using the vehicle's driving data and the current road map data. When the target vehicle is controlled to change to a lane with a shorter travel time, its travel time on the current road is reduced. Furthermore, by uploading the current road traffic status to the cloud, this information can be pushed to other vehicles connected to the cloud. This helps drivers of other vehicles identify the lanes with the fastest traffic flow in congested areas in advance, allowing them to change lanes to the optimal route and quickly pass through congested sections. If other vehicles are using intelligent driving mode, they can also change lanes to the optimal route in advance based on the cloud-push traffic status, greatly improving the driver's driving experience, enhancing human-computer interaction, and reducing driver fatigue.

[0100] It should be noted that the vehicle driving route selection system provided in the above embodiments and the vehicle driving route selection method provided in the above embodiments belong to the same concept. The specific way in which the vehicle driving route selection method performs its operation has been described in detail in the above method embodiments, and will not be repeated here. In practical applications, the vehicle driving route selection system provided in the above embodiments can be assigned to different functional modules as needed. That is, the internal structure of the vehicle driving route selection system can be divided into different functional modules, and then all or part of the functions of the corresponding functional modules can be implemented through the vehicle driving route selection method described in the above embodiments. No specific limitations are imposed here.

[0101] This application embodiment also provides a vehicle-mounted control device, which may include a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to cause the vehicle-mounted control device to perform... Figure 1 The steps of the vehicle driving route selection method are described above. Figure 5A schematic diagram of an on-board control device 1000 is shown. (See attached diagram.) Figure 5 As shown, the vehicle control device 1000 includes: a processor 1010, a memory 1020, a power supply 1030, a display unit 1040, and an input unit 1060.

[0102] The processor 1010 is the control center of the vehicle control device 1000. It connects various components via various interfaces and lines, and executes various functions of the vehicle control device 1000 by running or executing computer programs / instructions stored in the memory 1020, thereby providing overall monitoring of the vehicle control device 1000. In this embodiment, when the processor 1010 calls the computer program stored in the memory 1020, it executes... Figure 1 The steps of the vehicle driving road selection method are described above. Optionally, the processor 1010 may include one or more processing units; preferably, the processor 1010 may integrate an application processor and a modem processor, wherein the application processor mainly handles the operating system, user interface, and applications, and the modem processor mainly handles wireless communication. In some embodiments, the processor and memory can be implemented on a single chip; in some embodiments, they can also be implemented separately on independent chips.

[0103] The memory 1020 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, various applications, etc.; the data storage area may store instruction data created based on the use of the vehicle control device 1000, etc. In addition, the memory 1020 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other non-volatile solid-state storage device.

[0104] The vehicle control device 1000 also includes a power supply 1030 (such as a battery) that supplies power to various components. The power supply can be logically connected to the processor 1010 through a power management system, thereby enabling the management of charging, discharging, and power consumption.

[0105] The display unit 1040 can be used to display information input by the user or information provided to the user, as well as various menus of the vehicle control device 1000. In this embodiment, it is mainly used to display the display interfaces of various applications in the vehicle control device 1000, as well as text, images, and other objects displayed on the display interfaces. The display unit 1040 may include a display panel 1050. The display panel 1050 may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0106] The input unit 1060 can be used to receive information such as numbers or characters input by the user. The input unit 1060 may include a touch panel 1070 and other input devices 1080. The touch panel 1070, also known as a touch screen, can collect touch operations on or near the touch panel 1070 by the user (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near the touch panel 1070).

[0107] Specifically, the touch panel 1070 can detect user touch operations and the signals generated by these operations, convert them into touch point coordinates, send them to the processor 1010, and receive and execute commands from the processor 1010. Furthermore, the touch panel 1070 can be implemented using various types of touch technologies, including resistive, capacitive, infrared, and surface acoustic wave. Other input devices 1080 can include, but are not limited to, one or more of the following: physical keyboard, function keys (such as volume control buttons, power buttons, etc.), trackball, mouse, joystick, etc.

[0108] Of course, the touch panel 1070 can cover the display panel 1050. When the touch panel 1070 detects a touch operation on or near it, it transmits the information to the processor 1010 to determine the type of touch event. Subsequently, the processor 1010 provides corresponding visual output on the display panel 1050 based on the type of touch event. Although in Figure 5 In this embodiment, the touch panel 1070 and the display panel 1050 are two separate components to realize the input and output functions of the vehicle control device 1000. However, in some embodiments, the touch panel 1070 and the display panel 1050 can be integrated to realize the input and output functions of the vehicle control device 1000.

[0109] The vehicle control device 1000 may also include one or more sensors, such as pressure sensors, gravity acceleration sensors, proximity sensors, etc. Of course, depending on the specific application requirements, the vehicle control device 1000 may also include other components such as cameras.

[0110] This application also provides a computer-readable storage medium storing a computer program / instructions. When executed by a processor, the computer program / instructions enable the aforementioned device to perform the functions described in this application. Figure 1 The steps of the vehicle driving route selection method are described above.

[0111] It will be understood by those skilled in the art that Figure 5This is merely an example of an in-vehicle control device and does not constitute a limitation on the device. The device may include more or fewer components than illustrated, or a combination of certain components, or different components. For ease of description, the above sections are divided into modules (or units) according to their functions and described separately. Of course, in implementing this application, the functions of each module (or unit) can be implemented in one or more software or hardware components.

[0112] Those skilled in the art will understand that this application may take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application, and should be understood to be achievable by computer program instructions for each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams. These computer program instructions may be applied to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 The computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The functions specified in one or more boxes. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable apparatus for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0113] In another exemplary embodiment of this application, the embodiment also provides a vehicle, which includes a vehicle driving route selection system as described in the above embodiments, or includes an on-board control device as described in the above embodiments. It should be noted that since the specific methods of operation of the vehicle driving route selection system and the on-board control device have been described in detail in the embodiments, the technical functions and effects of the vehicle provided in this embodiment can be referred to in the above embodiments, and will not be repeated here.

[0114] It should be noted that the above embodiments, in collecting, storing, using, processing, transmitting, providing, disclosing, and deleting relevant data (such as map data, driving data, etc.), are carried out with or with the user's consent. For example, map data and driving data are obtained with the user's knowledge and consent; or are provided voluntarily by the user after reading the relevant instructions; or are actively authorized / provided / uploaded by the user when using some or all of the functions described in the above embodiments; or are obtained through other means or channels with the user's consent.

[0115] The above embodiments are merely illustrative of the principles and effects of this application and are not intended to limit this application. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of this application. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in this application should still be covered by the claims of this application.

Claims

1. A method for selecting a vehicle's driving route, characterized in that, The method includes the following steps: The traffic status of the current road is identified based on the map data of the current road and the driving data of the target vehicle on the current road. The traffic status includes: congestion status and normal traffic status; wherein, the current road includes at least one lane. When the road is congested, the system uses sensor data to perform synchronous positioning and map construction to generate perception information for the target vehicle; wherein, the sensor data is generated by sensors pre-configured on the target vehicle. The driving speed of the target vehicle is calculated based on the driving data of the target vehicle on the current road, and the perception information of the target vehicle and the number of lanes on the current road are associated to generate the road selection strategy of the target vehicle. The target vehicle is controlled to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change. The process of identifying the traffic status of the current road based on the map data of the current road and the driving data of the target vehicle on the current road includes: Based on the map data of the current road, acquire the speed and geographical location data of multiple vehicles. If the real-time speed of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed, or the geographical location change distance of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset distance, then the corresponding road segment is recorded as a target road segment, and the traffic status of the target road segment is marked as congested; and, Based on the driving data of the target vehicle on the target road segment, the distance between the target vehicle and the vehicle in front is obtained, and the average driving speed of the vehicle in front is calculated through the distance between the two vehicles within a preset time period; and, based on the speed limit of the target road segment and the average driving speed of the vehicle in front within the preset time period, the traffic status of the target vehicle on the target road segment is determined; wherein, the vehicle in front is located in front of the target vehicle. The current road traffic status is determined based on the traffic status of the target road segment and the traffic status of the target vehicle on the target road segment.

2. The vehicle driving route selection method according to claim 1, characterized in that, The process of generating perception information for the target vehicle through synchronous positioning and map building using sensor data includes: The sensor data is generated by acquiring laser point cloud data of the surrounding environment of the target vehicle through a pre-configured lidar on the target vehicle, and by collecting view data through an image capturing device pre-configured on the target vehicle. Using the sensor data, synchronous positioning and map construction are performed to generate the motion equation and observation equation of the target vehicle; wherein, the motion equation is used to characterize the pose change of the target vehicle at different times, and the observation equation is used to characterize the surrounding environmental features observed by the target vehicle at different poses. The perception information of the target vehicle is generated based on the motion equation and observation equation of the target vehicle.

3. The vehicle driving route selection method according to claim 1 or 2, characterized in that, If the current road has only one lane, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: The system acquires the real-time speed of the vehicle ahead and the deceleration of the target vehicle; wherein the vehicle ahead is located in front of the target vehicle. Based on the real-time speed of the vehicle in front and the deceleration of the target vehicle, calculate the minimum safe distance between the target vehicle and the vehicle in front. The road selection strategy is set to follow without changing lanes; and the target vehicle is controlled to follow the vehicle in front at the minimum safe distance for normal driving.

4. The vehicle driving route selection method according to claim 1 or 2, characterized in that, If the current road has only two lanes, the process of generating a road selection strategy for the target vehicle and controlling the target vehicle to change lanes according to the road selection strategy includes: Based on the perception information of the target vehicle, identify whether there is a vehicle in front of the target vehicle in the current lane and the adjacent lane, and compare the speeds of the vehicle in front of the target vehicle in the current lane and the vehicle in front of the adjacent lane when there is a vehicle in front of the target vehicle in the current lane and the vehicle in front of the adjacent lane. If the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to change to the adjacent lane, and the target vehicle is controlled to change from the current lane to the adjacent lane based on the perception information of the target vehicle. If the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the adjacent lane, the road selection strategy is set to follow without changing lanes; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

5. The vehicle driving route selection method according to claim 1 or 2, characterized in that, If the current road has only three or more lanes, a road selection strategy for the target vehicle is generated, and the process of controlling the target vehicle to change lanes according to the road selection strategy includes: The lane position of the target vehicle is identified based on the perception information of the target vehicle; When the target vehicle is in the middle lane of the current road, the system identifies whether there are vehicles in front of the target vehicle in the current lane, the left lane, and the right lane based on the target vehicle's perception information; and when there is a vehicle in front in the current lane, a vehicle in front in the left lane, and a vehicle in front in the right lane, the system compares the speeds of the vehicle in front in the current lane with those of the vehicles in front in the left lane and the vehicles in front in the right lane, respectively. If the speed of the vehicle in front of the current lane is less than the speed of the vehicle in front of the left lane or the speed of the vehicle in front of the right lane, the road selection strategy is determined to change to the lane with the fastest speed, and the target vehicle is controlled to change from the current lane to the corresponding lane based on the perception information of the target vehicle. If the speed of the vehicle ahead in the current lane is greater than or equal to the speed of the vehicle ahead in the left lane, and greater than or equal to the speed of the vehicle ahead in the right lane, then the road selection strategy is determined to be following, and no lane change is performed; and the target vehicle is controlled to follow the vehicle ahead in the current lane at the minimum safe distance for normal driving.

6. The vehicle driving route selection method according to claim 1, characterized in that, When identifying the traffic status of the current road based on map data of the current road and driving data of the target vehicle on the current road, the method further includes: The traffic status obtained based on the map data of the current road is recorded as the map traffic status, and the traffic status obtained based on the driving data of the target vehicle on the current road is recorded as the driving traffic status. Determine whether the map traffic status is consistent with the driving traffic status; If the map traffic status is consistent with the driving traffic status, then the map traffic status or the driving traffic status shall be taken as the current road traffic status; If the map traffic status is inconsistent with the driving traffic status, the driving traffic status is taken as the current road traffic status; and the current road traffic status is uploaded to the cloud and pushed to other vehicles connected to the cloud.

7. A vehicle driving route selection system, characterized in that, The system includes: The traffic status module is used to identify the traffic status of the current road based on the map data of the current road and the driving data of the target vehicles on the current road. The traffic status includes: congestion status and normal traffic status. The current road includes at least one lane. The process of identifying the traffic status of the current road based on the map data of the current road and the driving data of the target vehicles on the current road includes: acquiring the speed data and geographical location data of multiple vehicles based on the map data of the current road; if the real-time speed of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed, or the geographical location change distance of more than a preset number of vehicles in one or more road segments of the current road is less than or equal to a preset speed... If a distance is defined, the corresponding road segment is recorded as the target road segment, and the traffic status of the target road segment is marked as congested. Furthermore, based on the driving data of the target vehicle on the target road segment, the distance between the target vehicle and the vehicle ahead is obtained, and the average driving speed of the vehicle ahead within a preset time period is calculated using the distance. Also, based on the speed limit of the target road segment and the average driving speed of the vehicle ahead within the preset time period, the traffic status of the target vehicle on the target road segment is determined; wherein, the vehicle ahead is located in front of the target vehicle. The traffic status of the current road is determined based on the traffic status of the target road segment and the traffic status of the target vehicle on the target road segment. The perception information module is used to generate perception information of the target vehicle by synchronously locating and building a map using sensor data when the current road is congested; wherein, the sensor data is generated by sensors pre-configured on the target vehicle. The road selection strategy module is used to calculate the driving speed of the target vehicle based on the driving data of the target vehicle on the current road, and associate the perception information of the target vehicle with the number of lanes on the current road to generate the road selection strategy of the target vehicle. The lane change module is used to control the target vehicle to change lanes according to the road selection strategy, so that the travel time of the target vehicle after the lane change is less than or equal to the travel time before the lane change.

8. A vehicle-mounted control device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the vehicle driving route selection method according to any one of claims 1 to 6.

9. A vehicle, characterized in that, The vehicle includes the vehicle driving route selection system as described in claim 7, or the on-board control device as described in claim 8.

Images