Patent ID: 12241972

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

JP 2011-133965 A discloses a technique of enhancing safety during lane change, by issuing an alarm in accordance with a collision probability with a following vehicle during lane change. Specifically, in a case where the following vehicle is present, whether the driver of an own vehicle has an intention of changing lanes is determined. When it is determined that the driver has the intention of changing the lanes, the blinker is automatically set to ON and an alarm controlled by an alarm actuator is set to ON in order to inform the driver of the collision probability with the following vehicle.

In JP 2011-133965 A, whether the driver has the intention of changing the lanes is determined based on a steering state of the steering wheel, manipulated by the driver, that has been acquired from a steering angle sensor. Even when the steering wheel is manipulated, however, the driver does not always have the intention of changing the lanes. This might cause a problem that an alarm is issued, though the driver has no intention of changing the lanes. Such a problem is not limited to the lane change, and is common among course changes in general including making a turn and the like.

In consideration of the above circumstances, the present disclosure provides a measure to estimate the driver's intention of changing course appropriately, and in addition, to provide assistance in collision avoidance appropriately.

As illustrated inFIG.1, a vehicle10includes information output devices20, internal field sensors50, a collision avoidance assistance mechanism80, and an ECU90. The vehicle10is a four-wheel automobile.

The information output devices20include external field sensors30, a GNSS receiver41, a route guidance device42, a microphone43, and a communication device44. These components each have a function of outputting information generated by acquisition or calculation.

The external field sensors30acquire information for detecting an obstacle outside the vehicle, and output the acquired information. The external field sensors30, in the present embodiment, are constituted by a front radar31, two front lateral side radars32, two rear lateral side radars33, a front camera34, and a rear camera35. The front radar31is a millimeter-wave radar operating at a frequency of 77 GHz. The front lateral side radars32and the rear lateral side radars33are all millimeter-wave radars operating at a frequency of 24 GHz. The front camera34and the rear camera35are both monocular cameras. It is noted that the external field sensors30are not limited to these sensors.

As illustrated inFIG.2, the front radar31senses a range (e.g., a range of ±45 degrees) in which the front side of the vehicle10is set at the center. The front lateral side radars32respectively sense ranges (e.g., ranges of ±45 degrees) in which the front lateral sides of the vehicle10are set at the center. The front lateral sides of the vehicle10include one range in which 45-degree diagonal front right of the vehicle10is set at the center and the other range in which 45-degree diagonal front left of the vehicle10is set at the center. The rear lateral side radars33respectively sense ranges (e.g., ranges of ±45 degrees) in which the rear lateral sides of the vehicle10are set at the center. The rear lateral sides of the vehicle10include one range in which 45-degree diagonal rear right of the vehicle10is set at the center and the other range in which 45-degree diagonal rear left of the vehicle10is set at the center. The imaging range of the front camera34is a range in which the front side of the vehicle10is set at the center. The imaging range of the rear camera35is a range in which the rear side of the vehicle10is set at the center. It is noted that the sensing ranges of the radars and the imaging ranges of the cameras are not limited to the above ones.

The GNSS receiver41receives radio waves from plural navigation satellites. The route guidance device42displays the current location, and performs route guidance, by using information obtained from the radio waves that the GNSS receiver41has acquired.

The microphone43acquires voices inside the vehicle. The communication device44has a function of performing vehicle-to-vehicle communication, and has a function of performing road-to-vehicle communication.

The internal field sensors50are constituted by sensors for respectively sensing state quantities of the own vehicle. The internal field sensors50include, for example, a steering angle sensor51for detecting a steering angle of the vehicle10, a yaw rate sensor52for detecting a yaw rate of the vehicle10, and a blinker control device53. The blinker control device53causes the blinker of the vehicle10to flash or turn off. The blinker control device53is capable of outputting information on whether the blinker is flashing or not. Hence, in the present embodiment, the blinker control device53is included in the internal field sensors50.

The collision avoidance assistance mechanism80includes a brake device81and an alarm device82. The brake device81includes a foot brake and a brake ECU. The foot brake is a brake mechanism for braking in accordance with a stepped-on amount of the brake pedal. Even if the brake pedal is not depressed, the brake ECU causes the foot brake to work when the ECU90gives an instruction. The foot brake working in such a manner is referred to as automatic brake.

The alarm device82alarms the driver about a collision probability. The alarm issued by the alarm device82includes at least one of an alarm sound output, seatbelt fastening, and displaying on a head-up display.

The ECU90(computer) includes a processor91and a storage medium92. The storage medium92is, for example, a non-transitory tangible computer readable storage medium such as a semiconductor memory. The storage medium92stores a program for implementing a collision avoidance assistance process described later. The processor91executes the program stored in the storage medium92, and thus the ECU90performs the process for implementing a collision avoidance assistance method. Specifically, the ECU90acquires information from the information output devices20and the internal field sensors50, and controls the collision avoidance assistance mechanism80.

The collision avoidance assistance process illustrated inFIG.3is performed in a repeated manner by the ECU90at least while the vehicle10is traveling.

First, as S110, the ECU90recognizes a road structure in the traveling direction. The road structure denotes information indicating whether the road runs straight or is curved and to what extent the road is curved in a case where the road is curved.

The ECU90, in the present embodiment, performs S110by integrating an analysis result of an image captured by the front camera34with information input from the route guidance device42. The information input from the route guidance device42in S110includes information indicating the latitude and longitude of a current location and a curvature of the road in the traveling direction.

The analysis of the image captured by the front camera34is conducted for a white line defining a lane, a location of a preceding vehicle, and the like. Accordingly, the curvature of the road in the traveling direction is obtained as an analysis result. Since a straight road can be represented as zero curvature, the curvature of the road in the traveling direction can indicate the degree of a curve in a case where the road is curved and whether the road runs straight or is curved. In this manner, the use of the route guidance device42and the front camera34enables the recognition of the road structure with high accuracy.

In another embodiment, without using the image captured by the front camera34, the information input from the route guidance device42may be used for performing S110. In yet another embodiment, the ECU90may recognize the road structure only from the analysis of the image captured by the front camera34.

Next, proceeding to S120, the ECU90predicts a change in steering angle over time, when traveling along the road is assumed.

Next, proceeding to S130, the ECU90determines the magnitude of a probability that the own vehicle makes a course change, by using the predicted value of the steering angle obtained in S120and the information from the internal field sensors50. Hereinafter, the determination in S130is referred to as a first determination. The course change in the present embodiment denotes making a turn. Making a turn includes a U-turn, also. The ECU90determines the probability of making a turn with three stages of probability values including high, medium, and low, based on the steering angle, the yaw rate, and the flashing state of the blinker. The probability of making a turn in the present embodiment means likelihood that the driver intends to make a turn and is manipulating the steering wheel, the accelerator pedal, and the like.

As illustrated inFIG.4, in traveling along the curved road, the value indicated by the steering angle and the yaw rate is approximate to the predicted value of the steering angle. In such a case, in S130, the probability of making a turn is determined to be low.

As illustrated inFIG.5, in a case where the steering wheel is being manipulated to make a turn on a straight road, the steering angle and the yaw rate are greater than those in the case of traveling along the straight road. Hence, in S130, the probability of making a turn is determined to be high. When the right blinker is flashing or the left and right blinkers are flashing, the probability of making a turn tends to be determined to be higher. The left and right blinkers flash when a hazard lamp switch installed in the vehicle10is pushed.

Next, proceeding to S140, the ECU90determines the probability of the course change by using information related to a traveling situation. Hereinafter, the determination in S140is referred to as a second determination. The information related to the traveling situation is, for example, a guide route (planned route). Specifically, in a case where the vehicle has traveled on a different route from the guide route set by the route guidance device42, the probability of the course change is determined to be higher than that in the case where the vehicle is traveling along the guide route.

As illustrated inFIG.6, for example, in a case where a guide route N is a route of turning to the right at an intersection C1, it is assumed that the vehicle10has traveled straight through the intersection C1. In this case, if the vehicle10then enters an intersection C2and makes a turn there, the vehicle10can return to the intersection C1. Hence, there is a probability that the driver tries to make a turn at the intersection C2in order to return to the guide route N. On the assumption of such a situation, in the present embodiment, in the case where the vehicle has traveled on a different route from the guide route, the probability of the course change is determined to be higher.

The period during which the probability of the course change is determined to be high continues from the time immediately after the vehicle departs from the guide route to the time when the probability of making a turn in order to return to the guide route becomes lower. Whether the probability of making a turn in order to return to the guide route becomes lower is determined by using an elapsed time and a traveled distance after the vehicle departs from the guide route, a determination whether the vehicle is traveling in accordance with a guide route that has been newly retrieved, or the like.

Next, proceeding to S150, the ECU90decides (selects) an operation mode of collision avoidance assistance according to a combination of the probability values that have been determined in the above-described two methods. Specifically, as illustrated inFIG.7, the operation mode of the collision avoidance assistance is decided in accordance with a lower one of the probability values that have been determined in the above-described two methods. That is, in a case where either one of the probabilities that have been determined in the above-described two methods is low, the operation mode is set to weak. The weak operation mode is the mode of an initial setting.

In a case of a medium operation mode, automatic brake can work even at a probability that does not work in the weak operation mode, and in addition, an alarm is issued by the alarm device82at an earlier timing than the case of the weak operation mode. In a case of a strong operation mode, the automatic brake can work even at a probability that does not work in the medium operation mode, and in addition, the alarm is issued by the alarm device82at an earlier timing than the case of the medium operation mode.

Next, proceeding to S160, the ECU90determines whether the collision probability with an obstacle has been detected. The obstacle includes an automobile, a two-wheel vehicle, a pedestrian, and the like. The ECU90determines YES in S160, upon detection of the collision probability. Proceeding to S170, the ECU90assists in collision avoidance. Then, the process returns to S110. Upon not detecting the collision probability, the ECU determines NO in S160and the process returns to S110.

According to the present embodiment, the collision avoidance assistance can be carried out more appropriately than an embodiment in which only either one of the probability values determined in the two determination methods is used.

In the case of the situation illustrated inFIG.6, for example, at a timing immediately after the vehicle10passed through the intersection C1, the probability value in the second determination becomes high. At this timing, however, the vehicle10is traveling straight. Hence, the collision probability with a vehicle12, which is traveling in an adjacent lane, is not so high. Thus, at this timing, the weak operation mode is desirable. In the present embodiment, at the timing immediately after the vehicle passed through the intersection C1, the probability value in the first determination is low and the operation mode becomes weak, accordingly.

Subsequently, the driver turns the steering wheel to the right, the vehicle10starts turning to the right, and then the probability value in the first determination becomes medium. In the case illustrated inFIG.6, the probability value in the second determination is kept high, at least until the vehicle10enters the intersection C2. As a result, when the vehicle10starts turning to the right, the operation mode becomes medium. When the vehicle10further turns to the right, the probability value in the first determination becomes high. As a result, the operation mode becomes strong. In the case of a medium or strong operation mode, the probability of being capable of avoiding a collision with the vehicle12becomes higher than the case of the weak operation mode. To achieve such collision avoidance, the provision of the rear lateral side radar33is beneficial.

In the case of the situation illustrated inFIG.4, on the other hand, the probability of the course change is determined to be low in the first determination. For this reason, even if a vehicle11, which is traveling in an adjacent lane, is approaching the vehicle10, the operation mode is kept weak. Accordingly, implementation of strong collision avoidance assistance more than necessary can be prevented.

A second embodiment will be described. The description of the second embodiment will be given mainly for differences from the first embodiment. Unless otherwise specified, the configurations are the same as those of the first embodiment.

The ECU90, in the present embodiment, as the information used for the second determination in S140, voice information that has been acquired from the microphone43is used in addition to the information that has been acquired from the route guidance device42. The voice information is one type of the information related to the traveling situation.

To be specific, the ECU90analyzes the voice information that has been acquired from the microphone43, and determines whether a predefined word or phrase is included. The predefined word or phrase is, for example, “Make a turn here!”, “Make a U-turn!”, or the like, which is a word or phrase that means a request for the course change. The ECU90, upon determination that such a word or phrase is included, makes the probability value of the second determination higher in accordance with the meanings of the content, the loudness of the voice, or the like.

According to the present embodiment, the intention of the passenger on the vehicle10can be estimated in a more accurate manner.

A third embodiment will be described. The description of the third embodiment will be given mainly for differences from the first embodiment. Unless otherwise specified, the configurations are the same as those of the first embodiment.

The ECU90, in the present embodiment, in addition to the information that has been collected by the external field sensors30, at least any of information acquired by vehicle-to-vehicle communication and information acquired by road-to-vehicle communication is considered for determining the collision probability in S160.

The situation ofFIG.6will be described as an example. In the case of using the vehicle-to-vehicle communication, the ECU90determines the collision probability by communicating with the vehicle12. In the case of using the road-to-vehicle communication, the ECU90communicates with a road-side device installed in the intersection C2. This allows a probability of being capable of detecting a collision probability with an obstacle that cannot be detected by the external field sensors30. Examples of the above-described obstacle may include an oncoming vehicle that is traveling straight to pass through the intersection C2.

According to the present embodiment, the probability can be detected in a more accurate manner.

The ECU90corresponds to a collision avoidance assistance device, S130performed by the ECU90corresponds to a first determination section, S140performed by the ECU90corresponds to a second determination section, S150performed by the ECU90corresponds to a decision section, and S170performed by the ECU90corresponds to an assistance section. The weak operation mode corresponds to a first mode, the strong operation mode corresponds to a second mode, the low probability value corresponds to first and third probability values, and the high probability value corresponds to second and fourth probability values.

The present disclosure is not limited to the embodiments described herein, and is achievable with various configurations without departing from the spirit of the present disclosure. For example, the technical features in the embodiments corresponding to the technical features in the respective aspects described later can be replaced or combined appropriately, to solve a part or all of the above-described problems or to attain a part of or all of the advantageous effects described herein. Unless such technical features are described herein as essential ones, they can be deleted, as necessary. The following embodiments are given as examples.

In the second determination, in a case where the guide route includes making a turn, the probability of making a turn may be determined to be high, when a driver turns the steering wheel to make a turn in accordance with the guide route.

The course change is not limited to making a turn, and may include at least any of the lane change, turning to the left, and turning to the right. The course change may include at least any of the lane change, turning to the left, and turning to the right, without including making a turn.

The ECU90, by recording a location point where making a turn or the lane change was conducted in the past, may determine that the probability of the course change is high when the vehicle travels in the vicinity of such a location point. The location point where making a turn or the lane change was conducted in the past is one type of the information related to the traveling situation.

With the use of a traveling history of the own vehicle, the scene where the course change probability is high may be determined. The traveling history of the own vehicle is one type of the information related to the traveling situation. The traveling history denotes information indicating at which location point, how frequently the own vehicle traveled in the past. In a case of a road on which the own vehicle travels frequently, the probability of making the course change, such as making a turn, is estimated to be low. On the other hand, in a case of a road on which the own vehicle travels for the first time, the route is easily mistaken. The probability of a sudden course change, such as making a turn, is estimated to be higher.

In the second embodiment, without using the information that has been acquired from the route guidance device42, only the information that has been acquired from the microphone43may be used.

In the second embodiment, a device for carrying out the voice recognition may be additionally included. This device decides the probability value in the second determination, and inputs the probability value to the ECU90.

The external field sensors30may include at least one sensor. The sensors included in the external field sensors30are not limited to those that have been given as examples in the embodiments. For example, any frequency bandwidth of the radars may be applicable. A stereo camera, a LIDAR, an ultrasonic sensor, or the like may be used. LIDAR is an abbreviation of Light Detection And Ranging.

In a case where the operation mode is made stronger, the operation timing of the automatic brake or the alarm may be made earlier, and in addition, the operation degree may be stronger, or the operation period may be longer. For example, the braking force of the automatic brake may be stronger, the volume of an alarm sound may be increased, or the alarm sound may continue for a longer period of time.

The operation modes of the automatic brake and the alarm may not necessarily be changed in association with each other, and may be changed independently. For example, the operation mode of the alarm only may be changed.

The probability value determinations in the first and second determinations may take any stages. For example, two stages may be applicable.

The decision of the operation mode in accordance with a combination of the probability values of the first and second determinations is not limited to the example illustrated inFIG.7. For example, the probability value may be calculated by numerical values, and the operation mode may be decided in accordance with a sum or product of two probability values.

The collision avoidance assistance device may not necessarily be the ECU90. The collision avoidance assistance device may be constituted by, for example, plural ECUs in cooperation with each other. Alternatively, the collision avoidance assistance device may be a computer incorporated into any of the components of the external field sensors30. For example, the collision avoidance assistance device may be a camera ECU incorporated into either one of the front camera34or the rear camera35, or may be a computer incorporated into the rear lateral side radar33.

In the above-described embodiments, a part or all of the functions and processes implemented by software may be implemented by hardware. Further, a part or all of the functions and processes implemented by hardware may be implemented by software. As hardware, for example, various circuits may be used, such as an integrated circuit, a discrete circuit, or a circuit module in combination of those circuits.

An aspect of the present disclosure is a collision avoidance assistance device (90) of a vehicle (10). The vehicle includes: information output devices (20) that output information for detecting an obstacle, information for recognizing a road structure in a traveling direction, and information related to a traveling situation of the vehicle; internal field sensors (50) that detect a state quantity of the vehicle; and a collision avoidance assistance mechanism (80) for assisting in avoidance of a collision with the obstacle. The collision avoidance assistance device includes: a first determination section (S110, S120, S130) that determines a probability that the vehicle changes course, by using a recognition result of the road structure by the information output devices and a detection result by the internal field sensors; a second determination section (S140) that determines the probability that the vehicle changes course, by using the information related to the traveling situation output by the information output devices; a decision section (S150) that decides (selects) an operation mode of collision avoidance assistance using the collision avoidance assistance mechanism, by using a combination of a determination result of the first determination section and a determination result of the second determination section; and an assistance section (S170) that performs a process for controlling the collision avoidance assistance mechanism in the operation mode that has been decided (selected) by the decision section, upon detection of a collision probability with the obstacle using the information output by the information output devices (S160, YES).

According to this aspect, with the use of the information for recognizing the road structure in the traveling direction and the information related to the traveling situation of the vehicle, the driver's intention of changing course can be estimated appropriately. In addition, the operation mode of the collision avoidance can be decided (selected) in accordance with an estimated result of the driver's intention. Therefore, the collision avoidance can be assisted appropriately.