JP7252513B2 - Vehicle driving support system - Google Patents

Description

The present invention relates to a vehicle driving support system mounted on a vehicle.

Potential method, spline interpolation function, A star (A*), RRT, state lattice method, etc. are known as algorithms used for setting vehicle route candidates (that is, candidates that can be the target route for actually driving the vehicle). ing. A vehicle driving support system using such an algorithm has also been proposed.

According to the algorithm described above, it is possible to set a plurality of route candidates for the travel route of the vehicle. The route cost of each route candidate is calculated from the viewpoint of obstacle avoidance and the like, and one route candidate judged appropriate based on the calculation result is selected as the target route. For example, Patent Literature 1 discloses a vehicle driving support system that sets a plurality of route candidates on a grid map and selects one route candidate based on travel costs.

WO2013/051081

The system described in Patent Literature 1 calculates movement costs in all cells through which route candidates pass among a plurality of cells in a grid map. Such a method of calculating route costs at a large number of positions on a route candidate is significant from the viewpoint of improving the evaluation accuracy of the route cost of the route candidate, but entails a large computational load.

In particular, when using a method such as the state lattice method that can set a large number of route candidates, the route cost calculation load may become enormous. For this reason, it has been desired to achieve both a reduction in the computational load and an evaluation accuracy of the route cost.

SUMMARY OF THE INVENTION The present invention has been made to solve such problems, and it is an object of the present invention to provide a vehicle driving support system capable of achieving both the accuracy of route cost evaluation of route candidates and the reduction of the calculation load. do.

In order to solve the above problems, the present invention provides a vehicle driving support system mounted on a vehicle, comprising a traveling road information acquisition device for acquiring traveling road information about a traveling road, and obstacle information about obstacles on the traveling road. and a control device that sets a target route on the travel route based on the travel route information and controls the vehicle to travel along the target route, wherein the control device comprises: Based on the traveling road information, a plurality of curved route candidates are set on the traveling road, and a plurality of sampling points are set at predetermined intervals along the curved shape of each of the plurality of route candidates. and select one route candidate from a plurality of route candidates as a target route based on the route cost. set a warning area having an outer shape according to the moving speed and moving direction of the route candidate, set sampling points at a first interval along the part included in the warning area among the route candidates, and set sampling points at the first interval along the other part It is characterized in that the sampling points are set at a second interval that is larger than the interval.

According to this configuration, the control device sets a caution area having an outer shape according to the moving speed and moving direction of the obstacle in the vicinity of the obstacle. In addition, the control device sets sampling points at first intervals along a portion of the route candidate that is included in the caution area. Since the first interval is smaller than the second interval, a plurality of sampling points are set at a relatively high density near the obstacle. As a result, it is possible to improve the accuracy of route cost evaluation in the range in which movement of obstacles is considered.

On the other hand, for the other portion of the route candidate (that is, the portion not included in the caution area), the control device sets sampling points at second intervals along the other portion. Since the second interval is larger than the first interval, a plurality of sampling points are set at relatively low density in the other portion. As a result, it becomes possible to reduce the calculation load of the route cost in the other portion. Since the density of sampling points is relatively low, the evaluation accuracy of the route cost in the other portion is also low, but the influence of the evaluation accuracy on the traveling of the vehicle in the caution area is relatively small.

That is, according to the above configuration, it is possible to reduce the computational load and make the route cost evaluation accuracy practically sufficient. As a result, it is possible to achieve both the accuracy of route cost evaluation of route candidates and the reduction of the calculation load.

Further , the control device is configured to increase the size of the caution area in the moving direction of the obstacle as the moving speed of the obstacle increases.
According to this configuration, it is possible to evaluate the route cost in consideration of obstacles after movement. As a result, it is possible to achieve both the accuracy of route cost evaluation of route candidates and the reduction of the calculation load.

It should be noted that the dimension of the caution area in the moving direction of the obstacle does not need to increase continuously as the moving speed of the obstacle increases. For example, the scope of the present invention also includes a configuration in which the dimension increases stepwise as the moving speed of the obstacle increases.

In the present invention, preferably, the control device is configured to increase the dimension of the caution area in the direction orthogonal to the moving direction of the obstacle as the distance from the obstacle in the moving direction increases.
According to this configuration, it is possible to evaluate the route cost in consideration of the uncertain destination of the obstacle. As a result, it is possible to achieve both the accuracy of route cost evaluation of route candidates and the reduction of the calculation load.

It should be noted that the dimension of the caution area in the direction orthogonal to the moving direction of the obstacle does not need to increase continuously as the distance from the obstacle increases. For example, a configuration in which the dimension increases stepwise with increasing distance from the obstacle is also included within the scope of the present invention.

In the present invention, preferably, the control device is configured to increase the outline of the caution area when the obstacle is a vehicle compared to when the obstacle is a pedestrian.
According to this configuration, when the obstacle is a vehicle, it is possible to improve the accuracy of route cost evaluation in a wider range than when the obstacle is a pedestrian. That is, it is possible to further improve the accuracy of route cost evaluation for a vehicle, which is an obstacle with a relatively high moving speed. As a result, while the calculation load is reduced, it is possible to make the route cost evaluation accuracy practically sufficient.

Advantageous Effects of Invention According to the present invention, it is possible to provide a vehicle driving support system capable of achieving both the accuracy of route cost evaluation of route candidates and the reduction of the calculation load.

1 is a configuration diagram of a vehicle driving support system according to an embodiment; FIG. FIG. 4 is an explanatory diagram of route candidates and sampling points; FIG. 4 is an explanatory diagram of route candidates and sampling points; FIG. 2 is a flow chart showing calculations executed by an ECU in FIG. 1; FIG.

Embodiments will be described below with reference to the accompanying drawings. In order to facilitate understanding of the description, the same components are denoted by the same reference numerals in each drawing, and overlapping descriptions are omitted.

First, an overview of a vehicle driving support system 100 according to the present invention will be described with reference to FIGS. 1 and 2. FIG. FIG. 1 is a configuration diagram of a vehicle driving support system 100. As shown in FIG. FIG. 2 is an explanatory diagram of route candidates RC and sampling points SP.

A vehicle driving support system 100 is mounted on a vehicle 1 and provides driving support control for causing the vehicle 1 to travel along a target route. As shown in FIG. 1, a vehicle driving support system 100 includes an ECU (electronic control unit) 10, a plurality of sensors, and a plurality of control systems. The plurality of sensors include a camera 21, a radar 22, a vehicle speed sensor 23 for detecting the behavior of the vehicle 1 and the driving operation by the occupant, an acceleration sensor 24, a yaw rate sensor 25, a steering angle sensor 26, an accelerator sensor 27, a brake A sensor 28 is included. Furthermore, the multiple sensors include a positioning system 29 for detecting the position of the vehicle 1 and a navigation system 30 . The multiple control systems include an engine control system 31 , a brake control system 32 and a steering control system 33 .

In addition, as other sensors, a peripheral sonar for measuring the distance and position of peripheral structures with respect to the vehicle 1, a corner radar for measuring the approach of peripheral structures at four corners of the vehicle 1, and a vehicle interior of the vehicle 1 may include an inner camera that captures the

The ECU 10 is an example of a control device according to the invention. The ECU 10 is configured by a computer having a CPU, a memory for storing various programs, an input/output device, and the like. The ECU 10 performs various calculations based on signals received from a plurality of sensors, and appropriately controls the engine system, brake system, and steering system for the engine control system 31, brake control system 32, and steering control system 33, respectively. send a control signal to activate the

The ECU 10 performs calculations for specifying a position on the travel road based on the travel road information. The road information is information about the road on which the vehicle 1 is traveling, and includes information about the shape of the road (straight line, curve, curve curvature), width of the road, number of lanes, width of the lane, and the like. . Traveling route information is acquired by the camera 21, the radar 22, the navigation system 30, and the like.

FIG. 2 shows the vehicle 1 running on the road 5. As shown in FIG. The ECU 10 sets a plurality of virtual grid points G _n (n=1, 2, . . . N) on the traveling road 5 existing in the traveling direction of the vehicle 1 by calculation based on the traveling road information. When the direction in which the travel path 5 extends is defined as the x direction and the width direction of the travel path 5 is defined as the y direction, the grid points G _n are arranged in a grid along the x direction and the y direction.

The range in which the ECU 10 sets the grid points _Gn extends a distance L ahead of the vehicle 1 along the travel path 5 . Distance L is calculated based on the speed of vehicle 1 at the time of execution of the calculation. In this embodiment, the distance L is the distance (L=V×t) that is expected to be traveled in a predetermined fixed time t (for example, 3 seconds) at the speed (V) at the time of execution of the calculation. However, the distance L may be a predetermined fixed distance (eg 100m) or it may be a function of velocity (and acceleration). Also, the width W of the range in which the grid points G _n are set is set to a value substantially equal to the width of the travel path 5 . By setting a plurality of grid points G _n in this way, it becomes possible to specify the position on the travel path 5 .

Since the running path 5 shown in FIG. 2 is a straight section, the grid points G _n are arranged in a rectangular shape. However, since the grid points _Gn are arranged along the direction in which the road extends, if the road includes a curved section, the grid points _Gn are arranged along the curve of the curved section.

Further, the ECU 10 performs an operation for setting a route candidate RC (that is, a candidate that can be a target route for actually traveling the vehicle 1) based on the traveling road information and the obstacle information. The obstacle information includes the presence or absence of obstacles (e.g., preceding vehicles, parked vehicles, pedestrians, fallen objects, etc.) on the travel path 5 in the traveling direction of the vehicle 1, their types, sizes, moving directions, moving speeds, and the like. Information about Obstacle information is acquired by the camera 21 and the radar 22 .

The ECU 10 sets a plurality of route candidates RC by route search using the state lattice method. According to the state lattice method, a plurality of route candidates RC branching from the starting point P _s toward each grid point G _n existing in the traveling direction of the vehicle 1 are set. The starting point P _s is the position of the vehicle 1 when the calculation is executed. In the example shown in FIG. 2, the vehicle 1 is located at the origin of the xy coordinates, so the coordinates of the starting point P _s are (0, 0). The ECU 10 defines a multi-order function in which the y-coordinate has the x-coordinate as a variable, and sets a curve drawn on the x-y coordinates based on the multi-order function as a route candidate RC. The multi-order function is, for example, a quintic function or a cubic function. FIG. 2 shows route candidates RC _a , RC _b , and RC _c that are part of a plurality of route candidates RC set by the ECU 10 .

Also, the ECU 10 selects one route candidate RC with the lowest route cost from the plurality of route candidates RC. Specifically, first, the ECU 10 sets a plurality of sampling points SP along each route candidate RC, as shown in FIG. A plurality of sampling points SP are spaced apart from each other on each route candidate RC. FIG. 2 shows, as an example, sampling points SP set at regular intervals along the entire route candidates RC _a , RC _b , and RC _c .

Next, the ECU 10 calculates path costs at each sampling point SP. Furthermore, for each route candidate RC, the ECU 10 sums the route costs at the sampling points SP set along the route candidate RC, and divides the sum by the total length of the route candidate RC. The ECU 10 sets the value obtained by the division as the route cost of the route candidate RC. The ECU 10 selects the route candidate RC with the lowest route cost from among the plurality of route candidates RC, and sets it as the target route.

In addition, the ECU 10 sets control amounts for speed control and steering control of the vehicle 1 at each sampling point. The control amount is set based on the speed and steering required for the vehicle 1 to travel along the target route, and is also used to calculate the route cost. The ECU 10 transmits control signals to the engine control system 31, the brake control system 32, and the steering control system 33 based on the control amounts.

The camera 21 is an example of a travel path information acquisition device according to the present invention, and is also an example of an obstacle information acquisition device. The camera 21 photographs the surroundings of the vehicle 1 and outputs image data. Based on the image data received from the camera 21, the ECU 10 detects objects (e.g., preceding vehicles, parked vehicles, pedestrians, roads, lane markings (lane boundaries, white lines, yellow lines), traffic lights, traffic signs, stop lines, intersections, etc.). Further, when the target object is a vehicle, the ECU 10 identifies the type (large vehicle, passenger car, etc.). It should be noted that the ECU 10 may acquire information on the object from the outside through traffic infrastructure, vehicle-to-vehicle communication, or the like. As a result, the type, relative position, movement direction, etc. of the object are specified.

The radar 22 is an example of a travel path information acquisition device according to the present invention, and is also an example of an obstacle information acquisition device. The radar 22 measures the positions and velocities of objects (particularly preceding vehicles, parked vehicles, pedestrians, fallen objects on the travel path 5, etc.). As the radar 22, for example, a millimeter wave radar can be used. The radar 22 transmits radio waves in the traveling direction of the vehicle 1 and receives reflected waves generated when the transmitted waves are reflected by an object. Then, the radar 22 measures the distance between the vehicle 1 and the object (for example, the inter-vehicle distance) and the relative speed of the object with respect to the vehicle 1 based on the transmitted wave and the received wave. In addition, in this embodiment, instead of the radar 22, a laser radar, an ultrasonic sensor, or the like may be used to measure the distance to the object and the relative speed. Also, a plurality of sensors may be used to configure the position and speed measuring device.

A vehicle speed sensor 23 detects the absolute speed of the vehicle 1 . The acceleration sensor 24 detects the acceleration of the vehicle 1 (vertical acceleration/deceleration in the longitudinal direction, lateral acceleration/deceleration in the lateral direction). A yaw rate sensor 25 detects the yaw rate of the vehicle 1 . The steering angle sensor 26 detects the rotation angle (steering angle) of the steering wheel of the vehicle 1 . The accelerator sensor 27 detects the depression amount of the accelerator pedal. A brake sensor 28 detects the amount of depression of the brake pedal.

The positioning system 29 is a GPS system and/or a gyro system, and detects the position of the vehicle 1 (current vehicle position information). The navigation system 30 stores map information inside and can provide the map information to the ECU 10 . Based on the map information and the current vehicle position information, the ECU 10 identifies roads, intersections, traffic lights, buildings, etc. existing around the vehicle 1 (especially in the traveling direction). Map information may be stored in the ECU 10 .

The engine control system 31 controls the engine of the vehicle 1 . The ECU 10 sends a control signal to the engine control system 31 to change the engine output when the vehicle 1 needs to be accelerated or decelerated.

The brake control system 32 controls the braking device of the vehicle 1 . When the vehicle 1 needs to be decelerated, the ECU 10 sends a control signal to the brake control system 32 to generate braking force.

The steering control system 33 controls the steering device of the vehicle 1 . When the traveling direction of the vehicle 1 needs to be changed, the ECU 10 transmits a control signal to the steering control system 33 to change the steering direction.

Next, calculations for setting the sampling points SP will be described with reference to FIG. FIG. 3 is an explanatory diagram of route candidates RC and sampling points SP.

As described above, the ECU 10 sets a plurality of sampling points SP along each route candidate RC. As the number of sampling points SP to be set increases, the accuracy of evaluating the route cost of each route candidate RC increases, but the calculation load increases, impairing practicality. Therefore, the ECU 10 sets the sampling points SP based on the warning area WA in order to achieve both the accuracy of the route cost evaluation and the reduction of the calculation load. A method of setting the sampling points SP will be described below.

FIG. 3 shows route candidates RC and sampling points SP when the vehicle 1 is traveling on the lane 51a of the travel road 51. As shown in FIG. A pedestrian 91 exists in the left lane 51b of the lane 51a, and another vehicle 92 exists in the right lane 51c of the lane 51a. A pedestrian 91 and another vehicle 92 are moving in directions indicated by arrows V ₁ and V ₂ , respectively.

Route candidates RC ₁ to RC ₅ are set on the traveling road 51 by the route search using the state lattice method described above.

The ECU 10 sets a warning area WA ₁ on the travel path 5 . The caution area WA ₁ is a virtual area containing the pedestrian 91 . Specifically, the caution area WA ₁ extends in the direction of the arrow V ₁ by a length L ₂ (for example, 10 m), and the width W ₁₁ of the side closer to the pedestrian 91 is wider than the width W ₁₂ of the opposite side. It has a small trapezoidal shape. That is, the dimension of the caution area WA ₁ in the direction orthogonal to the direction of the arrow V ₁ increases as the distance from the pedestrian 91 increases in the moving direction. The ECU 10 sets the length L ₂ to be greater as the moving speed of the pedestrian 91 increases. Therefore, the caution area WA ₁ can be considered as a range within which the pedestrian 91 can move within a predetermined time. In the example shown in FIG. 3, the caution area WA ₁ includes portions of each of the route candidates RC ₁ and RC ₂ .

Further, the ECU 10 sets a warning area _WA2 on the travel path 5. FIG. The caution area WA ₂ is a virtual area including another vehicle 92 . Specifically, the caution area WA ₂ extends in the direction of the arrow V ₂ by a length L ₃ (for example, 30 m), and the width W ₂₁ of the side closer to the other vehicle 92 is wider than the width W ₂₂ of the opposite side. It has a small trapezoidal shape. That is, the dimension of the caution area _WA2 in the direction perpendicular to the direction of the arrow _V2 increases as the distance from the other vehicle 92 increases in the moving direction. The ECU 10 sets the length _L3 to be larger as the moving speed of the other vehicle 92 is higher. Therefore, the caution area _WA2 can be considered as a range within which the other vehicle 92 can move within a predetermined period of time. In the example shown in FIG. 3, the caution area _WA2 includes a portion of each of the route candidates _RC4 and _RC5 .

The ECU 10 sets sampling points SP at intervals d ₁ along portions near the vehicle 1 on each of the route candidates RC ₁ , RC ₂ , RC ₄ and RC ₅ . The interval _d1 is an example of the first interval according to the invention. Specifically, the ECU 10 sets sampling points SP at intervals _d1 along the first portions _RC11 , _RC21 , _RC41 , _RC51 of the route candidates _RC1 , _RC2 , _RC4 , _RC5 . . The first portions RC ₁₁ , RC ₂₁ , RC ₄₁ , RC ₅₁ extend from the vehicle 1 in the x-direction (see FIG. 2) by a length L ₁ (eg, 10 m). The ECU 10 sets the length L ₁ larger as the moving speed of the vehicle 1 increases.

The ECU 10 sets sampling points SP at intervals d ₁ along respective portions of the route candidates RC ₁ and RC ₂ relatively close to the pedestrian 91 . Specifically, the ECU 10 sets sampling points SP at intervals _{d 1 along} the second portions RC ₁₂ and RC ₂₂ included in the caution area WA ₁ of the route candidates RC ₁ and RC 2 .

Further, the ECU 10 sets sampling points SP at intervals d ₁ along portions of each of the route candidates RC ₄ and RC ₅ that are relatively close to the other vehicle 92 . Specifically, the ECU 10 sets sampling points SP at intervals d ₁ along the second portions RC ₄₂ and RC ₅₂ included in the warning area WA ₂ of the route candidates RC ₄ and RC ₅ .

Further, the ECU 10 selects the first portions _RC11 , _RC21 , _RC41 , _RC51 and _the second portions _RC12 , _RC22 , _RC42 , _RC52 of the route candidates RC1, RC2, _RC4 , _{RC5 .} Sampling points SP are set at intervals of d ₂ along the portion excluding both. The interval _d2 is an example of the second interval according to the invention.

Spacing d ₂ is greater than spacing d ₁ (eg, d ₁ =0.2 m, d ₂ =2.0 m). Therefore, the sampling points SP are set at a relatively high density along the first portions _RC11 , _RC21 , _RC41 , _RC51 and the second portions _RC12 , _RC22 , _RC42 , _RC52 , and the other portions Sampling points SP are set at a relatively low density along the . In other words, the number of sampling points SP per unit length in the first portions _RC11 , _RC21 , _RC41 , _RC51 and the second portions _RC12 , _RC22 , _RC42 , _RC52 is the same as in the other portions. more than that.

On the other hand, regarding the sampling points SP along the route candidate RC ₃ not included in any of the caution areas WA ₁ and WA ₂ , the ECU 10 determines that the first portion RC ₃₁ extending from the vehicle 1 by the length L ₁ in the x direction It is set with an interval _d1 , and the other parts are set with an interval _d2 .

As can be understood from FIG. 3 , the ECU 10 preferentially sets the sampling points SP within a range in which the pedestrian 91 and the other vehicle 92 can move within a predetermined time and in the vicinity of the vehicle 1 . In other words, in the portion of the route candidate RC excluding both the portion included in the range in which the pedestrian 91 and the other vehicle 92 can move within a predetermined time and the portion in the vicinity of the vehicle 1, the ECU 10 , sampling points SP are thinned out. As a result, it is possible to reduce the calculation load of the route cost in other parts while increasing the accuracy of the route cost evaluation in the range in which the pedestrian 91 and the other vehicle 92 can move within a predetermined time and in the vicinity of the vehicle 1. becomes possible. That is, it is possible to achieve both a reduction in the calculation load and an evaluation accuracy of the route cost.

Next, with reference to FIG. 4, calculations executed by the ECU 10 when providing driving support control will be described. FIG. 4 is a flow chart showing calculations executed by the ECU 10 . The ECU 10 repeatedly executes the calculation shown in FIG. 4 (every 0.05 to 0.2 seconds, for example).

First, in step S1, the ECU 10 acquires travel route information from the camera 21, the radar 22, and the navigation system 30 (see FIG. 1).

Next, in step S2, the ECU 10 identifies the shape of the road (for example, the direction in which the road extends, the width of the road, etc.) based on the road information, and sets a plurality of grid points _Gn on the road. (n=1, 2, . . . N) are set. For example, the ECU 10 sets grid points _Gn at intervals of 10 m in the x direction (see FIG. 2) and at intervals of 0.875 m in the y direction (see FIG. 2).

Next, in step S<b>3 , the ECU 10 acquires obstacle information from the camera 21 and the radar 22 . That is, the ECU 10 acquires information about the presence or absence of obstacles on the traveling road in the traveling direction of the vehicle 1, the types of obstacles, the direction of movement of obstacles, the speed of movement of obstacles, and the like.

Next, in step S4, the ECU 10 sets a plurality of route candidates RC on the traveling road. Specifically, the ECU 10 defines curves extending from the starting point P _s (see FIG. 2), which is the position of the vehicle 1 at the time of execution of the calculation, to each grid point G _n set in step S2, and defines these curves as paths. Set as a candidate RC.

Next, in step S5, the ECU 10 determines whether or not there is an obstacle in the traveling direction of the vehicle 1 based on the obstacle information. If it is determined that there is an obstacle in the traveling direction of the vehicle 1 (S5: YES), the ECU 10 proceeds to step S6.

Next, in step S<b>6 , the ECU 10 sets a warning area WA on the travel road 5 . As described above, the ECU 10 sets the caution area WA including the obstacle and having an outer shape according to the moving speed and moving direction of the obstacle.

If the obstacle is a vehicle, the ECU 10 may increase the outline of the warning area WA according to its type (large vehicle, passenger car, etc.). For example, when the obstacle is a large vehicle such as a truck or a bus, the ECU 10 may make the outline of the warning area WA larger than when the obstacle is a passenger car. After setting the warning area WA in step S6, the ECU 10 proceeds to step S7.

On the other hand, when it is determined in step S5 that there is no obstacle in the traveling direction of the vehicle 1 (S5: NO), the ECU 10 proceeds to step S7 without going through step S6. That is, the ECU 10 proceeds to step S7 without setting the warning area WA.

Step S7 includes setting of sampling points SP (steps S7a to 7d) and calculation of route costs (step S7e).

At step 7a, the ECU 10 sets sampling points SP at intervals _d1 along the portion of the route candidate RC near the vehicle 1. FIG. Here, sampling points SP are set along a portion of the route candidate RC that extends from the vehicle 1 in the x direction (see FIG. ₂ ) by a length L1 (see FIG. 3).

Next, in step S7b, the ECU 10 determines whether or not the route candidate RC is included in the warning area WA. When determining that the route candidate RC is included in the warning area WA (S7b: YES), the ECU 10 proceeds to step S7c.

Next, in step S7c, the ECU 10 sets sampling points SP at intervals _d1 along the portion of the route candidate RC that is included in the caution area WA.

Next, in step S7d, the ECU 10 extends the distance d ₂ sets the sampling point SP.

On the other hand, when it is determined in step S7b that the route candidate RC is not included in the warning area WA (S7b: NO), the ECU 10 proceeds to step S7d without going through step S7c. Further, even if the ECU 10 determines in step S5 that there is no obstacle in the traveling direction of the vehicle 1 (S5: NO) and the warning area WA is not set, the ECU 10 determines that the route candidate RC is within the warning area WA. (S7b: NO), and the process proceeds to step S7d without going through step S7c.

If the route candidate RC is not included in the caution area WA (S7b: NO), the ECU 10, in step S7d, follows the route candidate RC along the rest of the route candidate RC (that is, the portion excluding the vicinity of the vehicle 1). , set sampling points SP at intervals d ₂ . At this time, the range in which the sampling points SP are set at the interval _d2 is larger than when the route candidate RC is included in the caution area WA (S7b: YES). That is, when the route candidate RC is not included in the caution area WA, the number of sampling points SP to be set is smaller than when the route candidate RC is included in the caution area WA.

Next, in step S7e, the ECU 10 calculates the route cost at each sampling point SP of the route candidate RC. Path costs include costs related to velocity, acceleration, lateral acceleration, path change rate, obstacles, and the like. These costs can be set as appropriate. Generally speaking, path costs include travel costs and safety costs. For example, when traveling on a straight route, the travel distance is short, so the travel cost is small. Also, the movement cost increases as the lateral acceleration increases. As described above, the ECU 10 stores the value obtained by the division in a memory (not shown) as the route cost of the route candidate RC.

The ECU 10 performs the calculation of step S7 for all of the plurality of route candidates RC set in step S4.

Next, in step S8, the ECU 10 sets a target route. Specifically, the ECU 10 selects the route candidate RC with the lowest route cost and sets the route candidate RC as the target route.

Next, in step S9, the ECU 10 transmits control signals to the engine control system 31, the brake control system 32, and the steering control system 33 so that the vehicle 1 travels along the target route. The control signal is generated based on the control amount of the speed control and steering control of the vehicle 1 set at each sampling point SP of the target route.

The operation of the vehicle driving support system 100 of this embodiment will be described below.

According to the above configuration, the ECU 10, which is the control device, sets the warning area WA having an outer shape according to the moving speed and moving direction of the obstacle in the vicinity of the obstacle. In addition, the ECU 10 sets sampling points SP at intervals _d1 along the portion of the route candidate RC that is included in the caution area WA. Since the interval d ₁ is smaller than the interval d ₂ , a plurality of sampling points SP are set at a relatively high density near the obstacle. As a result, it is possible to improve the accuracy of route cost evaluation in the range in which movement of obstacles is considered.

On the other hand, the ECU 10 sets sampling points SP at intervals _d2 along the other portion of the route candidate RC (that is, the portion not included in the caution area WA). Since the interval _d2 is larger than the interval _d1 , a plurality of sampling points SP are set at a relatively low density in the other portion. As a result, it becomes possible to reduce the calculation load of the route cost in the other portion. Since the density of the sampling points SP is relatively low, the evaluation accuracy of the route cost in the other portion is also low, but the influence of the evaluation accuracy on the traveling of the vehicle 1 in the warning area WA is relatively small.

That is, according to the above configuration, it is possible to reduce the computational load and make the route cost evaluation accuracy practically sufficient. As a result, it is possible to achieve both the accuracy of evaluating the route cost of the route candidate RC and the reduction of the calculation load.

A plurality of sampling points SP may be set such that the density of the sampling points SP inside the caution area WA gradually increases from the end to the center of the caution area WA. This makes it possible to reduce the computational load while increasing the accuracy of path cost evaluation in the central portion of the warning area WA where there is a high possibility that obstacles are present.

Further, the ECU 10 is configured to increase the dimension of the warning area WA in the moving direction of the obstacle as the moving speed of the obstacle increases.
According to this configuration, it is possible to evaluate the route cost in consideration of obstacles after movement. As a result, it is possible to achieve both the accuracy of evaluating the route cost of the route candidate RC and the reduction of the calculation load.

Further, the ECU 10 is configured to increase the dimension of the warning area WA in the direction perpendicular to the moving direction of the obstacle as the distance from the obstacle in the moving direction increases.
According to this configuration, it is possible to evaluate the route cost in consideration of the uncertain destination of the obstacle. As a result, it is possible to achieve both the accuracy of evaluating the route cost of the route candidate RC and the reduction of the calculation load.

Further, the ECU 10 is configured to increase the outer shape of the warning area WA when the obstacle is a vehicle compared to when the obstacle is a pedestrian.
According to this configuration, when the obstacle is a vehicle, it is possible to improve the accuracy of route cost evaluation in a wider range than when the obstacle is a pedestrian. That is, it is possible to further improve the accuracy of route cost evaluation for a vehicle, which is an obstacle with a relatively high moving speed. As a result, while the calculation load is reduced, it is possible to make the route cost evaluation accuracy practically sufficient.

The embodiments of the present invention have been described above with reference to specific examples. However, the invention is not limited to these specific examples. In other words, the scope of the present invention includes any design modifications made by those skilled in the art to these specific examples as long as they have the features of the present invention.

1 vehicle 10 ECU (control device)
21 camera (travel path information acquisition device, obstacle information acquisition device)
22 radar (running path information acquisition device, obstacle information acquisition device)
30 navigation system (running route information acquisition device)
100 Vehicle driving support system RC Route candidate SP Sampling point

Claims (3)

A vehicle driving support system mounted on a vehicle,
a traveling road information acquisition device that acquires traveling road information about the traveling road;
an obstacle information acquisition device that acquires obstacle information about obstacles on the traveling road;
a control device that sets a target route on the travel route based on the travel route information and controls the vehicle to travel along the target route;
The control device is
setting a plurality of curved route candidates on the traveling road based on the traveling road information;
setting a plurality of sampling points at predetermined intervals along the curve shape of each of the plurality of route candidates;
calculating a path cost at each of the plurality of sampling points;
configured to select one route candidate from the plurality of route candidates as the target route based on the route cost;
Furthermore, the control device
setting a warning area near the obstacle having an outer shape according to the moving speed and moving direction of the obstacle;
The sampling points are set at a first interval along a portion of the route candidate included in the caution area, and the sampling points are set at a second interval larger than the first interval along the other portion. ,
The size of the caution area in the movement direction of the obstacle is increased as the movement speed of the obstacle is increased .
A vehicle driving support system characterized by: 2. The vehicle according to claim 1 , wherein said control device is configured to increase the size of said caution area in a direction perpendicular to the movement direction of said obstacle as the distance from said obstacle increases in said movement direction. driving assistance system. 3. The control device according to claim 1 or 2 , wherein when the obstacle is a vehicle, the outer shape of the warning area is made larger than when the obstacle is a pedestrian. Vehicle driving assistance system.

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