Vehicle control method and electronic equipment

Abstract

The invention relates to a vehicle control method and electronic equipment, and the method comprises the steps: determining a target angle of a rotating arm carrying a sensor in a vehicle in response to the detected change of a steering wheel angle of the vehicle, and then controlling the rotating arm to rotate to the target angle, so that the sensor is aligned with a driving blind area of the vehicle, according to the method, under the condition that the steering wheel of the vehicle rotates, the angle of the rotating arm is adjusted so that the sensor can be aligned with the driving blind area, such as vehicle turning and vehicle lane changing, the driving blind area is detected through the sensor, and the driving blind area is controlled according to the detected blind area. Complete sensing information can be provided for an automatic driving system of a vehicle, especially information such as the position of an obstacle in a blind area, people or moving objects in the blind area can be prevented from entering the blind area, and therefore the driving safety of the vehicle is ensured.

Description

Technical Field

[0001] The present disclosure relates to the field of autonomous driving technology, and in particular to a vehicle control method and electronic equipment. Background Art

[0002] A car train usually consists of a tractor and one or more trailers constrained by a traction pin. In logistics scenarios such as ports, airports, and factories, the unmanned closed-loop process of car trains has been widely used to help realize automatic cargo transportation within a set area and improve transportation efficiency.

[0003] However, when a train turns, the sensors on the train may not be able to detect all trailers because the train body is too wide or carries too many trailers, which may result in blind spots and pose certain risks to vehicle driving. Summary of the invention

[0004] In order to solve the above technical problems or at least partially solve the above technical problems, the embodiments of the present disclosure provide a vehicle control method and electronic equipment to solve the problems such as driving risks caused by blind spots in the vehicle's field of vision in the prior art.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for controlling a vehicle, the method comprising:

[0006] In response to detecting a change in a steering wheel angle of a vehicle, determining a target angle of a rotating arm in the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle;

[0007] Controlling the rotating arm to rotate to the target angle so that the sensor is aligned with the blind spot of the vehicle;

[0008] Obtain blind spot detection data collected by the sensor, and control the vehicle according to the blind spot detection data.

[0009] In a second aspect, an embodiment of the present disclosure further provides a vehicle control device, the device comprising:

[0010] an angle determination module, configured to determine a target angle of a rotating arm in the vehicle in response to detecting a change in a steering wheel angle of the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle;

[0011] A rotation control module, used for controlling the rotation arm to rotate to the target angle so that the sensor is aligned with the driving blind spot of the vehicle;

[0012] The blind spot detection module is used to obtain the blind spot detection data collected by the sensor and control the vehicle according to the blind spot detection data.

[0013] In a third aspect, an embodiment of the present disclosure further provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the vehicle control method as described above.

[0014] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the vehicle control method as described above.

[0015] A vehicle control method provided by an embodiment of the present disclosure determines a target angle of a rotating arm equipped with a sensor in the vehicle in response to detecting a change in a steering wheel angle of the vehicle, and then controls the rotating arm to rotate to the target angle so that the sensor is aimed at a driving blind spot of the vehicle, thereby obtaining blind spot detection data collected by the sensor, and controlling the vehicle according to the blind spot detection data. The method can adjust the angle of the rotating arm to align the sensor with the driving blind spot when the steering wheel of the vehicle is turned, such as in conditions such as vehicle turning and vehicle lane changing. By detecting the driving blind spot through the sensor, the vehicle's automatic driving system can be provided with complete perception information, especially information such as the location of obstacles in the blind spot, which can prevent people or moving objects in the blind spot from cutting in, thereby ensuring the driving safety of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the originals and elements are not necessarily drawn to scale.

[0017] Figure 1 is a flow chart of a vehicle control method according to an embodiment of the present disclosure;

[0018] Figure 2 A schematic diagram of the rotation of a rotating arm provided in an embodiment of the present disclosure;

[0019] Figure 3 A schematic diagram of a region of interest provided in an embodiment of the present disclosure;

[0020] Figure 4 A schematic diagram of a vehicle control process provided by an embodiment of the present disclosure;

[0021] Figure 5 is a structural schematic diagram of a vehicle control device in an embodiment of the present disclosure;

[0022] Figure 6It is a structural schematic diagram of an electronic device in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0023] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0024] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0025] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0026] Figure 1 1 is a flow chart of a vehicle control method in an embodiment of the present disclosure. The method can be executed by a vehicle control device, which can be implemented in software and / or hardware, and can be configured in an electronic device. Figure 1 As shown, the method may specifically include the following steps:

[0027] S110 . In response to detecting a change in a steering wheel angle of the vehicle, determining a target angle of a rotating arm in the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle.

[0028] The sensor may be a sensor used for environmental perception in the vehicle's automatic driving system, such as a camera, a laser radar, etc. Specifically, the sensor may be installed on a rotating arm of the vehicle, and the rotating arm drives the sensor to move.

[0029] In the disclosed embodiment, the rotating arm can be arranged on the roof of the tractor in the vehicle, or arranged in front of the front of the tractor, and the rotation of the rotating arm can be realized by a rotating motor, which can control the rotating arm to rotate at any angle in three-dimensional space. Figure 2 A schematic diagram of the rotation of a rotating arm provided in an embodiment of the present disclosure, wherein one end of the rotating arm is connected to a motor and the other end is connected to a sensor, and the rotating arm can rotate on any plane in a three-dimensional space.

[0030] In order to ensure the smooth rotation of the rotating arm, a bearing connection can be used between the rotating arm and the rotating motor, and a structure that minimizes the friction between the rotating arm and the rotating motor can be used. In order to ensure the stability of the sensor during the rotation of the rotating arm, a eccentric weight can be used between the rotating arm and the rotating motor to maintain the position of the sensor with the help of the counterweight of the eccentric weight, so that the sensor will not be rotated with the rotation of the rotating arm, thereby keeping the sensor stable and avoiding tilting or shaking of the sensor, which may cause incorrect detection data.

[0031] Specifically, the rotation domain controller can control the operation of the rotating motor, thereby controlling the rotation of the rotating arm. Among them, the rotating domain controller can be composed of an MCU (Microcontroller Unit) and a SoC (System on Chip). The MCU can be connected to the rotating motor, the SoC can be connected to the sensor, and the sensor and the rotating motor can be synchronized through the MCU. The VCU (Vehicle Control Unit) can transmit body data (such as steering wheel angle), vehicle start and stop signals, vehicle speed, etc. to the MCU, and then the MCU can transmit motor power, ground signal, maximum speed, minimum speed, reset signal, body data, etc. to the rotating motor to control the operation of the rotating motor; the SoC can transmit clock signals to the sensor to control the operation of the sensor. The MCU can also be connected to the vehicle's GPS (Global Positioning System) to obtain the vehicle's location information through GPS.

[0032] In the disclosed embodiment, taking into account that in conditions such as turning, changing lanes, and serpentine driving, the trailer carried by the vehicle makes the vehicle body length longer, resulting in a larger inner wheel difference of the vehicle, thereby forming a driving blind spot. In order to realize blind spot detection under such conditions, the steering wheel angle of the vehicle can be obtained in real time, and then compared with the steering wheel angle at the previous moment to detect whether the vehicle is in a condition where there is a driving blind spot.

[0033] Specifically, if the difference between the current steering wheel angle and the steering wheel angle at the previous moment is greater than a preset angle difference threshold, it can be determined that the steering wheel angle has changed, and the vehicle may be in a condition where there is a driving blind spot. Further, the target angle of the rotating arm in the vehicle can be determined. The target angle can be the angle to which the rotating arm is expected to be adjusted, including the angle of the rotating arm relative to each axis of the vehicle body coordinate system.

[0034] It should be noted that the rotating arm in the embodiment of the present disclosure may be a rotating component of fixed size, or may be a retractable rotating component. If the rotating arm adopts a retractable structural design, it is possible to determine whether the length of the rotating arm needs to be adjusted before determining the target angle of the rotating arm, so as to ensure that the camera mounted thereon can accurately aim at the driving blind spot when the rotating arm rotates. For example, considering that the length of the vehicle body will affect the position and size of the blind spot, the corresponding working length of the rotating arm can be determined according to the length of the vehicle body or the number of trailers carried. If the current length of the rotating arm does not meet the working length of the rotating arm, the rotating arm is controlled to be retracted to the working length of the rotating arm.

[0035] In a specific embodiment, determining a target angle of a rotating arm in a vehicle comprises the following steps:

[0036] Step 11: Acquire vehicle status information of the vehicle, and determine a predicted driving trajectory of the vehicle according to the vehicle status information;

[0037] Step 12: Determine the target angle of the rotating arm according to the predicted driving trajectory.

[0038] In step 11, the vehicle status information may include steering wheel angle, vehicle speed, acceleration, position, and heading angle of the tractor. Specifically, considering that in application scenarios such as airports and express delivery transfer stations, unmanned vehicles usually travel on a fixed track to transport goods. Therefore, the predicted driving track of the vehicle can be queried based on the vehicle status information.

[0039] For example, a vehicle's driving route in a road network can be pre-planned. Based on the vehicle's position and heading angle, a point that matches the position and heading angle can be located from the driving route. Then, with the located point in the road network as the starting point, a partial trajectory can be selected from the driving route in the road network as the vehicle's predicted driving trajectory.

[0040] In addition to querying and obtaining the predicted driving trajectory, the predicted driving trajectory of the vehicle can also be calculated in real time based on the vehicle state information. For example, the heading angle, speed, acceleration and position of the tractor can be derived in turn based on the heading angle, speed, acceleration and position of the tractor at each subsequent moment in combination with the vehicle motion model to form the predicted driving trajectory of the vehicle, wherein the vehicle motion model can be a mathematical model that describes the change of the vehicle state between adjacent moments.

[0041] For another example, the heading angle, speed, acceleration and position of the tractor may be input into a pre-trained trajectory prediction model to obtain a predicted driving trajectory output by the model, wherein the trajectory prediction model may be a neural network model for trajectory prediction.

[0042] After the predicted driving trajectory of the vehicle is obtained, further, in step 12, the target angle of the rotating arm can be determined according to the predicted driving trajectory. The blind spot monitoring angle of the rotating arm under each driving trajectory can be pre-calibrated, and then based on the calibration result, the blind spot monitoring angle corresponding to the predicted driving trajectory can be queried as the target angle; or the minimum turning radius in the predicted driving trajectory can be determined, and the corresponding target angle can be determined according to the minimum turning radius.

[0043] Through the above steps 11 and 12, the vehicle's driving trajectory can be predicted based on the vehicle's vehicle status information, and then the target angle can be determined based on the predicted driving trajectory. The rotating arm can be rotated in advance to achieve predictive detection of driving blind spots, providing complete perception information for the autonomous driving system.

[0044] In another specific embodiment, determining a target angle of a rotating arm in a vehicle comprises the following steps:

[0045] Step 21, obtaining the steering wheel angle of the tractor in the vehicle and the geometric structure parameters of the vehicle;

[0046] Step 22: determining a predicted heading angle of each trailer in the vehicle according to the steering wheel angle, the geometric structure parameters and the vehicle motion model;

[0047] Step 23: Determine the target angle of the rotating arm according to the predicted heading angle of each trailer in the vehicle.

[0048] In step 21, the steering wheel angle of the tractor and the geometric parameters of the vehicle may be obtained. The geometric parameters may be used to describe the structure of the tractor and the trailer in the vehicle, for example, the geometric parameters may include the position of the hinge point between the tractor and the trailer, the size of the tractor, the size of the trailer, the length of the half-axle, and the position of the center of mass.

[0049] Specifically, in step 22, the steering wheel angle, geometric structure parameters and the position of the tractor can be substituted into the vehicle motion model to calculate the predicted heading angle of each trailer. The vehicle motion model can also be used to describe the motion cascade relationship between the tractor and the trailer, or the motion cascade relationship between the trailers at the same time.

[0050] Furthermore, in step 23, the target angle of the rotating arm may be determined according to the predicted heading angle of each trailer in the vehicle. For example, the difference between the predicted heading angles of the first trailer and the last trailer may be calculated, and the blind spot range of the driving blind spot may be determined according to the heading angle difference. For example, the blind spot range corresponding to each heading angle difference may be pre-calibrated, and then the target angle may be determined according to the blind spot range.

[0051] In the above steps 21 to 23, considering that the difference between the heading angles of the trailers affects the blind spot range, the heading angle of each trailer in the vehicle can be predicted based on the steering wheel angle and geometric structure parameters of the vehicle, and then the target angle is determined based on the predicted heading angle, thereby ensuring the accuracy of the rotation of the rotating arm and allowing the sensor to accurately detect the driving blind spot.

[0052] In the disclosed embodiment, after the predicted driving trajectory is obtained, the actual driving trajectory of the vehicle can also be detected in real time, the predicted driving trajectory can be promptly corrected according to the detected actual driving trajectory, and the corresponding target angle can be updated.

[0053] S120, controlling the rotating arm to rotate to a target angle so that the sensor is aligned with the driving blind spot of the vehicle.

[0054] Specifically, after the target angle is obtained, the rotating arm can be controlled to rotate to the target angle, so that the sensor carried on the rotating arm can be aligned with the driving blind spot.

[0055] In the embodiment of the present application, in the process of controlling the rotating arm to rotate to the target angle, the detection data can also be collected in real time by the sensor to further ensure the reliability of the vehicle environment perception.

[0056] For example, when the rotation angle of the rotating motor reaches the set angle, a synchronization pulse signal is output to the MCU, and then the MCU synchronizes the position of the sensor based on the signal (i.e., determines the position of the sensor relative to the vehicle), and sends the synchronization signal to the SoC, which triggers the sensor to collect detection data. The set angle of the rotating motor can be determined based on the acquisition frequency of the sensor.

[0057] For example, in a slow state, the rotating motor rotates at 60 revolutions per minute (in a fast state, it can reach 120 revolutions per minute), that is, the rotating motor rotates one circle per second, and the frame rate of the sensor is 25fps (taking the camera as an example, it is exposed and photographed 25 times per second, and the acquisition frequency is 25Hz). It can be seen that the sensor collects data once when the rotating motor rotates 14.4°. In other words, the set angle for the rotating motor to trigger the sensor to collect data can be 14.4°.

[0058] The position of the synchronization sensor may specifically be to determine the position of the sensor relative to the vehicle. For example, the real-time position of the rotating arm may be calculated by the reset point time of the rotating motor and the angular velocity of the rotating motor, thereby determining the position of the sensor relative to the vehicle according to the real-time position of the rotating arm.

[0059] It should be noted that, in the process of rotating the rotating arm, the rotation speed of the rotating arm can be determined according to the steering speed of the vehicle. For example, the rotation speed of the rotating motor can be determined according to the steering speed of the vehicle. The faster the steering speed, the faster the rotation speed of the rotating motor, and thus the faster the rotation speed of the rotating arm, so as to achieve the purpose of adaptively adjusting the rotation efficiency of the rotating arm according to the actual situation of the vehicle, and ensure that the sensor can detect the driving blind spot in time.

[0060] S130: Obtain blind spot detection data collected by the sensor, and control the vehicle according to the blind spot detection data.

[0061] After the rotating arm rotates to the target angle, the sensor can be triggered to collect data to sense the driving blind spot and obtain blind spot detection data. For example, if the sensor is a camera, the blind spot detection data is a blind spot detection image, and if the sensor is a laser radar, the blind spot detection data is a blind spot detection point cloud.

[0062] Specifically, after obtaining the blind spot detection data, the blind spot detection data can be used to determine whether the vehicle meets the safe driving conditions, so as to achieve control of the vehicle. In order to improve the processing efficiency of the blind spot detection data, an area of ​​interest can also be selected from the blind spot detection data to determine whether the vehicle meets the safe driving conditions based on the data in the area of ​​interest.

[0063] In one example, before controlling the vehicle according to the blind spot detection data, the following steps are also included:

[0064] Step 31, determining the area position of the area of ​​interest in the blind spot detection data according to the target angle;

[0065] Step 32: locate the region of interest in the blind spot detection data according to the region position, and remove other data outside the region of interest in the blind spot detection data, or update the weight or confidence of other data.

[0066] Among them, in step 31, after obtaining the blind spot detection data collected by the sensor, the regional position of the region of interest can be determined first. Specifically, the regional position of the region of interest is related to the rotation angle of the rotating arm, and the regional position of the region of interest at different rotation angles can be pre-calibrated, and then the corresponding regional position can be queried according to the target angle.

[0067] For example, Figure 3A schematic diagram of a region of interest provided for an embodiment of the present disclosure, taking a camera as an example, in an original detection image captured by the camera, if the rotating arm rotates to the upper left, the region of interest may be located in the upper left portion of the original detection image; if the rotating arm rotates to the lower right portion, the region of interest may be located in the lower right portion of the original detection image.

[0068] After determining the area position of the region of interest, further, in step 32, the region of interest can be located from the blind spot detection data according to the area position, and then other data except the region of interest can be eliminated, or the weight or confidence of other data except the region of interest can be reduced.

[0069] Through the above steps 31 and 32, the accuracy of the blind spot detection data can be ensured, and the data of the region of interest can be screened out, thereby greatly improving the processing efficiency of the blind spot detection data. In addition, by selecting the region of interest, the region of interest can be dynamically and adaptively selected with the rotating arm to achieve the purpose of optimal field of view detection.

[0070] In an embodiment of the present application, the blind spot detection data is processed to determine whether the vehicle meets the safe driving conditions. The position of each obstacle target is first determined based on the blind spot detection data, and then whether the safe driving conditions are met based on the position of the obstacle target.

[0071] In a specific implementation, controlling a vehicle according to blind spot detection data includes the following steps:

[0072] Step 41: Determine the position of the obstacle target in the driving blind spot relative to the vehicle according to the blind spot detection data;

[0073] Step 42: Control the vehicle to stop or slow down, or control the acoustic light warning system of the vehicle to operate, according to the position of the obstacle target relative to the vehicle.

[0074] Among them, in step 41, the position of the obstacle target in the driving blind spot relative to the vehicle can be determined based on the weight or confidence of each point in the blind spot detection data; the obstacle target includes but is not limited to pedestrians, other vehicles and dropped goods. Specifically, determining the position of the obstacle target relative to the vehicle can be divided into two steps, namely, first determining the position of the obstacle relative to the sensor, and then determining the position of the obstacle relative to the vehicle.

[0075] With respect to the above step 41, in some implementations, determining the position of the obstacle target in the driving blind spot relative to the vehicle according to the blind spot detection data includes the following steps:

[0076] Step 411: determining external parameters of the sensor according to the target angle, wherein the external parameters are used to describe the positional relationship between the sensor and the vehicle;

[0077] Step 412: determining the position of the obstacle target relative to the sensor according to the blind spot detection data;

[0078] Step 413: Determine the position of the obstacle target relative to the vehicle based on the external parameters and the position of the obstacle target relative to the sensor.

[0079] In step 411, considering that the angle of the rotating arm affects the position of the sensor relative to the vehicle, the positional relationship between the sensor and the vehicle, that is, the position of the sensor relative to the vehicle, can be determined according to the target angle of the rotating arm. Exemplarily, the external parameters of the sensor at different angles can be pre-calibrated, and then the corresponding external parameters can be queried according to the target angle.

[0080] Specifically, in step 412, the blind spot detection data can be used to project each point collected by the sensor into the three-dimensional space to obtain the position of the obstacle target relative to the sensor. In this process, it is necessary to rely on the internal parameters of the sensor, which are used to reflect the mapping relationship between the points in the detection data and the points in the three-dimensional space.

[0081] Considering that the selection of the region of interest will affect the internal parameters, the internal parameters can also be determined in combination with the region of interest to determine the position of the obstacle target relative to the sensor. With respect to the above step 412, in one example, determining the position of the obstacle target relative to the sensor based on the blind spot detection data includes:

[0082] The internal parameters of the sensor are determined according to the area position of the area of ​​interest; based on the internal parameters, the points in the blind spot detection data are mapped into space to obtain the position of the obstacle target relative to the sensor.

[0083] The internal parameters are calibration parameters of the mapping relationship, and the mapping relationship is the relationship between points in the data detected by the sensor and points in space. For example, the internal parameters of the sensor at different regional positions can be pre-calibrated, and then the corresponding internal parameters can be queried according to the regional position of the area of ​​interest.

[0084] Specifically, the internal parameters of the sensor may be added, and after verification, the points in the blind spot detection data may be mapped into a three-dimensional space according to the internal parameters, so as to accurately calculate the position of the obstacle target relative to the sensor.

[0085] Through the above example, the internal parameters of the sensor can be determined according to the region of interest, so as to determine the position of the obstacle target and ensure the recognition accuracy of the obstacle target.

[0086] After obtaining the position of the obstacle target relative to the sensor, further, in step 413, the position of the obstacle target relative to the sensor may be converted into the position of the obstacle target relative to the vehicle according to external parameters.

[0087] Through the above steps 411 to 413, the internal and external parameters of the sensor can be synchronized in real time through the target angle of the rotating arm, thereby accurately determining the position of the detected obstacle target relative to the vehicle, thereby ensuring the recognition accuracy of the obstacle target.

[0088] After determining the position of the obstacle target in the driving blind spot relative to the vehicle, further, in step 42, it can be determined whether the vehicle meets the safe driving condition according to the position of the obstacle target relative to the vehicle. Exemplarily, the minimum distance between the obstacle target and the vehicle can be calculated based on the position of the obstacle target relative to the vehicle, and when the minimum distance is less than the set distance, it is determined that the vehicle does not meet the safe driving condition.

[0089] If the vehicle does not meet the safe driving conditions, the vehicle can be controlled to stop or slow down, or the acoustic light alarm system of the vehicle can be controlled to work. Among them, the acoustic light alarm system can specifically control the sound equipment and light equipment of the vehicle. Specifically, controlling the operation of the acoustic light alarm system can include controlling the sound equipment to emit a warning sound, the light equipment to flash, or sending a notification to the associated terminal.

[0090] In the embodiment of the present disclosure, when the vehicle does not meet the safe driving conditions, it is also possible to select a specific execution strategy among parking, deceleration, and controlling the operation of the acoustic light alarm system in combination with the type of obstacle target and the distance between the obstacle target and the vehicle. For example, if the type of obstacle target is a pedestrian, or the distance between the obstacle target and the vehicle is less than the minimum distance threshold, the vehicle is controlled to stop and the acoustic light alarm system is controlled to operate; if the type of obstacle target is cargo, and the distance between the obstacle target and the vehicle is greater than the minimum distance threshold, the vehicle is controlled to decelerate and avoid the obstacle.

[0091] Through the above steps 41 and 42, the controller can stop the vehicle, slow down the vehicle, or control the acoustic light alarm system to work based on the data detected in the driving blind spot, so as to improve the driving safety and anti-theft capabilities of the vehicle, and remind pedestrians and other traffic participants to pay attention to safety.

[0092] In the disclosed embodiment, taking into account the possible existence of sections such as tunnels and viaducts that restrict the width and height of the vehicle body, in order to ensure the passability of the vehicle equipped with a rotating arm, the position of the vehicle in the road network can be located in real time, and then the rotating arm can be rotated to a safe position in the section where the width and height of the vehicle body are restricted.

[0093] In a specific implementation, the vehicle control method provided by the embodiment of the present disclosure further includes the following steps:

[0094] Step 51: During the driving process of the vehicle, the actual position of the vehicle in the road network is obtained;

[0095] Step 52: in response to detecting that the actual position is located in a preset road network area, determining a safe angle of the rotating arm according to the preset road network area, and recording the current angle of the rotating arm;

[0096] Step 53: Control the rotating arm to rotate to a safe angle, and when it is detected that the vehicle moves out of the preset road network area, control the rotating arm to rotate to a recorded angle.

[0097] In step 51 and step 52, the vehicle can be positioned in real time during the driving process to obtain the actual position of the vehicle in the road network, and then determine whether the actual position is within the preset road network area. The preset road network area can be an area in the pre-set road network that limits the width and height of the vehicle.

[0098] If the actual position of the vehicle is within the preset road network area, the safety angle of the rotating arm can be determined based on the preset road network area, wherein the safety angle can be an angle that can ensure that the rotating arm and the sensors mounted thereon are not hit. For example, the safety angle of the rotating arm can be determined based on the height or width of the preset road network area limit combined with the height or width of the vehicle. In addition to determining the safety angle, the current angle of the rotating arm can be recorded so that the angle of the rotating arm can be restored after the vehicle subsequently drives out of the preset road network area.

[0099] Furthermore, in step 53, the rotating arm can be controlled to rotate to a safe angle, and then the actual position of the vehicle can continue to be detected. If the actual position is outside the preset road network area, that is, the vehicle has driven out of the preset road network area, the rotating arm can be controlled to rotate to the recorded angle.

[0100] Through the above steps 51 to 53, it is achieved that during the driving process of the vehicle, the rotating arm can be rotated to a safe position in areas such as tunnels and viaducts where the width and height of the vehicle body are restricted, so as to avoid collision or scratching of the sensor.

[0101] In addition, in the embodiment of the present disclosure, considering that when the vehicle is started or stopped, there may be unexpected events such as cargo falling, trailer separation, etc., therefore, the rotating arm can also be rotated to detect events such as cargo falling, trailer separation, etc. through the sensors carried on the rotating arm.

[0102] In a specific implementation, the vehicle control method provided by the embodiment of the present disclosure further includes the following steps:

[0103] Step 61, in response to the start / stop signal of the vehicle, controlling the rotating arm to rotate;

[0104] Step 62: During the rotation of the rotating arm, the trailer area of ​​the vehicle is detected by the sensor to obtain trailer detection data of the vehicle;

[0105] Step 63: judging whether there is a preset alarm event in the trailer area according to the trailer detection data;

[0106] Step 64: In response to a preset alarm event in the trailer area, the vehicle is controlled to stop, or a corresponding alarm message is generated and sent to an associated device.

[0107] Wherein, in step 61, if the start-stop signal (i.e., the start signal or the stop signal) of the vehicle is detected, the rotating arm can be controlled to rotate. For example, the rotating arm can be controlled to rotate in a circle, and the number of rotations can be preset.

[0108] Furthermore, during the rotation of the rotating arm, the trailer area can be detected by a sensor to obtain trailer detection data. The sensor can synchronize the position and trigger data collection when the working time of the rotating motor reaches a set period.

[0109] In step 63, the target type and target position (the position of the target relative to the vehicle) of each target in the trailer area can be determined based on the trailer detection data, and then whether there is a preset alarm event can be determined based on the target type and target position. The target position can be determined by combining the internal parameters and external parameters of the sensor. The specific process can be referred to the above description and will not be repeated here.

[0110] Specifically, the preset alarm events may include trailer separation, cargo falling, bucket door opening, and mobile target cutting in. Through the trailer detection data, preset alarm events such as trailer separation, cargo falling, bucket door opening, and mobile target cutting in can be detected. If a preset alarm event is detected in the trailer area, the vehicle can be controlled to stop, or an alarm message corresponding to the preset alarm event can be generated and sent to an associated device. The associated device can be an administrator terminal or a cloud that manages all vehicles in the entire park.

[0111] Through the above steps 61 to 64, it is possible to continuously scan data through mobile sensors when the vehicle starts and stops, detect events such as trailer separation, cargo falling, bucket door opening, and moving target cutting in, thereby ensuring the safety of vehicle driving, trailer and cargo.

[0112] For example, Figure 4 A schematic diagram of a vehicle control process provided by an embodiment of the present disclosure, such as Figure 4As shown, first, it can be determined whether the vehicle is started or stopped. If so, the rotating arm can be controlled to rotate, driving the sensor to routinely scan the trailer area to detect whether there is a preset alarm event in the trailer area. If not, it can continue to determine whether the vehicle is located in the preset road network area during the vehicle's driving process.

[0113] If it is within the preset road network area, the rotating motor can be controlled to rotate so that the rotating arm is in a safe position until it exits the preset road network area and restores the previous angle of the rotating arm; if it is outside the preset road network area, it can continue to determine whether the vehicle is going straight during the driving process. If it is going straight, the rotating arm can be controlled to rotate to a specific position and select the area of ​​interest, or perform periodic routine scanning.

[0114] If the vehicle is not moving straight, it can continue to determine whether the vehicle is turning or changing lanes. In the case of changing lanes, the rotating arm is controlled to move to the driving blind spot and the area of ​​interest is selected; in the case of turning, it is determined whether the vehicle is turning left or right. If it is turning left, the rotating arm is rotated to the left and the left side is selected as the area of ​​interest. If it is turning right, the rotating arm is rotated to the right and the right side is selected as the area of ​​interest.

[0115] The vehicle control method provided by the embodiment of the present disclosure determines the target angle of a rotating arm equipped with a sensor in the vehicle in response to detecting a change in the steering wheel angle of the vehicle, and then controls the rotating arm to rotate to the target angle so that the sensor is aimed at the vehicle's driving blind spot, thereby obtaining blind spot detection data collected by the sensor, and controlling the vehicle according to the blind spot detection data. The method can adjust the angle of the rotating arm to align the sensor with the driving blind spot when the vehicle's steering wheel is turned, such as vehicle turning, vehicle lane changing and other working conditions. By detecting the driving blind spot through the sensor, the vehicle's automatic driving system can be provided with complete perception information, especially information such as the location of obstacles in the blind spot, which can prevent people or moving objects in the blind spot from cutting in, thereby ensuring the vehicle's driving safety.

[0116] Figure 5 FIG. 1 is a schematic diagram of the structure of a vehicle control device in an embodiment of the present disclosure, and the device is applicable to the vehicle control method provided in an embodiment of the present disclosure. Figure 5 As shown: the device includes: an angle determination module 510, a rotation control module 520 and a blind spot detection module 530, wherein:

[0117] an angle determination module, configured to determine a target angle of a rotating arm in the vehicle in response to detecting a change in a steering wheel angle of the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle;

[0118] A rotation control module, used for controlling the rotation arm to rotate to the target angle so that the sensor is aligned with the driving blind spot of the vehicle;

[0119] The blind spot detection module is used to obtain the blind spot detection data collected by the sensor and control the vehicle according to the blind spot detection data.

[0120] The vehicle control device provided in the embodiment of the present disclosure can execute the steps in the vehicle control method provided in the method embodiment of the present disclosure, and the execution steps and beneficial effects are no longer repeated here.

[0121] Figure 6 Schematic diagram of the structure of an electronic device in the embodiment of the present disclosure. Figure 6 , which shows a structural schematic diagram of an electronic device 600 suitable for implementing the embodiments of the present disclosure. Figure 6 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0122] like Figure 6 As shown, the electronic device 600 may include a processing device 601, a ROM 602, a RAM 603, a bus 604, an input / output (I / O) interface 605, an input device 606, an output device 607, a storage device 608, and a communication device 609. The processing device (e.g., a central processing unit, a graphics processor, etc.) 601 can perform various appropriate actions and processes to implement the method of the embodiment described in the present disclosure according to the program stored in the read-only memory (ROM) 602 or the program loaded from the storage device 608 to the random access memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic device 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other through the bus 604. The input / output (I / O) interface 605 is also connected to the bus 604.

[0123] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart, thereby implementing the control method of the vehicle as described above. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. When the computer program is executed by the processing device 601, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0124] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0125] The computer-readable medium may be included in the electronic device, or may exist independently without being installed in the electronic device. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the electronic device, the electronic device:

[0126] In response to detecting a change in a steering wheel angle of a vehicle, determining a target angle of a rotating arm in the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle;

[0127] Controlling the rotating arm to rotate to the target angle so that the sensor is aligned with the blind spot of the vehicle;

[0128] Obtain blind spot detection data collected by the sensor, and control the vehicle according to the blind spot detection data.

[0129] Optionally, when the above one or more programs are executed by the electronic device, the electronic device may also execute other steps described in the above embodiments.

[0130] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0131] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

Claims

1. A vehicle control method, characterized in that: The method comprises: In response to detecting a change in a steering wheel angle of a vehicle, determining a target angle of a rotating arm in the vehicle, wherein the rotating arm is a rotatable component carrying a sensor in the vehicle; Controlling the rotating arm to rotate to the target angle so that the sensor is aligned with the blind spot of the vehicle; Obtain blind spot detection data collected by the sensor, and control the vehicle according to the blind spot detection data.

2. The method according to claim 1, determining a target angle of a rotating arm in the vehicle, comprising: Acquiring vehicle state information of the vehicle, and determining a predicted driving trajectory of the vehicle according to the vehicle state information; The target angle of the rotating arm is determined according to the predicted driving trajectory.

3. The method according to claim 1, determining a target angle of a rotating arm in the vehicle, comprising: Acquire a steering wheel angle of a tractor in the vehicle and geometric structure parameters of the vehicle; Determining a predicted heading angle of each trailer in the vehicle according to the steering wheel angle, the geometric structure parameters and the vehicle motion model; A target angle of the rotating arm is determined based on the predicted heading angle of each trailer in the vehicle.

4. The method according to claim 1, controlling the vehicle according to the blind spot detection data, comprising: Determining the position of the obstacle target in the driving blind spot relative to the vehicle according to the blind spot detection data; According to the position of the obstacle target relative to the vehicle, the vehicle is controlled to stop or slow down, or the acoustic light warning system of the vehicle is controlled to operate.

5. The method according to claim 4, characterized in that Determining the position of the obstacle target in the driving blind spot relative to the vehicle according to the blind spot detection data includes: Determining an external parameter of the sensor according to the target angle, wherein the external parameter is used to describe a positional relationship between the sensor and the vehicle; determining a position of the obstacle target relative to the sensor according to the blind spot detection data; A position of the obstacle object relative to the vehicle is determined based on the external parameters and the position of the obstacle object relative to the sensor.

6. The method according to claim 5, characterized in that Before controlling the vehicle based on blind spot detection data, it also includes: Determining the area position of the area of ​​interest in the blind spot detection data according to the target angle; According to the area position, the area of ​​interest is located in the blind spot detection data, and for other data in the blind spot detection data that is outside the area of ​​interest, the other data is removed, or the weight or confidence of the other data is updated.

7. The method according to claim 6, characterized in that Determining the position of the obstacle target relative to the sensor according to the blind spot detection data includes: Determining internal parameters of the sensor according to the area position of the region of interest, wherein the internal parameters are calibration verification parameters of a mapping relationship, and the mapping relationship is a relationship between a point in the data detected by the sensor and a point in space; According to the internal parameters, the points in the blind spot detection data are mapped into space to obtain the position of the obstacle target relative to the sensor.

8. The method according to claim 1, characterized in that The method further comprises: During the driving of the vehicle, obtaining the actual position of the vehicle in the road network; In response to detecting that the actual position is located within a preset road network area, determining a safe angle of the rotating arm according to the preset road network area, and recording a current angle of the rotating arm; The rotating arm is controlled to rotate to the safety angle, and when it is detected that the vehicle moves out of the preset road network area, the rotating arm is controlled to rotate to the recorded angle.

9. The method according to claim 1, characterized in that: The method further comprises: In response to a start / stop signal of the vehicle, controlling the rotation arm to rotate; During the rotation of the rotating arm, the trailer area of ​​the vehicle is detected by the sensor to obtain trailer detection data of the vehicle; According to the trailer detection data, determining whether there is a preset alarm event in the trailer area; In response to the presence of the preset alarm event in the trailer area, the vehicle is controlled to stop, or corresponding alarm information is generated and sent to an associated device.

10. An electronic device, characterized in that: The electronic device comprises: one or more processors; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 9.

Images