Vehicle driving road selection method and system, vehicle-mounted control equipment and vehicle

Abstract

The invention provides a vehicle driving road selection method and system, a vehicle-mounted control device and a vehicle, and the method comprises the steps: recognizing the traffic state of a current road based on the map data of the current road and the driving data of a target vehicle on the current road, and carrying out the synchronous positioning and map construction through sensor data when the current road is in a congestion state, generating sensing information of the target vehicle; the driving speed of the target vehicle is calculated according to the driving data, perception information of the target vehicle and the number of lanes of the current road are associated, and a road selection strategy of the target vehicle is generated; and controlling the target vehicle to change the lane according to the road selection strategy, so that the passing time of the target vehicle after the lane change is less than or equal to the passing time before the lane change. Through the driving data of the current vehicle and the map data of the current road, the lane with relatively short passing time in the current road can be quickly obtained, so that the passing time of the target vehicle on the current road is reduced.

Description

Technical Field

[0001] The present application relates to the field of vehicle control technology, and in particular to a vehicle driving road selection method and system, a vehicle-mounted control device and a vehicle. Background Art

[0002] With the continuous updating and improvement of intelligent driving system technology, many car models are now equipped with intelligent driving functions. The intelligent driving function can update perception information in a timely manner through laser radar, cameras and other equipment, and help the driver drive the vehicle on the road, thereby improving the driver's driving experience.

[0003] However, the currently commonly used intelligent driving functions can only help drivers drive on a single road. When there is congestion ahead, they will only follow the car in front and drive slowly. They cannot change the road in time when entering a congested section or prompt the driver to drive to a road with faster traffic. In addition, manual driving may not be able to make quick judgments due to the unknown road ahead. Therefore, how to help drivers identify the lane with the fastest traffic in a congested road in advance and pass through the congested section quickly is an urgent problem that needs to be solved. Summary of the invention

[0004] In view of the above-mentioned shortcomings of the prior art, the purpose of the present application is to provide a vehicle driving road selection method and system, a vehicle-mounted control device and a vehicle, so as to solve the technical problems in the prior art.

[0005] To achieve the above-mentioned purpose and other related purposes, the present application provides a method for selecting a vehicle driving road, comprising the following steps:

[0006] Identifying the traffic state 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, wherein the traffic state includes: a congested state and a normal traffic state; wherein the current road includes at least one lane;

[0007] When the current road is in a congested state, synchronous positioning and map construction are performed through sensor data to generate perception information of the target vehicle; wherein the sensor data is generated by a sensor pre-configured on the target vehicle;

[0008] Calculating the driving speed of the target vehicle according to the driving data of the target vehicle on the current road, and associating the perception information of the target vehicle with the number of lanes on the current road to generate a road selection strategy for 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 the present application, 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:

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

[0012] Based on the driving data of the target vehicle on the target road section, the interval distance between the target vehicle and the front vehicle is obtained, and the average driving speed of the front vehicle in a preset time period is calculated according to the interval distance; and based on the speed limit of the target road section and the average driving speed of the front vehicle in the preset time period, the traffic state of the target vehicle on the target road section is determined; wherein the front vehicle is located in front of the target vehicle;

[0013] The traffic state of the current road is determined according to the traffic state of the target road section and the traffic state of the target vehicle on the target road section.

[0014] In one embodiment of the present application, the process of performing synchronous positioning and map construction through sensor data to generate the perception information of the target vehicle includes:

[0015] Acquiring laser point cloud data of the surrounding environment of the target vehicle through a laser radar pre-configured on the target vehicle, and constructing and generating the sensor data through view data collected by an image capture device pre-configured on the target vehicle;

[0016] The sensor data is used to perform synchronous positioning and map construction to construct a motion equation and an observation equation for the target vehicle; wherein the motion equation is used to characterize the position and posture changes of the target vehicle at different times, and the observation equation is used to characterize the surrounding environment characteristics observed by the target vehicle at different positions and postures;

[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 the present 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] Acquire the real-time speed of the front vehicle and the deceleration of the target vehicle; wherein the front vehicle is located in front of the target vehicle;

[0020] Calculating a minimum safe distance between the target vehicle and the vehicle ahead based on the real-time speed of the vehicle ahead and the deceleration of the target vehicle;

[0021] The road selection strategy is determined as following driving without changing lanes; and the target vehicle is controlled to follow the front vehicle at the minimum safety distance for normal driving.

[0022] In one embodiment of the present 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] Identify whether there is a vehicle ahead of the target vehicle in the current lane and the adjacent lane based on the sensing information of the target vehicle, and compare the speeds of the vehicle ahead of the current lane and the vehicle ahead of the adjacent lane when there is a vehicle ahead of the current lane and a vehicle ahead of the adjacent lane;

[0024] If the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to be changed 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 driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to be following driving without changing lanes; and the target vehicle is controlled to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

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

[0027] Identifying a lane position of the target vehicle based on the perception information of the target vehicle;

[0028] When the target vehicle is in the middle lane of the current road, identifying whether there is a vehicle in front of the target vehicle in the current lane, the left lane and the right lane based on the perception information of the target vehicle; and when there is a vehicle in front of the current lane, the left lane and the right lane, comparing the speed of the vehicle in front of the current lane with the vehicle in front of the left lane and the vehicle in front of the right lane respectively;

[0029] If the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the left lane or the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to change to the lane with the fastest driving 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 driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the left lane, and greater than or equal to the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to be following driving without changing lanes; and the target vehicle is controlled to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

[0031] In one embodiment of the present application, when identifying the traffic state 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 method further includes:

[0032] Recording the traffic state obtained based on the map data of the current road as the map traffic state, and recording the traffic state obtained based on the driving data of the target vehicle on the current road as the driving traffic state;

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

[0034] If the map traffic state is consistent with the driving traffic state, the map traffic state or the driving traffic state is used as the traffic state of the current road;

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

[0036] The present application also provides a vehicle driving road selection system, the system comprising:

[0037] A traffic status module, 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, wherein the traffic status includes: congestion status and normal traffic status; wherein the current road includes at least one lane;

[0038] A perception information module, used to perform synchronous positioning and map construction through sensor data to generate perception information of the target vehicle when the current road is in a congested state; wherein the sensor data is generated by a sensor pre-configured on the target vehicle;

[0039] A road selection strategy module, used to calculate the driving speed of the target vehicle according to 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 a road selection strategy for 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] The present application also provides a vehicle-mounted control device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the above-mentioned vehicle driving road selection methods.

[0042] The present application also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of any one of the above-mentioned vehicle driving road selection methods are implemented.

[0043] As described above, the present application provides a vehicle driving road selection method and system, a vehicle-mounted control device and a vehicle, which have the following beneficial effects: the present 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, and when the current road is in a congested state, 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 according to 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 a road selection strategy for 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. It can be seen from this that this application aims at how to choose a fast road to pass when encountering congested road conditions when the current intelligent driving technology is not perfect, and the situation that the manual driving mode may not be able to choose the best road to pass due to the unclear road conditions ahead. The current vehicle's driving data and the map data of the current road can be used to quickly obtain the lane with a relatively short travel time in the current road in a short time. When the target vehicle is controlled to change to a lane with a relatively short travel time, the travel time of the target vehicle on the current road can be reduced. In addition, by uploading the traffic status of the current road to the cloud, the traffic status of the current road can be pushed to other vehicles connected to the cloud, thereby helping the drivers of other vehicles to identify the lane with the fastest traffic flow in the congested road in advance, facilitating the drivers of other vehicles to change lanes to the optimal route in advance and quickly pass through the congested section. If other vehicles adopt the intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed by the cloud, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a process flow of a vehicle driving road selection method provided in an embodiment of the present application;

[0045] Figure 2 A schematic diagram of a target vehicle driving on a certain road section provided in an embodiment of the present application;

[0046] Figure 3 A schematic diagram of the principle of a vehicle driving road selection method provided in an embodiment of the present application;

[0047] Figure 4 A schematic diagram of the hardware structure of a vehicle driving road selection system provided in an embodiment of the present application;

[0048] Figure 5 The present invention is a schematic diagram of the hardware structure of a vehicle-mounted control device suitable for implementing one or more embodiments of the present application. DETAILED DESCRIPTION

[0049] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0050] It should be noted that the illustrations provided in this embodiment only illustrate the basic concept of the present application in a schematic manner, and the figures only show the components related to the present application rather than being drawn according to the number, shape and size of the components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

[0051] Figure 1 FIG. 1 is a flow chart of a method for selecting a vehicle driving road provided by an embodiment of the present application. Specifically, in an exemplary embodiment, Figure 1 As shown, this embodiment provides a method for selecting a vehicle driving road, the method comprising the following steps:

[0052] S110, based on the map data of the current road and the driving data of the target vehicle on the current road, the traffic state of the current road is identified, and the traffic state includes: congestion state, normal traffic state; 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 including an intelligent driving function and a manual driving function, or a vehicle including only a manual driving function, or a vehicle including only an intelligent driving function. In this embodiment or other embodiments, the target vehicle can also be referred to as a self-vehicle. In this embodiment or other embodiments, the traffic state 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, referred to as ECU).

[0053] S120, when the current road is in a congested state, synchronously locate and construct a map through 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 laser radar, millimeter wave radar, ultrasonic radar, image capture device (such as camera), etc.

[0054] S130, calculating the target vehicle's driving speed based on the target vehicle's driving data on the current road, and associating the target vehicle's perception information with the number of lanes on the current road to generate a road selection strategy for the target vehicle;

[0055] S140: 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.

[0056] It can be seen that this embodiment aims at how to choose a fast road to pass when encountering congested road conditions when the current intelligent driving technology is not perfect, and the situation that the manual driving mode may not be able to choose the best road to pass due to unclear road conditions ahead. Through the driving data of the current vehicle and the map data of the current road, the lane with a relatively short travel time on the current road can be quickly obtained in a short time. When the target vehicle is controlled to change to a lane with a relatively short travel time, the travel time of the target vehicle on the current road can be reduced. Therefore, this embodiment can help the driver identify the lane with the fastest traffic flow on the congested road in advance and quickly pass the congested section.

[0057] In an exemplary embodiment, the process of identifying the traffic state 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: obtaining the speed data and geographic 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 sections of the current road is less than or equal to the preset speed, or the geographic location change distance of more than a preset number of vehicles in one or more sections of the current road is less than or equal to the preset distance, then the corresponding section is recorded as the target section, and the traffic state of the target section is marked as a congested state; and, based on the driving data of the target vehicle on the target section, obtaining the interval distance between the target vehicle and the front vehicle, and calculating the average driving speed of the front vehicle within a preset time period through the interval distance; and, based on the speed limit of the target section and the average driving speed of the front vehicle within the preset time period, determining the traffic state of the target vehicle on the target section; wherein the front vehicle is located in front of the target vehicle; and determining the traffic state of the current road according to the traffic state of the target section and the traffic state of the target vehicle on the target section. As an example, in this embodiment or other embodiments, the preset number and the preset vehicle speed can be set according to actual conditions, and this embodiment does not limit the specific numerical values.

[0058] Specifically, Figure 2 As shown, Figure 2 Figure 1 shows a schematic diagram of a target vehicle traveling on a certain road section. Figure 2In the figure, A is the target vehicle, B and C are the vehicles in front of the target vehicle A, point P is the camera position of the target vehicle A, image plane I is generated by the projection points of vehicles B and C after they are reversed through point P, f is the focal length of the camera, H is the height of the camera, y1 and y2 are the distances from point 0 projected from vehicle B and vehicle C on image plane I, and z1 and z2 are the distances from vehicle B and vehicle C to the target vehicle A. Therefore, the process of determining the traffic status of the target vehicle on the target road section in this embodiment can be: It can be known from the similar triangle formula: At the same time from Figure 2 It can be seen that the farther the vehicle is, the smaller the distance y between the bottom of the vehicle and the horizontal line in the image plane I is. The distance y of the front vehicle projected onto the image plane I can be obtained by converting the coordinate system after the camera P takes a photo of the front vehicle. Therefore, the average speed v of the front vehicle in the time period Δt can be expressed as: Thus, the average speed of the vehicle ahead in the time period Δt can be calculated, and then the speed limit of the current road section can be obtained through the map data in the map software. Assuming that the average speed v of the vehicle ahead in the time period Δt is lower than 30% of the speed limit, it can be considered that the lane where the target vehicle is located is congested, and the same applies to other lanes. At this time, if the target vehicle uploads the congestion information to the cloud, if there are other vehicles connected to the cloud on the current road section, the other vehicles can receive the congestion information of this road section. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, the congestion information can be uploaded to the cloud through the vehicle controller in the target vehicle.

[0059] In an exemplary embodiment, when identifying the traffic state 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, it can also include: recording the traffic state obtained based on the map data of the current road as the map traffic state, and recording the traffic state obtained based on the driving data of the target vehicle on the current road as the driving traffic state; judging whether the map traffic state is consistent with the driving traffic state; if the map traffic state is consistent with the driving traffic state, the map traffic state or the driving traffic state is used as the traffic state of the current road; if the map traffic state is inconsistent with the driving traffic state, the driving traffic state is used as the traffic state of the current road; and uploading the traffic state of the current road to the cloud, and pushing the traffic state of the current road to other vehicles connected to the cloud. It can be seen that when identifying the traffic state of the current road, this embodiment also determines the priority of the map data and the driving data. Since the driving data is real-time and true, when the map traffic state is inconsistent with the driving traffic state, this embodiment uses the driving traffic state as the traffic state of the current road to avoid the delay error caused by the map data. At the same time, by uploading the traffic status of the current road to the cloud, this embodiment can push the traffic status of the current road to other vehicles connected to the cloud, thereby helping the drivers of other vehicles to identify the lane with the fastest traffic flow in the congested road in advance, and facilitating the drivers of other vehicles to change lanes to the optimal route in advance and quickly pass through the congested road section. If other vehicles adopt the intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed by the cloud, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue.

[0060] In an exemplary embodiment, the process of performing simultaneous positioning and mapping through sensor data to generate perception information of the target vehicle includes: obtaining laser point cloud data of the surrounding environment of the target vehicle through a laser radar pre-configured on the target vehicle, and generating sensor data through view data collected by an image capture device pre-configured on the target vehicle; using the sensor data to perform simultaneous positioning and mapping to construct the motion equation and observation equation of the target vehicle; wherein the motion equation is used to characterize the position change of the target vehicle at different times, and the observation equation is used to characterize the surrounding environment characteristics observed by the target vehicle at different positions; generating the perception information of the target vehicle based on the motion equation and observation equation of the target vehicle. Specifically, in this embodiment, when the current road is in a congested state, the lane information of the target vehicle can be fed back through the simultaneous positioning and mapping (SLAM) method, for example, the laser point cloud data of the surrounding environment of the target vehicle is obtained through a laser radar, and the laser radar can measure the angle and distance of objects around the car with high accuracy. In terms of vision, the data collected by the camera is used for simultaneous positioning and mapping; at the same time, the perception information of the target vehicle can be regarded as a mathematical modeling process, then there is a motion equation x k =f(x k-1 )+u k-1 and the observation equation y k =h(x k )+v k In the equation of motion, x k represents the position of the target vehicle at time k, and the position at time k-1 is f(x k-1 ) is determined; the actual environment may have errors, so a noise amount u is added k-1 This forms certain constraints on the change of posture. In the observation equation, y k represents the sensor observation value at time k, which is represented by the current target vehicle position h(x k ) decides, k is the actual environmental influence error. In this embodiment, the motion equation describes the position x at time k-1: k-1 How does it change to the position x at time k? k , the observation equation describes how to get from the pose x at time k k Get the observed data y k Therefore, the motion equation and observation equation can more realistically reflect the actual position of the target vehicle and the current environment.

[0061] In an exemplary embodiment, if the current road includes only one lane, a road selection strategy for the target vehicle is generated, and a process of 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 driving without changing lanes; and controlling the target vehicle to follow the vehicle in front for normal driving at 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: Where MSFD represents the minimum safe distance between the target vehicle and the vehicle ahead, s p It 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, 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: identifying whether there is a vehicle in front of the target vehicle in the current lane and the side lane based on the perception information of the target vehicle, and when there is a vehicle in front of the current lane and a vehicle in front of the side lane, comparing the speeds of the vehicle in front of the current lane and the vehicle in front of the side lane; if the driving speed of the vehicle in front of the current lane is less than the driving speed of the vehicle in front of the side lane, determining the road selection strategy to change to the side lane, and controlling the target vehicle to change from the current lane to the side lane based on the perception information of the target vehicle; if the driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the side lane, determining the road selection strategy to follow driving without changing lanes; and controlling the target vehicle to follow the vehicle in front of the current lane at a minimum safety 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, and a 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 perception information of the target vehicle; 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 perception information of the target vehicle; and when there are vehicles in front of the current lane, the left lane, and the right lane, respectively, comparing the vehicles in front of the current lane with the vehicles in front of the left lane and the vehicles in front of the right lane. Perform speed comparison; 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, determine the road selection strategy to change to the lane with the fastest driving speed, and control the target vehicle 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 in front of the current lane is greater than or equal to the speed of the vehicle in front of the left lane, and greater than or equal to the speed of the vehicle in front of the right lane, determine the road selection strategy to follow driving without lane change; and control the target vehicle to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

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

[0065] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the left lane is higher 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 driving 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 perception information of the target vehicle.

[0066] As another example, if the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the left lane, and the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the right lane, and at the same time the driving speed of the vehicle in front of the left lane is equal to the driving 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 driving speed, that is, the road selection strategy is determined to change to the left lane or the right lane, and based on the perception information of the target vehicle, the target vehicle is controlled to change from the current lane to the left lane or the right lane.

[0067] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the left lane, the road selection strategy is determined to change to the lane with the fastest driving 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 perception information of the target vehicle.

[0068] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the right lane is higher 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 driving 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 perception information of the target vehicle.

[0069] In another exemplary embodiment of the present application, the embodiment further provides a method for selecting a driving road when the road is congested. The principle schematic diagram of the method is shown in FIG. Figure 3 Specifically, Figure 3 As shown, the method comprises the following steps:

[0070] Step S1: The vehicle is driving normally along the navigation, and the current traffic information of the road can be fed back by the map software. The map software can determine whether it is congested through the user generated content (UGC) data collection and analysis method. This method is to upload the vehicle speed, GPS (Global Positioning System, GPS) position and other information of the user in the process of using the map software to the background for analysis, and update the road conditions in real time through analysis. If there are multiple users with slow speeds on the same road section, it will be considered congested. At this time, when the target vehicle drives to the congested section, the map software actively interacts with the vehicle controller ECU to proceed to step S2;

[0071] Step S2: If the vehicle navigation is not turned on and the driver encounters congestion during self-driving, the congestion information will be reported to the vehicle controller ECU. Figure 2 As shown, in Figure 2 In the figure, A is the target vehicle, B and C are the vehicles in front of the target vehicle A, point P is the camera position of the target vehicle A, image plane I is generated by the projection point of vehicles B and C after reversing through point P, f is the focal length of the camera, H is the height of the camera, y1 and y2 are the distances from point 0 of vehicle B and vehicle C projected onto image plane I, and z1 and z2 are the distances from vehicle B and vehicle C to the target vehicle A. Therefore, the following process can be referred to in this embodiment to determine whether there is congestion based on vehicle driving data: It can be known from the similar triangle formula: At the same time from Figure 2 It can be seen that the farther the vehicle is, the smaller the distance y between the bottom of the vehicle and the horizontal line in the image plane I is. The distance y of the front vehicle projected onto the image plane I can be obtained by converting the coordinate system after the camera P takes a photo of the front vehicle. Therefore, the average speed v of the front vehicle in the time period Δt can be expressed as: Thus, the average speed of the vehicle ahead in the time period Δt can be calculated, and then the speed limit of the current road section can be obtained through the map data in the map software. Assuming that the average speed v of the vehicle ahead in the time period Δt is lower than 30% of the speed limit, it can be considered that the lane where the target vehicle is located is congested, and the same applies to other lanes. At this time, if the target vehicle uploads the congestion information to the cloud, if there are other vehicles connected to the cloud on the current road section, the other vehicles can receive the congestion information of this road section. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, the congestion information can be uploaded to the cloud through the vehicle controller in the target vehicle.

[0072] Step S3: After the vehicle controller ECU obtains the road congestion information report, it controls the perception system to obtain road information and can feedback the lane information of the target vehicle through the simultaneous localization and mapping (SLAM) method. For example, the laser point cloud data of the target vehicle's surrounding environment is obtained through the laser radar. The laser radar can measure the angle and distance of objects around the car with high accuracy. The data collected by the camera is used for simultaneous positioning and mapping in terms of vision. At the same time, the perception information of the target vehicle can be regarded as a mathematical modeling process, so there is a motion equation x k =f(x k-1 )+u k-1 and the observation equation y k =h(x k )+v k In the equation of motion, x krepresents the position of the target vehicle at time k, and the position at time k-1 is f(x k-1 ) is determined; the actual environment may have errors, so a noise amount u is added k-1 In the observation equation, yk represents the sensor observation value at time k, which is determined by the current target vehicle posture h(xk), v k is the actual environmental influence error. In this embodiment, the motion equation describes the position x at time k-1: k-1 How does it change to the position x at time k? k , the observation equation describes how to get from the pose x at time k k Get the observed data y k Therefore, the motion equation and observation equation can more realistically reflect the actual position of the target vehicle and the current environment.

[0073] Step S4: By calculating the speed in step S2 and the position of the target vehicle through the sensing information in step S3, the relative relationship between the target vehicle and other vehicles can be obtained, and single lanes, double lanes, and three lanes or more can be processed separately.

[0074] Specifically, the first case is a single lane. If there is only a single lane or a solid lane, the real-time speed of the vehicle in front and the deceleration of the target vehicle are obtained; wherein the vehicle in front is in front of the target vehicle; based on the real-time speed of the vehicle in front and the deceleration of the target vehicle, the minimum safe distance between the target vehicle and the vehicle in front is calculated; the road selection strategy is determined to be following driving without lane change; and the target vehicle is controlled to follow the vehicle in front at the minimum safe distance for normal driving. The process of calculating the minimum safe distance between the target vehicle and the vehicle in front can be: Where MSFD represents the minimum safe distance between the target vehicle and the vehicle ahead, s p It indicates the real-time speed of the vehicle ahead, and de indicates the deceleration of the target vehicle.

[0075] The second case is a two-lane road. Based on the perception information of the target vehicle, it is identified whether there is a vehicle in front of the target vehicle in the current lane and the side lane, and when there is a vehicle in front of the current lane and the side lane, the speed of the vehicle in front of the current lane and the vehicle in front of the side lane are compared; if the driving speed of the vehicle in front of the current lane is less than the driving speed of the vehicle in front of the side lane, the road selection strategy is determined to change to the side lane, and the target vehicle is controlled to change from the current lane to the side lane based on the perception information of the target vehicle in step S3; if the driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the side lane, the road selection strategy is determined to follow driving without lane change; and the target vehicle is controlled to follow the vehicle in front of the current lane at the minimum safe distance for normal driving.

[0076] The third case is three lanes or more. Based on the perception information of the target vehicle in step S3, the lane position of the target vehicle is identified. When the target vehicle is in the middle lane of the current road, the perception information of the target vehicle is used to identify whether there is a vehicle in front of the target vehicle in the current lane, the left lane and the right lane; and, when there is a vehicle in front of the current lane, the left lane and the right lane, the speed of the vehicle in front of the current lane is compared with the vehicle in front of the left lane and the vehicle in front of the right lane respectively; if the driving speed of the vehicle in front of the current lane is less than the driving speed of the vehicle in front of the left lane or the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to change to the lane with the fastest driving 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 driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the left lane, and greater than or equal to the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to follow the vehicle in front of the current lane at the minimum safe distance for normal driving.

[0077] Step S5: After receiving the information sent by the vehicle controller ECU, the cockpit control system will provide voice and card pop-up text mode prompts. If the driver is in manual driving mode, only text and voice prompts will be given for one-way communication without driver feedback. If in intelligent driving mode, the cockpit control system can be prompted to ask whether to change lanes to the adjacent lane. After receiving the user's interactive feedback, the cockpit control system will return the information to the vehicle controller ECU. If the user feedback does not require lane change, the vehicle will continue to drive in the current lane. If the user feedback requires lane change, the vehicle controller ECU will send the information to the intelligent driving control system, and the intelligent driving will control the vehicle to change lanes.

[0078] Step S6: When the vehicle controller ECU receives the congestion signal, after calculating the lane with the fastest traffic speed through step S4, this information is synchronized to the vehicle cloud system at the same time. The vehicle cloud system is a huge cloud system, and the same vehicle model driven by the driver is in the same vehicle cloud environment. If the vehicle cloud system receives the congestion information reported by the vehicle controller ECU, it will record the specific road section, time, and the optimal lane information after being processed by the vehicle controller ECU in the driver's target vehicle. At the same time, if there are other vehicles under the same vehicle cloud system, whether it is intelligent driving or manual driving, they will enter or have entered the current congested road section in a similar time period, then they will receive the optimal lane information issued by the vehicle cloud system, and voice and text prompts will be given. After human-computer interaction, intelligent driving can also automatically enter the optimal lane. If the vehicle controller ECU in the target vehicle has uploaded congestion information, lane information, and time information to the vehicle cloud system, it will no longer receive information issued by the vehicle cloud system to avoid blocking the channel between the vehicle controller ECU and the vehicle cloud system.

[0079] It can be seen from this that, in view of the fact that the current intelligent driving technology has not yet been perfected, how to choose a fast road to pass when encountering congested road conditions, the manual driving mode may also be unable to choose the optimal road to pass due to the unclear road conditions ahead. This embodiment can accurately identify whether the current road is congested through navigation, target vehicle driving information and vehicle-cloud system interaction; in the case of congestion, the optimal road can be quickly identified through the vehicle controller ECU and various related parts; after identifying the optimal road, the vehicle controller ECU can upload it to the vehicle-cloud system, and then the vehicle-cloud system will send the road information to the vehicle that will drive to the congested road. This method can help the driver identify the optimal lane in advance before the driver enters the congested road section through the cloud, and choose the optimal lane, and help the driver have a better driving experience. Therefore, this embodiment can greatly improve the time for fast passage in congested sections through the interaction between the target vehicle and the vehicle-cloud system. Regardless of whether the driver is in intelligent driving or manual driving mode, the current vehicle lane information and the fastest road information can be quickly obtained in a short time, which can help the driver quickly pass through the congested road section, thereby obtaining a better driving experience. Moreover, this embodiment greatly optimizes the system response time by adding interaction with the vehicle-cloud system. It can allow the driver to perceive the information of the current congested road in advance and quickly help the driver choose the best road. If it is manual driving, the driver can be prompted to enter the best road in advance. If it is an intelligent driving mode, the lane can also be changed to the best route in advance, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue.

[0080] In summary, the present application provides a method for selecting a vehicle driving road. First, the traffic state 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. When the current road is in a congested state, the sensor data is used to perform synchronous positioning and map construction to generate the perception information of the target vehicle; then the driving speed of the target vehicle is calculated according to 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; at the same time, the target vehicle is controlled to change lanes according to the road selection strategy, so that the target vehicle's travel time after the lane change is less than or equal to the travel time before the lane change. It can be seen that this method is aimed at how to choose a fast road to pass when the current intelligent driving technology is not perfect and encounters congested road conditions, and the manual driving mode may also be unable to choose the optimal road to pass due to the unclear road conditions ahead. The current vehicle's driving data and the map data of the current road can be used to quickly obtain the lane with a relatively short travel time in the current road in a short time. When the target vehicle is changed to a lane with a relatively short travel time after control, the travel time of the target vehicle on the current road can be reduced. In addition, by uploading the traffic status of the current road to the cloud, the traffic status of the current road can be pushed to other vehicles connected to the cloud, thereby helping the drivers of other vehicles to identify the lanes with the fastest traffic flow in congested roads in advance, making it easier for the drivers of other vehicles to change lanes to the optimal route in advance and quickly pass through congested sections. If other vehicles use intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed by the cloud, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue.

[0081] In another exemplary embodiment of the present application, Figure 4 As shown, this embodiment also provides a vehicle driving road 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 including an intelligent driving function and a manual driving function, or a vehicle including only a manual driving function, or a vehicle including only an intelligent driving function. In this embodiment or other embodiments, the target vehicle can also be referred to as a self-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, referred to as ECU).

[0083] The perception information module 420 is used to perform synchronous positioning and map construction through sensor data to generate perception information of the target vehicle when the current road is in a congested state; 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 laser radar, millimeter wave radar, ultrasonic radar, image capture device (such as camera), etc.

[0084] A 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 a road selection strategy for 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] It can be seen that this embodiment aims at how to choose a fast road to pass when encountering congested road conditions when the current intelligent driving technology is not perfect, and the situation that the manual driving mode may not be able to choose the best road to pass due to unclear road conditions ahead. Through the driving data of the current vehicle and the map data of the current road, the lane with a relatively short travel time on the current road can be quickly obtained in a short time. When the target vehicle is controlled to change to a lane with a relatively short travel time, the travel time of the target vehicle on the current road can be reduced. Therefore, this embodiment can help the driver identify the lane with the fastest traffic flow on the congested road in advance and quickly pass the congested section.

[0087] In an exemplary embodiment, the process of identifying the traffic state 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: obtaining the speed data and geographic 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 sections of the current road is less than or equal to the preset speed, or the geographic location change distance of more than a preset number of vehicles in one or more sections of the current road is less than or equal to the preset distance, then the corresponding section is recorded as the target section, and the traffic state of the target section is marked as a congested state; and, based on the driving data of the target vehicle on the target section, obtaining the interval distance between the target vehicle and the front vehicle, and calculating the average driving speed of the front vehicle within a preset time period through the interval distance; and, based on the speed limit of the target section and the average driving speed of the front vehicle within the preset time period, determining the traffic state of the target vehicle on the target section; wherein the front vehicle is located in front of the target vehicle; and determining the traffic state of the current road according to the traffic state of the target section and the traffic state of the target vehicle on the target section. As an example, in this embodiment or other embodiments, the preset number and the preset vehicle speed can be set according to actual conditions, and this embodiment does not limit the specific numerical values.

[0088] Specifically, Figure 2 As shown, Figure 2 Figure 1 shows a schematic diagram of a target vehicle traveling on a certain road section. Figure 2 In the figure, A is the target vehicle, B and C are the vehicles in front of the target vehicle A, point P is the camera position of the target vehicle A, image plane I is generated by the projection points of vehicles B and C after they are reversed through point P, f is the focal length of the camera, H is the height of the camera, y1 and y2 are the distances from point 0 projected from vehicle B and vehicle C on image plane I, and z1 and z2 are the distances from vehicle B and vehicle C to the target vehicle A. Therefore, the process of determining the traffic status of the target vehicle on the target road section in this embodiment can be: It can be known from the similar triangle formula: At the same time from Figure 2 It can be seen that the farther the vehicle is, the smaller the distance y between the bottom of the vehicle and the horizontal line in the image plane I is. The distance y of the front vehicle projected onto the image plane I can be obtained by converting the coordinate system after the camera P takes a photo of the front vehicle. Therefore, the average speed v of the front vehicle in the time period Δt can be expressed as: Thus, the average speed of the vehicle ahead in the time period Δt can be calculated, and then the speed limit of the current road section can be obtained through the map data in the map software. Assuming that the average speed v of the vehicle ahead in the time period Δt is lower than 30% of the speed limit, it can be considered that the lane where the target vehicle is located is congested, and the same applies to other lanes. At this time, if the target vehicle uploads the congestion information to the cloud, if there are other vehicles connected to the cloud on the current road section, the other vehicles can receive the congestion information of this road section. As an example, in this embodiment or other embodiments, when the target vehicle uploads the congestion information to the cloud, the congestion information can be uploaded to the cloud through the vehicle controller in the target vehicle.

[0089] In an exemplary embodiment, when identifying the traffic state 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, it can also include: recording the traffic state obtained based on the map data of the current road as the map traffic state, and recording the traffic state obtained based on the driving data of the target vehicle on the current road as the driving traffic state; judging whether the map traffic state is consistent with the driving traffic state; if the map traffic state is consistent with the driving traffic state, the map traffic state or the driving traffic state is used as the traffic state of the current road; if the map traffic state is inconsistent with the driving traffic state, the driving traffic state is used as the traffic state of the current road; and uploading the traffic state of the current road to the cloud, and pushing the traffic state of the current road to other vehicles connected to the cloud. It can be seen that when identifying the traffic state of the current road, this embodiment also determines the priority of the map data and the driving data. Since the driving data is real-time and true, when the map traffic state is inconsistent with the driving traffic state, this embodiment uses the driving traffic state as the traffic state of the current road to avoid the delay error caused by the map data. At the same time, by uploading the traffic status of the current road to the cloud, this embodiment can push the traffic status of the current road to other vehicles connected to the cloud, thereby helping the drivers of other vehicles to identify the lane with the fastest traffic flow in the congested road in advance, and facilitating the drivers of other vehicles to change lanes to the optimal route in advance and quickly pass through the congested road section. If other vehicles adopt the intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed by the cloud, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue.

[0090] In an exemplary embodiment, the process of performing simultaneous positioning and mapping through sensor data to generate the perception information of the target vehicle includes: obtaining laser point cloud data of the surrounding environment of the target vehicle through a laser radar pre-configured on the target vehicle, and constructing sensor data through view data collected by an image capture device pre-configured on the target vehicle; using the sensor data to perform simultaneous positioning and mapping to construct the motion equation and observation equation of the target vehicle; wherein the motion equation is used to characterize the position change of the target vehicle at different times, and the observation equation is used to characterize the surrounding environment characteristics observed by the target vehicle at different positions; based on the motion equation and observation equation of the target vehicle, the perception information of the target vehicle is generated. Specifically, in this embodiment, when the current road is in a congested state, the lane information of the target vehicle can be fed back through the simultaneous positioning and mapping (SLAM) method, for example, the laser point cloud data of the surrounding environment of the target vehicle is obtained through a laser radar, and the laser radar can measure the angle and distance of objects around the car with high accuracy. In terms of vision, the data collected by the camera is used for simultaneous positioning and mapping; at the same time, the perception information of the target vehicle can be regarded as a mathematical modeling process, then there is a motion equation x k =f(x k-1 )+u k-1 and the observation equation y k =h(x k )+v k In the equation of motion, x k represents the position of the target vehicle at time k, and the position at time k-1 is f(x k-1 ) is determined; the actual environment may have errors, so a noise amount u is added k-1 This forms certain constraints on the change of posture. In the observation equation, y k represents the sensor observation value at time k, which is represented by the current target vehicle position h(x k ) decides, k is the actual environmental influence error. In this embodiment, the motion equation describes the position x at time k-1: k-1 How does it change to the position x at time k? k , the observation equation describes how to get from the pose x at time k k Get the observed data y k Therefore, the motion equation and observation equation can more realistically reflect the actual position of the target vehicle and the current environment.

[0091] In an exemplary embodiment, if the current road includes only one lane, a road selection strategy for the target vehicle is generated, and a process of 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 driving without changing lanes; and controlling the target vehicle to follow the vehicle in front for normal driving at 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: Where MSFD represents the minimum safe distance between the target vehicle and the vehicle ahead, s p It 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, 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: identifying whether there is a vehicle in front of the target vehicle in the current lane and the side lane based on the perception information of the target vehicle, and when there is a vehicle in front of the current lane and a vehicle in front of the side lane, comparing the speeds of the vehicle in front of the current lane and the vehicle in front of the side lane; if the driving speed of the vehicle in front of the current lane is less than the driving speed of the vehicle in front of the side lane, determining the road selection strategy to change to the side lane, and controlling the target vehicle to change from the current lane to the side lane based on the perception information of the target vehicle; if the driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the side lane, determining the road selection strategy to follow driving without changing lanes; and controlling the target vehicle to follow the vehicle in front of the current lane at a minimum safety 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, and a 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 perception information of the target vehicle; 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 perception information of the target vehicle; and when there are vehicles in front of the current lane, the left lane, and the right lane, respectively, comparing the vehicles in front of the current lane with the vehicles in front of the left lane and the vehicles in front of the right lane. Perform speed comparison; 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, determine the road selection strategy to change to the lane with the fastest driving speed, and control the target vehicle 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 in front of the current lane is greater than or equal to the speed of the vehicle in front of the left lane, and greater than or equal to the speed of the vehicle in front of the right lane, determine the road selection strategy to follow driving without lane change; and control the target vehicle to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

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

[0095] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the right lane, and the speed of the vehicle in front of the left lane is higher 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 driving 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 perception information of the target vehicle.

[0096] As another example, if the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the left lane, and the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the right lane, and at the same time the driving speed of the vehicle in front of the left lane is equal to the driving 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 driving speed, that is, the road selection strategy is determined to change to the left lane or the right lane, and based on the perception information of the target vehicle, the target vehicle is controlled to change from the current lane to the left lane or the right lane.

[0097] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the left lane, the road selection strategy is determined to change to the lane with the fastest driving 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 perception information of the target vehicle.

[0098] As another example, if the speed of the vehicle in front of the current lane is lower 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 lower than the speed of the vehicle in front of the left lane, and the speed of the vehicle in front of the right lane is higher 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 driving 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 perception information of the target vehicle.

[0099] In summary, the present application provides a vehicle driving road selection system, firstly, based on the map data of the current road and the driving data of the target vehicle on the current road, the traffic state of the current road is identified, when the current road is in a congested state, the sensor data is used to perform synchronous positioning and map construction, and the perception information of the target vehicle is generated; then the driving speed of the target vehicle is calculated according to 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; at the same time, the target vehicle is controlled to change lanes according to the road selection strategy, so that the passing time of the target vehicle after the lane change is less than or equal to the passing time before the lane change. It can be seen that the system is aimed at how to choose a fast road to pass when the current intelligent driving technology is not perfect and encounters congested road conditions, and the manual driving mode may also be unable to choose the best road to pass due to the unclear road conditions ahead. The current vehicle's driving data and the map data of the current road can be used to quickly obtain the lane with a relatively short passing time in the current road in a short time. When the target vehicle is changed to a lane with a relatively short passing time after control, the passing time of the target vehicle on the current road can be reduced. In addition, by uploading the traffic status of the current road to the cloud, the traffic status of the current road can be pushed to other vehicles connected to the cloud, thereby helping the drivers of other vehicles to identify the lanes with the fastest traffic flow in congested roads in advance, making it easier for the drivers of other vehicles to change lanes to the optimal route in advance and quickly pass through congested sections. If other vehicles use intelligent driving mode, they can also change lanes to the optimal route in advance based on the traffic status pushed by the cloud, which greatly improves the driver's driving experience, improves the stickiness of human-computer interaction, and helps the driver reduce driving fatigue.

[0100] It should be noted that the vehicle driving road selection system provided in the above embodiment and the vehicle driving road selection method provided in the above embodiment belong to the same concept, wherein the specific manner in which the vehicle driving road selection method performs operations has been described in detail in the above method embodiment, and will not be repeated here. In actual applications, the vehicle driving road selection system provided in the above embodiment can allocate the above functions to different functional modules as needed, that is, divide the internal structure of the vehicle driving road selection system into different functional modules, and then implement all or part of the functions of the corresponding functional modules through the vehicle driving road selection method described in the above embodiment, and this is not specifically limited here.

[0101] The embodiment of the present application also provides a vehicle-mounted control device, which may include a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to enable the vehicle-mounted control device to execute Figure 1 The steps of the vehicle driving road selection method. Figure 51 shows a schematic diagram of the structure of a vehicle-mounted control device 1000. Figure 5 As shown, the vehicle-mounted 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 uses various interfaces and lines to connect various components, and executes various functions of the vehicle control device 1000 by running or executing computer programs / instructions stored in the memory 1020, thereby monitoring the vehicle control device 1000 as a whole. In the embodiment of the present application, when the processor 1010 calls the computer program stored in the memory 1020, the following is executed: Figure 1 The steps of the vehicle driving road selection method. 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 processes the operating system, user interface and application, etc., and the modem processor mainly processes wireless communication. In some embodiments, the processor and the memory may be implemented on a single chip, and in some embodiments, they may also be implemented separately on separate chips.

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

[0104] The vehicle-mounted control device 1000 also includes a power source 1030 (such as a battery) for supplying power to various components. The power source can be logically connected to the processor 1010 through a power management system, thereby managing functions such as charging, discharging, and power consumption through the power management system.

[0105] The display unit 1040 may be used to display information input by the user or information provided to the user and various menus of the vehicle control device 1000, and in the embodiment of the present application, it is mainly used to display the display interface of each application in the vehicle control device 1000 and objects such as text and pictures displayed in the display interface. 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), etc.

[0106] The input unit 1060 may 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, may collect touch operations of the user on or near it (such as operations of the user using a finger, a stylus, or any other suitable object or accessory on or near the touch panel 1070).

[0107] Specifically, the touch panel 1070 can detect the user's touch operation, detect the signal brought by the touch operation, convert these signals into touch point coordinates, send them to the processor 1010, and receive and execute the command sent by the processor 1010. In addition, the touch panel 1070 can be implemented in various types such as resistive, capacitive, infrared and surface acoustic wave. Other input devices 1080 can include but are not limited to one or more of a physical keyboard, function keys (such as volume control keys, power on / off keys, etc.), a trackball, a mouse, a 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 is transmitted to the processor 1010 to determine the type of touch event, and then the processor 1010 provides a corresponding visual output on the display panel 1050 according to the type of touch event. Figure 5 In the embodiment, the touch panel 1070 and the display panel 1050 are two independent components to realize the input and output functions of the vehicle control device 1000, but 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-mounted control device 1000 may further include one or more sensors, such as a pressure sensor, a gravity acceleration sensor, a proximity light sensor, etc. Of course, according to the needs of specific applications, the vehicle-mounted control device 1000 may also include other components such as a camera.

[0110] The embodiment of the present application also provides a computer-readable storage medium, in which a computer program / instruction is stored. When the computer program / instruction is executed by a processor, the above-mentioned device can perform the above-mentioned Figure 1 The steps of the vehicle driving road selection method.

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

[0112] Those skilled in the art should understand that the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be applied to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the functions in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be stored in a computer-readable memory that can guide a computer or other programmable data processing device to work in a specific way, so that the instructions stored in the computer-readable memory produce a product including an instruction device, which implements the functions specified in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide for implementing the process in the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] In another exemplary embodiment of the present application, the embodiment further provides a vehicle, which includes a vehicle driving road selection system as described in the above embodiment, or includes a vehicle-mounted control device as described in the above embodiment. It should be noted that since the specific manner in which the vehicle driving road selection system and the vehicle-mounted control device perform operations have been described in detail in the embodiments, the technical functions and effects of the vehicle provided in this embodiment can be referred to the above embodiments, and will not be repeated here.

[0114] It should be noted that the above embodiments collect, store, use, process, transmit, provide, disclose, delete, etc. related data (such as map data, driving data, etc.) with or with the consent of the user. For example, map data and driving data are authorized with the knowledge and consent of the user; or are actively provided 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 in other ways / channels with or with the consent of the user.

[0115] The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims

1. A method for selecting a vehicle driving road, characterized in that: The method comprises the following steps: Identifying the traffic state 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, wherein the traffic state includes: a congested state and a normal traffic state; wherein the current road includes at least one lane; When the current road is in a congested state, synchronous positioning and map construction are performed through sensor data to generate perception information of the target vehicle; wherein the sensor data is generated by a sensor pre-configured on the target vehicle; Calculating the driving speed of the target vehicle according to the driving data of the target vehicle on the current road, and associating the perception information of the target vehicle with the number of lanes on the current road to generate a road selection strategy for 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.

2. The vehicle driving road selection method according to claim 1, characterized in that: 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, the speed data and the geographic location data of multiple vehicles are obtained. If the real-time speed of more than a preset number of vehicles in one or more sections of the current road is less than or equal to the preset speed, or the geographic location change distance of more than a preset number of vehicles in one or more sections of the current road is less than or equal to the preset distance, the corresponding section is recorded as a target section, and the traffic status of the target section is marked as a congested state; and, Based on the driving data of the target vehicle on the target road section, the interval distance between the target vehicle and the front vehicle is obtained, and the average driving speed of the front vehicle in a preset time period is calculated according to the interval distance; and based on the speed limit of the target road section and the average driving speed of the front vehicle in the preset time period, the traffic state of the target vehicle on the target road section is determined; wherein the front vehicle is located in front of the target vehicle; The traffic state of the current road is determined according to the traffic state of the target road section and the traffic state of the target vehicle on the target road section.

3. The vehicle driving road selection method according to claim 1, characterized in that: The process of performing synchronous positioning and map construction through sensor data to generate the perception information of the target vehicle includes: Acquiring laser point cloud data of the surrounding environment of the target vehicle through a laser radar pre-configured on the target vehicle, and constructing and generating the sensor data through view data collected by an image capture device pre-configured on the target vehicle; The sensor data is used to perform synchronous positioning and map construction to construct a motion equation and an observation equation for the target vehicle; wherein the motion equation is used to characterize the position and posture changes of the target vehicle at different times, and the observation equation is used to characterize the surrounding environment characteristics observed by the target vehicle at different positions and postures; The perception information of the target vehicle is generated based on the motion equation and observation equation of the target vehicle.

4. The vehicle driving road selection method according to any one of claims 1 to 3, characterized in that: 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: Acquire the real-time speed of the front vehicle and the deceleration of the target vehicle; wherein the front vehicle is located in front of the target vehicle; Calculating a minimum safe distance between the target vehicle and the vehicle ahead based on the real-time speed of the vehicle ahead and the deceleration of the target vehicle; The road selection strategy is determined as following driving without changing lanes; and the target vehicle is controlled to follow the front vehicle at the minimum safety distance for normal driving.

5. The vehicle driving road selection method according to any one of claims 1 to 3, characterized in that: 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: Identify whether there is a vehicle ahead of the target vehicle in the current lane and the adjacent lane based on the sensing information of the target vehicle, and compare the speeds of the vehicle ahead of the current lane and the vehicle ahead of the adjacent lane when there is a vehicle ahead of the current lane and a vehicle ahead of the adjacent lane; If the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to be changed 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 driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the adjacent lane, the road selection strategy is determined to be following driving without changing lanes; and the target vehicle is controlled to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

6. The vehicle driving road selection method according to any one of claims 1 to 3, characterized in that: If the current road includes only three or more lanes, a road selection strategy for the target vehicle is generated, and a process of controlling the target vehicle to change lanes according to the road selection strategy includes: Identifying a lane position of the target vehicle based on the perception information of the target vehicle; When the target vehicle is in the middle lane of the current road, identifying whether there is a vehicle in front of the target vehicle in the current lane, the left lane and the right lane based on the perception information of the target vehicle; and when there is a vehicle in front of the current lane, the left lane and the right lane, comparing the speed of the vehicle in front of the current lane with the vehicle in front of the left lane and the vehicle in front of the right lane respectively; If the driving speed of the vehicle in front of the current lane is lower than the driving speed of the vehicle in front of the left lane or the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to change to the lane with the fastest driving 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 driving speed of the vehicle in front of the current lane is greater than or equal to the driving speed of the vehicle in front of the left lane, and greater than or equal to the driving speed of the vehicle in front of the right lane, the road selection strategy is determined to be following driving without changing lanes; and the target vehicle is controlled to follow the vehicle in front of the current lane at a minimum safe distance for normal driving.

7. The vehicle driving road selection method according to claim 1 or 2, characterized in that: When identifying the traffic state 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 method further includes: Recording the traffic state obtained based on the map data of the current road as the map traffic state, and recording the traffic state obtained based on the driving data of the target vehicle on the current road as the driving traffic state; Determining whether the map traffic status is consistent with the driving traffic status; If the map traffic state is consistent with the driving traffic state, the map traffic state or the driving traffic state is used as the traffic state of the current road; If the map traffic status is inconsistent with the driving traffic status, the driving traffic status is used as the traffic status of the current road; and the traffic status of the current road is uploaded to the cloud, and the traffic status of the current road is pushed to other vehicles connected to the cloud.

8. A vehicle driving road selection system, characterized in that: The system comprises: A traffic status module, 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, wherein the traffic status includes: congestion status and normal traffic status; wherein the current road includes at least one lane; A perception information module, used to perform synchronous positioning and map construction through sensor data to generate perception information of the target vehicle when the current road is in a congested state; wherein the sensor data is generated by a sensor pre-configured on the target vehicle; A road selection strategy module, used to calculate the driving speed of the target vehicle according to 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 a road selection strategy for 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.

9. A vehicle-mounted control device, characterized in that: The invention comprises 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 as claimed in any one of claims 1 to 7.

10. A vehicle, characterized in that: The vehicle includes the vehicle driving road selection system as claimed in claim 8, or includes the vehicle-mounted control device as claimed in claim 9.

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