WO2021111943A1 - Driving assistance system and driving assistance method - Google Patents

Driving assistance system and driving assistance method Download PDF

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Publication number
WO2021111943A1
WO2021111943A1 PCT/JP2020/043808 JP2020043808W WO2021111943A1 WO 2021111943 A1 WO2021111943 A1 WO 2021111943A1 JP 2020043808 W JP2020043808 W JP 2020043808W WO 2021111943 A1 WO2021111943 A1 WO 2021111943A1
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WIPO (PCT)
Prior art keywords
tire
tire force
information acquisition
force
area information
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PCT/JP2020/043808
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French (fr)
Japanese (ja)
Inventor
寛篤 長谷川
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Ｔｏｙｏ Ｔｉｒｅ株式会社
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Publication of WO2021111943A1 publication Critical patent/WO2021111943A1/en

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60C—VEHICLE TYRES; TYRE INFLATION; TYRE CHANGING; CONNECTING VALVES TO INFLATABLE ELASTIC BODIES IN GENERAL; DEVICES OR ARRANGEMENTS RELATED TO TYRES
    • B60C19/00—Tyre parts or constructions not otherwise provided for
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
    • B60W40/06—Road conditions
    • B60W40/064—Degree of grip
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
    • G01M17/00—Testing of vehicles
    • G01M17/007—Wheeled or endless-tracked vehicles
    • G01M17/02—Tyres

Definitions

  • the present invention relates to a driving support system and a driving support method that estimate the force generated by tires and friction with the road surface when the vehicle is running and apply it to the driving of the vehicle.
  • the vehicle driving support system estimates the friction value and braking distance of the road surface, and automatically controls the braking operation and steering on behalf of the driver in order to avoid collisions with obstacles outside the vehicle and other vehicles. Assisting the driver is being considered.
  • Patent Document 1 describes a conventional method for determining a friction value and a method for controlling a vehicle function.
  • the method of determining the friction value in the contact between the vehicle tires and the roadway is the step of processing the sensor signal using the processing rules to generate the processed sensor signal, in which case the sensor signal is at least A step representing at least state data that can correlate with the friction value for the peripheral region having a contact position between the vehicle tire and the roadway, read by one detector, and the friction value using the processed sensor signal. It has a step to determine.
  • the vehicle function control method includes a step of receiving a control signal generated by using the friction value and a step of operating the vehicle function by using the reception control signal.
  • the traveling data of the vehicle is used as an example of the sensor signal.
  • the present inventor has noticed that there is room for improvement in vehicle running support by automatic control by estimating the tire force generated in the tire with higher accuracy. Furthermore, the present inventor has found that the slipperiness of the road surface can be evaluated based on the tire force and the limit tire force to support the running of the vehicle, and information can be provided about the slippery part on the road.
  • the present invention has been made in view of such circumstances, and an object of the present invention is to provide running support capable of estimating tire force with high accuracy and further estimating limit tire force to support the running of a vehicle.
  • the purpose is to provide a system and a driving support method.
  • the driving support system includes a sensor information acquisition unit that acquires the physical quantity of the tire measured by a sensor arranged on the tire, and an area information acquisition unit that acquires external area information regarding the peripheral area of the position where the tire contacts the road surface.
  • a tire force calculation unit that calculates the tire force by inputting the physical quantity of the tire acquired by the sensor information acquisition unit and the external area information acquired by the area information acquisition unit into the calculation model.
  • the driving support method includes a sensor information acquisition step of acquiring the physical quantity of the tire measured by a sensor arranged on the tire, and an area information acquisition step of acquiring external area information regarding a peripheral area of a position where the tire contacts the road surface.
  • a tire force calculation step of inputting the physical quantity of the tire acquired by the sensor information acquisition step and the external region information acquired by the region information acquisition step into the calculation model to calculate the tire force is provided.
  • the present invention it is possible to estimate the tire force with high accuracy and further estimate the limit tire force to support the running of the vehicle.
  • FIGS. 1 to 6 based on a preferred embodiment.
  • the same or equivalent components and members shown in the drawings shall be designated by the same reference numerals, and redundant description will be omitted as appropriate.
  • the dimensions of the members in each drawing are shown enlarged or reduced as appropriate for easy understanding.
  • some of the members that are not important for explaining the embodiment in each drawing are omitted and displayed.
  • FIG. 1 is a block diagram showing a functional configuration of the traveling support system 100 according to the embodiment.
  • the travel support system 100 measures tire physical quantities such as acceleration, air pressure, and temperature generated in the tire 10 by a sensor 20 arranged on the tire 10 when the vehicle is traveling, and the tire 10 is in contact with the road surface. Acquires external area information about the area around the position.
  • the external area information is information indicating a situation related to slipperiness between the tire and the road surface, such as weather information and unevenness of the road surface.
  • the running support system 100 inputs the acquired physical quantity of the tire 10 and external area information into the calculation model 35a, and calculates the tire force and the limit tire force.
  • the calculation model 35a is a learning model such as a neural network. The accuracy of the calculation model 35a is improved by using the tire force actually measured on the tire 10 and the limit tire force as teacher data and repeating the learning by executing the calculation and updating the calculation model.
  • the limit tire force is the tire force immediately before the tire 10 starts to slide on the road surface, and is a value obtained by multiplying the vertical load of the tire 10 by the maximum coefficient of friction with the road surface.
  • the running support system 100 evaluates the slipperiness of the tire 10 on the road surface on which the vehicle has traveled by calculating a margin with respect to the calculated limit tire force of the tire force.
  • the travel support system 100 evaluates the degree of slipperiness based on the size of the margin.
  • the travel support system 100 can provide information such as an accurately calculated tire force, a limit tire force, and a margin for the limit tire force of the tire force to the vehicle control device to support the vehicle travel.
  • the traveling support system 100 includes a server device or the like as an external device, accumulates the evaluated degree of slipperiness of the road surface in association with the position on the map in the external device, and distributes the accumulated information. Can be provided.
  • the provided information on the slipperiness of the road surface can be used by clearly indicating the slippery position or section on the map displayed on the display device provided in the vehicle.
  • the driving support system 100 includes a sensor 20 and a tire force estimation device 30.
  • the sensor 20 includes an acceleration sensor 21, a pressure sensor 22, a temperature sensor 23, and the like, and measures physical quantities in the tire 10 such as acceleration, tire pressure, and tire temperature.
  • the sensor 20 may have a strain gauge to measure the strain generated in the tire 10. These sensors measure the physical quantity related to the deformation and movement of the tire 10 as the physical quantity of the tire 10.
  • the acceleration sensor 21 is arranged on a tire body portion formed of a rubber material of the tire 10 or a wheel 15 forming a part of the tire 10, and accelerates generated in the tire 10 while mechanically moving together with the tire 10. To measure.
  • the acceleration sensor 21 measures the acceleration of the tire 10 in the three axes of the circumferential direction, the axial direction, and the radial direction.
  • the pressure sensor 22 and the temperature sensor 23 are arranged, for example, by mounting the tire 10 on the air valve or fixing the tire 10 to the wheel 15, and measure the air pressure and temperature of the tire 10, respectively. Further, the pressure sensor 22 and the temperature sensor 23 may be arranged on the inner liner or the like of the tire 10.
  • the sensor 20 measures physical quantities of the tire 10 such as acceleration and strain of the tire 10, tire air pressure, and tire temperature, and outputs the measured data to the tire force estimation device 30.
  • the tire force estimation device 30 estimates the tire force F based on the data measured by the sensor 20.
  • the tire 10 may be equipped with, for example, an RFID 11 or the like to which unique identification information is attached in order to identify each tire.
  • the calculation model 35a may be selected and set from a data group prepared in advance according to the unique information of the RFID 11 attached to the tire 10, or may be selected from a database provided by a server device or the like. It may be. Further, the specifications of the tire 10 may be recorded with respect to the unique information of the RFID 11, and the calculation model 35a corresponding to the specifications of the tire 10 may be provided in the database. The specifications of the tire 10 may be called from the unique information of the RFID 11, and the calculation model 35a may be set, or the calculation model 35a according to the specifications of the called tire 10 may be selected from the database.
  • the tire force estimation device 30 includes a position information acquisition unit 31, an area information acquisition unit 32, a sensor information acquisition unit 33, a communication unit 34, and a tire force calculation unit 35.
  • the tire force estimation device 30 is an information processing device such as a PC (personal computer).
  • Each part of the tire force estimation device 30 can be realized by an electronic element such as a computer CPU or a mechanical component in terms of hardware, and can be realized by a computer program or the like in terms of software. It depicts a functional block realized by cooperation. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by combining hardware and software.
  • the position information acquisition unit 31 acquires the vehicle position data measured by the GPS receiver 50 and outputs it to the area information acquisition unit 32. Based on the vehicle position data input from the position information acquisition unit 31, the area information acquisition unit 32 provides external area information such as weather information and road surface unevenness with respect to the peripheral area of the position where the tire 10 is in contact with the road surface. Obtained via the communication unit 34. External area information such as weather information and road surface unevenness is information indicating a situation related to slipperiness between the tire and the road surface, has a correlation with the tire force and the limit tire force, and is a calculation model. It becomes an input element to 35a. The area information acquisition unit 32 acquires information having a correlation with the tire force and the limit tire force, such as weather information, information such as road surface unevenness, and road surface freezing information based on temperature, time zone, and road traffic information. You may.
  • the sensor information acquisition unit 33 acquires physical tire quantities such as acceleration, tire pressure, and tire temperature measured by the sensor 20 by wireless communication or the like.
  • the communication unit 34 communicates with the external device by wired or wireless communication or the like, and receives the external area information acquired by the area information acquisition unit 32 from the external device. Further, the communication unit 34 transmits the position data, the tire force F, the limit tire force, and the margin information to the external server device as described later.
  • the tire force calculation unit 35 has a calculation model 35a and a correction processing unit 35b, inputs information from the area information acquisition unit 32 and the sensor information acquisition unit 33 into the calculation model 35a, and calculates the tire force F and the limit tire force. To do. As shown in FIG. 1, the tire force F has three axial components of the front-rear front-rear force Fx of the tire 10, the lateral force Fy in the lateral direction, and the load Fz in the vertical direction. The tire force calculation unit 35 may calculate all of these three axial components, or may calculate at least one component or two components by any combination.
  • the tire force calculation unit 35 calculates the margin of the tire force F with respect to the limit tire force based on the tire force F and the limit tire force calculated by the calculation model 35a.
  • the margin of the tire force F with respect to the limit tire force is larger as the tire force F is smaller than the limit tire force.
  • the calculation model 35a uses a learning model such as a neural network.
  • the calculation model 35a is, for example, a CNN (Convolutional Neural Network) type, and uses a learning type model including a convolutional operation and a pooling operation used in the so-called LeNet which is the prototype thereof.
  • the calculation model 35a extracts the features of the data input to the input layer by using a convolution operation and a pooling operation, transmits the features to each node of the intermediate layer, and performs a linear operation or the like for each node of the intermediate layer. Is executed to fully connect and connect to each node of the output layer. In the full coupling, in addition to the linear operation, a non-linear operation may be executed by using an activation function or the like.
  • the tire force F and the limit tire force in the three axial directions are output to each node of the output layer of the calculation model 35a.
  • FIG. 2 is a schematic diagram for explaining the learning of the calculation model 35a.
  • the input data to the calculation model 35a is the tire physical quantity acquired by the sensor information acquisition unit 33, the external area information acquired by the area information acquisition unit 32, and the like.
  • For the physical quantity of the tire acceleration, tire pressure, tire temperature, strain generated in the tire, and the like are used.
  • the external area information meteorological information such as weather, temperature and precipitation, and road surface information such as road surface unevenness, temperature and frozen state are used.
  • the input data may use the vehicle weight, speed, etc. based on the data of the digital tachograph mounted on the vehicle.
  • the accuracy of the calculation model 35a is improved by comparing the tire force F and the limit tire force as the calculation result with the teacher data and repeating the update of the calculation model 35a. Further, in the calculation model 35a, for example, the configuration and weighting of the number of layers in all the joints in the model change according to the specifications of the tire 10, but the rotation of the tire 10 (including the wheels) of each specification. The learning of the calculation model 35a can be performed in the test.
  • the calculation model 35a is trained and constructed for each type of passenger car tire, truck tire, etc., and the tire force F and the limit tire force are estimated within a certain error range, so that the tire force F and the limit tire force are included in a plurality of specifications.
  • One calculation model 35a may be shared for the tire 10 to be used, and the number of calculation models may be reduced. Further, the calculation model 35a can also carry out learning of the calculation model 35a by mounting the tire 10 on an actual vehicle and running the vehicle in a test run.
  • the specifications of the tire 10 include information on tire performance such as tire size, tire width, flatness, tire strength, tire outer diameter, road index, and date of manufacture.
  • the calculation model 35a may be learned by performing a rotation test by changing the road surface friction coefficient (maximum friction coefficient) of the ground contact surface on which the tire 10 is grounded. Further, it is also possible to mount the tire 10 on an actual vehicle and run the vehicle on a test run on a road surface having a different coefficient of friction on the road surface to execute learning of the calculation model 35a.
  • the correction processing unit 35b corrects the calculation model 35a based on the state of the tire 10. Alignment error occurs when the tire 10 is mounted on a vehicle, physical property values such as rubber hardness change with time, and wear progresses as the tire runs. The state of the tire 10 including factors such as alignment error, physical property value, and wear changes depending on the usage conditions, and an error occurs in the calculation of the tire force F and the limit tire force by the calculation model 35a.
  • the correction processing unit 35b performs a process of adding a correction term according to the state of the tire 10 to the calculation model 35a in order to reduce the error of the calculation model 35a.
  • FIG. 3 is a flowchart showing the procedure of the tire force estimation process by the tire force estimation device 30.
  • the position information acquisition unit 31 of the tire force estimation device 30 acquires the position data, and the area information acquisition unit 32 starts the acquisition of the external area information (S1).
  • the sensor information acquisition unit 33 starts acquiring tire physical quantities such as acceleration, tire air pressure, and tire temperature in the tire 10 measured by the sensor 20 (S2).
  • the tire force calculation unit 35 inputs the external region information and the tire physical quantity into the calculation model 35a, and calculates the tire force F and the limit tire force (S3).
  • the tire force calculation unit 35 calculates a margin of the calculated tire force F with respect to the limit tire force (S4), and ends the process.
  • the tire force estimation device 30 calculates and estimates the tire force F, the limit tire force, and the margin in time series by repeating the processes from step S1 to step S4.
  • FIG. 4 is a schematic diagram for explaining the margin of the tire force F with respect to the limit tire force.
  • the horizontal axis represents the front-rear force Fx of the tire force F
  • the vertical axis represents the lateral force Fy of the tire force F
  • the circle centered on the origin indicates the limit tire force.
  • the tire force F1 and F2 calculated by the calculation model 35a the tire force F1 is smaller than the tire force F2, and the margin is large with respect to the limit tire force.
  • the limit tire force changes in magnitude depending on the maximum coefficient of friction between the tire 10 and the road surface. Further, the tire force F1 becomes large when acceleration occurs in the left-right direction of the vehicle due to a curve of the traveling route of the vehicle or the like. Generally, on a road with many curves, an area with a high probability of rainfall, etc., the tire force F tends to be large, the limit tire force tends to be small, and the margin is small.
  • the running support system 100 can improve the calculation accuracy of the tire force F, the limit tire force, and the margin by the calculation model 35a in which the physical quantity of the tire and the external region information are input.
  • the tire force estimation device 30 outputs the calculated tire force F, the limit tire force, and the margin to the vehicle control device or the like.
  • the vehicle control device estimates the braking distance based on the tire force F, the limit tire force and the margin input from the tire force estimation device 30, application to vehicle control and automatic driving, and information on safe driving of the vehicle. Can be notified.
  • FIG. 5 is a block diagram showing the functional configuration of the traveling support system 100 including the server device 7, and FIG. 6 is a block diagram showing the functional configuration of the server device 7.
  • the tire force estimation device 30 calculates the position data, the tire force F, the limit tire force, and the margin, and transmits the position data, the tire force F, the limit tire force, and the margin to the server device 7 via the communication network 9.
  • the server device 7 accumulates the received position data, the tire force F, the limit tire force, and the margin, and evaluates the degree of slipperiness of the road surface.
  • the server device 7 includes a communication unit 71, a storage unit 72, and a tire road surface condition evaluation unit 73.
  • the communication unit 71 receives the position data, the tire force F, the limit tire force, and the margin transmitted from the vehicle via the communication network 91.
  • the storage unit 72 is composed of a storage device such as a hard disk, and stores the position data, the tire force F, the limit tire force, and the margin received by the communication unit 71.
  • the tire road surface condition evaluation unit 73 reads out the tire force F, the limit tire force and the margin stored in the storage unit 72, and the current tire friction characteristics (such as the degree of decrease in grip due to the influence of the type and the degree of wear) and the road surface.
  • the degree of slipperiness is evaluated, and the tire state (air pressure, tire temperature, etc.), tire friction characteristics, and the degree of slipperiness are stored in the storage unit 72 in association with the position data.
  • the degree of slipperiness of the road surface may be evaluated in multiple stages, for example.
  • the server device 7 distributes the position data stored in the storage unit 72 and the degree of slipperiness of the road surface to the vehicle side via the communication unit 71. Supports the running of the vehicle by clearly indicating the slippery position and section on the map displayed on the display device provided on the vehicle based on the delivered position data and the degree of slipperiness of the road surface. be able to. In addition, by grasping slippery positions and sections, it can be used for road maintenance management such as repair.
  • the traveling support system 100 includes a sensor information acquisition unit 33, an area information acquisition unit 32, and a tire force calculation unit 35.
  • the sensor information acquisition unit 33 acquires the physical quantity of the tire 10 measured by the sensor 20 arranged on the tire 10.
  • the area information acquisition unit 32 acquires external area information regarding the peripheral area of the position where the tire 10 comes into contact with the road surface.
  • the tire force calculation unit 35 calculates the tire force F by inputting the physical quantity of the tire 10 acquired by the sensor information acquisition unit 33 and the external area information acquired by the area information acquisition unit 32 into the calculation model 35a. As a result, the traveling support system 100 can accurately estimate the tire force F based on the physical quantity of the tire 10 measured by the sensor 20 and the external region information.
  • the tire force calculation unit 35 further calculates the limit tire force by the calculation model 35a.
  • the traveling support system 100 can support the traveling of the vehicle by the calculated tire force F and the limit tire force.
  • a communication unit 34 as a transmission unit that calculates a margin of the tire force F calculated by the tire force calculation unit 35 with respect to the limit tire force and transmits the margin to the server device 7 which is an external device is further provided.
  • the travel support system 100 provides the server device 7 with a margin for the limit tire force of the tire force F calculated when the vehicle is traveling, and the server device 7 evaluates the slipperiness of the road surface and accumulates data. Can be planned.
  • the server device 7 which is an external device, stores the tire road surface condition evaluation unit 73, which evaluates the degree of slipperiness based on the margin transmitted by the communication unit 34, and the position of the vehicle and the degree of slipperiness in association with each other. It has a storage unit 72 to be used. As a result, the traveling support system 100 can evaluate the slipperiness of the road surface based on the margin of the tire force F calculated when the vehicle is traveling with respect to the limit tire force, and support the traveling of the vehicle.
  • the driving support method includes a sensor information acquisition step, an area information acquisition step, and a tire force calculation step.
  • the sensor information acquisition step acquires the physical quantity of the tire 10 measured by the sensor 20 arranged on the tire 10.
  • the area information acquisition step acquires external area information regarding the peripheral area of the position where the tire 10 contacts the road surface.
  • the tire force calculation step the physical quantity of the tire 10 acquired in the sensor information acquisition step and the external area information acquired in the area information acquisition step are input to the calculation model 35a to calculate the tire force F. According to this traveling support method, the tire force F can be accurately estimated based on the physical quantity of the tire 10 measured by the sensor 20 and the external region information.
  • the present invention relates to a driving support system and a driving support method that estimate the force generated by tires and friction with the road surface when the vehicle is running and apply it to the driving of the vehicle.

Abstract

A driving assistance system 100 comprises a sensor information acquisition unit 33, a region information acquisition unit 32, and a tire force calculation unit 35. The sensor information acquisition unit 33 acquires a physical quantity of a tire 10 measured by a sensor 20 provided to the tire 10. The region information acquisition unit 32 acquires external region information relating to a peripheral region of a position where the tire 10 contacts a road surface. The tire force calculation unit 35 calculates a tire force F by inputting, to a computation model 35a, the physical quantity of the tire 10 acquired by the sensor information acquisition unit 33 and the external region information acquired by the region information acquisition unit 32.

Description

走行支援システムおよび走行支援方法Driving support system and driving support method
　本発明は、車両の走行時におけるタイヤで発生する力や路面との摩擦を推定して車両の運転に応用する走行支援システムおよび走行支援方法に関する。 The present invention relates to a driving support system and a driving support method that estimate the force generated by tires and friction with the road surface when the vehicle is running and apply it to the driving of the vehicle.
　車両の走行支援システムでは、路面の摩擦値および制動距離を推定し、車両外部の障害物や他車両への衝突回避のために、運転者に代わってブレーキ操作や操舵を自動的に制御し、運転者を支援することが検討されている。 The vehicle driving support system estimates the friction value and braking distance of the road surface, and automatically controls the braking operation and steering on behalf of the driver in order to avoid collisions with obstacles outside the vehicle and other vehicles. Assisting the driver is being considered.
　特許文献１には従来の摩擦値の決定方法および車両機能の制御方法が記載されている。車両のタイヤと車道の間の接触における摩擦値の決定方法は、処理センサ信号を発生させるために、処理規定を使用してセンサ信号を処理するステップであって、この場合、センサ信号は、少なくとも１つの検出装置により読み取られた、車両のタイヤと車道の間の接触位置を有する周辺領域に関する、摩擦値と相関可能な少なくとも状態データを表わすステップと、前記処理センサ信号を使用して摩擦値を決定するステップと、を有する。車両機能の制御方法は、摩擦値を使用して発生された制御信号を受信するステップと、受信制御信号を使用して車両機能を操作するステップと、を有する。 Patent Document 1 describes a conventional method for determining a friction value and a method for controlling a vehicle function. The method of determining the friction value in the contact between the vehicle tires and the roadway is the step of processing the sensor signal using the processing rules to generate the processed sensor signal, in which case the sensor signal is at least A step representing at least state data that can correlate with the friction value for the peripheral region having a contact position between the vehicle tire and the roadway, read by one detector, and the friction value using the processed sensor signal. It has a step to determine. The vehicle function control method includes a step of receiving a control signal generated by using the friction value and a step of operating the vehicle function by using the reception control signal.
特表２０１９－０３４７２１号公報Special Table 2019-034721
　特許文献１に記載の摩擦値の決定方法では、センサ信号の一例として車両の走行データを用いている。本発明者は、タイヤで発生しているタイヤ力をより精度良く推定することで、自動制御による車両の走行支援において改善の余地があることに気づいた。さらに本発明者は、車両の走行を支援するために、タイヤ力および限界タイヤ力に基づいて路面の滑り易さを評価し、道路上の滑り易い箇所について情報を提供し得ることに気付いた。 In the method for determining the friction value described in Patent Document 1, the traveling data of the vehicle is used as an example of the sensor signal. The present inventor has noticed that there is room for improvement in vehicle running support by automatic control by estimating the tire force generated in the tire with higher accuracy. Furthermore, the present inventor has found that the slipperiness of the road surface can be evaluated based on the tire force and the limit tire force to support the running of the vehicle, and information can be provided about the slippery part on the road.
　本発明は、斯かる事情に鑑みてなされたものであり、その目的とするところは、精度良くタイヤ力を推定し、更には限界タイヤ力を推定し車両の走行を支援することができる走行支援システムおよび走行支援方法を提供することにある。 The present invention has been made in view of such circumstances, and an object of the present invention is to provide running support capable of estimating tire force with high accuracy and further estimating limit tire force to support the running of a vehicle. The purpose is to provide a system and a driving support method.
　本発明のある態様は走行支援システムである。走行支援システムは、タイヤに配設されたセンサによって計測されるタイヤの物理量を取得するセンサ情報取得部と、タイヤが路面に接触する位置の周辺領域に関する外部領域情報を取得する領域情報取得部と、前記センサ情報取得部によって取得したタイヤの物理量、および前記領域情報取得部によって取得した外部領域情報を演算モデルに入力してタイヤ力を算出するタイヤ力算出部と、を備える。 One aspect of the present invention is a driving support system. The driving support system includes a sensor information acquisition unit that acquires the physical quantity of the tire measured by a sensor arranged on the tire, and an area information acquisition unit that acquires external area information regarding the peripheral area of the position where the tire contacts the road surface. A tire force calculation unit that calculates the tire force by inputting the physical quantity of the tire acquired by the sensor information acquisition unit and the external area information acquired by the area information acquisition unit into the calculation model.
　本発明の別の態様は走行支援方法である。走行支援方法は、タイヤに配設されたセンサによって計測されるタイヤの物理量を取得するセンサ情報取得ステップと、タイヤが路面に接触する位置の周辺領域に関する外部領域情報を取得する領域情報取得ステップと、前記センサ情報取得ステップによって取得したタイヤの物理量、および前記領域情報取得ステップによって取得した外部領域情報を演算モデルに入力してタイヤ力を算出するタイヤ力算出ステップと、を備える。 Another aspect of the present invention is a traveling support method. The driving support method includes a sensor information acquisition step of acquiring the physical quantity of the tire measured by a sensor arranged on the tire, and an area information acquisition step of acquiring external area information regarding a peripheral area of a position where the tire contacts the road surface. A tire force calculation step of inputting the physical quantity of the tire acquired by the sensor information acquisition step and the external region information acquired by the region information acquisition step into the calculation model to calculate the tire force is provided.
　本発明によれば、精度良くタイヤ力を推定し、更には限界タイヤ力を推定し車両の走行を支援することができる。 According to the present invention, it is possible to estimate the tire force with high accuracy and further estimate the limit tire force to support the running of the vehicle.
実施形態に係る走行支援システムの機能構成を示すブロック図である。It is a block diagram which shows the functional structure of the driving support system which concerns on embodiment. 演算モデルの学習について説明するための模式図である。It is a schematic diagram for demonstrating the learning of the calculation model. タイヤ力推定装置によるタイヤ力推定処理の手順を示すフローチャートである。It is a flowchart which shows the procedure of the tire force estimation processing by a tire force estimation apparatus. タイヤ力Ｆの限界タイヤ力に対するマージンを説明するための模式図である。It is a schematic diagram for demonstrating the margin with respect to the limit tire force of a tire force F. サーバ装置を含む走行支援システムの機能構成を示すブロック図である。It is a block diagram which shows the functional structure of the driving support system including a server device. サーバ装置の機能構成を示すブロック図である。It is a block diagram which shows the functional structure of a server device.
　以下、本発明を好適な実施の形態をもとに図１から図６を参照しながら説明する。各図面に示される同一または同等の構成要素、部材には、同一の符号を付するものとし、適宜重複した説明は省略する。また、各図面における部材の寸法は、理解を容易にするために適宜拡大、縮小して示される。また、各図面において実施の形態を説明する上で重要ではない部材の一部は省略して表示する。 Hereinafter, the present invention will be described with reference to FIGS. 1 to 6 based on a preferred embodiment. The same or equivalent components and members shown in the drawings shall be designated by the same reference numerals, and redundant description will be omitted as appropriate. In addition, the dimensions of the members in each drawing are shown enlarged or reduced as appropriate for easy understanding. In addition, some of the members that are not important for explaining the embodiment in each drawing are omitted and displayed.
（実施形態）
　図１は、実施形態に係る走行支援システム１００の機能構成を示すブロック図である。走行支援システム１００は、タイヤ１０に配設されたセンサ２０によってタイヤ１０で発生している加速度、空気圧および温度等のタイヤ物理量を車両の走行時に計測し、さらにタイヤ１０が路面に接触している位置の周辺領域に関して外部領域情報を取得する。外部領域情報は、タイヤと路面との間の滑り易さに関係する状況を示す情報であり、例えば気象情報、路面の凹凸などの情報である。 (Embodiment)
FIG. 1 is a block diagram showing a functional configuration of the traveling support system 100 according to the embodiment. The travel support system 100 measures tire physical quantities such as acceleration, air pressure, and temperature generated in the tire 10 by a sensor 20 arranged on the tire 10 when the vehicle is traveling, and the tire 10 is in contact with the road surface. Acquires external area information about the area around the position. The external area information is information indicating a situation related to slipperiness between the tire and the road surface, such as weather information and unevenness of the road surface.
　走行支援システム１００は、取得したタイヤ１０の物理量および外部領域情報を演算モデル３５ａに入力し、タイヤ力および限界タイヤ力を算出する。演算モデル３５ａは、例えばニューラルネットワーク等の学習型モデルである。演算モデル３５ａは、タイヤ１０において実際に計測したタイヤ力および限界タイヤ力を教師データとし、演算の実行と演算モデルの更新による学習を繰り返すことによって精度が高められる。限界タイヤ力は、タイヤ１０が路面上で滑り始める直前のタイヤ力であり、タイヤ１０の鉛直方向の荷重に、路面との最大摩擦係数を掛けた値である。 The running support system 100 inputs the acquired physical quantity of the tire 10 and external area information into the calculation model 35a, and calculates the tire force and the limit tire force. The calculation model 35a is a learning model such as a neural network. The accuracy of the calculation model 35a is improved by using the tire force actually measured on the tire 10 and the limit tire force as teacher data and repeating the learning by executing the calculation and updating the calculation model. The limit tire force is the tire force immediately before the tire 10 starts to slide on the road surface, and is a value obtained by multiplying the vertical load of the tire 10 by the maximum coefficient of friction with the road surface.
　走行支援システム１００は、算出したタイヤ力の限界タイヤ力に対するマージンを算出することで、車両が走行した路面上でのタイヤ１０の滑り易さを評価する。走行支援システム１００は、マージンの大きさに基づいて滑り易さの程度を評価する。 The running support system 100 evaluates the slipperiness of the tire 10 on the road surface on which the vehicle has traveled by calculating a margin with respect to the calculated limit tire force of the tire force. The travel support system 100 evaluates the degree of slipperiness based on the size of the margin.
　走行支援システム１００は、精度良く算出されたタイヤ力、限界タイヤ力、およびタイヤ力の限界タイヤ力に対するマージンなどの情報を車両制御装置へ提供し、車両の走行を支援することができる。また、走行支援システム１００は、外部装置としてのサーバ装置等を含み、外部装置において、評価した路面の滑り易さの程度を地図上での位置に対応付けて蓄積し、蓄積された情報を配信して提供することができる。例えば、提供された路面の滑り易さの情報は、車両に設けられた表示装置に表示される地図上において、滑り易い位置や区間を明示すること等によって利用することができる。 The travel support system 100 can provide information such as an accurately calculated tire force, a limit tire force, and a margin for the limit tire force of the tire force to the vehicle control device to support the vehicle travel. Further, the traveling support system 100 includes a server device or the like as an external device, accumulates the evaluated degree of slipperiness of the road surface in association with the position on the map in the external device, and distributes the accumulated information. Can be provided. For example, the provided information on the slipperiness of the road surface can be used by clearly indicating the slippery position or section on the map displayed on the display device provided in the vehicle.
　走行支援システム１００は、センサ２０およびタイヤ力推定装置３０を備える。センサ２０は、加速度センサ２１、圧力センサ２２および温度センサ２３等を有し、加速度、タイヤ空気圧およびタイヤ温度などタイヤ１０における物理量を計測する。センサ２０は、タイヤ１０に生じる歪を計測するために歪ゲージを有していてもよい。これらのセンサは、タイヤ１０の物理量として、タイヤ１０の変形や動きに関わる物理量を計測している。 The driving support system 100 includes a sensor 20 and a tire force estimation device 30. The sensor 20 includes an acceleration sensor 21, a pressure sensor 22, a temperature sensor 23, and the like, and measures physical quantities in the tire 10 such as acceleration, tire pressure, and tire temperature. The sensor 20 may have a strain gauge to measure the strain generated in the tire 10. These sensors measure the physical quantity related to the deformation and movement of the tire 10 as the physical quantity of the tire 10.
　加速度センサ２１は、タイヤ１０のゴム材料等で形成されたタイヤ本体部分またはタイヤ１０の一部をなすホイール１５に配設されており、タイヤ１０とともに機械的に運動しつつ、タイヤ１０に生じる加速度を計測する。加速度センサ２１は、タイヤ１０の周方向、軸方向および径方向の３軸における加速度を計測する。圧力センサ２２および温度センサ２３は、例えばタイヤ１０のエアバルブへの装着やホイール１５への固定によって配設されており、それぞれタイヤ１０の空気圧および温度を計測する。また圧力センサ２２および温度センサ２３は、タイヤ１０のインナーライナー等に配設されていてもよい。 The acceleration sensor 21 is arranged on a tire body portion formed of a rubber material of the tire 10 or a wheel 15 forming a part of the tire 10, and accelerates generated in the tire 10 while mechanically moving together with the tire 10. To measure. The acceleration sensor 21 measures the acceleration of the tire 10 in the three axes of the circumferential direction, the axial direction, and the radial direction. The pressure sensor 22 and the temperature sensor 23 are arranged, for example, by mounting the tire 10 on the air valve or fixing the tire 10 to the wheel 15, and measure the air pressure and temperature of the tire 10, respectively. Further, the pressure sensor 22 and the temperature sensor 23 may be arranged on the inner liner or the like of the tire 10.
　センサ２０は、タイヤ１０における加速度および歪、タイヤ空気圧、並びにタイヤ温度などタイヤ１０の物理量を計測しており、計測したデータをタイヤ力推定装置３０へ出力する。タイヤ力推定装置３０は、センサ２０で計測されたデータに基づいてタイヤ力Ｆを推定する。 The sensor 20 measures physical quantities of the tire 10 such as acceleration and strain of the tire 10, tire air pressure, and tire temperature, and outputs the measured data to the tire force estimation device 30. The tire force estimation device 30 estimates the tire force F based on the data measured by the sensor 20.
　タイヤ１０は、各タイヤを識別するために、例えば固有の識別情報が付与されたＲＦＩＤ１１等が取り付けられていてもよい。例えば、タイヤ１０に取り付けたＲＦＩＤ１１の固有情報に応じて、演算モデル３５ａを予め用意したデータ群の中から選択して設定してもよいし、またはサーバ装置などで提供されるデータベースから選択するようにしてもよい。また、ＲＦＩＤ１１の固有情報に対してタイヤ１０の仕様が記録され、更にタイヤ１０の仕様に応じた演算モデル３５ａがデータベースで提供されてもよい。ＲＦＩＤ１１の固有情報からタイヤ１０の仕様を呼び出し、演算モデル３５ａを設定してもよいし、呼び出したタイヤ１０の仕様に応じた演算モデル３５ａをデータベースから選択するようにしてもよい。 The tire 10 may be equipped with, for example, an RFID 11 or the like to which unique identification information is attached in order to identify each tire. For example, the calculation model 35a may be selected and set from a data group prepared in advance according to the unique information of the RFID 11 attached to the tire 10, or may be selected from a database provided by a server device or the like. It may be. Further, the specifications of the tire 10 may be recorded with respect to the unique information of the RFID 11, and the calculation model 35a corresponding to the specifications of the tire 10 may be provided in the database. The specifications of the tire 10 may be called from the unique information of the RFID 11, and the calculation model 35a may be set, or the calculation model 35a according to the specifications of the called tire 10 may be selected from the database.
　タイヤ力推定装置３０は、位置情報取得部３１、領域情報取得部３２、センサ情報取得部３３、通信部３４およびタイヤ力算出部３５を有する。タイヤ力推定装置３０は、例えばＰＣ（パーソナルコンピュータ）等の情報処理装置である。タイヤ力推定装置３０における各部は、ハードウェア的には、コンピュータのＣＰＵをはじめとする電子素子や機械部品などで実現でき、ソフトウェア的にはコンピュータプログラムなどによって実現されるが、ここでは、それらの連携によって実現される機能ブロックを描いている。したがって、これらの機能ブロックはハードウェア、ソフトウェアの組合せによっていろいろな形態で実現できることは、当業者には理解されるところである。 The tire force estimation device 30 includes a position information acquisition unit 31, an area information acquisition unit 32, a sensor information acquisition unit 33, a communication unit 34, and a tire force calculation unit 35. The tire force estimation device 30 is an information processing device such as a PC (personal computer). Each part of the tire force estimation device 30 can be realized by an electronic element such as a computer CPU or a mechanical component in terms of hardware, and can be realized by a computer program or the like in terms of software. It depicts a functional block realized by cooperation. Therefore, it is understood by those skilled in the art that these functional blocks can be realized in various forms by combining hardware and software.
　位置情報取得部３１は、ＧＰＳ受信機５０によって計測される車両の位置データを取得し、領域情報取得部３２へ出力する。領域情報取得部３２は、位置情報取得部３１から入力される車両の位置データに基づき、タイヤ１０が路面に接触している位置の周辺領域について、気象情報、路面の凹凸などの外部領域情報を通信部３４を介して取得する。気象情報、路面の凹凸などの外部領域情報は、タイヤと路面との間の滑り易さに関係する状況を示す情報であり、タイヤ力および限界タイヤ力と相関関係を有しており、演算モデル３５ａへの入力要素となる。領域情報取得部３２は、気象情報、路面の凹凸など情報のほか、気温、時間帯、道路交通情報による路面の凍結情報など、タイヤ力および限界タイヤ力と相関関係を有する情報を取得するようにしてもよい。 The position information acquisition unit 31 acquires the vehicle position data measured by the GPS receiver 50 and outputs it to the area information acquisition unit 32. Based on the vehicle position data input from the position information acquisition unit 31, the area information acquisition unit 32 provides external area information such as weather information and road surface unevenness with respect to the peripheral area of the position where the tire 10 is in contact with the road surface. Obtained via the communication unit 34. External area information such as weather information and road surface unevenness is information indicating a situation related to slipperiness between the tire and the road surface, has a correlation with the tire force and the limit tire force, and is a calculation model. It becomes an input element to 35a. The area information acquisition unit 32 acquires information having a correlation with the tire force and the limit tire force, such as weather information, information such as road surface unevenness, and road surface freezing information based on temperature, time zone, and road traffic information. You may.
　センサ情報取得部３３は、無線通信等によりセンサ２０で計測された加速度、タイヤ空気圧およびタイヤ温度等のタイヤ物理量を取得する。通信部３４は、外部装置との間で有線または無線通信等によって通信し、領域情報取得部３２で取得する外部領域情報を当該外部装置から受信する。また通信部３４は、後述するように位置データ、タイヤ力Ｆ、限界タイヤ力およびマージン情報を外部のサーバ装置へ送信する。 The sensor information acquisition unit 33 acquires physical tire quantities such as acceleration, tire pressure, and tire temperature measured by the sensor 20 by wireless communication or the like. The communication unit 34 communicates with the external device by wired or wireless communication or the like, and receives the external area information acquired by the area information acquisition unit 32 from the external device. Further, the communication unit 34 transmits the position data, the tire force F, the limit tire force, and the margin information to the external server device as described later.
　タイヤ力算出部３５は、演算モデル３５ａおよび補正処理部３５ｂを有し、領域情報取得部３２およびセンサ情報取得部３３からの情報を演算モデル３５ａに入力し、タイヤ力Ｆおよび限界タイヤ力を算出する。図１に示すように、タイヤ力Ｆは、タイヤ１０の前後方向の前後力Ｆｘ、横方向の横力Ｆｙ、および鉛直方向の荷重Ｆｚの３軸方向成分を有する。タイヤ力算出部３５は、これら３軸方向成分のすべてを算出してもよいし、少なくともいずれか１成分の算出または任意の組合せによる２成分の算出を行うようにしてもよい。 The tire force calculation unit 35 has a calculation model 35a and a correction processing unit 35b, inputs information from the area information acquisition unit 32 and the sensor information acquisition unit 33 into the calculation model 35a, and calculates the tire force F and the limit tire force. To do. As shown in FIG. 1, the tire force F has three axial components of the front-rear front-rear force Fx of the tire 10, the lateral force Fy in the lateral direction, and the load Fz in the vertical direction. The tire force calculation unit 35 may calculate all of these three axial components, or may calculate at least one component or two components by any combination.
　タイヤ力算出部３５は、演算モデル３５ａによって算出したタイヤ力Ｆおよび限界タイヤ力に基づいて、タイヤ力Ｆの限界タイヤ力に対するマージンを算出する。タイヤ力Ｆの限界タイヤ力に対するマージンは、タイヤ力Ｆが限界タイヤ力よりも小さいほど大きい。 The tire force calculation unit 35 calculates the margin of the tire force F with respect to the limit tire force based on the tire force F and the limit tire force calculated by the calculation model 35a. The margin of the tire force F with respect to the limit tire force is larger as the tire force F is smaller than the limit tire force.
　演算モデル３５ａは、ニューラルネットワーク等の学習型モデルを用いる。演算モデル３５ａは、例えばＣＮＮ（Convolutional Neural Network）型であり、その原型であるいわゆるＬｅＮｅｔで使用された畳み込み演算およびプーリング演算を備える学習型モデルなどを用いる。演算モデル３５ａは、入力層に入力されたデータに対して畳み込み演算およびプーリング演算などを用いて特徴量を抽出して中間層の各ノードへ伝達し、中間層の各ノードに対して線形演算等を実行して全結合し、出力層の各ノードへ結び付ける。全結合では、線形演算に加えて、活性化関数などを用いて非線形演算を実行するようにしてもよい。演算モデル３５ａの出力層の各ノードには、３軸方向のタイヤ力Ｆおよび限界タイヤ力が出力される。 The calculation model 35a uses a learning model such as a neural network. The calculation model 35a is, for example, a CNN (Convolutional Neural Network) type, and uses a learning type model including a convolutional operation and a pooling operation used in the so-called LeNet which is the prototype thereof. The calculation model 35a extracts the features of the data input to the input layer by using a convolution operation and a pooling operation, transmits the features to each node of the intermediate layer, and performs a linear operation or the like for each node of the intermediate layer. Is executed to fully connect and connect to each node of the output layer. In the full coupling, in addition to the linear operation, a non-linear operation may be executed by using an activation function or the like. The tire force F and the limit tire force in the three axial directions are output to each node of the output layer of the calculation model 35a.
　図２は演算モデル３５ａの学習について説明するための模式図である。演算モデル３５ａへの入力データは、センサ情報取得部３３によって取得されたタイヤ物理量、および領域情報取得部３２によって取得された外部領域情報等である。タイヤ物理量には、加速度、タイヤ空気圧、タイヤ温度およびタイヤに生じる歪などを用いる。外部領域情報には、天候、気温および降水量などの気象情報、並びに、路面の凹凸、温度および凍結状態等の路面情報を用いる。入力データは、これらの他、車両に搭載されたデジタルタコグラフのデータによる車重、速度などを用いてもよい。 FIG. 2 is a schematic diagram for explaining the learning of the calculation model 35a. The input data to the calculation model 35a is the tire physical quantity acquired by the sensor information acquisition unit 33, the external area information acquired by the area information acquisition unit 32, and the like. For the physical quantity of the tire, acceleration, tire pressure, tire temperature, strain generated in the tire, and the like are used. As the external area information, meteorological information such as weather, temperature and precipitation, and road surface information such as road surface unevenness, temperature and frozen state are used. In addition to these, the input data may use the vehicle weight, speed, etc. based on the data of the digital tachograph mounted on the vehicle.
　演算モデル３５ａの学習の際には、演算結果としてのタイヤ力Ｆおよび限界タイヤ力と、教師データとを比較して演算モデル３５ａの更新を繰り返すことによって演算モデル３５ａの精度が高められる。また、演算モデル３５ａは、基本的にタイヤ１０の仕様に応じて例えばモデル内の全結合部における階層数等の構成や重みづけが変わるが、各仕様のタイヤ１０（ホイールを含む）での回転試験において演算モデル３５ａの学習を実行することができる。 When learning the calculation model 35a, the accuracy of the calculation model 35a is improved by comparing the tire force F and the limit tire force as the calculation result with the teacher data and repeating the update of the calculation model 35a. Further, in the calculation model 35a, for example, the configuration and weighting of the number of layers in all the joints in the model change according to the specifications of the tire 10, but the rotation of the tire 10 (including the wheels) of each specification. The learning of the calculation model 35a can be performed in the test.
　但し、厳密にタイヤ１０の仕様ごとに演算モデル３５ａの学習を実行する必要性はない。例えば乗用車用タイヤ、トラック用タイヤなどのタイプ別に演算モデル３５ａを学習させて構築し、タイヤ力Ｆおよび限界タイヤ力が一定の誤差範囲内で推定されるようにすることで、複数の仕様に含まれるタイヤ１０に対して１つの演算モデル３５ａを共用し、演算モデル数を低減してもよい。また演算モデル３５ａは、実際の車両にタイヤ１０を装着し、該車両を試験走行させて演算モデル３５ａの学習を実行することもできる。タイヤ１０の仕様には、例えばタイヤサイズ、タイヤ幅、扁平率、タイヤ強度、タイヤ外径、ロードインデックス、製造年月日など、タイヤの性能に関する情報が含まれる。 However, it is not necessary to strictly learn the calculation model 35a for each tire 10 specification. For example, the calculation model 35a is trained and constructed for each type of passenger car tire, truck tire, etc., and the tire force F and the limit tire force are estimated within a certain error range, so that the tire force F and the limit tire force are included in a plurality of specifications. One calculation model 35a may be shared for the tire 10 to be used, and the number of calculation models may be reduced. Further, the calculation model 35a can also carry out learning of the calculation model 35a by mounting the tire 10 on an actual vehicle and running the vehicle in a test run. The specifications of the tire 10 include information on tire performance such as tire size, tire width, flatness, tire strength, tire outer diameter, road index, and date of manufacture.
　また演算モデル３５ａは、タイヤ１０を接地させる接地面の路面摩擦係数（最大摩擦係数）を変えて回転試験を行って学習させてもよい。さらには、実際の車両にタイヤ１０を装着し、該車両を路面摩擦係数の異なる路面を試験走行させて演算モデル３５ａの学習を実行することもできる。 Further, the calculation model 35a may be learned by performing a rotation test by changing the road surface friction coefficient (maximum friction coefficient) of the ground contact surface on which the tire 10 is grounded. Further, it is also possible to mount the tire 10 on an actual vehicle and run the vehicle on a test run on a road surface having a different coefficient of friction on the road surface to execute learning of the calculation model 35a.
　補正処理部３５ｂは、タイヤ１０の状態に基づいて演算モデル３５ａを補正する。タイヤ１０は、車両への装着時にアライメント誤差が生じ、経時的にゴム硬度等の物性値が変化し、走行することによって摩耗が進行する。アライメント誤差、物性値や摩耗等の要素を含むタイヤ１０の状態が使用状況によって変化し、演算モデル３５ａによるタイヤ力Ｆおよび限界タイヤ力の算出に誤差が生じる。補正処理部３５ｂは、演算モデル３５ａの誤差を低減するためにタイヤ１０の状態に応じた補正項を演算モデル３５ａに付加する処理を行う。 The correction processing unit 35b corrects the calculation model 35a based on the state of the tire 10. Alignment error occurs when the tire 10 is mounted on a vehicle, physical property values such as rubber hardness change with time, and wear progresses as the tire runs. The state of the tire 10 including factors such as alignment error, physical property value, and wear changes depending on the usage conditions, and an error occurs in the calculation of the tire force F and the limit tire force by the calculation model 35a. The correction processing unit 35b performs a process of adding a correction term according to the state of the tire 10 to the calculation model 35a in order to reduce the error of the calculation model 35a.
　次に走行支援システム１００の動作を説明する。図３は、タイヤ力推定装置３０によるタイヤ力推定処理の手順を示すフローチャートである。タイヤ力推定装置３０の位置情報取得部３１により位置データを取得し、領域情報取得部３２により外部領域情報の取得を開始する（Ｓ１）。センサ情報取得部３３は、センサ２０で計測されたタイヤ１０における加速度、タイヤ空気圧およびタイヤ温度などのタイヤ物理量の取得を開始する（Ｓ２）。 Next, the operation of the driving support system 100 will be described. FIG. 3 is a flowchart showing the procedure of the tire force estimation process by the tire force estimation device 30. The position information acquisition unit 31 of the tire force estimation device 30 acquires the position data, and the area information acquisition unit 32 starts the acquisition of the external area information (S1). The sensor information acquisition unit 33 starts acquiring tire physical quantities such as acceleration, tire air pressure, and tire temperature in the tire 10 measured by the sensor 20 (S2).
　タイヤ力算出部３５は、外部領域情報およびタイヤ物理量を演算モデル３５ａに入力し、タイヤ力Ｆおよび限界タイヤ力を算出する（Ｓ３）。タイヤ力算出部３５は、算出したタイヤ力Ｆの限界タイヤ力に対するマージンを算出し（Ｓ４）、処理を終了する。タイヤ力推定装置３０は、ステップＳ１からステップＳ４までの処理を繰り返すことによって、時系列的にタイヤ力Ｆ、限界タイヤ力およびマージンを算出して推定する。 The tire force calculation unit 35 inputs the external region information and the tire physical quantity into the calculation model 35a, and calculates the tire force F and the limit tire force (S3). The tire force calculation unit 35 calculates a margin of the calculated tire force F with respect to the limit tire force (S4), and ends the process. The tire force estimation device 30 calculates and estimates the tire force F, the limit tire force, and the margin in time series by repeating the processes from step S1 to step S4.
　図４は、タイヤ力Ｆの限界タイヤ力に対するマージンを説明するための模式図である。図４では、横軸にタイヤ力Ｆの前後力Ｆｘ、縦軸にタイヤ力Ｆの横力Ｆｙをとり、原点を中心とする円で限界タイヤ力を示している。演算モデル３５ａによって算出されたタイヤ力Ｆ１およびＦ２について、タイヤ力Ｆ１はタイヤ力Ｆ２よりも小さく、限界タイヤ力に対してマージンが大きい。 FIG. 4 is a schematic diagram for explaining the margin of the tire force F with respect to the limit tire force. In FIG. 4, the horizontal axis represents the front-rear force Fx of the tire force F, the vertical axis represents the lateral force Fy of the tire force F, and the circle centered on the origin indicates the limit tire force. Regarding the tire forces F1 and F2 calculated by the calculation model 35a, the tire force F1 is smaller than the tire force F2, and the margin is large with respect to the limit tire force.
　限界タイヤ力は、タイヤ１０と路面との最大摩擦係数に依存して大きさが変わる。また、タイヤ力Ｆ１は、車両の走行ルートのカーブなどで車両の左右方向に加速度が生じる場合などに大きくなる。一般に、カーブが多い道路、降雨確率が高い地域などでは、タイヤ力Ｆが大きく、限界タイヤ力が小さくなる傾向にあり、マージンは小さくなる。 The limit tire force changes in magnitude depending on the maximum coefficient of friction between the tire 10 and the road surface. Further, the tire force F1 becomes large when acceleration occurs in the left-right direction of the vehicle due to a curve of the traveling route of the vehicle or the like. Generally, on a road with many curves, an area with a high probability of rainfall, etc., the tire force F tends to be large, the limit tire force tends to be small, and the margin is small.
　走行支援システム１００は、タイヤ物理量および外部領域情報を入力とする演算モデル３５ａによって、タイヤ力Ｆ、限界タイヤ力およびマージンの算出精度を高めることができる。タイヤ力推定装置３０は、算出したタイヤ力Ｆ、限界タイヤ力およびマージンを車両制御装置等へ出力する。例えば車両制御装置は、タイヤ力推定装置３０から入力されたタイヤ力Ｆ、限界タイヤ力およびマージンに基づいて、制動距離の推定、車両制御および自動運転への適用、更には車両の安全走行に関する情報の報知などを行うことができる。 The running support system 100 can improve the calculation accuracy of the tire force F, the limit tire force, and the margin by the calculation model 35a in which the physical quantity of the tire and the external region information are input. The tire force estimation device 30 outputs the calculated tire force F, the limit tire force, and the margin to the vehicle control device or the like. For example, the vehicle control device estimates the braking distance based on the tire force F, the limit tire force and the margin input from the tire force estimation device 30, application to vehicle control and automatic driving, and information on safe driving of the vehicle. Can be notified.
　図５はサーバ装置７を含む走行支援システム１００の機能構成を示すブロック図であり、図６はサーバ装置７の機能構成を示すブロック図である。タイヤ力推定装置３０は、位置データ、タイヤ力Ｆ、限界タイヤ力およびマージンを算出し、通信ネットワーク９を介してサーバ装置７へ送信する。サーバ装置７は、受信した位置データ、タイヤ力Ｆ、限界タイヤ力およびマージンを蓄積し、路面の滑り易さの程度を評価する。 FIG. 5 is a block diagram showing the functional configuration of the traveling support system 100 including the server device 7, and FIG. 6 is a block diagram showing the functional configuration of the server device 7. The tire force estimation device 30 calculates the position data, the tire force F, the limit tire force, and the margin, and transmits the position data, the tire force F, the limit tire force, and the margin to the server device 7 via the communication network 9. The server device 7 accumulates the received position data, the tire force F, the limit tire force, and the margin, and evaluates the degree of slipperiness of the road surface.
　サーバ装置７は、通信部７１、記憶部７２およびタイヤ路面状態評価部７３を備える。通信部７１は、通信ネットワーク９１を介して車両から送信される位置データ、タイヤ力Ｆ、限界タイヤ力およびマージンを受信する。記憶部７２は、ハードディスク等の記憶装置で構成されており、通信部７１によって受信した位置データ、タイヤ力Ｆ、限界タイヤ力およびマージンを記憶する。 The server device 7 includes a communication unit 71, a storage unit 72, and a tire road surface condition evaluation unit 73. The communication unit 71 receives the position data, the tire force F, the limit tire force, and the margin transmitted from the vehicle via the communication network 91. The storage unit 72 is composed of a storage device such as a hard disk, and stores the position data, the tire force F, the limit tire force, and the margin received by the communication unit 71.
　タイヤ路面状態評価部７３は、記憶部７２に記憶されたタイヤ力Ｆ、限界タイヤ力およびマージンを読み出し、現在のタイヤ摩擦特性（種別や摩耗度などの影響によるグリップの低下度など）と路面の滑り易さの程度を評価し、位置データに対応付けてタイヤの状態（空気圧やタイヤ温度など）、タイヤ摩擦特性、および滑り易さの程度を記憶部７２に記憶させる。路面の滑り易さの程度は、例えば多段階で評価されてもよい。 The tire road surface condition evaluation unit 73 reads out the tire force F, the limit tire force and the margin stored in the storage unit 72, and the current tire friction characteristics (such as the degree of decrease in grip due to the influence of the type and the degree of wear) and the road surface. The degree of slipperiness is evaluated, and the tire state (air pressure, tire temperature, etc.), tire friction characteristics, and the degree of slipperiness are stored in the storage unit 72 in association with the position data. The degree of slipperiness of the road surface may be evaluated in multiple stages, for example.
　サーバ装置７は、記憶部７２に記憶された位置データおよび路面の滑り易さの程度を車両側へ通信部７１を介して配信する。配信された位置データおよび路面の滑り易さの程度に基づいて、車両に設けられた表示装置に表示される地図上において、滑り易い位置や区間を明示すること等によって、車両の走行を支援することができる。また、滑り易い位置や区間などを把握することによって、補修などの道路の保守管理に利用することができる。 The server device 7 distributes the position data stored in the storage unit 72 and the degree of slipperiness of the road surface to the vehicle side via the communication unit 71. Supports the running of the vehicle by clearly indicating the slippery position and section on the map displayed on the display device provided on the vehicle based on the delivered position data and the degree of slipperiness of the road surface. be able to. In addition, by grasping slippery positions and sections, it can be used for road maintenance management such as repair.
　次に実施形態に係る走行支援システム１００の特徴について説明する。
　実施形態に係る走行支援システム１００は、センサ情報取得部３３、領域情報取得部３２およびタイヤ力算出部３５を備える。センサ情報取得部３３は、タイヤ１０に配設されたセンサ２０によって計測されるタイヤ１０の物理量を取得する。領域情報取得部３２は、タイヤ１０が路面に接触する位置の周辺領域に関する外部領域情報を取得する。タイヤ力算出部３５は、センサ情報取得部３３によって取得したタイヤ１０の物理量、および領域情報取得部３２によって取得した外部領域情報を演算モデル３５ａに入力してタイヤ力Ｆを算出する。これにより、走行支援システム１００は、センサ２０によって計測されるタイヤ１０の物理量、および外部領域情報に基づいてタイヤ力Ｆを精度良く推定することができる。 Next, the features of the traveling support system 100 according to the embodiment will be described.
The traveling support system 100 according to the embodiment includes a sensor information acquisition unit 33, an area information acquisition unit 32, and a tire force calculation unit 35. The sensor information acquisition unit 33 acquires the physical quantity of the tire 10 measured by the sensor 20 arranged on the tire 10. The area information acquisition unit 32 acquires external area information regarding the peripheral area of the position where the tire 10 comes into contact with the road surface. The tire force calculation unit 35 calculates the tire force F by inputting the physical quantity of the tire 10 acquired by the sensor information acquisition unit 33 and the external area information acquired by the area information acquisition unit 32 into the calculation model 35a. As a result, the traveling support system 100 can accurately estimate the tire force F based on the physical quantity of the tire 10 measured by the sensor 20 and the external region information.
　またタイヤ力算出部３５は、更に演算モデル３５ａにより限界タイヤ力を算出する。これにより、走行支援システム１００は、算出したタイヤ力Ｆおよび限界タイヤ力によって、車両の走行を支援することができる。 Further, the tire force calculation unit 35 further calculates the limit tire force by the calculation model 35a. As a result, the traveling support system 100 can support the traveling of the vehicle by the calculated tire force F and the limit tire force.
　またタイヤ力算出部３５によって算出されたタイヤ力Ｆの限界タイヤ力に対するマージンを算出し、外部装置であるサーバ装置７へ送信する送信部としての通信部３４を更に備える。これにより、走行支援システム１００は、車両の走行の際に算出されたタイヤ力Ｆの限界タイヤ力に対するマージンをサーバ装置７へ提供し、サーバ装置７において路面の滑り易さに関する評価や、データ蓄積を図ることができる。 Further, a communication unit 34 as a transmission unit that calculates a margin of the tire force F calculated by the tire force calculation unit 35 with respect to the limit tire force and transmits the margin to the server device 7 which is an external device is further provided. As a result, the travel support system 100 provides the server device 7 with a margin for the limit tire force of the tire force F calculated when the vehicle is traveling, and the server device 7 evaluates the slipperiness of the road surface and accumulates data. Can be planned.
　外部装置であるサーバ装置７は、通信部３４によって送信されたマージンに基づいて滑り易さの程度を評価するタイヤ路面状態評価部７３、および車両の位置と滑り易さの程度を対応付けて記憶する記憶部７２を有する。これにより、走行支援システム１００は、車両の走行の際に算出されたタイヤ力Ｆの限界タイヤ力に対するマージンに基づいて路面の滑り易さを評価し、車両の走行を支援することができる。 The server device 7, which is an external device, stores the tire road surface condition evaluation unit 73, which evaluates the degree of slipperiness based on the margin transmitted by the communication unit 34, and the position of the vehicle and the degree of slipperiness in association with each other. It has a storage unit 72 to be used. As a result, the traveling support system 100 can evaluate the slipperiness of the road surface based on the margin of the tire force F calculated when the vehicle is traveling with respect to the limit tire force, and support the traveling of the vehicle.
　走行支援方法は、センサ情報取得ステップ、領域情報取得ステップおよびタイヤ力算出ステップを備える。センサ情報取得ステップは、タイヤ１０に配設されたセンサ２０によって計測されるタイヤ１０の物理量を取得する。領域情報取得ステップは、タイヤ１０が路面に接触する位置の周辺領域に関する外部領域情報を取得する。タイヤ力算出ステップは、センサ情報取得ステップによって取得したタイヤ１０の物理量、および領域情報取得ステップによって取得した外部領域情報を演算モデル３５ａに入力してタイヤ力Ｆを算出する。この走行支援方法によれば、センサ２０によって計測されるタイヤ１０の物理量、および外部領域情報に基づいてタイヤ力Ｆを精度良く推定することができる。 The driving support method includes a sensor information acquisition step, an area information acquisition step, and a tire force calculation step. The sensor information acquisition step acquires the physical quantity of the tire 10 measured by the sensor 20 arranged on the tire 10. The area information acquisition step acquires external area information regarding the peripheral area of the position where the tire 10 contacts the road surface. In the tire force calculation step, the physical quantity of the tire 10 acquired in the sensor information acquisition step and the external area information acquired in the area information acquisition step are input to the calculation model 35a to calculate the tire force F. According to this traveling support method, the tire force F can be accurately estimated based on the physical quantity of the tire 10 measured by the sensor 20 and the external region information.
　以上、本発明の実施の形態をもとに説明した。これらの実施の形態は例示であり、いろいろな変形および変更が本発明の特許請求範囲内で可能なこと、またそうした変形例および変更も本発明の特許請求の範囲にあることは当業者に理解されるところである。従って、本明細書での記述および図面は限定的ではなく例証的に扱われるべきものである。 The above description has been made based on the embodiment of the present invention. It will be appreciated by those skilled in the art that these embodiments are exemplary and that various modifications and modifications are possible within the claims of the invention, and that such modifications and modifications are also within the claims of the present invention. It is about to be done. Therefore, the descriptions and drawings herein should be treated as exemplary rather than limiting.
　本発明は、車両の走行時におけるタイヤで発生する力や路面との摩擦を推定して車両の運転に応用する走行支援システムおよび走行支援方法に関する。 The present invention relates to a driving support system and a driving support method that estimate the force generated by tires and friction with the road surface when the vehicle is running and apply it to the driving of the vehicle.
　１０　タイヤ、　２０　センサ、　３２　領域情報取得部、
　３３　センサ情報取得部、　３４　通信部（送信部）、　３５　タイヤ力算出部、
　３５ａ　演算モデル、　７　サーバ装置（外部装置）、　７２　記憶部、
　７３　タイヤ路面状態評価部、　１００　走行支援システム。 10 tires, 20 sensors, 32 area information acquisition unit,
33 Sensor information acquisition unit, 34 Communication unit (transmission unit), 35 Tire force calculation unit,
35a Arithmetic model, 7 Server device (external device), 72 Storage unit,
73 Tire road surface condition evaluation department, 100 Driving support system.

Claims (5)

  1. 　タイヤに配設されたセンサによって計測されるタイヤの物理量を取得するセンサ情報取得部と、
    　タイヤが路面に接触する位置の周辺領域に関する外部領域情報を取得する領域情報取得部と、
    　前記センサ情報取得部によって取得したタイヤの物理量、および前記領域情報取得部によって取得した外部領域情報を演算モデルに入力してタイヤ力を算出するタイヤ力算出部と、
    を備えることを特徴とする走行支援システム。     A sensor information acquisition unit that acquires the physical quantity of the tire measured by a sensor placed on the tire,
    An area information acquisition unit that acquires external area information about the area around the position where the tire contacts the road surface,
    A tire force calculation unit that calculates the tire force by inputting the physical quantity of the tire acquired by the sensor information acquisition unit and the external area information acquired by the area information acquisition unit into the calculation model.
    A driving support system characterized by being equipped with.
  2. 　前記タイヤ力算出部は、更に前記演算モデルにより限界タイヤ力を算出することを特徴とする請求項１に記載の走行支援システム。 The running support system according to claim 1, wherein the tire force calculation unit further calculates a limit tire force by the calculation model.
  3. 　前記タイヤ力算出部によって算出されたタイヤ力の限界タイヤ力に対するマージンを算出し、外部装置へ送信する送信部を更に備えることを特徴とする請求項２に記載の走行支援システム。 The traveling support system according to claim 2, further comprising a transmission unit that calculates a margin with respect to the limit tire force of the tire force calculated by the tire force calculation unit and transmits the margin to an external device.
  4. 　前記外部装置は、前記送信部によって送信されたマージンに基づいて滑り易さの程度を評価するタイヤ路面状態評価部、および車両の位置と滑り易さの程度を対応付けて記憶する記憶部を有することを特徴とする請求項３に記載の走行支援システム。 The external device has a tire road surface condition evaluation unit that evaluates the degree of slipperiness based on the margin transmitted by the transmission unit, and a storage unit that stores the position of the vehicle and the degree of slipperiness in association with each other. The driving support system according to claim 3, wherein the vehicle is characterized by the above.
  5. 　タイヤに配設されたセンサによって計測されるタイヤの物理量を取得するセンサ情報取得ステップと、
    　タイヤが路面に接触する位置の周辺領域に関する外部領域情報を取得する領域情報取得ステップと、
    　前記センサ情報取得ステップによって取得したタイヤの物理量、および前記領域情報取得ステップによって取得した外部領域情報を演算モデルに入力してタイヤ力を算出するタイヤ力算出ステップと、
    を備えることを特徴とする走行支援方法。     A sensor information acquisition step that acquires the physical quantity of the tire measured by a sensor placed on the tire, and
    Area information acquisition step to acquire external area information about the peripheral area of the position where the tire contacts the road surface,
    A tire force calculation step for calculating the tire force by inputting the physical quantity of the tire acquired by the sensor information acquisition step and the external area information acquired by the area information acquisition step into the calculation model.
    A driving support method characterized by being provided with.
PCT/JP2020/043808 2019-12-02 2020-11-25 Driving assistance system and driving assistance method WO2021111943A1 (en)

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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0699761A (en) * 1992-09-17 1994-04-12 Toyota Motor Corp Wheel movement load factor outputting device
JPH11263152A (en) * 1998-03-18 1999-09-28 Toyota Central Res & Dev Lab Inc Braking and driving force control device
JP2004074845A (en) * 2002-08-12 2004-03-11 Toyota Central Res & Dev Lab Inc Self-aligning torque reference value calculating device and road surface friction state resumption device
JP2010083302A (en) * 2008-09-30 2010-04-15 Nissan Motor Co Ltd Vehicle deceleration controller and method thereof
JP2018096785A (en) * 2016-12-12 2018-06-21 東洋ゴム工業株式会社 Turning simulation method, device and program
JP2018517978A (en) * 2015-05-20 2018-07-05 コンパニー ゼネラール デ エタブリッスマン ミシュラン How to determine the operating speed limit
JP2018173765A (en) * 2017-03-31 2018-11-08 株式会社トヨタマップマスター Road friction coefficient management device, server device, methods therefor, computer program and recording medium with computer program recorded thereon

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH0699761A (en) * 1992-09-17 1994-04-12 Toyota Motor Corp Wheel movement load factor outputting device
JPH11263152A (en) * 1998-03-18 1999-09-28 Toyota Central Res & Dev Lab Inc Braking and driving force control device
JP2004074845A (en) * 2002-08-12 2004-03-11 Toyota Central Res & Dev Lab Inc Self-aligning torque reference value calculating device and road surface friction state resumption device
JP2010083302A (en) * 2008-09-30 2010-04-15 Nissan Motor Co Ltd Vehicle deceleration controller and method thereof
JP2018517978A (en) * 2015-05-20 2018-07-05 コンパニー ゼネラール デ エタブリッスマン ミシュラン How to determine the operating speed limit
JP2018096785A (en) * 2016-12-12 2018-06-21 東洋ゴム工業株式会社 Turning simulation method, device and program
JP2018173765A (en) * 2017-03-31 2018-11-08 株式会社トヨタマップマスター Road friction coefficient management device, server device, methods therefor, computer program and recording medium with computer program recorded thereon

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