JP2020169901A - Position estimating device and driving assistance device - Google Patents

Abstract

To provide a technology with which it is possible to estimate the position of a vehicle in which the technology is implemented, with good accuracy even under a condition where it is difficult to visually detect the position of the vehicle.SOLUTION: An ECU as a position estimating device comprises: a map information acquisition unit 51 for acquiring the map information of a road that a vehicle 10 travels; an acceleration sensor 23 and a yaw rate sensor 24 as inertial sensors mounted in the vehicle; a lateral gradient detection unit 55, a vertical gradient detection unit 56, a curvature detection unit 57 and a joint detection unit 58 as shape detection units that detect the road surface shape of the road that the vehicle travels, on the basis of the traveling state of the vehicle detected by at least one of vehicle speed sensors 21; a relative position detection unit 53 for detecting the relative position of the vehicle to the road surface shape; and a vehicle position estimation unit 60 for comparing the road surface shape detected by the shape detection unit with the road surface shape included in the map information, specifying the position of the road surface shape in the map position, and estimating the position of the vehicle on the basis of the specified position of the road surface shape and the relative position.SELECTED DRAWING: Figure 1

Description

The present invention relates to a position estimation device that estimates the position of a vehicle and a driving support device that executes driving assistance based on the position of the vehicle estimated by the position estimation device.

Patent Document 1 describes that the current position of the own vehicle is estimated by collating the sign position around the own vehicle detected by the camera sensor mounted on the own vehicle with the sign position read from the map information. ing.

U.S. Pat. No. 9623905

In Patent Document 1, the sign position around the own vehicle is detected based on the visual information acquired by the camera sensor. For this reason, in bad weather such as rainy weather or thick fog, if it is difficult to visually detect the sign position due to factors such as the difference in brightness around the vehicle, vibration of the vehicle, and obstacles around the vehicle, the vehicle's own vehicle It was difficult to accurately estimate the current position.

In view of the above, an object of the present invention is to provide a technique capable of accurately estimating the position of the own vehicle even in a situation where it is difficult to visually detect the position of the own vehicle.

The first position estimation device according to the present invention includes a map information acquisition unit that acquires map information of the road on which the vehicle travels, and at least one of an inertial sensor and a vehicle speed sensor mounted on the vehicle. A shape detection unit that detects the road surface shape of the road on which the own vehicle travels based on the traveling state of the own vehicle detected by the vehicle, and a relative position detection unit that detects the relative position of the own vehicle with respect to the road surface shape. The road surface shape detected by the shape detection unit is collated with the road surface shape included in the map information to specify the position of the road surface shape in the map information, and the position of the specified road surface shape and the relative position. It is provided with a own vehicle position estimation unit that estimates the position of the own vehicle based on the above.

According to the first position estimation device, the road surface shape of the road on which the vehicle travels is based on the traveling condition of the vehicle detected by the shape detection unit by at least one of the inertial sensor and the vehicle speed sensor. Is detected. For example, the road surface shape such as undulations and slopes of the road is detected based on the traveling state such as vibration, acceleration, speed, and yaw angle of the own vehicle. In addition, the relative position detection unit detects the relative position of the own vehicle with respect to the detected road surface shape. Then, the vehicle position estimation unit collates the road surface shape detected by the shape detection unit with the road surface shape in the map information acquired by the map information acquisition unit, and specifies the position of the road surface shape in the map information. Further, the position of the own vehicle in the map information can be estimated based on the position of the road surface shape and the detected relative position of the own vehicle. According to the first position estimation device, the position of the own vehicle is estimated based on the running state of the own vehicle detected by at least one of the inertial sensor and the vehicle speed sensor without using visual information. be able to. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle, the position of the own vehicle can be estimated accurately.

The second position estimation device according to the present invention is mounted on the own vehicle and transmits / receives a signal between the map information acquisition unit that acquires the map information of the road on which the own vehicle travels and the outside of the own vehicle. A road structure detection unit that detects a road structure on the road on which the vehicle travels based on the sensitivity of the external communication device, and a relative position detection unit that detects the relative position of the vehicle with respect to the road structure. The road structure detected by the road structure detection unit is collated with the road structure included in the map information to identify the position of the road structure in the map information, and the specified road structure is specified. The vehicle includes a vehicle position estimation unit that estimates the position of the vehicle based on the position and the relative position.

According to the second position estimation device, the road structure detection unit detects the road structure on the road on which the own vehicle travels, based on the sensitivity of the external communication device. For example, when communication in an external communication device is interrupted, a shield that interferes with the communication can be detected as a road structure. Then, the relative position of the own vehicle with respect to the road structure and the relative position of the own vehicle with respect to the detected road structure are detected by the relative position detection unit. Then, the vehicle position estimation unit collates the road structure detected by the road structure detection unit with the road structure in the map information acquired by the map information acquisition unit, and the position of the road structure in the map information is collated. To identify. Further, the position of the own vehicle in the map information can be estimated based on the position of the road structure and the detected relative position of the own vehicle. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle, the position of the own vehicle can be estimated accurately.

The third position estimation device according to the present invention has a map information acquisition unit that acquires map information of the road on which the own vehicle travels, and the own vehicle that is mounted on the own vehicle and travels by using the reflected wave of the exploration wave. The road structure detection unit that detects the road structure of the road, the relative position detection unit that detects the relative position of the own vehicle with respect to the road structure, and the road structure detected by the road structure detection unit. The position of the road structure in the map information is specified by collating with the road structure included in the map information, and the position of the own vehicle is determined based on the position of the specified road structure and the relative position. It is provided with a vehicle position estimation unit for estimating.

According to the third position estimation device, the road structure detection unit can detect the road structure on the road on which the own vehicle travels by using the reflected wave of the exploration wave. Then, as in the second position estimation device, the road structure detected by the own vehicle position estimation unit is collated with the road structure in the map information, and the position of the road structure in the map information and the road surface are checked. The position of the own vehicle in the map information can be estimated based on the relative position of the own vehicle with respect to the structure. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle, the position of the own vehicle can be estimated accurately.

The present invention also provides a driving support device that executes driving support based on the position of the vehicle estimated by the above-mentioned first to third position estimation devices. According to the driving support device according to the present invention, the route map information which is the map information of the road which is the traveling route of the own vehicle is acquired based on the position of the own vehicle estimated by the first to third position estimation devices. However, the traveling of the own vehicle can be controlled based on this route map information. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle, it is possible to execute appropriate driving support based on the accurately estimated position of the own vehicle.

FIG. 3 is a schematic view of a vehicle equipped with an ECU that functions as a position estimation device and a driving support device according to the first embodiment. Diagram showing roads and their joints. The figure which shows the case where a vehicle passes a joint of a road. FIG. 4A is a diagram showing vertical acceleration obtained from the acceleration sensor. FIG. 4B is a diagram showing a vibration score calculated from FIG. 4A. The figure which shows the x-axis and the y-axis set with respect to the reference line of the traveling lane of the own vehicle. The figure which shows the relative position of the own vehicle with respect to a joint. A control block diagram showing the control executed by the lateral control unit. A control block diagram showing the control executed by the vertical control unit. The figure which shows a plurality of synchronization points set for a plurality of reference lines. The flowchart which shows the position estimation process and the driving support process which the ECU which concerns on 1st Embodiment execute. FIG. 11A is a diagram showing the curvature of the road. FIG. 10B is a diagram showing the lateral slope of the road. FIG. 11C is a diagram showing the vertical slope of the road. FIG. 10D is a diagram showing a lateral gradient of a road obtained by linearly approximating FIG. 10B for each predetermined section. FIG. 12A is a diagram showing a predetermined section divided along a reference line. FIG. 12B is a diagram showing the curvature of the road linearly approximated for each predetermined section. FIG. 12C is a diagram showing the lateral slope of the road linearly approximated for each predetermined section. FIG. 12D is a diagram showing the vertical slope of the road linearly approximated for each predetermined section. The conceptual diagram which shows the map information DB which stores the position shown in FIG. 12, the curvature, the horizontal gradient, and the vertical gradient in association with each other. The flowchart which shows the position estimation process and driving support process which the ECU which concerns on 2nd Embodiment executes. The flowchart which shows the position estimation process and the driving support process which the ECU which concerns on 3rd Embodiment executes. The figure which shows the relative position of the own vehicle with respect to the road structure which is a shield which shields communication with the outside. The flowchart which shows the position estimation process and the driving support process which the ECU which concerns on 4th Embodiment executes. FIG. 18A is a diagram showing the positional relationship between a plurality of shields in a traveling path and a plurality of artificial satellites. 18 (b) and 18 (c) are diagrams showing transmission / reception history patterns of a plurality of artificial satellites, respectively. The figure which shows the relative position of the own vehicle with respect to the road structure detected by a radar sensor. The flowchart which shows the position estimation process and the driving support process which the ECU which concerns on 4th Embodiment executes.

(First Embodiment)
As shown in FIG. 1, the own vehicle 10 is a vehicle including a sensor group 20, an external communication device 30, an ECU 40, and a controlled object 80. The ECU 40 functions as a position estimation device that estimates the position of the own vehicle 10, and also functions as a driving support device that executes driving support of the own vehicle based on the position of the own vehicle 10 estimated by the position estimation device.

The sensor group 20 includes a vehicle speed sensor 21, a steering angle sensor 22, an acceleration sensor 23, a yaw rate sensor 24, and a radar sensor 25.

The vehicle speed sensor 21 is attached to, for example, a wheel portion of a wheel, and outputs a vehicle speed signal corresponding to the wheel speed of the vehicle to the ECU 40. When the vehicle speed sensors 21 are installed on a plurality of wheels, the average value, the intermediate value, or the like of the detected values of the plurality of vehicle speed sensors 21 may be used as the vehicle speed V of the own vehicle 10. For example, when the vehicle speed sensor 21 is installed on each of the four wheels, the second detection value from the fastest of the four detection values may be used.

The steering angle sensor 22 is attached to the steering rod of the vehicle, for example, and outputs a steering angle signal to the ECU 40 according to a change in the steering angle of the steering wheel due to the operation of the driver.

The acceleration sensor 23 detects the acceleration around three orthogonal axes defined around the own vehicle 10 and outputs an acceleration signal to the ECU 40. The acceleration sensor 23 is sometimes referred to as a G sensor.

The yaw rate sensor 24 outputs a yaw rate signal to the ECU 40 according to the change speed of the steering amount of the own vehicle 10. Only one yaw rate sensor 24 may be installed, or a plurality of yaw rate sensors 24 may be installed. When only one is installed, for example, it is installed at the center position of the own vehicle 10. When a plurality of yaw rate sensors 24 are installed, an average value, an intermediate value, or the like of the detected values of the plurality of yaw rate sensors 24 may be used as the detection value.

The acceleration sensor 23 and the yaw rate sensor 24 are inertial sensors. The inertial sensor may be provided with a gyro sensor or the like in addition to the above. The gyro sensor can detect the rotation angles around three orthogonal axes defined around the own vehicle 10.

The radar sensor 25 is a sensor capable of detecting an object around the own vehicle 10 by using the reflected wave of the exploration wave. More specifically, the radar sensor 25 is, for example, a known millimeter-wave radar that uses a high-frequency signal in the millimeter-wave band as a transmission wave. Only one radar sensor 25 may be installed in the own vehicle 10, or a plurality of radar sensors 25 may be installed in the own vehicle 10. The radar sensor 25 is provided at the front end of the own vehicle 10, for example, and has a detection range in which an object can be detected in a region within a predetermined detection angle, and can detect the position of an object within the detection range. Specifically, the exploration wave is transmitted at a predetermined cycle, and the reflected wave is received by a plurality of antennas. The distance to the object can be calculated from the transmission time of the exploration wave and the reception time of the reflected wave.

Further, according to the radar sensor 25, the relative velocity of the reflected wave reflected by the object can be calculated from the frequency changed by the Doppler effect. In addition, the orientation of the object can be calculated from the phase difference of the reflected waves received by the plurality of antennas. If the position and orientation of the object can be calculated, the relative position between the object and the own vehicle 10 can be specified.

Similar to the radar sensor 25, it is equipped with a sensor such as an ultrasonic sensor and LIDAR (Light Detection and Ranger / Laser Imaging Detection and Ranger) as a sensor that can detect an object around the own vehicle 10 by using the reflected wave of the search wave. You may.

The sensor that transmits the exploration wave, such as the radar sensor 25, sequentially outputs the scanning result based on the received signal obtained when the reflected wave reflected by the obstacle is received to the ECU 40 as sensing information. A sensor that transmits an exploration wave, such as a radar sensor 25, can be suitably used for detecting an object having a large reflected power. The sensor that transmits the exploration wave, such as the radar sensor 25, is not limited to the object in front of the own vehicle 10, and may detect and use an object in the rear or side.

The external communication device 30 includes a radio wave communication device 31 and a GNSS (Global Navigation Satellite System) receiving device 32. The ECU 40 can communicate with the external server 12 installed outside the own vehicle 10 by the external communication device 30. The external server 12 includes an external map information database (DB) 13.

The external map information DB 13 stores map information used for traveling guidance and route search of the own vehicle 10. Map information is composed of various information necessary for route guidance and map display. For example, new road information for identifying each new road, map display data for displaying a map, intersection data for each intersection, and so on. It includes road data related to roads, search data for searching routes, facility data related to POI (Point of Information) such as stores, which is a type of facility, and search data for searching points.

The road data includes road length, width, position (for example, position represented by latitude and longitude), number of lanes, slope information regarding road slope (for example, horizontal slope information, vertical slope information), and road. The curvature information regarding the curvature of the road joint, the joint information regarding the road joint, and the road structure information regarding the road structure can be exemplified.

The slope information includes information on the magnitude and position of the road slope, as well as information on detection data (detection value and detection waveform) when the road slope is detected by sensors. The vertical gradient information is information on the gradient in the vertical direction (traveling direction) of the own vehicle 10, and the horizontal gradient information is information on the gradient in the lateral direction (horizontal width direction orthogonal to the traveling direction) of the own vehicle 10. The curvature information includes information on the magnitude, direction, and position of the curvature of the road, as well as information on detection data when the curvature is detected by sensors.

The joint information includes information on the position and size of the joint, as well as detection data when the joint is detected by sensors. As shown in FIG. 2, the joint 100 is a connecting member provided at the joint of the road 90. The rectangular fitting portion of the joint 100 and the connecting portion between the joint 100 and the road 90 are undulating, and the undulations cause the vehicle 10 to vibrate when passing through the joint 100. As shown in FIGS. 3A and 3B, the road 90 has undulations at the joints 101 and 102 provided on the road 90 in the traveling direction of the own vehicle 10. Therefore, when passing through the joints 101 and 102, the own vehicle 10 vibrates in the vertical direction. Detection data related to this vibration is included as joint information.

The road structure information includes information on the type, size, and position of the road structure, as well as detection data when the road structure is detected by sensors.

The detection data included in the map information is the data detected by the sensors when actually traveling on the road. Only one detection data may be stored for the detection target, or a plurality of detection data may be stored. Further, the detected data may be stored in the external map information DB 13 in a state in which changes in the detected values corresponding to the position and the distance are patterned.

The radio wave communication device 31 is a device for the own vehicle 10 to communicate with the outside by transmitting and receiving radio waves. The radio wave communication device 31 is based on Wifi (registered trademark) radio waves, mobile base station radio waves, vehicle information and communication system (VICS (registered trademark)) radio waves, and V2X (Vehicle to X) radio waves. An example of a device that performs communication can be illustrated.

The GNSS receiving device 32 is a receiving device in a system that performs position measurement, navigation, and time distribution using signals emitted from artificial satellites. As satellite systems that provide GNSS functions, in addition to GPS (Global positioning system), GLO (Global Navigation Satellite System; GLONASS), GAL (Galileo), QZS (Quasi-Zenith Satellite System, Quasi-Zenith) , BDS (Hokuto Satellite Navigation System, BeiDou Navigation Satellite System) can be exemplified. The GNSS receiving device 32 receives the positioning signal at predetermined intervals. The position of the own vehicle 10 can be estimated sequentially by sequentially receiving the positioning signal from the artificial satellite by the GNSS receiving device 32.

The ECU 40 is mainly composed of a microcomputer including a CPU, ROM, RAM, backup RAM, I / O, etc. (none of which are shown), and by executing various control programs stored in the ROM, the present specification Each function explained in the book can be realized.

The ECU 40 includes an in-vehicle map information DB 41, a position estimation unit 50, and a driving support unit 70. The in-vehicle map information DB 41 stores the map information acquired from the external map information DB 13. The in-vehicle map information DB 41 may be configured to store only the map information related to the travel path of the own vehicle 10 among the map information that can be acquired from the external map information DB 13. Alternatively, the in-vehicle map information DB 41 may be configured to be stored in a lightweight state by approximating the map information acquired from the external map information DB 13.

The position estimation unit 50 detects a predetermined characteristic element on the traveling road which is the road on which the own vehicle 10 travels, and collates the characteristic element with one or more characteristic elements included in the map information. Then, the position of the characteristic element in the collated map information is specified as the position of the detected characteristic element. Then, the relative position of the own vehicle 10 with respect to the characteristic element is detected, and the position of the own vehicle 10 is estimated. The predetermined characteristic element may be, but is not limited to, a road surface shape such as a horizontal slope, a vertical slope, a curvature, and undulations of a traveling road, a road structure, and the like.

The position estimation unit 50 includes a map information acquisition unit 51, a transmission / reception history acquisition unit 52, a relative position detection unit 53, a vibration detection unit 54, a horizontal gradient detection unit 55, a vertical gradient detection unit 56, and a curvature detection unit. It includes 57, a joint detection unit 58, a road structure detection unit 59, a vehicle position estimation unit 60, an error correction unit 61, and a storage unit 62.

The map information acquisition unit 51 acquires information on characteristic elements of the travel path included in the map information. Specifically, gradient information regarding the slope of the travel path, curvature information regarding the curvature of the travel path, joint information regarding the road joint, road structure information regarding the road structure, and the like are acquired. More specifically, information on the type, position, shape, size, detection data, etc. of the gradient, curvature, joint, and on-road structure on the traveling road is acquired. The map information acquisition unit 51 may acquire map information from the external map information DB 13 or may acquire map information from the vehicle-mounted map information DB 41 via the external communication device 30.

The map information acquisition unit 51 may be configured to acquire only map information in the vicinity of the own vehicle 10. For example, it may be configured to acquire map information within a predetermined range from the approximate position of the own vehicle 10 estimated by the positioning signal using the GNSS receiving device 32. The acquired map information may be stored in the vehicle-mounted map information DB 41 by the storage unit 62 described later.

The transmission / reception history acquisition unit 52 acquires the transmission / reception history of the external communication device 30. As the transmission / reception history, for example, the time-dependent change in the sensitivity of the external communication device 30 is acquired. The acquired transmission / reception history may be configured to be stored in the ECU 40 by the storage unit 62 described later.

The relative position detection unit 53 detects the relative position xr of the own vehicle 10 with respect to a predetermined characteristic element in the traveling path of the own vehicle 10. The relative position detection unit 53 is the relative of the own vehicle 10 to the characteristic elements detected by the horizontal gradient detection unit 55, the vertical gradient detection unit 56, the curvature detection unit 57, the joint detection unit 58, and the road structure detection unit 59, which will be described later. The position xr is detected.

The vibration detection unit 54 acquires the detection value of the inertial sensor such as the acceleration sensor 23, and detects the vibration of the own vehicle 10 in the vertical direction based on the acquired detection value. For example, the vibration score shown in FIG. 4B is calculated from the change in the vertical acceleration of the own vehicle 10 shown in FIG. 4A. The positions of the own vehicle 10 shown on the horizontal axis in FIGS. 4A and 4B are the same. As shown in FIGS. 4A and 4B, the vibration score is large in the section where the gravitational acceleration in the vertical direction changes greatly in the positive and negative directions.

Specifically, a high-pass filter (for example, a third-order filter) is applied to the detection value Gz1 of the vertical acceleration as shown in FIG. 4A to remove the bias component of the signal. As a result, the signal value S1 is acquired. Further, the predetermined value S0 is subtracted from the abs (S1) which is the absolute value of the acquired signal value S1 by the following equation (1) to acquire the signal value S2. It is preferable that the predetermined value S0 is appropriately adjusted based on the detection performance of the acceleration sensor 23.

S2 = abs (S1) -S0 ... (1)

Further, the signal value S3 is set based on the signal value S2. When S2 <0, it is set to S3 = 0, and when S2 ≧ 0, it is set to S3 = S2. As a result, the signal value S2 that is too small can be canceled.

Then, the weighted moving average is applied to the plurality of positive signal values S3 obtained on the traveling path of the own vehicle 10. For example, the weighted moving average value calculated for n positive signal values S3 acquired from the present time to the past is defined as the signal value S4. FIG. 4B shows the signal value S4 calculated by the above procedure.

The horizontal gradient detection unit 55, the vertical gradient detection unit 56, the curvature detection unit 57, and the joint detection unit 58 are specific examples of the shape detection unit that detects the road surface shape of the traveling path of the own vehicle 10. The horizontal gradient, vertical gradient, and curvature detected by the horizontal gradient detecting unit 55, the vertical gradient detecting unit 56, and the curvature detecting unit 57 are stored in the ECU 40 as changes in the horizontal gradient corresponding to the mileage and traveling time of the own vehicle 10. You may.

Hereinafter, as shown in FIG. 5, the x-axis is set along the reference line B of the traveling path of the own vehicle 10, and the y-axis is set in the lateral direction perpendicular to the x-axis for description. The reference line B is a line located at the center of the traveling lane 91 of the own vehicle 10 on the road 90 shown in FIG. 3 in the lane width direction. In the present specification, the x-axis direction shown in FIG. 5 may be referred to as a traveling direction or a vertical direction of the own vehicle 10. Further, the y direction shown in FIG. 5 may be referred to as a lateral direction. Further, the lateral gradient is a gradient in the lateral direction, and indicates a gradient in the y direction. The lateral gradient is sometimes referred to as a cant, a transverse gradient, or the like. The vertical gradient is a gradient in the vertical direction, and indicates a gradient in the x direction. The vertical gradient is sometimes referred to as a slope, a vertical gradient, or the like.

The lateral gradient detection unit 55 itself is based on the vehicle speed detection value V of the own vehicle 10 by the vehicle speed sensor 21, the lateral acceleration detection value Ay by the acceleration sensor 23, and the yaw rate detection value YR by the yaw rate sensor 24. The lateral gradient Sy of the traveling path of the vehicle 10 is detected.

Specifically, each detected value is smoothed by a low-pass filter (LPF), and the lateral gradient Sy is calculated from the following equation (2) using the smoothed vehicle speed Vsmo, lateral acceleration Ay_smo, and yaw rate YRsmo. In addition, g represents the gravitational acceleration.

Sy = (Ay_smo + Vsmo x YRsmo) / g ... (2)

The vertical gradient detection unit 56 detects the vertical gradient of the traveling path of the own vehicle 10 based on the detection value V of the vehicle speed of the own vehicle 10 by the vehicle speed sensor 21 and the detection value Ax of the vertical acceleration by the acceleration sensor 23. ..

Specifically, first, each detected value is smoothed by LPF. Then, for the smoothed vehicle speed Vsmo, the differential value dVsmo based on the forward difference is calculated as shown in the following equation (3). Note that dt is the time step interval, Vsmo (i) is the current (current step time) vehicle speed, and Vsmo (i-1) is the previous (previous step time) vehicle speed.

dVsmo = (Vsmo (i) -Vsmo (i-1)) / dt ... (3)

Then, the vertical gradient Sx is calculated from the following equation (4) using the differential value dVsmo and the vertical acceleration Ax_smo.

Sx =-(Ax_smo + dVsmo) / g ... (4)

The curvature detection unit 57 detects the curvature Cu of the traveling path of the own vehicle 10 based on the detected values of the vehicle speed sensor 21, the steering angle sensor 22, the acceleration sensor 23, the yaw rate sensor 24, and the like. For example, the curvature Cu is calculated from the following equation (5) using the yaw rate YR and the vehicle speed V.

Cu = YR / V ... (5)

The joint detection unit 58 detects the undulations of the road surface caused by the joints provided on the traveling path of the own vehicle 10. As shown in FIGS. 3A and 3B, when the own vehicle 10 is traveling on the road 90 and passes through the joints 101 and 102 provided on the road 90, the own vehicle 10 vibrates in the vertical direction. This vibration is detected by the vibration detection unit 54, and the vibration score shown in FIG. 4B can be obtained.

The joint detection unit 58 sets a score threshold value Fth for the vibration score shown in FIG. 4B, and detects that there is a joint when the vibration score is equal to or higher than the threshold value Fth. In FIG. 4B, the presence of one joint is detected. The score threshold value Fth is set as a lower limit value recognized as a vibration score derived from the joint. By setting the score threshold value Fth, vibration and noise due to undulations of the road surface other than the joint can be excluded.

The road structure detection unit 59 detects the road structure based on the transmission / reception history acquired by the transmission / reception history acquisition unit 52 and the object information detected by the radar sensor 25. For example, while the own vehicle 10 is passing through the tunnel, the reception sensitivity of the GNSS receiving device 32 decreases. Therefore, the road structure detection unit 59 extracts a section in which the reception sensitivity of the GNSS receiving device 32 decreases from the acquired transmission / reception history. As a result, it is possible to detect a tunnel or the like in the traveling path of the own vehicle 10 and estimate its size or the like.

Further, for example, when the exploration wave output by the radar sensor 25 is reflected by a metal structure such as a guardrail, a median strip, a road sign, or a signboard, it becomes a strong reflected wave and is received by the radar sensor 25. Therefore, the road structure detection unit 59 extracts a section in which a strong reflected wave is detected by the radar sensor 25. As a result, the road structure can be detected and its size and the like can be estimated.

The own vehicle position estimation unit 60 collates the detected characteristic elements of the travel path (for example, road surface shape and road structure) with the characteristic elements of the travel path included in the map information, and in the collated map information. The position of the characteristic element is specified as the position of the detected characteristic element. Then, based on the following equation (6), the map is obtained from the position xb of the specified characteristic element and the relative position xr (detected by the relative position detection unit 53) of the own vehicle 10 with respect to the detected characteristic element. The position xc of the own vehicle 10 in the information is estimated. The relative position xr is set to a positive value when the own vehicle 10 is on the traveling direction side (traveling direction forward side) with respect to the detected characteristic element.

xc = xb + xr ... (6)

Specifically, for example, as shown in FIG. 6, when the joints 101 and 102 provided on the road 90, which is the traveling path of the own vehicle 10, are passed, the position Pj1 of the joint 101 is determined based on the map information. , The position Pj2 of the joint 102 is specified. The relative position detection unit 53 can calculate the relative position xr of the own vehicle 10 with respect to the position Pj1 or Pj2. The relative position xr of the own vehicle 10 with respect to the joint 102 is a positive value represented by the distance Lc2 between the joint 102 and the own vehicle 10. The relative position of the own vehicle 10 with respect to the joint 101 is a positive value represented by the distance (Lj2 + Lc2) between the joint 101 and the own vehicle 10.

For example, the position Pj2 of the joint 102 is specified from the map information, and the relative position Lc2 of the own vehicle 10 with respect to the joint 102 is calculated based on the vehicle speed V and the like of the own vehicle 10. Then, in the above equation (6), by setting xb = Pj2 and xr = Lc2, the position Pc of the own vehicle 10 can be estimated based on the map information.

The error correction unit 61 has an inertial sensor (for example, an acceleration sensor 23, a yaw rate sensor 24) and a vehicle speed sensor mounted on the vehicle 10 based on the road surface shape around the vehicle 10 acquired by the map information acquisition unit 51. The detection error is corrected for at least one of 21.

The storage unit 62 stores map information acquired from the external map information DB 13 of the external server 12, detected values acquired from the sensor group 20, and calculated values calculated based on the detected values, as a storage means (RAM or the like) provided in the ECU 40. ). The map information is stored in the in-vehicle map information DB 41. The storage unit 62 is configured to store the map information regarding the slope or curvature of the travel path acquired by the map information acquisition unit 51 in the vehicle-mounted map information DB 41 by linearly approximating each predetermined section of the travel path. You may. By storing the map information in an approximate manner in this way, the load on the storage capacity of the ECU 40 can be reduced.

The driving support unit 70 executes a process related to driving support of the own vehicle 10 based on the position of the own vehicle 10 estimated by the position estimation unit 50. As driving support, for example, a control command signal for controlling the control target 80 is output. The driving support unit 70 includes a route map information acquisition unit 71 and a travel control unit 72.

The route map information acquisition unit 71 acquires map information on the travel route on which the vehicle 10 is about to travel, based on the position of the vehicle 10 estimated by the position estimation unit 50. The route map information acquisition unit 71 may acquire map information from the external map information DB 13 or may acquire map information from the vehicle-mounted map information DB 41 via the external communication device 30.

The travel control unit 72 includes a lateral control unit 73 and a vertical control unit 74. The travel control unit 72 includes a lateral control unit 73 and a vertical control unit 74, so that the vehicle 10 can be automatically driven and parked according to a travel plan or the like. The travel control unit 72 functions as an LKA (Lane Keeping Assist), an LCA (Lane Change Assist), an ACC (Adaptive Cruise Control), or the like during automatic driving. LKA is a function of maintaining a running lane and driving a vehicle by generating a steering force in a direction that prevents the vehicle from approaching the traveling lane. LCA is a function of automatically moving a vehicle to an adjacent lane. Further, ACC is a function of controlling the traveling speed of the own vehicle so as to maintain the target inter-vehicle distance from the preceding vehicle by adjusting the driving force and the braking force.

The travel control unit 72 may be further configured to have a function other than the above. For example, a PCS (Pre-Crash Safety) system that determines the presence or absence of a collision with an object located around a vehicle and controls the object to avoid a collision with the object or to reduce collision damage. It may be configured to have such a function as. Objects around the own vehicle 10 can be detected by a radar sensor 25 or the like.

The lateral control unit 73 controls the steering of the own vehicle 10 by using the steering angle target value of the own vehicle 10 calculated based on the curvature information and the lateral gradient information. The lateral control unit 73 can control the lateral position y of the own vehicle 10. The vertical control unit 74 performs drive control and braking control of the own vehicle 10 by using the acceleration / deceleration target value calculated based on the vertical gradient information. The vehicle speed V of the own vehicle 10 can be controlled by the vertical control unit 74.

The control block diagrams in the horizontal direction (y-axis direction) and the vertical direction (x-axis direction) are shown in FIGS. 7 and 8, respectively. The lateral control block diagram shown in FIG. 7 includes a process executed on the ECU 40 side and a process executed on the controlled target 80 side. The lateral control process executed on the ECU 40 side is executed by the lateral control unit 73. The lateral control unit 73 includes a steering angle calculation unit 111, a lateral position feedback (FB) control unit 112, and a steering angle FB control unit 113. The control target 80 includes a steering angle dynamics 114 and a vehicle / wheel dynamics 115.

The steering angle calculation unit 111 is based on the input of the vehicle speed V of the own vehicle 10 acquired from the vehicle speed sensor 21, the curvature Cu of the traveling path of the own vehicle 10 acquired from the map information, and the lateral gradient (cant) Sy. The steering angle feed forward (FF) term Dff is calculated.

The lateral position FB control unit 112 steers based on the inputs of the lateral position target value yob and the yaw angle target value θob and the current lateral position y and yaw angle θ of the current own vehicle 10 output by the vehicle / wheel dynamics 115. The angle FB term Dfb is output. In order to drive the own vehicle 10 along the reference line B, the lateral position target value yob and the yaw angle target value θob are preferably set to zero. The rudder angle FB term Dfb can be calculated by, for example, the following equation (7). In addition, kpy is a proportional control constant, and kdy is a differential control constant.

Dfb = kpy × (yoby) + kdy × (θob-θ)… (7)

The rudder angle FB term Dfb and the rudder angle FF term Dff are added and input to the rudder angle FB control unit as a rudder angle command value Dc. The rudder angle command value Dc corresponds to the rudder angle target value. The steering angle FB control unit 113 outputs the steering torque Tq based on the input of the steering angle command value Dc and the steering angle Dm of the current own vehicle 10 output by the steering angle dynamics 114. The steering torque Tq is calculated as the steering torque required to control the steering angle Dm to the steering angle command value Dc.

The steering angle dynamics 114 is a control target of the own vehicle 10 regarding the steering angle, and corresponds to the steering device 83. That is, the steering device 83 is steered and controlled based on the input steering torque Tq. The vehicle / wheel dynamics 115 is a control target of the own vehicle 10 with respect to the vehicle / wheel, and outputs the lateral position y and the yaw angle θ of the own vehicle 10 when the steering device 83 is steered by the steering torque Tq.

The vertical control block diagram shown in FIG. 8 includes a process executed on the ECU 40 side and a process executed on the controlled object 80 side. The vertical control process executed on the ECU 40 side is executed by the vertical control unit 74. The vertical control unit 74 includes an acceleration calculation unit 121, a vehicle speed feedback (FB) control unit 122, and an engine / brake (E / B) FB control unit 123. The control target 80 includes E / B dynamics 124 and vehicle / wheel dynamics 125.

The acceleration calculation unit 121 sets the acceleration FF term Aff based on the input of the vehicle speed V of the own vehicle 10 acquired from the vehicle speed sensor 21 and the vertical gradient Sx of the traveling path of the own vehicle 10 acquired from the yaw rate sensor 24. calculate.

The vehicle speed FB control unit 122 outputs the acceleration FB term Afb based on the input of the vehicle speed target value Vob and the vehicle speed V of the current own vehicle 10 output by the vehicle / wheel dynamics 125. The acceleration FB term Afb can be calculated by, for example, the following equation (8).

Afb = kpx × (Vob-V)… (8)

The acceleration FB term Afb and the acceleration FF term Aff are added and input to the E / B / FB control unit 123 as an acceleration command value Ac. The acceleration command value Ac corresponds to the acceleration / deceleration target value. The E / B / FB control unit 123 outputs the E / B control value EB based on the input of the acceleration command value Ac and the current acceleration Am of the own vehicle 10 output by the E / B dynamics 124. The E / B control value EB is a control value of the engine or the brake for controlling the acceleration Am to the acceleration command value Ac, and specifically, is a control value of the engine opening degree, the brake cylinder pressure, and the like.

The E / B dynamics 124 is a control target of the own vehicle 10 regarding the engine brake, and corresponds to the drive device 81 and the braking device 82. The drive device 81 and the braking device 82 are controlled based on the E / B control value EB. The vehicle / wheel dynamics 125 outputs the vehicle speed V of the own vehicle 10 when the drive device 81 and the braking device 82 are controlled by the E / B control value EB.

According to the lateral control unit 73 and the vertical control unit 74, the steering angle FF, which is an FF term, is based on the lateral gradient information, the longitudinal gradient information, and the curvature information in the traveling route of the own vehicle 10 acquired as the route map information. The term Dff and the acceleration FF term Aff can be calculated. This FF term is added to the steering angle FB term Dfb and the acceleration FB term Afb, which are the FB terms, respectively, and the own vehicle 10 is accurately based on the steering angle command value Dc and the acceleration command value Ac obtained as the sum. Can be controlled. Therefore, the traveling controllability of the own vehicle 10 is improved.

In particular, when passing through a curved road, the traveling controllability of the own vehicle 10 is remarkably improved. For example, when the curvature of a curved road is detected by an imaging device and the vehicle travel control is performed according to the detected curvature, there is a concern that the detection of the curvature by the imaging device is slow and the steering control is delayed. On the other hand, according to the driving support unit 70, the curvature of the curved road can be quickly acquired as map information based on the position of the own vehicle 10 accurately estimated by the position estimation unit 50. Therefore, the delay in the steering control on the curved road can be eliminated, and the steering control of the own vehicle 10 can be accurately executed.

Further, as a function related to LCA, the driving support unit 70 is configured to have a function of making the vertical position of the current driving lane reference line correspond to the reference line of the traveling lane after the lane change when the lane is changed. You may be.

For example, for a road 90 having three lanes on each side as shown in FIG. 3, reference lines B1 to B3 are set for each lane as shown in FIG. For the own vehicle 10 traveling along the reference line B2, the vertical position on the reference line B2 is estimated, but the vertical position on the reference lines B1 and B3 is not estimated. Therefore, when the own vehicle 10 changes lanes, the vertical position of the own vehicle 10 on the reference line B2 is associated with the vertical position on the reference line (reference line B1 or reference line B3) after the lane change. To do.

Specifically, as shown in FIG. 9, synchronization points MP1 to MP4 are set on the reference lines B1 to B3. Then, for example, the reference line B2 is selected as the main reference line, and the length Lmp1 of the reference line B2 from the previous synchronization point to the current synchronization point is calculated for each synchronization point. Further, the lengths Lmp2 and Lmp3 of the reference lines B1 and B3 from the previous synchronization point to the current synchronization point are calculated. Then, dLmp1 (= Lmp1-Lmp2), which is the difference between the length Lmp2 and the length Lmp1, and dLmp3 (= Lmp3-Lmp2), which is the difference between the length Lmp2 and the length Lmp3, are calculated. A map information DB including Lmp2, dLmp1 and dLmp3 calculated for each synchronization point as map information is prepared.

The route map information acquisition unit 71 acquires map information including Lmp2, dLmp1, and dLmp3 stored for each synchronization point MP1 to MP4. For example, when the own vehicle 10 changes lanes and the reference line of the traveling path of the own vehicle 10 is changed from the reference line B2 to the reference line B1, Lmp2 and dLmp1 at the synchronization point closest to the current position of the own vehicle 10 , DLmp3 can be used to convert the vertical position of the vehicle 10 estimated on the reference line B2 to the vertical position estimated on the reference line B1.

It is preferable to adjust the setting interval and the number of synchronization points according to the form of the reference line. For example, in a region where the difference in distance between reference lines is large, such as a curved road having a large curvature, the number of synchronization points is increased and the interval is set narrow, as shown in, for example, synchronization points MP2 to MP4. On the other hand, in an area where the difference in distance between reference lines such as a substantially orthogonal road is small, the number of synchronization points is reduced and the interval is set wide as shown in synchronization points MP1 to MP2. Further, it is preferable to set synchronization points at the connection points and separation points of the road so that the positional relationship between the reference lines can be updated.

The control target 80 includes a drive device 81, a braking device 82, a steering device 83, an alarm device 84, and a display device 85. The control target 80 is configured to operate based on a control command from the ECU 40 and to operate according to an operation input of the driver. The driver's operation input may be input to the control target 80 as a control command signal to the ECU 40 after being appropriately processed by the ECU 40.

The drive device 81 is a device for driving the vehicle, and is controlled by the driver's operation of the accelerator or the like or a command from the driving support unit 70 of the ECU 40. Specifically, the drive source of the vehicle such as an internal combustion engine, a motor, and a storage battery, and each configuration related thereto can be mentioned as the drive device 81. The ECU 40 has a function of automatically controlling the drive device 81 according to the travel plan of the own vehicle 10 and the vehicle state.

The braking device 82 is a device for braking the own vehicle 10, and is controlled by a driver's braking operation or a command from the driving support unit 70 of the ECU 40. The ECU 40 has a brake assist function that enhances and assists the braking force by the driver's brake operation as a brake function for avoiding a collision with an object or reducing collision damage, and automatic braking when there is no driver's brake operation. It may have an automatic braking function to perform the above. The braking device 82 can perform brake control by these functions based on the control command signal from the ECU 40.

The steering device 83 is a device for steering the own vehicle 10, and is controlled by a steering operation of the driver or a command from the driving support unit 70 of the ECU 40. The ECU 40 has a function of automatically controlling the steering device 83 for collision avoidance or lane change.

The alarm device 84 is a device for aurally notifying the driver or the like, for example, a speaker or a buzzer installed in the vehicle interior of the own vehicle 10. The alarm device 84 issues an alarm sound or the like based on the control command signal from the ECU 40 to notify the driver, for example, that a danger is present.

The display device 85 is a device for visually notifying the driver and the like, and is, for example, a display and instruments installed in the vehicle interior of the own vehicle 10. The display device 85 displays an alarm message or the like based on the control command signal from the ECU 40 to notify, for example, the driver that there is a danger.

FIG. 10 shows a flowchart showing the position estimation process and the driving support process executed by the ECU 40 by exemplifying a case where the undulations due to the joints are detected as the road surface shape to estimate the position of the own vehicle and the driving support is executed. The process shown in FIG. 10 is repeatedly executed at a predetermined cycle when the own vehicle 10 is driven.

In step S101, the joint information on the traveling path of the own vehicle 10 is acquired as the map information. Specifically, map information including the position of the joint, the vibration waveform of the vehicle when traveling on the joint, and the like is acquired. The vibration waveform included in the map information is a vibration waveform detected by the acceleration sensor 23 when actually traveling on the road. The process proceeds to step S102.

In step S102, the detection values including the acceleration, vehicle speed, etc. of the own vehicle 10 are acquired from the sensor group 20, and the process proceeds to step S104.

In step S104, for example, the vibration score as shown in FIG. 4B is calculated from the vertical acceleration detected by the acceleration sensor 23 as shown in FIG. 4A. Then, the process proceeds to step S105.

In step S105, it is determined whether or not a joint is detected in the traveling path of the own vehicle 10 based on the vibration score. Specifically, the score threshold value Fth is set for the calculated vibration score Fs. Then, when Fs ≧ Fth, it is determined that the joint has been detected. Further, when Fs <Fth, it is determined that the joint is not detected. When the joint is detected, the processes of steps S106 to S114 are executed. If the joint is not detected, the processes of steps S122 to S124 are executed.

The processes of steps S106 to S114 include the processes of steps S106 to S111 related to the position estimation of the own vehicle 10 and the processes of steps S112 to S114 related to the error correction of the vehicle speed sensor 21.

First, in step S106, the waveform (vibration waveform) of the detected joint vibration score is acquired as the detected waveform Jd. Then, the process proceeds to step S107.

In step S107, from the map information acquired in step S101, the vibration waveform of the vehicle when traveling on the joint is acquired as the map waveform Jm. It is preferable that the map waveform Jm is obtained by extracting a plurality of vibration waveforms of joints located within a predetermined range along the traveling path of the own vehicle 10 from the positions of the own vehicle 10 estimated in the past. After the own vehicle 10, the process proceeds to step S108.

In step S108, the detected waveform Jd is collated with a plurality of map waveforms Jm, and the map waveform Jm having the highest degree of coincidence with the detected waveform Jd is selected. After that, the process proceeds to step S109.

In step S109, the position of the selected map waveform Jm is acquired from the map information and specified as the detected joint position xjm. After that, the process proceeds to step S110.

In step S110, the relative position xr of the own vehicle 10 with respect to the specified joint position xjm is detected. The relative position xr can be calculated as the mileage of the own vehicle 10 that has traveled from the time when the joint is detected to the present. For example, the product (V × Tl) of the average processing time Tl required for the processing from the time when the sensor detection value is acquired in step S102 to step S110 and the vehicle speed V of the own vehicle 10 acquired in step S102 is relative. It may be calculated as the position xr. After that, the process proceeds to step S111.

In step S111, the position xc of the own vehicle 10 is estimated by the following equation (9) based on the joint position xjm specified in step S109 and the relative position xr. Then, the process proceeds to step S112.

xc = xjm + xr ... (9)

In step S112, the position of the own vehicle 10 estimated in the past is acquired. For example, the estimated own vehicle position xcb is acquired in the cycle in which the joint is detected before the current cycle. After that, the process proceeds to step S113.

In step S113, the estimated mileage xp1 (x = xc−xb) obtained as the difference between the own vehicle position xcb estimated in the past and the own vehicle position xc estimated in the current cycle is calculated. Further, the calculated mileage xp2 is calculated from the elapsed time Tpas from the time when the past own vehicle position xcb is estimated to the time when the current own vehicle position xc is estimated and the change in the vehicle speed V between the elapsed time Tpas. .. Then, the process proceeds to step S114.

In step S114, the error of the vehicle speed sensor 21 is corrected based on the difference between the estimated mileage xp1 and the calculated mileage xp2. Then, the process proceeds to step S130.

On the other hand, in step S122, as in step S112, the own vehicle position xcb estimated in the past is acquired, and the process proceeds to step S123. In step S123, the vehicle is calculated from the change in the detected value of the vehicle speed sensor 21 between the elapsed time Tpas from the time when the past vehicle position xcb is estimated to the time when the current vehicle position xc is estimated and the elapsed time Tpas. The distance xp2 is calculated. Then, the current own vehicle position xcc is estimated from the past own vehicle position xcc and the calculated mileage xp2 by the following equation (10). Then, the process proceeds to step S130.

xcc = xcb + xp2 ... (10)

In step S130, map information (route map information) about the traveling route that the own vehicle 10 is about to travel is acquired based on the own vehicle position estimated in step S111 or step S124. The route map information includes information on the curvature Cu, the horizontal gradient Sy, and the vertical gradient Sx. After that, the process proceeds to step S131.

In step S131, the steering angle command value Dc is calculated based on the curvature Cu and the lateral gradient Sy acquired as the route map information. The rudder angle command value Dc can be calculated, for example, by the process shown in the control block diagram of FIG. 7. After that, the process proceeds to step S132.

In step S132, the acceleration command value Ac is calculated based on the vertical gradient Sx acquired as the route map information. The acceleration command value Ac can be calculated, for example, by the process shown in the control block diagram of FIG. After that, the process proceeds to step S133.

In step S133, driving support is executed for the drive device 81, the braking device 82, the steering device 83, and the like based on the calculated steering angle command value Dc and the acceleration command value Ac, and the process ends.

According to the present embodiment, the ECU 40 uses the detection value of the acceleration sensor 23 mounted on the vehicle to generate the own vehicle 10 when the own vehicle 10 passes through a joint provided in the traveling path. Vibration can be detected. Then, the own vehicle 10 can detect the joint based on the detected vibration of the own vehicle 10. Furthermore, the position of the detected joint can be specified by collating the vibration waveform when the joint is detected with the vibration waveform for each joint included in the map information. Further, the position of the own vehicle 10 can be estimated based on the position of the specified joint and the relative position of the own vehicle 10 with respect to the joint.

According to the ECU 40, the position of the own vehicle 10 can be estimated based on the map information by detecting the joint by using the acceleration sensor 23 mounted on the vehicle. Therefore, the position of the own vehicle 10 can be estimated accurately even in a situation where it is difficult to visually detect the position of the own vehicle 10.

For example, when estimating the position of the own vehicle 10 by recognizing a road sign or the like using an imaging device, the weather such as rainy weather or dense fog, the difference in brightness such as day and night or backlight, image blurring due to vibration, and an adjacent vehicle Under visually impaired environmental conditions such as shielding by, etc., the shape of the sign may not be detected. On the other hand, in the present embodiment, since the vibration accompanying the passage of the joint is detected, the detection is not hindered even under the above-mentioned visually hindered environmental conditions. Therefore, according to the present embodiment, the position estimation of the own vehicle 10 is less likely to be hindered by the environmental conditions.

Further, when estimating the position of the own vehicle 10 by recognizing a road sign or the like using an image pickup device, there is a concern that the confusing shape of the surroundings may be erroneously recognized. According to the present embodiment, in order to estimate the position of the own vehicle 10 by detecting the vibration of the own vehicle 10 due to the passage of the joint, the position of the own vehicle 10 due to the detection error of the joint is compared with the conventional technique using the imaging device. The occurrence of errors in estimation can be suppressed.

In addition, since the position and shape of the joint will not change unless the road structure is significantly modified, the position and shape of the joint will change compared to the frequency with which the position and type of road signs are changed. The frequency of being done is extremely low. Therefore, the frequency of updating the map information regarding the joint can be reduced.

Further, according to the present embodiment, the joint can be detected by using the acceleration sensor 23 generally mounted on the vehicle without adding a new sensor to detect the joint. Therefore, the position of the own vehicle 10 can be estimated accurately while ensuring low cost and small size and light weight of the vehicle.

Further, according to the present embodiment, the position of the own vehicle 10 in the traveling direction (vertical direction, x-axis direction) is estimated with higher accuracy than when the position of the own vehicle 10 is estimated by the imaging device or the GNSS receiving device 32. it can. The detection performance of the joint changes depending on the detection performance of the acceleration sensor 23, but even considering the performance of the generally used acceleration sensor 23, the position of the own vehicle 10 is higher than that when the imaging device or the GNSS receiving device 32 is used. Can be estimated with high accuracy.

For example, the accuracy of the position estimation of the own vehicle 10 by the joint detection according to the present embodiment is about 1 to 2 m and 1 kHz when the own vehicle 10 is traveling at 100 km / h and the sampling period of the acceleration sensor 23 is 60 Hz. When it is about 10 cm, it is expected to be about 1 cm when it is about 10 kHz.

On the other hand, when the position of the own vehicle 10 is estimated using an image detected by an image pickup device such as a stereo camera, the own vehicle 10 is traveling at 100 km / h when the frame rate (FPS) is 100. In this case, the accuracy of the position estimation of the own vehicle 10 is about several meters. Further, since the acceleration sensor has a lower cost and the sampling cycle can be easily increased as compared with the imaging device, the position estimation of the own vehicle 10 can be performed more accurately according to the present embodiment. can do.

Further, the accuracy of the position estimation of the own vehicle 10 by the general GNSS positioning signal is about 10 m or more. Further, according to the present embodiment, the position of the own vehicle 10 can be estimated even in a situation where communication by the GNSS receiving device 32 is not possible, such as when the own vehicle 10 is traveling in a tunnel.

Further, since the image information obtained by the image pickup device is two-dimensional, the load of detection and processing is large. On the other hand, according to the present embodiment, the detected value acquired by the acceleration sensor 23 is one-dimensional data, and only detects the vibration accompanying the passage of the joint. Therefore, the load of detection and processing can be made smaller than that of the conventional technique using an imaging device.

Further, according to the present embodiment, as shown in FIGS. 7 and 8, the steering angle FF term is based on the lateral gradient information, the vertical gradient information, and the curvature information in the traveling route of the own vehicle 10 acquired as the route map information. Dff and acceleration FF term Aff are calculated and added to the rudder angle FB term Dfb and acceleration FB term Afb, respectively. Then, the own vehicle 10 can be accurately controlled based on the steering angle command value Dc and the acceleration command value Ac obtained as the sum. Therefore, the traveling controllability of the own vehicle 10 is improved. In particular, when passing through a curved road, the traveling controllability of the own vehicle 10 is remarkably improved.

(Second Embodiment)
In the second embodiment, a case where the slope or curvature of the road is detected to estimate the position of the own vehicle and the driving support is executed as the road surface shape will be described as an example. FIG. 11 is a diagram showing changes in the road surface shape on the traveling path of the own vehicle 10 with respect to the position on the reference line. 11 (a) shows the change in curvature, FIGS. 11 (b) and 11 (d) show the change in the horizontal gradient, and FIG. 11 (c) shows the change in the vertical gradient.

As shown in FIG. 11A, the change in curvature acquired as map information by the map information acquisition unit 51 from the external map information DB 13 of the external server 12 is stored in the ECU 40 by the storage unit 62 for each predetermined traveling section. Will be done. Similarly, as shown in FIGS. 11B and 11C, the change in the horizontal gradient and the change in the vertical gradient acquired as the map information are stored in the storage unit 62 for each predetermined traveling section of the ECU 40 in-vehicle map information DB 41. Stored in.

FIG. 11 (d) is a linear approximation of the map information regarding the lateral gradient shown in FIG. 11 (b) for each predetermined section of the road separated by the broken line extending in the vertical direction. For comparison, the change in the lateral gradient shown in FIG. 11 (b) is shown by a broken line in FIG. 11 (d). The amount of information on the lateral gradient can be reduced by being approximated by the straight line indicated by the solid line in each of the divided sections. The predetermined section can be arbitrarily set according to the data for linear approximation. The section width of the predetermined section is appropriately adjusted so that the data can be linearly approximated within the predetermined section.

The storage unit 62 may be configured to be stored in the in-vehicle map information DB 41 of the ECU 40 after approximating each information of the curvature, the horizontal gradient, and the vertical gradient as shown in FIG. 11D. .. As a result, the load on the storage capacity of the ECU 40 can be significantly reduced.

For example, when the own vehicle 10 is traveling along the reference line B as shown in FIG. 12 (a), the curvature, the horizontal gradient, and the vertical gradient are determined as shown in FIGS. 12 (b) to 12 (d). A linear approximation can be performed for each section divided at positions BP1 to BP5. As shown in FIG. 13, the storage unit 62 can store the curvature, the horizontal gradient, and the vertical gradient as constants in the vehicle-mounted map information DB 41 for each of the positions BP1 to BP5. The information enclosed in the five squares on the right side of FIG. 13 is associated with each other and stored in the vehicle-mounted map information DB 41. For example, regarding the "position BP1", the information "curvature; zero, horizontal gradient; Sy1, vertical gradient; Sx1" shown in the same quadrangle is associated and stored in the in-vehicle map information DB 41.

In the second embodiment, the own vehicle position estimation unit 60 shows changes in the road surface shape detected by the horizontal gradient detection unit 55, the vertical gradient detection unit 56, and the curvature detection unit 57 within a predetermined section in FIGS. The position of the road surface shape is specified by collating with the change in the road surface shape within a predetermined section included in the map information as shown in 13. False detection of the road surface shape due to a collation error by collating as a change in the road surface shape patterned along the traveling direction of the own vehicle 10 within a predetermined section instead of the detected value at a certain point on the traveling road of the own vehicle 10. Can be suppressed. A predetermined section for patterning can be arbitrarily set.

FIG. 14 shows a flowchart showing a position estimation process and a driving support process executed by the ECU 40 in the second embodiment. The process shown in FIG. 14 is repeatedly executed at a predetermined cycle when the own vehicle 10 is driven.

In step S201, the horizontal gradient information and the vertical gradient information in the traveling path of the own vehicle 10 are acquired as the map information. For example, changes in the magnitude of the horizontal gradient and the vertical gradient with respect to the position on the reference line of the traveling path of the own vehicle 10 are acquired as map information. As shown in FIG. 13, the acquired changes in the magnitudes of the horizontal gradient and the vertical gradient are linearly approximated for each predetermined section, linked with the section start position, and stored in the vehicle-mounted map information DB 41 of the ECU 40.

In step S202, the detection values including the acceleration, vehicle speed, yaw rate, etc. of the own vehicle 10 are acquired from the sensor group 20, and the process proceeds to step S203.

In step S203, the acquired detected value is smoothed by LPF, and the horizontal gradient detected value Syd and the vertical gradient detected value Sxd are calculated based on the above equations (2) to (4). Then, the process proceeds to step S204.

In step S204, the horizontal gradient Sym and the vertical gradient Sxm linearly approximated to the map information acquired in step S201 are acquired, and the process proceeds to step S205.

In step S205, the detected horizontal gradient Sid and vertical gradient Sxd are collated with the horizontal gradient Sym and vertical gradient Sxm in the map information, and the horizontal gradient Sym and vertical gradient Sxm having the highest degree of coincidence are selected. Then, the process proceeds to step S206.

In step S206, the positions associated with the selected horizontal gradient Sym and vertical gradient Sxm are acquired from the map information, and are specified as the detected horizontal gradient Syd and vertical gradient Sxd positions xsm. Then, the process proceeds to step S207.

In step S207, the relative position xr of the own vehicle 10 with respect to the position xsm of the specified horizontal gradient Sid and vertical gradient Sxd is detected. The relative position xr can be calculated as the mileage of the own vehicle 10 that has traveled from the time when the horizontal gradient Syd and the vertical gradient Sxd are detected to the present. For example, the product (V × Tl) of the average processing time Tl required for processing from the time when the sensor detection value is acquired in step S202 to step S207 and the vehicle speed V of the own vehicle 10 acquired in step S202 is relative. It may be calculated as the position xr. Then, the process proceeds to step S208.

In step S208, the position xc of the own vehicle 10 is estimated based on the positions xsm of the horizontal and vertical gradients specified in step S206 and the relative positions xr. For example, in the above equation (9), xc can be calculated by replacing xjm with xsm. Then, the process proceeds to step S230.

Since the processes shown in steps S230 to S233 are the same as the processes shown in steps S130 to S133 of FIG. 10, the description thereof will be omitted. After step S233, the process proceeds to step S234. In step S234, the lateral gradient Sys at the position xc of the own vehicle 10 is acquired as map information, and the error of the yaw rate sensor 24 or the like is corrected based on the lateral gradient Sys. After that, the process ends.

According to the present embodiment, the ECU 40 can detect the gradient of the traveling path of the own vehicle 10 by using the detection values of the vehicle speed sensor 21, the acceleration sensor 23, and the yaw rate sensor 24 mounted on the vehicle. Then, by collating the detected gradient of the own vehicle 10 with the gradient included in the map information, the position of the detected gradient can be specified. Further, the position of the own vehicle 10 can be estimated based on the position of the specified slope and the relative position of the own vehicle 10 with respect to the slope.

According to the ECU 40, the position of the own vehicle 10 is converted into map information by detecting the slope of the traveling path of the own vehicle 10 by using the vehicle speed sensor 21, the acceleration sensor 23, and the yaw rate sensor 24 mounted on the vehicle. It can be estimated based on. Therefore, the position of the own vehicle 10 can be estimated accurately even in a situation where it is difficult to visually detect the position of the own vehicle 10. According to the present embodiment, as in the first embodiment, the detection is not hindered even under the visually impaired environmental conditions, so that the position estimation of the own vehicle 10 is hindered by the environmental conditions. Less is.

In addition, the road surface shape such as slope and curvature does not change unless the road structure is significantly modified. Therefore, the position and size of the road sign are different from the frequency of change of the position and type of the road sign. It is changed very infrequently. Therefore, it is possible to reduce the frequency of updating the map information regarding the road surface shape such as the gradient and the curvature.

Further, in the present embodiment, in order to detect the slope of the traveling path of the own vehicle 10, the position of the own vehicle 10 is based on the position xjm of the joint in the map information because the joint does not exist as in the first embodiment. Can not be estimated. Therefore, there is little need for the own vehicle position estimation process to supplement the case where the characteristic element of the traveling path cannot be detected as shown in steps S122 to S124 of FIG.

(Third Embodiment)
In the present embodiment, the content of the position estimation process of the own vehicle 10 is switched based on the vehicle speed V of the own vehicle 10. FIG. 15 is a flowchart showing a position estimation process and a driving support process executed by the ECU 40 in the present embodiment. The process shown in FIG. 15 is repeatedly executed at a predetermined cycle when the own vehicle 10 is driven.

In step S301, similarly to step S101 and step S201, as map information, map information including joint information, horizontal gradient information, and vertical gradient information in the traveling path of the own vehicle 10 is acquired. As shown in FIG. 13, the acquired changes in the magnitudes of the horizontal gradient and the vertical gradient are linearly approximated for each predetermined section, linked with the section start position, and stored in the vehicle-mounted map information DB 41 of the ECU 40.

In step S302, the detection values including the acceleration, vehicle speed, yaw rate, etc. of the own vehicle 10 of the own vehicle 10 are acquired from the sensor group 20, and the process proceeds to step S303.

In step S303, it is determined whether or not the vehicle speed V of the own vehicle 10 is equal to or higher than a predetermined speed threshold value Vth. When the speed V of the own vehicle 10 is high, the vibration of the own vehicle 10 becomes large, so that the joint can be detected accurately. Therefore, the speed threshold value Vth can be set, for example, to the vehicle speed of the own vehicle 10 so that the detection sensitivity of the vibration of the own vehicle 10 becomes sufficiently large in the detection of the joint. When V ≧ Vth, the position estimation process by joint detection shown in steps S304 to S311 is executed. When V <Vth, the position estimation process by the gradient detection shown in steps S323 to S328 is executed.

In step S304, similarly to step S104, the vibration score is calculated from the longitudinal acceleration detected by the acceleration sensor 23, and the process proceeds to step S305.

In step S305, as in step S105, it is determined whether or not a joint is detected in the traveling path of the own vehicle 10 based on the vibration score. Specifically, the score threshold value Fth is set for the calculated vibration score Fs. Then, when Fs ≧ Fth, it is determined that the joint has been detected. Further, when Fs <Fth, it is determined that the joint is not detected.

In step S305, when the joint is detected, the processes of steps S306 to S311 and S330 to S333 are executed. Since the processes of steps S306 to S311 and S330 to S333 are the same as the processes shown in steps S106 to S111 and S130 to S133 of FIG. 10, the description thereof will be omitted.

If the joint is not detected in step S305, the position estimation process by the gradient detection shown in steps S323 to S328 is executed. That is, when it is determined in step S303 that V <Vth and in step S305 it is determined that the joint is not detected, each process of position estimation by gradient detection shown in steps S323 to S328 is executed. To do. Since the processes shown in steps S323 to S328 are the same as the processes shown in steps S223 to S228 of FIG. 14, the description thereof will be omitted.

When the speed V of the own vehicle 10 is high, the vibration of the own vehicle 10 becomes large, so that the joint can be detected accurately. According to the present embodiment, the speed threshold value Vth is set to the vehicle speed of the own vehicle 10 so that the detection sensitivity of the vibration of the own vehicle 10 becomes sufficiently large in the detection of the joint. Then, the ECU 40 is configured to select the own vehicle position estimation process using the joint detection when the speed V is equal to or higher than a predetermined speed threshold value Vth. Therefore, the position of the own vehicle 10 can be estimated by an appropriate estimation method according to the traveling state of the own vehicle 10.

Further, the ECU 40 uses the gradient detection of the traveling path when the speed V of the own vehicle 10 is low and it is difficult to detect the joint, or when the joint cannot be detected due to the absence of the joint or the like. Select the position estimation process. Therefore, even when it is difficult or impossible to detect the joint, the position of the own vehicle can be estimated accurately by detecting the gradient of the traveling path.

(Fourth Embodiment)
In the fourth embodiment, a case where the road structure is detected, the position of the own vehicle is estimated, and the driving support is executed based on the history of the transmission / reception sensitivity of the external communication device 30 will be described as an example.

As shown in FIG. 16, when the tunnel 103 or the like exists on the road 90 which is the traveling path, the communication radio wave of the external communication device 30 is blocked in the own vehicle 10a traveling in the tunnel 103. Therefore, the transmission / reception history acquisition unit 52 acquires the transmission / reception sensitivity history of the external communication device 30, and detects the transmission / reception loss period during which the communication radio wave is cut off and the transmission / reception is not performed, so that the shield such as the tunnel 103 is shielded. The presence can be detected.

The road structure detection unit 59 can detect the length Hd of the section (shielded section) in which the shield exists by performing time integration with respect to the vehicle speed V during the transmission / reception loss period. The length Hd of the shielded section can be represented by the distance from the start position Pss of the shield (tunnel 103) to the end position Pse in the traveling direction of the own vehicle 10.

The own vehicle position estimation unit 60 can specify the position of the detected shield by, for example, collating the detected length Hd of the shield section with the length Hm of the shield section in the map information. Further, the end position Pse of the shielded section by the specified shield can be acquired from the map information, and the relative position Lce of the own vehicle 10 with respect to the end position Pse can be calculated by the relative position detection unit 53. Then, in the above equation (6), by setting xb = Pse and xr = Lce, the position Pc of the own vehicle 10 can be estimated based on the map information.

FIG. 17 is a flowchart showing a position estimation process and a driving support process executed by the ECU 40 in the fourth embodiment. The process shown in FIG. 17 is repeatedly executed at a predetermined cycle when the own vehicle 10 is driven.

In step S401, the road structure information in the traveling path of the own vehicle 10 is acquired as the map information. Specifically, the map information including the type and position of the shield and the length Hm of the shield section in which the shield exists is acquired. Next, in step S402, the history of transmission / reception sensitivity is acquired from the external communication device 30, and the process proceeds to step S403.

In step S403, it is determined whether or not there is a transmission / reception loss period based on the history of transmission / reception sensitivity. For example, if there is a period in which the transmission / reception sensitivity is equal to or less than a predetermined sensitivity threshold value for a predetermined time or longer due to a change over time, that period is recognized as a transmission / reception loss period. Then, it is determined that there is a transmission / reception loss period.

If it is determined that the transmission / reception loss period exists, the process proceeds to step S404, and after determining that the shield exists, the process proceeds to step S405. If it is determined that the transmission / reception loss period does not exist, the process proceeds to step S421, and after determining that there is no shield, the processes shown in steps S422 to S424 are executed. Since the processes shown in steps S422 to S424 are the same as the processes shown in steps S122 to S124 of FIG. 10, the description thereof will be omitted. After the process of step S424, the process proceeds to step S430.

In step S405, the detected length Hd of the shielded section is calculated based on the detected transmission / reception loss period and the vehicle speed V acquired in step S402. Subsequently, in step S406, the length Hm of the shielded section is acquired from the map information acquired in step S401, and the process proceeds to step S407.

In step S407, the detected length Hd of the shielded section is collated with the length Hm of the shielded section in the map information, and the shielded section corresponding to the Hm having a high degree of coincidence is selected. After that, the process proceeds to step S408.

In step S408, the type of road structure is specified. Specifically, the type of the shield existing in the selected shield section is acquired from the map information, and the type of the detected road structure (for example, a tunnel) is specified. Subsequently, in step S409, the position of the road structure corresponding to the selected shielded section is acquired from the map information and specified as the detected position xhm of the road structure. Then, the process proceeds to step S410.

In step S410, the relative position xr of the own vehicle 10 with respect to the position xhm of the specified road structure is detected. The relative position xr can be calculated as the mileage of the own vehicle 10 that has traveled from the time when the shield is detected as the road structure to the present. For example, the product (V × Th) of the elapsed time Th from the end of the transmission / reception loss period to the present and the vehicle speed V of the own vehicle 10 acquired in step S402 may be calculated as the relative position xr. After that, the process proceeds to step S411.

In step S411, the position xc of the own vehicle 10 is estimated based on the position xhm of the specified road structure and the relative position xr. For example, in the above formula (9), xc can be calculated by replacing xjm with xhm. After that, the process proceeds to step S430. Since the processes shown in steps S430 to S433 are the same as the processes shown in steps S130 to S133 of FIG. 10, the description thereof will be omitted.

According to the present embodiment, the ECU 40 can detect a shield such as a tunnel 103 that shields the transmission and reception of communication radio waves as a road structure by using the transmission / reception history of the external communication device 30 mounted on the vehicle. it can. Then, by collating the detected length of the road structure with the length of the road structure included in the map information, the type and position of the detected road structure can be specified. Further, the position of the own vehicle 10 can be estimated based on the position of the specified road structure and the relative position of the own vehicle 10 with respect to the road structure. Therefore, the position of the own vehicle 10 can be estimated accurately even in a situation where it is difficult to visually detect the position of the own vehicle. According to the present embodiment, as in the first to third embodiments, the detection is not hindered even under visually hindered environmental conditions, so that the position estimation of the own vehicle 10 is hindered by the environmental conditions. It is rarely done.

In the fourth embodiment, a tunnel is illustrated as a shield, and a case where the position xc of the own vehicle 10 is estimated by specifying the position xhm of each shield is illustrated and described, but other than the tunnel. Shields can also be used. As the shield, various structures provided above or to the side of the traveling path to shield the transmitted / received wave can be used. Specifically, in addition to tunnels, elevated roads, pedestrian bridges, road sign boards and their supports (arch shape, shape protruding above the road, etc.), street lights, sound insulation walls, high-rise buildings located on the side of the road, etc. are shielded. Can be exemplified as. Further, the position xc of the own vehicle 10 may be estimated by patterning the history of the transmission / reception sensitivity and storing it as map information and comparing it with the history of the transmission / reception sensitivity in the own vehicle 10.

(Modification example)
With reference to FIG. 18, the relationship between a plurality of shields in the traveling path of the own vehicle 10 and a pattern of reception history from artificial satellites 140L and 140R having a plurality of GNSS functions will be described. FIG. 18A shows the positional relationship between the plurality of shields in the traveling path of the own vehicle 10 and the artificial satellites 140L and 140R having a plurality of GNSS functions. FIG. 18B shows the reception history from the artificial satellite 140L, and FIG. 18C shows the reception history from the artificial satellite 140R.

As shown in FIG. 18A, tunnel 131, road sign 132, elevated road 133, street light 134, 135, and skyscraper 136, 137 exist along the reference line B in the traveling route of the own vehicle 10. .. The road sign 132 is a road sign in which a sign plate is installed on an arch-shaped support that crosses above the road on which the own vehicle 10 travels. The elevated road is an elevated road that crosses above the road on which the own vehicle 10 travels. The street lights 134 and 135 are street lights having a shape protruding from the left side above the road on which the own vehicle 10 travels. The skyscrapers 136 and 137 are located on the left and right sides of the road on which the own vehicle 10 travels, respectively.

It should be noted that the metal structure tends to block the GNSS received wave relatively easily, and even if a thin metal structure as small as an iron pillar exists between the artificial satellite and the in-vehicle GNSS receiving device, the GNSS received wave Is easily blocked. That is, even a thin metal structure such as an iron columnar street lamp 134 or 135 can be a shield.

The artificial satellite 140L is located in the sky to the left of the vehicle 10 and the reference line B, and the artificial satellite 140R is located in the sky to the right of the vehicle 10 and the reference line B. There is. When the own vehicle 10 travels along the reference line B, the received wave from the artificial satellite 140L is a shield existing on the left side of the reference line B from the reference line B, that is, a tunnel 131, a road sign 132, and an elevated road 133. , Street lights 134, 135, and high-rise building 136, and the reception history shown in FIG. 18B can be obtained. The strength of the received signal SGN1 in the shielded section Hd31 by the tunnel 131, the shielded section Hd32 by the road sign, the shielded section Hd33 by the elevated road 133, the shielded sections Hd34 and 35 by the street lights 134 and 135, and the shielded section Hd36 by the skyscraper 136. It becomes zero.

Further, the received wave from the artificial satellite 140R is shielded by a shield existing on the right side of the reference line B from the reference line B, that is, a tunnel 131, a road sign 132, an elevated road 133, and a skyscraper 137. The reception history shown in c) can be obtained. The strength of the received signal SGN2 becomes zero in the shielded sections Hd31 to Hd33 and the shielded section Hd37 by the skyscraper 137.

By collating the series of reception history patterns shown in FIGS. 18B and 18C with the reception history pattern stored as map information, the map information is shown in FIGS. 18B and 18C. The position where the reception history pattern can be obtained can be specified, and the current position of the own vehicle 10 can be estimated by this. Since the types and arrangements of the structures existing around the road are unique to each location, the reception history pattern as shown in FIGS. 18 (b) and 18 (c) can be collated with the map information to obtain the map information. The position can be specified.

Further, as shown in FIG. 18A, there are structures (specific examples, street lamps 134, 135, skyscrapers 136, 137) whose presence or absence can be a shield depends on the position of the artificial satellite. In the case, as shown in FIGS. 18 (b) and 18 (c), different reception history patterns can be obtained between the artificial satellite 140L and the artificial satellite 140R. By collating the pattern of a plurality of reception histories obtained from a plurality of artificial satellites having different directions and elevation angles with respect to the own vehicle 10 with the pattern of the reception history stored as map information. Even when the reception history pattern is disturbed due to noise or the like, it is possible to suppress collation errors and, by extension, improve the collation accuracy.

Since the satellite arrangement information, which is the position information of each artificial satellite, is almost determined by the date and time, the actual position of each artificial satellite at that date and time can be predicted by acquiring the satellite arrangement information in advance. Further, the artificial satellite transmits a C / A (Coarse / Accuracy) code, a P (Precision) code, a navigation message, etc. by the L1 carrier wave, and transmits the P code by the L2 carrier wave. It is also possible to calculate the satellite arrangement information based on the broadcasting calendar calculated from the orbit information of the artificial satellite included in the navigation message. Since the navigation message is repeatedly transmitted every 30 seconds with 1 mainframe = 5 subframes as one unit, satellite arrangement information can be acquired once every 30 seconds by using the navigation message.

Further, since each artificial satellite uses a diffusion code unique to the C / A code, it is possible to identify the artificial satellite and acquire the reception history by the correlation between the GNSS received wave and the C / A code. it can. For example, since the C / A code transmits a pseudo-random number code in a cycle of 1 ms, the reception history can be performed with high accuracy of about 1 to 2 ms by monitoring the change in the correlation value of the C / A code. You can get the time in. Further, since the period of the carrier wave is about 1 μs, the time in the reception history can be acquired by using the carrier wave. Specifically, when the own vehicle 10 is traveling at 100 km / h and the time in the reception history is acquired with an accuracy of 1 ms, the position of the shield in the traveling direction (vertical direction, x direction) is specified. The accuracy of is estimated to be about 2.8 to 5.6 cm. That is, by comparing the reception sensitivity in the reception history of the GNSS received wave with the map information, the position of the own vehicle 10 in the traveling direction can be estimated with high accuracy.

(Fifth Embodiment)
In the fifth embodiment, a case where the road structure is detected, the position of the own vehicle is estimated based on the detection of the radar sensor 25 and the like, and the driving support is executed will be described as an example.

As shown in FIG. 19, when a metal structure 104 on the road such as a guardrail is present along the road 90 which is the traveling path of the own vehicle 10, the exploration wave of the radar sensor 25 is reflected by the metal structure 104. Then, the intensity of the received wave received by the radar sensor 25 increases. Therefore, the road structure detection unit 59 acquires the history of the received wave signal of the radar sensor 25 and detects that the received wave intensity IL is equal to or higher than the predetermined intensity threshold ILth. Thereby, the presence of the metal structure 104 can be detected. The road structure in which the intensity of the received wave received by the radar sensor 25 is increased is not limited, but is limited to a guardrail, a fence-shaped or columnar metal structure such as a median strip, a road sign, a metal signboard, or the like. It can be exemplified.

The road structure detection unit 59 can detect the length Ed of the metal structure 104 by performing time integration with respect to the vehicle speed V in a strong reception period in which the received wave intensity IL is equal to or higher than a predetermined intensity threshold ILth. The length Ed of the metal structure 104 can be represented by the distance from the existence start position Pss of the metal structure 104 to the existence end position Pse in the traveling direction of the own vehicle 10.

The own vehicle position estimation unit 60 identifies the position of the detected metal structure 104 by, for example, collating the detected length Ed of the metal structure 104 with the length Em of the road structure in the map information. be able to. Further, the existence start position Pss of the specified metal structure 104 can be acquired from the map information, and the relative position Lcs of the own vehicle 10 with respect to the existence start position Pss can be calculated by the relative position detection unit 53. Then, in the above equation (6), by setting xb = Pss and xr = Lcs, the position Pc of the own vehicle 10 can be estimated based on the map information.

Instead of the length of the metal structure 104, it is detected by using parameters such as the waveform and intensity of the received wave of the radar sensor 25, and the distance in the lateral or height direction with respect to the detected reference line of the metal structure 104. The metal structure 104 may be collated with the road structure stored as map information.

FIG. 20 is a flowchart showing a position estimation process and a driving support process executed by the ECU 40 in the fifth embodiment. The process shown in FIG. 20 is repeatedly executed at a predetermined cycle when the own vehicle 10 is driven.

In step S501, the road structure information in the traveling path of the own vehicle 10 is acquired as the map information. Specifically, the map information including the type and position of the road structure and the length Hm of the road structure is acquired.

Next, in step S502, the received wave intensity IL is acquired from the radar sensor 25, and the vehicle speed V of the own vehicle 10 is acquired from the vehicle speed sensor 21. After that, the process proceeds to step S503.

In step S503, it is determined whether or not the received wave intensity IL is equal to or less than a predetermined intensity threshold ILth. When IL ≧ ILth, the process proceeds to step S504, and after determining that the road structure exists, the process proceeds to step S505. If IL <ILth, the process proceeds to step S521, and after determining that the road structure does not exist, the process shown in steps S522 to S524 is executed. Since the processes shown in steps S522 to S524 are the same as the processes shown in steps S122 to S124 of FIG. 10, the description thereof will be omitted. After the process of step S524, the process proceeds to step S530.

In step S505, the detected length Ed of the road structure is calculated based on the strong reception period in which IL ≧ ILth and the vehicle speed V acquired in step S502. Subsequently, in step S506, the length Em of the road structure is acquired from the map information acquired in step S501, and the process proceeds to step S507.

In step S507, the detected length Ed of the road structure is collated with the length Em of the road structure in the map information, and the road structure corresponding to Em having a high degree of coincidence is selected. After that, the process proceeds to step S508.

In step S508, the type of road structure is specified. Specifically, the type of the road structure selected from the map information is acquired from the map information and specified as the detected type of the road structure (for example, a guardrail). Subsequently, in step S509, the position of the selected road structure is specified as the detected position xem of the road structure. After that, the process proceeds to step S510.

In step S510, the relative position xr of the own vehicle 10 with respect to the position xem of the specified road structure is detected. The relative position xr can be calculated as the mileage of the own vehicle 10 that has traveled from the time when the metal structure 104 is detected as the road structure to the present. For example, the product (V × Te) of the elapsed time Te from the end of the strong reception period to the present and the vehicle speed V of the own vehicle 10 acquired in step S502 may be calculated as the relative position xr. After that, the process proceeds to step S511.

In step S511, the position xc of the own vehicle 10 is estimated based on the position xem of the specified road structure and the relative position xr. For example, in the above equation (9), xc can be calculated by replacing xjm with xem. Then, the process proceeds to step S530. Since the processes shown in steps S530 to S533 are the same as the processes shown in steps S130 to S133 of FIG. 9, the description thereof will be omitted.

According to this embodiment, the ECU 40 can detect a road structure having a high reflected power such as a metal structure 104 by utilizing the received wave intensity of the radar sensor 25 mounted on the vehicle. Then, by collating the detected length of the road structure with the length of the road structure included in the map information, the type and position of the detected road structure can be specified. Further, the position of the own vehicle 10 can be estimated based on the position of the specified road structure and the relative position of the own vehicle 10 with respect to the road structure. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle 10, the position of the own vehicle 10 can be estimated accurately. According to the present embodiment, as in the first to fourth embodiments, the detection is not hindered even under visually hindered environmental conditions, so that the position estimation of the own vehicle 10 is hindered by the environmental conditions. It is rarely done.

According to each of the above embodiments, the following effects can be obtained.

The ECU 40 includes a map information acquisition unit 51, a horizontal gradient detection unit 55, a vertical gradient detection unit 56, a curvature detection unit 57, a shape detection unit exemplified as a joint detection unit 58, and a road structure detection unit 59. A relative position detection unit 53 and a vehicle position estimation unit 60 are provided, and the device functions as a position estimation device for estimating the position of the vehicle 10.

The map information acquisition unit 51 acquires map information of the road on which the own vehicle 10 travels. The shape detection unit is based on the running state of the own vehicle 10 detected by at least one of the inertial sensor exemplified by the acceleration sensor 23, the yaw rate sensor 24, and the vehicle speed sensor 21. Detects the road surface shape of the traveling road. The road structure detection unit 59 detects the road structure on the road on which the own vehicle 10 travels, based on the sensitivity of the external communication device 30 or by using the reflected wave of the exploration wave. The relative position detection unit 53 detects the relative position of the own vehicle 10 with respect to the road surface shape or the road structure. The own vehicle position estimation unit 60 collates the detected road surface shape or road structure with the road surface shape or road structure included in the map information, and identifies the position of the road surface shape or road structure in the map information. Further, the own vehicle position estimation unit 60 estimates the position of the own vehicle 10 based on the specified road surface shape or the position and relative position of the road structure.

Therefore, according to the ECU 40, the position of the own vehicle 10 is estimated based on the running state of the own vehicle 10 detected by at least one of the inertial sensor and the vehicle speed sensor 21 without using visual information. can do. Therefore, the position of the own vehicle 10 can be estimated accurately even in a situation where it is difficult to visually detect the position of the own vehicle 10.

When the speed V of the own vehicle 10 is equal to or higher than a predetermined speed threshold value Vth, the own vehicle position estimation unit 60 collates the undulations of the road detected by the joint detection unit 58 with the road surface shape included in the map information. It may be configured to estimate the position of the own vehicle 10. Further, the own vehicle position estimation unit 60 has a road gradient detected by the horizontal gradient detection unit 55, the vertical gradient detection unit 56, the curvature detection unit 57, etc. when the speed V of the own vehicle 10 is less than the speed threshold Vth. Alternatively, it may be configured to estimate the position of the own vehicle by comparing the curvature with the slope or curvature of the road included in the map information. Furthermore, even when the speed V of the own vehicle 10 is equal to or higher than the predetermined speed threshold value Vth, when the joint cannot be detected, the slope or curvature of the road is detected and collated with the map information, and the own vehicle is used. The position may be estimated.

The ECU 40 includes a storage unit 62 that stores map information regarding the slope or curvature of the road acquired by the map information acquisition unit by linearly approximating each predetermined section of the road. As a result, the load on the storage capacity in the in-vehicle map information DB of the ECU 40 can be reduced.

The own vehicle position estimation unit 60 may be configured to collate the change in the road surface shape detected by the shape detection unit within a predetermined section with the change in the road surface shape included in the map information. By comparing the detection data with the map information in the change of the road surface shape patterned in the predetermined section, it is possible to suppress the erroneous detection of the road surface shape due to the collation error.

The ECU 40 detects a detection error for at least one of the inertial sensor and the vehicle speed sensor 21 mounted on the own vehicle 10 based on the road surface shape around the own vehicle 10 acquired by the map information acquisition unit 51. An error correction unit 61 for correction is provided. Therefore, it is possible to reduce errors in joint detection, road gradient or curvature detection, etc., which are derived from the accuracy of the sensor group 20, and the position of the own vehicle 10 can be estimated more accurately.

Further, the ECU 40 includes a route map information acquisition unit 71 and a travel control unit 72, and has a function as a driving support device that executes driving support for the own vehicle 10 based on the estimated position of the own vehicle 10. .. Therefore, even in a situation where it is difficult to visually detect the position of the own vehicle, it is possible to execute appropriate driving support based on the accurately estimated position of the own vehicle.

The route map information acquisition unit 71 acquires route map information, which is map information of the road that is the travel route of the own vehicle 10, based on the estimated position of the own vehicle 10. For example, the curvature information, the horizontal gradient information, and the vertical gradient information of the road that is the traveling route of the own vehicle 10 are acquired as the route map information. Then, the travel control unit 72 controls the travel of the own vehicle 10 based on the route map information. For example, the traveling control unit 72 includes the lateral control unit 73, and uses the steering angle target value (steering angle command value Dc) of the own vehicle 10 calculated based on the curvature information and the lateral gradient information of the own vehicle. 10 steering controls are performed. Further, by including the vertical control unit 74, the drive control and braking control of the own vehicle 10 are performed using the acceleration / deceleration target value (acceleration command value Ac) calculated based on the vertical gradient information. Therefore, the traveling controllability of the own vehicle 10 is improved. In particular, when passing through a curved road, the traveling controllability of the own vehicle 10 is remarkably improved.

In each of the above embodiments, a vehicle not provided with an imaging device has been described as an example. However, the configuration of the ECU 40 or the like according to each of the above embodiments shall be applied to a vehicle provided with an imaging device. Can be done. In this case, the image pickup device may be used only for applications other than the own vehicle position estimation (for example, collision avoidance control, etc.), and the position of the own vehicle 10 is estimated in parallel with each of the above embodiments. It may be used for various purposes.

Further, in each of the above embodiments, as the detection unit for detecting the characteristic element of the traveling path of the own vehicle 10, the horizontal gradient detection unit 55, the vertical gradient detection unit 56, the curvature detection unit 57, the joint detection unit 58, and the road structure Although the ECU 40 including all of the object detection units 59 has been described as an example, the present invention is not limited to this, and a part of each of the above detection units may be provided.

Further, the ECU 40 is configured to be able to acquire map information from both the external map information DB 13 and the in-vehicle map information DB 14, but is configured to be able to use only the map information from either one of the map information DBs. You may be. Further, instead of the in-vehicle map information DB 14, a map information DB stored in a storage medium removable from the own vehicle 10 may be used. When the own vehicle 10 is provided with a navigation system, the map information stored in the above-mentioned map information DB may be used in the navigation system.

Further, the control target controlled by the ECU 40 may include devices other than the devices exemplified as the control target 80.

10 ... own vehicle, 21 ... vehicle speed sensor, 23 ... acceleration sensor, 24 ... yaw rate sensor, 51 ... map information acquisition unit, 53 ... relative position detection unit, 55 ... horizontal gradient detection unit, 56 ... vertical gradient detection unit, 57 ... Curvature detection unit, 58 ... Joint detection unit, 60 ... Vehicle position estimation unit

Claims (11)

The map information acquisition unit (51) that acquires the map information of the road on which the own vehicle (10) travels, and
Based on the traveling state of the own vehicle detected by at least one of the inertial sensor (23, 24) and the vehicle speed sensor (21) mounted on the own vehicle, the road on which the own vehicle travels. A shape detection unit (55-58) that detects the road surface shape, and
A relative position detection unit (53) that detects the relative position of the own vehicle with respect to the road surface shape, and
The road surface shape detected by the shape detection unit is collated with the road surface shape included in the map information to specify the position of the road surface shape in the map information, and the position of the specified road surface shape and the relative position are set. A position estimation device including a vehicle position estimation unit (60) that estimates the position of the vehicle based on the vehicle. The position estimation device according to claim 1, wherein the shape detection unit (58) detects undulations due to joints of the road as the road surface shape. The position estimation device according to claim 1 or 2, wherein the shape detection unit (55-57) detects the slope or curvature of the road as the road surface shape. The own vehicle position estimation unit
When the speed of the own vehicle is equal to or higher than a predetermined speed threshold value, the undulations of the road joint detected by the shape detection unit are compared with the road surface shape included in the map information to determine the position of the own vehicle. Estimate and
A claim for estimating the position of the own vehicle by collating the slope of the road detected by the shape detection unit with the road surface shape included in the map information when the speed of the own vehicle is less than the speed threshold value. Item 6. The position estimation device according to any one of Items 1 to 3. The invention according to any one of claims 1 to 4, further comprising a storage unit (62) that stores the map information regarding the slope or curvature of the road acquired by the map information acquisition unit by linearly approximating each predetermined section of the road. Position estimation device. The vehicle position estimation unit according to any one of claims 3 to 5, wherein the change in the road surface shape detected by the shape detection unit within a predetermined section is collated with the change in the road surface shape included in the map information. Position estimation device. An error correction unit that corrects a detection error for at least one of an inertial sensor and a vehicle speed sensor mounted on the own vehicle based on the road surface shape around the own vehicle acquired by the map information acquisition unit. The position estimation device according to any one of claims 1 to 6, comprising (61). The map information acquisition unit (51) that acquires the map information of the road on which the own vehicle (10) travels, and
Road structure detection that detects road structures on the road on which the vehicle travels, based on the sensitivity of the external communication device (30) mounted on the vehicle and transmitting and receiving signals to and from the outside of the vehicle. Department (59) and
A relative position detection unit (53) that detects the relative position of the own vehicle with respect to the road structure, and
The road structure detected by the road structure detection unit is collated with the road structure included in the map information to identify the position of the road structure in the map information, and the specified road structure is specified. A position estimation device including a own vehicle position estimation unit (60) that estimates the position of the own vehicle based on the position and the relative position. The map information acquisition unit (51), which acquires map information of the road on which the vehicle travels,
A road structure detection unit (59) mounted on the own vehicle and detecting a road structure on the road on which the own vehicle travels by using reflected waves of exploration waves.
A relative position detection unit (53) that detects the relative position of the own vehicle with respect to the road structure, and
The road structure detected by the road structure detection unit is collated with the road structure included in the map information to identify the position of the road structure in the map information, and the specified road structure is specified. A position estimation device including a own vehicle position estimation unit (60) that estimates the position of the own vehicle based on the position and the relative position. A driving support device (40) that executes driving support for the own vehicle based on the position of the own vehicle estimated by the position estimation device according to any one of claims 1 to 9.
Based on the estimated position of the own vehicle, the route map information acquisition unit (71) that acquires the route map information that is the map information of the road that is the travel route of the own vehicle, and
A travel control unit (72) that controls the travel of the own vehicle based on the route map information,
A driving support device equipped with. The route map information acquisition unit acquires the curvature information, the horizontal gradient information, and the vertical gradient information of the road serving as the traveling route of the own vehicle as the route map information.
The travel control unit
The lateral control unit (73) that controls the steering of the own vehicle by using the steering angle target value of the own vehicle calculated based on the curvature information and the lateral gradient information.
The driving support device according to claim 10, further comprising a vertical control unit (74) that performs drive control and braking control of the own vehicle using an acceleration / deceleration target value calculated based on the vertical gradient information.

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