STATE INDICATOR DETECTION DEVICE

Abstract

An indication that a stuck condition is about to occur is appropriately detected. A stuck condition indication detection device (2) comprises: a computation section (201) configured to compare a first wheel speed of a drive wheel with a second wheel speed, which is an average of the drive wheel's wheel speed, in order to calculate a deviation-related value regarding any deviation of the first wheel speed from the second wheel speed; and a stuck condition determination section (202) configured to determine a probability that the vehicle will become stuck in a case where (i) the deviation-related value is not less than a predetermined threshold and (ii) an acceleration request has been generated in the vehicle.

Description

Technical field

[0001] The present disclosure relates to a stuck-state indication detection device. State of the art

[0002] Patent literature 1 discloses a jamming state detection device which, upon detecting a state in which the rotational speed of an electric motor driving wheels is less than a jamming state determination speed defined according to the rotational speeds of main drive wheels for a period of not less than a set time, determines that the main drive wheels are in a jamming state in which the main drive wheels are idling. Citation list [patent literature]

[0003] [Patent Literature 1] Japanese patent application, Tokukai, No. 2006-230130 Summary of the invention: Technical problem

[0004] Patent literature 1 describes the determination of whether the drive wheels have become stuck or not. However, given the serious impact that a vehicle stuck due to sudden heavy snowfall or similar events has on traffic conditions, there is a need for a technology that, by detecting an indication that a stuck condition is about to occur, enables the prevention of the stuck condition itself. However, there is still room for improvement regarding the detection of an indication that a stuck condition is about to occur.

[0005] One function of an aspect of the present disclosure is to adequately capture indications that a stuck condition will occur by appropriately determining a probability of the stuck condition occurring. Solution to the problem

[0006] To achieve the task, a stuck-state detection device according to one aspect of the present disclosure comprises: a computation section configured to compare a first wheel speed with a second wheel speed in order to calculate a deviation-related value regarding a deviation of the first wheel speed relative to the second wheel speed, wherein the first wheel speed is a wheel speed of a drive wheel of a vehicle and the second wheel speed is an average value of the wheel speed of the drive wheel; and a stuck-state determination section configured to determine a probability that the vehicle will become stuck in a case where (i) it has been determined that the deviation-related value is not less than a predetermined threshold, and (ii) an acceleration request has been generated in the vehicle.

[0007] A stuck-state indicator detection device according to any aspect of the present disclosure can be implemented by a computer. In such a case, the present disclosure comprises (i) a control program of the stuck-state indicator detection device, wherein the control program of the computer causes the sections (software elements) contained in the stuck-state indicator detection device to serve as the stuck-state indicator detection device, and (ii) a computer-readable storage medium on which the control program is stored. Advantageous effects of the invention

[0008] One aspect of the present disclosure makes it possible to adequately determine the probability of a stuck condition occurring. Brief description of the drawings Fig. Figure 1 is a configuration diagram of a stuck-state indicator detection system comprising a stuck-state indicator detection device according to an embodiment of the present disclosure. Fig. Figure 2 is a diagram illustrating an example configuration of a stuck-state indicator detection device according to an embodiment of the present disclosure. Fig. Figure 3 is a diagram illustrating an example configuration of a stuck-state indicator detection device according to an embodiment of the present disclosure. Fig. Figure 4 is a diagram used to describe a vehicle stuck in a jammed state. Fig. Figure 5 is a flowchart that represents a processing sequence for determining the probability of a stuck condition occurring, which is performed by a stuck condition indicator detection device according to an embodiment of the present disclosure. Description of implementation examples (configuration of a stuck-state indicator detection device)

[0009] Fig. Figure 1 is a configuration diagram of a stuck-state indicator detection system, comprising a stuck-state indicator detection device according to an embodiment of the present disclosure. It should be noted that "stuck" refers to the following conditions caused by the effects of snowdrifts or similar phenomena: a condition while driving in which the continued spinning or slipping of the drive wheels of a vehicle causes non-driven wheels to stop or lock, and the vehicle to stop or come to a standstill; and a condition during the operation of starting or moving forward in which the drive wheels spin or slip, and the vehicle cannot initiate or move.

[0010] The in Fig. The depicted stuck-state detection system 1 comprises at least one vehicle control unit 2 and one server 3. The stuck-state detection system 1 determines the probability that a vehicle will become stuck, will become stuck, or enter a stuck-state condition, and provides a user with information including the result of this determination. Fig. Vehicle Management Company 4, shown in Figure 1, is an example of a user of the stuck-wheel condition indicator detection system 1 and owns different vehicles (not shown) than vehicles V1 and V2. The vehicles owned by Vehicle Management Company 4 may or may not be equipped with the vehicle control device 2.

[0011] The vehicle control device 2 is an example of a stuck-wheel condition indicator detection device according to an embodiment of the present disclosure and is provided in a vehicle. Fig. In this system, the vehicle control unit 2 is installed in each of the vehicles V1 and V2. Vehicles V1 and V2 are, for example, passenger cars. The vehicle control unit 2 determines the probability that the vehicles V1 and V2, in which the vehicle control unit 2 is installed, will become stuck and provides information to the occupants of vehicles V1 and V2, including the result of this determination. The occupants of the vehicles V1 and V2, in which the vehicle control unit 2 is installed, are examples of users of the stuck-state indicator detection system 1.

[0012] Server 3 is an example of a stuck-state indication detection device according to an embodiment of the present disclosure. Server 3 is, for example, a cloud server located outside of the vehicles V1 and V2 provided with the vehicle control device 2. Server 3 can send information to and receive information from the vehicles V1 and V2 provided with the vehicle control device 2. Based on the information received from the vehicle control device 2, Server 3 determines the probability that the vehicles (not shown) owned by the vehicle management company 4 will become stuck and provides information to the vehicle management company 4 that includes the result of the determination. The vehicles (not shown) owned by the vehicle management company 4 are, for example, trucks classified as large vehicles.

[0013] Fig. Figure 2 is a diagram illustrating an example configuration of the stuck-state indicator detection device according to an embodiment of the present disclosure. In the following description, it is assumed that the Fig. The vehicle control unit 2 shown in section 2 is provided in vehicle V1. Fig. 2 The vehicle control device 2 shown comprises a control section 20, a memory section 21, an input / output interface 22, an operation amount recording section 23, a driving state recording section 24 and a display section 25.

[0014] The control section 20 is, for example, a central processing unit (CPU). The control section 20 reads a program from the memory section 21 and executes the program.

[0015] Memory section 21 includes, for example, a storage medium such as a hard disk drive (HDD) or a solid-state drive (SSD). The program to be executed by control section 20 and the vehicle specifications of vehicle V1 are stored in memory section 21.

[0016] Memory section 21 also includes a temporary storage medium, such as random access memory (RAM), which is used as a workspace by control section 20.

[0017] Examples of vehicle specifications stored in memory section 21 include information on the propulsion system of vehicle V1, information on the braking system of vehicle V1, information on the steering system of vehicle V1, information on the weight of vehicle V1, information on the dimensions of vehicle V1, information on the tires of vehicle V1, and the like.

[0018] The input / output interface 22 is, for example, a USB port (USB, Universal Serial Bus), a LAN port (LAN, Local Area Network), or similar. The vehicle control unit 2 is connected via the input / output interface 22 to a vehicle body communication network, such as a control area network (CAN, Controller Area Network), and the vehicle control unit 2 is able to send information to and receive information from the server 3 via the CAN.

[0019] The operation amount recording section 23 records an operation amount of an operation element of vehicle V1. Examples of the operation element of vehicle V1 include an accelerator pedal, a brake pedal, and a steering wheel.

[0020] The vehicle state detection section 24 detects a vehicle state of V1. Examples of the vehicle state of V1 include information about the position at which the vehicle V1 is traveling, wheel speeds of the drive wheels of the vehicle V1, wheel speeds of the non-drive wheels of the vehicle V1, a speed of the vehicle V1, accelerations of the vehicle V1 in three directions, namely longitudinal, lateral and vertical, angular velocities of the vehicle V1 in three directions, namely pitch, yaw and roll, and the master cylinder pressure.

[0021] For example, display section 25 is a liquid crystal display device and shows a settings screen for the vehicle control device 2, a screen to provide information to a user regarding the probability of a stuck condition occurring, and the like.

[0022] Fig. Figure 3 is a diagram illustrating an example of a configuration of the stuck-state indicator detection device according to an embodiment of the present disclosure. The diagram shown in Fig. Server 3, as shown, comprises a control section 30, a storage section 31, and an input / output interface 32. The control section 30, the storage section 31, and the input / output interface 32 have similar configurations to those of the control section 20, the storage section 21, and the input / output interface 22 of the server shown in Figure 3. Fig. 2. Vehicle control unit shown 2.

[0023] A storage medium, such as an SSD, of memory section 31 stores large amounts of data based on information obtained from the vehicle control unit 2. (Vehicle stuck)

[0024] With reference to Fig. 4 describes a vehicle stuck in a state of instability. In the following description, it is assumed that the vehicle V1 is a front-wheel-drive vehicle. It is assumed that the road surface has a steep gradient and is covered with snow that has accumulated in an uncompacted state. (a) in Fig. Figure 4 shows an example of changes in the wheel speed of a left front wheel among the drive wheels of vehicle V1 over time. (b) in Fig. Figure 4 presents an example of the changes in wheel speed over time of a left rear wheel among the non-driven wheels of vehicle V1. In (a) and (b) in Fig. 4 indicates the horizontal axis as the time t from which an ignition switch of vehicle V1 is switched on.

[0025] In (a) of Fig. 4. The left front wheel of vehicle V1 remains in a state of adhesion until time T0, and the wheel speed increases according to an increase in the accelerator pedal opening degree (not shown) of vehicle V1. At time T0, the left front wheel of vehicle V1 approaches a limit of adhesion. As the left front wheel of vehicle V1 approaches the limit of adhesion, slippage occurs, and a rotational fluctuation in wheel speed occurs.

[0026] (c) in Fig. 4 represents the slip of the left front wheel among the drive wheels of vehicle V1. It should be noted that the slip of a drive wheel is calculated using the following equation (1). Slip amount = Wheel speed of the drive wheel − Average of the wheel speeds of the left and right non-driven wheels

[0027] If the slip amount of the left front wheel increases, as in (c) in Fig. As shown in 4, the wheel speed of the left rear wheel decreases, as in (b) in Fig. 4 shown. When the drive wheels, which comprise the left front wheel, of vehicle V1 reach the limit of traction and this condition persists, the non-drive wheels, which comprise the left rear wheel, of vehicle V1 stop or remain stationary. In (b) of Fig. 4 stops the left rear wheel of vehicle V1 at time T1, and vehicle V1 is stuck. (Function of the stuck-state indicator detection device)

[0028] Vehicle control unit 2 and server 3 determine the probability that the vehicle will become stuck, get stuck, or enter a stuck state by calculating a variance proxy value. This value is a parameter representing the rotational variation in the wheel speed of a drive wheel as it approaches a traction limit. The following description discusses the functions of vehicle control unit 2 and server 3.

[0029] The in Fig. The control section 20 of the vehicle control unit 2 shown in Figure 2 functions as a first procurement section 200, a calculation section 201, a stuck-state determination section 202 and a determination result output section 203, by executing a program stored in the memory section 21.

[0030] The first procurement section 200 obtains information about the operation amount of an operation element of vehicle V1 from operation amount acquisition section 23. For example, the first procurement section 200 obtains information from operation amount acquisition section 23 relating to an operation amount of an accelerator pedal of vehicle V1. Additionally, the first procurement section 200 obtains information about a driving state of vehicle V1 from driving state acquisition section 24. For example, the first procurement section 200 obtains from driving state acquisition section 24 the wheel speed of the right front wheel and the wheel speed of the left front wheel of vehicle V1, as well as the wheel speed of the right rear wheel and the wheel speed of the left rear wheel of vehicle V1.

[0031] Based on the wheel speed of a drive wheel and the wheel speeds of the non-driven wheels of vehicle V1, which are procured from the first procurement section 200, the calculation section 201 calculates a slip amount of the drive wheel of vehicle V1 according to the equation (1) described above.

[0032] Furthermore, calculation section 201 calculates a variance proxy value X based on the wheel speed of the drive wheel of vehicle V1 procured by the first procurement section 200, which is calculated by equation (2). X(t)=∑|X1(t)−X2(t)|

[0033] In equation (2) t represents time.

[0034] X1(t) is an example of a first wheel speed and is the wheel speed of the drive wheel of vehicle V1, which is procured by the first procurement section 200 at time t.

[0035] X2(t) is an example of a second wheel speed and is a time-averaged value of the wheel speed of the drive wheel of vehicle V1, procured from the first procurement section 200 until time t. Computation section 201 updates X2(t) when the wheel speed X1(t) of the drive wheel of vehicle V1 is procured from the first procurement section 200.

[0036] The variance proxy value X(t) is an example of a deviation-related value. Calculation section 201 calculates the variance proxy value X(t) based on the wheel speed X1(t) of the drive wheel of vehicle V1 obtained within a predetermined period and the time-averaged value X2(t) of the wheel speed of the drive wheel of vehicle V1 corresponding to X1(t).

[0037] (d) in Fig. Figure 4 presents an example of the variance proxy value X(t). In (d) in Fig. 4 is a sum of X1(t) - X2(t), where X1(t) - X2(t) ≥ 0 in the predetermined period, represented in an upper section (+ component). Furthermore, a sum of X1(t) - X2(t), where X1(t) - X2(t) < 0 in the predetermined period, is represented in a lower section (- component). The value of the variance proxy X(t) is a sum of the + component (upper section) and the - component (lower section). The value of the variance proxy X(t) gives the magnitude of the rotational variation of the wheel speed of the left front wheel of vehicle V1, as shown in (a) of Fig. As shown in 4, exactly the same.

[0038] The stuck state determination section 202 determines the probability that vehicle V1 will become stuck, based on (i) the information about the operation amount of the accelerator pedal of vehicle V1 and the information about the wheel speeds of the right rear wheel and the left rear wheel, which are the non-driven wheels of vehicle V1, procured by the first procurement section 200, and (ii) the variance proxy value X(t) calculated by the computation section 201.

[0039] The stuck-state determination section 202 determines, based on information about the accelerator pedal operation amount of vehicle V1, acquired by the first acquisition section 200, whether or not an acceleration request was generated in vehicle V1. For example, if the accelerator pedal operation amount of vehicle V1 is 0, the stuck-state determination section 202 determines that no acceleration request was generated in vehicle V1. It should be noted that even in a case where no accelerator pedal operation occurs (e.g., in an autonomous vehicle), if an acceleration request was generated by other devices, the stuck-state determination section 202 will still determine that an acceleration request was generated. In that case, the stuck-state determination section 202 provides a determination result of "No Determination" for determining the probability that vehicle V1 will become stuck.

[0040] In a case where the operation amount of the accelerator pedal of vehicle V1 is not equal to 0, the stuck-state determination section 202 begins by determining the probability that vehicle V1 will become stuck and performs a first stuck-state determination and a second stuck-state determination, which are described below. (Initial determination of the stuck state) [1.1] Is the slip of the left front wheel under the drive wheels of vehicle V1 less than a predetermined threshold? [1.2] Is the slip of the right front wheel under the drive wheels of vehicle V1 less than a predetermined threshold? [1.3] Is the variance proxy value X(t) of the left front wheel less than a predetermined threshold? [1.4] Is the variance proxy value X(t) of the right front wheel less than a predetermined threshold?

[0041] The slip values ​​of the left and right front wheels of vehicle V1 and the variance proxy values ​​X(t) of the left and right front wheels of vehicle V1 are calculated by calculation section 201. The thresholds for determinations [1.1] to [1.4] are defined for each vehicle V1 and stored in a storage medium such as an SSD in storage section 21. In a case where all determinations [1.1] to [1.4] are positive, the stuck-state determination section 202 provides a determination result "adhesion" for determining the probability that vehicle V1 will become stuck. (Second determination of the stuck state) [2.1] Is the left rear wheel of vehicle V1 stopped among the non-driven wheels? [2.2] Is the right rear wheel of vehicle V1 stopped among the non-driven wheels? [2.3] Is the larger of the two slip values ​​of the left and right drive wheels of vehicle V1 greater than a predetermined threshold?

[0042] Whether the left and right rear wheels of vehicle V1 are stopped or not is determined based on the wheel speeds of the left and right rear wheels of vehicle V1, which are obtained by the first procurement section 200. The slip amounts of the left and right front wheels of vehicle V1 are calculated by the calculation section 201. The threshold for determination [2.3] is defined for each vehicle V1 and stored in the storage medium, for example, an SSD, in storage section 21. In a case where all determinations [2.1] to [2.3] are positive, the stuck-state determination section 202 provides a determination result of "Beyond the Limit of Liability" for determining the probability that vehicle V1 will become stuck. In a case where at least one of the determinations [2.1] to [2.3] is positive, the stuck-state determination section 202 provides a determination result of "Beyond the Limit of Liability" for determining the probability that vehicle V1 will become stuck.3] If the probability of vehicle V1 becoming stuck is negative, section 202 of the stuck-state determination provides a result of "Near the limit of adhesion" for determining the probability that vehicle V1 will become stuck. In a case where the probability that vehicle V1 will become stuck is determined by section 202 of the stuck-state determination as "Beyond the limit of adhesion", it is very likely that vehicle V1 is actually in a stuck-state condition.

[0043] (a Fig. Figure 4 shows an example of a determination result from section 202 of the stuck-state determination procedure. In (e) of Fig. In section 4, a determination result of "No determination" is represented by 0, a determination result of "Adhesion" by 1, a determination result of "Near the limit of adhesion" by 2, and a determination result of "Beyond the limit of adhesion" by 3. Near time T0, when rotational fluctuations in the wheel speed of the left front wheel of vehicle V1 begin to occur, the determination result of the stuck-state determination section 202 changes gradually from "Adhesion" to "Near the limit of adhesion." At time T1, when the left rear wheel of vehicle V1 stops, the determination result of the stuck-state determination section 202 changes from "Near the limit of adhesion" to "Beyond the limit of adhesion."

[0044] The determination result output section 203 in Fig. 2 outputs the determination result of the stuck-state determination section 202. For example, the determination result output section 203 can output the determination result to the display section 25. For example, the determination result output section 203 transmits the determination result of the stuck-state determination section 202, the information procured by the first procurement section 200, and the information calculated by the calculation section 201 to server 3 via the input / output interface 22.

[0045] The in Fig. The control section 30 of server 3 shown in Figure 3 functions as a second procurement section 300, a calculation section 301, a stuck-state determination section 302 and an information provision section 303, by executing a program stored in the memory section 31.

[0046] The second procurement section 300 obtains information from the vehicle control units 2 of vehicles V1 and V2 regarding vehicles V1 and V2. For example, the second procurement section 300 obtains information via the input / output interface 32, which is output by the destination output section 203. The second procurement section 300 stores the acquired information as large data or big data in the SSD or similar of storage section 31. Furthermore, the second procurement section 300 obtains information from the vehicle management company 4, such as vehicle specifications and position information for the vehicles owned by the vehicle management company 4.

[0047] Calculation section 301 has similar functions to those of calculation section 201. For example, if the second procurement section 300 has obtained information about a vehicle, calculation section 301 calculates a slip amount and a variance proxy value for that vehicle. Examples of vehicles for which calculation section 301 calculates a slip amount and a variance proxy value include vehicles in which the vehicle control device 2 is not provided (e.g., the vehicles owned by the vehicle management company 4).

[0048] The stuck state determination section 302 has similar functions to those of the stuck state determination section 202. For example, based on the information obtained by the second procurement section 300 and the slip amount and variance proxy value calculated by the calculation section 301, the stuck state determination section 302 determines the probability that the vehicles owned by vehicle management company 4 will become stuck.

[0049] Furthermore, the stuck-state determination section 302, based on the information obtained by the second procurement section 300 from the vehicle control unit 2, determines the probability that a vehicle will become stuck. For example, the stuck-state determination section 302 performs statistical processing of the large data or big data stored in the SSD or similar of memory section 31 and determines the probability of the vehicle becoming stuck for each driving region and each vehicle classification. In a case, for example, where the stuck-state determination section 202 in the vehicle control unit 2 of vehicle V1 has determined "adhesion", it is determined that an area in which vehicle V1 drives has a "low risk of a stuck-state occurring" with respect to the probability of large vehicles becoming stuck.In a case where the stuck-state determination section 202 in the vehicle control unit 2 of vehicle V1 has determined "Near the limit of adhesion", it is determined that the area in which vehicle V1 travels has a "medium risk of a stuck-state occurring" with respect to the probability that large vehicles will become stuck. In a case where the stuck-state determination section 202 in the vehicle control unit 2 of vehicle V1 has determined "Beyond the limit of adhesion", it is determined that the area in which vehicle V1 travels has a "high risk of a stuck-state occurring" with respect to the probability that large vehicles will become stuck.

[0050] Based on the result determined by the stuck-state determination section 302, the information provision section 303 provides information to the vehicle management company 4 that includes the determination result regarding the probability that the vehicle will become stuck. For example, the information provision section 303 transmits, via the input / output interface 32, information determined by the stuck-state determination section 302 regarding the probability that large vehicles will become stuck to the vehicle management company 4. Based on the information thus provided, the vehicle management company 4 creates schedules and similar information for the vehicles owned by the vehicle management company 4. This allows the probability that large vehicles will become stuck to be determined.The likelihood of getting stuck is reduced, and the probability of disruption to the road network is lowered. (Processing by the stuck-state indicator detection device)

[0051] Fig. Figure 5 is a flowchart depicting a processing sequence for determining the probability of a stuck condition occurring, as performed by the stuck condition indicator detection device according to an embodiment of the present disclosure. A series of processes, which are described in Fig. The process shown in Figure 5 is repeated by control section 20 of the vehicle control device 2 and control section 30 of the server 3. Once control section 20 of the vehicle control device 2 and control section 30 of the server 3 have completed the operation described in Figure 5, the following steps are performed: Fig. Once the processing described in step 5 is complete, control section 20 and control section 30 begin the next processing cycle. The following describes a processing sequence that takes place in control section 20 of the vehicle control unit 2 of vehicle V1.

[0052] In S100, control section 20 acts as the first acquisition section 200 and obtains information from operation amount acquisition section 23 and driving condition acquisition section 24. For example, control section 20 obtains information from operation amount acquisition section 23 relating to the operation amount of the accelerator pedal of vehicle V1. Control section 20 obtains from driving condition acquisition section 24 the wheel speed of the right front wheel and the wheel speed of the left front wheel of vehicle V1, as well as the wheel speed of the right rear wheel and the wheel speed of the left rear wheel of vehicle V1.

[0053] In S110, the control section 20 acts as the calculation section 201 and calculates a slip amount and a variance proxy value for the left front wheel and the right front wheel of vehicle V1 based on the information obtained in S200.

[0054] In S120, control section 20 functions as the stuck-state determination section 202 and determines whether an acceleration request has been generated in vehicle V1. If an acceleration request has been generated in vehicle V1 (S120: YES), control section 20 proceeds to S130. Conversely, if no acceleration request has been generated in vehicle V1 (S120: NO), control section 20 provides a determination result of "No determination" for determining the probability that vehicle V1 will become stuck (S150).

[0055] In S130, control section 20 functions as the stuck-state determination section 202 and performs the first stuck-state determination described above. If all of the determinations [1.1] to [1.4] included in the first stuck-state determination are positive (S130: YES), control section 20 provides a determination result of "adhesion" for determining the probability that vehicle V1 will become stuck (S160). If at least one of the determinations [1.1] to [1.4] included in the first stuck-state determination is negative (S130: NO), control section 20 proceeds to S140.

[0056] In S140, control section 20 functions as the stuck-state determination section 202 and performs the second stuck-state determination described above. In a case where all of the determinations [2.1] to [2.3] included in the second stuck-state determination are positive (S140: YES), control section 20 provides a determination result of "Beyond the Limit of Liability" for determining the probability that vehicle V1 will become stuck (S180). In a case where at least one of the determinations [2.1] to [2.3] included in the second stuck-state determination is negative (S140: NO), control section 20 provides a determination result of "Near the Limit of Liability" for determining the probability that vehicle V1 will become stuck (S170). (Variation)

[0057] In the embodiment described above, the control section 20 of the vehicle control unit 2 provided in the vehicle V1 functions as the calculation section 201 and the immobilization determination section 202, determining the probability that the vehicle V1 will become stuck. However, the control section 20 of the vehicle control unit 2 does not necessarily function as the calculation section 201 and the immobilization determination section 202. For example, the control section 20 can transmit the information acquired by the first acquisition section 200 to the server 3 via the input / output interface 22. The control section 30 of the server 3 can then function as the calculation section 301 and the immobilization determination section 302, determining the probability that the vehicle V1 will become stuck based on the information received from the vehicle control unit 2.In a case where server 3 has determined the probability that vehicle V1 will become stuck, it is preferable for information provision section 303 to transmit the determination result to vehicle control unit 2.

[0058] The control section 20 of the vehicle control unit 2 can be configured to act as the first procurement section 200, the calculation section 201, the stuck-state determination section 202 and the determination result output section 203, by executing a program stored in the memory section 31 of the server 3.

[0059] The stuck condition indicator detection system does not necessarily include Server 3. In a case where the stuck condition indicator detection system does not include Server 3, the determination result output section 203 does not transmit information, such as a determination result from the stuck condition determination section 202, to Server 3.

[0060] In the above embodiment, calculation section 201 and calculation section 301 calculate a variance proxy value as a parameter that indicates a rotational variation in the wheel speed of the drive wheel. However, a parameter calculated by calculation section 201 that indicates a rotational variation in the wheel speed of the drive wheel is not limited to the variance proxy value. For example, a statistical variance value can be calculated as a parameter that indicates the rotational variation in the wheel speed of the drive wheels. In the above embodiment, calculation section 201 and calculation section 301 calculate the variance proxy value, which is an example of a deviation-related value, by calculating the deviation of the wheel speed of a drive wheel of vehicle V1, procured by the first procurement section 200, relative to a time-averaged value of the wheel speed of the drive wheel of vehicle V1, procured by the first procurement section 200. However, a method for calculating the deviation-related value is not limited to this. For example, the deviation-related value can be calculated according to a frequency with which the wheel speed of a drive wheel of vehicle V1 procured by the first procurement section 200 exceeds a time-averaged value of the wheel speeds of the drive wheel of vehicle V1 procured by the first procurement section 200.Calculation section 201 and calculation section 301 can calculate, as a deviation-related value, a deviation of the wheel speed of a drive wheel of vehicle V1 procured by the first procurement section 200 from a moving average value of the wheel speed of the drive wheel of vehicle V1.

[0061] In the embodiment described above, in a case where an acceleration request has been generated in vehicle V1, the stuck-state determination section 202 and the stuck-state determination section 302 begin determining the probability that vehicle V1 will become stuck. However, the condition under which stuck-state determination section 202 and the stuck-state determination section 302 begin determining the probability that vehicle V1 will become stuck is not limited to the case where an acceleration request has been generated in vehicle V1. Examples of the condition for beginning the determination of the probability that vehicle V1 will become stuck could be a condition such that a deviation-related value, or a change amount or rate of change therein, calculated by computation section 201 and computation section 301 is not less than a predetermined threshold.For example, the Stuck Condition Determination Section 202 and the Stuck Condition Determination Section 302 can be configured to begin determining the probability of vehicle V1 becoming stuck in a case where (i) an acceleration request has been generated in vehicle V1 and (ii) a deviation-related value, or a change amount or rate of change of the deviation-related value calculated by computation section 201 and computation section 301, is not less than a predetermined threshold. The predetermined threshold can vary for each vehicle V1.

[0062] In the description of the above embodiment, it is assumed that vehicle V1 is a front-wheel-drive vehicle. However, vehicles V1 and V2 are not limited to front-wheel-drive vehicles. For example, vehicles V1 and V2 could be rear-wheel-drive or all-wheel-drive vehicles. In a case where vehicles V1 and V2 are rear-wheel-drive vehicles, the drive wheels of each vehicle are a left rear wheel and a right rear wheel, and the non-driven wheels are a left front wheel and a right front wheel.In a case where vehicles V1 and V2 are all-wheel drive vehicles, all wheels of each of vehicles V1 and V2 serve as drive wheels, and the wheel speed of a driven wheel of each of vehicles V1 and V2 is an estimated vehicle body speed estimated from the respective wheel speeds of each of vehicles V1 and V2 and serves as the wheel speed of a non-driven wheel.

[0063] The processing sequence for determining the probability of a stuck state occurring, which is determined by the in Fig.The determination of the probability of vehicle V1 becoming stuck, as shown in Figure 5, is merely an example and not limited to this. For instance, in a case where the probability of vehicle V1 becoming stuck is determined by the Stability Determination Section 202 as "Near the Limit of Grip" (S170), it can further determine whether a variance proxy value X(t) of a drive wheel of vehicle V1 exceeds a predetermined threshold. The Stability Determination Section 202 can be configured to update the determination result regarding the probability of vehicle V1 becoming stuck to "Beyond the Limit of Grip" in a case where the variance proxy value X(t) of the drive wheels of vehicle V1 exceeds the predetermined threshold. [Example of software implementation]

[0064] Functions of the stuck-state indicator detection device (hereinafter referred to as the "device") can be implemented by a program that causes a computer to act as the device, the program causing the computer to act as control blocks (in particular sections included in control section 20 and control section 30) of the device.

[0065] In this case, the hardware for executing the program comprises a computer, which includes at least one control unit (e.g., a processor) and at least one storage unit (e.g., memory). The functions described in the above embodiments are realized by executing the program using the control unit and the storage unit.

[0066] The program may be recorded on one or more non-transient, computer-readable recording media. These recording media may or may not be located within the facility. In the latter case, the program may be made available to the facility via any wired or wireless transmission medium.

[0067] Furthermore, all or some of the functions of the control blocks can also be implemented by a logic circuit. For example, the present disclosure includes an integrated circuit in which a logic circuit is implemented that functions as each of the control blocks. Additionally, the function of each of the control blocks can be implemented, for example, by a quantum computer.

[0068] Furthermore, each of the processes described in the above examples can be executed by artificial intelligence (AI).

[0069] Aspects of the present invention can also be expressed as follows: A stuck-state detection device according to one aspect of the present disclosure comprises: a computation section configured to compare a first wheel speed with a second wheel speed to calculate a deviation-related value regarding a deviation of the first wheel speed relative to the second wheel speed, wherein the first wheel speed is a wheel speed of a drive wheel of a vehicle and the second wheel speed is an average value of the wheel speed of the drive wheel; and a stuck-state determination section configured to determine a probability that the vehicle will become stuck in a case where (i) it has been determined that the deviation-related value is not less than a predetermined threshold, and (ii) an acceleration request has been generated in the vehicle.

[0070] The inventor has discovered that before a vehicle becomes stuck, the amount and frequency of axle wobble increase. Accordingly, the present disclosure calculates a deviation-related value based on the difference between an average wheel speed and an actual wheel speed. This deviation-related value indicates the amount and frequency of axle wobble that occurs as the vehicle approaches a stuck state from a state of traction. If the deviation-related value is not less than a predetermined threshold and an acceleration request has been generated in the vehicle, it is determined that the vehicle is very likely to become stuck. This allows an indication of the onset of a stuck state to be detected before the vehicle becomes stuck.

[0071] A stuck-state indication detection device according to one aspect of the present disclosure is configured such that the stuck-state determination section is configured to (i) in a case where the acceleration request has been generated in the vehicle, and (ii) according to the deviation-related value or a change amount or rate of change of the deviation-related value, whether or not to begin determining the probability that the vehicle will become stuck.

[0072] According to the above embodiment, by taking into account a condition relating to a deviation-related value or a change amount or rate of change of the deviation-related value when determining whether to start determining the probability that the vehicle will get stuck, it is possible to determine the probability of the occurrence of the stuck condition with higher accuracy.

[0073] A stuck-state detection device according to one aspect of the present disclosure is configured such that the calculation section is configured to calculate a slip amount based on the first wheel speed and a third wheel speed of the non-driven wheel of the vehicle, and the stuck-state determination section is configured to determine, in a case where (i) an acceleration request has been generated in the vehicle and (ii) according to the deviation-related value or the slip amount, the probability that the vehicle will become stuck.

[0074] According to the above embodiment, by taking into account the amount of slip of the drive wheel when determining the probability that the vehicle will become stuck, it is possible to determine the probability of the occurrence of the stuck condition with greater accuracy.

[0075] A stuck-state indication detection device according to one aspect of the present disclosure is configured such that the stuck-state determination section is configured to determine, in a case where (i) an acceleration request has been generated in the vehicle and (ii) according to the deviation-related value or wheel speed of a non-driven wheel of the vehicle, the probability that the vehicle will become stuck.

[0076] In a case where the vehicle's drive wheels still cannot achieve traction, the vehicle's non-driven wheels could stop or come to a standstill. According to the embodiment above, by considering the wheel speed of the vehicle's non-driven wheel when determining the probability of the vehicle becoming stuck, the stuck-condition determination section can determine the probability of the vehicle becoming stuck with greater accuracy. [Additional note]

[0077] The present disclosure is not limited to the embodiments described above, but may be modified within the scope of the claims. The present disclosure also encompasses, within its technical scope, any embodiment derived by a suitable combination of the technical means disclosed in different embodiments. Reference symbol list 1 Stuck condition indicator detection system 2 Vehicle control unit (stuck condition indicator detection unit) 3 servers (stuck condition indicator detection device) 201, 301 Calculation section 202, 302 Stuck condition determination section QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] JP 2006-230130

[0003]

Claims

A stuck-state detection device comprising: a computation section configured to compare a first wheel speed with a second wheel speed to calculate a deviation-related value regarding a deviation of the first wheel speed from the second wheel speed, wherein the first wheel speed is a wheel speed of a drive wheel of a vehicle and the second wheel speed is an average value of the wheel speed of the drive wheel; and a stuck-state determination section configured to determine, in a case where (i) it has been determined that the deviation-related value is not less than a predetermined threshold, and (ii) an acceleration request has been generated in the vehicle, a probability that the vehicle will become stuck. Stuck condition indication detection device according to claim 1, wherein the stuck condition determination section is configured to (i) in a case where the acceleration request has been generated in the vehicle, and (ii) according to the deviation-related value or a change amount or rate of change of the deviation-related value, to begin determining the probability that the vehicle will become stuck or not.

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