WO2010097943A1 - 車両相対位置推定装置及び車両相対位置推定方法 - Google Patents
車両相対位置推定装置及び車両相対位置推定方法 Download PDFInfo
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- WO2010097943A1 WO2010097943A1 PCT/JP2009/053720 JP2009053720W WO2010097943A1 WO 2010097943 A1 WO2010097943 A1 WO 2010097943A1 JP 2009053720 W JP2009053720 W JP 2009053720W WO 2010097943 A1 WO2010097943 A1 WO 2010097943A1
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- 238000000034 method Methods 0.000 title claims description 118
- 230000001133 acceleration Effects 0.000 claims description 115
- 230000004927 fusion Effects 0.000 claims description 9
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- 238000005259 measurement Methods 0.000 description 21
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- 238000010586 diagram Methods 0.000 description 12
- 238000012545 processing Methods 0.000 description 10
- 238000004088 simulation Methods 0.000 description 8
- 238000004364 calculation method Methods 0.000 description 7
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/16—Anti-collision systems
- G08G1/161—Decentralised systems, e.g. inter-vehicle communication
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/45—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement
- G01S19/46—Determining position by combining measurements of signals from the satellite radio beacon positioning system with a supplementary measurement the supplementary measurement being of a radio-wave signal type
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
- G01S19/51—Relative positioning
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/0009—Transmission of position information to remote stations
- G01S5/0072—Transmission between mobile stations, e.g. anti-collision systems
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0291—Fleet control
- G05D1/0293—Convoy travelling
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/22—Platooning, i.e. convoy of communicating vehicles
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9316—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles combined with communication equipment with other vehicles or with base stations
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/932—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles using own vehicle data, e.g. ground speed, steering wheel direction
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
- G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
- G01S2013/9325—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles for inter-vehicle distance regulation, e.g. navigating in platoons
Definitions
- the present invention relates to an apparatus and method for estimating a vehicle relative position.
- Patent Document 1 acquires traveling data such as the vehicle speed, acceleration / deceleration, and ID (convoy order) of the preceding vehicle by inter-vehicle communication with the preceding vehicle, and uses a magnetic sensor provided in the own vehicle to The lateral displacement is acquired, and the platooning is performed based on the acquired information.
- traveling data such as the vehicle speed, acceleration / deceleration, and ID (convoy order) of the preceding vehicle by inter-vehicle communication with the preceding vehicle, and uses a magnetic sensor provided in the own vehicle to The lateral displacement is acquired, and the platooning is performed based on the acquired information.
- the present invention has been made to solve such a technical problem, and an object thereof is to provide a vehicle relative position estimation device capable of accurately estimating the relative position between vehicles.
- the vehicle relative position estimation apparatus is a vehicle relative position estimation apparatus that estimates a relative position of a first vehicle with respect to a second vehicle, and includes vehicle control information that controls a motion state of the first vehicle or the first vehicle.
- the motion state of the first vehicle detected by the vehicle-mounted device of one vehicle and the vehicle control information for controlling the motion state of the second vehicle or the motion state of the second vehicle detected by the vehicle-mounted device of the second vehicle Each of which is acquired by the exercise state acquisition unit, the relative position acquisition unit that acquires the relative position detected by the in-vehicle device mounted on the first vehicle or the second vehicle, and the exercise state acquisition unit Before acquiring the vehicle control information or the motion state of the first vehicle and the vehicle control information or the motion state of the second vehicle and acquiring them by the relative position acquisition unit Constructed and a estimation unit that estimates the relative position by using a Kalman filter relative positions as the observation amount.
- the motion state acquisition unit controls the vehicle control information for controlling the motion state of the first vehicle or the motion state of the first vehicle detected by the in-vehicle device of the first vehicle and the motion state of the second vehicle.
- the movement state of the second vehicle detected by the vehicle control information or the in-vehicle device of the second vehicle is acquired, and the relative position detected by the in-vehicle device mounted on the first vehicle or the second vehicle is acquired by the relative position acquisition unit.
- the estimation unit receives the vehicle control information or the motion state of the first vehicle and the vehicle control information or the motion state of the second vehicle, and estimates the relative position using the Kalman filter with the relative position as an observation amount.
- the relative position obtained from the in-vehicle device mounted on the first vehicle or the second vehicle having a large measurement error, noise or the like alone is combined with the motion state of the first vehicle and the second vehicle using the Kalman filter. Therefore, it is possible to estimate the relative position with reduced measurement error, noise, and the like. Therefore, it is possible to accurately estimate the relative position between the vehicles.
- the motion state acquisition unit acquires acceleration as the motion state
- the relative position acquisition unit uses GPS information as the relative position
- the relative position calculated from GPS information including measurement error, noise, and the like can be combined with the acceleration of the first vehicle and the second vehicle using the Kalman filter, so that measurement error, noise, etc. It is possible to estimate the relative position with reduced.
- the estimation unit changes a degree of fusion by the Kalman filter in accordance with a capturing state of an in-vehicle device that is mounted on the first vehicle or the second vehicle and detects the relative position.
- the degree of fusion by the Kalman filter can be changed according to the capture state of the in-vehicle device, so that the capture state of the in-vehicle device that detects the relative position can be reflected in the estimated value of the relative position.
- the estimated value can be calculated, so that the availability of the vehicle relative position estimation device is improved. Can do.
- the estimation unit may switch the gain of the Kalman filter calculated in advance in accordance with a capturing state of an in-vehicle device that is mounted on the first vehicle or the second vehicle and detects the relative position.
- the relative position acquisition unit is mounted on the first vehicle or the second vehicle and the relative position is calculated.
- the estimation unit is configured to acquire the vehicle control information or the motion state of the first vehicle and the vehicle control information of the second vehicle acquired by the motion state acquisition unit or It is preferable to estimate the relative position based on the motion state.
- the estimation unit estimates the relative position based on the vehicle control information or the motion state. Therefore, the availability of the vehicle relative position estimation device can be improved.
- the estimation unit includes the motion state of the first vehicle and When estimating the relative position based on the second motion state, the accuracy of the in-vehicle device mounted on the first vehicle and detecting the motion state of the first vehicle, or mounted on the second vehicle and the It is preferable to include a control unit that changes the target relative position of the first vehicle or the second vehicle based on the accuracy of the in-vehicle device that detects the motion state of the second vehicle.
- a vehicle relative position estimation method for estimating a relative position of a first vehicle with respect to a second vehicle, wherein the vehicle control information for controlling a motion state of the first vehicle or the vehicle-mounted device of the first vehicle is detected.
- An exercise state acquisition step for acquiring the movement state of the second vehicle detected by the vehicle control information for controlling the movement state of the first vehicle and the movement state of the second vehicle or the in-vehicle device of the second vehicle;
- Relative position acquisition step for acquiring the relative position detected by an on-vehicle device mounted on the first vehicle or the second vehicle, and vehicle control information or an exercise state of the first vehicle acquired by the exercise state acquisition step
- the vehicle control information or the motion state of the second vehicle as input, and the relative position acquired by the relative position acquisition step is viewed. Configured and an estimating step of estimating the relative position by using a Kalman filter as the amount.
- the motion state acquisition step acquires acceleration as the motion state
- the relative position acquisition step uses GPS information as the relative position
- the degree of fusion by the Kalman filter is changed in accordance with a capture state of an in-vehicle device mounted on the first vehicle or the second vehicle and detecting the relative position.
- the vehicle relative position estimation method has the same effect as the vehicle relative position estimation device described above.
- 1 is a schematic configuration diagram of a row running system including a vehicle relative position estimation device according to a first embodiment. It is a schematic diagram explaining a row running system provided with a vehicle relative position estimating device concerning a 1st embodiment. It is a schematic diagram explaining the vehicle running state in a row running system provided with a vehicle relative position estimating device concerning a 1st embodiment. It is a schematic diagram explaining the Kalman filter of the vehicle relative position estimation apparatus according to the first embodiment. It is a block diagram explaining the function of the Kalman filter of the vehicle relative position estimation apparatus which concerns on 1st Embodiment. It is a flowchart which shows operation
- FIG. 15 is a partially enlarged view of FIG. 14. It is a simulation result of the estimated value of the vehicle relative position estimation apparatus which concerns on 3rd Embodiment.
- FIG. 17 is a partially enlarged view of FIG. 16. It is a simulation result of the accumulated error of the vehicle relative position estimating device according to the fourth embodiment. It is the simulation result of the target which the vehicle relative position estimation apparatus which concerns on 4th Embodiment sets.
- the vehicle relative position estimation device is a device that estimates the relative position (inter-vehicle distance) between vehicles, and is preferably employed in a row running control system in which a plurality of vehicles run in a row, for example. Is.
- the row running control system 1 shown in FIG. 1 is a system that controls the running state of vehicles belonging to a row in a row running in which a plurality of vehicles run in a row.
- This row running control system 1 for example, as shown in FIG. 2, a row running in which an arbitrary number of vehicles run in a vertical line with a relatively narrow inter-vehicle distance is realized.
- the n-th (n: natural number) vehicle counted from the head of the platoon is represented by “C n ”.
- C n the n-th (n: natural number) vehicle counted from the head of the platoon.
- each vehicle is traveling in the direction of arrow Y in the figure, and the entire vehicle is made up of m units (m: natural number, m ⁇ n).
- D n the inter-vehicle distance between the vehicle C n and the vehicle C n + 1 is represented by “D n ”.
- the convoy travel control system 1 includes a vehicle control ECU (Electronic Control Unit) 10.
- vehicle control ECU 10 is an electronic control unit that performs overall control of the platooning control system 1, and is configured mainly by a computer including a CPU, a ROM, and a RAM, for example. Detailed functions of the vehicle control ECU 10 will be described later.
- the row running control system 1 includes sensors (on-vehicle equipment) for detecting the running state of the host vehicle (vehicle C n ).
- sensors include, for example, a front inter-vehicle distance sensor 21a, a rear inter-vehicle distance sensor 22a, a wheel speed sensor 23a, and an acceleration sensor 24a.
- the front inter-vehicle distance sensor 21a is the front sensor ECU 21
- the rear inter-vehicle distance sensor 22a is the rear sensor ECU 22
- the wheel speed sensor 23a is the wheel speed sensor ECU 23
- the acceleration sensor 24a is the acceleration sensor ECU 24.
- Front inter-vehicle distance sensor 21a and the front sensor ECU21 has the function of detecting an inter-vehicle distance D_ FR of the vehicle C n-1 that travels just before the vehicle C n.
- the rear inter-vehicle distance sensor 22a and the rear sensor ECU22 has the function of detecting an inter-vehicle distance D_ RR of the vehicle C n + 1 that travels immediately after the vehicle C n.
- Such front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a for example, a millimeter-wave radar which is provided, respectively front and rear of the vehicle C n, respectively, are employed.
- the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a have functions of transmitting electromagnetic waves such as millimeter waves so as to scan in the left-right direction and receiving reflected waves.
- the front sensor ECU 21 and the rear sensor ECU 22 vehicle distance based on the time it takes to receive and transmit electromagnetic waves D_ RR, and has a function of calculating a D_ FR.
- Front sensor ECU21 and the rear sensor ECU22 has the function of outputting to the vehicle control ECU10 vehicle distance D_ RR, the D_ FR as inter-vehicle distance information.
- the detected inter-vehicle distance D_ RR, D_ FR is the measurement accuracy, operation accuracy, and includes an error such as noise.
- Wheel speed sensors 23a and the wheel speed sensor ECU23 has the function of detecting a wheel speed Vh n of the vehicle C n.
- the wheel speed sensor 23a for example, an electromagnetic pickup sensor that detects wheel rotation as a pulse signal is employed.
- the wheel speed sensor 23a has a function of outputting a pulse signal accompanying the rotation of the wheel to the wheel speed sensor ECU 23, and the wheel speed sensor ECU 23 has a function of calculating the wheel speed Vh n based on the pulse signal.
- Wheel speed sensor ECU23 has the function of outputting to the vehicle control ECU10 wheel speed Vh n as the wheel speed information.
- the acceleration sensor 24a and the acceleration sensor ECU24 has the function of detecting the acceleration a n of the vehicle C n.
- a gas rate sensor or a gyro sensor is employed as the acceleration sensor 24a.
- the acceleration sensor 24a has a function of outputting a signal indicative of the displacement due to acceleration to the acceleration sensor ECU 24, the acceleration sensor ECU 24 has a function of calculating the acceleration a n based on the signal.
- Acceleration sensor ECU24 has the function of outputting to the vehicle control ECU10 acceleration a n as acceleration information.
- the acceleration a n which is detected, measurement accuracy, operation accuracy, and includes an error such as noise.
- the front sensor ECU 21, the rear sensor ECU 22, the wheel speed sensor ECU 23, and the acceleration sensor ECU 24 are connected to the vehicle control ECU 10 via a communication / sensor system CAN 20 constructed as an in-vehicle network.
- the sensors mounted on the vehicle C n forward inter-vehicle distance information about the vehicle C n, the rear inter-vehicle distance information, wheel speed information and acceleration information is detected.
- the front inter-vehicle distance information, the rear inter-vehicle distance information, the wheel speed information, and the acceleration information may be collectively referred to as travel state information.
- the system 1 is to operate the acceleration and deceleration, steering of the vehicle C n, the engine control ECU 31, and a brake control ECU32 and the steering control ECU 33.
- the engine control ECU 31, the brake control ECU 32, and the steering control ECU 33 are connected to the vehicle control ECU 10 via a control system CAN30.
- the engine control ECU 31 has a function of inputting acceleration request value information output from the vehicle control ECU 10 and operating a throttle actuator or the like with an operation amount corresponding to the acceleration request value.
- the brake control ECU 32 has a function of inputting the acceleration request value information and operating a brake actuator or the like with an operation amount corresponding to the acceleration request value.
- the steering control ECU 33 has a function of inputting steering command value information output from the vehicle control ECU 10 and operating a steering actuator or the like with an operation amount corresponding to the steering command value.
- the platooning control system 1 includes a wireless antenna 26a and a wireless control ECU 26 so as to exchange traveling state information and the like with other constituent vehicles of the platoon.
- Each vehicle in the platoon communicates with each other by the wireless antenna 26a and the wireless control ECU 26 to acquire vehicle specification information, traveling state information, acceleration request value information, steering command value information, etc. of all other constituent vehicles. as well as, to send the vehicle specification information of the vehicle C n, running state information, the acceleration request value information and the steering command value information such as the other vehicle (broken line in FIG. 2).
- various types of information can be exchanged between vehicles without being limited to these pieces of information.
- the vehicle control ECU 10 of all the vehicles can share the vehicle specification information, the traveling state information, and the acceleration request value information of all the vehicles.
- the radio control ECU 26 is connected to the vehicle control ECU 10 via the communication / sensor system CAN 20 described above.
- Vehicle control ECU10 is based on the running state information or the acceleration request value information of another vehicle obtained above running state information or the acceleration request value information obtained by the sensors of the vehicle C n, and the inter-vehicle communication, for example It has an autonomous function of controlling the inter-vehicle distance D n between the inter-vehicle distance D n-1 or the rear vehicle C n + 1 to the preceding vehicle C n-1.
- the vehicle control ECU 10 determines the acceleration request value information and the steering so that the inter - vehicle distances D n ⁇ 1 and D n become the target inter - vehicle distance based on the traveling state information or the acceleration required value information of the vehicle C n and other vehicles.
- the target inter-vehicle distance is set by the vehicle control ECU 10 based on an estimated value of the inter-vehicle distance described later, taking into consideration the performance of the vehicle C n traveling in the platoon, the traveling environment, and the like.
- the vehicle control ECU 10 includes a vehicle relative position estimation unit (vehicle relative position estimation device) 11 in order to accurately estimate the inter-vehicle distance between the vehicles traveling in the platoon.
- vehicle relative position estimation unit 11 includes a motion state acquisition unit 12, a relative position acquisition unit 13, and an estimation unit 14.
- Motion state obtaining section 12 includes a motion state or the acceleration request value information of the vehicle C n, and a function of acquiring the motion state or the acceleration request value information of the other vehicle.
- the exercise state indicates, for example, the vehicle speed and acceleration, and is included in the above-described travel state information.
- Motion state obtaining section 12 has, for example, a function of the motion state detected by the mounted wheel speed sensor 23a and the acceleration sensor 24a, to get through the communication-sensor system CAN20 the vehicle C n. Alternatively, and it has a function of inputting an acceleration request value information of the vehicle C n.
- the motion state acquisition unit 12 has a function of acquiring the motion state detected by the wheel speed sensor 23a and the acceleration sensor 24a mounted on the other vehicle via the communication / sensor system CAN20 by inter-vehicle communication, for example. is doing. Or it has a function which acquires the acceleration required value information of other vehicles via communication and sensor system CAN20 by inter-vehicle communication.
- the movement state acquisition unit 12 has a function of outputting the acquired movement state or acceleration request value information of the vehicle C n and the movement state or acceleration request value information of the other vehicle to the estimation unit 14.
- the relative position acquisition unit 13 has a function of acquiring a measured relative position between vehicles traveling in a row.
- the relative position acquisition unit 13 has a function of acquiring the inter-vehicle distances D n ⁇ 1 and D n detected by the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a mounted on the vehicle C n .
- the relative position acquisition part 13 has a function which acquires the inter-vehicle distance detected by the front inter-vehicle distance sensor 21a and the back inter-vehicle distance sensor 22a mounted in the other vehicle, for example.
- the relative position acquisition unit 13 has a function of outputting the acquired inter-vehicle distance to the estimation unit 14.
- the estimation unit 14 includes the motion state or acceleration request value information of the vehicle C n acquired by the motion state acquisition unit 12, the motion state or acceleration request value information of the other vehicle, and the inter-vehicle distance acquired by the relative position acquisition unit 13. Based on this, it has a function of estimating the inter-vehicle distance between vehicles traveling in a platoon. Specifically, the estimation unit 14 has a function of estimating an inter-vehicle distance between vehicles using a Kalman filter.
- the Kalman filter of the vehicle relative position estimation unit 11 has a function of calculating a motion state estimation value by combining measurement values and vehicle motion (system).
- the Kalman filter is an algorithm that estimates an optimal system state by balancing a plurality of measured values with different accuracy and an estimated value based on a state equation describing vehicle motion.
- the Kalman filter is an algorithm that estimates the most probable system state by appropriately weighting according to the magnitude of these errors when there is an error in both the measured value and the estimated value. .
- the motion equation of the system and the observation equation based on the measurement values used for the Kalman filter will be described with reference to an example of a vehicle that travels in a row as shown in FIG. As shown in FIG. 3, five vehicles C 1 to C 5 are traveling in the Y direction.
- the acceleration a 1 ⁇ a 5 each vehicle C 1 ⁇ C 5, the acceleration obtained by the acceleration sensor 24a and an acceleration sensor ECU24 mounted on each of the vehicle C 1 ⁇ C 5, or, the vehicle C 1 ⁇ C 5 Is an acceleration obtained from the acceleration request value calculated by the vehicle control ECU 10 mounted on the vehicle.
- the relative speed between the vehicles C 1 to C 5 is Vr 1 to Vr 4
- the inter-vehicle distance is D 1 to D 4
- the system noise applied to the vehicles C 1 to C 5 is q 1 to q 5 .
- the system noise includes acceleration fluctuation due to disturbance, measurement error of the acceleration sensor 24a, control error, motion equation error, and the like.
- a predetermined assumed value is used as the system noise. In the above system, the following equation of state is established.
- Equation 1 x is a state variable.
- the matrix A associates the system state and the state variable x when there is no noise.
- the matrix B associates the system input with the state variable x.
- the matrix H associates the system noise with the state variable x. From Equation 1, the motion of the vehicles C 1 to C 5 can be theoretically shown based on the accelerations a 1 to a 5 .
- the wheel speed difference between adjacent vehicles can be obtained from the wheel speeds Vh 1 to Vh 5 detected by the wheel speed sensors 23a of the vehicles C 1 to C 5 .
- This wheel speed difference is Vr h .
- the relative speed can be obtained based on the inter-vehicle distances D RF and D FF detected by the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a of each of the vehicles C 1 to C 5 . Let this relative velocity be Vr RF and Vr FF .
- the observation noise of the wheel speed difference calculated based on the wheel speed sensor 23a included in the vehicles C 1 to C 5 is v a
- the observation noise of the relative speed calculated based on the front inter-vehicle distance sensor 21a is v b
- the rear inter-vehicle distance is v c
- the inter-vehicle distance observation noise calculated based on the front inter-vehicle distance sensor 21a is v d
- the inter-vehicle distance is calculated based on the rear inter-vehicle distance sensor 22a.
- the noise and v e When all the sensor devices of the vehicles C 1 to C 5 are used, the observation equation shown in the following equation 2 is established.
- Equation 1 Y is an actual observation value.
- the matrix C associates the observed value (true value) when there is no noise with the actual observed value.
- the matrix v is an error of each sensor.
- Expression 2 can show the observation result of the motion of the vehicles C 1 to C 5 based on the measured values of the sensors.
- the Kalman filter calculates whether the theoretical value is prioritized or the observation value is prioritized and outputs an optimum estimated value.
- the input / output of the Kalman filter will be described with reference to FIG.
- the Kalman filter inputs each vehicle acceleration as a system input and calculates a state equation shown in Equation 1. Further, the Kalman filter acquires each relative speed and each inter-vehicle distance from the wheel speed sensor 23a, the front inter-vehicle distance sensor 21a, and the rear inter-vehicle distance sensor 22a as sensor information input, and calculates an observation equation. And a Kalman filter outputs the estimated value of each inter-vehicle distance and the estimated value of each relative speed as a relative motion estimated value.
- FIG. 5 is an example of a block diagram of the Kalman filter.
- the circuit K1 has a function of calculating a state equation using each vehicle acceleration as an input and predicting vehicle (vehicle group) motion.
- the circuit K2 has a function of feeding back an actual sensor value. This feedback is weighted according to the accuracy of the sensor value. That is, for example, an observation value with a large noise is fed back with a small gain so as not to trust the observation value. On the other hand, when the error of the state equation is large, it is fed back with a large gain so as to trust the observed value. This gain is a Kalman filter gain of Equation 3 described later.
- FIG. 6 is a flowchart showing the operation of the vehicle relative position estimation unit 11 according to this embodiment.
- the control process shown in FIG. 6 is repeatedly executed at a predetermined interval from the timing when the ignition is turned on, for example.
- the vehicle relative position estimation unit 11 starts the process from the other vehicle information input process (S10).
- the process of S10 is a process executed by the motion state acquisition unit 12 and the relative position acquisition unit 13 to input information on other vehicles.
- the movement state acquisition unit 12 acquires, via the communication / sensor system CAN20, the traveling state information or acceleration request value information of another vehicle input to the wireless antenna 25a and the wireless control ECU 25, for example, by inter-vehicle communication.
- the relative position acquisition unit 13 acquires the relative position information acquired by the other vehicle input to the wireless antenna 25a and the wireless control ECU 25 through, for example, inter-vehicle communication via the communication / sensor system CAN20.
- the process of S10 ends, the process proceeds to the own vehicle information acquisition process (S12).
- Process in S12 is a process of motion-state acquisition unit 12 and the relative position acquisition unit 13 executes, to obtain information from the sensors mounted on the vehicle (vehicle C n).
- the motion state acquisition unit 12 acquires wheel speed information and acceleration information output from the wheel speed sensor ECU 23 and the acceleration sensor ECU 24 via the communication / sensor system CAN20.
- the relative position acquisition unit 13 acquires the inter-vehicle distance information output from the front sensor ECU 21 and the rear sensor ECU 22 via the communication / sensor system CAN 20.
- the process of S14 is a process executed by the estimation unit 14 and inputting the previous value x (n) of the relative motion estimated value.
- the estimation unit 14 inputs the previous value x (n) of the relative motion estimated value recorded in the memory or the like with reference to the previous value. In the first case, a preset initial value is input.
- the process of S14 ends, the process proceeds to the Kalman filter calculation process (S16).
- the processes of S16 and S18 are processes that are executed by the estimation unit 14 and calculate the relative motion estimated value x (n + 1) by the Kalman filter.
- the estimation unit 14 performs a calculation using Expression 3 shown below.
- a and B shown in Equation 3 are matrices of the above-described state equation, u (n) is acceleration, L is Kalman filter gain, y is a true value of an observed value, and y (n) is an observed value. is there.
- the Kalman filter gain is calculated based on Equations 1 and 2 described above.
- the relative motion estimated value x (n + 1) generated in the process of S18 is the previous value input in the process of S14 in the next process.
- the motion-state acquisition section 12 the vehicle control information for controlling the motional state of the vehicle C n (acceleration request value) or the acceleration of the vehicle C n acceleration a n of the vehicle C n detected by the sensor 24a, and the acceleration of the other vehicle detected by the vehicle control information (acceleration request value) or other vehicle acceleration sensor 24a for controlling the motion state of another vehicle is acquired, the relative position acquisition unit 13, the front inter-vehicle distance sensor 21a mounted on the vehicle C n, or another vehicle, the rear inter-vehicle distance sensor 22a by the detected relative position D RF, D FF is acquired by the estimating unit 14, the vehicle C acceleration required value of n or the acceleration request value or the acceleration of the acceleration a n and the other vehicle as input, the relative position D RF, the D FF as observables
- the relative position using the Le Mans filter, the relative velocity is estimated.
- the relative position D RF , D FF obtained from the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a which have large measurement errors, noises, and the like with a single unit, can be obtained from the vehicle C n and others using the Kalman filter. Since it can be integrated with the motion state of the vehicle, it is possible to estimate the relative position and the relative speed with reduced measurement error, noise and the like. That is, it is possible to estimate the inter-vehicle distance (relative speed) with less noise and high accuracy by using the Kalman filter to fuse other vehicle information by inter-vehicle communication and the sensors of the host vehicle.
- the inter-vehicle distance of the platooning can be controlled to be short.
- the relative position with high accuracy can be acquired, there is no need to process the relative positions D RF and D FF obtained from the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a by an annealing process or the like, and a dead zone for vehicle control. Can be eliminated. It is also possible to finely quantize the state quantity used for feedback control in the Kalman filter.
- the relative position can be estimated regardless of the update frequency of the state equation and the observation equation, for example, the estimated value can be calculated more finely than the update period of the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a. Therefore, since the responsiveness of the traveling control is improved, it is possible to control the distance between the vehicles in the platooning. Moreover, since the information used for the estimation which the vehicle relative position estimation apparatus 11 performs is information regarding acceleration, speed, relative speed, and inter-vehicle distance, it can be estimated with a small communication amount. Moreover, since it is based on the information normally acquired by the vehicle, it is excellent in expandability without depending on other controls.
- the processing load can be reduced. Further, it is possible to control the platooning by estimating each vehicle independently. Furthermore, not only the relative position between the vehicle C n and the other vehicle C n ⁇ 1 but also the relative position between the other vehicles can be accurately estimated.
- the vehicle relative position estimation device (vehicle relative position estimation unit) according to the second embodiment is configured in substantially the same manner as the vehicle relative position estimation unit 11 according to the first embodiment, and relates to the first embodiment. Compared with the vehicle relative position estimation unit 11, the relative position information acquired by the relative position acquisition unit 13 is different. In the second embodiment, the description of the same parts as those in the first embodiment will be omitted, and the differences will be mainly described.
- the vehicle C n according to the second embodiment is configured in substantially the same manner as the vehicle C n according to the first embodiment, and is compared to the vehicle C n according to the first embodiment, the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a.
- the difference is that a navigation system (not shown) is provided instead of or in combination.
- the navigation system includes a GPS (Global Positioning System) receiver and has a function of receiving GPS information (X coordinate: X n , Y coordinate: Y n ) that is position information of the host vehicle (vehicle C n ). is doing.
- GPS is a measurement system using a satellite, and is preferably used for grasping the current position of the host vehicle.
- the navigation system is connected to the vehicle control ECU 10 via the communication / sensor system CAN 20 and has a function of outputting the received position information to the vehicle control ECU 10.
- the relative position acquisition unit 13 provided in the vehicle relative position estimation unit according to the second embodiment has a function of acquiring positional information of the vehicle C n navigation system prints. Further, the function of acquiring the position information of the other vehicle output from the navigation system of the other vehicle by inter-vehicle communication, or the navigation of the vehicle C n when the position information of the other vehicle is acquired by the navigation system of the vehicle C n . It has a function of acquiring position information of other vehicles output by the system. And the relative position acquisition part 13 has a function which calculates the relative position between vehicles based on the acquired positional information. Other functions are the same as those in the first embodiment.
- FIG. 7 is a schematic diagram illustrating position information (X n , Y n ) acquired by the relative position acquisition unit 13 included in the vehicle relative position estimation unit according to the second embodiment.
- FIG. 7 shows an example of traveling in two rows of the preceding vehicle C 1 and the following vehicle C 2 .
- the relative position acquisition unit 13 of the vehicle C 2 is the position information of the vehicle C 1 (X 1, Y 1 ) and the position information of the vehicle C 2 (X 2, Y 2 ) acquired, it has a function of calculating the relative distance D x in the X direction, the Y-direction relative distance D y.
- the dotted circle (error circle) shown in FIG. 7 is an error range indicating observation noise of GPS information obtained by the navigation system.
- the estimation unit 14 inputs each vehicle acceleration as a system input to obtain a state equation, and uses a relative distance D x in the X direction and a relative distance D in the Y direction as sensor inputs.
- y is input as an observation equation, and an estimated value of each inter-vehicle distance and an estimated value of each relative speed are output as relative motion estimated values using a Kalman filter.
- the equation of state and the observation equation of Equation 2 are shown for the two vehicles shown in FIG. Each matrix is the same as in the first embodiment.
- v x and v y in Equation 5 are observation noises of differences in the X and Y directions of GPS information.
- the estimation unit 14 estimates the inter-vehicle distance and the relative position by executing the control process shown in FIG. About operation
- movement of a vehicle relative position estimation apparatus since it is the same as that of the control processing shown in FIG. 6 demonstrated in 1st Embodiment, it abbreviate
- the vehicle relative position estimation apparatus As described above, according to the vehicle relative position estimation apparatus according to the second embodiment, the same effects as those of the vehicle relative position estimation apparatus 11 according to the first embodiment are obtained, and calculation is performed from GPS information including measurement error, noise, and the like. Since the relative position can be combined with the acceleration of the host vehicle C n and other vehicles using the Kalman filter, it is possible to estimate the relative position (relative speed) with reduced measurement error, noise, and the like. For this reason, even if the GPS information has a large error, the relative position and the relative speed can be accurately acquired based on the error circle and each vehicle heading acceleration even if the vehicle is not equipped with a sensor.
- the vehicle relative position estimation device (vehicle relative position estimation unit) according to the third embodiment is configured in substantially the same manner as the vehicle relative position estimation unit 11 according to the first embodiment, and relates to the first embodiment. Compared to the vehicle relative position estimation unit 11, a part of the function of the estimation unit 14 is different. In the third embodiment, the description of the same parts as those in the first embodiment will be omitted, and the description will focus on the differences.
- the vehicle C n according to the third embodiment is configured similarly to the vehicle C n according to the first embodiment.
- the estimation unit 14 included in the vehicle relative position estimation unit according to the third embodiment is configured in substantially the same manner as the estimation unit 14 included in the vehicle relative position estimation unit 11 according to the first embodiment, and is related to the first embodiment.
- the estimation unit 14 has a function of changing the degree of fusion of the observation value and the motion state by the sensor according to the capture state of the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a.
- the estimation unit 14 has a function of switching and controlling the Kalman filter gain according to the capture state of the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a.
- the estimation unit 14 provided in the vehicle relative position estimation unit according to the third embodiment, a case where two vehicles C 1 and C 2 are traveling in a row will be described.
- the vehicles C 1 and C 2 are the same as the vehicle C n described in the first embodiment, and the accelerations a 1 and a 2 , the inter-vehicle distance D 1 , the relative speed Vr 1 , and the system noises q 1 and q 2 are The same reference numerals are used (see vehicles C 1 and C 2 in FIGS. 2 and 3).
- Equation 6 the state equations of the vehicles C 1 and C 2 can be represented by the following Equation 6, and the observation equation by the sensor can be represented by the following Equation 7, respectively.
- the estimation unit 14 in accordance with the acquisition state of the front inter-vehicle distance sensor 21a and the vehicle C 1 of the rear inter-vehicle distance sensor 22a of the vehicle C 2, has a function of changing the matrix C of Equation 7.
- Front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a of the vehicle C 1 of the vehicle C 2 in order to detect the relative position by an electromagnetic wave such as a millimeter wave, information stably detected as compared with the wheel speed sensor 23a, an acceleration sensor 24a In some cases, the relative position cannot be detected due to noise or the like (lost state).
- Estimation unit 14 whether or not the captured state and capture the state of the rear inter-vehicle distance sensor 22a vehicle C 1 of the front inter-vehicle distance sensor 21a of the vehicle C 2, i.e. the front inter-vehicle distance sensor 21a of the vehicle C 2 is lost state, depending on whether the rear inter-vehicle distance sensor 22a of the vehicle C 1 is lost state, and has a function of switching matrix C previously prepared selectively.
- Front sensor ECU 21, the rear sensor ECU22 is front inter-vehicle distance sensor 21a of the vehicle C 2, the rear inter-vehicle distance sensor 22a of the vehicle C 1 has a respective function of determining whether a lost state.
- the front sensor ECU 21 and the rear sensor ECU 22 have a function of determining a lost state when a change amount such as the intensity of the received millimeter wave shows a value larger than a predetermined value.
- front sensor ECU21 and back sensor ECU22 have the function to output the determination result to vehicle control ECU10, respectively.
- Estimation unit 14 inputs the determination result front sensor ECU21 and the rear sensor ECU22 has output respectively, front inter-vehicle distance sensor 21a of the vehicle C 2, both of the vehicle C 1 of the rear inter-vehicle distance sensor 22a is a detectable state In the case (XTRGT_Status: 1), the matrix C shown in the following Expression 8 is adopted. Further, for example, the estimation unit 14, a detectable condition front inter-vehicle distance sensor 21a of the vehicle C 2 If the rear inter-vehicle distance sensor 22a of the vehicle C 1 is located in the lost state (XTRGT_Status: 2) The The matrix C shown in Equation 9 below is employed.
- the estimation unit 14 determines the capture state of the front inter-vehicle distance sensor 21a of the vehicle C 2, and the observation equation using the matrix C is switched in accordance with the acquisition state of the rear inter-vehicle distance sensor 22a vehicle C 1 . Then, based on the determined observation equation and the state equation shown in Equation 6, the Kalman filter gain L n is calculated.
- the Kalman filter gain is L 1.
- the Kalman filter gain is expressed as L 2 and Expression 10.
- the estimation unit 14 calculates the relative speed by integrating the accelerations a 1 and a 2 of the two vehicles C 1 and C 2 , and further integrates the integrated accelerations a 1 and a 2 to obtain the inter-vehicle distance. It has a function to calculate.
- FIG. 8 shows an example of a block diagram of the Kalman filter according to the present embodiment.
- the circuit K3 has a function of predicting vehicle (vehicle group) motion while feeding back an actual sensor value. This feedback is weighted by switching the gain (Kalman gain) according to the capture state of the sensors. For example, in the case of XTRGT_Status1 the observed value by sensors is weighted by the Kalman filter gain L 1, in the case of XTRGT_Status2 the observed value by sensors is weighted by the Kalman filter gain L 2, in the case of XTRGT_Status3 the sensors observations by are weighted by the Kalman filter gain L 3.
- the circuit K4 has a function of calculating a state equation using the accelerations a 1 and a 2 of the two vehicles C 1 and C 2 as inputs and predicting the vehicle (vehicle group) motion. That is, in the case of XTRGT_Status0, the estimation unit 14 has a function of calculating a relative motion estimated value without using any sensor value.
- FIG. 9 is a flowchart showing the operation of the vehicle relative position estimation unit according to the present embodiment.
- the control process shown in FIG. 9 is repeatedly executed at a predetermined interval from, for example, the timing when the ignition is turned on.
- a case where two vehicles C 1 and C 2 (own vehicle) are traveling in a row will be described in consideration of easy understanding.
- the vehicle relative position estimation unit 11 starts the process from the other vehicle information input process (S20). This process is the same as the process of S10 in FIG. When the process of S20 ends, the process proceeds to the own vehicle information acquisition process (S22).
- a process of motion-state acquisition unit 12 and the relative position acquisition unit 13 executes, to obtain information from the sensors mounted on the vehicle (vehicle C 2). This process is the same as the process of S12 of FIG. When the process of S22 ends, the process proceeds to the previous value input process (S24).
- the process of S24 is a process executed by the estimation unit 14 and inputting the previous value x (n) of the relative motion estimated value. This process is the same as the process of S14 of FIG. When the process of S24 is completed, the process proceeds to a capture state determination process (S26).
- the estimation unit 14 executes a process of determining acquisition status of the front inter-vehicle distance sensor 21a of the vehicle C 2, and a capture condition of the rear inter-vehicle distance sensor 22a of the vehicle C 1.
- the estimation unit 14 inputs the determination results of the capture state output by the front sensor ECU 21 and the rear sensor ECU 22 respectively, and determines which state of XTRGT_Status 0 to 3 is applicable. If the process of S26 does not correspond to the state of XTRGT_Status0, the process proceeds to the gain selection process (S28).
- the process of S28 is a process which the estimation part 14 performs and selects a Kalman filter gain according to XTRGT_Status.
- the process of S28 ends, the process proceeds to the Kalman filter calculation process (S30).
- the processes of S30 and S34 are executed by the estimation unit 14 and calculate a relative motion estimated value x (n + 1) using a Kalman filter.
- the estimation unit 14 calculates the relative motion estimated value x (n + 1) by replacing the Kalman filter gain L of Equation 3 shown in the first embodiment with the Kalman filter gains L 1 to L 3 selected in the process of S28. .
- the control process shown in FIG. 9 is finished.
- the control process shown in FIG. 9 is finished.
- the relative motion estimated value x (n + 1) generated in the process of S34 is the previous value input in the process of S24 in the next process.
- the captured state of the front inter-vehicle distance sensor 21a of the vehicle C 2 it is possible to change the fusion degree of the Kalman filter in accordance with the acquisition state of the rear inter-vehicle distance sensor 22a vehicle C 1 Therefore, even when the front inter-vehicle distance sensor 21a or the rear inter-vehicle distance sensor 22a cannot be detected, the inter-vehicle distance and the relative speed can be accurately estimated.
- Equation 1 in the first embodiment the case of using Equation 2, while it is possible to estimate all the inter-vehicle distance of the vehicle C 1 ⁇ C 5, the inter-vehicle distance of each vehicle C 1 ⁇ C 5
- the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a to be measured need to be in a detectable state. For this reason, when Formula 1 and Formula 2 of 1st Embodiment are used, there exists a possibility that the availability of a vehicle relative position estimation apparatus may become low.
- the vehicle relative position estimation device according to the third embodiment, the same effect as that of the vehicle relative position estimation device 11 according to the first embodiment is obtained, and the Kalman filter is used according to the capture state of the in-vehicle device.
- the degree of fusion can be changed. For this reason, since it becomes possible to reflect the capture state of the in-vehicle device that detects the relative position in the estimated value of the relative position, it is necessary that all the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a are in a detectable state. Absent.
- the estimated value can be calculated, so the availability of the vehicle relative position estimation device Can be improved.
- the estimation unit 14 when all the front inter-vehicle distance sensors 21a and the rear inter-vehicle distance sensors 22a that detect the relative positions cannot detect the relative positions for a predetermined time, the estimation unit 14, a relative position based on the acceleration a n (or acceleration request value information), it is possible to estimate the relative velocity, it is possible to improve the availability of the vehicle relative position estimation apparatus.
- the vehicle relative position estimation device (vehicle relative position estimation unit) according to the fourth embodiment is configured in substantially the same manner as the vehicle relative position estimation unit according to the third embodiment, and the vehicle according to the third embodiment. Compared with the relative position estimation unit, some functions of the vehicle control ECU (control unit) 10 are different. Note that in the fourth embodiment, the description of the same parts as those in the third embodiment will be omitted, and the description will focus on the differences.
- the vehicle C n according to the fourth embodiment is configured similarly to the vehicle C n according to the first embodiment.
- Vehicle control ECU10 includes relative speed estimating unit 14 estimates, errors caused in the inter-vehicle distance, i.e. the ability to predict the error ⁇ .DELTA.A r accumulated over time.
- the vehicle control ECU 10 uses the time when the estimation unit 14 starts to estimate the relative speed based on the acceleration and the inter-vehicle distance in the state of XTRGT_Status0 as an initial value, and integrates ⁇ A r using the elapsed time from the initial value. It has a function of predicting errors accumulated in time and changing the target relative speed and the target inter-vehicle distance based on the predicted errors.
- FIG. 10 is a block diagram showing functions of the vehicle control ECU 10. As shown in FIG.
- the estimation unit 14 stores the elapsed time t from the time that the relative velocity based on the acceleration, the following distance began to estimate the state of XTRGT_Status0, relative integrates the error .DELTA.A r of the relative acceleration The accumulated error of the speed is calculated, and the integrated value is further integrated to calculate the accumulated error of the inter-vehicle distance.
- the screen (Scope) in the drawing is provided for simulation to be described later, and need not be provided.
- the vehicle control ECU 10 has a function of setting the target relative speed and the target inter-vehicle distance so as to be equal to or greater than the accumulated error. Further, the vehicle control ECU 10 has a function of prohibiting the inter-vehicle distance control when the accumulated error exceeds the allowable error threshold. Other functions of the vehicle control ECU 10 are the same as those of the vehicle control ECU 10 according to the third embodiment.
- FIG. 11 is a flowchart for explaining the operation of the correction unit and the vehicle control ECU 10.
- the control process shown in FIG. 11 is repeatedly executed at a predetermined interval from the timing when the estimation unit 14 starts to estimate the relative speed based on acceleration and the inter-vehicle distance in the state of XTRGT_Status0 until the state of XTRGT_Status0 ends. .
- the case where two vehicles C 1 and C 2 are traveling in a row will be described as an example. Further, explaining the case where the vehicle C 2 is the vehicle.
- the process of S40 is a process that is executed by the vehicle control ECU 10 and calculates an accumulated error based on the accuracy of the acceleration sensor 24a mounted on the vehicles C 1 and C 2 .
- Vehicle control ECU10 integrates the error .DELTA.A r of relative acceleration based on the elapsed time t from the time began to estimate the inter-vehicle distance, to calculate the accumulated error in the relative velocity. Further, the vehicle control ECU 10 calculates the accumulated error of the inter-vehicle distance by integrating the accumulated error of the relative speed based on the elapsed time t from the time when the inter-vehicle distance is started to be estimated.
- S42 determines the process (S42).
- the process of S42 is a process that is executed by the vehicle control ECU 10 and determines whether or not the error calculated in the process of S40 exceeds an allowable error. For example, the vehicle control ECU 10 sets an error in an allowable range as a predetermined value in advance, and determines whether or not the accumulated error of the inter-vehicle distance calculated in the process of S40 is larger than the set predetermined value. In the process of S42, if the accumulated error of the inter-vehicle distance is not larger than the set predetermined value, that is, if the error calculated in the process of S40 does not exceed the allowable error, the target inter-vehicle distance change process (S44).
- Processing at S44 is executed by the vehicle control ECU 10, a process of changing the target following distance of the vehicle C 2 on the basis of the error calculated in the processing of S40.
- the vehicle control ECU 10 changes the target inter-vehicle distance so as to be equal to or greater than the accumulated error of the inter-vehicle distance calculated in the process of S40. Further, the vehicle control ECU 10 changes the target relative speed so as to be equal to or greater than the accumulated error of the relative speed calculated in the process of S40.
- S46 vehicle control process
- the vehicle control ECU10 executes a process for transitioning the vehicle C 2 on the basis of the target inter-vehicle distance change in the process of S44.
- the vehicle control ECU10 the target following distance changing in the process of S44, based on the target relative speed, the engine control ECU 31, the brake control ECU 32, controls the steering control ECU 33, shifts the vehicle C 2.
- the control process shown in FIG. 11 ends.
- the vehicle control prohibiting process (S48).
- the process of S48 is a process executed by the vehicle control ECU 10 to prohibit the control of the inter-vehicle distance.
- the control process shown in FIG. 11 ends.
- an estimated inter-vehicle distance estimated value error that increases with time is predicted according to the accuracy of the acceleration sensor 24a, and the target inter-vehicle distance is set to be equal to or greater than the predicted inter-vehicle distance estimated value error. Since it can be changed, the driving safety can be ensured. In addition, since the control of the inter-vehicle distance can be prohibited when the estimated inter-vehicle distance error is larger than the allowable value, compared to the case where the control is simply performed based on the time from the lost state. The estimation can be continued for a long time, and as a result, the availability of the inter-vehicle distance control can be improved.
- the front inter-vehicle distance sensor 21a of the vehicle C 2, both of the vehicle C 1 of the rear inter-vehicle distance sensor 22a is lost state, the vehicle C 1, in the case of estimating the relative position from the detected acceleration by the acceleration sensor 24a mounted on the C 2, the vehicle control ECU 10, the vehicle C 1, the measurement error of the acceleration sensor 24a mounted on the C 2, noise, etc. Since the target relative position can be changed in consideration of the above, traveling safety can be ensured.
- vehicle relative position estimation device shows an example of the vehicle relative position estimation device according to the present invention.
- the vehicle relative position estimation device according to the present invention is not limited to the vehicle relative position estimation device according to each embodiment, and the vehicle relative position estimation according to each embodiment is within a range not changing the gist described in each claim.
- the device may be modified or applied to others.
- the present invention is not limited to this and may be installed outside the vehicle.
- the relative motion estimation value is calculated using the acceleration observed by the acceleration sensor mounted on the own vehicle and the other vehicle.
- the acceleration request of the own vehicle and the other vehicle is described.
- the relative motion estimated value may be calculated by mixing the acceleration observed by the acceleration sensor and the acceleration request value.
- the example in which the observation equation is established using all the sensors of the five platooning vehicles has been described, but at least two of the two vehicles that calculate the relative distance are used. It is only necessary to have one sensor for detecting the relative position.
- the relative position estimation method described in each of the above-described embodiments may be mixed in one row.
- millimeter wave radar is used as the front inter-vehicle distance sensor 21a and the rear inter-vehicle distance sensor 22a for detecting the inter-vehicle distance
- an image sensor, a laser, or the like may be used.
- Example 1 Using the vehicle model, the platooning control was simulated by the platooning control system of the platoon consisting of five vehicles C 1 to C 5 .
- the configuration of each vehicle is the same as that of the vehicle according to the first embodiment. Further, an Fr millimeter wave radar is employed as the front inter-vehicle distance sensor 21a, and an Rr millimeter wave radar is employed as the rear inter-vehicle distance sensor 22a. Then, as shown in FIG. 12, the five vehicles were delayed by 1 second in order from the top and started to accelerate, and after 10 seconds each was brought into a steady state.
- FIG. 13 (a) is a relative speed Vr n time-dependent simulation results (partially enlarged graph), FIG. 13 (b), the inter-vehicle distance D n time-dependent simulation results (partially enlarged graph ).
- FIG. 13 (a) is a relative speed Vr n time-dependent simulation results (partially enlarged graph)
- FIG. 13 (b) the inter-vehicle distance D n time-dependent simulation results (partially enlarged graph ).
- Example 2 Vehicles C 1 and C 2 according to the third embodiment were actually run in a row, and acceleration, wheel speed, inter-vehicle distance, and relative speed were measured using sensors mounted on each vehicle. Note that an Fr millimeter wave radar is used as the front inter-vehicle distance sensor 21a, and an Rr millimeter wave radar is adopted as the rear inter-vehicle distance sensor 22a. Then, using the vehicle relative position estimation device according to the third embodiment, the relative position and the relative speed were estimated based on the measured acceleration, wheel speed, inter-vehicle distance, and relative speed. The results are shown in FIGS.
- FIG. 14A is a measurement result showing the time dependence of the capture state of the Fr millimeter wave radar and the Rr millimeter wave radar that measure the relative speed and the inter-vehicle distance.
- XTRGT_Status one period, the relative speed Vr 1 indicates that Fr millimeter-wave radar of the vehicle C 2 to measure the inter-vehicle distance D 1
- the Rr millimeter-wave radar of the vehicle C 1 are both detectable state
- XTRGT_Status 3 period indicates that Fr millimeter-wave radar of the vehicle C 2 is lost state.
- FIG. 14B is a graph showing the time dependence of the relative velocity Vr 1.
- FIG. 14 (c) shows a graph showing the time dependence of inter-vehicle distance D 1, the measured value of Fr millimeter-wave radar and Rr millimeter-wave radar, an estimate.
- FIGS. 15A to 15C are partially enlarged views of FIGS. 14A to 14C.
- the vehicle relative position estimation apparatus can estimate the relative speed and the inter-vehicle distance smoothly with good robustness according to the capture state of the sensor that detects the inter-vehicle distance.
- FIG. 16A shows the measurement results indicating the time dependence of the capture state of the Fr millimeter wave radar and the Rr millimeter wave radar that measure the relative speed and the inter-vehicle distance, as in FIG. 14A.
- the period of XTRGT_Status is 0, Fr millimeter-wave radar of the vehicle C 2 to measure the inter-vehicle distance, Rr millimeter-wave radar of the vehicle C 1 is shown to be both lost state, period of XTRGT_Status is 2, the vehicle C 1 indicates that the Rr millimeter wave radar is in a lost state.
- FIG. 16B is a graph showing the time dependency of the estimated value of the relative speed Vr 1
- FIG. 16C is a graph showing the time dependency of the estimated value of the inter-vehicle distance D 1 .
- FIGS. 17A to 17C are partially enlarged views of FIGS. 16A to 16C.
- the relative values are obtained by the Kalman filter using the measurement value by the acceleration sensor. It was confirmed that the speed Vr 1 and the inter-vehicle distance D 1 can be estimated. Further, as shown in FIG. 17A, even when both the Fr millimeter wave radar and the Rr millimeter wave radar are in a lost state, the relative velocity Vr 1 is smoothly obtained as shown in FIGS. and to be able to estimate the inter-vehicle distance D 1 has been confirmed (location surrounded by a dotted line). Therefore, it was confirmed that the vehicle relative position estimation apparatus according to the third embodiment has good robustness and can estimate the relative speed and the inter-vehicle distance smoothly.
- Example 3 Using the vehicle model, the platooning control was simulated by the platooning control system of the platoon consisting of the two vehicles C 1 and C 2 . Error in the inter-vehicle distance estimation value depending on the time by integrating the error .DELTA.A r of relative acceleration based on the acceleration sensor 24a of each vehicle (d_error), were calculated relative velocity error estimate (V_error). The results are shown in FIG. FIG. 18A shows the time dependency of the error D_error in the estimated distance between the vehicles, and FIG. 18B shows the time dependency of the error V_error in the relative speed estimated value. As shown in FIG. 18A, it was confirmed that the errors V_error and D_error increase with the elapsed time.
- FIGS. 19A and 19B show the target inter-vehicle distance and the target relative speed that are changed from the time when both the Fr millimeter-wave radar and the Rr millimeter-wave radar are in a lost state during travel of 10 m between the target vehicles.
- a safety margin is ensured by setting a target inter-vehicle distance and a target relative speed that are equal to or larger than the estimation errors shown in FIGS. It was confirmed that safety could be ensured.
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Abstract
Description
10 車両制御ECU
11 車両相対位置推定装置
12 運動状態取得部
13 相対位置取得部
14 推定部
本実施形態に係る車両相対位置推定装置は、車両間の相対位置(車間距離)を推定する装置であって、例えば複数の車両が隊列を組んで走行する隊列走行制御システムに好適に採用されるものである。
第2実施形態に係る車両相対位置推定装置(車両相対位置推定部)は、第1実施形態に係る車両相対位置推定部11とほぼ同様に構成されるものであって、第1実施形態に係る車両相対位置推定部11と比べ、相対位置取得部13が取得する相対位置情報が相違する。なお、第2実施形態においては、第1実施形態と重複する部分は説明を省略し、相違点を中心に説明する。
第3実施形態に係る車両相対位置推定装置(車両相対位置推定部)は、第1実施形態に係る車両相対位置推定部11とほぼ同様に構成されるものであって、第1実施形態に係る車両相対位置推定部11と比べ、推定部14の一部機能が相違する。なお、第3実施形態においては、第1実施形態と重複する部分は説明を省略し、相違点を中心に説明する。
第4実施形態に係る車両相対位置推定装置(車両相対位置推定部)は、第3実施形態に係る車両相対位置推定部とほぼ同様に構成されるものであって、第3実施形態に係る車両相対位置推定部と比べ、車両制御ECU(制御部)10が備える一部機能が相違する。なお、第4実施形態においては、第3実施形態と重複する部分は説明を省略し、相違点を中心に説明する。
車両モデルを用いて、5台の車両C1~C5からなる隊列の隊列走行制御システムにより、隊列走行制御のシミュレーションを行った。各車両の構成は、第1実施形態に係る車両と同一とした。また、前方車間距離センサ21aとしてFrミリ波レーダ、後方車間距離センサ22aとしてRrミリ波レーダを採用した。そして、図12に示すように、5台の車両を先頭から順に1秒ずつ遅らせて加速発進させ、それぞれ10秒後に定常状態とさせた。
第3実施形態に係る車両C1、C2を実際に隊列走行させて、各車両に搭載されたセンサ類を用いて加速度、車輪速、車間距離、相対速度を測定した。なお、前方車間距離センサ21aとしてFrミリ波レーダ、後方車間距離センサ22aとしてRrミリ波レーダを採用した。そして、第3実施形態に係る車両相対位置推定装置を用い、測定した加速度、車輪速、車間距離及び相対速度に基づいて、相対位置及び相対速度の推定を行った。結果を図14~図17に示す。
車両モデルを用いて、2台の車両C1、C2からなる隊列の隊列走行制御システムにより、隊列走行制御のシミュレーションを行った。各車両の加速度センサ24aに基づく相対加速度の誤差ΔArを積分して時間に依存する車間距離推定値の誤差(D_error)、相対速度推定値の誤差(V_error)を算出した。結果を図18に示す。図18(a)は車間距離推定値の誤差D_errorの時間依存性、図18(b)は相対速度推定値の誤差V_errorの時間依存性である。図18(a)に示すように、経過時間に応じて誤差V_error及びD_errorは大きくなることが確認された。そして、図18の算出結果に基づいて、車両制御ECU10により変更された目標車間距離、目標相対速度を図19(a)、(b)にそれぞれ示す。図19(a)、(b)は、目標車間10mの走行時において、Frミリ波レーダ及びRrミリ波レーダが共にロスト状態となった時間から変更された目標車間距離及び目標相対速度である。図19(a)、(b)に示すように、図18(a)、(b)で示す推定誤差以上の目標車間距離及び目標相対速度が設定されることで安全マージンを確保し、走行の安全性を確保することができることが確認された。
Claims (9)
- 第1車両の第2車両に対する相対位置を推定する車両相対位置推定装置であって、
前記第1車両の運動状態を制御する車両制御情報もしくは前記第1車両の車載機器により検出された前記第1車両の運動状態、及び前記第2車両の運動状態を制御する車両制御情報もしくは前記第2車両の車載機器により検出された前記第2車両の運動状態をそれぞれ取得する運動状態取得部と、
前記第1車両又は前記第2車両に搭載される車載機器により検出された前記相対位置を取得する相対位置取得部と、
前記運動状態取得部により取得した前記第1車両の車両制御情報もしくは運動状態及び前記第2車両の車両制御情報もしくは運動状態を入力とするとともに、前記相対位置取得部により取得した前記相対位置を観測量としてカルマンフィルタを用いて前記相対位置を推定する推定部と、
を備えることを特徴とする車両相対位置推定装置。 - 前記運動状態取得部は、前記運動状態として加速度を取得し、
前記相対位置取得部は、前記相対位置としてGPS情報を用いる請求項1に記載の車両相対位置推定装置。 - 前記推定部は、前記第1車両又は前記第2車両に搭載され前記相対位置を検出する車載機器の捕捉状態に対応して、前記カルマンフィルタによる融合の度合いを変更する請求項1に記載の車両相対位置推定装置。
- 前記推定部は、前記第1車両又は前記第2車両に搭載され前記相対位置を検出する車載機器の捕捉状態に対応して、予め算出した前記カルマンフィルタのゲインを切り替える請求項3に記載の車両相対位置推定装置。
- 前記相対位置取得部が、前記第1車両又は前記第2車両に搭載され前記相対位置を検出する車載機器により前記相対位置を取得できない場合には、
前記推定部は、前記運動状態取得部により取得された前記第1車両の車両制御情報もしくは運動状態及び前記第2車両の車両制御情報もしくは運動状態に基づいて、前記相対位置を推定する請求項3に記載の車両相対位置推定装置。 - 前記推定部が、前記第1車両の運動状態及び前記第2の運動状態に基づいて前記相対位置を推定する場合には、
前記第1車両に搭載され前記第1車両の運動状態を検出する車載機器の精度、又は前記第2車両に搭載され前記第2車両の運動状態を検出する車載機器の精度に基づいて、前記第1車両又は前記第2車両の目標相対位置を変更する制御部を備える請求項5に記載の車両相対位置推定装置。 - 第1車両の第2車両に対する相対位置を推定する車両相対位置推定方法であって、
前記第1車両の運動状態を制御する車両制御情報もしくは前記第1車両の車載機器により検出された前記第1車両の運動状態、及び前記第2車両の運動状態を制御する車両制御情報もしくは前記第2車両の車載機器により検出された前記第2車両の運動状態をそれぞれ取得する運動状態取得ステップと、
前記第1車両又は前記第2車両に搭載される車載機器により検出された前記相対位置を取得する相対位置取得ステップと、
前記運動状態取得ステップにより取得した前記第1車両の車両制御情報もしくは運動状態及び前記第2車両の車両制御情報もしくは運動状態を入力とするとともに、前記相対位置取得ステップにより取得した前記相対位置を観測量としてカルマンフィルタを用いて前記相対位置を推定する推定ステップと、
を備えることを特徴とする車両相対位置推定方法。 - 前記運動状態取得ステップは、前記運動状態として加速度を取得し、
前記相対位置取得ステップは、前記相対位置としてGPS情報を用いる請求項7に記載の車両相対位置推定方法。 - 前記推定ステップは、前記第1車両又は前記第2車両に搭載され前記相対位置を検出する車載機器の捕捉状態に対応して、前記カルマンフィルタによる融合の度合いを変更する請求項7に記載の車両相対位置推定方法。
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JP2011170555A (ja) * | 2010-02-17 | 2011-09-01 | Denso Corp | 車群走行制御装置 |
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JP2013033024A (ja) * | 2011-07-05 | 2013-02-14 | Denso Corp | 距離,速度測定装置 |
JP2015082324A (ja) * | 2013-10-22 | 2015-04-27 | ホンダ リサーチ インスティテュート ヨーロッパ ゲーエムベーハーHonda Research Institute Europe GmbH | 予測的運転者支援システムのための複合信頼度推定 |
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JP2021176051A (ja) * | 2020-05-01 | 2021-11-04 | 株式会社豊田中央研究所 | 自車位置推定装置及び自車位置推定プログラム |
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Also Published As
Publication number | Publication date |
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US8594920B2 (en) | 2013-11-26 |
JP5041099B2 (ja) | 2012-10-03 |
US20110301779A1 (en) | 2011-12-08 |
EP2402924A4 (en) | 2012-07-04 |
CN102077259A (zh) | 2011-05-25 |
EP2402924A1 (en) | 2012-01-04 |
CN102077259B (zh) | 2013-09-25 |
JPWO2010097943A1 (ja) | 2012-08-30 |
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