JP7322649B2 - SAFE DISTANCE DETERMINATION DEVICE AND SAFE DISTANCE DETERMINATION METHOD - Google Patents

Description

The present invention relates to a safe distance determining device and a safe distance setting method equipped with a braking capacity estimating device mounted on a vehicle.

In vehicle braking control, etc., it is necessary to estimate the braking capacity of the vehicle. As used herein, braking ability is the ability to slow down a vehicle. The braking distance varies depending on the speed and braking capacity of the vehicle.

A vehicle control device described in Patent Literature 1 calculates a safe inter-vehicle distance (hereinafter referred to as a safe distance) between a host vehicle and a vehicle immediately ahead. Then, when the inter-vehicle distance becomes equal to or less than the safety distance, the vehicle is brought to an emergency stop. The safe distance can be calculated based on the respective braking capabilities of the preceding vehicle and the own vehicle.

International Publication No. 2018/115963 pamphlet

Even for the same vehicle, if the road surface condition (hereinafter referred to as road surface condition) of the road on which the vehicle is traveling changes, the braking distance will change. That is, the braking ability changes depending on the road surface condition. Factors that affect the braking ability of a vehicle (hereinafter referred to as brake influence factors) include factors that change with time. Brake influencing factors include braking system devices such as tires and brake pads, and vehicle weight.

In Patent Literature 1, changes over time in characteristics of road surface conditions and brake influencing factors are not taken into consideration. Therefore, with the technology disclosed in Patent Document 1, the accuracy of estimating the braking capacity is insufficient. Moreover, if the estimation accuracy of the braking capacity is insufficient, the reliability of the safety distance will also be low.

The present disclosure has been made based on this situation, and its purpose is to improve the reliability of a safe distance by providing a braking capacity estimation device that can improve the accuracy of estimating braking capacity. To provide a safe distance determining device and a safe distance determining method capable of improving the reliability of the safe distance by improving the estimation accuracy of the braking ability.

The above objects are achieved by the combination of features stated in the independent claims, and the sub-claims define further advantageous embodiments. The symbols in parentheses described in the claims indicate the corresponding relationship with specific means described in the embodiments described later as one aspect, and do not limit the disclosed technical scope.

One disclosure related to a braking capacity estimating device provided in a safe distance setting device for achieving the above object is
A braking capacity estimating device that is mounted on a vehicle and estimates braking capacity that is the ability to stop the vehicle,
a road surface condition determination unit (112) that sequentially determines the surface condition of the road on which the own vehicle (1), which is a vehicle equipped with a braking capacity estimation device, is traveling;
A braking capacity estimating section (114) for sequentially estimating the braking capacity of the own vehicle based on the road surface state determined by the road surface state determining section.

The braking ability of the self-vehicle changes depending on the road surface condition. Therefore, the braking capacity estimating section estimates the braking capacity of the host vehicle based on the road surface condition determined by the road surface condition determining section. Therefore, the braking ability of the own vehicle can be estimated with higher accuracy than when the road surface condition is not considered.

Another disclosure related to a braking capacity estimating device provided in a safe distance setting device for achieving the above object is
A braking capacity estimating device that is mounted on a vehicle and estimates braking capacity that is the ability to stop the vehicle,
a characteristic updating unit (113) for sequentially updating characteristics of factors that change with time among brake influence factors that affect the braking ability of the own vehicle (1), which is a vehicle equipped with a braking ability estimating device; ,
A braking capacity estimator (114) for sequentially estimating the braking capacity of the own vehicle based on the characteristics of the brake influencing factors.

The braking ability of the own vehicle changes according to the characteristics of the brake influencing factors of the own vehicle. Also, some of the brake influence factors of the host vehicle change with time. Therefore, the characteristic update unit sequentially updates the characteristic of factors that change with time among the brake influence factors of the own vehicle. The braking capacity estimator sequentially estimates the braking capacity of the own vehicle based on the characteristics of the brake influencing factors of the own vehicle. Therefore, it is possible to accurately estimate the braking ability of the own vehicle.

One disclosure related to a safe distance determination device for achieving the above object is
a braking capacity estimation device;
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the subject vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle ,
The other-vehicle braking capacity estimator estimates the characteristics of the braking influence factor, which is a factor that affects the braking capacity of the preceding vehicle, and successively calculates the braking capacity of the preceding vehicle based on the estimated characteristics of the braking influence factor of the preceding vehicle. Estimate .
In addition, another disclosure related to a safe distance determination device for achieving the above object is
a braking capacity estimation device;
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the subject vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle,
When the braking ability of the preceding vehicle can be received from the preceding vehicle via wireless communication, the other vehicle braking ability estimating section estimates the braking ability of the preceding vehicle received via wireless communication instead of estimating the braking ability of the preceding vehicle. , to the safety distance determination unit.

In addition, one disclosure related to a safe distance determination method for achieving the above object is
A safe distance determination method for determining a safe distance between an own vehicle and a preceding vehicle traveling in front of the own vehicle ,
Based on the sensor values detected by the sensors mounted on the own vehicle, the road surface condition of the road on which the own vehicle is traveling is sequentially determined,
Based on the determined road surface condition, the vehicle 's braking ability is estimated sequentially ,
estimating the characteristics of the brake influence factor, which is a factor that affects the braking ability of the vehicle ahead, sequentially estimating the braking ability of the vehicle ahead based on the estimated characteristics of the brake influence factor of the vehicle ahead;
A safe distance is determined based on the braking ability of the host vehicle and the braking ability of the preceding vehicle .
In addition, another disclosure related to a safe distance determination method for achieving the above object is
A safe distance determination method for determining a safe distance between an own vehicle and a preceding vehicle traveling in front of the own vehicle,
Based on the sensor values detected by the sensors mounted on the own vehicle, the road surface condition of the road on which the own vehicle is traveling is sequentially determined,
Based on the determined road surface condition, the vehicle's braking ability is estimated sequentially,
Estimate the braking capacity of the vehicle in front,
Determining a safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle,
When the braking ability of the vehicle ahead can be received from the vehicle ahead by wireless communication, instead of estimating the braking ability of the vehicle ahead, the braking ability of the vehicle ahead is received by wireless communication.

In addition, another disclosure related to a safe distance determination method for achieving the above object is
A safe distance determination method for determining a safe distance between an own vehicle and a preceding vehicle traveling in front of the own vehicle ,
Sequentially updating the characteristics of the factors that change over time among the brake influence factors that affect the braking performance of the own vehicle,
Sequentially estimating the braking ability of the own vehicle based on the characteristics of the brake influencing factors ,
estimating the characteristics of the brake influence factor, which is a factor that affects the braking ability of the vehicle ahead, sequentially estimating the braking ability of the vehicle ahead based on the estimated characteristics of the brake influence factor of the vehicle ahead;
A safe distance is determined based on the braking ability of the host vehicle and the braking ability of the preceding vehicle .
In addition, another disclosure related to a safe distance determination method for achieving the above object is
A safe distance determination method for determining a safe distance between an own vehicle and a preceding vehicle traveling in front of the own vehicle ,
Sequentially updating the characteristics of the factors that change over time among the brake influence factors that affect the braking performance of the own vehicle,
Sequentially estimating the braking ability of the own vehicle based on the characteristics of the brake influencing factors ,
Estimate the braking capacity of the vehicle in front,
Determining a safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle,
When the braking ability of the vehicle ahead can be received from the vehicle ahead by wireless communication, instead of estimating the braking ability of the vehicle ahead, the braking ability of the vehicle ahead is received by wireless communication.

It is a figure which shows the structure of the vehicle control apparatus 100 of 1st Embodiment. FIG. 2 is a diagram showing an example of processing of a road surface state determining unit 112 of FIG. 1; FIG. It is a figure which shows the processing order until it calculates a safe distance. It is a figure which shows the process which presumes brake ability. It is a figure which shows the structure of the vehicle control apparatus 200 of 2nd Embodiment. It is a figure which shows the process which the brake capability estimation part 114 performs in 2nd Embodiment. FIG. 9 is a diagram showing processing executed by an other vehicle braking capability estimation unit 116 in the second embodiment; It is a figure which shows the structure of the vehicle control apparatus 300 of 3rd Embodiment. It is a figure which shows the process replaced with FIG. 4 and performed in 3rd Embodiment. FIG. 10 is a diagram showing in detail the processing of S51 of FIG. 9; FIG. It is a figure which shows the process which a sensor integration part performs in 4th Embodiment. FIG. 14 is a diagram showing processing executed by a road surface state determination unit 112 when calculating a road surface shape in the fifth embodiment; FIG. 13 is a diagram showing processing executed by a road surface state determination unit 112 when calculating a road surface friction coefficient _μe in the sixth embodiment; FIG. 21 is a diagram showing processing executed by a characteristic updating unit 113 in the seventh embodiment; FIG. It is a figure which shows the process which calculates friction coefficient (micro|micron|mu) in 7th Embodiment. FIG. 15 is a diagram showing processing executed by a characteristic updating unit 113 in place of FIG. 14 in the eighth embodiment; FIG. 21 is a diagram showing processing executed by a road surface state determining unit 112, a braking ability estimating unit 114, and an other vehicle braking ability estimating unit 116 in the ninth embodiment; It is a figure which shows the process replaced with FIG. 4 and performed in 10th Embodiment. It is a figure which shows the process which the brake capability estimation part 114 performs in 11th Embodiment. FIG. 21 is a diagram showing processing executed by an other vehicle braking capability estimating unit 116 in the twelfth embodiment;

<First embodiment>
Hereinafter, embodiments will be described based on the drawings. FIG. 1 is a diagram showing the configuration of a vehicle control device 100 according to the first embodiment. A vehicle control device 100 is mounted on the own vehicle 1 . When a certain vehicle control device 100 is used as a reference, the own vehicle 1 is a vehicle in which the vehicle control device 100 is mounted.

The vehicle control device 100 operates as a braking capacity estimation device, executes a braking capacity estimation method, and estimates the braking capacity of the host vehicle 1 . In addition, the vehicle control device 100 also operates as a safe distance determination device, estimates the braking ability of the preceding vehicle traveling in front of the own vehicle 1, and based on the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle. to determine the safety distance.

Braking ability is the ability to slow down the vehicle. The vehicle is not particularly limited as long as it travels on the road. Vehicles include passenger cars, trucks, buses, and the like. The vehicle control device 100 is a device that controls the behavior of the own vehicle 1 . Behavior includes speed and heading. The vehicle control device 100 executes vehicle control corresponding to an automatic driving level of level 1 or higher. The vehicle control device 100 automatically decelerates and stops the own vehicle 1 .

The vehicle control device 100 has one or more sensors 101 . Let the value output by the sensor 101 be a sensor value. The sensors 101 include sensors that detect the behavior of surrounding vehicles. A sensor that detects the behavior of the surrounding vehicle outputs a sensor value that indicates the behavior of the surrounding vehicle. Sensor 101 may include a camera. Alternatively, the sensor 101 may include a millimeter wave radar, Lidar. As the sensor 101, sensors 101a, 101b, and 101c are shown in FIG. These sensors 101a, 101b, and 101c are referred to as sensor 101 when they are not distinguished from each other.

The sensors 101 also include sensors that detect the position of the vehicle 1 and the behavior of the vehicle 1 . If the current position of the own vehicle 1 (hereinafter referred to as the own vehicle position) can be sequentially detected, the speed and traveling direction of the own vehicle 1, which are the behavior of the own vehicle 1, can be determined. Therefore, it is not necessary to include a sensor for detecting the position of the vehicle and not the sensor 101 for directly detecting the behavior of the vehicle 1 . A GNSS receiver can also be included in the sensor 101 that detects the position of the vehicle. The sensor 101 that detects the behavior of the own vehicle 1 can include a vehicle speed sensor, a yaw rate sensor, an acceleration sensor, and the like.

Also, the current position of the vehicle can be detected by comparing the shape of the surroundings of the vehicle 1 detected by Lidar or the like with the high-precision map. In this case, the position of the own vehicle 1 and the behavior of the own vehicle 1 are detected by the sensor 101 that detects the behavior of surrounding vehicles without providing the dedicated sensor 101 that detects the position of the own vehicle 1 and the behavior of the own vehicle 1. can do.

The sensor integration unit 110, the route planning unit 120, the accident responsibility determination unit 130, and the travel unit 140 can be implemented by a configuration including at least one processor. For example, the sensor integration unit 110, the route planning unit 120, the accident responsibility determination unit 130, and the travel unit 140 are computers having at least one processor, ROM, RAM, I/O, and bus lines connecting these components. It can be realized by The ROM stores a program for causing a general-purpose computer to function as a sensor integration unit 110, a route planning unit 120, an accident liability determination unit 130, and a traveling unit 140. FIG. The computer functions as a sensor integration unit 110, a route planning unit 120, an accident responsibility determination unit 130, and a travel unit 140 by the processor executing programs stored in the ROM while using the temporary storage function of the RAM. Execution of these functions means execution of the vehicle control method corresponding to the program.

The sensor integration unit 110, the route planning unit 120, the accident responsibility determination unit 130, and the travel unit 140 can be realized by separate processors. Moreover, the sensor integration unit 110, the route planning unit 120, the accident responsibility determination unit 130, and the traveling unit 140 may be realized by a configuration including three or less processors.

A sensor value is input from the sensor 101 to the sensor integration unit 110 . The sensor integration section 110 includes a vehicle identification section 111 , a road surface state determination section 112 , a braking capacity estimation section 114 , an other vehicle braking capacity estimation section 116 and a safe distance determination section 118 .

The vehicle identification unit 111 sequentially determines the relative behavior of surrounding vehicles based on the sensor values. The vehicle identification unit 111 also determines the position and behavior of the own vehicle 1 .

Relative behavior includes relative position and relative velocity. A relative position can be represented by a relative distance and a relative orientation. Relative behavior can also be determined from changes in the position of own vehicle 1 and the positions of surrounding vehicles.

The road surface condition determination unit 112 successively determines the road surface condition of the road on which the vehicle 1 travels. Road surface conditions include road surface shape, road surface slope, and road surface wetness.

FIG. 2 shows an example of the processing of the road surface state determination unit 112. As shown in FIG. In the example shown in FIG. 2, a camera and lidar are used as the sensor 101 that determines the road surface condition. The road surface state determining unit 112 periodically and repeatedly executes the processing shown in FIG. 2 while the vehicle 1 is running.

In step (hereinafter, step is omitted) S1, a camera image is acquired. This camera image is an image including an image of the road on which the vehicle 1 is traveling. In S2, the measured value by Lidar is acquired. In S3, based on the data obtained in S1 and S2, the shape of the road surface, the slope of the road surface, and the degree of wetness of the road surface are calculated. The road surface shape includes the shape of the road surface in the vertical direction, in other words, the roughness of the road surface. It is preferable to detect the road surface roughness with an accuracy that can distinguish the material of the road surface. The material of the road surface is, for example, asphalt, cobblestone, sand, or the like. Lidar measurement values may be able to detect the roughness of the road surface with such accuracy that the materials of the road surface can be distinguished. Alternatively, the camera image may be analyzed to determine the road surface material, and the road surface roughness may be estimated from the road surface material.

Road surface slope can be determined either from camera images or Lidar measurements. Further, if the sensor 101 includes a tilt sensor, the road surface tilt may be determined based on the detected value of the tilt sensor.

The road surface wetness can be determined by analyzing camera images. It is also possible to calculate the wetness of the road surface from the Lidar measurement values. Alternatively, the road surface wetness may be calculated by combining camera images, lidar measurement values, and other sensor values, that is, by sensor fusion. The shape of the road surface and the slope of the road surface may also be determined by combining multiple types of sensor values.

Returning to FIG. The braking capacity estimator 114 sequentially estimates the braking capacity of the own vehicle 1 . As mentioned above, braking ability is the ability to slow down the vehicle. The braking ability of the own vehicle 1 is determined based on the ability of the brake device provided with the own vehicle 1 . However, the braking ability of the own vehicle 1 cannot be accurately determined only by the ability of the brake device provided in the own vehicle 1 .

Even if the performance of the braking device is exactly the same, the braking distance when decelerating from the same vehicle speed changes if the road surface condition is different. Further, even if the performance of the brake device of the own vehicle 1 is exactly the same, the braking distance when decelerating from the same vehicle speed changes if the tire performance is different. Further, even if the performance of the braking device is exactly the same, if the vehicle weight changes, the braking distance when decelerating from the same vehicle speed changes. That is, even if the performance of the braking device is exactly the same, the braking performance of the own vehicle 1 changes. In this specification, a brake system includes a brake system including a brake pad and a member in a vehicle that is mechanically connected to the brake system and whose rotational speed is reduced by the braking force of the brake system. do. A braking device is a device that operates when the foot brake is stepped on. However, the braking device can also be actuated automatically. Brake system devices include brake devices and tires.

Furthermore, the performance of the brake device itself also changes due to wear of the brake pads and the like. Therefore, the vehicle control device 100 includes the braking capacity estimating section 114 to sequentially estimate the braking capacity of the own vehicle 1 .

In this embodiment, the braking ability of the own vehicle 1 is estimated based on the road surface condition determined by the road surface condition determination unit 112 . For example, a braking capacity estimation map that determines the braking capacity from the road surface condition is stored in advance, and the braking capacity of the own vehicle 1 is estimated using the road surface condition determined by the road surface condition determining unit 112 and the braking capacity estimation map. . In addition, a braking capacity estimation function that corrects the reference braking capacity according to the road surface condition is stored in advance, and the road surface condition determined by the road surface condition determination unit 112 and the braking capacity estimation function are used to determine the Braking capacity may be estimated.

The pre-stored braking capacity estimation map or braking capacity estimation function is determined through actual experiments or simulations. The braking capacity estimation map or braking capacity estimation function determined through experiments and simulations reflects the characteristics of the braking system. Therefore, by using these braking capacity estimation maps or braking capacity estimation functions, the braking capacity of the own vehicle 1 is estimated based on the characteristics of the brake system device of the own vehicle 1 .

Note that in the present embodiment, changes in the vehicle weight and changes in the performance of the braking system are not taken into consideration when estimating the braking performance. An example of estimating the braking ability of the own vehicle 1 in consideration of these will be described in the second embodiment and later. In addition, in the present embodiment, changes in the vehicle weight and changes in the performance of the braking system are not taken into consideration in estimating the braking performance. , the accuracy of the braking ability is inferior.

Therefore, the braking ability may be expressed as having a distribution such as a normal distribution. For example, the horizontal axis of the distribution is braking capacity and the vertical axis is probability. Alternatively, the braking capability may be represented by a distribution in which the horizontal axis is the braking distance at a certain vehicle speed and the vertical axis is the probability that the vehicle can be stopped at that braking distance. In the latter case, the braking distance on the horizontal axis is corrected according to the vehicle speed of the vehicle 1 at that time. By doing so, it is possible to obtain the distribution of the probability that the vehicle can be stopped at a certain braking distance based on the braking ability.

Also, unlike the above, the braking ability may be a single value that does not have a distribution. In this case, the vehicle weight, the capacity of the braking system, and the like are assumed to be standard values, and the braking capacity is estimated. Alternatively, the vehicle weight, the capacity of the brake system, and the like may be set to the worst values that should generally be considered in brake control.

The non-vehicle braking capacity estimator 116 successively estimates the braking capacity of the vehicle ahead of the host vehicle 1 . Since the braking ability of the vehicle ahead of the own vehicle 1 also changes depending on the road surface condition, etc., the other vehicle braking ability estimation unit 116 sequentially estimates the braking ability of the vehicle ahead of the own vehicle 1 . Vehicles in front of own vehicle 1 include the nearest preceding vehicle that runs in the same lane as own vehicle 1 . In addition, a preceding vehicle traveling in a lane adjacent to the lane in which the own vehicle 1 travels may be included.

The method of estimating the braking ability of the preceding vehicle by the other vehicle braking ability estimating section 116 may be the same as that of the braking ability estimating section 114 . That is, the braking capacity of the preceding vehicle is sequentially estimated using the braking capacity estimation map and the braking capacity estimation function. The braking capacity estimation map and braking capacity estimation function used by the other vehicle braking capacity estimating unit 116 may be the same as the map and function for the own vehicle, but they may also be dedicated for the preceding vehicle. Also, the braking capacity estimation map and the braking capacity estimation function for the forward vehicle may be provided for each vehicle type instead of one type.

Furthermore, like the braking ability of the own vehicle 1, the braking ability of the preceding vehicle may also be expressed as having a distribution such as a normal distribution. Also, unlike this, the braking ability of the preceding vehicle may also be a single value that does not have a distribution.

A safe distance determining unit 118 determines a safe distance between the host vehicle 1 and the preceding vehicle. The safe distance is a distance at which the host vehicle 1 does not collide with the forward vehicle even if the forward vehicle decelerates at the maximum possible speed for the forward vehicle and stops. Therefore, in order to determine the safe distance, the vehicle speed of the preceding vehicle, the braking ability of the preceding vehicle, the vehicle speed of the own vehicle 1, and the braking ability of the own vehicle 1 are required. Therefore, the safe distance determination unit 118 determines the safe distance from the speed of the vehicle ahead, the braking ability of the vehicle ahead estimated at 116 , the speed of the vehicle 1 , and the braking ability of the vehicle 1 estimated at 114 .

Sensor integration unit 110 outputs sensor base information S to route planning unit 120 and accident responsibility determination unit 130, respectively. The sensor base information S is sensor values input to the sensor integration unit 110 and information that can be derived based on the sensor values. Information that can be derived from sensor values includes target vehicle information and safe distance. The target vehicle information is information representing the relative behavior of surrounding vehicles determined by the vehicle identification unit 111 from sensor values and the position and behavior of the own vehicle 1 .

The route planning unit 120 sequentially plans candidate routes T _i (i=1, 2, 3, . A short-term route is a route for determining control to be executed by the traveling unit 140 . The traveling unit 140 controls the acceleration/deceleration and traveling direction of the own vehicle 1 . The short-term route is a route for which the direction and speed of the vehicle 1 is determined in the next control cycle executed by the traveling unit 140 . The short-term route also includes time information, and determines where the vehicle 1 should be positioned at a certain time.

The route planning unit 120 determines the candidate route T _i based on the relative behavior of the surrounding vehicles identified by the vehicle identification unit 111 . As described above, the candidate route T _i is a route that is a short-term route candidate. A short-term route is a route obtained by dividing a long-term route into a plurality of routes, and is a route that allows the vehicle to travel on the long-term route while avoiding surrounding vehicles. Therefore, the short-term route is a route for continuing travel. A long-term route is a route from the current position to the destination. If the destination is set by the occupant of the own vehicle 1, the destination can be set as the destination. Alternatively, the destination may be a point after traveling a certain distance on the road on which the vehicle 1 is currently traveling.

The route planning unit 120 plans a plurality of candidate routes T _i . The candidate route T _i is a candidate route for the short-term route to be instructed to the traveling unit 140 . Even two routes that change lanes to avoid a vehicle in front are different candidate routes T _i if they change lanes at different times. In addition, as described above, the short-term route also includes time information. Therefore, even if the route is the same straight route, if the position reached after Δt seconds is different, it becomes a different candidate route T _i . The number of candidate routes T _i planned by the route planning unit 120 is not particularly limited. The number of candidate routes T _i planned by the route planner 120 may vary depending on the situation. The route planning section 120 sends the planned candidate route T _i to the accident responsibility determination section 130 .

The accident liability determination unit 130 includes an accident liability prediction unit 131 , a route selection unit 132 and an emergency stop selection unit 133 . Accident liability prediction unit 131 _predicts the occurrence of an accident in own vehicle 1 while traveling along candidate route _Ti planned by route planning unit 120. Predict responsibility for accidents that occur in vehicle 1 . Accident liability can be represented, for example, by a potential accident liability value AL _val . The potential accident liability value AL _val is a value that indicates the degree of liability of the own vehicle 1 when an accident occurs between the subject vehicle and the own vehicle 1 .

In this embodiment, the potential accident liability value AL _val becomes a smaller value as the liability becomes lower. The potential accident liability value AL _val becomes a smaller value as the own vehicle 1 drives more safely. For example, when a sufficient inter-vehicle distance is ensured, the potential accident liability value AL _val becomes a small value. Also, the potential accident liability value AL _val can be set to a large value when the own vehicle 1 suddenly accelerates or decelerates. Further, the accident liability prediction unit 131 can set the potential accident liability value AL _val to a low value when the own vehicle 1 is traveling according to the traffic rules. In order to determine whether the own vehicle 1 is traveling according to the traffic rules, the accident liability prediction unit 131 can have a configuration for acquiring the traffic rules of the point where the own vehicle 1 is traveling.

As a configuration for acquiring the traffic rules of the point where the own vehicle 1 is traveling, a configuration can be adopted in which the position of the own vehicle 1 is detected and the traffic rules for that position are acquired from the rule database. In addition, the traffic rules for the current position can be acquired by analyzing the image captured by the camera that captures the surroundings of the vehicle 1 and detecting signs, traffic lights, road markings, and the like.

The route selection unit 132 selects a route to instruct the traveling unit 140 from the candidate routes T _i planned by the route planning unit 120 . The selected route is hereinafter referred to as a selected route T _passed . The selected path _{T_passed} must be the cautious path _{T_safe} . The cautious route T _safe is a route in which the target vehicle is not responsible for an accident.

The emergency stop selection unit 133 provides the traveling unit 140 with a preset emergency stop route _Te . The emergency stop route T _e is a route selected when there is no cautious route T _safe . The emergency stop route _Te is, for example, a route for decelerating the vehicle 1 at the maximum speed until the vehicle 1 stops without changing the steering angle.

Accident responsibility determining unit 130 outputs selected route T _passed to traveling unit 140 . The selected route T _passed is the cautious route T _safe when the route selection unit 132 selects the cautious route T _safe . When the emergency route planning unit 134 selects the emergency stop route _Te , it outputs the emergency stop route _Te to the traveling unit 140 as the selected route T _passed .

The traveling unit 140 determines the traveling direction and speed of the own vehicle 1 so as to travel along the selected route T _passed . Then, based on the determined traveling direction and speed, the steering actuator provided in the host vehicle 1 and the driving force source and braking device provided in the host vehicle 1 are controlled.

[Processing order until calculating the safety distance]
Next, the processing order up to the calculation of the safe distance will be described with reference to FIG. The safe distance needs to be determined sequentially while the own vehicle 1 is running. Therefore, the process shown in FIG. 3 is periodically executed while the own vehicle 1 is running.

In S11, the vehicle identification unit 111 determines the inter-vehicle distance to the preceding vehicle and the speed of the preceding vehicle. The inter-vehicle distance to the forward vehicle can be detected from detection values of lidar or camera, for example. The speed of the forward vehicle is determined from the temporal change in the position of the forward vehicle. Alternatively, the relative speed of the preceding vehicle with respect to the own vehicle 1 may be determined from the change in the inter-vehicle distance, and the speed of the preceding vehicle may be determined from this relative speed and the speed of the own vehicle 1, which will be described below.

In S<b>12 , the vehicle identification unit 111 determines the speed of the own vehicle 1 . In S<b>13 , the braking capacity estimator 114 estimates the braking capacity of the host vehicle 1 . In S14, the other vehicle braking capacity estimation unit 116 estimates the braking capacity of the preceding vehicle. The estimation of the braking ability is performed by the processing shown in FIG.

In S21, the road surface shape is acquired. In S22, the road surface inclination is acquired. In S23, the road surface wetness is acquired. The road surface shape, the road surface inclination, and the road surface wetness are calculated by the road surface condition determining unit 112 as described with reference to FIG.

In S24, the braking capacity is estimated from the road surface shape, road surface inclination, road surface wetness obtained in S21 to S23, and the braking capacity estimation map or braking capacity estimation function described above. The braking capacity of the own vehicle 1 can be estimated by using the one for the own vehicle as the braking capacity estimation map or the braking capacity estimation function. If the brake capacity estimation map or the brake capacity estimation function for the preceding vehicle is used, the braking capacity of the preceding vehicle can be estimated.

Returning the description to FIG. At S15, a safe distance is calculated from the speed and braking ability of the host vehicle 1 and the speed and braking ability of the preceding vehicle determined at S11 to S14. Specifically, the braking distance of the own vehicle 1 is obtained from the speed and braking ability of the own vehicle 1 . Also, the braking distance of the preceding vehicle can be obtained from the speed and braking capacity of the preceding vehicle. From these two differences, the distance at which the own vehicle 1 approaches the preceding vehicle when the own vehicle 1 and the preceding vehicle stop is obtained. This distance is the safety distance, and if the current inter-vehicle distance determined in S11 is longer than the safety distance, the possibility of collision between the vehicle 1 and the preceding vehicle is low.

Incidentally, as described above, the braking ability can be distributed. In this case, when the own vehicle 1 and the preceding vehicle stop, the distance at which the own vehicle 1 approaches the preceding vehicle also has a distribution. If there is a distribution in the distance at which the own vehicle 1 approaches the preceding vehicle, the distance corresponding to a predetermined probability is set as the safe distance.

[Summary of the first embodiment]
The braking ability of the own vehicle 1 changes according to road surface conditions. Therefore, the braking capacity estimating section 114 estimates the braking capacity of the host vehicle 1 based on the road surface state determined by the road surface state determining section 112 and a pre-stored braking capacity estimation map or braking capacity estimation function. . Therefore, the braking ability of the own vehicle 1 can be estimated with higher accuracy than when the road surface condition is not considered.

In addition, in this embodiment, the braking ability of the preceding vehicle is also estimated in consideration of the road surface condition determined by the road surface condition determination unit 112 . Then, the safe distance between the preceding vehicle and the own vehicle 1 is sequentially determined from the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle, which are successively estimated in consideration of the road surface condition. Therefore, the reliability of the safety distance is also improved.

<Second embodiment>
Next, a second embodiment will be described. In the following description of the second embodiment, the elements having the same reference numerals as those used so far are the same as the elements having the same reference numerals in the previous embodiments unless otherwise specified. Moreover, when only part of the configuration is described, the previously described embodiments can be applied to the other portions of the configuration.

FIG. 5 shows the configuration of a vehicle control device 200 according to the second embodiment. The vehicle control device 200 differs from the sensor integration section 110 of the first embodiment in the configuration of the sensor integration section 210 . The sensor integrator 210 of the second embodiment includes a characteristic updater 113 instead of the road surface condition determiner 112 .

The characteristic update unit 113 sequentially updates the characteristic of the brake influence factor in the own vehicle 1 . Specifically, the tire condition, vehicle weight, and brake pad wear condition are sequentially updated. Specifically, the state of the tire in this embodiment is the wear state of the tire. As the sensor 101, a camera may be installed below a mirror or the like in order to capture an image of the periphery of the vehicle, which tends to be a blind spot for the driver. A camera that captures an image of the periphery of a vehicle sometimes includes tires within the image capture range. In that case, the wear state of the tire can be estimated by analyzing the camera image. Further, the wear state of the tire may be estimated from changes in the relationship between the deceleration and the actuation for decelerating the vehicle 1, such as the amount of brake depression and the brake hydraulic pressure.

By attaching a load sensor to the suspension, it is possible to measure the change in vehicle weight from the reference weight. The standard weight is the weight determined by the model of the vehicle. The wear state of the brake pads can be estimated from the mileage since the brake pads were replaced. Further, a sensor for detecting the wear state of the brake pads may be provided, and the wear state of the brake pads may be estimated from the detected value of the sensor. In addition, the change in the relationship between the operation of decelerating the host vehicle 1 and the deceleration affects not only the wear state of the tires but also the wear state of the brake pads. Therefore, the wear state of the tire and the wear state of the brake pad may be estimated together from the change in the relationship between the deceleration of the vehicle 1 and the deceleration.

The frequency with which the characteristic updating unit 113 updates these characteristics, that is, the tire wear state, the brake pad wear state, and the vehicle weight, can be, for example, every run. One run is a run from ignition on to ignition off. These characteristics estimated by the characteristic updating unit 113 are overwritten and saved in place of the characteristics already stored in a predetermined storage unit.

FIG. 6 shows processing executed by the braking capacity estimation unit 114 in the second embodiment. In S31, the wear condition of the tire of the own vehicle 1 is acquired. In S32, the vehicle weight of the own vehicle 1 is acquired. In S33, whether engine braking is possible or not is acquired. If the driving force source of the own vehicle 1 is only the motor and the own vehicle 1 is not equipped with an engine, the engine brake cannot be operated. During braking, the accelerator is turned off, so if the own vehicle 1 is equipped with an engine as a driving force source, the engine brake operates. However, in S33, information is acquired for determining whether a stronger braking force can be generated by engine braking. If the gear ratio can be increased when the accelerator is off, the braking force by the engine brake can be made larger than when the gear ratio is not changed. Therefore, in S33, information indicating whether an engine is mounted as a driving force source and whether the gear ratio can be changed by the control device is acquired.

If the gear ratio can be increased and the engine brake can be applied during braking, the braking capability will be enhanced. In the following description, activating engine braking by increasing the gear ratio during braking is simply referred to as being capable of engine braking. If engine braking is possible, the braking capability will be high. Therefore, whether engine braking is possible is a characteristic of the brake influencing factors that affect braking ability.

In S34, the state of wear of the brake pads is obtained. Tire wear, vehicle weight and brake pad condition also affect braking ability. Therefore, the wear condition of these tires, the vehicle weight, and the condition of the brake pads are also characteristics of the brake influencing factors.

At S35, the braking ability of the own vehicle 1 is estimated based on the information acquired at S31 to S34. In order to estimate the braking capacity of the own vehicle 1, a braking capacity estimation map or a braking capacity estimation function is stored in advance, with which the braking capacity can be estimated from the information obtained in S31 to S34, as in the first embodiment. . The braking capacity of the own vehicle 1 is estimated based on the braking capacity estimation map or the braking capacity estimation function and the information obtained in S31 to S34. Also in the second embodiment, the braking ability of the own vehicle 1 may have a distribution such as a normal distribution.

The braking capacity estimation map or braking capacity estimation function estimates that the braking capacity is higher when engine braking is possible than when engine braking is not available. An example of how much the braking capability is changed depending on whether engine braking is possible or not is shown below. For example, if the braking capacity has a distribution, when engine braking is possible, compared to when engine braking is not available, the center value of the distribution is shifted to the higher side by a predetermined constant value. change.

FIG. 7 shows processing executed by the other vehicle braking capability estimation unit 116 in the second embodiment. In S41, the state of wear of the tires of the preceding vehicle is estimated. For example, if the front camera of the vehicle 1 can photograph the tires of the vehicle ahead when the vehicle ahead is stopped, the wear state of the tires of the vehicle ahead can be estimated.

In S42, the vehicle weight of the preceding vehicle is estimated. As for the vehicle weight of the forward vehicle, when the forward vehicle can be photographed by a camera, the standard vehicle weight of the vehicle type or model can be obtained based on the vehicle type or model of the forward vehicle. Also, the number of occupants in the forward vehicle is estimated from the image of the forward vehicle captured by the camera. Multiply this number of occupants by the standard weight per person to estimate the total weight of the occupants. Then, the sum of the standard vehicle weight and the total weight of the occupants is estimated as the vehicle weight. The tire wear condition and vehicle weight of the preceding vehicle may also be estimated each time the vehicle travels and each time the preceding vehicle is changed to another vehicle.

In S43, based on the values acquired in S41 and S42, the braking ability of the preceding vehicle is estimated. In order to estimate the braking capacity of the preceding vehicle, a braking capacity estimation map or a braking capacity estimation function is stored in advance, with which the braking capacity can be estimated from the information acquired in S41 and S42, as in the first embodiment. As for the vehicle ahead, the state of the brake pads is not acquired, and the braking capability of the vehicle ahead is estimated without requiring the wear condition of the brake pads of the vehicle ahead for the brake capability estimation map or the brake capability estimation function. It is a map or function that can be used. This is because it is difficult to estimate the state of wear of the brake pads of the forward vehicle.

Also in the second embodiment, the braking ability of the preceding vehicle may have a distribution such as a normal distribution. In addition, unlike the own vehicle 1, the wear state of the brake pads is not taken into account. Therefore, when the braking ability of the preceding vehicle has a distribution, the distribution is wider than the distribution of the braking ability of the own vehicle 1. It may be a distribution.

[Summary of the second embodiment]
The braking ability of the own vehicle 1 changes depending on the characteristics of the brake influencing factors of the own vehicle 1 . In addition, the factors that affect the braking of the own vehicle 1 include those that change with time, such as tire wear, vehicle weight, and brake pad wear. Therefore, in the vehicle control device 200 of the second embodiment, the characteristic updating unit 113 sequentially updates the wear state of the tires, the vehicle weight, and the wear state of the brake pads of the host vehicle 1 . The braking capacity estimator 114 sequentially estimates the braking capacity of the vehicle 1 based on the wear condition of the tires of the vehicle 1, the vehicle weight, and the wear condition of the brake pads. Therefore, it is possible to estimate the braking ability of the host vehicle 1 with high accuracy.

Moreover, the braking ability of the own vehicle 1 also changes depending on the presence or absence of engine braking. Therefore, the braking capacity estimation unit 114 of the second embodiment also acquires whether or not the host vehicle 1 can perform engine braking. Then, when engine braking is possible, it is estimated that the braking capability is higher than when engine braking cannot be used. As described above, in the second embodiment, the braking ability is estimated in consideration of whether or not engine braking is possible, so the braking ability of the host vehicle 1 can be estimated with high accuracy.

In addition, in this embodiment, the wear condition of the tires of the vehicle ahead and the weight of the vehicle ahead, which are examples of the characteristics of the brake influence factor, are sequentially estimated, and the braking ability of the vehicle ahead is also determined by the wear of the tires of the vehicle ahead. It is estimated considering the state and the weight of the vehicle ahead. Then, the safe distance between the preceding vehicle and the preceding vehicle is sequentially determined from the braking ability of the preceding vehicle and the braking ability of the preceding vehicle, which are successively estimated in consideration of the characteristics of the braking influence factors of the own vehicle and the preceding vehicle. have decided. Therefore, the reliability of the safety distance is also improved.

<Third Embodiment>
FIG. 8 shows the configuration of a vehicle control device 300 according to the third embodiment. The vehicle control device 200 differs from the sensor integration section 110 of the first embodiment in the configuration of the sensor integration section 310 . The sensor integration unit 310 of the third embodiment includes the same road surface condition determination unit 112 as in the first embodiment and the characteristic update unit 113 as in the second embodiment.

Then, in the third embodiment, the process shown in FIG. 9 is executed instead of that shown in FIG. In S51, the friction coefficient μ between the road surface on which the vehicle 1 is traveling and the tires of the vehicle 1 and the friction coefficient μ between the road surface and the vehicle ahead are calculated. The processing of S51 is shown in detail in FIG. In S511, the road surface shape is acquired. In S512, the road surface inclination is acquired. In S513, the road surface wetness is acquired. These are successively updated by the road surface state determination unit 112 .

In S514, the wear condition of the tire is acquired. This is updated by the characteristic update unit 113 . Similar to FIG. 4, FIG. 9 calculates the braking capabilities of the own vehicle 1 and the preceding vehicle. Therefore, in S514, the tire wear state of the own vehicle 1 and the tire wear state of the preceding vehicle are acquired.

In S515, the coefficient of friction μ with respect to the road surface of the host vehicle 1 is calculated, and the coefficient of friction μ with respect to the road surface of the preceding vehicle is also calculated. Both the coefficient of friction μ with respect to the road surface of the own vehicle 1 and the coefficient of friction μ with respect to the road surface of the vehicle in front are the values obtained in steps S511 to S514, and the values obtained in steps S511 to S514, and are stored in advance to determine the coefficient of friction μ based on these values. It is calculated using a map or function provided.

Returning to FIG. In S52, the vehicle weight of the own vehicle 1 is obtained, and the vehicle weight of the preceding vehicle is estimated. The vehicle weight of the own vehicle 1 acquires the value updated by the characteristic updating unit 113 . The vehicle weight of the forward vehicle is estimated in the same manner as in S42 of the second embodiment.

In S53, the braking ability of the host vehicle 1 and the braking ability of the preceding vehicle are estimated. At the time when S53 is executed, the coefficient of friction μ, the vehicle weight, and the slope of the road surface are acquired for the host vehicle 1 and the preceding vehicle. The frictional force can be calculated from the coefficient of friction μ, the vehicle weight, and the slope of the road surface. Based on this frictional force, the braking capabilities of the host vehicle 1 and the preceding vehicle are estimated from a preset relationship between the frictional force and the braking capability. Further, a map or function is prepared in advance that can directly determine the braking ability of the own vehicle 1 and the preceding vehicle from the friction coefficient μ, vehicle weight, and road surface inclination without calculating the frictional force. may be used to estimate the braking capabilities of the own vehicle 1 and the preceding vehicle.

After estimating the braking ability of the host vehicle 1 and the braking ability of the preceding vehicle, S15 is executed to calculate the safe distance, as in the first embodiment.

[Summary of the third embodiment]
In this third embodiment, the coefficient of friction μ between the tires of the vehicle 1 and the road surface is determined. Note that the coefficient of friction μ is an example of the road surface condition. The braking ability of the own vehicle 1 is estimated based on this friction coefficient μ. The braking ability of the own vehicle 1 changes depending on the coefficient of friction μ between the tires of the own vehicle 1 and the road surface. Therefore, the braking ability of the vehicle 1 can be estimated with higher accuracy than when the coefficient of friction μ between the tires of the vehicle 1 and the road surface is not considered.

In addition, in this embodiment, the braking ability of the preceding vehicle is also estimated in consideration of the coefficient of friction μ. Then, the safe distance between the preceding vehicle and the own vehicle 1 is sequentially determined from the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle, which are respectively estimated in consideration of the coefficient of friction μ. Therefore, the reliability of the safety distance is also improved.

<Fourth Embodiment>
FIG. 11 shows processing executed by the sensor integration unit in the fourth embodiment. S61 to S63 are processes executed by the road surface state determination unit 112. FIG. S<b>64 and S<b>65 are executed by the braking ability estimating unit 114 and the other vehicle braking ability estimating unit 116 .

S61 is the same as S1 and acquires a camera image. S62 is the same as S2, and acquires the measured value by Lidar. At S63, the tilt angle and the road surface friction coefficient _μe are calculated from the camera images obtained at S61 and S62 and the measured values by the lidar. The tilt angle can be obtained, for example, from the measurement result of the road tilt by Lidar. The road surface friction coefficient μ _e is a value representing the friction coefficient of the road surface. The coefficient of friction is not determined by only one substance, and the coefficient of friction changes when different combinations of substances are in contact with each other. Here, the road surface friction coefficient μ _e is a value determined assuming that the other material in contact with the road surface is a preset standard tire.

The road friction coefficient μ _e is expressed as having a normal distribution. That is, Equation 1 expresses the road surface friction coefficient μ _e . In Equation 1, μ _e0 is the median of the normal distribution and σ _e ² is the variance of the normal distribution.

(Equation 1) μ _e =N (μ _e0 , σ _e ² )
The road surface friction coefficient μ _e is determined based on the uneven shape of the road surface determined from the camera image and measurement by Lidar. There is a correlation between the uneven shape of the road surface and the coefficient of friction. Therefore, the relationship between the uneven shape of the road surface and the road surface friction coefficient _μe is determined in advance. Based on this relationship and the uneven shape of the road surface determined from the camera image and Lidar measurement, the road surface friction coefficient μ _e is determined.

In S64, the vehicle weight of the own vehicle 1 is obtained and the vehicle weight of the preceding vehicle is estimated. The vehicle weight of the host vehicle 1 is successively updated by the characteristic updating unit 113 . The vehicle weight of the preceding vehicle is estimated in the same manner as in S42.

At S65, the brake capacity is estimated. The method of estimating the braking capacity here is substantially the same as in S53 in the third embodiment. The difference from S53 is that the road surface friction coefficient μe is used instead of the friction coefficient _μ used in S53. Also, since the road surface friction coefficient _μe is used instead of the friction coefficient μ, the map or function for determining the braking ability is different from that in S53. Others are the same as S53.

In the third embodiment, the braking capacity estimating section 114 and the other vehicle braking capacity estimating section 116 calculate the coefficient of friction μ based on the road surface shape, road surface inclination, etc. determined by the road surface state determining section 112 . On the other hand, in the fourth embodiment, 112 calculates the inclination angle and the road surface friction coefficient _μe . Despite this difference, the fourth embodiment also estimates the braking ability of the host vehicle 1 based on the road surface friction coefficient _μe , which is an example of the road surface condition. Therefore, it is possible to estimate the braking ability of the own vehicle 1 with high accuracy.

Further, since the braking ability of the preceding vehicle is also estimated based on the road surface friction coefficient μ _e , the braking ability of the preceding vehicle and the own vehicle 1 is determined based on the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle. It also improves the reliability of the safety distance between

<Fifth Embodiment>
In the fifth embodiment, the road surface condition determination unit 112 calculates the road surface shape by the processing shown in FIG. 12 . In S71, a suspension vibration signal is obtained. A vibration signal of the suspension can be detected by a vibration sensor attached to the suspension. In S72, a technique such as independent component analysis is applied to the signal acquired in S71 to extract a signal derived from the unevenness of the road surface. Then, the uneven shape of the road surface is determined from the signal derived from the unevenness of the road surface.

The methods described in the previous embodiments can be applied except for the calculation of the road surface shape. As in the fifth embodiment, the road surface shape may be indirectly calculated by detecting the vibration of the road surface transmitted to the own vehicle 1 using a sensor attached to the own vehicle 1 .

<Sixth embodiment>
In the sixth embodiment, the road surface state determination unit 112 calculates the road surface friction coefficient μ _e by the processing shown in FIG. 13 . In S81, a suspension vibration signal is obtained. This process is the same as S71. In S82, a method such as independent component analysis is applied to the signal acquired in S81 to extract a signal derived from the unevenness of the road surface. Furthermore, the uneven shape of the road surface is determined from the signal derived from the unevenness of the road surface. Based on the uneven shape of the road surface, the road surface friction coefficient _μe is calculated in the same manner as in S63.

The processing after calculating the road surface friction coefficient _μe is the same as in the fourth embodiment. As in the sixth embodiment, the road surface friction coefficient μ _e may be calculated based on the signal detected by the sensor attached to the own vehicle 1 .

<Seventh Embodiment>
In the seventh embodiment, the characteristic updating unit 113 sequentially executes the processing shown in FIG. 14 to sequentially update the tire state. The tire condition is a condition related to the tire and affects braking ability. Tire condition is therefore an example of a brake influencing factor. Specifically, as the tire condition, the tire friction coefficient _μW is calculated in the seventh embodiment.

In S91 in FIG. 14, road surface information is acquired. Specifically, the road surface information is the road surface friction coefficient μ _e described with reference to FIG. 11 . In S92, operation information is acquired. The operation information includes the amount of depression of the brake pedal by the driver of the own vehicle 1 or the amount of change in the brake hydraulic pressure that changes accordingly. The operation information also includes the speed of the vehicle 1 when the vehicle 1 starts to decelerate due to the driver's operation of the brake pedal.

In S93, if the driver of the vehicle 1 has stopped the vehicle 1 by operating the brake pedal in S92, the braking distance from the operation of the brake pedal to the stop of the vehicle 1 is acquired.

In S94, a tire friction coefficient _μW is calculated based on the road surface information, operation information, and braking distance acquired in S91, S92, and S93. The relationship between road surface information, operation information, braking distance, and tire friction coefficient _μW is determined in advance based on experiments and the like. The tire friction coefficient _μW is calculated based on this predetermined relationship, the road surface information, the operation information, and the braking distance obtained in S91, S92, and S93.

The coefficient of friction is determined by various factors, and cannot be uniquely determined only by road surface information, operation information, and braking distance. Therefore, like the road surface friction coefficient μ _e described in the fourth embodiment, the tire friction coefficient μ _W is also represented by Equation 2 assuming that it has a distribution, more specifically, a normal distribution. In Equation 2 ^, μ _W0 is the median of the normal distribution and σ _W2 is the variance of the normal distribution.

(Formula 2) μ _W =N (μ _W0 , σ _W ² )
In the seventh embodiment, the braking capacity estimating section 114 and the other vehicle braking capacity estimating section 116 calculate the braking capacity of the host vehicle 1 and the braking capacity of the preceding vehicle based on the friction coefficient μ calculated by executing FIG. to estimate The processing shown in FIG. 15 is processing executed in place of FIG.

In S101, the road surface friction coefficient _μe , which is the road surface information, is obtained from the road surface condition determination unit 112. FIG. The road surface state determination unit 112 calculates the road surface friction coefficient _μe by the processing described with reference to FIG. At S102, the tire friction coefficient _μW calculated at S94 is acquired. In S103, the coefficient of friction μ is calculated by Equation 3 based on the coefficient of road friction _μe obtained in S101 and the coefficient of tire friction _μW obtained in S102.

(Formula 3) μ = μ _e (μ _e + μ _W )
After calculating the coefficient of friction μ, the process proceeds to S52 in FIG. Thus, instead of the method of calculating μ described in the third embodiment, the road surface friction coefficient μ _e and the tire friction coefficient μ _W are calculated, and from these two friction coefficients, the friction coefficient μ between the road surface and the tire is calculated. can also be calculated.

<Eighth embodiment>
FIG. 16 shows processing executed by the characteristic updating unit 113 instead of FIG. 14 in the eighth embodiment. In S111, the tire temperature of the own vehicle 1 is acquired. The tire temperature is detected, for example, by a thermo camera installed at a position where the tire can be photographed. In S112, a tire friction coefficient _μW , which is an example of the tire condition, is calculated based on the tire temperature. If the tire temperature changes, the tire friction coefficient _μW changes. Therefore, the relationship between the tire temperature and the tire friction coefficient _μW is determined in advance, and the tire friction coefficient _μW is calculated based on the relationship and the tire temperature acquired in S111. The tire friction coefficient _μW determined in S112 also has a distribution. The tire temperature used in calculating the tire friction coefficient _μW is also an example of the tire condition.

<Ninth Embodiment>
FIG. 17 shows the processing executed by the road surface state determining section 112, the braking capacity estimating section 114, and the other vehicle braking capacity estimating section 116 in the ninth embodiment. S121 is a process executed by the road surface state determination unit 112 . In S121, the vehicle-to-vehicle communication is performed to acquire the inclination angle and the road surface friction coefficient _μe from the surrounding vehicle. In addition, in the ninth embodiment, the own vehicle 1 is provided with a wireless device that wirelessly communicates with surrounding vehicles.

When the surrounding vehicle is equipped with the vehicle control device and the wireless device described in the fourth embodiment, and the surrounding vehicle sequentially transmits the measured inclination angle and the road surface friction coefficient _μe , the own vehicle 1 From the vehicle, it is possible to obtain the inclination angle and the road surface friction coefficient μ _e .

At S122, the braking ability of the host vehicle 1 and the braking ability of the preceding vehicle are estimated based on the inclination angle and the road surface friction coefficient _μe obtained at S121. As in FIG. 4, the weight of own vehicle 1 and the weight of the preceding vehicle are obtained or estimated, and the weight of own vehicle 1 and the weight of the preceding vehicle are also taken into consideration, and the braking ability of own vehicle 1 and the braking of the preceding vehicle are determined. Ability may be estimated. However, the braking capacity of the vehicle 1 and the braking capacity of the vehicle ahead may be estimated without using the vehicle weights of the vehicle 1 and the vehicle ahead.

<Tenth Embodiment>
FIG. 18 shows processing executed instead of FIG. 4 in the tenth embodiment. The tenth embodiment is a combination of the embodiments described so far. In S131, the road surface condition is acquired. Various specific conditions described in the previous embodiments can be adopted as the road condition. Specifically, the road surface condition includes road surface inclination, road surface shape, road surface wetness, road surface friction coefficient _μe, and the like. The road surface condition acquired in S131 is one or more of the specific road surface conditions described above.

In S132, the brake influence factor of the own vehicle 1 and the brake influence factor of the preceding vehicle are acquired. One or more of the various specific brake influence factors described in the above embodiments can also be employed as the brake influence factor of the own vehicle 1 and the brake influence factor of the preceding vehicle acquired in S132.

At S133, the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle are estimated in consideration of both the road surface condition and the brake influence factors acquired at S131 and S132. Also in S133, in order to estimate the braking performance, a relationship that enables the estimation of the braking performance is obtained in advance based on the road surface state and the braking influence factor. Based on this relationship and the information obtained in S131 and S132, the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle are estimated.

In this tenth embodiment, both the road surface condition and the braking influence factor of the vehicle are taken into account to estimate the braking ability of the own vehicle 1 and the braking ability of the preceding vehicle. Therefore, it is possible to estimate the braking ability of the host vehicle 1 and the braking ability of the preceding vehicle with higher accuracy.

<Eleventh Embodiment>
FIG. 19 shows the processing executed by the braking capacity estimation unit 114 in the eleventh embodiment. In S141, the road surface condition is acquired. The road surface condition is information for estimating whether or not the vehicle 1 will slip when decelerating with full braking. For example, the road surface conditions are the road surface shape, the road surface inclination, and the road surface wetness described above. Further, the road surface condition may be the road surface friction coefficient μ _e .

In S142, the tire condition and the vehicle weight of the own vehicle 1 are acquired. As described above, the tire condition is a tire-related condition that affects the braking performance. Specifically, the tire condition is, for example, the tire friction coefficient μ _W , the tire temperature, and the like.

At S143, it is determined whether or not only the foot brake is sufficient. Whether or not only the footbrake is sufficient is determined by determining whether or not slipping occurs when the footbrake alone is applied and the vehicle is fully braked. Note that only the foot brake here means that the engine brake cannot be actively used. When the foot brake is applied, the accelerator is turned off, and if the engine is provided as a driving force source, engine braking is automatically applied when the accelerator is turned off. Actively using the engine brake means that the gear ratio is changed to a higher value during the foot brake to generate a greater braking force than the engine brake that automatically acts instead of the engine brake that acts automatically. To tell. If the skid does not occur even with only the foot brake and full braking, the determination result of S143 is YES.

In order to judge whether or not the vehicle slips only with the foot brake, the frictional force between the tire and the road surface generated by full braking is compared with the inertial force generated in the own vehicle 1 during deceleration. If the frictional force is larger, the own vehicle 1 will not slip. The frictional force is calculated from the coefficient of friction μ between the road surface and the tires and the vehicle weight. The coefficient of friction μ between the road surface and the tire is calculated by the processing shown in FIG. 10 or 15, for example. The inertial force generated in the host vehicle 1 during deceleration can be calculated by multiplying the deceleration set in advance as the deceleration during full braking by the vehicle weight.

If the determination result of S143 is Yes, the process proceeds to S144. At S144, the braking ability of only the foot brake is estimated. The braking ability with only the foot brake is the braking ability estimated in S35 when it is determined in S33 that the engine braking cannot be used in the processing shown in FIG.

If the determination result of S143 is No, the process proceeds to S145. In S145, the engine state is acquired. The engine state is information indicating whether or not the host vehicle 1 is equipped with an engine and is in a state in which the gear ratio can be increased.

At S146, it is determined whether or not engine braking can be used based on the information obtained at S145. If the judgment result of S146 is No, it will progress to S147. The processing of S147 is the same as that of S144. That is, in S147, the braking ability of only the foot brake is estimated.

If the judgment result of S146 is Yes, it will progress to S148. In S148, the braking capacity when using engine braking is estimated. The braking ability when the engine brake is used has, for example, a distribution of the braking ability, as explained in S35. When the engine brake is used, the braking ability is changed to the side where the braking ability is higher than when the engine braking cannot be used by a predetermined constant value of the center value of the distribution of the braking ability. In S149, the ECU controlling the transmission is notified that the engine brake will be used.

After estimating the braking ability of the own vehicle 1, S14 and S15 of FIG. 3 are performed, and a safe distance is calculated.

In the eleventh embodiment, the braking capability is estimated when the engine braking is used in addition to the foot braking. When the engine brake can be used, the braking distance of the own vehicle 1 can be shortened by using the engine brake.

<Twelfth Embodiment>
FIG. 20 shows processing executed by the other vehicle braking capability estimation unit 116 in the twelfth embodiment. In this embodiment, the own vehicle 1 is equipped with a radio for communicating with surrounding vehicles, and the vehicle control device can transmit and receive signals to and from the radio.

In S151, it is determined whether vehicle-to-vehicle communication with the preceding vehicle is possible. This determination is made based on whether or not the signal transmitted from the preceding vehicle has been received. If the judgment result of S151 is Yes, it will progress to S152.

In S152, vehicle-to-vehicle communication is performed with the vehicle in front, and the brake capability of the vehicle in front and the speed of the vehicle in front are received. If the preceding vehicle is equipped with a vehicle control device similar to the own vehicle 1, it is possible to receive not only the speed of the preceding vehicle but also the braking capability of the preceding vehicle from the preceding vehicle.

If the judgment result of S151 is No, it will progress to S153. In S153, the speed of the preceding vehicle is determined. This process is the same as that described in S11. In S154, the braking ability of the preceding vehicle is estimated. This process is the same as S14. It should be noted that S153 and S154 may be executed even when the vehicle-to-vehicle communication with the vehicle in front was possible, but the braking capability could not be received from the vehicle in front.

After the speed and braking capacity of the preceding vehicle are determined in this way, and the braking capacity estimating section 114 estimates the braking capacity of the own vehicle 1, the safe distance determining section 118 calculates the safe distance.

It can be expected that the braking ability of the preceding vehicle estimated by the preceding vehicle, which is received through inter-vehicle communication, is more accurate than the braking ability of the preceding vehicle estimated by the own vehicle 1 . Therefore, by using the braking ability of the forward vehicle estimated by the forward vehicle, the calculation accuracy of the safe distance is improved.

Although the embodiments have been described above, the disclosed technology is not limited to the above-described embodiments, and the following modifications are also included in the disclosed scope. Various modifications can be made.

<Modification 1>
The road surface friction coefficient _μe is a value that can be determined without considering the tire condition. Therefore, the road surface friction coefficient μ _e is stored in advance as map information, and based on the current position of the vehicle 1, the road surface friction coefficient μ _e of the road on which the vehicle 1 is traveling is obtained from the map information. good too.

<Modification 2>
In the ninth embodiment, the inclination angle and the road surface friction coefficient _μe are received from surrounding vehicles through inter-vehicle communication. However, the inclination angle and road surface friction coefficient μ _e may be received from the roadside unit. Further, the communication between own vehicle 1 and surrounding vehicles may be communication via a base station.

<Modification 3>
In the twelfth embodiment, the own vehicle 1 receives the braking ability of the preceding vehicle through inter-vehicle communication. However, the own vehicle 1 may receive the braking ability of the preceding vehicle by communication via a base station.

<Modification 4>
In the first embodiment, the braking ability is estimated based on the road surface shape, road surface inclination, and road surface wetness as road surface conditions. However, the braking ability may be estimated using any two of the road surface shape, the road surface slope, and the road surface wetness, or using only one of them.

<Modification 5>
The sensor integration unit 110, the route planning unit 120, the accident liability determination unit 130, and the travel unit 140 described in the present disclosure are control units, and the control unit and its method may be one or more embodied by a computer program. may be implemented by a special purpose computer comprising a processor programmed to perform the functions of Alternatively, the controller and techniques described in this disclosure may be implemented by dedicated hardware logic circuitry. Alternatively, the controller and techniques described in this disclosure may be implemented by one or more dedicated computers configured by a combination of a processor executing a computer program and one or more hardware logic circuits. Hardware logic circuits are, for example, ASICs and FPGAs.

Further, the storage medium for storing the computer program is not limited to the ROM, and may be stored in a computer-readable non-transition tangible storage medium as instructions executed by the computer. For example, the program may be stored in a flash memory.

1: Host Vehicle 100: Vehicle Control Device 101: Sensor 110: Sensor Integration Unit 111: Vehicle Identification Unit 112: Road Condition Determination Unit 113: Characteristics Update Unit 114: Brake Capacity Estimation Unit 116: Other Vehicle Brake Capacity Estimation Unit 118: Safety Distance determination unit 120: Route planning unit 130: Accident liability determination unit 131: Accident liability prediction unit 132: Route selection unit 133: Emergency stop selection unit 134: Emergency route planning unit 140: Travel unit 200: Vehicle control device 210: Sensor Integration Unit 300: Vehicle Control Device 310: Sensor Integration Unit

Claims (16)

A braking capacity estimating device mounted on a vehicle for estimating a braking capacity that is a capacity to stop the vehicle, the road on which the own vehicle (1), which is the vehicle on which the braking capacity estimating device is mounted, is traveling. a road surface condition determination unit (112) for successively determining the road surface condition of the vehicle; and a braking capability estimation unit (114) for successively estimating the braking capability of the host vehicle based on the road condition determined by the road surface condition determination unit and a braking capacity estimation device comprising
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the own vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle ,
The other-vehicle braking capacity estimating unit estimates the characteristics of a brake influence factor that is a factor that affects the braking capacity of the preceding vehicle, and estimates the characteristics of the brake influence factor of the preceding vehicle based on the estimated characteristics of the brake influence factor of the preceding vehicle. A safe distance determination device that sequentially estimates the braking ability of A braking capacity estimating device mounted on a vehicle for estimating a braking capacity that is a capacity to stop the vehicle, wherein the braking capacity is affected in a subject vehicle (1) that is a vehicle in which the braking capacity estimating device is mounted. a characteristic updating unit (113) for sequentially updating the characteristic of a factor that changes with time among the brake influencing factors that give a braking capacity estimating device comprising a braking capacity estimating unit (114) ;
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the own vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle ,
The other-vehicle braking capacity estimating unit estimates the characteristics of a brake influence factor that is a factor that affects the braking capacity of the preceding vehicle, and estimates the characteristics of the brake influence factor of the preceding vehicle based on the estimated characteristics of the brake influence factor of the preceding vehicle. A safe distance determination device that sequentially estimates the braking ability of A braking capacity estimating device mounted on a vehicle for estimating a braking capacity that is a capacity to stop the vehicle, the road on which the own vehicle (1), which is the vehicle on which the braking capacity estimating device is mounted, is traveling. a road surface condition determination unit (112) for successively determining the road surface condition of the vehicle; and a braking capability estimation unit (114) for successively estimating the braking capability of the host vehicle based on the road condition determined by the road surface condition determination unit and a braking capacity estimation device comprising
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the own vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle ,
When the braking capability of the forward vehicle can be received from the forward vehicle by wireless communication, the other vehicle braking capability estimating unit estimates the braking capability of the forward vehicle, instead of estimating the braking capability of the forward vehicle. A safe distance determination device that outputs a vehicle braking capability to the safe distance determination unit. A braking capacity estimating device mounted on a vehicle for estimating a braking capacity that is a capacity to stop the vehicle, wherein the braking capacity is affected in a subject vehicle (1) that is a vehicle in which the braking capacity estimating device is mounted. a characteristic updating unit (113) for sequentially updating the characteristic of a factor that changes with time among the brake influencing factors that give a braking capacity estimating device comprising a braking capacity estimating unit (114) ;
a non-vehicle braking capacity estimating unit (116) for estimating the braking capacity of a preceding vehicle traveling in front of the own vehicle;
A safe distance determination unit (118) that determines a safe distance between the own vehicle and the preceding vehicle based on the braking ability of the own vehicle and the braking ability of the preceding vehicle ,
When the braking capability of the forward vehicle can be received from the forward vehicle by wireless communication, the other vehicle braking capability estimating unit estimates the braking capability of the forward vehicle, instead of estimating the braking capability of the forward vehicle. A safe distance determination device that outputs a vehicle braking capability to the safe distance determination unit. The other vehicle braking capacity estimating unit sequentially estimates the braking capacity of the preceding vehicle based on information obtained by photographing the preceding vehicle with a camera provided in the vehicle when the braking capacity of the preceding vehicle cannot be received. A safe distance determination device according to claim 3 or 4. The other vehicle braking capacity estimating unit affects the braking capacity of the preceding vehicle based on information obtained by photographing the preceding vehicle with a camera provided in the vehicle when the braking capacity of the preceding vehicle cannot be received. 5. The safe distance determination device according to claim 3 or 4, wherein a characteristic of a brake influencing factor that is a factor is estimated, and the braking ability of the preceding vehicle is sequentially estimated based on the estimated characteristics of the brake influencing factor of the preceding vehicle. . The braking capacity estimation device includes a road surface condition determination unit (112) that determines the condition of the road surface on which the vehicle is traveling,
5. The safety system according to claim 2, wherein the braking capacity estimating section sequentially estimates the braking capacity of the own vehicle based on the road surface state determined by the road surface state determining section and the braking influence factor. distance determination device. 8. The safe distance determination device according to claim 1 , wherein said road surface condition determination unit determines one or more of road surface inclination, road surface shape, and road surface wetness as said road surface condition. 8. The safe distance determination device according to claim 1 , wherein said road surface condition determining unit determines a coefficient of friction of a road surface as said road surface condition. The characteristic updating unit sequentially updates the tire condition of the own vehicle as the characteristic of the brake influence factor,
The road surface condition determination unit determines a coefficient of friction between the road surface and tires of a vehicle traveling on the road based on one or both of road surface shape and road surface wetness and the tire condition. 8. A safety distance determination device according to claim 7 . 3. The braking capacity estimating unit estimates the braking capacity using at least one of tire wear, brake pad wear, vehicle weight, and presence or absence of engine braking as the brake influencing factors. , 4 or 7 . The braking capacity estimating unit estimates the braking capacity using whether or not the engine braking is possible. 12. A safe distance determination device according to claim 11 , which estimates that is high. A safe distance determination method for determining a safe distance between an own vehicle and a forward vehicle traveling in front of the own vehicle ,
sequentially determining the road surface condition of the road on which the vehicle is traveling based on the sensor values detected by the sensors mounted on the vehicle ;
sequentially estimating the braking capability of the own vehicle based on the determined road surface condition ;
estimating the characteristics of a brake influence factor, which is a factor that affects the braking ability of the vehicle ahead, and sequentially estimating the braking ability of the vehicle ahead based on the estimated characteristics of the brake influence factor of the vehicle ahead;
A safe distance determination method for determining the safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle . A safe distance determination method for determining a safe distance between an own vehicle and a forward vehicle traveling in front of the own vehicle ,
sequentially updating the characteristics of factors that change with time among the brake influence factors that affect the braking ability of the own vehicle;
successively estimating the braking capability of the own vehicle based on the characteristics of the braking influence factor ;
estimating the characteristics of a brake influence factor, which is a factor that affects the braking ability of the vehicle ahead, and sequentially estimating the braking ability of the vehicle ahead based on the estimated characteristics of the brake influence factor of the vehicle ahead;
A safe distance determination method for determining the safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle . A safe distance determination method for determining a safe distance between an own vehicle and a forward vehicle traveling in front of the own vehicle ,
sequentially determining the road surface condition of the road on which the vehicle is traveling based on the sensor values detected by the sensors mounted on the vehicle ;
sequentially estimating the braking capability of the own vehicle based on the determined road surface condition ;
estimating the braking capability of the forward vehicle;
determining the safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle;
When the braking ability of the vehicle in front can be received from the vehicle in front by wireless communication, instead of estimating the braking ability of the vehicle in front, the braking ability of the vehicle in front is received by wireless communication to determine a safe distance . Method. A safe distance determination method for determining a safe distance between an own vehicle and a forward vehicle traveling in front of the own vehicle ,
sequentially updating the characteristics of factors that change with time among the brake influence factors that affect the braking ability of the own vehicle;
successively estimating the braking capability of the own vehicle based on the characteristics of the braking influence factor ;
estimating the braking capability of the forward vehicle;
determining the safe distance based on the braking ability of the own vehicle and the braking ability of the preceding vehicle;
When the braking ability of the vehicle in front can be received from the vehicle in front by wireless communication, instead of estimating the braking ability of the vehicle in front, the braking ability of the vehicle in front is received by wireless communication to determine a safe distance . Method.

Images