Workshop time interval determination method, computer equipment, storage medium and vehicle

Abstract

The invention provides a vehicle-to-vehicle time interval determination method, computer equipment, a storage medium and a vehicle, and the method comprises the steps: determining a first adhesion coefficient corresponding to a driving road surface according to a road environment image collected by a first vehicle in real time in a process that the first vehicle follows a second vehicle to drive; the wheel slip rate of the first vehicle is determined according to the actually measured vehicle speed of the first vehicle and the wheel speed of the wheels of the first vehicle, and a second adhesion coefficient corresponding to the driving road surface is determined according to an adhesion coefficient determination mode matched with the value of the wheel slip rate; if the value ranges of the wheel slip rates are different, the corresponding adhesion coefficient determination modes are different; determining a target attachment coefficient according to the confidence coefficients corresponding to the first attachment coefficient and the second attachment coefficient; and according to the target adhesion coefficient and the actually measured vehicle speed, determining a target vehicle-to-vehicle time interval of the first vehicle, and controlling the first vehicle to run according to the target vehicle-to-vehicle time interval.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent driving technology, and in particular to a method for determining time headway between vehicles, a computer device, a storage medium, and a vehicle. Background Art

[0002] After the assisted driving cruise function is turned on, the ego vehicle can follow the target vehicle in front according to the pre-set time interval. When the speed of the target vehicle is lower than that of the ego vehicle, the assisted driving cruise function can be used to request the controller to perform a braking operation to ensure that the ego vehicle can maintain the preset time interval between vehicles.

[0003] However, in some special weather conditions (such as rainy and snowy weather) or on some special roads (such as icy roads, slippery roads, etc.), the road adhesion coefficient will change. If you still follow the vehicle according to the preset headway, you may rear-end the vehicle in front due to insufficient braking distance, which reduces driving safety. Therefore, how to improve driving safety during following a vehicle has become a technical problem that needs to be solved urgently. Summary of the invention

[0004] The embodiments of the present disclosure at least provide a method for determining time headway between vehicles, a computer device, a storage medium, and a vehicle.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for determining a time headway between vehicles, including:

[0006] In the process of a first vehicle following a second vehicle, a first adhesion coefficient corresponding to a driving road surface is determined according to a road environment image collected by the first vehicle in real time; a wheel slip rate of the first vehicle is determined according to an actually measured vehicle speed of the first vehicle and a wheel speed of the first vehicle, and a second adhesion coefficient corresponding to the driving road surface is determined according to an adhesion coefficient determination method that matches the value of the wheel slip rate; different value ranges of the wheel slip rate correspond to different adhesion coefficient determination methods; a target adhesion coefficient corresponding to the driving road surface is determined according to confidences corresponding to the first adhesion coefficient and the second adhesion coefficient respectively; the confidence corresponding to the first adhesion coefficient is related to the image content quality of the road environment image, and the confidence corresponding to the second adhesion coefficient is related to the value of the wheel slip rate; a target time headway of the first vehicle is determined according to the target adhesion coefficient and the actually measured vehicle speed, and the first vehicle is controlled to travel according to the target time headway.

[0007] In this way, during the following driving of the first vehicle, the first adhesion coefficient corresponding to the driving road surface can be predicted more accurately by using the road environment image; at the same time, the wheel slip rate can be accurately calculated according to the actual driving data of the first vehicle (such as the measured vehicle speed and wheel speed). According to the value of the wheel slip rate, different adhesion coefficient determination methods are used to determine the adhesion coefficient, which can improve the rationality of the determined second adhesion coefficient and more accurately calculate the second adhesion coefficient that the driving road surface can provide for the first vehicle in the current driving state. Then, by combining the first adhesion coefficient and the second adhesion coefficient and the corresponding confidence levels of the two, the real target adhesion coefficient that the driving road surface can provide can be accurately calculated. The target adhesion coefficient and the measured vehicle speed can be used to accurately determine the safe target time headway of the first vehicle when following the vehicle on the current driving road surface. By controlling the first vehicle to drive according to the target time headway, it can be ensured that there is a sufficient safe braking distance between the first vehicle and the following second vehicle, avoiding the occurrence of rear-end collision, and improving driving safety.

[0008] In a possible implementation, a braking distance corresponding to the first vehicle is determined based on the relative speed between the first vehicle and the second vehicle and the target adhesion coefficient; the second vehicle travels in front of the first vehicle and in the same direction as the first vehicle; a minimum time headway required for the braking process of the first vehicle is determined based on the braking distance and the measured speed of the first vehicle; a target time headway for the first vehicle is determined based on the minimum time headway and a preset time headway corresponding to the first vehicle.

[0009] In this way, the safe braking distance can be calculated according to the target adhesion coefficient, and the minimum time distance between vehicles required for the braking process of the first vehicle can be accurately calculated according to the calculated braking distance and the actual measured speed of the first vehicle; and then, through the minimum time distance between vehicles and the preset time distance between vehicles, the reasonable target time distance between vehicles under the current driving state can be accurately determined.

[0010] In a possible implementation, when the preset time interval between workshops is less than the minimum time interval between workshops, the target time interval between workshops is determined based on the minimum time interval between workshops and a preset time interval increment; or, when the preset time interval between workshops is greater than or equal to the minimum time interval between workshops, the preset time interval between workshops is used as the target time interval between workshops.

[0011] In this way, when the preset time headway is less than the minimum time headway, by adjusting the preset time headway to the target time headway determined by the minimum time headway and the preset time headway increment, the time headway can be increased to a reasonable value, thereby improving the rationality of the time headway used and improving driving safety. When the preset time headway is greater than or equal to the minimum time headway, it can be said that driving according to the preset time headway can ensure driving safety on the current driving road surface. Therefore, the preset time headway can continue to be used as the target time headway to ensure driving safety.

[0012] In one possible implementation, a braking state corresponding to the first vehicle is monitored; when an anti-lock braking function corresponding to the first vehicle is triggered, a wheel slip rate of the first vehicle is determined based on an actual vehicle speed of the first vehicle and a wheel speed of the first vehicle.

[0013] In this way, since when the vehicle ABS function is triggered, it can be explained that the adhesion coefficient that the road surface can provide may be smaller and the vehicle driving risk is greater, when the vehicle ABS function is triggered, the second adhesion coefficient is determined in combination with the actual measured vehicle speed and wheel speed of the first vehicle in the actual driving state, which can improve the rationality and accuracy of the determined second adhesion coefficient and thus improve driving safety.

[0014] In a possible implementation, when the wheel slip rate is less than a preset slip rate, the average pressure corresponding to the wheel is determined based on the braking pressure values ​​of the wheel of the first vehicle collected at various historical moments; and the second adhesion coefficient is determined based on the average pressure and a preset braking efficiency corresponding to the first vehicle.

[0015] In this way, the wheel slip rate can reflect the wetness of the road surface, and the brake pressure values ​​collected at various historical moments can reflect the changes in the vehicle's brake pressure. The determined pressure average can better reflect the characteristics of the brake pressure values ​​at all moments. Finally, the pressure average and the preset braking efficiency can be used to determine a more accurate second adhesion coefficient.

[0016] In a possible implementation manner, the braking force of the wheel is determined according to the pressure mean, the preset braking efficiency, and the rolling radius of the wheel; and the second adhesion coefficient is determined according to the braking force and the wheel mass.

[0017] In this way, the braking force can more accurately reflect the adhesion coefficient, so a more accurate second adhesion coefficient can be determined using the determined braking force and wheel mass.

[0018] In a possible implementation, when the wheel slip rate is greater than or equal to the preset slip rate, a target slip rate interval corresponding to the wheel slip rate is determined from multiple first preset slip rate intervals; and a preset adhesion coefficient corresponding to the target slip rate interval is used as the second adhesion coefficient.

[0019] In a possible implementation manner, the confidence levels respectively corresponding to the first adhesion coefficient and the second adhesion coefficient are determined according to the following steps:

[0020] A first confidence level corresponding to the first adhesion coefficient is determined based on a road environment image collected in real time by the first vehicle; a second confidence level corresponding to the second adhesion coefficient is determined based on the wheel slip rate and a preset slip rate; and the first adhesion coefficient and the second adhesion coefficient are weighted based on the first confidence level and the second confidence level to obtain the target adhesion coefficient.

[0021] In this way, by determining the first confidence level and the second confidence level and performing weighted processing on the first adhesion coefficient and the second adhesion coefficient, a target adhesion coefficient that is more consistent with the confidence level can be obtained, thereby improving the rationality and accuracy of the determined target adhesion coefficient.

[0022] In a possible implementation manner, when the wheel slip rate is less than a preset slip rate, the second confidence level is determined according to the wheel slip rate and a first association relationship between each second preset slip rate interval and the first preset confidence level; or,

[0023] When the wheel slip rate is greater than or equal to the preset slip rate, the second confidence level is determined based on a second association relationship between each first preset slip rate interval and the second preset confidence level; wherein the second confidence level determined using the first association relationship is greater than the second confidence level determined using the second association relationship.

[0024] Here, when the magnitude relationship between the wheel slip ratio and the preset slip ratio is different, the rationality and accuracy of the determined second confidence level can be improved by using different association relationships to determine the second confidence level.

[0025] In one possible implementation, a first degree of slipperyness and a third confidence level corresponding to the driving road surface are determined based on the road environment image; a second degree of slipperyness and a fourth confidence level corresponding to the driving road surface are determined based on real-time weather data; a target degree of slipperyness corresponding to the driving road surface is determined based on the first degree of slipperyness, the third confidence level, the second degree of slipperyness, and the fourth confidence level; and the first adhesion coefficient is determined based on the target degree of slipperyness.

[0026] In this way, by combining real-time weather data and real road environment images to determine the road slipperiness, it is possible to determine the road slipperiness by combining multi-angle information, and then determine the first adhesion parameter under different road environments (such as different weather and different road conditions), thereby improving the rationality and accuracy of the determined first adhesion coefficient. Combined with the second adhesion coefficient, the road adhesion coefficient under different road environments and different driving conditions can be determined, further improving the rationality and accuracy of the determined first adhesion coefficient.

[0027] In a second aspect, an optional implementation of the present disclosure further provides a computer device, a processor, and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory, and when the machine-readable instructions are executed by the processor, the machine-readable instructions perform the steps in the above-mentioned first aspect, or any possible implementation of the first aspect.

[0028] In a third aspect, an optional implementation of the present disclosure further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed, the steps of the above-mentioned first aspect, or any possible implementation of the first aspect are executed.

[0029] In a fourth aspect, an optional implementation of the present disclosure further provides a vehicle, wherein the vehicle includes the computer device as described in the second aspect above.

[0030] In a fifth aspect, an optional implementation of the present disclosure further provides a computer program product, including a computer program, which, when executed, implements the method as described in the first aspect, or a method in any possible implementation described in the first method.

[0031] For a description of the effects of the above-mentioned computer device, computer-readable storage medium, vehicle and computer program product, please refer to the description of the above-mentioned vehicle headway determination method, which will not be repeated here.

[0032] In order to make the above-mentioned objectives, features and advantages of the present disclosure more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A flow chart of a method for determining time headway between vehicles provided by some embodiments of the present disclosure is shown;

[0034] Figure 2 A specific implementation flow chart of a method for determining time headway between vehicles provided in some embodiments of the present disclosure is shown;

[0035] Figure 3A schematic structural diagram of a computer device provided in some embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure more clear, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure.

[0037] To facilitate the understanding of the technical solution of the present disclosure, the technical terms in the embodiments of the present disclosure are first explained:

[0038] Assisted driving cruise function: A function that uses a camera and laser radar to detect the relative distance and relative speed to the vehicle in front, and controls the throttle and brakes of the vehicle to achieve stable following of the vehicle in front. When following the vehicle in front, the headway between vehicles set by the driver can be included. When there is no vehicle in front, the vehicle can be guaranteed to drive stably at the speed set by the driver;

[0039] Time headway between vehicles: used to characterize the distance between the ego vehicle and the target vehicle ahead, obtained by dividing the relative distance between the ego vehicle and the target vehicle ahead by the speed of the ego vehicle;

[0040] Anti-lock braking system: ABS for short, its function is to automatically control the braking force when the car brakes, so that the wheels are not locked and are in a state of rolling and sliding, so as to ensure that the adhesion between the wheels and the ground is at the maximum value;

[0041] Adhesion coefficient: It is the ratio of adhesion to the normal pressure of the wheel (direction perpendicular to the road surface).

[0042] After the assisted driving cruise function is activated, when there is a target vehicle in front of the ego vehicle that is traveling at a lower speed than the ego vehicle, the controller will control the vehicle to slow down to ensure that the ego vehicle can maintain the set time gap between vehicles and follow the target vehicle. However, in rainy and snowy weather, the road is slippery or even icy. At this time, when the controller requests the ego vehicle to slow down and brake, due to the low road adhesion coefficient, if the set time gap between vehicles is small and the vehicle is still following the vehicle according to the time gap between vehicles, there may be a risk of insufficient braking distance for the ego vehicle and rear-end collision with the vehicle in front due to the low available road adhesion coefficient, which reduces driving safety. If the time gap between the ego vehicle and the vehicle in front is set too large, it will cause the problem of frequent congestion of vehicles in adjacent lanes, affecting the driving experience. Therefore, how to reasonably adjust the time gap between vehicles in the following process to ensure driving safety and driving experience in the following process has become an issue worthy of attention.

[0043] To facilitate understanding of this embodiment, a method for determining the time interval between trains disclosed in an embodiment of the present disclosure is first introduced in detail. The execution subject of the method for determining the time interval between trains provided in an embodiment of the present disclosure is generally a terminal device or other processing device with certain computing capabilities, wherein the terminal device may be a user equipment (UE), a mobile device, a user terminal, a terminal, a personal digital assistant (PDA), a handheld device, a computer device, etc.; in some possible implementations, the method for determining the time interval between trains may be implemented by a processor calling computer-readable instructions stored in a memory.

[0044] The following describes the method for determining the time headway between vehicles provided by the embodiment of the present disclosure by taking a computer device as an example. Figure 1 As shown, it is a flow chart of a method for determining time headway between vehicles provided by an embodiment of the present disclosure, which may include the following steps:

[0045] S101: When a first vehicle follows a second vehicle, a first adhesion coefficient corresponding to a driving road surface is determined according to a road environment image acquired in real time by the first vehicle.

[0046] Here, the first vehicle may be a vehicle with an assisted driving cruise function turned on, which may be referred to as the self-vehicle. The second vehicle may be a vehicle traveling in front of the first vehicle and traveling in the same direction as the first vehicle, and the first vehicle may follow the second vehicle.

[0047] The road environment image may be an image captured in real time by a camera device disposed on the first vehicle, and may specifically include an image of the driving road, the road environment, and the vehicle surrounding environment. For example, the road environment image may be a road environment image captured by a front-view camera of the first vehicle. The driving road surface is the road surface of the road on which the first vehicle is driving. The first adhesion coefficient may be an adhesion coefficient determined by using the road environment image.

[0048] In specific implementation, at each moment when the first vehicle follows the second vehicle, the pre-trained neural network model can be used to perform image recognition on the road environment image collected by the first vehicle at that moment, and output the wetness of the road surface that the first vehicle is currently traveling on. Then, the adhesion coefficient corresponding to the road surface can be determined according to the wetness, and the adhesion coefficient is the first adhesion coefficient.

[0049] The degree of slipperiness can be determined based on the material and image features of the road surface obtained by performing image recognition on the road environment image, wherein the road material may include, for example, asphalt surface material, cement surface material, ice surface material, water surface material, soil surface material, etc.

[0050] S102: Determine the wheel slip rate of the first vehicle according to the measured vehicle speed and the wheel speed of the first vehicle, and determine a second adhesion coefficient corresponding to the driving road surface according to an adhesion coefficient determination method that matches the value of the wheel slip rate; different ranges of wheel slip rates correspond to different adhesion coefficient determination methods.

[0051] Here, the measured vehicle speed is the real vehicle speed of the first vehicle at the current moment, which can be calculated using the vehicle-mounted GPS system or the fusion positioning algorithm module. The wheel speed can be determined according to the driving mode of the first vehicle. When the first vehicle is in the rear-wheel drive mode, the wheel speed can be the rear wheel speed of the first vehicle at the current moment; when the first vehicle is in the front-wheel drive mode, the wheel speed can be the front wheel speed of the first vehicle at the current moment; when the first vehicle is in the four-wheel drive mode, the wheel speed can be the front wheel speed, rear wheel speed or average wheel speed of the first vehicle at the current moment.

[0052] When the tire exerts traction or braking force, relative movement occurs between the tire and the ground, and the wheel slip rate is used to characterize the proportion of the sliding component of the wheel in the wheel movement. When the value of the wheel slip rate is in different value ranges, different adhesion coefficient determination methods can be used. Specifically, multiple value ranges can be set in advance, and different value ranges correspond to different adhesion coefficient determination methods. According to the value range in which the wheel slip rate is located, a matching adhesion coefficient determination method can be determined. The adhesion coefficient determination method is a method for determining the road adhesion coefficient corresponding to the driving road surface. The number and size of the value ranges can be set based on experience, and the embodiments of the present disclosure do not specifically limit it.

[0053] The second adhesion coefficient is determined according to the wheel slip rate, and is used to reflect the adhesion coefficient that can be provided by the driving road surface when the first vehicle is in an actual driving state.

[0054] In specific implementation, the measured vehicle speed and wheel speed of the first vehicle can be obtained, and then the speed difference between the measured vehicle speed and the wheel speed of the first vehicle can be determined, and then the wheel slip rate of the first vehicle can be determined according to the ratio of the speed difference to the measured vehicle speed. After the wheel slip rate is obtained, the value range of the wheel slip rate can be determined according to the value of the wheel slip rate, and the adhesion coefficient determination method corresponding to the value range is used as the adhesion coefficient determination method to be used, and then the second adhesion coefficient corresponding to the driving road surface can be determined according to the adhesion coefficient determination method and the driving conditions of the vehicle (such as speed, vehicle mass, brake pressure, etc.).

[0055] In one embodiment, the value range may include two, one is a first value range less than a preset slip ratio, and the other is a second value range greater than the preset slip ratio, wherein the preset slip ratio may be set based on experience and is not specifically limited in the embodiment of the present disclosure. In this case, the step of "determining the second adhesion coefficient" in the above S102 may be implemented as follows:

[0056] S102-1: When the wheel slip rate is less than a preset slip rate, determine the pressure average corresponding to the wheel according to the brake pressure values ​​collected at various historical moments of the wheel of the first vehicle.

[0057] Here, when the comparison result of the wheel slip ratio and the preset slip ratio is different, it is determined that the wheel slip ratio belongs to a different value range, and the corresponding second adhesion coefficient to be used is determined in a different manner. The brake pressure value may be a value of a hydraulic brake pressure, and the historical moment may be set based on experience, for example, each historical moment in the past 3 seconds, each historical moment in the past 5 seconds, etc.

[0058] In specific implementation, after determining the wheel slip rate, it can be determined that the wheel slip rate is less than the preset slip rate. If so, it can be determined that the wheel slip rate corresponds to the first value range. Then, the second adhesion coefficient can be determined according to the adhesion coefficient determination method corresponding to the first value range, that is, first obtain the brake pressure values ​​of the wheels of the first vehicle collected at various historical moments. Here, the brake pressure value obtained can be the brake pressure value of the wheel used when collecting the wheel speed. For example, when the first vehicle is in rear-wheel drive mode, the brake pressure values ​​of the rear wheels of the first vehicle at various historical moments can be obtained; when the first vehicle is in front-wheel drive mode, the brake pressure values ​​of the front wheels of the first vehicle at various historical moments can be obtained.

[0059] After obtaining the brake pressure values ​​collected by the wheel at each historical moment, an average operation may be performed on the brake pressure values ​​at each moment to obtain the pressure averages corresponding to the wheel at multiple historical moments.

[0060] S102-2: Determine a second adhesion coefficient according to the pressure average and a preset braking efficiency corresponding to the first vehicle.

[0061] Here, the preset braking efficiency can be determined when the first vehicle leaves the scene, and is an inherent property of the vehicle. The efficiency can be expressed by a cost performance ratio (CP for short), and the preset braking efficiency is the preset braking CP value.

[0062] Exemplarily, after obtaining the pressure average, the braking distance of the first vehicle at the pressure average can be determined based on the pressure average and a preset braking efficiency, and the second adhesion coefficient of the driving road surface can be determined based on the braking distance and the mass of the vehicle.

[0063] In this way, the wheel slip rate can reflect the wetness of the road surface, and the brake pressure values ​​collected at various historical moments can reflect the changes in the vehicle's brake pressure. The determined pressure average can better reflect the characteristics of the brake pressure values ​​at all moments. Finally, based on the pressure average and the preset braking efficiency, a more accurate second adhesion coefficient can be determined.

[0064] In one embodiment, the above S102-2 may be implemented according to the following steps:

[0065] S102-2-1: Determine the braking force of the wheel based on the pressure average, the preset braking efficiency and the rolling radius of the wheel.

[0066] Here, the rolling radius of the wheel is the rolling radius corresponding to the wheel for which the brake pressure value is collected, and is also the rolling radius corresponding to the wheel for which the wheel speed is collected. The braking force can be the force when the wheel end generates deceleration.

[0067] Exemplarily, the product of the pressure average corresponding to the rear wheels of the first vehicle and the preset braking efficiency corresponding to the first vehicle can be determined, and the product is divided by the rolling radius corresponding to the rear wheels of the first vehicle to obtain the braking force of the rear wheel end of the first vehicle when deceleration occurs.

[0068] S102-2-2: Determine the second adhesion coefficient based on the braking force and the wheel mass.

[0069] In specific implementation, half of the wheel mass of the rear wheel of the first vehicle (ie, 1 / 2 of the wheel mass) may be determined first, and then the braking force may be divided by 1 / 2 of the wheel mass to obtain the second adhesion coefficient.

[0070] Alternatively, the wheel mass may be the mass of the wheel axle of the wheel where the wheel speed is collected, such as the rear wheel axle mass. In specific implementation, the braking force may be divided by 1 / 2 of the rear wheel axle mass to obtain the second adhesion coefficient.

[0071] In this way, the braking force can more accurately reflect the adhesion coefficient, so a more accurate second adhesion coefficient can be determined using the determined braking force and wheel mass.

[0072] In another embodiment, the step of "determining the second adhesion coefficient" in the above S102 can also be implemented according to the following steps: when the wheel slip rate is greater than or equal to the preset slip rate, a target slip rate interval corresponding to the wheel slip rate can be determined from multiple first preset slip rate intervals. Then, the preset adhesion coefficient corresponding to the target slip rate interval can be used as the second adhesion coefficient.

[0073] Here, the first preset slip rate interval may be a pre-calibrated slip rate interval, each first preset slip rate interval may be associated with a corresponding preset adhesion coefficient, different first preset slip rate intervals may be associated with different preset adhesion coefficients, and the preset adhesion coefficients associated with each first preset slip rate interval may also be pre-calibrated.

[0074] Exemplarily, when the wheel slip rate of the rear wheel is greater than or equal to the preset slip rate, it can be determined that the wheel slip rate belongs to the second value range, and then the second adhesion coefficient can be determined according to the adhesion coefficient determination method corresponding to the second value range, that is, multiple first preset slip rate intervals can be obtained, and the target slip rate interval into which the wheel slip rate falls can be determined according to the value of the wheel slip rate, and then the preset adhesion coefficient corresponding to the target slip rate interval can be used as the second adhesion coefficient corresponding to the driving road surface.

[0075] S103: Determine a target adhesion coefficient corresponding to the driving road surface according to the confidences corresponding to the first adhesion coefficient and the second adhesion coefficient respectively; the confidence corresponding to the first adhesion coefficient is related to the image content quality of the road environment image, and the confidence corresponding to the second adhesion coefficient is related to the value of the wheel slip rate.

[0076] Here, the target adhesion coefficient is the adhesion coefficient corresponding to the driving road surface determined at the current moment, and is a road surface adhesion coefficient finally determined. The target adhesion coefficient is used to adjust the inter-vehicle time distance of the first vehicle.

[0077] The first adhesion coefficient and the second adhesion coefficient may both have a corresponding confidence level. The confidence level of the first adhesion coefficient is related to the image content quality of the road environment image. The higher the image content quality, the higher the recognition accuracy, and the higher the confidence level. The confidence level corresponding to the second adhesion coefficient is related to the value of the wheel slip rate. The larger the value of the wheel slip rate, the smaller the confidence level. Both the confidence level of the first adhesion coefficient and the confidence level of the second adhesion coefficient can be determined synchronously when determining the adhesion coefficient.

[0078] In a specific implementation, after obtaining the first adhesion coefficient, the second adhesion coefficient and the confidences of the two adhesion coefficients, an adhesion coefficient with a larger corresponding confidence can be selected as the target adhesion coefficient. Alternatively, when the confidences of the two adhesion coefficients are not greater than the preset confidences, the minimum adhesion coefficient of the first adhesion coefficient and the second adhesion coefficient can be used as the target adhesion coefficient. Alternatively, different weighted weights can be set for the first adhesion coefficient and the second adhesion coefficient respectively according to the confidence of the first adhesion coefficient and the confidence of the second adhesion coefficient, and then the first adhesion coefficient and the second adhesion coefficient are weighted by using the weighted weight corresponding to the first adhesion coefficient and the weighted weight corresponding to the second adhesion coefficient to obtain the target adhesion coefficient.

[0079] In one embodiment, the confidence levels corresponding to the first adhesion coefficient and the second adhesion coefficient respectively may be determined according to the following steps:

[0080] For the first adhesion coefficient, a first confidence level corresponding to the first adhesion coefficient may be determined according to a road environment image collected in real time by the first vehicle.

[0081] Here, the first confidence level is the confidence level corresponding to the first adhesion coefficient. In specific implementation, a pre-trained neural network model can be used to perform image recognition processing on the road environment image collected in real time by the first vehicle, and then when outputting the wetness of the road surface, the confidence level of the wetness is output at the same time. Then, the first adhesion coefficient can be determined according to the output wetness, and the confidence level of the wetness is used as the confidence level of the first adhesion coefficient.

[0082] Optionally, the neural network model may also directly output the first adhesion coefficient and the confidence level corresponding to the first adhesion coefficient according to the road environment image, and the confidence level may be used as the first confidence level.

[0083] For the second adhesion coefficient, a second confidence level corresponding to the second adhesion coefficient may be determined according to the wheel slip rate and a preset slip rate.

[0084] Here, the second confidence level can represent the confidence level corresponding to the second adhesion coefficient. In specific implementation, the determination result of the second confidence level can be determined according to the comparison result between the wheel slip rate and the preset slip rate.

[0085] Specifically, when the wheel slip rate is less than the preset slip rate, the second confidence level may be determined according to the wheel slip rate and a first correlation relationship between each second preset slip rate interval and the first preset confidence level.

[0086] Here, the first association relationship is used to indicate the first preset reliability associated with each second preset slip rate interval. Different second preset slip rate intervals are associated with different first preset reliability. Each second preset slip rate interval can be pre-calibrated, and the first association relationship corresponding to each second preset slip rate interval can also be pre-calibrated.

[0087] In specific implementation, when the wheel slip rate is less than the preset slip rate, each second preset slip rate interval and its corresponding first association relationship can be obtained, and then the target second preset slip rate interval into which the wheel slip rate falls can be determined, and then the first preset confidence level indicated by the first association relationship corresponding to the target second preset slip rate interval can be used as the second confidence level of the second adhesion coefficient.

[0088] On the contrary, when the wheel slip rate is greater than or equal to the preset slip rate, the second confidence level can be determined based on the second correlation relationship between each first preset slip rate interval and the second preset confidence level; wherein the second confidence level determined using the first correlation relationship is greater than the second confidence level determined using the second correlation relationship.

[0089] Here, the second association relationship is used to indicate the second preset reliability associated with each first preset slip rate interval. Different first preset slip rate intervals are associated with different second preset reliability. Each first preset slip rate interval can be pre-calibrated, and the second association relationship corresponding to each first preset slip rate interval can also be pre-calibrated.

[0090] The first preset slip rate interval and the second preset slip rate interval may be the same or different. When the first preset slip rate interval and the second preset slip rate interval are the same, the second preset confidence indicated by the second association relationship of the first preset slip rate interval is less than the first preset confidence indicated by the first association relationship of the second preset slip rate interval. Regardless of whether the first preset slip rate interval and the second preset slip rate interval are the same, the second confidence determined by using the first association relationship will be greater than the second confidence determined by using the second association relationship. That is, the second confidence determined when the wheel slip rate is less than the preset slip rate is greater than the second confidence determined when the wheel slip rate is not less than the preset slip rate.

[0091] In specific implementation, when the wheel slip rate is greater than or equal to the preset slip rate, each first preset slip rate interval and its corresponding second association relationship can be obtained, and then the target slip rate interval into which the wheel slip rate falls can be determined, and the second preset confidence indicated by the second association relationship corresponding to the target slip rate interval is used as the second confidence.

[0092] Exemplarily, the wheel slip rate of the rear wheel can be determined according to the measured vehicle speed of the first vehicle and the wheel speed of the rear wheel. When the wheel slip rate is less than the preset slip rate, the second adhesion coefficient can be determined according to the pressure mean, the preset braking efficiency, the rolling radius of the rear wheel and the wheel mass of the rear wheel, and at the same time, the first preset confidence corresponding to the target second preset slip rate interval in which the wheel slip rate falls can be used as the second confidence corresponding to the second adhesion coefficient.

[0093] When the wheel slip rate of the rear wheel is greater than or equal to less than the preset slip rate, the target slip rate interval into which the wheel slip rate falls can be determined from multiple first preset slip rate intervals, the preset adhesion coefficient corresponding to the target slip rate interval is used as the second adhesion coefficient, and the first preset confidence level corresponding to the target slip rate interval is used as the second confidence level corresponding to the second adhesion coefficient.

[0094] Further, after the first confidence level and the second confidence level are determined, the above S103 may be implemented according to the following steps:

[0095] The first adhesion coefficient and the second adhesion coefficient are weighted according to the first confidence level and the second confidence level to obtain a target adhesion coefficient.

[0096] For example, the first weighted weight corresponding to the first confidence level may be used to perform weighted processing on the first adhesion coefficient to obtain the first weighted coefficient, and the second weighted weight corresponding to the second confidence level may be used to perform weighted processing on the second adhesion coefficient to obtain the second weighted coefficient, and the sum of the first weighted coefficient and the second weighted coefficient may be used as the target adhesion coefficient, or the mean of the first weighted coefficient and the second weighted coefficient may be used as the target adhesion coefficient, or the minimum value of the first weighted coefficient and the second weighted coefficient may be used as the target adhesion coefficient. The weighted weights corresponding to different confidence levels may be pre-calibrated.

[0097] In this way, by determining the first confidence level and the second confidence level and performing weighted processing on the first adhesion coefficient and the second adhesion coefficient, a target adhesion coefficient that is more consistent with the confidence level can be obtained, thereby improving the rationality and accuracy of the determined target adhesion coefficient.

[0098] S104: Determine a target time headway between vehicles of the first vehicle according to the target adhesion coefficient and the measured vehicle speed, and control the first vehicle to travel according to the target time headway between vehicles.

[0099] Here, the target time headway between vehicles is the time headway between vehicles determined when driving on the current driving road surface. Driving safety can be improved by following the second vehicle on the current driving road surface according to the target time headway between vehicles.

[0100] In specific implementation, for the first vehicle, after determining the target adhesion coefficient, the relative speed between the first vehicle and the second vehicle can be determined according to the measured speed of the first vehicle and the measured speed of the second vehicle collected by the sensor. Then, the first braking distance of the first vehicle can be determined according to the target adhesion coefficient and the measured speed of the first vehicle, and then the second braking distance can be determined according to the relative speed and the target adhesion coefficient. The target time headway between vehicles can be determined according to the first braking distance and the second braking distance, and then the first vehicle can be controlled to follow the second vehicle according to the target time headway between vehicles.

[0101] In this way, during the following driving of the first vehicle, the first adhesion coefficient corresponding to the driving road surface can be predicted more accurately by using the road environment image; at the same time, the wheel slip rate can be accurately calculated according to the actual driving data of the first vehicle (such as the measured vehicle speed and wheel speed). According to the value of the wheel slip rate, different adhesion coefficient determination methods are used to determine the adhesion coefficient, which can improve the rationality of the determined second adhesion coefficient and more accurately calculate the second adhesion coefficient that the driving road surface can provide for the first vehicle in the current driving state. Then, by combining the first adhesion coefficient and the second adhesion coefficient and the corresponding confidence levels of the two, the real target adhesion coefficient that the driving road surface can provide can be accurately calculated. The target adhesion coefficient and the measured vehicle speed can be used to accurately determine the safe target time headway of the first vehicle when following the vehicle on the current driving road surface. By controlling the first vehicle to drive according to the target time headway, it can be ensured that there is a sufficient safe braking distance between the first vehicle and the following second vehicle, avoiding the occurrence of rear-end collision, and improving driving safety.

[0102] In one embodiment, the above S104 can be implemented according to the following steps:

[0103] S104-1: Determine a braking distance corresponding to the first vehicle according to a relative speed and a target adhesion coefficient between the first vehicle and the second vehicle; the second vehicle travels in front of the first vehicle and in the same direction as the first vehicle.

[0104] Here, the first vehicle and the second vehicle are two vehicles traveling in the same direction on the same road, and the second vehicle travels in front of the first vehicle.

[0105] During specific implementation, the minimum safe braking distance for avoiding collision between the first vehicle and the second vehicle may be determined according to the relative speed and the target adhesion coefficient.

[0106] S104-2: Determine the minimum inter-vehicle time required for the braking process of the first vehicle based on the braking distance and the measured vehicle speed of the first vehicle.

[0107] Here, the minimum time distance between vehicles can be understood as the time distance between vehicles that can ensure that the first vehicle can also stop safely when the second vehicle brakes when the road surface provides the target adhesion coefficient. At this time distance between vehicles, the first vehicle will not collide with the second vehicle when braking.

[0108] In specific implementation, the braking distance may be divided by the actually measured vehicle speed of the first vehicle, and the obtained value may be used as the minimum vehicle-to-vehicle time distance required for the braking process of the first vehicle.

[0109] S104-3: Determine a target time headway for the first vehicle according to the minimum time headway for the first vehicle and a preset time headway for the first vehicle.

[0110] Here, the preset vehicle-to-vehicle time interval can be set independently by the driver when the assisted driving cruise function is turned on.

[0111] Exemplarily, the minimum time headway between two vehicles and the preset time headway between two vehicles may be compared, and the target time headway between two vehicles may be determined based on the comparison result and the minimum time headway between two vehicles and the preset time headway between two vehicles.

[0112] Specifically, for the above S104-3, the target headway time may be determined as follows:

[0113] Method 1: When the preset time interval between workshops is less than the minimum time interval between workshops, the target time interval between workshops is determined according to the minimum time interval between workshops and the preset time interval increment.

[0114] Here, the preset time interval increment can be set based on experience, and the embodiment of the present disclosure does not make any specific limitation. The purpose of setting the preset time interval increment is to prevent the problem of affecting driving safety due to the direct use of the determined minimum time interval between vehicles which is not accurate enough. The setting of the preset time interval increment can improve the robustness of the time interval adjustment between vehicles and further ensure driving safety.

[0115] Exemplarily, when the preset time headway corresponding to the first vehicle is less than the minimum time headway, the sum of the minimum time headway and the preset time headway increment may be used as the target time headway.

[0116] In this way, when the preset time interval between vehicles is less than the minimum time interval between vehicles, by adjusting the preset time interval between vehicles to the target time interval between vehicles determined by the minimum time interval between vehicles and the preset time interval increment, the time interval between vehicles can be increased to a reasonable value, thereby improving the rationality of the time interval used and improving driving safety.

[0117] Method 2: When the preset inter-vehicle time distance is greater than or equal to the minimum inter-vehicle time distance, the preset inter-vehicle time distance is used as the target inter-vehicle time distance.

[0118] Here, when the preset time interval between vehicles is greater than or equal to the minimum time interval between vehicles, it can be said that driving according to the preset time interval between vehicles can ensure driving safety under the current driving road surface. Therefore, the preset time interval between vehicles can continue to be used as the target time interval between vehicles to ensure driving safety.

[0119] Method three: when the preset workshop time interval is greater than or equal to the minimum workshop time interval, the average of the preset workshop time interval and the minimum workshop time interval can be used as the target workshop time interval; or when the preset workshop time interval is greater than the minimum workshop time interval, any value greater than the minimum workshop time interval and less than the preset workshop time interval can be used as the target workshop time interval.

[0120] In this way, when the first vehicle is following the vehicle, the target adhesion coefficient of the current road surface is estimated in real time by integrating the slippery road surface output by the visual perception algorithm and the real-time weather data provided by the Internet of Vehicles, combined with the motion data (such as the measured vehicle speed, wheel speed, pressure average, etc.) provided by the vehicle chassis during actual driving. According to the calculated target adhesion coefficient, the target time distance between the vehicle and the vehicle ahead is dynamically adjusted, which improves the driving experience while avoiding the safety problem of rear-end collision caused by insufficient braking distance.

[0121] In one embodiment, before executing S102, the braking state corresponding to the first vehicle may also be monitored. Here, the braking state is used to indicate whether the anti-lock braking function (ABS function) of the first vehicle is triggered. When it is detected that the braking state indicates that the anti-lock braking function corresponding to the first vehicle is triggered, the wheel slip rate of the first vehicle may be determined according to the measured vehicle speed of the first vehicle and the wheel speed of the first vehicle. That is, when the anti-lock braking function corresponding to the first vehicle is triggered, S102 may be executed.

[0122] For example, the braking state corresponding to the first vehicle can be monitored in real time, and then it can be determined whether the ABS function corresponding to the first vehicle is triggered according to the braking state. If not, it can be explained that the driving road surface currently provides sufficient adhesion coefficients, and driving according to the preset vehicle headway can ensure the driving safety of the first vehicle. At this time, the first adhesion coefficient can be directly used as the target adhesion coefficient. If yes, that is, when the ABS function corresponding to the first vehicle is triggered and the auxiliary driving cruise function is always turned on, the measured speed of the first vehicle and the wheel speed of the first vehicle can be obtained, and then, the second adhesion coefficient corresponding to the driving road surface can be determined according to the measured speed and wheel speed of the first vehicle.

[0123] In this way, since when the vehicle ABS function is triggered, it can be shown that the adhesion coefficient that the road surface can provide may be small and the vehicle driving risk is greater, when the vehicle ABS function is triggered, the second adhesion coefficient is determined in combination with the actual measured vehicle speed and wheel speed of the first vehicle in the actual driving state, which can improve the rationality and accuracy of the determined second adhesion coefficient, thereby improving driving safety.

[0124] Optionally, in a specific implementation, regardless of whether the ABS function corresponding to the first vehicle is triggered, the measured vehicle speed and wheel speed of the first vehicle can be used to determine the second adhesion coefficient corresponding to the driving road surface, and then the target adhesion coefficient can be determined in combination with the second adhesion coefficient.

[0125] In an embodiment, in order to further improve the accuracy of the determined first adhesion coefficient, the step of determining the first adhesion coefficient in S101 above may also be implemented according to the following steps:

[0126] S101 - 1 : Determine a first slippery degree and a third confidence level corresponding to a driving road surface according to a road environment image.

[0127] Here, the third confidence level may be the confidence level corresponding to the first slippery degree.

[0128] In specific implementation, the visual algorithm perception module of the first vehicle can be used to perform image recognition on the road environment image using the deployed neural network model, and output the first degree of slipperiness of the road surface on which the first vehicle is currently traveling, as well as the confidence level corresponding to the first degree of slipperiness (i.e., the third confidence level).

[0129] S101 - 2: Determine a second slippery degree and a fourth confidence level corresponding to the driving road surface according to the real-time weather data.

[0130] Here, the fourth confidence level may be the confidence level corresponding to the second slippery degree.

[0131] In specific implementation, real-time weather data corresponding to the current position of the first vehicle can be obtained through the Internet of Vehicles corresponding to the first vehicle. Then, the second degree of slipperyness corresponding to the driving road surface can be predicted using the real-time weather data, and the fourth confidence level corresponding to the second degree of slipperyness can be determined using the pre-calibrated correlation between the second degree of slipperyness and the confidence level.

[0132] S101 - 3 : Determine a target slippery degree corresponding to the driving road surface according to the first slippery degree, the third confidence level, the second slippery degree and the fourth confidence level.

[0133] In specific implementation, the first slippery degree may be weighted by using the weighted weight corresponding to the third confidence level to obtain the third slippery degree; meanwhile, the second slippery degree may be weighted by using the weighted weight corresponding to the fourth confidence level to obtain the fourth slippery degree. Then, the sum / average of the third slippery degree and the fourth slippery degree may be used as the target slippery degree.

[0134] S101-4: Determine a first adhesion coefficient according to a target slippery degree.

[0135] In a specific implementation, the first adhesion coefficient corresponding to the target slippery degree may be determined according to the corresponding relationship between the target slippery degree and the adhesion coefficient.

[0136] It is understandable that after obtaining the third confidence level and the fourth confidence level, the first confidence level corresponding to the first adhesion coefficient can be determined according to the third confidence level and the fourth confidence level. For example, the average of the third confidence level and the fourth confidence level can be used as the first confidence level, or the minimum of the third confidence level and the fourth confidence level can be used as the first confidence level, or the confidence level corresponding to the maximum slippery level of the first slippery level and the second slippery level can be used as the first confidence level.

[0137] In this way, by combining the real-time weather data and the real road environment image to determine the road slipperiness, it is possible to determine the road slipperiness by combining multi-angle information, and then determine the first adhesion parameter under different road environments (such as different weather and different road conditions), thereby improving the rationality and accuracy of the determined first adhesion coefficient. Combined with the second adhesion coefficient, the road surface adhesion coefficient under different road environments and different driving conditions can be determined, further improving the rationality and accuracy of the determined first adhesion coefficient. In addition, by combining the real-time weather data and the real road environment image to determine the first confidence, the rationality and accuracy of the determined first confidence can also be improved.

[0138] like Figure 2 As shown, a specific implementation flow chart of a method for determining time headway between vehicles provided by an embodiment of the present disclosure may include the following steps:

[0139] S201: When a first vehicle follows a second vehicle, a first slippery degree and a third confidence level corresponding to a driving road surface are determined according to a road environment image acquired in real time by the first vehicle.

[0140] S202: Determine a second slippery degree and a fourth confidence level corresponding to the driving road surface according to the real-time weather data.

[0141] S203: Determine a target slippery degree corresponding to the driving road surface according to the first slippery degree, the third confidence level, the second slippery degree and the fourth confidence level.

[0142] S204: determining a first adhesion coefficient according to the target slippery degree, and determining a first confidence level corresponding to the first adhesion coefficient according to the third confidence level and the fourth confidence level.

[0143] S205: When the ABS function corresponding to the first vehicle is triggered, determine the wheel slip rate of the first vehicle according to the measured vehicle speed of the first vehicle and the rear wheel speed of the first vehicle.

[0144] S206: Determine whether the wheel slip rate is less than a preset slip rate.

[0145] If yes, execute the following S207 to S209; if no, execute the following S210.

[0146] S207: Determine a pressure average corresponding to the rear wheels according to the brake pressure values ​​of the rear wheels of the first vehicle collected at various historical moments.

[0147] S208: Determine the braking force of the rear wheels according to the pressure average, the preset braking efficiency and the rolling radius of the rear wheels.

[0148] S209: determining a second adhesion coefficient according to the braking force and the rear wheel mass, and determining a second confidence level corresponding to the second adhesion coefficient according to the wheel slip rate and a first correlation relationship between each second preset slip rate interval and the first preset confidence level.

[0149] After executing S209, the following S211 may be continued to be executed.

[0150] S210: Determine a target slip rate interval corresponding to the wheel slip rate from multiple first preset slip rate intervals, and use the preset adhesion coefficient corresponding to the target slip rate interval as the second adhesion coefficient, and use the second preset confidence corresponding to the target slip rate interval as the second confidence corresponding to the second adhesion coefficient.

[0151] After executing S210, the following S211 may be continued to be executed.

[0152] S211: performing weighted processing on the first adhesion coefficient and the second adhesion coefficient according to the first confidence level and the second confidence level to obtain a target adhesion coefficient.

[0153] S212: Determine a target time headway between the first vehicle and the second vehicle according to the relative speed between the first vehicle and the second vehicle, the target adhesion coefficient, and the measured vehicle speed of the first vehicle, and control the first vehicle to travel according to the target time headway between the first vehicle and the second vehicle.

[0154] By using the above method, when the first vehicle is following the vehicle, the first adhesion coefficient corresponding to the driving road surface can be predicted more accurately by using the road environment image; at the same time, the wheel slip rate can be accurately calculated according to the actual driving data of the first vehicle (such as the measured vehicle speed and wheel speed). According to the value of the wheel slip rate, different adhesion coefficient determination methods are used to determine the adhesion coefficient, which can improve the rationality of the determined second adhesion coefficient and more accurately calculate the second adhesion coefficient that the driving road surface can provide for the first vehicle in the current driving state. Then, by combining the first adhesion coefficient and the second adhesion coefficient and the corresponding confidence of the two, the real target adhesion coefficient that the driving road surface can provide can be accurately calculated. The target adhesion coefficient and the measured vehicle speed can be used to accurately determine the safe target time headway of the first vehicle when following the vehicle on the current driving road surface. By controlling the first vehicle to travel according to the target time headway, it can be ensured that there is a sufficient safe braking distance between the first vehicle and the following second vehicle, avoiding the occurrence of rear-end collision, and improving driving safety.

[0155] Regarding the specific implementation steps of S201 to S212 above, reference may be made to the above embodiments and will not be repeated here.

[0156] Those skilled in the art will appreciate that, in the above method of specific implementation, the order in which the steps are written does not imply a strict execution order and does not constitute any limitation on the implementation process. The specific execution order of the steps should be determined by their functions and possible internal logic.

[0157] Based on the same technical concept, the embodiment of the present application also provides a computer device. Figure 3 FIG. 1 is a schematic diagram of a computer device provided in an embodiment of the present application, including:

[0158] Processor 301, memory 302 and bus 303. The memory 302 stores machine-readable instructions executable by the processor 301, and the processor 301 is used to execute the machine-readable instructions stored in the memory 302. When the machine-readable instructions are executed by the processor 301, the processor 301 performs the following steps: S101: in the process of the first vehicle following the second vehicle, according to the road environment image collected in real time by the first vehicle, determine the first adhesion coefficient corresponding to the driving road surface; S102: according to the measured vehicle speed of the first vehicle and the wheel speed of the first vehicle, determine the wheel slip rate of the first vehicle, and according to the attachment coefficient matching the value of the wheel slip rate; The method for determining the adhesion coefficient is used to determine the second adhesion coefficient corresponding to the driving road surface; the value range of the wheel slip rate is different, and the corresponding adhesion coefficient determination method is different; S103: according to the confidence levels corresponding to the first adhesion coefficient and the second adhesion coefficient, the target adhesion coefficient corresponding to the driving road surface is determined; the confidence level corresponding to the first adhesion coefficient is related to the image content quality of the road environment image, and the confidence level corresponding to the second adhesion coefficient is related to the value of the wheel slip rate; and S104: according to the target adhesion coefficient and the measured vehicle speed, the target time interval between the first vehicle and the vehicle is determined, and the first vehicle is controlled to travel according to the target time interval between the first vehicle and the vehicle.

[0159] The above-mentioned memory 302 includes internal memory 3021 and external memory 3022; the memory 3021 here is also called internal memory, which is used to temporarily store the calculation data in the processor 301, as well as the data exchanged with the external memory 3022 such as a hard disk. The processor 301 exchanges data with the external memory 3022 through the internal memory 3021. When the computer device is running, the processor 301 communicates with the memory 302 through the bus 303, so that the processor 301 executes the execution instructions mentioned in the above-mentioned method embodiment.

[0160] The embodiment of the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the vehicle headway determination method described in the above method embodiment are executed. The storage medium can be a volatile or non-volatile computer-readable storage medium.

[0161] The embodiment of the present disclosure also provides a schematic diagram of a vehicle, which includes the computer device in the above embodiment.

[0162] The computer program product of the method for determining the time headway between vehicles provided in the embodiments of the present disclosure includes a computer-readable storage medium storing program code, and the instructions included in the program code can be used to execute the steps of the method for determining the time headway between vehicles described in the above method embodiments. For details, please refer to the above method embodiments, which will not be repeated here.

[0163] The computer program product may be implemented in hardware, software or a combination thereof. In one optional embodiment, the computer program product is embodied as a computer storage medium, and in another optional embodiment, the computer program product is embodied as a software product, such as a software development kit (SDK) and the like.

[0164] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, the specific working process of the vehicle described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here. In the several embodiments provided in the present disclosure, it should be understood that the disclosed vehicle and method can be implemented in other ways. The embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the units can be electrical, mechanical or other forms.

[0165] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0166] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0167] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present disclosure, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present disclosure. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0168] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present disclosure, which are used to illustrate the technical solutions of the present disclosure, rather than to limit them. The protection scope of the present disclosure is not limited thereto. Although the present disclosure is described in detail with reference to the above-described embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-described embodiments within the technical scope disclosed in the present disclosure, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present disclosure, and should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for determining time headway between vehicles, characterized in that: include: In the process of the first vehicle following the second vehicle, determining a first adhesion coefficient corresponding to the driving road surface according to the road environment image collected in real time by the first vehicle; Determining the wheel slip ratio of the first vehicle according to the measured vehicle speed of the first vehicle and the wheel speed of the first vehicle, and determining the second adhesion coefficient corresponding to the driving road surface according to an adhesion coefficient determination method that matches the value of the wheel slip ratio; different values ​​of the wheel slip ratio have different corresponding adhesion coefficient determination methods; determining a target adhesion coefficient corresponding to the driving road surface according to the confidences corresponding to the first adhesion coefficient and the second adhesion coefficient respectively; the confidence corresponding to the first adhesion coefficient is related to the image content quality of the road environment image, and the confidence corresponding to the second adhesion coefficient is related to the value of the wheel slip rate; A target time interval between vehicles of the first vehicle is determined according to the target adhesion coefficient and the measured vehicle speed, and the first vehicle is controlled to travel according to the target time interval between vehicles.

2. The method according to claim 1, characterized in that: The determining, according to the target adhesion coefficient and the measured vehicle speed, a target inter-vehicle time headway of the first vehicle comprises: determining a braking distance corresponding to the first vehicle according to a relative speed between the first vehicle and the second vehicle and the target adhesion coefficient; the second vehicle travels in front of the first vehicle and in the same direction as the first vehicle; Determining a minimum headway time required for a braking process of the first vehicle according to the braking distance and the measured vehicle speed of the first vehicle; A target time headway for the first vehicle is determined according to the minimum time headway between vehicles and a preset time headway between vehicles corresponding to the first vehicle.

3. The method according to claim 2, characterized in that The determining, according to the minimum time headway between vehicles and a preset time headway between vehicles corresponding to the first vehicle, a target time headway between vehicles of the first vehicle includes: In the case where the preset time headway between vehicles is less than the minimum time headway between vehicles, determining the target time headway between vehicles according to the minimum time headway between vehicles and the preset time headway increment; or When the preset time headway between vehicles is greater than or equal to the minimum time headway between vehicles, the preset time headway between vehicles is used as the target time headway between vehicles.

4. The method according to claim 1, characterized in that Determining a wheel slip rate of the first vehicle according to the measured vehicle speed of the first vehicle and the wheel speed of the first vehicle includes: monitoring a braking state corresponding to the first vehicle; When the anti-lock braking function corresponding to the first vehicle is triggered, the wheel slip rate of the first vehicle is determined according to the measured vehicle speed of the first vehicle and the wheel speed of the first vehicle.

5. The method according to claim 1, characterized in that Determining a second adhesion coefficient corresponding to the driving road surface according to an adhesion coefficient determination method that matches the value of the wheel slip rate includes: When the wheel slip rate is less than a preset slip rate, determining a pressure average corresponding to the wheel according to the brake pressure values ​​collected at various historical moments of the wheel of the first vehicle; The second adhesion coefficient is determined according to the pressure average and a preset braking efficiency corresponding to the first vehicle.

6. The method according to claim 5, characterized in that The determining the second adhesion coefficient according to the pressure average and a preset braking efficiency corresponding to the first vehicle includes: determining the braking force of the wheel according to the pressure average, the preset braking efficiency and the rolling radius of the wheel; The second adhesion coefficient is determined according to the braking force and the wheel mass.

7. The method according to claim 5, characterized in that Determining a second adhesion coefficient corresponding to the driving road surface according to an adhesion coefficient determination method that matches the value of the wheel slip rate includes: When the wheel slip rate is greater than or equal to the preset slip rate, determining a target slip rate interval corresponding to the wheel slip rate from a plurality of first preset slip rate intervals; The preset adhesion coefficient corresponding to the target slip ratio interval is used as the second adhesion coefficient.

8. The method according to claim 1, characterized in that The confidence levels corresponding to the first adhesion coefficient and the second adhesion coefficient are determined according to the following steps: Determining a first confidence level corresponding to the first adhesion coefficient according to a road environment image collected in real time by the first vehicle; determining a second confidence level corresponding to the second adhesion coefficient according to the wheel slip rate and a preset slip rate; The step of determining a target adhesion coefficient corresponding to the driving road surface according to the confidences respectively corresponding to the first adhesion coefficient and the second adhesion coefficient includes: The first adhesion coefficient and the second adhesion coefficient are weighted according to the first confidence level and the second confidence level to obtain the target adhesion coefficient.

9. The method according to claim 8, characterized in that The determining, according to the wheel slip rate and the preset slip rate, a second confidence level corresponding to the second adhesion coefficient includes: When the wheel slip rate is less than a preset slip rate, the second confidence level is determined according to the wheel slip rate and a first correlation relationship between each second preset slip rate interval and the first preset confidence level; or, When the wheel slip rate is greater than or equal to the preset slip rate, the second confidence level is determined based on a second association relationship between each first preset slip rate interval and the second preset confidence level; wherein the second confidence level determined using the first association relationship is greater than the second confidence level determined using the second association relationship.

10. The method according to claim 1, characterized in that The determining, based on the road environment image and the real-time weather data collected in real time by the first vehicle, a first adhesion coefficient corresponding to the driving road surface comprises: determining, according to the road environment image, a first slippery degree and a third confidence level corresponding to the driving road surface; determining, according to the real-time weather data, a second slippery degree and a fourth confidence level corresponding to the driving road surface; determining a target slippery degree corresponding to the driving road surface according to the first slippery degree, the third confidence level, the second slippery degree, and the fourth confidence level; The first adhesion coefficient is determined according to the target slippery degree.

11. A computer device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and the processor is used to execute the machine-readable instructions stored in the memory. When the machine-readable instructions are executed by the processor, the processor executes the steps of the method for determining the time headway between vehicles as described in any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program. When the computer program is executed by a computer device, the computer device executes the steps of the method for determining time headway between vehicles according to any one of claims 1 to 10.

13. A vehicle, characterized in that: The vehicle comprises the computer device of claim 11.

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