Vehicle location determination methods and devices, radar, storage media

Abstract

This application provides a vehicle position determination method, apparatus, radar, and storage medium. The method includes: acquiring M-frame echo signals corresponding to a radar with a frame length of M frames; wherein each echo signal in the M-frame echo signals includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by a vehicle on a target road, and the target road is the road detected by the radar; determining the lane where the vehicle is located on the target road in each echo signal based on the M-frame echo signals; if the lane where the vehicle is located on the target road includes a first lane and an adjacent lane of the first lane, calculating the probability values ​​of the vehicle being in the first lane and the adjacent lane in each echo signal based on the M-frame echo signals; wherein the first lane is the lane where the vehicle is located as determined based on the previous echo signal from the radar; and determining the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each echo signal. This application can accurately determine the vehicle position.

Description

Technical Field

[0001] This application relates to the field of radar technology, and in particular to a vehicle position determination method and device, radar, and storage medium. Background Technology

[0002] In enclosed environments, radar is prone to unstable vehicle measurement data due to multipath effects, resulting in vehicle tracks exhibiting jitter and serpentine movement. When a vehicle is in motion, if jitter and serpentine movement occur, existing radar technologies may misjudge the vehicle's position. For example, due to jitter and serpentine movement, the radar may mistakenly believe that the vehicle has changed lanes, uploading the incorrect lane change event to the monitoring platform, which will affect the effectiveness of the track display on the monitoring platform.

[0003] Therefore, there is an urgent need for a method that can accurately determine the location of vehicles to solve the above problems. Summary of the Invention

[0004] This application provides a vehicle location determination method and device, radar, and storage medium to solve the problem that the accuracy of vehicle location determination is low in the prior art, which affects the trajectory display effect of the intelligent platform.

[0005] In a first aspect, embodiments of this application provide a method for determining the location of a vehicle, including:

[0006] The radar acquires M-frame echo signals with a frame length of M frames; each frame of the M-frame echo signals includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by vehicles on the target road, and the target road is the road detected by the radar;

[0007] The lane in which the vehicle is located on the target road is determined based on the M-frame echo signal;

[0008] If the vehicle is in a lane on the target road that includes the first lane and the adjacent lane of the first lane, then the probability value of the vehicle being in the first lane and the adjacent lane in each frame of the echo signal is calculated based on the M-frame echo signal.

[0009] The first lane is the lane where the vehicle is located, as determined by the previous frame echo signal of the radar.

[0010] The current position of the vehicle is determined based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal.

[0011] In one possible implementation, determining the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal includes:

[0012] The corresponding lane change factor is determined based on the relative magnitude of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal; wherein, the lane change factor is used to determine whether the vehicle has changed lanes;

[0013] The current position of the vehicle is determined based on the lane change factor.

[0014] In one possible implementation, determining the corresponding lane change factor based on the relative magnitudes of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal includes:

[0015] according to Determine the corresponding lane change factor, or determine the corresponding lane change factor based on δ = P1 - P2;

[0016] Wherein, δ is the lane change factor corresponding to a single frame echo signal, P1 is the probability value of the vehicle in the adjacent lane in the single frame echo signal, and P2 is the probability value of the vehicle in the first lane in the single frame echo signal.

[0017] In one possible implementation, determining the current position of the vehicle based on the lane change factor includes:

[0018] If the lane change factor corresponding to N echo signals in M ​​frame echo signals is greater than the first preset value, then the preset position on the adjacent lane is determined as the current position of the vehicle.

[0019] If the lane change factor corresponding to N echo signals in M ​​frame echo signals is less than the second preset value, then the preset position on the first lane is determined as the current position of the vehicle.

[0020] If the lane change factor corresponding to N echo signals in M ​​frame echo signals is not less than a second preset value and not greater than a first preset value, then the target position on the first lane is determined as the current position of the vehicle; wherein, the target position on the first lane is located between the preset position on the first lane and the preset position on the adjacent lane.

[0021] In one possible implementation, calculating the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal includes:

[0022] Through formula Calculate the probability value of the vehicle being in the first lane and the adjacent lane in each frame of echo signal;

[0023] Among them, h ik is the probability value of the vehicle being in the first lane or the adjacent lane in a single frame of echo signal. i The number of echo signals of the vehicle in the first lane or the adjacent lane in a single frame of echo signal, where k is the total number of echo signals of the vehicle in the first lane and the adjacent lane in a single frame of echo signal.

[0024] In one possible implementation, determining the lane of the vehicle on the target road in each frame of the M-frame echo signal includes:

[0025] A coordinate system is established with the horizontal center point of the target road as the origin, the horizontal direction of the target road as the x-axis, and the lane direction as the y-axis.

[0026] The x-axis coordinate of the vehicle in the coordinate system is calculated based on the M-frame echo signals.

[0027] Based on the x-axis coordinate of the vehicle in each frame of the echo signal in the coordinate system, determine the lane on the target road in each frame of the echo signal.

[0028] In one possible implementation, the vehicle position determination method further includes: if the vehicle is in a lane on the target road that contains only one lane, then a preset position on that lane is determined as the vehicle's current position.

[0029] Secondly, embodiments of this application provide a vehicle location determination device, comprising:

[0030] The signal acquisition module is used to acquire M-frame echo signals corresponding to the radar with a frame length of M frames; wherein, each frame echo signal in the M-frame echo signal includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by vehicles on the target road, and the target road is the road detected by the radar;

[0031] The lane determination module is used to determine the lane on the target road where the vehicle is located in each frame of the echo signal based on the M-frame echo signal.

[0032] The probability value calculation module is used to calculate the probability value of the vehicle in the first lane and the adjacent lane in each frame of the echo signal based on the M-frame echo signal if the lane in which the vehicle is located on the target road includes the first lane and the adjacent lane of the first lane.

[0033] The first lane is the lane where the vehicle is located, as determined by the previous frame echo signal of the radar.

[0034] A location determination module is used to determine the current location of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal.

[0035] Thirdly, embodiments of this application provide a radar including a processing terminal. The processing terminal includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect or any possible implementation of the first aspect.

[0036] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method as described in the first aspect or any possible implementation of the first aspect.

[0037] The beneficial effects of the vehicle location determination method and device, radar, and storage medium provided in this application embodiment are as follows:

[0038] In this embodiment, considering that in the prior art, if a vehicle experiences shaking or serpentine movement while driving, the radar may misjudge the vehicle's position. This embodiment acquires the corresponding M-frame echo signals from the radar and determines the lane the vehicle is in on the target road in each echo frame, thus more accurately determining the vehicle's lane. This application calculates the probability values ​​of the vehicle being in the first lane and the adjacent lane, further clarifying the vehicle's lane in each echo frame. It also calculates the probability values ​​for both lanes in each echo frame, using these probability values ​​from each of the M echo frames to determine the vehicle's current position. Based on this solution, radar misjudgment can be avoided when shaking or serpentine movement occurs, and the vehicle's current position determined by calculating probability values ​​is more accurate. In other words, this application can more accurately determine the vehicle's current position, avoiding radar misjudgment and thus effectively solving the problems of the prior art. Attached Figure Description

[0039] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0040] Figure 1 This is a flowchart illustrating the vehicle location determination method provided in the embodiments of this application;

[0041] Figure 2This is a schematic diagram of the coordinate system provided in the embodiments of this application;

[0042] Figure 3 This is a schematic diagram of the radar's determination of lane change events provided in an embodiment of this application;

[0043] Figure 4 This is a schematic diagram of the vehicle position determination device provided in the embodiments of this application;

[0044] Figure 5 This is a schematic diagram of the radar processing terminal provided in the embodiments of this application. Detailed Implementation

[0045] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0046] To make the objectives, technical solutions, and advantages of this application clearer, the following description will be provided in conjunction with the accompanying drawings and specific embodiments.

[0047] Figure 1 This is a flowchart illustrating the vehicle location determination method provided in an embodiment of this application. Figure 1 As shown, the method includes:

[0048] S101: Acquire the M-frame echo signal corresponding to the radar with a frame length of M frames. Each frame of the M-frame echo signal includes multiple echo signals. These multiple echo signals are single-frame echo signals reflected by vehicles on the target road, which is the road detected by the radar.

[0049] In this embodiment, the radar, which can be a millimeter-wave radar, is installed on the target road. This application allows a side-mounted or front-mounted millimeter-wave radar and camera to be connected to an edge computing unit via a network cable, sending the data to a smart platform. The radar generates a transmitted signal, which is reflected by the vehicle target's reflection point to form an echo signal. Each echo signal frame includes multiple echo signals corresponding to the radar. This application uses M frames as the frame length to determine the current vehicle's position, effectively avoiding the problem of inaccurate determination in a single frame.

[0050] S102: Determine the lane of the vehicle on the target road in each frame of echo signal based on the M-frame echo signal.

[0051] In this embodiment, a coordinate system can be established based on the actual road conditions. The positional relationship between the vehicle and the radar along the x-axis of the coordinate system can be determined based on the echo signals, thereby determining the vehicle's x-axis coordinate in the coordinate system. The vehicle's lane on the target road can be determined using its x-axis coordinate. For example, with M=5, in 5 echo signals, the lane on the target road determined based on the first echo signal is lane 1. Subsequently, the lane numbers determined sequentially based on each echo signal frame are lane 1, lanes 1 and 2, lanes 1 and 2, and lanes 1 and 2.

[0052] In real-world scenarios, determining the vehicle's lane on the target road based on the M-frame echo signal could involve two lanes (the first lane and its adjacent lane) or just one lane. For example, in the case of M=5, the vehicle's lane on the target road would be determined to be either lane 1 (the first lane) or lane 2 (the adjacent lane of the first lane).

[0053] S103: If the vehicle's lane on the target road includes the first lane and the adjacent lane of the first lane, then calculate the probability value of the vehicle being in the first lane and the adjacent lane in each frame of the echo signal based on the M-frame echo signal.

[0054] The first lane is the lane where the vehicle is located, determined based on the echo signal from the previous radar frame.

[0055] In this embodiment, the first lane is the lane the vehicle was in before changing lanes, and the adjacent lanes of the first lane are the lanes the vehicle is in after changing lanes. If the vehicle is in a lane on the target road that includes the first lane and its adjacent lanes, it indicates that the vehicle may have changed lanes. In this application, a probability value can be calculated once based on each frame of echo signal. Therefore, based on M frames of echo signals, M probability values ​​of the vehicle being in the first lane and in an adjacent lane can be calculated. Calculating the probability values ​​of the vehicle being in the first lane and in an adjacent lane in each frame of echo signal based on M frames of echo signals can further determine whether the vehicle has changed lanes, effectively improving the accuracy of lane change judgment and thus improving the accuracy of vehicle position determination.

[0056] S104: Determine the vehicle's current position based on the probability values ​​of the vehicle being in the first lane and in the adjacent lane in each frame of echo signal.

[0057] In this embodiment, the vehicle's position in a given frame is determined based on the probability values ​​of the vehicle being in the first lane and in an adjacent lane in a single frame of echo signal. The vehicle's position in each of the M echo frames is determined based on the probability values ​​of the vehicle being in the first lane and in an adjacent lane in each of the M echo frames. Determining the vehicle's current position based on the position in each of the M echo frames can effectively improve the accuracy of vehicle position determination.

[0058] In this embodiment, considering that in the prior art, if a vehicle experiences shaking or serpentine movement while driving, the radar may misjudge the vehicle's position. This embodiment acquires the corresponding M-frame echo signals from the radar and determines the lane the vehicle is in on the target road in each echo frame, thus more accurately determining the vehicle's lane. This application calculates the probability values ​​of the vehicle being in the first lane and the adjacent lane, further clarifying the vehicle's lane in each echo frame. It also calculates the probability values ​​for both lanes in each echo frame, using these probability values ​​from each of the M echo frames to determine the vehicle's current position. Based on this solution, radar misjudgment can be avoided when shaking or serpentine movement occurs, and the vehicle's current position determined by calculating probability values ​​is more accurate. In other words, this application can more accurately determine the vehicle's current position, avoiding radar misjudgment and thus effectively solving the problems of the prior art.

[0059] In one possible implementation, determining the vehicle's current position based on the probability values ​​of the vehicle being in the first lane and in the adjacent lane in each frame of echo signal includes:

[0060] The lane change factor is determined based on the relative magnitudes of the probability values ​​of a vehicle being in the first lane and the adjacent lane in each frame of the echo signal. The lane change factor is used to determine whether a vehicle has changed lanes.

[0061] The vehicle's current position is determined based on the lane change factor.

[0062] In this embodiment, considering that the probability value of a vehicle in the first lane and the adjacent lane will change when changing lanes, this embodiment of the application can know which lane the vehicle is in based on the relative magnitude of the probability values ​​of the vehicle in the two lanes, and thus determine the current position of the vehicle.

[0063] In this embodiment, considering that in the prior art, if a vehicle experiences vibration or serpentine movement while driving, the radar may mistakenly interpret it as a lane change. This application addresses this issue by recognizing that vehicles typically change lanes between two lanes. If it is determined that a vehicle is in two lanes (the first lane and its adjacent lane), this application further determines whether the vehicle has changed lanes by using the probability values ​​of the vehicle being in the first lane and the adjacent lane—that is, the probability values ​​of the vehicle being in both lanes. Based on this application's solution, it can avoid misinterpreting vibration or serpentine movement occurring in only one lane as a lane change, and it can also avoid misinterpreting vibration or serpentine movement occurring in two lanes by calculating probability values. In other words, this application can more accurately determine whether a vehicle has changed lanes, preventing the radar from misinterpreting vibration or serpentine movement as a lane change.

[0064] In one possible implementation, the corresponding lane change factor is determined based on the relative magnitudes of the probability values ​​of a vehicle in the first lane and in the adjacent lane in each frame of echo signal, including:

[0065] according to Determine the corresponding lane change factor, or determine the corresponding lane change factor based on δ = P1 - P2.

[0066] Where δ is the lane change factor corresponding to a single frame echo signal, P1 is the probability value of a vehicle in an adjacent lane in a single frame echo signal, and P2 is the probability value of a vehicle in the first lane in a single frame echo signal.

[0067] In this embodiment, the lane change factor can be determined based on the ratio or difference between the probability values ​​of a vehicle in the first lane and the probability values ​​of it in the adjacent lane. In this embodiment, the lane change factor mainly reflects the changing trend of the probability values ​​of a vehicle being in two lanes. In real lane change scenarios, the probability value of a vehicle in the adjacent lane will always increase, while the probability value of a vehicle in the first lane will decrease. Therefore, the lane change factor obtained based on the ratio or difference can be used to determine whether a vehicle should change lanes.

[0068] In one possible implementation, determining the vehicle's current position based on a lane change factor includes:

[0069] If the lane change factor corresponding to N echo signals in M ​​frames is greater than the first preset value, then the preset position on the adjacent lane is determined as the vehicle's current position.

[0070] If the lane change factor corresponding to N echo signals in M ​​frames is less than the second preset value, then the preset position on the first lane is determined as the current position of the vehicle.

[0071] If the lane change factor corresponding to N echo signals in M ​​frames is not less than a second preset value and not greater than a first preset value, then the target position on the first lane is determined as the vehicle's current position. The target position on the first lane is located between a preset position on the first lane and a preset position on the adjacent lane.

[0072] In this embodiment, for example, when a vehicle is driving in a serpentine pattern, the vehicle may be in two lanes. At this time, the lane change factor determined by a single frame of echo signal may be greater than the first preset value. However, the vehicle has not changed lanes at this time. Therefore, the vehicle position determined by a single frame of echo signal is random and not accurate enough.

[0073] In this embodiment, the preset position on the adjacent lane or the first lane can be set and modified according to actual needs. For example, it can be the center position of the lane. The target position on the first lane is located at the connection between the first lane and the adjacent lane, and is closer to the adjacent lane than the preset position on the first lane. The target position of the vehicle on the first lane facilitates a smooth transition to the adjacent lane in real lane-changing scenarios.

[0074] For example, if a vehicle was previously in lane 1 and later changed to lane 2 during a certain frame detection, but the lane change factor δ does not meet the first preset value, it may be due to unstable echo signals. In this case, the predicted position of the vehicle is definitely between lanes 1 and 2. Therefore, this application sets an intermediate transition interval, that is, the lane change factor is not less than the second preset value and not greater than the first preset value. When the lane change factor corresponding to N echo signals in M ​​frames is not less than the second preset value and not greater than the first preset value, this application forces the current position of the vehicle to be near lane 2 (the target position of lane 1). In this way, when the lane change factor corresponding to N echo signals in M ​​frames is greater than the first preset value, the vehicle trajectory can transition to the adjacent lane relatively smoothly. If the current position of the vehicle is forcibly set to the preset position of the first lane, such as the center position, the horizontal position of the vehicle will jump when the actual lane change occurs, the transition is not smooth enough, and the trajectory display effect is affected.

[0075] In this embodiment, the first and second preset values ​​are adjusted according to different lane change factor calculation methods. The first preset value can be 1.5. The lane change factor determined by the ratio and difference between the probability values ​​of a vehicle in the first lane and in the adjacent lane corresponds to different first and second preset values. That is, the lane change factor obtained based on the ratio corresponds to the first preset value a and the second preset value b. The lane change factor obtained based on the difference corresponds to the first preset value c and the second preset value d. In this embodiment, the above-mentioned "M frames of echo signals contain N frames of echo signals" can also be "M calculations contain N calculations," where one frame of echo signal can correspond to one calculation of the lane change factor, or it can correspond to multiple calculations of the lane change factor. For example, when one frame of echo signal corresponds to one calculation of the lane change factor, N times (frames) can be consecutive N times (frames), or it can reach N times (frames) within M times (frames) (e.g., M≤N+2).

[0076] In this embodiment, the vehicle's current position can also be determined based on the linear relationship between the lane change factor and the lane line distance. The lane line distance is the distance between the vehicle and the lane line. Specifically, the lane line can be the lane line on the side of the first lane furthest from the adjacent lane, or it can be the lane line on the side of the adjacent lane furthest from the first lane. In actual calculations, due to the large size of the vehicle, the center point of the vehicle or both sides can be used; this is not limited here. If the lane line on the side of the first lane furthest from the adjacent lane is used, the lane change factor and the lane line distance are positively correlated. If the lane line on the side of the adjacent lane furthest from the first lane is used, the lane change factor and the lane line distance are negatively correlated. Based on the linear relationship between the lane change factor and the lane line distance, the vehicle's specific position on the target road can be determined. The accuracy of the determined vehicle position is higher, lane changes are smoother, and the trajectory is more fluid, effectively improving the trajectory display effect of the intelligent platform.

[0077] In one possible implementation, the probability values ​​of a vehicle in the first lane and in the adjacent lane in each frame of the echo signal are calculated, including:

[0078] Through formula Calculate the probability values ​​of vehicles in the first lane and the adjacent lane in each frame of echo signal.

[0079] Among them, h i k represents the probability value of a vehicle being in the first lane or an adjacent lane in a single frame of echo signal. i denoted by , represents the number of vehicle echo signals in the first lane or adjacent lane in a single frame of echo signal, and k represents the total number of vehicle echo signals in the first lane and adjacent lane in a single frame of echo signal.

[0080] In this embodiment, the probability value for each lane is the ratio of the number of echo signals in each lane to the total number of vehicle echo signals in a single frame of echo signal. For example, if a single frame of echo signal includes 5 echo signals, with 1 echo signal for the vehicle in the first lane and 4 echo signals for the vehicle in adjacent lanes, then the probability value for the vehicle in the first lane is... The probability value of a vehicle being in an adjacent lane is

[0081] In one possible implementation, determining the vehicle's lane on the target road in each frame of the echo signal based on the M-frame echo signal includes:

[0082] Establish a coordinate system with the horizontal center point of the target road as the origin, the horizontal direction of the target road as the x-axis, and the lane direction as the y-axis.

[0083] The x-axis coordinates of the vehicle in the coordinate system are calculated based on the M-frame echo signals.

[0084] Based on the vehicle's x-axis coordinate in the coordinate system in each frame of echo signal, determine the lane the vehicle is in on the target road in each frame of echo signal.

[0085] In this embodiment, the radar can establish a corresponding lane model based on the actual number and width of lanes on the target road, using a Cartesian coordinate system. The x-axis coordinate of the vehicle in each frame of the echo signal is calculated based on M frames of echo signals. This includes calculating a first distance based on the straight-line distance between the echo signal and the radar, the radar's deflection angle, and the target angle of the echo signal relative to the radar normal. The first distance is the distance between the echo signal and the radar along the x-axis. The vehicle's x-axis coordinate is obtained based on the difference between the second distance and the first distance. The second distance is the radar's x-axis coordinate. The radar's deflection angle is the angle between the radar normal and the y-axis.

[0086] In this application, each frame of echo signal includes multiple echo signals. Each echo signal calculates an x-axis coordinate of the vehicle in the coordinate system. Each x-axis coordinate can determine a lane. Therefore, each frame of echo signal can have multiple x-axis coordinates of the vehicle in the coordinate system. For example, a single frame of echo signal includes 5 echo signals. The x-axis coordinates of the vehicle in the coordinate system in this single frame of echo signal are x1, x2, x3, x4, and x5. x1, x2, x3, x4, and x5 correspond to lane 1, lane 1, lane 2, lane 2, and lane 2, respectively. Then, the lanes where the vehicle is located on the target road in this frame of echo signal are lane 1 and lane 2.

[0087] by Figure 2 As shown in the schematic diagram of the coordinate system provided in this application embodiment, the radar can be installed at point A on the x-axis. The second distance OA is the x-axis coordinate (lateral offset) of the radar. The deflection angle of the radar installation is α. By performing a 3DFFT (Three Dimension Fast Fourier Transform) on the echo signal, the target angle β of the echo signal relative to the radar normal can be obtained. By performing a 1DFFT (One Dimension Fast Fourier Transform), the straight-line distance r of the echo signal from the radar can be obtained. At this time, the horizontal distance (first distance) of the echo signal from the radar installation position can be obtained by r*sin(α-β). OA-r*sin(α-β) is the horizontal coordinate of the vehicle in the Cartesian coordinate system (the x-axis coordinate of the vehicle). Based on this value, the lane number of the echo signal can be determined. The lane numbers are 1, 2...N from left to right.

[0088] In one possible implementation, the vehicle position determination method further includes: if the vehicle is in a lane on the target road that contains only one lane, then a preset position in that lane is determined as the vehicle's current position.

[0089] In this embodiment, if the vehicle has just entered the target lane, there is no echo signal from the previous frame. Based on the M-frame echo signal, it is determined that the vehicle is only in one lane on the target road in each frame echo signal. Therefore, it is determined that the vehicle has not changed lanes, and the preset position on that lane can be the center position of the lane.

[0090] In this embodiment, after acquiring multiple echo signals corresponding to the radar, the embodiment further includes: processing the echo signals, constant false alarm rate (CFAR) processing, and clustering. CFAR (Constant False Alarm Rate) is a technique used by radar systems to distinguish between the signal and noise output by the receiver while maintaining a constant false alarm probability to determine the presence of a target signal.

[0091] Figure 3 This is a schematic diagram of the radar's lane change event detection process provided in this application embodiment. The preset threshold value th is a first preset value. The radar installed on the target road generates a transmission signal. After the transmission signal is reflected by the target reflection point of a vehicle on the target road, a reflected signal (echo signal) is generated. The radar receives the reflected signal and performs calculations, constant false alarm rate (CFAR) detection, and clustering on the reflected signal. By statistically analyzing the lane numbers corresponding to the reflected signals and superimposing them into the accumulation of M consecutive frames, the probability value of the vehicle being in each lane is calculated. When a lane change occurs in the flight path, the probability value of the vehicle being in the first lane (the lane where the vehicle was before the lane change) and the adjacent lanes is determined. The probability values ​​on the lane (the lane where the vehicle is located after changing lanes) are calculated to obtain the lane change factor. This factor δ is compared with a first preset value. If the lane change factor corresponding to N echo signals in M ​​frames is greater than the first preset value, it indicates that the vehicle has indeed changed lanes and a lane change event is generated normally. If the lane change factor corresponding to N echo signals in M ​​frames is not less than the second preset value and not greater than the first preset value, it indicates that the vehicle has not changed lanes and the system returns to the first lane for filtering and prediction. The vehicle is forced to be located in the target position in the first lane, that is, near the adjacent lane, to facilitate the correlation prediction of the actual lane change.

[0092] In this embodiment, a corresponding coordinate system can be established based on the actual conditions of the target road. Within this coordinate system, the x-axis coordinate of the vehicle can be determined by angle and distance measurement, thereby determining the lane the vehicle is in on the target road. The lane location determined by this solution has high accuracy. This application also considers the issue of insufficient smoothness in vehicle trajectory display. By setting a target position on the first lane, when the lane change factor corresponding to N echo signals in M ​​frames is not less than a second preset value and not greater than a first preset value, the vehicle's current position is near an adjacent lane. This facilitates the correlation prediction of real lane changes, allowing the vehicle to smoothly transition to adjacent lanes, resulting in a smoother trajectory display. Furthermore, this application can determine the vehicle's current position based on the linear relationship between the lane change factor and the lane line distance, and can determine the vehicle's real-time position based on the real-time changes in the lane change factor, further improving the trajectory display effect.

[0093] The solution based on this application can reduce the unexpected jitter of vehicle tracks caused by false alarm signal interference due to multipath problems in enclosed environments (such as tunnels), thus preventing erroneous lane change events. The erroneous lane change events are reported to the intelligent platform. This application effectively improves the track display effect of millimeter-wave radar in enclosed environments, reduces the occurrence of erroneous lane change events, reduces camera captures, saves social resources, and improves the accuracy of lane change event reporting.

[0094] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0095] The following are device embodiments of this application. For details not described in detail, please refer to the corresponding method embodiments described above.

[0096] Figure 4 A schematic diagram of the vehicle position determination device provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown, and are described in detail below:

[0097] like Figure 4 As shown, the vehicle position determination device 40 includes:

[0098] The signal acquisition module 41 is used to acquire the M-frame echo signals corresponding to the radar, with a frame length of M frames. Each frame of the M-frame echo signal includes multiple echo signals. These multiple echo signals are single-frame echo signals reflected by vehicles on the target road, which is the road detected by the radar.

[0099] Lane determination module 42 is used to determine the lane on the target road in each frame of echo signal based on the M-frame echo signal.

[0100] The probability value calculation module 43 is used to calculate the probability value of the vehicle in the first lane and the adjacent lane in each frame of the echo signal based on the M-frame echo signal if the lane in which the vehicle is located on the target road includes the first lane and the adjacent lane of the first lane.

[0101] The first lane is the lane where the vehicle is located, determined based on the echo signal from the previous radar frame.

[0102] The position determination module 44 is used to determine the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and in the adjacent lane in each frame of echo signal.

[0103] In one possible implementation, the position determination module 44 is used to determine the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and in the adjacent lane in each frame of echo signal.

[0104] The vehicle's current position is determined based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal, including:

[0105] The lane change factor is determined based on the relative magnitudes of the probability values ​​of a vehicle being in the first lane and the adjacent lane in each frame of the echo signal. The lane change factor is used to determine whether a vehicle has changed lanes.

[0106] The vehicle's current position is determined based on the lane change factor.

[0107] In one possible implementation, the position determination module 44 is used to determine the corresponding lane change factor based on the relative magnitude of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal.

[0108] The lane change factor is determined based on the relative magnitudes of the probability values ​​of a vehicle in the first lane and the adjacent lane in each frame of echo signal, including:

[0109] according to Determine the corresponding lane change factor, or determine the corresponding lane change factor based on δ = P1 - P2.

[0110] Where δ is the lane change factor corresponding to a single frame echo signal, P1 is the probability value of a vehicle in an adjacent lane in a single frame echo signal, and P2 is the probability value of a vehicle in the first lane in a single frame echo signal.

[0111] In one possible implementation, the position determination module 44 is used to determine the current position of the vehicle based on the lane change factor.

[0112] Determining the vehicle's current position based on lane change factors includes:

[0113] If the lane change factor corresponding to N echo signals in M ​​frames is greater than the first preset value, then the preset position on the adjacent lane is determined as the vehicle's current position.

[0114] If the lane change factor corresponding to N echo signals in M ​​frames is less than the second preset value, then the preset position on the first lane is determined as the current position of the vehicle.

[0115] If the lane change factor corresponding to N echo signals in M ​​frames is not less than a second preset value and not greater than a first preset value, then the target position on the first lane is determined as the vehicle's current position. The target position on the first lane is located between a preset position on the first lane and a preset position on the adjacent lane.

[0116] In one possible implementation, the probability value calculation module 43 is used to calculate the probability value of a vehicle in the first lane and in the adjacent lane in each frame of echo signal.

[0117] Calculate the probability values ​​of vehicles in the first lane and the adjacent lane in each frame of echo signal, including:

[0118] Through formula Calculate the probability values ​​of vehicles in the first lane and the adjacent lane in each frame of echo signal.

[0119] Among them, h i k represents the probability value of a vehicle being in the first lane or an adjacent lane in a single frame of echo signal. i denoted by , represents the number of vehicle echo signals in the first lane or adjacent lane in a single frame of echo signal, and k represents the total number of vehicle echo signals in the first lane and adjacent lane in a single frame of echo signal.

[0120] In one possible implementation, the lane determination module 42 is used to determine the lane on the target road in each frame of the echo signal based on the M-frame echo signal.

[0121] Establish a coordinate system with the horizontal center point of the target road as the origin, the horizontal direction of the target road as the x-axis, and the lane direction as the y-axis.

[0122] The x-axis coordinates of the vehicle in the coordinate system are calculated based on the M-frame echo signals.

[0123] Based on the vehicle's x-axis coordinate in the coordinate system in each frame of echo signal, determine the lane the vehicle is in on the target road in each frame of echo signal.

[0124] In one possible implementation, the vehicle position determination device 40 is also used in a vehicle position determination method.

[0125] The vehicle position determination method also includes: if the vehicle is in a lane on the target road that contains only one lane, then the preset position in that lane is determined as the vehicle's current position.

[0126] This application also provides a radar, which includes a processing terminal, see [link to example]. Figure 5 , Figure 5 This is a schematic diagram of the radar processing terminal provided in an embodiment of this application. For example... Figure 5 As shown, the processing terminal 50 of this embodiment includes: a processor 51, a memory 52, and a computer program 53 stored in the memory 52 and executable on the processor 51. When the processor 51 executes the computer program 53, it implements the steps in the various vehicle position determination method embodiments described above, for example... Figure 1 S101 to S104 are shown. Alternatively, when processor 51 executes computer program 53, it implements the functions of each module in the above-described device embodiments, for example... Figure 4 The functions of modules 41 to 44 are shown.

[0127] For example, computer program 53 can be divided into one or more modules, one or more modules are stored in memory 52 and executed by processor 51 to complete this application. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 53 in processing terminal 50. For example, computer program 53 can be divided into... Figure 4 Modules 41 to 44 are shown.

[0128] The processing terminal 50 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The processing terminal 50 may include, but is not limited to, a processor 51 and a memory 52. ​​Those skilled in the art will understand that... Figure 5 This is merely an example of processing terminal 50 and does not constitute a limitation on processing terminal 50. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal may also include input / output devices, network access devices, buses, etc.

[0129] The processor 51 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor.

[0130] The memory 52 can be an internal storage unit of the processing terminal 50, such as a hard disk or RAM of the processing terminal 50. The memory 52 can also be an external storage device of the processing terminal 50, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the processing terminal 50. Furthermore, the memory 52 can include both internal storage units and external storage devices of the processing terminal 50. The memory 52 is used to store computer programs and other programs and data required by the terminal. The memory 52 can also be used to temporarily store data that has been output or will be output.

[0131] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0132] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0133] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0134] In the embodiments provided in this application, it should be understood that the disclosed devices / terminals and methods can be implemented in other ways. For example, the device / terminal embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0135] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0136] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0137] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various vehicle position determination method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electrical carrier signals and telecommunication signals.

[0138] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for determining the location of a vehicle, characterized in that, The vehicle location determination method includes: The radar acquires M-frame echo signals with a frame length of M frames; each frame of the M-frame echo signals includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by vehicles on the target road, and the target road is the road detected by the radar; The lane in which the vehicle is located on the target road is determined based on the M-frame echo signal; If the vehicle is in a lane on the target road that includes the first lane and the adjacent lane of the first lane, then the probability value of the vehicle being in the first lane and the adjacent lane in each frame of the echo signal is calculated based on the M-frame echo signal. The first lane is the lane where the vehicle is located, as determined by the previous frame echo signal of the radar. The current position of the vehicle is determined based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal; The calculation of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal includes: Through formula Calculate the probability value of the vehicle being in the first lane and the adjacent lane in each frame of echo signal; in, This represents the probability value of the vehicle being in the first lane or the adjacent lane in a single frame of echo signal. The number of echo signals from the vehicle in the first lane or the adjacent lane in a single frame of echo signal. The total number of echo signals of the vehicle in the first lane and the adjacent lane in a single frame of echo signal.

2. The method according to claim 1, characterized in that, Determining the current position of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal includes: The corresponding lane change factor is determined based on the relative magnitude of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal; wherein, the lane change factor is used to determine whether the vehicle has changed lanes; The current position of the vehicle is determined based on the lane change factor.

3. The method according to claim 2, characterized in that, The step of determining the corresponding lane change factor based on the relative magnitude of the probability values ​​of the vehicle in the first lane and the adjacent lane in each frame of echo signal includes: according to Determine the corresponding lane change factor, or based on Determine the corresponding lane change factor; in, This refers to the lane change factor corresponding to a single frame of echo signal. This represents the probability value of the vehicle being in the adjacent lane within a single frame of the echo signal. This represents the probability value of the vehicle being in the first lane in a single frame of echo signal.

4. The method according to claim 2, characterized in that, Determining the current position of the vehicle based on the lane change factor includes: If the lane change factor corresponding to N echo signals in M ​​frame echo signals is greater than the first preset value, then the preset position on the adjacent lane is determined as the current position of the vehicle. If the lane change factor corresponding to N echo signals in M ​​frame echo signals is less than the second preset value, then the preset position on the first lane is determined as the current position of the vehicle. If the lane change factor corresponding to N echo signals in M ​​frame echo signals is not less than a second preset value and not greater than a first preset value, then the target position on the first lane is determined as the current position of the vehicle; wherein, the target position on the first lane is located between the preset position on the first lane and the preset position on the adjacent lane.

5. The method according to claim 1, characterized in that, The step of determining the lane of the vehicle on the target road in each frame of the echo signal based on the M-frame echo signal includes: A coordinate system is established with the horizontal center point of the target road as the origin, the horizontal direction of the target road as the x-axis, and the lane direction as the y-axis. The x-axis coordinate of the vehicle in the coordinate system is calculated based on the M-frame echo signals. Based on the x-axis coordinate of the vehicle in each frame of the echo signal in the coordinate system, determine the lane on the target road in each frame of the echo signal.

6. The method according to claim 1, characterized in that, The vehicle position determination method further includes: if the vehicle is in a lane on the target road that contains only one lane, then a preset position on that lane is determined as the current position of the vehicle.

7. A vehicle position determination device, characterized in that, include: The signal acquisition module is used to acquire M-frame echo signals corresponding to the radar with a frame length of M frames; wherein, each frame echo signal in the M-frame echo signal includes multiple echo signals; the multiple echo signals are single-frame echo signals reflected by vehicles on the target road, and the target road is the road detected by the radar; The lane determination module is used to determine the lane on the target road where the vehicle is located in each frame of the echo signal based on the M-frame echo signal. The probability value calculation module is used to calculate the probability value of the vehicle in the first lane and the adjacent lane in each frame of the echo signal based on the M-frame echo signal if the lane in which the vehicle is located on the target road includes the first lane and the adjacent lane of the first lane. The first lane is the lane where the vehicle is located, as determined by the previous frame echo signal of the radar. A location determination module is used to determine the current location of the vehicle based on the probability values ​​of the vehicle being in the first lane and the adjacent lane in each frame of echo signal; Specifically, the probability value calculation module is used for: Through formula Calculate the probability value of the vehicle being in the first lane and the adjacent lane in each frame of echo signal; in, This represents the probability value of the vehicle being in the first lane or the adjacent lane in a single frame of echo signal. The number of echo signals from the vehicle in the first lane or the adjacent lane in a single frame of echo signal. The total number of echo signals of the vehicle in the first lane and the adjacent lane in a single frame of echo signal.

8. A radar comprising a processing terminal, the processing terminal including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 6 above.

9. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 6 above.

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