Travel state prediction device, travel state prediction method, and travel state prediction program

Abstract

A travel state prediction device predicts the travel state of a vehicle provided with a movement speed acquisition means and a deceleration position prediction means. The movement speed acquisition unit acquires speed result information as information related to a result of a movement speed of one or more vehicles. The deceleration position prediction means predicts the deceleration position of the host vehicle on the basis of the acquired speed result information. Provided is a method for predicting the traveling state of a vehicle by acquiring speed result information and predicting the deceleration position of the vehicle on the basis of the acquired speed result information. A travel state prediction program includes a movement speed acquisition process and a deceleration position prediction process that predicts a deceleration position of a host vehicle.

Description

Technical Field

[0001] The present disclosure relates to a driving state prediction device, a driving state prediction method, and a driving state prediction program for predicting the driving state of a host vehicle. Background Art

[0002] As related art, for example, JP-A-2009-67350 discloses a vehicle energy consumption prediction device, a vehicle energy consumption prediction method, and a computer program for vehicle energy consumption prediction, which are configured to predict the energy consumption consumed by a drive source of a vehicle while taking into account the driving pattern of the vehicle when passing through an intersection. Specifically, the vehicle energy consumption prediction device including a path recognition device and an energy consumption prediction device is provided with an intersection recognition device, a speed limit acquisition device, and an acceleration prediction device.

[0003] The path recognition device recognizes a predetermined driving path of the vehicle. The energy consumption prediction device predicts the energy consumption consumed by the drive source that generates the driving force of the vehicle when driving through the predetermined driving path recognized by the path recognition device. The intersection recognition device recognizes intersections on the predetermined driving path. The speed limit acquisition device acquires the speed limit of the road connected to the intersection recognized by the intersection recognition device. The acceleration prediction device predicts the acceleration time of the vehicle when passing through the intersection based on the speed limit acquired by the speed limit acquisition device and a predetermined acceleration. The energy consumption prediction device predicts the energy consumption based on the acceleration time of the vehicle predicted by the acceleration prediction device.

[0004] According to the technology disclosed in the above-mentioned patent document, it is possible to predict the energy consumption caused by acceleration resistance when the vehicle passes through an intersection. However, the probability that the vehicle stops at an intersection cannot be widely used as traffic information. Therefore, the technology disclosed in the above-mentioned patent document is only executed in a limited environment. Summary of the Invention

[0005] The present disclosure has been made in view of the above-described exemplary circumstances. The present disclosure provides a driving state prediction technology for a host vehicle with excellent versatility.

[0006] The driving state prediction device (4) is configured to predict the driving state of the host vehicle. The driving state prediction device according to the first aspect is provided with: a moving speed acquisition unit (5), which acquires speed result information as information related to the result of the moving speed of one or more vehicles; and a deceleration position prediction unit (6), which predicts the deceleration position of the host vehicle based on the acquired speed result information. The driving state prediction method according to the tenth aspect is a method for predicting the driving state of the host vehicle, which is realized by the following means: acquiring speed result information as information related to the result of the moving speed of one or more vehicles, and predicting the deceleration position of the host vehicle based on the acquired speed result information. The driving state prediction program according to the eleventh aspect is a computer program executed by the driving state prediction device (4) that predicts the driving state of the host vehicle, including: a moving speed acquisition process that acquires speed result information as information related to the result of the moving speed of one or more vehicles; and a deceleration position prediction process that predicts the deceleration position of the host vehicle based on the acquired speed result information.

[0007] The above-described configuration and method acquire speed result information as information related to the result of the moving speed of one or more vehicles, and predict the deceleration position of the host vehicle based on the acquired speed result information. The speed result information can be calculated based on widely provided traffic information or information that can be easily calculated from traffic information. Therefore, according to the above-described configuration and method, the driving state of the host vehicle can be advantageously predicted based on widely provided traffic information. Therefore, according to the above-described configuration and method, a driving state prediction technology for the host vehicle with excellent versatility can be provided.

[0008] Note that reference numerals in parentheses can be attached to each component in each column of the specification. However, the reference numerals only indicate examples of the relationship between each component and the specific device described later in the embodiments. Thus, the present disclosure is not specifically limited by the above-described reference numerals. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] The above and other objects, features, and advantages of the present disclosure will be further clarified by the following detailed description with reference to the accompanying drawings. In the drawings: Figure 1 is a block diagram showing the overall configuration of a system provided with a driving state prediction device according to an embodiment of the present disclosure; Figure 2 is a schematic diagram showing Figure 1 the overall operation of the driving state prediction device shown; Figure 3 is a schematic diagram showing Figure 1Block diagram of the overall functional configuration of the moving speed calculation function shown; Figure 4 Shows the Figure 1 Block diagram of the overall functional configuration of the target speed determination function provided in the driving state prediction device shown; Figure 5 Flowchart showing the overall operation of the driving state prediction device according to the first embodiment; Figure 6 Graph showing the overall operation of the driving state prediction device according to the first embodiment; Figure 7 Graph showing the overall operation of the driving state prediction device according to the first embodiment; Figure 8 Shows the Figure 1 Block diagram of the overall functional configuration of the target speed determination function provided in the driving state prediction device shown; Figure 9 Flowchart showing the overall operation of the driving state prediction device according to the second embodiment; Figure 10 Graph showing the overall operation of the driving state prediction device according to the second embodiment; Figure 11 Graph showing the overall operation of the driving state prediction device according to the second embodiment; Figure 12 Graph showing the overall operation of the driving state prediction device according to the second embodiment; Figure 13 Shows the Figure 1 Block diagram of the overall functional configuration of the target speed determination function provided in the driving state prediction device shown; Figure 14 Flowchart showing the overall operation of the driving state prediction device according to the third embodiment; Figure 15 Graph showing the overall operation of the driving state prediction device according to the third embodiment; Figure 16 Graph showing the overall operation of the driving state prediction device according to the third embodiment; and Figure 17 Graph showing the overall operation of the driving state prediction device according to the third embodiment. Detailed Description of the Invention

[0010] (Embodiment) Hereinafter, exemplary embodiments and specific examples of the present disclosure will be described with reference to the drawings. First, refer toFigures 1 to 3 The overall configuration of system 1 applicable to a vehicle traveling on a road will be described. Note that a vehicle to which system 1 is applied, that is, a vehicle provided with all or some elements of system 1, is referred to as the host vehicle. As Figure 1 shown, system 1 is provided with path coordinate information 2, path traffic information 3, and a driving state prediction device 4.

[0011] The path coordinate information 2 includes the coordinate information of each point RP on the predetermined driving path R of the host vehicle, that is, longitude and latitude information. The path coordinate information 2 can be obtained from the map data storage area of an external server of the host vehicle or a non-transitory physical recording medium (such as a flash memory) installed in the host vehicle. The predetermined driving path R can be obtained from an external server of the host vehicle or a navigation unit installed in the host vehicle. In Figure 2 the figure, the point RP that is the starting point of the predetermined travel path R is represented by the starting point RPs, and the point RP that is the ending point of the predetermined driving path R is represented by the ending point RPg. Note that Figure 2 the number and intervals of the points RP on the map shown are set for simplicity in describing the present disclosure and do not limit the content of the present disclosure.

[0012] The path traffic information 3 represents the traffic state of each point RP on the predetermined driving path R, that is, information related to the driving state results of one or more vehicles, and this information can be obtained by an external server of the host vehicle or the like. Specifically, the path traffic information 3 includes the travel time between predetermined points obtained through a map information API server or the like. API is an abbreviation for Application Programming Interface. Note that the predetermined points for which the travel time can be obtained are not limited to those points in each part corresponding to all the points RP shown in Figure 2 the figure. Specifically, for example, the travel time can be obtained only for points between main points such as intersections, branch points, crosswalks, or points where there are signals. In this case, in addition to the main points, point RPs as shown in Figure 2 the figure can also be set for the internal division points between the main points. In this case, the travel time between adjacent point RPs can be calculated by multiplying the travel time between the obtained main points by the ratio of the distance between adjacent point RPs to the distance between the main points.

[0013] The driving state prediction device 4 is configured to predict the driving state of the host vehicle based on at least the path coordinate information 2 and the path traffic information 3. According to the present embodiment, the driving state prediction device 4 is configured as an in-vehicle microprocessor (i.e., ECU: Electronic Control Unit) installed in the host vehicle. That is to say, the driving state prediction device 4 is provided with a processor composed of a CPU or MPU and a recording medium communicatively connected to the processor, and the processor is configured to read computer programs from the recording medium and execute them to implement predetermined functions. Among various non-transitory physical recording media such as ROM, non-volatile rewritable memory, etc., the recording medium at least includes ROM or non-volatile rewritable memory. The non-volatile rewritable memory is configured to be able to rewrite data during power supply and retain data during power-off and when the rewrite operation is disabled. The non-volatile rewritable memory is, for example, a flash memory, etc. The recording medium includes the above-mentioned computer programs and various data for executing the computer programs, such as initial values, maps, and lookup tables.

[0014] As Figure 1 shown, as a functional configuration implemented on the in-vehicle microprocessor by executing a computer program, the driving state prediction device 4 includes a moving speed calculation function 5 and a target speed determination function 6. The moving speed calculation function 5, as a moving speed acquisition unit according to the present disclosure, is configured to obtain speed result information based on the path coordinate information 2 and the path traffic information 3, and the speed result information is information related to the result of the moving speed (i.e., vehicle speed) of one or more vehicles. The target speed determination function 6, as a deceleration position prediction unit, predicts the deceleration position of the host vehicle based on the obtained speed result information. Note that according to the present disclosure, "deceleration" in "deceleration position" includes stop or substantial stop. In addition, "substantial stop" includes a situation where the vehicle speed temporarily (e.g., within a few seconds) decreases from the vehicle speed during normal driving (e.g., higher than 10 km / h) to a low speed at which the vehicle can stop immediately or lower, similar to the situation where the vehicle passes through an intersection where temporary vehicle stop is not required. The low speed refers to a speed of 10 km / h at which the vehicle can stop within 1 meter. The low speed includes a very slow speed of about several km / h. In other words, "deceleration" in "deceleration position" refers to a temporary deceleration that immediately requires starting acceleration or similar rising acceleration after the temporary deceleration.

[0015] As Figure 3As shown, according to this embodiment, the moving speed calculation function 5 includes a path information acquisition function 51, a distance acquisition function 52, a moving speed acquisition function 53, and a speed calculation function 54. The path information acquisition function 51 acquires path coordinate information 2 from an external server outside the vehicle itself. The distance acquisition function 52 is configured to acquire the distance between adjacent points RP located along a predetermined driving path R based on the acquired path coordinate information 2. The moving time acquisition function 53 acquires the moving time between adjacent points RP located along the predetermined driving path R based on the acquired path traffic information 3. The speed calculation function 54 is configured to acquire the moving speed between points RP as speed result information based on the distance between points RP acquired by the distance acquisition function 52 and the moving time between points RP acquired by the moving time acquisition function 53. According to this embodiment, the speed calculation function 54 calculates the average speed of at least one of the resultant vehicle speeds of the vehicle as the moving speed between points RP.

[0016] (First Embodiment) Figure 4 Shows the overall functional configuration of the target speed determination function 6 of the driving state prediction device 4 according to the first embodiment. Refer to Figure 1 Shown is the overall functional configuration of the target speed determination function 6 of the driving state prediction device 4. Refer to Figure 4 According to the first embodiment, the target speed determination function 6 includes a target speed acquisition function 611, a deceleration determination function 612, and a target speed setting function 613.

[0017] The target speed acquisition function 611 acquires the temporary target speed at each point RP on the predetermined driving path R. According to this embodiment, the temporary target speed is the speed limit at each point RP. This speed limit can be acquired from the map information API service or navigation map data installed in the vehicle itself.

[0018] The deceleration determination function 612 is configured to determine whether each point RP is in a deceleration position, that is, whether there is a large degree of deceleration, based on the speed result information. Note that "large deceleration" includes stopping and substantial stopping. Whether there is a large deceleration can be determined based on the change in the average speed. Specifically, it can be determined whether there is a large deceleration based on whether the average speed is lower than the speed threshold or whether the change amount of the average speed is higher than the threshold change amount.

[0019] The target speed setting function 613 is configured to set the target speed of the host vehicle at each point RP based on the temporary target speed acquired by the target speed acquisition function 611 and the deceleration position determined (predicted) by the deceleration determination function 612. Specifically, the target speed setting function 613 sets the target speed to the predetermined stop speed V0 when the point RP is a deceleration point, and sets the target speed to the temporary target speed when the point RP is not a deceleration point. The stop speed V0 is 0 km / h or a predetermined speed value lower than the low speed, that is, a predetermined speed value of 1 km / h to 3 km / h corresponding to a very low speed. According to the present embodiment, the target speed setting function 613 sets the target speeds at the starting point RPs and the ending point RPg to the stop speed of 0 km / h.

[0020] Figures 5 to 7 FIG. 4 shows a specific example of the driving state prediction device 4, the driving state prediction method, and the driving state prediction program executed by the driving state prediction device 4 according to the present embodiment. Hereinafter, the driving state prediction device 4, the driving state prediction method, and the driving state prediction program executed by the driving state prediction device 4 according to the present embodiment are referred to as "the present embodiment". In Figure 5 the flowcharts shown, S is an abbreviation for step. The same applies to the flowcharts shown in other drawings. In Figure 6 etc., the black circled points represent the average speed at each point RP. However, each point is a simple indication for simply describing the present disclosure and does not limit the content of the present disclosure. Therefore, the black circled points are actually schematic points and do not correspond to the arrangement of the points RP shown in Figure 2 FIG. 5.

[0021] In step S101, the driving state prediction device 4 acquires predetermined path information, that is, the coordinate information of the predetermined driving path R. Step 101 corresponds to the path information acquisition function 51. In step S102, the driving state prediction device 4 acquires the distance between adjacent points, that is, the adjacent points RP on the predetermined driving path R. Step 102 corresponds to the distance acquisition function 52. In step 103, the driving state prediction device 4 acquires the moving time between adjacent points. Step 103 corresponds to the moving time acquisition function 53. In step 104, the driving state prediction device 4 calculates the average speed as the moving speed between adjacent points. Step 104 corresponds to the speed calculation function 54. Figure 6 FIG. 6 is a diagram showing the average speeds of the respective points RP in the order shown on the predetermined driving path R. Since the target speeds of the starting point RPs and the ending point RPg are set to the stop speed, that is, 0 km / h, the average speeds at the starting point RPs and the ending point RPg are set to 0 km / h. The same applies to the average speed of the vehicle in other drawings.

[0022] In step 105, the driving state prediction device 4 sets the target speeds of the starting point RPs and the ending point RPg at each point RP on the predetermined driving road R to 0 km / h, and sets the target speeds of other points to the temporary target speed, i.e., the speed limit. Step 105 corresponds to the target speed acquisition function 611 and the target speed setting function 613. In step 106, the driving state prediction device 4 determines whether there is a large degree of deceleration at each point RP. Step 106 corresponds to the deceleration determination function 612. Figure 7 The upper part of shows an example of the determination method for determining whether there is a large degree of deceleration at each point RP. As Figure 7 shown by the arrows in, it can be determined that there is a large degree of deceleration when the average speed is lower than the speed threshold or the decrease amount of the average speed is higher than the threshold amount. The speed threshold or the threshold amount can be obtained through computer simulation or optimization experiments. For example, the speed threshold can be set to 10 - 15 km / h. For example, the threshold amount can be set to 20 - 30 km / h.

[0023] In the case where there is a large degree of deceleration (i.e., step 106 = yes), the driving state prediction device 4 performs the process of step 107. In step S107, as Figure 7 shown by the position of the upward arrow in, the driving state prediction device 4 sets the target speed at the deceleration position where there is a large degree of deceleration, i.e., the point RP, to the predetermined stop speed V0. Step S107 corresponds to the target speed setting function 613. On the contrary, in the case where there is no large degree of deceleration (i.e., step 106 = no), the driving state prediction device 4 skips the process of step 107. In this case, the target speed is maintained as the speed limit which is the temporary target speed.

[0024] According to the present embodiment, speed result information which is information related to the result of the moving speed of one or more vehicles is acquired, and the deceleration position of the host vehicle is predicted based on the acquired speed result data. The speed result information is widely provided traffic information or information that can be easily calculated from traffic information. Therefore, in the present embodiment, the driving state of the host vehicle, especially the traveling speed pattern or the deceleration position of the host vehicle, can be appropriately predicted. Therefore, according to the present embodiment, a driving state prediction technology of the host vehicle with excellent versatility can be provided.

[0025] (Second Embodiment) Figure 8 shows the overall functional structure of the target speed determination function 6 of the second embodiment of the driving state prediction device 4 according to Figure 1 shown. Refer to Figure 8, according to the present embodiment, the target speed determination function 6 includes a target speed acquisition function 621, a reference speed acquisition function 622, a speed difference determination function 623, and a target speed setting function 624. The target speed acquisition function 621 is configured to acquire the temporary target speed at each point RP. That is, the target speed acquisition function 621 is similar to the target speed acquisition function 611 in the first embodiment described above. Therefore, hereinafter, the respective functional configurations of the reference speed acquisition function 622, the speed difference determination function 623, and the target speed setting function 624 will be mainly described.

[0026] The reference speed acquisition function 622 is configured to acquire the moving speed of the vehicle during non-stop periods at each point RP as the reference speed. Note that the "moving speed of the vehicle during non-stop periods" refers to the expected moving speed (e.g., speed limit) of the vehicle at each point RP under normal traffic conditions without traffic obstacles such as traffic control or traffic jams. The speed difference determination function 623 is configured to calculate the relationship between the reference speed and the average speed, i.e., the ratio or difference therebetween. In addition, the speed difference determination function 623 is configured to determine whether the calculated ratio or difference exceeds a threshold value. Specifically, the speed difference determination function 623 predicts the point RP where the calculated ratio or difference exceeds the threshold value as the deceleration position.

[0027] The target speed setting function 624 sets the target speed of the host vehicle at each point RP based on the determination result of the speed difference determination function 623. Specifically, the target speed setting function 624 sets the target speed to the predetermined stop speed V0 when the point RP is the deceleration position, and sets the target rotational speed to the temporary target speed when the point RP is not the deceleration point.

[0028] Figures 9 to 12 A specific example of the driving state prediction device 4, the driving state prediction method, and the driving state prediction program executed by the driving state prediction device 4 according to the present embodiment is shown. Note that Figure 9 The content of steps 201 to 204 shown in the flowchart shown is the same as Figure 5 the content of steps 101 to 104 in the flowchart shown. Therefore, the description of steps 101 to 104 in the first embodiment described above applies to the content of steps 201 to 204, and the processing after step 204 will be described hereinafter.

[0029] The driving state prediction device 4 sets the target speeds of the starting point RPs and the ending point RPg at each point RP on the predetermined driving road R to 0 km / h, and sets the target speeds of other points to the temporary target speed, i.e., the speed limit. Step 205 corresponds to the target speed acquisition function 621 and the target speed setting function 624. In step 206, as Figure 10As shown, the driving state prediction device 4 acquires the speed limit as the reference speed for each point RP. Step 206 corresponds to the reference speed acquisition function 622. In step 207, the driving state prediction device 4 calculates the speed difference ΔV as the difference between the reference speed and the average speed. The difference between the reference speed and the average speed is Figure 11 the difference between the reference speed shown by the solid line in Figure 11 and the average speed shown by the dashed line in

[0030] In step 208, the driving state prediction device 4 determines whether the speed difference ΔV exceeds the threshold speed difference ΔVth. Steps 207 and 208 correspond to the speed difference determination function. The threshold speed difference ΔVth can be obtained through computer simulation or optimization experiments. The threshold speed difference ΔVth can be set to 20 - 30 km / h. Figure 12 When the speed difference ΔV exceeds the threshold speed difference ΔVth (i.e., step 208 = yes), the driving state prediction device 4 performs processing in step 209. In step 209, the driving state prediction device 4 determines the point RP where the speed difference ΔV exceeds the threshold speed difference ΔVth as the deceleration point, and sets the target speed of the point RP to the deceleration point, i.e., the stop speed V0. Step 209 corresponds to the target speed setting function 624. Conversely, when the speed difference ΔV is less than or equal to the threshold speed difference ΔVth (i.e., step 208 = no), the driving state prediction device 4 skips the processing in step 209. In this case, the target speed is maintained as the speed limit which is the temporary target speed. Therefore, as

[0031] shown, the driving state prediction device 4 sets the final target speed at each point RP according to the processing result of step 205 and the determination result of step 208.

[0032] (Third Embodiment) Figure 13 Shows the overall functional structure of the target speed determination function 6 of the driving state prediction device 4 according to the third embodiment. Refer to Figure 1 shown Figure 13, according to this embodiment, the target speed determination function 6 includes a target speed acquisition function 631, a deceleration probability acquisition function 632, and a target speed setting function 633. The target speed acquisition function 631 is configured to acquire the temporary target speed at each point RP. That is to say, the target speed acquisition function 621 is similar to the target speed acquisition function 611 in the first embodiment described above. Therefore, hereinafter, the respective functional configurations of the deceleration probability acquisition function 632 and the target speed setting function 633 will be mainly described.

[0033] The deceleration probability acquisition function 632 is configured to acquire the deceleration probability of the vehicle at each point RP. The deceleration probability refers to the occurrence probability that the vehicle stops or substantially stops at each point RP under normal traffic conditions without traffic control or traffic jams and other traffic obstacles. The deceleration probability can be obtained based on the recorded driving state of each point RP. Specifically, the deceleration probability can be obtained according to the historical information of the driving speed results of one or more vehicles at each point RP. More specifically, the speed change parameter is defined as the change in the average speed, that is, the decrease in the average speed, or the relationship (such as the difference) between the reference speed of the moving speed during the non-stop period and the average speed. A statistical process is applied to the correlation between the speed change parameter and the occurrence state of the vehicle stop or substantial stop, so as to obtain a mapping or formula indicating the relationship between the speed change parameter and the deceleration probability. For example, the mapping or formula can be calculated in a server or the like located outside the vehicle. The mapping or formula is read from the server or the like at an appropriate time and used in the vehicle. In addition, the deceleration probability acquisition function 632 can acquire the deceleration probability at each point RP based on the mapping or formula and the speed change parameter at each point RP.

[0034] In addition, the deceleration probability acquisition function 632 is configured to determine whether the deceleration probability of the vehicle at each point RP is lower than the probability threshold. In other words, the deceleration probability acquisition function 632 determines whether each point RP is in a deceleration position. Then, the target speed setting function 633 sets the target speed of the vehicle at each point RP based on the determination result of the deceleration probability acquisition function 632. Specifically, the target speed setting function 633 sets the target speed to the stop speed V0 when the point RP is a deceleration point, and sets the target speed to the temporary target speed when the point RP is not a deceleration point.

[0035] Figures 14 to 17 A specific example of the driving state prediction device 4, the driving state prediction method, and the driving state prediction program executed by the driving state prediction device 4 according to this embodiment is shown. Note that Figure 14 The content of steps 301 to 304 shown in the flowchart shown is the same as Figure 5The content of steps 101 to 104 in the flowchart shown is the same. Therefore, the description of steps 101 to 104 in the first embodiment as described above is applied to the content of steps 301 to 304, and the processing after step 304 will be described below.

[0036] In step 305, the driving state prediction device 4 sets the target speeds of the starting points RPs and the ending points RPg at each point RP on the predetermined driving road R to 0 km / h, and sets the target speeds of other points to the temporary target speed, that is, the speed limit. Step 305 corresponds to the target speed acquisition function 631 and the target speed setting function 633. In step 306, the driving state prediction device 4 acquires the deceleration probability at each point RP. According to this specific example, as Figure 15 shown, the decrease amount of the average speed is used to calculate the deceleration probability. In step 307, the driving state prediction device 4 determines whether there is a large degree of deceleration at each point RP. That is, the driving state prediction device 4 is based on Figure 16 the mapping shown representing the relationship between the deceleration probability and the decrease amount of the average speed to determine whether the deceleration probability at each point RP exceeds the probability threshold. Steps 306 and 307 correspond to the deceleration probability acquisition function 632.

[0037] When the deceleration probability exceeds the probability threshold (that is, step 307 = yes), the driving state prediction device 4 performs processing in step 308. In step 308, the driving state prediction device 4 uses the point RP where the deceleration probability exceeds the probability threshold as the deceleration position, and sets the target speed of the point RP as the deceleration position to the predetermined stop speed V0. Step 308 corresponds to the target speed setting function 633. Conversely, when the deceleration probability does not exceed the probability threshold (that is, step 307 = no), the driving state prediction device 4 skips the processing in step 308. In this case, the target speed is maintained as the speed limit which is the temporary target speed. Therefore, as Figure 17 shown, the driving state prediction device 4 sets the final target speed at each point RP according to the processing result of step 305 and the processing result of step 308 based on the determination result of step 307.

[0038] (Variant example) The present disclosure is not limited to the embodiments and specific examples described above. Therefore, the embodiments described above can be appropriately modified. Hereinafter, typical modification examples will be described. In the following modification examples, the configurations different from those in the embodiments described above will be mainly described. In addition, the same reference numerals are applied to the same or equivalent configurations between the embodiments described above and the modification examples. Therefore, in the following modification examples, unless there is a technical inconsistency or any additional explanation, the description of the embodiments described above will be applied to the components having the same reference numerals as those in the embodiments described above.

[0039] The present disclosure is not limited to the specific uses or device configurations described in the embodiments above. That is, for example, the driving state prediction device 4 can be used for various purposes, including predicting vehicle driving energy or the remaining battery capacity (i.e., SOC). In addition, a part or some configurations of the driving state prediction device 4 can be provided in a server outside the vehicle. Specifically, for example, the moving speed calculation function 5 can be provided in a server outside the vehicle.

[0040] In addition, a part or some configurations of the driving state prediction device 4 can be digital circuits configured to be able to implement the functions or operations described above. For example, it can be composed of an ASIC (application specific integrated circuit) or an FPGA (field programmable gate array). In the driving state prediction device 4, the in-vehicle microprocessor part and the digital circuit part can coexist.

[0041] Note that a program capable of performing various operations, processes, or treatments described in the above embodiments according to the present disclosure can be downloaded or upgraded via V2X communication. V2X is an abbreviation for vehicle-to-X. In addition, the program can be downloaded or upgraded through a terminal device provided by a vehicle manufacturer, a maintenance facility, a dealer of the vehicle, etc. The program can be stored in a memory card, an optical disc, a magnetic disk, etc.

[0042] Each of the functional configurations and processes described above can be implemented by a dedicated computer composed of a processor and a memory, which is programmed to execute one or more functions implemented by a computer program. Alternatively, each of the functional configurations and processes described above can be implemented by a dedicated computer provided by a processor composed of one or more dedicated hardware logic circuits. In addition, each of the functional configurations and processes described above can be implemented by one or more dedicated computers, which are combined by a processor programmed to execute one or more functions and a memory and a processor composed of one or more hardware logic circuits. In addition, a computer program can be stored as instruction codes to be executed by a computer in a computer-readable non-transitory tangible recording medium. That is, each of the functional configurations and processes described above can be represented by a computer program or a computer-readable non-transitory tangible recording medium storing these programs, and the above computer programs include processes for implementing each of the functional structures and processes described above.

[0043] The present disclosure is not limited to the specific operation modes described in the embodiments above. Specifically, for example, all the points RP can be acquired as traffic information, that is, the travel time between adjacent points RP. In addition, Figure 5 The execution order of the process in step 102 and the process in step 103 shown can be reversed, or these processes can be executed simultaneously. In addition, Figure 6 Various diagrams such as those shown are only used to simply describe the present disclosure and do not limit the content of the present disclosure. In addition, the relationship between each functional configuration and the corresponding step in the flowchart can be appropriately changed. In other words, for example, step 208 can correspond to the target speed setting function 624. In addition, the stop speed V0 can be changed between types of stop positions. Specifically, for example, for a stop position where the vehicle needs to stop temporarily, the stop speed V0 can be set to V0 = 0 km / h, and for a stop position where the vehicle does not need to stop temporarily, the stop speed V0 can be set to V0 > 0 km / h. For a situation where it is determined whether to stop temporarily according to the situation, such as an intersection without signals, the stop speed V0 can be set to V0 > 0 km / h. In addition, for a stop position where the stop speed V0 ≠ 0 km / h, the stop speed can be changed according to the respective traffic conditions.

[0044] Note that as long as there is no technical inconsistency, terms used in this specification, such as "acquire", "calculate", "estimate", "detect", "determine" and similar terms can be appropriately interchanged with each other. In addition, as long as there is no technical inconsistency, "detect" and "extract" can be appropriately interchanged with each other. In addition, as long as there is no technical inconsistency, "exceed the threshold" and "be greater than or equal to the threshold" can be appropriately interchanged with each other. The same applies to "be less than the threshold" and "be less than or equal to the threshold".

[0045] In the above-described embodiments, the elements constituting the embodiments are not necessarily essential unless the elements are explicitly specified as essential or theoretically essential. Even when numerical values such as the number of components, numerical values, quantities, ranges, etc. are mentioned in the above-described embodiments, the above numerical values are not limited to specific values unless they are specified as required or theoretically limited to a specific quantity. When the materials, shapes, directions, positional relationships, etc. of the components in the above-described embodiments are mentioned, they are not limited to the materials, directions, shapes, and positional relationships, except when they are explicitly specified or theoretically limited to specific materials, shapes, directions, and positional relationships.

[0046] The modification examples are not limited to the examples described above. For example, as long as there is no technical inconsistency, all or part of one example among multiple specific examples can be combined with all or part of another example. The number of combinations can be without particular limitation. Similarly, as long as there is no technical inconsistency, all or part of one example among multiple modification examples can be combined with all or part of another example. In addition, as long as there is no technical inconsistency, all or part of the specific examples can be combined with all or part of the modification examples described above.

[0047] (Structure) It can be clearly seen from the above-described embodiments and modification examples that the present specification discloses at least the following structures.

[0048] [Structure 1-1] A driving state prediction device, the driving state prediction device (4) predicts the driving state of the own vehicle, including: A moving speed acquisition unit (5), the moving speed acquisition unit acquires speed result information as information related to the result of the moving speed of one or more vehicles; and A deceleration position prediction unit (6), the deceleration position prediction unit predicts the deceleration position of the own vehicle based on the acquired speed result information. [Structure 1-2] The driving state prediction device according to Structure 1-1, wherein, The above speed result information is an average speed. [Structure 1-3] The driving state prediction device according to Structure 1-2, wherein, The deceleration position prediction unit predicts the deceleration position based on the change in the average speed. [Structure 1-4] The driving state prediction device according to Structure 1-3, wherein, The above deceleration position prediction unit predicts the deceleration position based on whether the above average speed is lower than the speed threshold or whether the change amount of the above average speed is higher than the threshold change amount. [Structure 1-5] The traveling state prediction device according to Structure 1-2, wherein The above traveling state prediction device includes a reference speed acquisition unit (622), and the reference speed acquisition unit acquires a reference speed that is the moving speed of the vehicle during non-stop. The above deceleration position prediction unit predicts the deceleration position based on the relationship between the above reference speed and the above average speed. [Structure 1-6] The traveling state prediction device according to Structure 1-5, wherein The above relationship is the ratio or difference between the above reference speed and the above average speed. [Structure 1-7] The traveling state prediction device according to Structure 1-2, wherein The above traveling state prediction device includes a deceleration probability acquisition unit (632), and the deceleration probability acquisition unit acquires a deceleration probability calculated based on the change of the above average speed or the relationship between the reference speed that is the moving speed of the vehicle during non-stop and the above average speed. The above deceleration position prediction unit predicts the deceleration position based on the above deceleration probability. [Structure 1-8] The traveling state prediction device according to Structure 1-7, wherein The above deceleration position prediction unit predicts the deceleration position based on whether the above deceleration probability is lower than the probability threshold. [Structure 1-9] The traveling state prediction device according to Structure 1-7 or 1-8, wherein The above deceleration probability is calculated based on historical information of the results of the moving speeds of one or more vehicles at a predetermined position.

[0049] [Structure 2-1] A method for predicting the traveling state of one's own vehicle, including: Acquiring speed result information as information related to the results of the moving speeds of one or more vehicles; and Predicting the deceleration position of the above own vehicle based on the acquired above speed result information. [Structure 2-2] The method according to Structure 2-1, wherein The above speed result information is the average speed. [Configuration 2-3] According to the method described in Configuration 2-2, wherein, The above method predicts the deceleration position based on the change in the above average speed. [Configuration 2-4] According to the method described in Configuration 2-3, wherein, The above method predicts the deceleration position based on whether the above average speed is lower than the speed threshold or whether the change amount of the above average speed is higher than the threshold change amount. [Configuration 2-5] According to the method described in Configuration 2-2, wherein, The above method obtains a reference speed as the moving speed of the vehicle during non-stop, and predicts the deceleration position based on the relationship between the above reference speed and the above average speed. [Configuration 2-6] According to the method described in Configuration 2-5, wherein, The above relationship is the ratio or difference between the above reference speed and the above average speed. [Configuration 2-7] According to the method described in Configuration 2-2, wherein, The above method obtains a deceleration probability calculated based on the change in the above average speed or the relationship between the reference speed as the moving speed of the vehicle during non-stop and the above average speed, and predicts the deceleration position based on the above deceleration probability. [Configuration 2-8] According to the method described in Configuration 2-7, wherein, The above method predicts the deceleration position based on whether the above deceleration probability is lower than the probability threshold. [Configuration 2-9] According to the method described in Configuration 2-7 or 2-8, wherein, The above method calculates the above deceleration probability based on the historical information of the results of the moving speeds of one or more vehicles at a predetermined position.

[0050] [Configuration 3-1] A driving state prediction program, which is executed by a driving state prediction device (4) that predicts the driving state of the own vehicle. The above driving state prediction program includes: A moving speed acquisition process, which acquires speed result information as information related to the results of the moving speeds of one or more vehicles; and A deceleration position prediction process, which predicts the deceleration position of the own vehicle based on the acquired speed result information. [Configuration 3-2] According to the procedure described in Configuration 3-1, where the above speed result information is the average speed. [Configuration 3-3] According to the procedure described in Configuration 3-2, where in the above deceleration position prediction process, the above deceleration position is predicted based on the change in the above average speed. [Configuration 3-4] According to the procedure described in Configuration 3-3, where in the above deceleration position prediction process, the above deceleration position is predicted based on whether the above average speed is lower than the speed threshold or whether the change amount of the above average speed is higher than the threshold change amount. [Configuration 3-5] According to the procedure described in Configuration 3-2, where the above procedure includes a reference speed acquisition process that acquires a reference speed as the moving speed of the vehicle during non-stop periods, and in the above deceleration position prediction process, the above deceleration position is predicted based on the relationship between the above reference speed and the above average speed. [Configuration 3-6] According to the procedure described in Configuration 3-5, where the above relationship is the ratio or difference between the above reference speed and the above average speed. [Configuration 3-7] According to the procedure described in Configuration 3-2, where the above procedure includes a deceleration probability acquisition process that acquires a deceleration probability calculated based on the change in the above average speed or the relationship between a reference speed as the moving speed of the vehicle during non-stop periods and the above average speed, and in the above deceleration position prediction process, the above deceleration position is predicted based on the above deceleration probability. [Configuration 3-8] According to the procedure described in Configuration 3-7, where in the above deceleration probability acquisition process, the above deceleration position is predicted based on whether the above deceleration probability is lower than the probability threshold. [Configuration 3-9] According to the procedure described in Configuration 3-7 or 3-8, where the above deceleration probability is calculated based on historical information of the results of the moving speeds of one or more vehicles at a predetermined position.

Claims

1. A driving state prediction device that predicts the driving state of the host vehicle, comprising: A moving speed acquisition unit that acquires speed result information as information related to the result of the moving speed of one or more vehicles; And A deceleration position prediction unit that predicts the deceleration position of the host vehicle based on the acquired speed result information.

2. The driving state prediction device according to claim 1, wherein The speed result information is an average speed.

3. The driving state prediction device according to claim 2, wherein The deceleration position prediction unit predicts the deceleration position based on the change in the average speed.

4. The driving state prediction device according to claim 3, wherein The deceleration position prediction unit predicts the deceleration position based on whether the average speed is lower than a speed threshold or whether the change amount of the average speed is higher than a threshold change amount.

5. The driving state prediction device according to claim 2, wherein The driving state prediction device includes a reference speed acquisition unit that acquires a reference speed as the moving speed of the vehicle during non-stop, The deceleration position prediction unit predicts the deceleration position based on the relationship between the reference speed and the average speed.

6. The driving state prediction device according to claim 5, wherein The relationship is a ratio or a difference between the reference speed and the average speed.

7. The driving state prediction device according to claim 2, wherein The driving state prediction device includes a deceleration probability acquisition unit that acquires a deceleration probability calculated based on the change in the average speed or the relationship between the reference speed as the moving speed of the vehicle during non-stop and the average speed, The deceleration position prediction unit predicts the deceleration position based on the deceleration probability.

8. The driving state prediction device according to claim 7, wherein The deceleration position prediction unit predicts the deceleration position based on whether the deceleration probability is lower than a probability threshold.

9. The driving state prediction device according to claim 7 or 8, wherein The deceleration probability is calculated based on historical information of the results of the moving speeds of one or more vehicles at a predetermined position.

10. A method for predicting the driving state of the host vehicle, comprising: Acquiring speed result information as information related to the result of the moving speed of one or more vehicles; And Predicting the deceleration position of the host vehicle based on the acquired speed result information.

11. A driving state prediction program executed by a driving state prediction device that predicts the driving state of the host vehicle, the driving state prediction program including: A moving speed acquisition process that acquires speed result information as information related to the result of the moving speed of one or more vehicles; And Deceleration position prediction processing, where the deceleration position prediction processing predicts the deceleration position of the host vehicle based on the acquired speed result information.

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