Vehicle control method, device and computer equipment

Abstract

The present disclosure provides a vehicle control method, device and computer equipment, and relates to the technical field of vehicles. The vehicle control method comprises: acquiring a driving state parameter of a target vehicle; determining whether the driving state of the target vehicle is abnormal according to the driving state parameter; if the driving state of the target vehicle is normal, controlling the driving state of the ego vehicle by using at least one target parameter; and if the driving state of the target vehicle is abnormal, performing weighted calculation on the at least one target parameter to obtain at least one weighted parameter, and controlling the driving state of the ego vehicle by using the weighted parameter. The vehicle control method of the present disclosure introduces the use of the weighted parameter on the basis of the control of the existing adaptive cruise system, and can cope with the situation that the front vehicle is regularly braked, is emergently braked, or is faulty during the driving process of following the front vehicle. In this way, the ego vehicle can be intervened in advance, and the panic caused by the excessively large deceleration at the end of the deceleration of the adaptive cruise system and the collision risk can be avoided.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of vehicles, in particular to a vehicle control method and device and computer equipment. BACKGROUND

[0002] With the development of technology, there are more and more road vehicles, the traffic environment is deteriorating, and the levels of drivers are uneven. Rear-end collisions, forced lane changes, parking scratches, and high-speed fatigue driving are increasing. The Advanced Driving Assistance System (ADAS) that is committed to improving the comfort and safety of automobile driving is increasingly valued.

[0003] ADAS is usually based on perception sensors (radar, camera, etc.) to sense the surrounding environment at any time during vehicle driving, collect data, identify, detect and track static and dynamic objects, and perform system operation and analysis to warn the driver in the form of sound or image, and to a certain extent, control the vehicle to improve driving comfort and safety.

[0004] The Adaptive Cruise Control (ACC) is the most basic function in ADAS. Through the feedback signal of the vehicle distance sensor, the ACC control unit can determine the road conditions according to the moving speed of the object close to the vehicle and control the driving state of the vehicle.

[0005] In related technologies, the ACC control unit relies on a single control logic to control the driving state of the vehicle, which has a safety hazard of delay and inaccuracy and cannot cope with the increasingly complex traffic environment. SUMMARY

[0006] The present disclosure provides a vehicle control method, device and computer equipment, which can solve the problem of single ACC control logic, safety hazard, and inability to cope with the increasingly complex traffic environment.

[0007] The technical solution is as follows:

[0008] In one aspect, a vehicle control method is provided, the vehicle control method comprising:

[0009] obtaining a driving state parameter of a target vehicle;

[0010] determining whether the driving state of the target vehicle is abnormal according to the driving state parameter;

[0011] if the driving state of the target vehicle is normal, controlling the driving state of the ego vehicle with at least one target parameter;

[0012] If the driving state of the target vehicle is abnormal, at least one weighted parameter is calculated by weighting the at least one target parameter, and the driving state of the ego vehicle is controlled according to the weighted parameter.

[0013] In some embodiments, the at least one target parameter is calculated by weighting to obtain at least one weighted parameter, including:

[0014] At least one weighting coefficient is obtained.

[0015] The at least one weighting coefficient is multiplied by the at least one target parameter to obtain the at least one weighted parameter.

[0016] In some embodiments, the weighting coefficient includes:

[0017] At least one of a first weighting coefficient corresponding to the brake light state of the target vehicle, a second weighting coefficient corresponding to the turn signal state of the target vehicle, a third weighting coefficient corresponding to the vehicle speed of the target vehicle, a fourth weighting coefficient corresponding to the deceleration of the target vehicle, a fifth weighting coefficient corresponding to the deceleration rate of the target vehicle, a sixth weighting coefficient corresponding to the hazard warning light state of the target vehicle, and a seventh weighting coefficient corresponding to the extended signal.

[0018] In some embodiments, the target parameter includes at least one of an acceleration target parameter, a time-distance target parameter, and an acceleration rate target parameter.

[0019] In some embodiments, the driving state parameter of the target vehicle is obtained, including:

[0020] The driving state parameter of the target vehicle is obtained by a perception module.

[0021] The driving state parameter includes at least one of a brake light state, a turn signal state, a hazard warning light state, a distance from a lane line, a deceleration, and a deceleration rate.

[0022] In some embodiments, the driving state of the target vehicle is determined to be abnormal according to the driving state parameter, including:

[0023] When the brake light of the target vehicle is in an on state, the driving state of the target vehicle is determined to be abnormal.

[0024] When the turn signal of the target vehicle is in an on state, the driving state of the target vehicle is determined to be abnormal.

[0025] When the hazard warning light of the target vehicle is in an on state, the driving state of the target vehicle is determined to be abnormal.

[0026] determining that the driving state of the target vehicle is abnormal when the distance between the target vehicle and the lane line is less than a target distance;

[0027] determining that the driving state of the target vehicle is abnormal when the deceleration of the target vehicle is less than a target deceleration;

[0028] determining that the driving state of the target vehicle is abnormal when the rate of change of the deceleration of the target vehicle is less than a target rate of change of deceleration.

[0029] In some embodiments, the vehicle control method further comprises:

[0030] obtaining a current time distance between the ego vehicle and the target vehicle;

[0031] determining whether the current time distance is greater than a target safety time distance;

[0032] controlling the driving state of the ego vehicle with at least one target parameter if the current time distance is greater than the target safety time distance.

[0033] In some embodiments, the target vehicle comprises at least one of a front vehicle in the same lane, a rear vehicle in the same lane, a front vehicle in an adjacent lane, a rear vehicle in an adjacent lane, an overtaking vehicle in an adjacent lane, and a meeting vehicle in an adjacent lane.

[0034] The same lane is a lane in which the ego vehicle is currently driving, the adjacent lane is a lane adjacent to the same lane, the overtaking vehicle is a vehicle expected to overtake the ego vehicle from the adjacent lane, and the meeting vehicle is a vehicle driving in the opposite direction to the ego vehicle and expected to pass the ego vehicle.

[0035] In another aspect, a vehicle control device is provided, which comprises:

[0036] a perception module configured to obtain a driving state parameter of a target vehicle;

[0037] a determination module configured to receive the driving state parameter input by the perception module and determine whether the driving state of the target vehicle is abnormal according to the driving state parameter;

[0038] a control module configured to control the driving state of the ego vehicle with a target parameter when the driving state of the target vehicle is normal, and to obtain a weighted parameter by weighting the target parameter when the driving state of the target vehicle is abnormal, and control the driving state of the ego vehicle with the weighted parameter.

[0039] In another aspect, a computer device is provided, which includes a processor and a memory, and the memory stores at least one program code, which is loaded and executed by the processor to implement the vehicle control method according to the present disclosure.

[0040] The technical solution provided by the present disclosure has at least the following beneficial effects:

[0041] The vehicle control method according to the present disclosure introduces the use of a weighting parameter on the basis of the control of the existing adaptive cruise system, so that the ego vehicle can intervene in advance when the front vehicle is in a normal braking, emergency braking, or front vehicle failure scenario, thereby reducing the panic and collision risk caused by the excessive deceleration at the end of the adaptive cruise system deceleration. BRIEF DESCRIPTION OF DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed in the embodiment description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without creative labor.

[0043] Figure 1 is a flowchart of the vehicle control method provided by the present embodiment;

[0044] Figure 2 is a flowchart of the vehicle control method provided by another embodiment of the present disclosure;

[0045] Figure 3 is a flowchart of the vehicle control method provided by another embodiment of the present disclosure;

[0046] Figure 4 is a flowchart of the vehicle control method provided by another embodiment of the present disclosure;

[0047] Figure 5 is a flowchart of the vehicle control method provided by another embodiment of the present disclosure;

[0048] Figure 6 is a structural schematic diagram of the vehicle control device provided by the present embodiment;

[0049] Figure 7 is a control logic diagram of the vehicle control method provided by the present embodiment;

[0050] Figure 8 is a structural schematic diagram of the computer device provided by the present embodiment.

[0051] The reference signs in the drawings represent the following:

[0052] 100, perception module; 200, determination module; 300, control module; 400, perception sensor; 500, ADAS controller; 600, ESP; 700, EMS; 800, brake; 900, processor; 1000, memory; 1100, communication interface; 1200, bus. DETAILED DESCRIPTION

[0053] The exemplary embodiments will be described in detail herein with reference to the attached drawings. In the following description, like reference numerals refer to like elements throughout the description. The following exemplary embodiments are not representative of all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present disclosure, as detailed in the appended claims.

[0054] Unless otherwise defined, all technical terms used in the embodiments of the present disclosure have the same meaning as commonly understood by one of ordinary skill in the art.

[0055] ADAS is a system that uses various sensors (millimeter wave radar, laser radar, single\double camera and satellite navigation) installed on the car to sense the environment around the car at any time during driving, collect data, identify, detect and track static and dynamic objects, and combine with navigation map data to perform system operation and analysis, so as to make the driver aware of possible dangers in advance, effectively increase the comfort and safety of car driving.

[0056] ACC is a new system that adds a reasonable distance control function to the cruise control system at the set speed. During vehicle driving, the distance sensor (radar) installed on the front of the vehicle continuously scans the road in front of the vehicle, and the wheel speed sensor collects the vehicle speed signal. When the distance between the target front vehicle is too small, the ACC control unit can make the wheels brake appropriately and make the engine output power decrease by coordinating with the anti-lock braking system and engine control system, so that the vehicle and the front vehicle always maintain a safe distance.

[0057] Through the feedback signal of the distance sensor, the ACC control unit can judge the road conditions according to the moving speed of the object close to the vehicle, and control the driving state of the vehicle. Through the feedback of the accelerator pedal, the ACC control unit can determine whether to execute the cruise control to reduce the driver's fatigue.

[0058] In the process of controlling a vehicle by an adaptive cruise system (ACC), a mainstream solution in the market is single time-distance control. Although different time distances can be selected, most of them are selected from 3 gears to 7 gears. However, the control logic is single, and cannot meet the needs of the actual traffic environment, which may cause panic and collision risk in some working conditions.

[0059] Therefore, the present disclosure provides a vehicle control method, which can realize early intervention, reduce the panic caused by excessive deceleration at the end of adaptive cruise system deceleration, and avoid collision risk.

[0060] The technical solution provided by the present disclosure is applicable to vehicles using ACC control technology, such as electric vehicles, fuel vehicles, and new energy vehicles.

[0061] In order to make the purpose, technical solution and advantages of the present disclosure clearer, the embodiments of the present disclosure will be described in further detail below with reference to the drawings.

[0062] Figure 1 FIG. 1 is a flowchart of a vehicle control method provided by an embodiment of the present disclosure.

[0063] In one aspect, in combination with Figure 1 As shown in FIG. 1, the embodiment provides a vehicle control method, which comprises the following steps.

[0064] Step S1, obtaining a driving state parameter of a target vehicle;

[0065] Step S2, judging whether the driving state of the target vehicle is abnormal according to the driving state parameter;

[0066] Step S3, if the driving state of the target vehicle is normal, controlling the driving state of the ego vehicle by at least one target parameter;

[0067] Step S4, if the driving state of the target vehicle is abnormal, performing weighted calculation on the at least one target parameter to obtain at least one weighted parameter, and controlling the driving state of the ego vehicle by the weighted parameter.

[0068] The vehicle control method of the embodiment introduces the use of weighted parameters on the basis of the control of the existing adaptive cruise system, and can realize early intervention of the ego vehicle in the process of following the preceding vehicle, reduce the panic caused by excessive deceleration at the end of adaptive cruise system deceleration, and avoid collision risk in the scenes of regular braking, emergency braking, and preceding vehicle failure of the preceding vehicle.

[0069] In some possible implementation manners, the number of target parameters is one, two, three, or the like. The target parameter as a parameter for controlling the driving state of the ego vehicle can be a set value or a value calculated by a vehicle-mounted computer.

[0070] Exemplarily, the target parameter can be a torque signal or a braking force signal, and the longitudinal control of the ego vehicle, i.e., the acceleration, deceleration, braking, etc. of the ego vehicle, can be performed.

[0071] Figure 2 is a flowchart of a vehicle control method provided by another embodiment of the present disclosure.

[0072] In combination Figure 2 As shown in some embodiments, the at least one target parameter in step S4 is weighted to obtain at least one weighted parameter, including:

[0073] Step S41, obtaining at least one weighting coefficient;

[0074] Step S42, multiplying the at least one weighting coefficient with the at least one target parameter to obtain at least one weighted parameter.

[0075] The weighted parameter in the present embodiment is obtained by multiplying the target parameter with the weighting coefficient, wherein the weighting coefficient is used to increase or decrease the target parameter in a corresponding manner by multiplying the weighting coefficient, so as to improve the intervention sensitivity of the ego vehicle, increase the intervention time and intervention distance of the ego vehicle in abnormal situations, and make the ACC longitudinal control more gentle and comfortable.

[0076] In some possible implementations, the weighting coefficient is a calibration quantity, i.e., it is calibrated manually or by a computer according to the actual vehicle performance in the development stage.

[0077] For example, when the target vehicle is in a normal driving state, the weighting coefficient associated with the braking control of the ego vehicle is 1, and when the target vehicle is in an abnormal driving state, the weighting coefficient associated with the braking control of the ego vehicle is 2, so that when the target vehicle is in an abnormal driving state, the braking system of the ego vehicle will perform braking control with a target parameter twice as large, which can be embodied as, for example, that the braking distance is increased to twice the original value, or the deceleration is increased to twice the original value, etc.

[0078] In some embodiments, the weighting coefficient includes at least one of a first weighting coefficient corresponding to the brake light state of the target vehicle, a second weighting coefficient corresponding to the turn signal state of the target vehicle, a third weighting coefficient corresponding to the vehicle speed of the target vehicle, a fourth weighting coefficient corresponding to the deceleration of the target vehicle, a fifth weighting coefficient corresponding to the deceleration rate of the target vehicle, a sixth weighting coefficient corresponding to the hazard warning light state of the target vehicle, and a seventh weighting coefficient corresponding to the extension signal.

[0079] Exemplarily, the weighting coefficient includes the first weighting coefficient, so that after the brake light of the target vehicle is turned on, the first target parameter is multiplied by the first weighting coefficient to obtain a first weighted parameter, and the ego vehicle controls the driving state of the ego vehicle with the first weighted parameter, such as increasing the braking distance, etc.

[0080] Exemplarily, the weighting coefficients include a second weighting coefficient, so that after the target vehicle speed appears abnormal, the second target parameter is multiplied by the second weighting coefficient to obtain a second weighting parameter, and the ego vehicle controls the driving state of the ego vehicle with the second weighting parameter, such as increasing the safety time interval.

[0081] Exemplarily, the weighting coefficients include a first weighting coefficient, a second weighting coefficient, and a third weighting coefficient, so that when any one of the three situations of the brake light of the target vehicle being on, the turn signal of the target vehicle being on, and the speed of the target vehicle being abnormal appears, the corresponding target parameter is multiplied by the corresponding weighting coefficient to obtain a corresponding weighting parameter, and then the ego vehicle controls the driving state of the ego vehicle with the corresponding weighting parameter.

[0082] When any two of the three situations appear or all of the three situations appear, the corresponding target parameter is multiplied by the corresponding weighting coefficient to obtain a corresponding weighting parameter, and then the ego vehicle controls the driving state of the ego vehicle with the three corresponding weighting parameters at the same time.

[0083] It can be understood that the weighting coefficients can include any one of the first to seventh weighting coefficients or a combination of any ones thereof, and the use of multiple weighting coefficients can enrich the control strategy of the ego vehicle and improve the driving safety and comfort of the ego vehicle.

[0084] In some possible implementations, the extended signal is, for example, corresponding to a passing state or a meeting state, and the seventh weighting coefficient is used to realize early intervention in the passing state or the meeting state, thereby improving the control safety and comfort of the adaptive cruise system.

[0085] In some embodiments, the target parameter includes at least one of an acceleration target parameter, a time interval target parameter, and an acceleration change rate target parameter.

[0086] It can be understood that the target parameter can also be other target parameters for realizing longitudinal control and lateral control of the ego vehicle.

[0087] Figure 3 is a flowchart of a vehicle control method provided by another embodiment of the disclosure.

[0088] In combination with Figure 3 As shown in the figure, in some embodiments, the driving state parameter of the target vehicle is obtained in step S1, including:

[0089] In step S11, the driving state parameter of the target vehicle is obtained by the perception module; the driving state parameter includes at least one of a brake light state, a turn signal state, a hazard warning flasher state, a distance from a lane line, a deceleration, and a deceleration change rate.

[0090] In the vehicle control method of the embodiment, the driving state parameter of the target vehicle is obtained by using the perception module. The driving state parameter can be any one of the brake light state, the turn signal light state, the hazard warning light state, the distance from the lane line, the deceleration, the deceleration rate, or a combination of any of the above. The driving state parameter can reflect the driving state of the target vehicle. By perceiving the driving state of the target vehicle, the interference and risk that the ego vehicle may be subjected to can be known, so that the adaptive cruise control system is controlled to perform corresponding control.

[0091] Exemplarily, the brake light state includes but is not limited to the on state, the off state, the always-on state, the flashing state, the high-brightness state, and the low-brightness state. The on state indicates that the target vehicle is braking, the off state indicates that the target vehicle is not braking, the always-on state indicates that the target vehicle is continuously braking, the flashing state indicates that the target vehicle is point braking, the high-brightness state indicates that the target vehicle is emergency braking, and the low-brightness state indicates that the target vehicle is gentle braking.

[0092] Each of the above brake light states corresponds to a weighting coefficient, for example, the high-brightness state corresponds to a weighting coefficient. When the target vehicle appears in the high-brightness state, the ego vehicle will brake according to the weighted parameter obtained by multiplying the weighting coefficient and the target parameter.

[0093] Alternatively, a plurality of states in the above brake light state correspond to a weighting coefficient. For example, the flashing state and the low-brightness state have similar vehicle conditions, so the flashing state and the low-brightness state correspond to the same weighting coefficient.

[0094] Figure 4 is a flowchart of a vehicle control method provided by another embodiment of the disclosure.

[0095] In combination Figure 4 As shown in FIG. 8, in some embodiments, the step S2 of determining whether the driving state of the target vehicle is abnormal according to the driving state parameter includes:

[0096] In step S21, when the brake light of the target vehicle is in the on state, it is determined that the driving state of the target vehicle is abnormal.

[0097] When the brake light of the target vehicle is on, it indicates that the target vehicle is braking, which will trigger step S4 of the disclosure, and the ego vehicle performs longitudinal control and / or lateral control according to the weighted parameter.

[0098] In step S22, when the turn signal light of the target vehicle is in the on state, it is determined that the driving state of the target vehicle is abnormal.

[0099] When the target vehicle's steering light is on, indicating that the target vehicle will turn, which can be turning into the lane or turning out of the lane, step S4 of the present disclosure will be triggered, and the ego vehicle will perform longitudinal control and / or lateral control on the ego vehicle with the weighting parameter.

[0100] Step S23, when the target vehicle's hazard warning flasher is on, it is determined that the target vehicle's driving state is abnormal.

[0101] When the target vehicle's hazard warning flasher is on, it indicates that the target vehicle is in a dangerous situation and may stop suddenly or turn sharply, which will trigger step S4 of the present disclosure, and the ego vehicle will perform longitudinal control and / or lateral control on the ego vehicle with the weighting parameter.

[0102] Step S24, when the distance between the target vehicle and the lane line is less than the target distance, it is determined that the target vehicle's driving state is abnormal.

[0103] When the distance between the target vehicle and the lane line is less than the target distance, it indicates that the target vehicle deviates from the normal driving direction, which poses a certain safety risk or the possibility of sudden turning, which will trigger step S4 of the present disclosure, and the ego vehicle will perform longitudinal control and / or lateral control on the ego vehicle with the weighting parameter.

[0104] For example, the target distance is 20cm-50cm.

[0105] Step S25, when the target vehicle's deceleration is less than the target deceleration, it is determined that the target vehicle's driving state is abnormal.

[0106] When the target vehicle's deceleration is less than the target deceleration, it indicates that the target vehicle has the possibility of deceleration or stopping, which will trigger step S4 of the present disclosure, and the ego vehicle will perform longitudinal control and / or lateral control on the ego vehicle with the weighting parameter.

[0107] Step S26, when the target vehicle's deceleration rate of change is less than the target deceleration rate of change, it is determined that the target vehicle's driving state is abnormal.

[0108] When the target vehicle's deceleration rate of change is less than the target deceleration rate of change, it indicates that the target vehicle's speed control is unstable, and there is a possibility of acceleration, deceleration, or stopping, which will trigger step S4 of the present disclosure, and the ego vehicle will perform longitudinal control and / or lateral control on the ego vehicle with the weighting parameter.

[0109] Steps S21-S26 in this embodiment can be selected to perform a single step or multiple steps, both of which can achieve the technical effects of this embodiment, and the present disclosure does not limit this.

[0110] Figure 5 is a flowchart of a vehicle control method provided by another embodiment of the present disclosure.

[0111] In conjunction with Figure 5 In some embodiments, the vehicle control method further comprises:

[0112] Step S5, obtaining a current time distance between the ego vehicle and the target vehicle;

[0113] Step S6, determining whether the current time distance is greater than the target safety time distance;

[0114] Step S7, if the current time distance is greater than the target safety time distance, controlling the driving state of the ego vehicle with at least one target parameter.

[0115] Time distance, also known as Time Headway (TH), is an important indicator for evaluating driving safety, which is closely related to traffic flow composition and driving behavior, and is an important basis for reflecting road capacity and service level, and has important significance for optimizing road design and management.

[0116] Time distance represents the time difference between the front ends of two vehicles passing through the same point, which can generally be calculated by dividing the distance between the front ends of the two vehicles by the speed of the following vehicle. Time distance represents the maximum reaction time of the driver of the following vehicle when the current vehicle brakes, so it does not fluctuate with changes in speed.

[0117] For safety, the target safety time distance is about 2s for a certain distance, i.e., target safety distance = minimum time headway x speed.

[0118] At the target safety time distance, the adaptive cruise control system has enough time and distance to perform vehicle control, and has good safety and comfort.

[0119] For example, the target safety time distance = basic safety time distance x weighting factor. The basic safety time distance is determined by the vehicle's own power and braking ability, and the weighting factor is determined according to the abnormal driving state of the target vehicle. For example, when the target vehicle exhibits an abnormal driving state, the weighting factor is greater than 1, so that the target safety time distance increases, increasing the safety distance between the ego vehicle and the target vehicle.

[0120] In some embodiments, the target vehicle includes at least one of a front vehicle in the same lane, a rear vehicle in the same lane, a front vehicle in the adjacent lane, a rear vehicle in the adjacent lane, an overtaking vehicle in the adjacent lane, and a vehicle meeting in the adjacent lane.

[0121] Wherein, the same lane is the lane currently driven by the ego vehicle, the adjacent lane is the lane adjacent to the same lane, the overtaking vehicle is the vehicle expected to overtake the ego vehicle from the adjacent lane, and the meeting vehicle is the vehicle driving in the opposite direction of the ego vehicle and expected to pass through the ego vehicle.

[0122] On the other hand, in conjunction with Figure 6 , 7As shown, the embodiment provides a vehicle control device, wherein Figure 6 FIG. 1 is a structural schematic diagram of a vehicle control device provided by an embodiment of the present disclosure; Figure 7 FIG. 2 is a control logic diagram of a vehicle control method provided by an embodiment of the present disclosure.

[0123] The vehicle control device comprises a perception module 100, the perception module 100 being configured to acquire a driving state parameter of a target vehicle; a judgment module 200, the judgment module 200 being configured to receive the driving state parameter input by the perception module 100, and judge whether the driving state of the target vehicle is abnormal according to the driving state parameter; and a control module 300, the control module 300 being configured to control the driving state of the ego vehicle according to a target parameter when the driving state of the target vehicle is normal, and perform weighted calculation on the target parameter to obtain a weighted parameter, and control the driving state of the ego vehicle according to the weighted parameter when the driving state of the target vehicle is abnormal.

[0124] The vehicle control device in the embodiment introduces the use of the weighted parameter on the basis of the control of the existing adaptive cruise system, and can intervene in advance when the ego vehicle is in a following vehicle driving process, such as normal braking, emergency braking, and vehicle fault of the front vehicle, so as to reduce the panic feeling and avoid collision risks caused by too large deceleration at the end of the adaptive cruise system.

[0125] In some possible implementation manners, the perception module 100 comprises at least one perception sensor 400, and the perception sensor 400 comprises, but is not limited to, a front camera module (FCM), a front radar module (FRM), an angular radar, and the like.

[0126] Optionally, the judgment module 200 and the control module 300 are integrated in an ADAS controller 500 of the vehicle, or the judgment and control functions are realized by using an inherent electronic circuit structure in the ADAS controller 500.

[0127] Referring to Figure 6 As shown, the ADAS controller 500 is electrically connected with an electronic stability program (ESP) 600, and the ESP 600 is electrically connected with an engine management system (EMS) 700 and a brake 800.

[0128] The state of the brake light, the turn signal, the hazard warning flasher of the target vehicle, or the vehicle speed, the deceleration, the deceleration rate of change, or other parameters capable of representing the driving state is acquired by the perception sensor 400, and is transmitted to the judgment module 200 and the control module 300 in the ADAS controller 500. The ADAS controller 500 outputs a control instruction to the ESP 600, and the ESP 600 outputs a control instruction to the EMS 700 and the brake 800, so as to complete the control of the vehicle.

[0129] In another aspect, the embodiment provides a computer device, which comprises a processor 900 and a memory 1000, and the memory 1000 stores at least one program code, and the at least one program code is loaded and executed by the processor 900 to implement the vehicle control method of the present disclosure.

[0130] Figure 8 FIG. 1 is a structural schematic diagram of a computer device provided by the embodiment of the present disclosure, referring to Figure 8 The computer device comprises one or more of the following components: a processor 900, a memory 1000, a communication interface 1100 and a bus 1200.

[0131] The processor 900 comprises one or more processing cores, and the processor 900 executes various functional applications and information processing by running software programs and modules. The memory 1000 and the communication interface 1100 are connected to the processor 900 through the bus 1200. The memory 1000 can be used to store at least one instruction, and the processor 900 is used to execute the at least one instruction to implement each step in the above method embodiment.

[0132] In addition, the memory 1000 can be realized by any type of volatile or non-volatile storage device or a combination thereof, including but not limited to: a magnetic or optical disk, an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a static random access memory (SRAM), a read-only memory (ROM), a magnetic memory, a flash memory, a programmable read-only memory (PROM).

[0133] In another aspect, the embodiment provides a readable storage medium, and the readable storage medium stores at least one program code, and the at least one program code is loaded and executed by a processor to implement the vehicle control method of the present disclosure. For example, the non-transitory computer readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk and an optical data storage device, etc.

[0134] The terms "several", "at least one", "multiple", "at least two" mean one or more than one. The term "and / or" describes associativity of the associated objects, which means that there can be three cases, for example, A and / or B can mean that A exists alone, A and B exist together, and B exists alone. The character " / " generally represents an "or" relationship between the associated objects before and after it.

[0135] In the description of the present specification, the description of the terms "certain embodiments", "one embodiment", "some embodiments", "illustrative embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in connection with the embodiments or examples are included in at least one embodiment or example of the present disclosure.

[0136] The above only describes the embodiments of the present disclosure, and does not limit the present disclosure. Any modification, equivalent replacement, improvement, etc. made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A vehicle control method, characterized in that, The vehicle control method includes: Obtain the driving status parameters of the target vehicle; Determine whether the driving status of the target vehicle is abnormal based on the driving status parameters; If the target vehicle is in a normal driving state, then the driving state of the vehicle is controlled by at least one target parameter. If the driving state of the target vehicle is abnormal, the at least one target parameter is weighted to obtain at least one weighted parameter, and the driving state of the vehicle is controlled by the weighted parameter. The at least one target parameter is weighted to obtain at least one weighted parameter, including: Obtain at least one weighting coefficient; the at least one weighting coefficient is a calibrated value determined based on the actual situation of the vehicle; The at least one weighting coefficient is multiplied by the at least one target parameter to obtain the at least one weighting parameter; When the weighting coefficients include: When at least two of the following are selected: a first weighting coefficient corresponding to the brake light status of the target vehicle, a second weighting coefficient corresponding to the turn signal status of the target vehicle, a third weighting coefficient corresponding to the vehicle speed of the target vehicle, a fourth weighting coefficient corresponding to the deceleration of the target vehicle, a fifth weighting coefficient corresponding to the rate of change of deceleration of the target vehicle, a sixth weighting coefficient corresponding to the hazard warning flasher status of the target vehicle, and a seventh weighting coefficient corresponding to the extended signal, the corresponding target parameter is multiplied by the corresponding weighting coefficient to obtain the corresponding weighting parameter, and the driving state of the vehicle is controlled with at least two corresponding weighting parameters; The step of determining whether the driving status of the target vehicle is abnormal based on the driving status parameters includes: When the brake lights of the target vehicle are illuminated, it is determined that the driving status of the target vehicle is abnormal. When the turn signal of the target vehicle is illuminated, it is determined that the driving status of the target vehicle is abnormal. When the hazard warning lights of the target vehicle are illuminated, it is determined that the driving status of the target vehicle is abnormal. When the distance between the target vehicle and the lane line is less than the target distance, the driving state of the target vehicle is determined to be abnormal. When the deceleration of the target vehicle is less than the target deceleration, the driving state of the target vehicle is determined to be abnormal. When the rate of change of deceleration of the target vehicle is less than the rate of change of target deceleration, the driving state of the target vehicle is determined to be abnormal. Also includes: Obtain the current time distance between the vehicle and the target vehicle; Determine whether the current time interval is greater than the target safe time interval; If the current time distance is greater than the target safe time distance, the driving state of the vehicle is controlled by at least one target parameter; wherein, the target safe time distance = basic safe time distance × weighting coefficient, the basic safe time distance is determined by the vehicle's own power and braking capabilities, and the weighting coefficient is determined according to the abnormal driving state of the target vehicle.

2. The vehicle control method according to claim 1, characterized in that, The target parameters include at least one of the following: acceleration target parameters, time-distance target parameters, and acceleration rate of change target parameters.

3. The vehicle control method according to claim 1, characterized in that, The acquisition of the target vehicle's driving status parameters includes: The driving status parameters of the target vehicle are obtained through the sensing module; The driving status parameters include at least one of the following: brake light status, turn signal status, hazard warning flasher status, distance to lane lines, deceleration, and rate of change of deceleration.

4. The vehicle control method according to claim 1, characterized in that, The target vehicle includes at least one of the following: the vehicle in front in this lane, the vehicle behind in this lane, the vehicle in front in the adjacent lane, the vehicle behind in the adjacent lane, the overtaking vehicle in the adjacent lane, and the vehicle passing in the adjacent lane.

5. A computer device, characterized in that, The computer device includes a processor and a memory, the memory storing at least one piece of program code, the at least one piece of program code being loaded and executed by the processor to implement the vehicle control method as described in any one of claims 1-4.

Images