Patent Application
20240101127
The present invention relates to a driving assistance device, a driving assistance method, and a driving assistance program.
Conventionally, there has been known a technique to predict the collapse of cargo loaded on a cargo bed of a traveling vehicle by acquiring information such as acceleration of the vehicle (for example, see Patent Document 1).
However, in the conventional technique described above, there is room for further improvement in reducing the cargo collapse on the vehicle since there is room for improvement in a prediction accuracy of cargo collapse.
The present invention has been made in view of the above, and an object thereof is to provide a driving assistance device, a driving assistance method, and a driving assistance program capable of reducing the cargo collapse, for example.
The driving assistance device according to claim 1 includes an acquisition means and a presentation means. The presentation means acquires travel information including acceleration of a moving body. The presentation means presents, to a driver, information regarding cargo collapse on the moving body specified on the basis of a distribution of the acceleration of the moving body in multiple axes on the basis of the travel information acquired by the acquisition means.
Further, the driving assistance method according to claim 10 is a driving assistance method to be executed by the driving assistance device, the driving assistance method acquiring travel information including acceleration of a moving body, and presenting, to a driver, information regarding cargo collapse on the moving body specified on the basis of a distribution of the acceleration of the moving body in multiple axes on the basis of the acquired travel information.
Further, the driving assistance program according to claim 11 acquires travel information including acceleration of a moving body, and causes a computer to execute a process to present, to a driver, information regarding cargo collapse on the moving body specified on the basis of a distribution of the acceleration of the moving body in multiple axes on the basis of the acquired travel information.
With reference to the drawings, the following describes embodiments for carrying out the present invention (hereinafter referred to as embodiment). The present invention is not limited to the embodiments described below. Further, the same numbers and signs are assigned to identical parts in the drawings.
First, a configuration of a control system 1 according to the embodiment 1 will be described with reference to
The server 2 controls the plurality of vehicles 3 as a control network. Each of the plurality of vehicles 3 includes a corresponding control device 4. These server 2 and the plurality of vehicles 3 are connected to each other via a network (for example, Internet) N by, for example, a wireless Local Area Network (LAN) communication, or a Wide Area Network (WAN) communication, and a mobile phone communication or the like, and communication of various information is possible therebetween.
Next, a configuration of the server 2 according to the embodiment 1 will be described with reference to
Note that, the server 2 may include an input unit (for example, keyboard or mouse or the like) that accepts various operations from a manager or the like who uses the server 2, and a display unit (for example, liquid crystal display or the like) to display the various kinds of information.
The communication unit 11 is implemented by, for example, a Network Interface Card (NIC) or the like. The communication unit 11 is connected to the network N in a wired or wireless manner, and further performs transmission and reception of information between the communication unit 11 and the plurality of vehicles 3.
The storage unit 12 is implemented by, for example, a semiconductor memory element such as a Random Access Memory (RAM), a Flash Memory, or the like, or a storage device such as a hard disk, an optical disk, or the like. As shown in
The road information storage unit 12a stores road position information that indicates a position of the road, such as map information. The road surface information storage unit 12b stores therein information regarding a road surface condition of the road (hereinafter also referred to as “road surface information”). The road surface information storage unit 12b stores therein, for example, information regarding a position of a road surface at which a road-surface roughness exists, and information regarding details of the road-surface roughness (for example, shape or the like) that is associated with information regarding the position of the road surface. The cargo collapse information storage unit 12c stores therein information regarding cargo collapse on the vehicle 3 (hereinafter also referred to as cargo collapse information). The cargo collapse information storage unit 12c sores therein, for example, information regarding a position at which a degree of an influence given to the cargo collapse is large, and information regarding a degree of an influence given to the cargo collapse that is associated with information regarding the position of the large influence.
The control unit 13 may be a controller to be realized in a case where various programs stored in the storage device inside the server 2 are executed by, for example, a Central Processing Unit (CPU) or a Micro Processing Unit) MPU), having the RAM as a working area. Further, the control unit 13 may be, for example, a controller to be realized by an integrated circuit such as an Application Specific Integrated Circuit (ASIC) or a Field Programmable Gate Array (FPGA), or the like.
As shown in
The acquisition means 13a acquires the road surface information that is estimated by the control device 4 of the vehicle 3 and transmitted from the control device 4, and stores the road surface information in the road surface information storage unit 12b. Further, the acquisition means 13a acquires the cargo collapse information that is identified by the control device 4 of the vehicle 3 and transmitted from the control device 4, and stores the cargo collapse information in the cargo collapse information storage unit 12c.
The transmission means 13b transmits the road surface information stored in the road surface information storage unit 12b and the cargo collapse information stored in the cargo collapse information storage unit 12c on the basis of a command from the control device 4 of the vehicle 3.
Next, details of a configuration of the vehicle 3 and a road surface condition estimation process to be implemented in the vehicle 3 according to the embodiment 1 are explained with reference to
As shown in
The three axes acceleration sensor 5 is a sensor to detect acceleration in respective directions in, for example, the X axis (for example, front-back direction of vehicle 3), the Y axis (for example, lateral direction of vehicle 3), and the Z axis (for example, vertical direction of vehicle 3), and supplies a detected signal thereof to the control device 4. Note that the three axes acceleration sensor 5 may further detect angular velocity, angular acceleration and the like of an operation of the vehicle 3.
The GPS sensor 6 receives radio waves carrying downlink data including measurement data, and supplies the measurement data to control device 4. The control device 4 is capable of detecting an absolute position of the vehicle 3 from positional information included in the measurement data (for example, latitude and longitude).
The speed sensor 7 is, for example, the sensor to detect speed of the vehicle 3, and supplies a detected signal thereof to the control device 4. The display unit 8 is provided in, for example, an instrumental panel of the vehicle 3, and includes a liquid crystal display, an organic Electro Luminescence (EL) element, and the like.
The control device 4 includes a communication unit 21, a storage unit 22, and a control unit 23. The communication unit 21 is implemented by, for example, the NIC or the like. The communication unit 21 is connected to the network N in a wired or wireless manner, and further performs the transmission and reception of information between the communication unit 21 and the server 2 via the network N.
The storage unit 22 is implemented by, for example, the semiconductor memory element such as the RAM, the Flash Memory, or the like, or the storage device such as the hard disk, the optical disk, or the like.
The control unit 23 may be a controller to be realized in a case where the various programs stored in the storage device inside the control device 4 are executed by, for example, the CPU or the MPU, having the RAM as the working area. Further, the control unit 23 may be, for example, a controller to be realized by the integrated circuit such as the ASIC or the FPGA or the like.
As shown in
In addition, as the travel information, the acquisition means 23a acquires, for example, positional information of the vehicle 3 from the GPS sensor 6, and acquires speed information of the vehicle 3 from the speed sensor 7. The generation means 23b generates an acceleration value distribution map that is a drawing in which a distribution of the acceleration in three axes in predetermined unit time is plotted in a three-dimensional coordinate system by using information regarding the acceleration of vehicle 3 in the front-back direction, the lateral direction, and the vertical direction acquired by the acquisition means 23a. Details of the acceleration value distribution map will be explained below.
In addition, in a case where the vehicle 3 is stopped with its engine idling, the plot range of the acceleration value distribution map becomes a plot range D2 in a spherical shape which is broader than the above-mentioned plot range D1 setting the origin of the three-dimensional coordinate system as the center.
Further, in a case where the vehicle 3 is traveling on a plane road surface, the plot range of the acceleration value distribution map becomes a plot range D3 in the spherical shape which is broader than the above-mentioned plot range D2 setting the origin of the three-dimensional coordinate system as the center. Note that, in
Next, the road surface condition estimation process using the acceleration value distribution map will be explained.
In this case, since a right front wheel FR and a right rear wheel RR of the vehicle 3 do not pass the road surface deterioration section X while a left front wheel FL and a left rear wheel RL of the vehicle 3 pass the road surface deterioration section X in this order, the vehicle 3 is swayed in the front-back direction, and further is swayed more greatly in the left direction than in the right direction.
Then, in a unit time of passing through the road surface deterioration section X, the generation means 23b generates the acceleration value distribution map as shown in
In the unit time of passing through the road surface deterioration section X is, as shown in
Returning to description of
The vibration information measured by the measurement means 23c may be, for example, an absolute value |A| of a size in the front-back direction in the acceleration value distribution map of the plot range D4 shown in
Further, the vibration information measured by the measurement means 23c may be, for example, an absolute value |B/C| of a ratio of a size B in the lateral direction in the acceleration value distribution map of the plot range D4 to a size C that spreads wider in the horizontal direction (left direction in drawing) with the origin set as reference.
Further, the vibration information measured by the measurement means 23c may be, for example, an absolute value |D| that is a size in the vertical direction in the acceleration value distribution map of the plot range D4.
Returning to the description of
For example, the estimation means 23d estimates that the larger is a value of the above-mentioned absolute value |A| measured by the measurement means 23c, the larger is a degree of deterioration (for example, roughness and the like) of the road surface deterioration section X.
In addition, the estimation means 23d estimates that, for example, the larger a value of the above-mentioned absolute value |B| measured by the measurement means 23c is, the larger the degree of deterioration (for example, roughness and the like) of the road surface deterioration section X is.
Further, the estimation means 23d estimates that, for example, the larger is a value of the above-mentioned absolute value |B/C| measured by the measurement means 23c, the more progresses a partial deterioration of the road surface deterioration section X. Further, the estimation means 23d is capable of estimating, for example, a horizontal position of the road surface deterioration section X (relative position in lateral direction of the road surface deterioration section X with respect to the vehicle 3) on the basis of the above-mentioned value of the absolute value |B/C| measured by the measurement means 23c.
Further, in a case where a value of a fluctuation of the above-mentioned absolute value |D| measured by the measurement means 23c is large, the estimation means 23d is capable of estimating that contribution of the degree of deterioration of the road surface deterioration section X to the value of the absolute value |B/C| is more largely affected by the partial deterioration than by the horizontal position of the road surface deterioration section X.
As described up to here, in the embodiment 1, the vibration information on the vehicle 3 is measured on the basis of the distribution of the acceleration of the vehicle 3 in the multiple axes (for example, acceleration value distribution map), and the road surface condition is estimated on the basis of the vibration information on the vehicle 3. Accordingly, it is possible to accurately estimate the road surface condition.
In addition, in the embodiment 1, the estimation means 23d may estimate the road surface condition on the basis of a size of the vibration of the vehicle 3 (for example, absolute value |A|, absolute value |B|, and absolute value |D|, and a deviation of a vibration position of the vehicle 3 (for example, absolute value |B/C|), as well as a temporal length of the vibration.
Thus, it is possible to further accurately estimate the road surface condition by estimating the degree of deterioration of the road surface deterioration section X with various parameters.
Further, in the embodiment 1, the measurement means 23c may measure the size of the vibration of the vehicle 3 and a deviation of the vibration position of the vehicle 3 on the basis of a shape of the acceleration value distribution map generated by the generation means 23b.
Accordingly, it is possible to accurately measure the size of the vibration of the vehicle 3 and the deviation of the vibration position of the vehicle 3. Therefore, according to the embodiment 1, it is possible to further accurately estimate the road surface condition.
In addition, in the embodiment 1, the estimation means 23d may estimate undulations of a road surface on the basis of the size of the vibration of the vehicle 3, and estimate a horizontal position of a point at which the road surface condition is damaged in a traveling lane on the basis of the deviation of the vibration position of the vehicle 3.
Accordingly, it is possible to estimate the degree of deterioration of the road surface deterioration section X by the various parameters, and estimate the horizontal position of the road surface deterioration section X. Therefore, according to the embodiment 1, it is possible to further accurately estimate the road surface condition.
In addition, in the embodiment 1, the estimation means 23d may directly estimate the road surface condition on the basis of the shape of the acceleration value distribution map generated by the generation means 23b. For example, the estimation means 23d is capable of estimating whether there is a bump on the road surface or whether there is a crack on the road surface on the basis of the shape of the acceleration value distribution map. Therefore, according to the embodiment 1, it is possible to further accurately estimate the road surface condition.
Further, in the embodiment 1, the acquisition means 23a may acquire the travel information from a three axes acceleration sensor 5 located inside the vehicle 3. Thus, since the acceleration value distribution map of the vehicle 3 can be easily generated, it is possible to estimate the road surface condition at a lower cost.
Note that, the three axes acceleration sensor 5 is not limited to a case of being mounted in the vehicle 3, but may be a three axes acceleration sensor mounted in, for example, an information terminal such as a smartphone or the like that is placed in the vehicle 3.
In addition, in the present disclosure, the number of three axes acceleration sensors 5 that measure the acceleration of the vehicle 3 is not limited to one, and may be plural.
Accordingly, since it is possible to accurately measure the acceleration of the vehicle 3, it is possible to further accurately estimate the road surface condition.
Returning to the description of
Accordingly, since information regarding a place where the road surface condition is poor is stored in the road surface information storage unit 12b of the server 2, the information regarding the place where the road surface condition is poor can be utilized in the plurality of vehicles 3 that are connected to the network N. An example of utilization of the road surface condition will be described later. In addition, in the embodiment 1, the shape or the size of the generated acceleration value distribution map may vary depending on the speed of the vehicle 3, a vehicle type of the vehicle 3, and a type of tires mounted in the vehicle 3 and the like.
Then, in the embodiment 1, the road surface condition may be estimated on the basis of information such as the speed of the vehicle 3, the vehicle type of the vehicle 3, and the type of tires mounted in the vehicle 3 and the like when passing the road surface deterioration section X in addition to the various vibration information described above.
For example, the vehicle 3 may travel on a road surface whose shape of roughness is preliminarily known so as to execute a calibration process on each of the vehicles 3.
Further, the server 2 or the control device 4 generates a learning model having the acceleration value distribution map as input information and the degree of deterioration of the road surface as output information on the basis of a set of acceleration value distribution maps of one of the vehicle 3. Then, the estimation means 23d may estimate the degree of deterioration of the road surface by using the learning model in every generation of the acceleration value distribution map.
Further, the server 2 generates a learning model having the acceleration value distribution map as input information and the degree of deterioration of the road surface as output information on the basis of a set of acceleration value distribution maps of a plurality of the vehicles 3 connected to the network N. Then, the estimation means 23d may estimate the degree of deterioration of the road surface by using the learning model in every generation of the acceleration value distribution map.
Further, in the embodiment 1, the estimation means 23d may generate the acceleration value distribution map per unit time throughout the entire travelling time during traveling, or may generate the acceleration value distribution map from a point of time when the three axes acceleration sensor 5 detects particular acceleration.
Next, details of a driving assistance process according to the embodiment 1 will be explained with reference to
The acquisition means 23a of the control unit 23 shown in
Further, as the travel information, the acquisition means 23a acquires, for example, the positional information of the vehicle 3 from the GPS sensor 6, and acquires the speed information of the vehicle 3 from the speed sensor 7.
The generation means 23b generates an acceleration value distribution map in which the distribution of the acceleration in the three axes in the predetermined unit time is plotted in the three-dimensional coordinate system by using the information regarding the acceleration of the vehicle 3 in the front-back direction, the lateral direction, and the vertical direction acquired by the acquisition means 23a.
The measurement means 23c measures the vibration information on the vehicle 3 on the basis of the distribution of the acceleration of the vehicle 3 in the multiple axes (for example, acceleration value distribution map generated by generation means 23b).
The measurement means 23c measures, for example, the size of the vibration of the vehicle 3 (for example, absolute value |A|, absolute value |B|, and absolute value |D|), and the deviation of the vibration position of the vehicle 3 (for example, absolute value |B/C|) as well as the road surface condition estimation process described above.
The specification means 23g specifies the information regarding the cargo collapse on the vehicle 3 (that is, cargo collapse information) on the basis of various information. The cargo collapse information may include, for example, a probability that the cargo collapse occurs, or a degree of the cargo collapse occurred.
Note that, in a following explanation, the probability that the cargo collapse occurs, and the degree of the cargo collapse occurred included in the cargo collapse information are comprehensively referred to as “degree of influence given to cargo collapse”. The specification means 23g may specify the cargo collapse information of the vehicle 3 by using, for example, the vibration information of the vehicle 3 measured by the measurement means 23c.
For example, the specification means 23g may specify that the larger is the value of the absolute value |A| (see
Note that the specification means 23g may provide a dead zone with respect to the vibration in the vehicle 3 in the front-back direction. Accordingly, it is possible to accurately specify the degree of the influence given to the cargo collapse.
Further, the specification means 23g may specify that, for example, the larger is the value of the absolute value |B| (see
Further, the specification means 23g may specify the cargo collapse information of the vehicle 3 using information that is different from the vibration information measured by the measurement means 23c.
Specifically, in
In this case, the extraction means 23f of the control unit 23 extracts, for example, information regarding a lateral direction component of the acceleration of the vehicle 3 from transition of acceleration of the vehicle 3 in the three axes. For example, the extraction means 23f extracts a value of an absolute value |E| of a size of a horizontal direction component in each plot (for example, plot P5) shown in
Then, the specification means 23g specifies that the larger is the value of the absolute value |E| of the size of the horizontal direction component, the larger is the degree of the influence given to the cargo collapse.
Further, the extraction means 23f may extract a value in which a distance between the plot P5 and the origin is taken into account in the absolute value |E| of the size of the horizontal direction component in each plot (for example, plot P5) shown in
Then, the specification means 23g specifies that the larger is the value of the absolute value |E| of the size of the horizontal direction component in which the distance between the plot P5 and the origin is taken into account, the larger is the degree of the influence given to the cargo collapse.
Further, the extraction means 23f may extract, for example, a value of an absolute value |F| of a deviation in each plot shown in
Then, the specification means 23g specifies that the larger is the value of the absolute value |F| of the deviation, the larger is the degree of the influence given to the cargo collapse. Further, in the embodiment 1, an acceleration value distribution map in one trip of the vehicle 3 may be generated, and the degree of the influence given to the cargo collapse may be specified on the basis of the acceleration value distribution map generated in the one trip.
The acceleration value distribution map (plot range D5) in the one trip of the vehicle 3 shown in
Then, the specification means 23g specifies that the larger is the degree of distortion of the acceleration value distribution map in the one trip, the larger is the degree of the influence given to the cargo collapse. In addition, in the embodiment 1, a moment to be added to a cargo loaded in the vehicle 3 may be extracted from the travel information of the vehicle 3 acquired by the acquisition means 23a, and the degree of the influence given to the cargo collapse may be specified on the basis of the moment to be added to the cargo.
In the example of
In this case, the extraction means 23f can extract a moment M to be added to the cargo based on a following equation (1).
M∝F
C
×L (1)
Then, the specification means 23g specifies that the larger is a value of the moment M to be added to the cargo (in a case where L is large, that is, a difference between the initial values of the gravity center is large, and/or in a case where a centrifugal force of F is large, that is, speed is high or traveling on a sharp curve), the larger is the degree of the influence given to the cargo collapse. Note that the position of the gravity center G of the cargo can be calculated by acceleration, angular velocity, or angular acceleration or the like detected by the three axes acceleration sensor 5.
Returning to the description of
Further, in the embodiment 1, out of various elements described above (for example, absolute value |A|, absolute value |B|, absolute value |B/C|, absolute value |E|, absolute value |E|, and moment M), an element in which the degree of the influence given to the cargo collapse is large may be individually presented to the driver.
Further, in the embodiment 1, the above-mentioned various elements (for example, absolute value |A|, absolute value |B|, absolute value |B/C|, absolute value |E|, absolute value |E|, and moment M) may be comprehensively taken into account in the magnitude of the degree of the influence to present the magnitude of the degree of the influence to the driver.
Further, in the embodiment 1, information on a point at which the degree of the influence given to the cargo collapse is large may be accumulated in the server 2. For example, the storing means 23e associates the positional information of the vehicle 3 acquired by the acquisition means 23a with the cargo collapse information specified by the specification means 23g, and stores the positional information and the cargo collapse information in the cargo collapse information storage unit 12c of the server 2.
Accordingly, since information regarding a place where the cargo collapse may easily occur is stored in the cargo collapse information storage unit 12c of the server 2, the information regarding the place where the cargo collapse may easily occur can be utilized in a plurality of vehicles 3 connected to the network N.
For example, the control device 4 may present a guide of a route on which the vehicle 3 plans to travel to the driver on the basis of information stored in the road surface information storage unit 12b and the cargo collapse information storage unit 12c of the server 2.
Specifically, the control device 4 may present, to the driver, the guide of a route to avoid, for example, a place where the road surface condition is poor which is stored in the road surface information storage unit 12b, and a place where the cargo collapse may easily occur which is stored in the cargo collapse information storage unit 12c (for example, a place where a degree of the influence given to cargo collapse is larger than a predetermined threshold).
Accordingly, it is possible to prevent the vehicle 3 from entering the place where the road surface condition is poor (for example, place where large irregularities are generated on the road surface or the like) or the place where the cargo collapse easily occurs (for example, curve having small curvature or the like) beforehand. Therefore, according to the embodiment 1, it is possible to effectively reduce the cargo collapse on the vehicle 3. In addition, in a case where the degree of the influence given to the cargo collapse becomes larger than a predetermined threshold while traveling on a road surface regarding which the road surface condition thereof is known to be good in advance, the control device 4 estimates that an increase in the degree of the influence results not from the road surface condition but from a way the driver drives by referring to the road surface information storage unit 12b.
Then, in this case, the presentation means 23h may present (advise), to the driver, a driving method for reducing the degree of the influence given to the cargo collapse. For example, in a case where the degree of distortion of the acceleration value distribution map in the one trip shown in
Accordingly, the control device 4 is capable of reducing the driving that may easily cause the cargo collapse. Therefore, according to the embodiment 1, it is possible to reduce the cargo collapse on the vehicle 3.
In addition, in the embodiment 1, in a case where the position of the gravity center G of the cargo is gradually moving, a guidance may be presented to the driver. In addition, in a case where it is assumed that balance of the cargo is significantly lost, the presentation means 23h may present the driver an advice to temporarily stop the vehicle 3 so as to check the cargo.
Next, a configuration of a vehicle 3A according to the embodiment 2 will be explained with reference to
As shown in
The three axes acceleration sensor 5 is, for example, a sensor that detects acceleration in each direction of the X axis, the Y axis, and the Z axis so as to supply a detected signal thereof to the control device 4A. Note that the three axes acceleration sensor 5 may further detect angular velocity and angular acceleration of an operation of the vehicle 3A.
The GPS sensor 6 receives radio waves carrying downlink data including measurement data from a plurality of GPS satellites and supplies the measurement data to control device 4A. The control device 4A is capable of detecting an absolute position of the vehicle 3A from positional information (for example, latitude and longitude) included in the measurement.
The speed sensor 7 is, for example, a sensor to detect speed of the vehicle 3A, and supplies a detected signal thereof to the control device 4A. The display unit 8 is provided to, for example, an instrumental panel of the vehicle 3A, and further includes a liquid crystal display, an organic EL element, and the like.
As shown in
The road information storage unit 31a stores therein road position information indicating a position of a road, for example, map information. The road surface information storage unit 31b stores therein road surface information of the road. The cargo collapse information storage unit 31c stores therein the cargo collapse information.
Note that since the road information storage unit 31a, the road surface information storage unit 31b, and the cargo collapse information storage unit 31c have configurations that are respectively similar to those of a road information storage unit 12a, a road surface information storage unit 12b, and a cargo collapse information storage unit 12c of the embodiment 1 shown in
The control unit 32 may be a controller to be realized in a case where various programs stored in the storage device inside the control device 4A are executed by, for example, a CPU or an MPU or the like, having the RAM as a working area. Further, the control unit 32 may be, for example, a controller to be realized by an integrated circuit such as an ASIC or an FPGA, or the like.
As shown in
The acquisition means 32a acquires travel information of the vehicle 3A. As the travel information, the acquisition means 32a acquires information regarding acceleration of the vehicle 3A in the front-back direction, the lateral direction, and the vertical direction from, for example, the three axes acceleration sensor 5.
In addition, as the travel information, the acquisition means 32a acquires positional information of the vehicle 3A from the GPS sensor 6, and acquires speed information of the vehicle 3A from the speed sensor 7.
The generation means 32b generates an acceleration value distribution map in which a distribution of the acceleration in three axes in predetermined unit time is plotted in a three-dimensional coordinate system by using information regarding the acceleration of the vehicle 3A in the front-back direction, the lateral direction, and the vertical direction acquired by the acquisition means 32a.
The measurement means 32c measures vibration information on the vehicle 3A on the basis of a distribution of the acceleration of the vehicle 3A in multiple axes (for example, acceleration value distribution map generated by generation means 32b). The estimation means 32d estimates a road surface condition of a road surface on which the vehicle 3A traveled on the basis of the vibration information measured by the measurement means 32c.
The storing means 32e associates the positional information of the vehicle 3A acquired by the acquisition means 32a with the road surface condition estimated by the estimation means 32d, and further stores the associated positional information and the road surface condition in the road surface information storage unit 31b of the storage unit 31.
Note that, since the acquisition means 32a, the generation means 32b, the measurement means 32c, the estimation means 32d, and the storing means 32e have configurations that are respectively similar to those of an acquisition means 23a, a generation means 23b, a measurement means 23c, an estimation means 23d, and a storing means 23e of the embodiment 1 shown in
Thus, in the embodiment 2, as is the case with the embodiment 1 described above, the vibration information of the vehicle 3A is measured on the basis of the distribution of the acceleration of the vehicle 3A in the multiple axes (for example, acceleration value distribution map), and the road surface condition is estimated on the basis of the vibration information of the vehicle 3A. Accordingly, it is possible to accurately estimate the road surface condition.
In addition, in the embodiment 2, the estimation means 32d may estimate the road surface condition on the basis of a size of the vibration of the vehicle 3A (for example, absolute value |A|, absolute value |B|, and absolute value |D|), and a deviation of a vibration position of the vehicle 3A (for example, absolute value |B/C|).
Thus, it is possible to further accurately estimate the road surface condition by estimating the degree of deterioration of the road surface deterioration section X with various parameters.
Further, in the embodiment 2, the measurement means 32c may measure the size of the vibration of the vehicle 3A and a deviation of the vibration position of the vehicle 3A on the basis of a shape of the acceleration value distribution map generated by the generation means 32b.
Accordingly, it is possible to accurately measure the size of the vibration of the vehicle 3A and the deviation of the vibration position of the vehicle 3A. Therefore, according to the embodiment 2, it is possible to further accurately estimate the road surface condition.
In addition, in the embodiment 2, the estimation means 32d may estimate undulation of a face of a road surface on the basis of the size of the vibration of the vehicle 3A, and estimate the horizontal position of a point at which the road surface condition is damaged in a traveling lane on the basis of the deviation of the vibration position of the vehicle 3A.
Accordingly, it is possible to estimate the degree of deterioration of the road surface deterioration section X by various parameters, and it is also possible to estimate the horizontal position of the road surface deterioration section X. Therefore, according to the embodiment 2, it is possible to further accurately estimate the road surface condition.
In addition, in the embodiment 2, the estimation means 32d may directly estimate the road surface condition on the basis of the shape of the acceleration value distribution map generated by the generation means 32b. For example, the estimation means 32d can estimate whether there is an uneven step on the road surface or whether there are cracks on the road surface on the basis of the shape of the acceleration value distribution map. Therefore, according to the embodiment 2, it is possible to further accurately estimate the road surface condition.
Further, in the embodiment 2, the acquisition means 32a may acquire the travel information from a three axes acceleration sensor 5 located inside the vehicle 3A. Thus, since the acceleration value distribution map of the vehicle 3A can be easily generated, it is possible to estimate the road surface condition at a lower cost.
Note that, the three axes acceleration sensor 5 is not limited to the one installed in the vehicle 3A, but may be a three axes acceleration sensor installed in, for example, an information terminal such as a smartphone or the like, and placed in the vehicle 3A.
In addition, in the present disclosure, a number of three axes acceleration sensors 5 that measure the acceleration of the vehicle 3A is not limited to one, and may be plural. Accordingly, since it is possible to accurately measure the acceleration of the vehicle 3A, it is possible to further accurately estimate the road surface condition.
Further, in the embodiment 2, the storing means 32e may associate the positional information of the vehicle 3A acquired by the acquisition means 32a with the road surface condition estimated by the estimation means 32d, and store the positional information and the road surface condition in the road surface information storage unit 31b of the storage unit 31.
Accordingly, since a place where the road surface condition is poor is stored in the road surface information storage unit 31b, the information regarding the road surface condition estimated by the vehicle 3A can be utilized when the vehicle 3A travels next time and thereafter.
In addition, in the embodiment 2, as is the case with the embodiment 1 described above, there may be a case where the shape and the size of the generated acceleration value distribution map vary depending on the speed of the vehicle 3A, a vehicle type of the vehicle 3A, and a type of tires mounted in the vehicle 3A or the like.
Then, in the embodiment 2, the road surface condition may be estimated on the basis of information such as the speed of the vehicle 3A, the vehicle type of the vehicle 3A, and the type of tires mounted in the vehicle 3A or the like when passing the road surface deterioration section X in addition to the various vibration information described above.
For example, by causing the vehicle 3A to travel on a road surface a shape of irregularities thereof is known in advance, a calibration process may be performed on the vehicle 3A.
Further, the control device 4A generates a learning model having the acceleration value distribution map as input information and the degree of deterioration of the road surface as output information on the basis of a set of the acceleration value distribution maps of the vehicle 3A. Then, the estimation means 32d may estimate the degree of deterioration of the road surface by using the learning model in every generation of the acceleration value distribution map.
Further, in the embodiment 2, the generation means 32b may generate the acceleration value distribution map per unit time throughout the entire travelling time during traveling, or may generate the acceleration value distribution map from a point of time when the three axes acceleration sensor 5 detects particular acceleration.
The extraction means 32f extracts information regarding a lateral direction component of the acceleration of the vehicle 3A and the like from, for example, transition of acceleration in the three axes of the vehicle 3A. The specification means 32g specifies the cargo collapse information of the vehicle 3A on the basis of various information.
The presentation means 32h presents the cargo collapse information of the vehicle 3A specified by the specification means 32g to a driver of the vehicle 3A. For example, the presentation means 32h presents the cargo collapse information of the vehicle 3A to the driver of the vehicle 3A by displaying the cargo collapse information of the vehicle 3A on the display unit 8.
Note that, since the extraction means 32f, the specification means 32g, and the presentation means 32h have configurations that are similar to those of the extraction means 23f, the specification means 23g, and the presentation means 23h of the embodiment 1 shown in
Thus, in the embodiment 2, as is the case with the embodiment 1 described above, the cargo collapse information of the vehicle 3A specified by the specification means 32g is presented to the driver of the vehicle 3A.
For example, the presentation means 32h presents to the driver that possibility of the cargo collapse occurrence is high in a case where the degree of the influence given to the cargo collapse is larger than a predetermined threshold. Accordingly, the control device 4A can reduce the driving that may cause the cargo collapse easily.
Further, the presentation means 32h may present degree of the cargo collapse that occurred to the driver in a case where, for example, the degree of the influence given to the cargo collapse is larger than a predetermined threshold. Thereby, also, the control device 4A can reduce the driving that may increase the degree of the cargo collapse. Therefore, according to the embodiment 2, it is possible to reduce the cargo collapse on the vehicle 3A.
Further, in the embodiment 2, out of various elements indicated in the embodiment 1 described above (for example, absolute value |A|, absolute value |B|, absolute value |B/C|, absolute value |E|, absolute value |F|, and moment M), an element that makes the degree of the influence given to the cargo collapse large may be individually presented to the driver.
In addition, in the embodiment 2, the above-mentioned various elements (for example, absolute value |A|, absolute value |B|, absolute value |B/C|, absolute value |E|, absolute value |F|, and moment M) may be comprehensively taken into account in the magnitude of the degree of the influence to present the magnitude of the degree of the influence to the driver.
Further, in the embodiment 2, information of a point at which the degree of the influence given to the cargo collapse is large may be stored in the storage unit 31. For example, the storing means 32e associates the positional information of the vehicle 3A acquired by the acquisition means 32a with the cargo collapse information specified by the specification means 32g, and stores the associated positional information and the cargo collapse information in the cargo collapse information storage unit 31c of the storage unit 31.
Accordingly, since information regarding a place where the cargo collapse may easily occur is stored in the road surface information storage unit 31b, the information regarding the place where the cargo collapse may easily occur can be utilized when the vehicle 3A travels next time and thereafter.
For example, the control device 4A may present, to the driver, a guide of a route on which the vehicle 3A plans to travel on the basis of information stored in the road surface information storage unit 31b and the cargo collapse information storage unit 31c of the storage unit 31.
Specifically, the control device 4A may present, to the driver, the guide of a route to avoid, for example, a place where the road surface condition is poor which is stored in the road surface information storage unit 31b, and a place where the cargo collapse may easily occur which is stored in the cargo collapse information storage unit 31c (for example, place where the degree of influence given to the cargo collapse is larger than a predetermined threshold).
Accordingly, it is possible to prevent the vehicle 3A from entering the place where the road surface condition is poor (for example, a place where large irregularities are generated on the road surface or the like) or the place where the cargo collapse may easily occur (for example, curve having small curvature or the like). Therefore, according to the embodiment 2, it is possible to effectively reduce the cargo collapse on the vehicle 3A.
In addition, in a case where the degree of the influence given to the cargo collapse becomes larger than a predetermined threshold while traveling on a road surface regarding which the road surface condition thereof is known to be good in advance, the control device 4A may estimate that an increase of the degree of the influence results not from the road surface condition but from a way the driver drives by referring to the road surface information storage unit 31b.
Then, in this case, the presentation means 32h may present (advise), to the driver, a driving method to reduce the degree of the influence given to the cargo collapse. For example, in a case where the degree of distortion of the acceleration value distribution map in the one trip is large, the presentation means 32h may present, to the driver, the driving method to reduce the degree of distortion of the acceleration value distribution map when the driver is resting after the one trip is over.
Accordingly, the control device 4A can reduce the driving that may cause the cargo collapse easily. Therefore, according to the embodiment 2, it is possible to reduce the cargo collapse on the vehicle 3A.
In addition, in the embodiment 2, in a case where the position of a gravity center G of the cargo is gradually moving, a guidance may be presented to the driver. In addition, in a case where it is assumed that balance of the cargo is significantly lost, the presentation means 32h may present the driver to stop the vehicle 3A temporarily and check the cargo.
Next, details of procedures of various processes according to the embodiment 1 will be explained with reference to
First, the acquisition means 23a acquires the travel information of vehicles 3 (step S101). As the travel information, the acquisition means 23a acquires, for example, information regarding acceleration of the vehicle 3 in the front-back direction, the lateral direction, and the vertical direction from the three axes acceleration sensor 5.
Next, the generation means 23b generates the acceleration value distribution map in which the distribution of the acceleration in the three axes in the predetermined unit time is plotted in the three-dimensional coordinate system by using the information regarding the acceleration of the vehicle 3 in the front-back direction, the lateral direction, and the vertical direction acquired by the acquisition means 23a (step S102).
Next, the measurement means 23c measures vibration information of the vehicle 3 on the basis of a distribution of the acceleration of the vehicle 3 in the multiple axes (for example, acceleration value distribution map generated by generation means 23b) (step S103).
Next, the estimation means 23d estimates a road surface condition of a road surface on which the vehicle 3 traveled on the basis of vibration information measured by the measurement means 23c (step S104).
Finally, the storing means 23e associates positional information of the vehicle 3 acquired by the acquisition means 23a with a road surface condition estimated by the estimation means 23d, and stores the associated positional information and the road surface condition in the road surface information storage unit 12b of the server 2 (step S105), and ends a series of road surface condition estimation processes.
Next, the specification means 23g specifies the cargo collapse information of the vehicle 3 on the basis of the distribution of the acceleration of the vehicle 3 in the multiple axes on the basis of the travel information acquired by the acquisition means 23a (step S202).
The specification means 23g specifies the cargo collapse information of the vehicle 3 on the basis of, for example, the vibration information of the vehicle 3 measured by the measurement means 23c, or various information extracted by the extraction means 23f (absolute value |E| or absolute value |F| or the like described above).
Finally, the presentation means 23h presents the cargo collapse information of the vehicle 3 specified by the specification means 23g to the driver of the vehicle 3 (step S203), and ends a series of driving assistance processes.
Although the embodiments of the present invention have been described above, the present invention is not limited to the aforementioned embodiments, but various changes can be made unless the changes otherwise depart from the spirit of the present invention. For example, in the embodiment described above, various processes that are implemented on the vehicle 3 are indicated, however, an object of the implementation of the present disclosure is applicable not only to a vehicle but also to various moving bodies (for example, motorcycle, train or the like).
In addition, in the embodiments described above, an example of presenting the cargo collapse information to the driver of the vehicle 3 by the presentation means 23h is indicated, however, an object to which the presentation means 23h presents the cargo collapse information is not limited to the driver of the vehicle 3, but may be a driver of another vehicle 3 or a manager of the server 2 or the like.
Further, in the embodiments described above, the acceleration value distribution map that is a drawing in which the distribution of the acceleration in the three axes in the predetermined unit time is plotted in the three-dimensional coordinate system is generated by the three axes acceleration sensor 5, and an example of implementing a road surface condition estimation process or the driving assistance process is indicated on the basis of the acceleration value distribution map.
However, the embodiments described above are not limited to the example, and the acceleration value distribution map that is a drawing in which a distribution of the acceleration in two axes in the predetermined unit time is plotted in a two-dimensional coordinate system may be generated by using, for example, acceleration of two axes in the X axis direction and the Y axis direction measured by an acceleration sensor, and the road surface condition estimation process or the driving assistance process may be implemented on the basis of the acceleration value distribution map.
A further effect or a modification example can be easily derived by a person skilled in the art. Therefore, a broader aspect of the present invention shown and described as above is not limited to specific details and representative embodiments. Therefore, various changes can be made without departing from the spirit and scope of a comprehensive concept of the invention defined by attached claims and equivalents thereof.
Additional advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.
This application is national stage application of International Application No. PCT/JP2021/006224, filed on Feb. 18, 2021, which designates the United States, incorporated herein by reference, and which claims the benefit of priority therefrom, the entire contents of which are incorporated herein by reference.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2021/006224 | 2/18/2021 | WO |
