JP4217900B2 - Vehicle travel control device - Google Patents

Description

  The present invention relates to a vehicle travel control device, and more particularly, to a vehicle travel control device that performs steering control in consideration of a crossing gradient of a travel road to maintain the host vehicle in a travel lane.

  As one of driving support systems for vehicles, a travel control device that assists the driver's steering so as to keep the host vehicle in a travel lane (a lane during travel) has been put into practical use. The travel control device sets a steering control torque necessary to hold the host vehicle in the travel lane based on an image of the in-vehicle camera and the like, and sets the steering actuator so that the steering control torque is applied to the steering shaft. It is something to control.

  In general, in this type of travel control, the travel lane is kept even when traveling on a curved road. Therefore, a correction amount for the steering control amount corresponding to the curve curvature is calculated, and this correction amount is taken into account. The steering control amount is obtained. On the other hand, for example, on a highway, the road is provided with a cross slope so that the curve is easy to bend. Therefore, the correction amount calculated according to the curve curvature is larger than the required amount, and as a result, the vehicle travel line is There is a disadvantage that it is offset inside the curve.

  Therefore, it is conceivable to correct the steering control amount in accordance with the crossing gradient of the road. For this purpose, it is necessary to estimate the crossing gradient of the road from, for example, the lateral acceleration and yaw rate applied to the vehicle when traveling on a curve. However, the output of the lateral acceleration sensor or the yaw rate sensor changes as the ambient temperature changes, and the drift amount of the sensor output accompanying the temperature change is, for example, about 0.1 G, for example, a transverse gradient of about 10 degrees. Larger than the sensor output level at the time of detection. Therefore, if the steering control is performed in consideration of the crossing gradient of the road estimated based on the sensor output, the vehicle may not be maintained near the center of the traveling lane during curve traveling. That is, the method for estimating the road crossing gradient based on the outputs of the lateral acceleration sensor and the yaw rate sensor is not practical.

In this regard, Patent Document 1 describes road shape data (including road longitudinal gradient and crossing gradient data) acquired from a map database based on the current position as the direction of travel of the vehicle and the direction of the road centerline. Correct according to the deviation, calculate the target vehicle speed to pass the curve based on the corrected shape data, and perform deceleration control etc. while taking into account the positional relationship between the current position and the curve and the traveling direction of the host vehicle An apparatus is described. In this way, by sequentially reading the crossing gradient of the traveling road from the in-vehicle database and using it for steering control, the steering control can be performed in consideration of the crossing gradient of the road.
JP-A-10-300480

  However, the crossing gradient of the road has various values for each part of the road (very short road section). Therefore, in order to accurately perform the steering control in consideration of the crossing slope of the road, a vast amount representing the crossing gradient at each part of the road is required. It is necessary to input various data into the database, and labor is required for data input (database change). In addition, there is a wide variety of data that is required to be input to the in-vehicle database, while the storage capacity of the storage medium of the in-vehicle database is limited. Therefore, it can be said that the method of storing the cross slope data for each place in the road in the in-vehicle database and using it for the steering control is not practical.

  SUMMARY OF THE INVENTION An object of the present invention is to provide a vehicle travel control device that can perform steering control that takes into account the crossing gradient of a road based on a small amount of data.

  In order to achieve the above object, a vehicle travel control apparatus according to claim 1 is provided with road curvature estimation means for estimating a road curvature of a travel lane, and cross slope gradient speed data correlated with a road cross slope. Based on the storage means stored for each road, the vehicle position detection means for detecting the current vehicle position, the estimated road curvature and the cross slope correlation speed at the detected current vehicle position, A cross slope estimation means for estimating and a control amount calculation means for calculating a steering control amount in consideration of the estimated cross slope are provided.

  According to the first aspect of the present invention, the crossing gradient of the traveling road is estimated based on the road curvature and the crossing gradient correlation speed. In general, on a road, for example, an expressway, a crossing gradient is set according to the road design speed and the road curvature in order to make the curve easier to turn. In other words, the road design speed has a correlation with the road crossing gradient, and the road crossing gradient is set according to the crossing slope correlation speed (design speed) and the road curvature. The present invention pays attention to this point and estimates the crossing gradient of the traveling road based on the crossing gradient correlation speed and the road curvature. Therefore, in the present invention, a storage unit that stores data on the cross-gradient correlation speed is used. The invention of Patent Document 1 requires a large amount of data representing the cross slope at various places (very short road sections) of the road, but the cross slope correlation speed (for example, road design speed) data used in the present invention is data for each road (long). The data amount is extremely small compared to the cross slope data used in Patent Document 1, and it takes less time to input data, and the required storage capacity can be reduced. In addition, when a lateral acceleration sensor or yaw rate sensor is used to estimate the crossing slope of a road, it is affected by the drift of the sensor output accompanying changes in ambient temperature, but such a sensor is not necessary for estimating the crossing slope according to the present invention. And is not affected by drift.

  According to a second aspect of the present invention, there is provided a vehicle travel control apparatus comprising: a road curvature estimation unit that estimates a road curvature of a traveling lane; a storage unit that stores road crossing gradient data for each road curvature; and the estimated road A cross-gradient estimating unit that estimates a cross-gradient of a road corresponding to a curvature as a cross-gradient of a traveling road, and a control amount calculating unit that calculates a steering control amount in consideration of the estimated cross gradient. And

  According to the invention described in claim 2, the crossing gradient of the traveling road is estimated based on the road curvature. As described above, the road crossing gradient is generally set according to the road design speed and road curvature. For example, the design speed of expressways is roughly divided into two types, 80 km / h and 100 km / h. The road with a design speed of 80 km / h has the maximum crossing in the range where the road curvature is about 0.002 (curvature radius is about 500R) or more. On the other hand, on roads with a design speed of 100 km / h, the road crossing gradient is set so that the maximum crossing slope is set in the range where the road curvature is about 0.001 (curvature radius is about 1000R) or higher. Also, the road crossing gradient increases as the road curvature increases. The present invention pays attention to the fact that the estimated cross slope is considerably adapted to the road of any design speed even if the cross slope of the road is estimated based only on the road curvature. In order to estimate the crossing gradient of the traveling road based on the road curvature, the present invention uses storage means for storing the road crossing gradient data for each road curvature, but the crossing gradient data for each road curvature has an extremely large amount of data. Since it is small, data input is easy and the required storage capacity can be reduced. Further, since the lateral acceleration sensor and the yaw rate sensor are not necessary for estimating the crossing gradient, the sensor output is not affected by the drift of the sensor output due to the ambient temperature change.

According to the first aspect of the present invention, the crossing gradient of the traveling road is estimated based on the road curvature of the traveling lane estimated by the road curvature estimating means and the data of the crossing gradient correlation speed stored for each road in the storage means. The data to be stored in the means can be very small.
Since the invention according to claim 2 estimates the crossing gradient of the traveling road based on the road curvature of the traveling lane estimated by the road curvature estimating means and the data of the crossing gradient stored for each road curvature in the storage means, the storage means The amount of data to be stored in the memory can be extremely small.

  According to the first and second aspects of the present invention, since the amount of data to be stored in the storage means is extremely small, it is possible to reduce the labor and required storage capacity for data input (database change), and a sensor accompanying changes in ambient temperature The cross slope can be accurately estimated without being affected by the output drift. Since the steering control amount is calculated in consideration of the estimated crossing gradient, accurate steering control can be performed in consideration of the estimated crossing gradient.

Hereinafter, with reference to FIG. 1, the vehicle travel control apparatus which concerns on one Embodiment of this invention is demonstrated.
A vehicle equipped with a vehicle travel control device (indicated by a block denoted by reference numeral 1) is applied to a steering shaft 2 for applying a steering torque to a steering shaft connected to a steering wheel (steering wheel) and a steering shaft. And a power steering mechanism 3 that assists the steering force in accordance with the steering torque. The steering actuator 2 applies a steering torque to the steering shaft by a DC electric motor, for example, and can steer the steered wheels without applying a steering force to the steering wheel by the driver. The power steering mechanism 3 is configured as, for example, an electronically controlled hydraulic power steering mechanism that controls the magnitude of hydraulic pressure that assists steering by electronically controlling a control valve. An electromagnetic clutch (not shown) is provided between the steering shaft and the steering actuator 2 so that the steering shaft and the steering actuator 2 can be connected to and separated from each other.

  The vehicle travel control device includes an electronic control unit 10 as a main component, and a navigation device 20, a camera 31, a handle angle sensor 32, a yaw rate sensor 33, and a vehicle speed sensor 34 are connected to the electronic control unit 10. In addition, a vehicle speed sensor 34 and a geomagnetic sensor 35 are connected to the navigation device 20. Here, the camera 31 is a video camera such as a CCD camera, for example, and is provided in the front part of the vehicle to photograph a road ahead of the vehicle.

  The electronic control unit 10 processes the image information from the camera 31 and recognizes the white line recognition means 11 for recognizing the white line of the road, and the lateral deviation amount yf in the traveling lane of the own vehicle in front of the own vehicle (see FIG. 2). The lateral deviation amount estimating means 12 for estimating, the yaw angle deviation estimating means 13 for estimating the yaw angle deviation θf with respect to the traveling lane direction of the own vehicle in front of the own vehicle, and the road curvature for estimating the road curvature ρf of the traveling lane in front of the own vehicle. The crossing gradient of the road based on the crossing gradient correlation speed (in this embodiment, the road design speed Vd) from the estimating means 14 and the navigation device 20 and the road curvature ρf from the road curvature estimating means 14 or based on the road curvature ρf. It is configured to exhibit the respective functions of the cross gradient estimating means 15 for estimating Rg and the steering control means 16 for controlling the steering actuator 2. There.

  For example, the white line recognition unit 11 scans a planar image obtained by geometrically transforming a camera image in a horizontal direction, and detects a portion where a large luminance change appears twice at an interval corresponding to the width of the white line. This is recognized as a white line, thereby recognizing the left and right white lines that define the traveling lane ahead of the host vehicle. Then, such white line recognition is performed farther in front of the host vehicle, and a straight line or a curve connecting the midpoints of many sets of left and right white lines is obtained as the center line of the driving lane.

  The lateral deviation amount estimation means 12 estimates the lateral deviation amount yf in the lateral direction of the center of the host vehicle from the center line of the host vehicle when the host vehicle goes straight a predetermined distance with the current direction from the relationship between the driving lane and the host vehicle. . The yaw angle deviation estimation means 13 determines the angle (yaw angle deviation) θf formed between the direction of the traveling lane and the direction of the own vehicle when the own vehicle has advanced a predetermined distance with the current direction being the relationship between the traveling lane and the own vehicle. Estimated from Further, the road curvature estimation means 14 estimates the road curvature ρf of the traveling lane ahead of the predetermined distance from the shape of the traveling lane.

  A navigation device 20 is connected to the cross slope estimation means 15. As shown in FIG. 3, the navigation device 20 outputs a map database storage unit that stores a map database, such as a CD-ROM 21, a vehicle position detection unit 22 that detects the current vehicle position, and route guidance data that represents a recommended route. And a display control / route guidance unit 23. The map database stored in the CD-ROM 21 includes road data for each of a very large number of mesh sections constituting, for example, a nationwide map as a whole, and road design for each road (for each road section if necessary). Includes data for velocity Vd. That is, the CD-ROM 21 constitutes storage means for storing the data of the cross gradient correlation speed (design speed Vd) for each road. The vehicle position detection unit 22 receives a signal from a satellite navigation system (GPS) and outputs data representing the absolute position of the vehicle, and a direction detected by the geomagnetic sensor 35 and a vehicle speed sensor 34. The dead reckoning navigation part 22b which outputs the data showing the relative position of a vehicle and a vehicle traveling locus based on the relative position. In the map matching unit 22c, the currently traveling road is specified based on the road shape on the map data input from the CD-ROM 21 via the CD-ROM controller 24 and the traveling locus from the dead reckoning navigation unit 22b. In the navigation unit 22d, the current vehicle position data is accurately obtained based on the absolute position data from the controller 24 and the output data from the map matching unit 22c. The display control / route guidance unit 23 uses the destination data set by the driver, the road data from the CD-ROM 21, and the like to obtain a road map around the traveling road and a recommended route from the current vehicle position to the destination. It is displayed on the display device 25.

  The cross slope estimation means 15 has a plurality of individual maps for each road design speed Vd and a map common to the plurality of design speeds Vd, and when the navigation device 20 is in operation (when a GPS signal is received), While obtaining the crossing gradient Rg corresponding to the road curvature ρf input from the road curvature estimation means 14 using the individual map selected according to the design speed Vd of the currently traveling road input from the navigation device 20, the GPS signal is not received. Sometimes, a common map is used to obtain the crossing gradient Rg corresponding to the road curvature ρf.

  In this embodiment, the cross gradient estimation means 15 is shown in FIG. 4B corresponding to two separate maps, namely, a first map shown in FIG. 4A corresponding to a design speed Vd of 100 km / h, and FIG. 4B corresponding to a design speed Vd of 80 km / h. And a second map. In the first map, as shown by a two-dot chain line in FIG. 4A, the crossing gradient Rg increases as the road curvature ρf increases in the range where the road curvature ρf is about 0.002 (the road curve radius is about 500 R). In the range where the road curvature ρf is about 0.002 or more, for example, the maximum value is set to 10%. On the other hand, as shown by a one-dot chain line in FIG. 4B, the crossing gradient Rg of the second map increases as the road curvature ρf increases in the range where the road curvature ρf is about 0.001 (the road curve radius is about 1000 R). In the range where the road curvature ρf is about 0.001 or more, for example, the maximum value is set to 10%.

  As described above, the reason why the two maps are provided according to the road design speed Vd is that, generally, on a road, for example, an expressway, in order to make the curve easy to bend, the crossing according to the road design speed Vd and the road curvature ρf This is because the gradient Rg is set and the design speed Vd of the highway having a correlation with the cross gradient Rg is roughly divided into two types, 100 km / h and 80 km / h. And since the data of design speed Vd for every road should just be stored in the storage area of CD-ROM21 as a memory | storage means which memorize | stores the design speed data used for estimation of crossing gradient Rg, it should be allocated as the said storage area The storage area requires only a small capacity, and data input (database change) does not take time and the required storage capacity can be reduced.

  The cross slope estimation means 15 includes the third map shown in FIG. 5 as a common map. In the third map, the cross slope Rg has a road curvature ρf of about 0.0005, for example, as shown by a solid line in FIG. In the following first range, as the road curvature ρf increases, the value increases from 0 to about 5% along the design speed 100 km / h line as in the case of the first map of FIG. 4A. In the second range of 0005 to about 0.005, the road curvature increases from about 5% to a maximum value of about 10% so that the design speed approaches 80 km / h line as the road curvature ρf increases, and the road curvature is about 0.005. In the third range described above, the maximum value is set to about 10%. That is, the cross slope estimation means 15 constitutes a storage means for storing road cross slope Rg data for each road curvature.

  If the crossing gradient Rg of the road is estimated based on only the road curvature ρf using the third map set as described above, the estimated crossing gradient is considerably adapted to any road. In other words, the design speed Vd of highways in Japan is roughly divided into two, 80 km / h and 100 km / h, and the design speed Vd is 100 km / h on a highway with a curve with a radius of about 1000R. On the other hand, in many cases, the design speed Vd is 80 km / h on a highway where a curve with a radius of about 500 R continues, so that the design speed approaches 100 km / h line when the curve radius is close to 1000 R. When the steering radius is controlled by estimating the crossing gradient Rg using the third map close to the design speed of 80 km / h line within the range of the curve radius less than that, the host vehicle does not deviate greatly from the center of the traveling lane. Further, since the data amount of the cross slope data (third map) for each road curvature is extremely small, data input is easy and the required storage capacity can be reduced.

  The steering control means 16 includes a lateral deviation amount yf estimated by the lateral deviation amount estimation means, a yaw angle deviation θf estimated by the yaw angle deviation estimation means 13, a road curvature ρf estimated by the road curvature estimation means 14, and a crossing The transverse gradient Rg estimated by the gradient estimating means 15, the vehicle speed V detected by the vehicle speed sensor 34, the handle angle α of the host vehicle detected by the handle angle sensor 32, and the own vehicle detected by the yaw rate sensor 33. The target steering torque T is calculated from the yaw rate γ according to the following equation, for example. That is, the steering control means 16 constitutes a control amount calculation means for calculating a steering control amount (target steering torque T) in consideration of the cross gradient Rg.

T = k1, α + k2, γ + k3, yf + k4, θf + k5, V, ρf + k6, Rg
In the above target torque calculation formula, symbols k1 to k6 represent control gains.
The steering control means 16 controls the electric motor of the steering actuator 3 so as to generate the target steering torque T.
Hereinafter, steering control by the vehicle travel control device having the above-described configuration will be described.

  When the operation power is turned on, the electronic control unit 10 starts executing the steering control routine shown in FIG. First, it is determined whether or not a predetermined sample period has elapsed (step S1). If the determination result is negative (No), the sample period is awaited. When the sample period elapses, the electronic control unit 10 inputs an image from the camera 31 (step S2), and performs the above-described lane recognition process by the white line recognition means 11 (step S3). In this lane recognition process, the camera image is geometrically converted to a planar view image, the left and right white lines defining the driving lane are recognized by scanning the image in the horizontal direction, and the driving lane center line is obtained. It is done.

  Next, in the electronic control unit 10, the lateral deviation amount estimating means 12 estimates the lateral deviation amount yf at the center of the own vehicle relative to the traveling lane center line in front of the own vehicle, and the yaw angle deviation estimating means 13 estimates the direction of the traveling lane in front of the own vehicle. And the yaw angle deviation θf, which is an angle formed by the direction of the host vehicle, and the road curvature ρf of the traveling lane ahead of the host vehicle is estimated by the road curvature estimation unit (step S4).

  Next, it is determined whether or not the navigation device 20 has received a GPS signal by the cross gradient estimation means 15 of the electronic control unit 10 (step S5). If a GPS signal is being received, the navigation device 20 detects the current vehicle position, performs conventionally known route guidance, and outputs data representing the design speed Vd of the currently traveling road. Therefore, when receiving the GPS signal, the cross slope estimation means 15 receives the design speed Vd from the navigation device 20 (step S6), and estimates the cross slope Rg according to the design speed Vd (step S7). That is, the cross slope estimation means 15 determines whether the design speed Vd input from the navigation device 20 is close to 100 km / h or 80 km / h. If the design speed Vd is close to 100 km / h, the crossing slope estimation means 15 performs the first operation shown in FIG. With reference to one map, the crossing gradient Rg corresponding to the road curvature ρf input from the road curvature estimation means 14 is obtained. If the design speed Vd input from the navigation device 20 is close to 80 km / h, the crossing gradient Rg corresponding to the road curvature ρf is obtained with reference to the second map of FIG. 4B.

On the other hand, if it is determined in step S5 that the GPS signal is not received, the crossing slope estimating means 15 refers to the third map shown in FIG. 5 and crosses the road curvature ρf input from the road curvature estimating means 14. A gradient Rg is obtained (step S9).
As described above, when the estimation of the cross gradient in step S7 or S9 is completed, the process proceeds to step S8, and the steering control unit 16 calculates the steering control amount. In the calculation of the steering control amount, the lateral deviation amount yf estimated by the deviation amount estimation means, the yaw angle deviation θf estimated by the yaw angle deviation estimation means 13, the road curvature ρf estimated by the road curvature estimation means 14, and The crossing gradient Rg estimated by the crossing gradient estimating means 15, the vehicle speed V detected by the vehicle speed sensor 34, the steering wheel angle α of the host vehicle detected by the steering wheel angle sensor 32, and the own vehicle speed detected by the yaw rate sensor 33. Based on the yaw rate γ of the vehicle, the steering control amount (target steering torque T) is calculated according to the above-described calculation formula T = k1 · α + k2 · γ + k3 · yf + k4 · θf + k5 · V · ρf + k6 · Rg. Then, when the calculation of the steering control amount ends, the process proceeds to step S1.

  As described above, the steering control amount (target steering torque T) is calculated for each sample period, and the steering control means 16 controls the electric motor of the steering actuator 3 to generate the target steering torque T. As a result, steering control in consideration of the crossing gradient Rg of the road is accurately performed, and it is possible to travel near the center of the travel lane even on a curved road. That is, when the GPS signal is received, the crossing gradient Rg corresponding to the road curvature ρf is estimated based on the first or second map that matches the design speed close to the road design speed Vd read from the map database. Good and accurate steering control is performed. In addition, when the GPS signal is not received, the crossing gradient Rg corresponding to the road curvature ρf is estimated based on the third map adapted to any of the roads of two types of design speeds. Steering control is performed.

Although the description of the vehicle travel control device according to the preferred embodiment of the present invention is finished as above, the present invention is not limited to the above embodiment and can be variously modified.
For example, in the above-described embodiment, the first or second map selected according to the road design speed (crossing gradient correlation speed) read from the map database when the GPS signal is received is referred to and based on the estimated road curvature. While the cross slope of the road is estimated, when the GPS signal is not received, the third map is referred to and the cross slope of the road is estimated based on the estimated road curvature. Regardless of whether the GPS signal is received or not The crossing gradient of the road may be estimated based on the estimated road curvature with reference to the third map. In this case, it is not necessary to add a navigation device to the vehicle travel control device, and the processing of steps S5 to S7 is not required in the steering control routine of FIG. On the other hand, on the assumption that GPS signals are always received, the road crossing gradient may be estimated based on the estimated road curvature with reference to the first or second map selected according to the road design speed. In this case, the third map is unnecessary, and the processes in steps S5 and S9 are not required.

  In the above embodiment, the number of maps selected according to the road design speed is two in view of the fact that the design speed of the highway is generally roughly divided into 80 km / h and 100 km / h. Three or more maps may be used. In the embodiment, the common map (third map) is set so as to be adapted to two types of design speeds, but may be set so as to be adapted to three or more types of design speeds as much as possible.

  In the above embodiment and the above modification, the storage means for storing road design speed data for each road and the vehicle position detection means for detecting the current vehicle position are configured by a navigation device having a route guidance function. It is not essential to configure the means and the vehicle position detecting means with a navigation device.

It is a schematic block diagram which shows the vehicle travel control apparatus by one Embodiment of this invention. It is a figure which shows lateral deviation | shift amount yf used for steering control implemented by the vehicle travel control apparatus of FIG. 1, yaw angle deviation | theta θf, road curvature (rho) f, vehicle speed V, and yaw rate (gamma) with the white line on either side which prescribes | regulates a driving lane. It is a block diagram which illustrates the composition of the navigation device shown in FIG. The 1st map used when the design speed Vd is 100 km / h in the steering control at the time of GPS signal reception is shown. The 2nd map used when the design speed Vd is 80 km / h in the steering control at the time of GPS signal reception is shown. It is a figure which shows the 3rd map used for steering control at the time of GPS signal non-reception. It is a flowchart of the steering control routine implemented by the electronic control unit shown in FIG.

Explanation of symbols

2 Steering actuator 10 Electronic control unit 12 Lateral deviation amount estimation means 13 Yaw angle deviation estimation means 14 Road curvature estimation means 15 Cross gradient estimation means (storage means)
16 Steering control means (control amount calculation means)
20 navigation device 21 CD-ROM (storage means)
31 Camera 32 Handle angle sensor 33 Yaw rate sensor 34 Vehicle speed sensor

Claims (2)

Road curvature estimation means for estimating the road curvature of the driving lane;
Storage means for storing cross slope gradient speed data correlated with the road cross slope for each road;
Vehicle position detecting means for detecting the current vehicle position;
Cross slope estimation means for estimating a cross slope of a traveling road based on the estimated road curvature and a cross slope correlation speed at the detected current vehicle position;
And a control amount calculating means for calculating a steering control amount in consideration of the estimated crossing gradient. Road curvature estimation means for estimating the road curvature of the driving lane;
Storage means for storing road cross slope data for each road curvature;
Cross slope estimating means for estimating a cross slope of a road corresponding to the estimated road curvature as a cross slope of a traveling road;
And a control amount calculating means for calculating a steering control amount in consideration of the estimated crossing gradient.

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