DRIVING CONDITION PREDICTION DEVICE, DRIVING CONDITION PREDICTION METHOD AND ASSOCIATED PROGRAM

Abstract

A driving state prediction device that predicts a driving state of a reference vehicle is provided with a moving speed acquisition unit and a deceleration location prediction unit. The moving speed acquisition unit acquires speed result information as information related to a moving speed result of one or more vehicles. The deceleration location prediction unit predicts a deceleration location of the reference vehicle based on the acquired speed result information. A method of predicting a driving state of a reference vehicle is a method of predicting a driving state of the reference vehicle performed by acquiring speed result information and predicting a deceleration location of the reference vehicle based on the acquired speed result information.A driving state prediction program includes a moving speed acquisition process and a deceleration location prediction process that predicts a deceleration location of the reference vehicle.

Description

BACKGROUND(Technical Field)The present disclosure relates to a traveling state prediction device, a traveling state prediction method, and a traveling state prediction program for predicting a traveling state of the own vehicle.(Description of Prior Art)As a related art, for example, JP-A-2009-67350 discloses a vehicle energy consumption prediction apparatus, a vehicle energy consumption prediction method, and a corresponding computer program for predicting the energy consumption consumed by a drive source of a vehicle, taking into account a travel mode of the vehicle when traveling through an intersection. More specifically, a vehicle energy consumption prediction apparatus including a route identification means and an energy consumption prediction means is provided with an intersection identification means, a speed limit acquisition means and an acceleration prediction means.The route identifying means identifies a scheduled travel route of the vehicle. The power consumption prediction means predicts the power consumption consumed by a drive source that generates a drive force for a vehicle when traveling through a planned travel route identified by the route identification means. The intersection identifying means identifies an intersection on the scheduled travel route. The speed limit acquisition means acquires a speed limit for a road connected to the intersection identified by the intersection identification means. The acceleration prediction means predicts an acceleration time of a vehicle when the vehicle passes through the intersection based on the speed limit acquired by the speed limit acquisition means and a predetermined acceleration. The energy consumption prediction means predicts an energy consumption based on the acceleration time of the vehicle predicted by the acceleration prediction means.According to a technique described by the above-described patent literature, the power consumption due to the acceleration resistance when passing through the intersection can be predicted. However, a probability of the vehicle stopping at the intersection as traffic information is not generally available. Therefore, the technique described in the above-described patent literature is applied only in a limited environment.SUMMARYThe present disclosure has been made in view of the above-described circumstances. The present disclosure provides a traveling state prediction technique of an own vehicle having excellent versatility.A traveling state prediction device ( 4) is configured to predict a traveling state of an own vehicle. A traveling state prediction device according to a first aspect is provided with a moving speed acquisition unit (5) that acquires speed result information as information related to a result of a moving speed of one or more vehicles; and a deceleration location prediction unit (6) that predicts a deceleration location of the own vehicle based on the acquired speed result information. A traveling state prediction method according to a tenth aspect is a method of predicting a traveling state of the own vehicle realized by acquiring speed result information as information related to a result of a moving speed of one or more vehicles and predicting a deceleration location of the own vehicle based on the acquired speed result information. A traveling state prediction program according to an eleventh aspect is a computer program executed by a traveling state prediction device (4) predicting a traveling state of an own vehicle, including a moving speed acquisition process that acquires speed result information as information related to a result of a moving speed of one or more vehicles; and a deceleration location prediction process that predicts a deceleration location of the own vehicle based on the acquired speed result information.The above-described configurations and methods acquire speed result information as information related to a result of a moving speed of one or more vehicles, and predict a deceleration location of the own vehicle based on the acquired speed result information. The speed result information may be calculated based on widely provided traffic information or information that can be easily calculated from the traffic information. According to the above-described configurations and methods, the traveling state of the own vehicle can be advantageously predicted based on the widely provided traffic information. Therefore, according to the above-described configurations and methods, a traveling state prediction technique of an own vehicle having excellent versatility can be provided.Note that reference numerals in parentheses may be added to the corresponding constituent elements in the corresponding columns of the description. However, reference numerals indicate only an example of a relationship between the respective constituent elements and specific devices which will be described later in the embodiments. Accordingly, the present disclosure is not particularly limited by the reference numerals described above.BRIEF DESCRIPTION OF THE DRAWINGSThe above-described objects and other objects, features and advantages of the present disclosure will be further understood from the following detailed description with reference to the accompanying drawings. The drawings are as follows: FIG. 1 is a block diagram showing an overall configuration of a system provided with a driving state prediction device according to an embodiment of the present disclosure; FIG. 2 is a schematic diagram illustrating an overall operation of the driving state prediction device shown in FIG. 1 ; FIG. 3 is a block diagram showing an overall functional configuration of a movement speed calculation function shown in FIG. 1 ; FIG. 4 is a block diagram showing an overall functional configuration of a target speed determination function provided in the traveling state prediction device according to the first embodiment shown in FIG. 1 ; FIG. 5 is a flowchart showing an overall operation of the traveling state prediction device according to the first embodiment; FIG. 6 is a graph showing an overall operation of the traveling state prediction device according to the first embodiment; FIG. 7 is a graph showing an overall operation of the traveling state prediction device according to the first embodiment; FIG. 8 is a block diagram showing an overall functional configuration of a target speed determination function provided in a traveling state prediction device according to a second embodiment shown in FIG. 1 ; FIG. 9 is a flowchart showing an overall operation of the traveling state prediction device according to the second embodiment; FIG. 10 is a graph showing an overall operation of the traveling state prediction device according to the second embodiment; FIG. 11 is a graph showing an overall operation of the traveling state prediction device according to the second embodiment; FIG. 12 is a graph showing an overall operation of the traveling state prediction device according to the second embodiment; FIG. 13 is a block diagram showing an overall functional configuration of a target speed determination function provided in a traveling state prediction device according to a third embodiment shown in FIG. 1 ; FIG. 14 is a flowchart showing an overall operation of the traveling state prediction device according to a third embodiment; FIG. 15 is a graph showing an overall operation of the traveling state prediction device according to the third embodiment; FIG. 16 is a graph showing an overall operation of the traveling state prediction device according to the third embodiment; and FIG. 17 is a graph showing an overall operation of the traveling state prediction device according to the third embodiment.DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS(Embodiments)Hereinafter, exemplary embodiments and specific examples of the present disclosure will be described with reference to the drawings. First, an overall configuration of a system 1 applicable to a vehicle running on a road will be described with reference to FIGS. 1 to 3. Note that the vehicle to which the system 1 is applied, i.e., a vehicle provided with all or some of the elements of the system 1, is referred to as a host vehicle. As shown in FIG. 1, the system 1 is provided with route coordinate information 2, route traffic information 3, and a traveling state prediction device 4.The route coordinate information 2 includes coordinate information of corresponding points RP on the planned travel route R of the own vehicle, i.e., latitude-longitude information. The route coordinate information 2 may be acquired from a map data storage area of an external server of the own vehicle or from a non-transitory substantial storage medium (e.g., flash memory) installed in the own vehicle. The scheduled travel route R may be acquired from the external server of the own vehicle or from a navigation unit installed in the own vehicle. In FIG. 2, a point RP as a starting point of the scheduled travel route R is indicated by a starting point RPs, and a point RP as an ending point of the scheduled travel route R is indicated by an ending point RPg. Note that the number of points RP and the distance therebetween are set on the map shown in FIG. 2 for easily describing the present disclosure, and do not limit the content of the present disclosure.The route traffic information 3 indicates a traffic state of the corresponding points RP on the scheduled travel route R, i.e., information related to the results of travel states of one or more vehicles that can be acquired from an external server or the like of the own vehicle. Specifically, the route traffic information 3 includes a travel time between predetermined points that can be acquired from a map information API service or the like. API is an abbreviation for Application Programming Interface. Note that the predetermined points at which the travel time can be acquired are not limited to those in the respective sections corresponding to all the points RP illustrated in FIG. 2. Specifically, for example, it is possible that only traveling times for points between main points such as an intersection, a branch point, a crosswalk, or points with signals are acquired. In this case, the points RP shown in FIG. 2 may be set for internally divided points between the main points, except for the main points. In this case, the travel time between adjacent points RP may be calculated by multiplying the acquired travel time between the main points by a ratio of a distance between adjacent points RP to the distance between main points.The traveling state prediction device 4 is configured to predict a traveling state of the own vehicle based on at least the route coordinate information 2 and the route traffic information 3. According to the present embodiment, the traveling state prediction device 4 is configured as an in-vehicle microprocessor (i.e., ECU: electronic control unit) mounted on the own vehicle. That is, the traveling state prediction device 4 is provided with a processor configured of a CPU or MPU and a recording medium communicatively connected to the processor, and is configured to read and execute computer programs from the recording medium, thereby executing predetermined functions. The recording medium includes, among various non-transitory substantial recording media such as ROM, nonvolatile rewritable memory, and the like, at least one ROM or nonvolatile rewritable memory. The nonvolatile rewritable memory is configured such that the data is rewritable during power supply and that the data is held during power shut-down that inhibits the rewriting operation. The nonvolatile rewritable memory is, for example, a flash memory or the like. The recording media include the above-mentioned computer programs and also various data for executing the computer programs, such as initial values, maps, and look-up tables.As shown in FIG. 1, the traveling state prediction device 4 includes, as a functional configuration realized on the in-vehicle microprocessor by executing the computer programs, 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 acquire speed result information, which is information related to a result of the moving speed (i.e., vehicle speed) of one or more vehicles, based on the route coordinate information 2 and the route traffic information 3. The target speed determination function 6 as a deceleration location prediction unit predicts a deceleration location of the own vehicle based on the acquired speed result information. Note that the term "deceleration" of the "deceleration location" includes stopping or substantially stopping (or substantially stopping) according to the present disclosure. Moreover, "substantially stopping" includes a case where the vehicle speed is temporarily lowered (e.g., within a few seconds) from a vehicle speed during normal travel (e.g., higher than 10 km / h) to a slow speed at which the vehicle can immediately stop or lower, similarly to a case where the vehicle passes an intersection at which the vehicle does not need to temporarily stop. The slow speed refers to a speed of 10 km / h at which the vehicle can stop within 1 meter. The slow speed also includes a very slow speed of several km / h. In other words, "deceleration" of the "deceleration location" refers to a transient deceleration that requires a starting acceleration or a similar increasing acceleration immediately after the transient deceleration.As shown in FIG. 3, the moving speed calculation function 5 according to the present embodiment includes a route information acquisition function 51, a distance acquisition function 52, a moving time acquisition function 53, and a speed calculation function 54. The distance acquisition function 52 is configured to acquire a distance between adjacent points RP located along the scheduled travel route R based on the acquired route coordinate information 2. The moving time acquisition function 53 acquires, based on the acquired route traffic information 3, the moving time between adjacent points RP located along the scheduled travel route R. The speed calculation function 54 is configured to acquire, based on the distance between the points RP acquired by the distance acquisition function 52 and the movement time between the points RP acquired by the movement time acquisition function 53, a movement speed between the points RP as the speed result information. According to the present embodiment, the speed calculation function 54 calculates an average speed of at least one of the resultant vehicle speeds of the vehicle as the moving speed between the points RP.(First Embodiment)FIG. 4 shows an overall functional configuration of the target speed determination function 6 of the traveling state prediction device 4 shown in FIG. 1 according to the first embodiment. Referring to FIG. 4, the target speed determination function 6 according to the first embodiment includes a target speed acquisition function 611, a deceleration determination function 612, and a target speed setting function 613.The target speed acquisition function 611 acquires a temporary target speed at corresponding points RP on the scheduled travel route R. According to the present embodiment, the temporary target speed is a speed limit at the corresponding points RP. The speed limit may be acquired from a map information API service or navigation map data installed on the own vehicle.The deceleration determination function 612 is configured to determine whether each point RP is at a deceleration location, i.e., whether there is a strong degree of deceleration, based on the speed result information. Note that "large deceleration" includes stopping and substantially stopping (or substantially stopping). Whether there is a strong deceleration may be determined according to a change in the average speed. Specifically, the determination of whether there is a strong deceleration may be made based on whether the average speed is below a speed threshold or whether an amount of change in the average speed is higher than a threshold change amount.The target speed setting function 613 is configured to set the target speed of the own vehicle at each point RP based on the temporary target speed acquired by the target speed acquisition function 611 and the deceleration location determined (predicted) by the deceleration determination function 612. Specifically, the target speed setting function 613 sets the target speed to a predetermined stopping speed V 0 when the point RP is at a deceleration point, and sets the target speed to a temporary target speed when the point RP is not at a deceleration point. The stopping speed V0 is Okm / h or a predetermined speed value less than the slow speed, i.e., 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 speed at a start point RPs and an end point RPg to the stopping speed Okm / h.FIGS. 5 to 7 illustrate a specific example of a traveling state prediction device 4 according to the present embodiment, a traveling state prediction method, and a traveling state prediction program executed by the traveling state prediction device 4. Hereinafter, the traveling state prediction device 4 according to the present embodiment, the traveling state prediction method, and the traveling state prediction program executed by the traveling state prediction device 4 will be referred to as "present embodiment". In a flowchart illustrated in FIG. 5, S refers to an abbreviation for step.The same applies to flowcharts in other drawings. In FIG. 6 and similar diagrams, a diagram of a black circle indicates an average speed at each point RP. However, each illustration is only a simple indication for easily describing the present disclosure and does not limit the content of the present disclosure. Therefore, the black circle representation is actually an outline representation and does not correspond to the arrangement of the point RP shown in Fig. 2.In step S 101, the traveling state prediction device 4 acquires the planned route information, i.e., the coordinate information of the planned traveling route R. Step 101 corresponds to the route information acquisition function 51. In step S 102, the traveling state prediction device 4 acquires a distance between adjacent points, i.e., adjacent points RP on the planned traveling route R. Step 102 corresponds to the distance acquisition function 52. In step 103, the traveling state prediction device 4 acquires the movement time between adjacent points. Step 103 corresponds to the movement time acquisition function 53. In step 104, the traveling state prediction device 4 calculates an average speed as a movement speed between adjacent points. Step 104 corresponds to the speed calculation function 54; FIG. 6 is a graph showing an average speed of the respective points RP in the order shown on the scheduled travel route R. Since the target speed is set to the stopping speed, i.e., 0 km / h, at the start point RPs and the end point RPg, the average speed is set to 0 km / h at the start point RPs and the end point RPg. The same applies to the average speed of vehicles in other drawings.In step 105, the traveling state prediction device 4 sets the target speed for the start point RPs and the end point RPg at the corresponding points RP on the planned traveling road R to 0 km / h, and sets the target speed for other points to a temporary target speed, i.e., to a speed limit. Step 105 corresponds to the target speed acquisition function 611 and the target speed setting function 613. In step 106, the traveling 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. An upper part of FIG. 7 shows an example of a determination method for determining whether a large degree of deceleration is present at each point RP. As indicated by an arrow in FIG. 7, in a case where the average speed is lower than a speed threshold value or an amount of decrease in the average speed is higher than a threshold amount, it is possible to determine that there is a large degree of deceleration. The speed threshold value or the threshold value amount may be determined by a computer simulation or an optimization experiment. The speed threshold value may be set to 10-15 km / h, for example. The threshold amount may be set to, for example, 20-30 km / h.In the case where there is a large degree of deceleration (i.e., step 106= JA), the traveling state prediction device 4 executes a process of step 107. In step S 107, the traveling state prediction device 4 sets the target speed at the point RP as a deceleration location where there is a large degree of deceleration to a predetermined stopping speed V 0 as a location indicated by an upward arrow in FIG. 7. Step S 107 corresponds to the target speed setting function 613. In contrast, in the case where a large degree of deceleration is not present (i.e., step 106=NO), the traveling state prediction device 4 skips the process of step 107. In this case, the target speed at the speed limit is maintained as a temporary target speed.According to the present embodiment, speed result information is acquired as information related to a result of the moving speed of one or more vehicles, and a deceleration location of the own vehicle is predicted based on the acquired speed result information. The speed result information is traffic information provided widely or information that can be easily calculated from the traffic information. In the present embodiment, therefore, it is possible to appropriately predict the traveling state of the own vehicle, specifically, a traveling speed pattern or a deceleration location of the own vehicle. Thus, according to the present embodiment, a traveling state prediction technique for the own vehicle having excellent versatility can be provided.(Second Embodiment)FIG. 8 shows an overall functional configuration of a target speed determination function 6 according to a second embodiment of the traveling state prediction device 4 shown in FIG. 1 ; referring to FIG. 8, the target speed determination function 6 according to the present embodiment 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 a 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, the following mainly describes the respective functional configurations of the reference speed acquisition function 622, the speed difference determination function 623, and the target speed acquisition function 624.The reference speed acquisition function 622 is configured to acquire a reference speed as a moving speed of the vehicle during non-stop at each point RP. Note that the "moving speed of the vehicle during non-stop" refers to an expected moving speed (e.g., speed limit) of the vehicle at each point RP during a normal traffic condition in which no traffic obstruction such as traffic regulation or traffic congestion occurs. The speed difference determination function 623 is configured to calculate a relationship between the reference speed and the average speed, i.e., a ratio or a difference therebetween. Further, the speed difference determination function 623 is configured to determine whether the calculated ratio or the difference exceeds a threshold value. Specifically, the speed difference determination function 623 determines a deceleration location as a point RP at which the calculated ratio or difference exceeds the threshold value.The target speed setting function 624 sets the target speed of the own vehicle at each point RP based on a determination result of the speed difference determination function 623. Specifically, the target speed setting function 624 sets the target speed to the predetermined stopping speed V 0 when the point RP is a deceleration location, and sets the target speed to a temporary target speed when the point RP is not a deceleration location.FIGS. 9 to 12 illustrate a specific example of a traveling state prediction device 4 according to the present embodiment, a traveling state prediction method, and a traveling state prediction program executed by the traveling state prediction device 4. Note that the contents of steps 201 to 204 in the flowchart shown in FIG. 9 are the same as those in steps 101 to 104 of the flowchart shown in FIG. 5. Therefore, the explanations about steps 101 to 104 of the above-described first embodiment are applied to the contents of steps 201 to 204, and the processes subsequent to step 204 will be described below.The traveling state prediction device 4 sets the target speed for the start point RPs and the end point RPg at corresponding points RP on the planned traveling road R to 0 km / h, and sets the target speed for other points to a temporary target speed, i.e., a speed limit. Step 205 corresponds to the target speed acquisition function 621 and the target speed setting function 624. In step 206, as shown in FIG. 10, the traveling state prediction device 4 acquires a speed limit as a reference speed of each point RP. Step 206 corresponds to the reference speed acquisition function 622. In step 207, the traveling state prediction device 4 calculates a speed difference ΔV as a difference between the reference speed and the average speed. The difference between the reference speed and the average speed is a difference between the reference speed indicated by a solid line in FIG. 11 and the average speed indicated by a dotted line in FIG. 11. In step 208, the traveling state prediction device 4 determines whether the speed difference ΔV exceeds a threshold speed difference ΔVth. Step 207 and step 208 correspond to the speed difference determination function. The threshold speed difference ΔVth may be determined by a computer simulation or an optimization experiment. The threshold speed difference ΔVth may be set to 20-30 km / h.When the speed difference ΔV exceeds the threshold speed difference ΔVth (i.e., step 208= JA), the traveling state prediction device 4 executes a process in step 209. In step 209, the traveling state prediction device 4 determines a point RP at which the speed difference ΔV exceeds the threshold speed difference ΔVth as a deceleration point, and sets the target speed of the point RP as a deceleration point to the stopping speed V 0. Step 209 corresponds to the target speed setting function 624. In contrast, when the speed difference ΔV is less than or equal to the threshold speed difference ΔVth (i.e., step 208=NO), the traveling state prediction device 4 skips the process of step 209. In this case, the target speed at the speed limit is maintained as a temporary target speed. Thus, as shown in FIG. 12, the traveling state prediction device 4 sets the final target speed at the corresponding points RP according to the processing result of step 205 and the determination result of step 208.The present embodiment predicts the deceleration point based on a relationship between the reference speed as the moving speed during non-stop and the average speed. Thus, the deceleration location such as a stop location can be accurately predicted. Therefore, the present embodiment is capable of providing a traveling state prediction technique of an own vehicle that is excellent in versatility and prediction accuracy.(Third Embodiment)FIG. 13 shows an overall functional configuration of a target speed determination function 6 in the traveling state prediction device 4 shown in FIG. 1 according to the third embodiment. Referring to FIG. 13, the target speed determination function 6 according to the present embodiment includes the 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 a temporary target speed at each point RP. That is, the target speed acquisition function 621 is similar to the target speed acquisition function 611 of the first embodiment described above. Therefore, the following mainly describes the respective functional configurations of the deceleration probability acquisition function 632 and the target speed setting function 633.The deceleration probability acquisition function 632 is configured to acquire a deceleration probability of the vehicle at each point RP. The deceleration probability refers to an occurrence probability of stopping or substantially stopping (or substantially stopping) the vehicle at the corresponding points RP during a normal traffic condition in which no traffic obstruction such as traffic regulation or traffic congestion occurs. The deceleration probability may be determined based on a recorded vehicle running state at each point RP. Specifically, the deceleration probability may be determined according to history information of a result of the moving speed at corresponding points RP of one or more vehicles. More specifically, a speed change parameter is defined as a change in the average speed, i.e., an amount of decrease in the average speed, or a relationship (e.g., a difference) between the reference speed as a moving speed during non-stop and the average speed. A statistical process is applied to a correlation between a speed change parameter and a state of occurrence of the stop or the substantial stop of the vehicle, thereby obtaining a map or a formula indicating a relationship between the speed change parameter and the deceleration probability. The map or overview or the formula can be calculated, for example, in a server or the like located outside the ego vehicle. The map or the formula is read by the server or the like at an appropriate time and thereby used in the own vehicle. Moreover, the deceleration probability acquisition function 632 is capable of acquiring the deceleration probability at corresponding points RP based on the map or the formula and the speed change parameter at corresponding points RP.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 a probability threshold. In other words, the deceleration probability acquisition function 632 determines whether each point RP is located at a deceleration location. Then, the target speed setting function 633 sets the target speed of the own 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 a stopping speed V 0 when the point RP is at a deceleration point, and sets the target speed to a temporary target speed when the point RP is not at a deceleration point.FIGS. 14 to 17 illustrate a specific example of a traveling state prediction device 4 according to the present embodiment, a traveling state prediction method, and a traveling state prediction program executed by the traveling state prediction device 4. Note that the contents of steps 301 to 304 in the flowchart shown in FIG. 14 are the same as in steps 101 to 104 of the flowchart shown in FIG. 5. Therefore, the explanations about steps 101 to 104 of the above-described first embodiment are applied to the contents of steps 301 to 304, and the processes subsequent to step 304 will be described below.In step 305, the traveling state prediction device 4 sets the target speed for the start point RPs and the end point RPg at corresponding points RP on the planned traveling road R to 0 km / h, and sets the target speed for other points to a temporary target speed, i.e., a speed limit. Step 305 corresponds to the target speed acquisition function 631 and the target speed setting function 633. In step 306, the traveling state prediction device 4 acquires a deceleration probability at each point RP. According to the present specific example, as shown in FIG. 15, the deceleration probability is calculated using an amount of decrease in the average speed. In step 307, the traveling state prediction device 4 determines whether there is a large degree of deceleration at each point RP. That is, the traveling state prediction device 4 determines whether the deceleration probability at each point RP exceeds the probability threshold based on the map shown in FIG. 16 indicating a relationship between the deceleration probability and the amount of decrease in the average speed. Step 306 and step 307 correspond to the deceleration probability acquisition function 632.In the case where the deceleration probability exceeds the probability threshold (i.e., step 307= JA), the traveling state prediction device 4 executes a process in step 308. In step 308, the traveling state prediction device 4 uses a point RP whose deceleration probability exceeds the speed threshold value as a deceleration location, and sets the target speed of the point RP as the deceleration location to a predetermined stopping speed V 0. Step 308 corresponds to the target speed setting function 633. In contrast, when the deceleration probability does not exceed the probability threshold (i.e., step 307=NO), the traveling state prediction device 4 skips the process in step 308. In this case, the target speed at the speed limit is maintained as a temporary target speed. Thus, as shown in FIG. 17, the traveling state prediction device 4 sets the final target speed at the corresponding points RP according to the processing result of step 305 and the processing result of step 308, based on the determination result of step 307.(Modification Example)The present disclosure is not limited to the above-described embodiments and specific examples. Therefore, the above-described embodiments can be appropriately modified. Typical modification examples will be described below. In the following modification examples, configurations different from those of the above-described embodiments will be mainly described. Further, the same reference numerals are used for the same or equivalent configurations between the above-described embodiments or modification examples. Therefore, in the following modification examples, the explanations to the above-described embodiments are applied to constituent elements having the same reference numerals as those in the above-described embodiments unless there are technical inconsistencies or additional explanations.The present disclosure is not limited to any particular use or device configuration described in the above-described embodiments. For example, the driving state prediction device 4 can be used for various purposes including prediction of a vehicle driving energy or the remaining battery capacity (i.e., SOC). Further, part or some of the configurations of the traveling state prediction device 4 may be provided in a server outside the own vehicle. Specifically, for example, the movement speed calculation function 5 may be provided in a server outside the own vehicle.Moreover, part or some of the configurations of the driving state prediction device 4 may be a digital circuit configured to be able to perform the above-described functions or operations, for example, may be configured as an ASIC (application specific integrated circuit) or an FPGA (field programmable gate array). In the traveling state prediction device 4, a microprocessor part on the vehicle side and a digital circuit part may be coexisted.Note that programs according to the present disclosure that can execute various operations, procedures, or processes described in the above embodiments can be downloaded or updated via V2X communication. V2X is an abbreviation for vehicle to X. Further, the programs may be downloaded or updated via terminals provided in a production facility, a maintenance facility, a dealer of the own vehicle, and the like. The programs may be stored on a memory card, an optical disk, a magnetic disk, and the like.The respective function configurations and processes described above may be executed by a dedicated computer consisting of a processor and a memory programmed to execute one or more functions embodied by computer programs. Alternatively, the respective functional configurations and processes described above may be executed by a dedicated computer provided by a processor configured from one or more dedicated hardware logic circuits. Further, the above-described function configurations and processes may be executed by one or more dedicated computers in which a processor and a memory programmed to execute one or more functions and a processor configured of one or more hardware logic circuits are combined. Moreover, the computer programs may be stored in the form of opcodes executed by the computer on a computer readable, non-transitory, tangible recording medium. That is, the above-described respective function configurations and processes may be expressed by computer programs including processes for realizing the above-described respective function configurations and processes, or by a computer-readable non-transitory tangible recording medium storing the programs.The present disclosure is not limited to specific operation modes described in the above-described embodiments. Specifically, for example, all points RP may be acquired as traffic information that is the moving time between adjacent points RP. Further, the order of execution of the process in step 102 and the process in step 103 may be reversed as shown in FIG. 5, or these processes may be executed simultaneously. Moreover, various graphs illustrated in FIG. 6 and the like are provided merely for describing the present disclosure, and do not limit the content of the present disclosure. Further, a relationship between each function configuration and the corresponding step in the flowchart may be changed as appropriate. In other words, for example, step 208 may correspond to the desired speed setting function 624. Further, the stopping speed V 0 may be changed between types of stopping locations. Specifically, the stopping speed V 0 may be set to, for example, V 0=Okm / h for the stopping location where the vehicle needs to temporarily stop and V 0>Okm / h for the stopping location where the vehicle does not need to stop. In the case of an intersection without signals where temporary stop is required depending on the situation, the stop speed V 0 may be set to V 0>Okm / h. Also for the stopping location at which the stopping speed V0≠Okm / h, the stopping speed can be changed depending on the corresponding traffic situation.Note that the terms such as "acquisition", "calculation", "estimation", "acquisition", "determination" and the like used in this specification can be appropriately interchanged as long as there is no technical inconsistency. The terms "acquisition" and "extraction" can also be exchanged with one another in a suitable manner as long as no technical inconsistency exists. Furthermore, "above the threshold value" or "exceeding the threshold value" and "greater than or equal to the threshold value" can be exchanged with one another in a suitable manner as long as no technical inconsistency exists. The same applies to "less than the threshold" and "less than or equal to the threshold".In the above-described embodiments, the elements constituting the embodiments are not necessarily required unless the elements are clearly specified as necessary or theoretically necessary. Also, in the case where numerical values such as the number of constituent elements, numerical values, amount, range, or the like are mentioned in the above-described embodiments, it is not limited to the specific values unless it is specified as necessary or theoretically limited to specific numbers. In the case where materials, shapes, directions, positional relationships, and the like are mentioned for the constituent elements in the above-described embodiments, it is not limited to the material, the directions, the shapes, and positional relationships unless they are uniquely specified or theoretically limited to specific materials, shapes, directions, positional relationships, and the like.The modification examples are not limited to the above-described examples. For example, all or a part of one example of a plurality of specific examples may be mutually combined with all or a part of another example, provided that there is no technical inconsistency. The number of combinations is not particularly limited. Similarly, all or a part of one example among a plurality of modification examples may be mutually combined with all or a part of another example as long as there is no technical inconsistency. Further, all or a part of the specific examples may be combined with all or a part of the above-described modification examples as long as there is no technical inconsistency.(Configurations)As apparent from the above-described embodiments and modification examples, at least the following configurations are disclosed in the present specification.[Configuration 1-1]A driving state prediction device (4) predicting a driving state of an own vehicle, comprising:a moving speed acquisition unit ( 5) that acquires speed result information as information related to a result of a moving speed of one or more vehicles; anda deceleration location prediction unit ( 6) that predicts a deceleration location of the own vehicle based on the acquired speed result information.[Configuration 1-2]The traveling state prediction device according to Configuration 1-1, wherein the speed result information is an average speed.[Configuration 1-3]The traveling state prediction device according to Configuration 1-2, wherein the deceleration location prediction unit predicts the deceleration location based on a change in the average speed.[Configuration 1-4]The traveling state prediction device according to Configurations 1- 3, wherein the deceleration location prediction unit predicts the deceleration location based on whether the average speed is lower than a speed threshold or whether an amount of change in the average speed is higher than a threshold change amount.[Configuration 1-5]The traveling state prediction device according to Configuration 1-2, wherein the traveling state prediction device includes a reference speed acquisition unit (622) that acquires a reference speed that is a moving speed of a vehicle during non-stop; and the deceleration location prediction unit predicts the deceleration location based on a relationship between the reference speed and the average speed.[Configuration 1-6]The driving state prediction device according to Configurations 1-5, wherein the relationship is a ratio or a difference therebetween.[Configuration 1-7]The traveling state prediction device according to Configuration 1-2, wherein the traveling state prediction device includes a deceleration probability acquisition unit (632) that acquires a deceleration probability calculated based on a change in the average speed or a relationship between a reference speed, which is a moving speed of a vehicle during non-stopping, and the average speed; and the deceleration location prediction unit predicts the deceleration location based on the deceleration probability.[Configuration 1-8]The traveling state prediction device according to Configurations 1- 7, wherein the deceleration location prediction unit predicts the deceleration location based on whether the deceleration probability is lower than a probability threshold.[Configuration 1-9]The driving state prediction device according to Configurations 1-7 or 1-8, wherein the deceleration probability is calculated based on history information of a result of a moving speed of one or more vehicles at a predetermined location.[Configuration 2-1]A method of predicting a traveling state of an own vehicle, comprising:acquiring speed result information as information related to a result of a moving speed of one or more vehicles; andpredicting a deceleration location of the own vehicle based on the acquired speed result information.[Configuration 2-2]The method according to configuration 2-1, wherein the speed result information is an average speed.[Configuration 2-3]The method according to configuration 2-2, wherein the method predicts the deceleration location based on a change in the average speed.[Configuration 2-4]The method according to configuration 2- 3, wherein the method predicts the deceleration location based on whether the average speed is lower than a speed threshold value or whether an amount of change in the average speed is higher than a threshold change amount.[Configuration 2-5]The method according to configuration 2- 2, wherein the method acquires a reference speed that is a moving speed of a vehicle during non-stop; and predicts the deceleration location based on a relationship between the reference speed and the average speed.[Configuration 2-6]The method according to configurations 2-5, wherein the relationship is a ratio or a difference therebetween.[Configuration 2-7]The method according to configuration 2- 2, wherein the method acquires a deceleration probability calculated based on a change in the average speed or a relationship between a reference speed, which is a moving speed of a vehicle during non-stop, and the average speed; and predicts the deceleration location based on the deceleration probability.[Configuration 2-8]The method according to configurations 2-7, wherein the method predicts the deceleration location based on whether the deceleration probability is lower than a probability threshold.[Configuration 2-9]The method according to configuration 2-7 or 2-8, wherein the method calculates deceleration probability based on history information of a result of a moving speed of one or more vehicles at a predetermined location.[Configuration 3-1]A driving state prediction program executed by a driving state prediction device (4) predicting a driving state of an own vehicle, comprising:a moving speed acquisition process that acquires speed result information as information related to a result of a moving speed of one or more vehicles; anda deceleration location prediction process predicting a deceleration location of the own vehicle based on the acquired speed result information.[Configuration 3-2]The program according to configuration 3-1, wherein the speed result information is an average speed.[Configuration 3-3]The program according to the configuration 3-2, wherein the deceleration location is predicted based on a change in the average speed in the deceleration location prediction process.[Configuration 3-4]The program according to Configuration 3-3, wherein the deceleration location is predicted based on whether the average speed is lower than a speed threshold or whether an amount of change in the average speed is higher than a threshold change amount, in the deceleration location prediction process.[Configuration 3-5]The program according to Configuration 3-2, wherein the program includes a reference speed acquisition process that acquires a reference speed that is a moving speed of a vehicle during non-stop; and the deceleration location is predicted based on a relationship between the reference speed and the average speed in the deceleration location prediction process.[Configuration 3-6]The program according to the configuration 3-5, wherein the relationship is a ratio or a difference therebetween.[Configuration 3-7]The program according to Configuration 3-2, wherein the program includes a deceleration probability acquisition process that acquires a deceleration probability predicted based on a change in the average speed or a relationship between a reference speed that is a moving speed of a vehicle during non-stopping; and the deceleration location based on the deceleration probability in the deceleration location prediction process.[Configuration 3-8]The program according to Configuration 3-7, wherein the deceleration location is predicted based on whether the deceleration probability is lower than a probability threshold value, in the deceleration probability acquisition process.[Configuration 3-9]The program according to Configuration 3-7 or 3-8, wherein the deceleration probability is calculated based on history information of a result of a moving speed of one or more vehicles at a predetermined location.References included in the specificationThis list of documents cited by the applicant has been produced in an automated manner and is only included for the better information of the reader. The list is not part of the German patent application or utility model application. The DPMA does not take any adhesion for any faults or omissions.Patent Literature citedJP-A-2009-67350

[0002]

Claims

A traveling state prediction device (4) predicting a traveling state of an own vehicle, comprising: a moving speed acquisition unit (5) acquiring speed result information as information related to a result of a moving speed of one or more vehicles; and a deceleration location prediction unit (6) predicting a deceleration location of the own vehicle based on the acquired speed result information.The driving state prediction device according to claim 1, wherein the speed result information is an average speed.The traveling state prediction device according to claim 2, wherein the deceleration location prediction unit predicts the deceleration location based on a change in the average speed.The traveling state prediction device according to claim 3, wherein the deceleration location prediction unit predicts the deceleration location based on whether the average speed is lower than a speed threshold value or whether an amount of change in the average speed is higher than a threshold change amount.The traveling state prediction device according to claim 2, wherein the traveling state prediction device includes a reference speed acquisition unit (622) that acquires a reference speed that is a moving speed of a vehicle during non-stopping; and the deceleration location prediction unit predicts the deceleration location based on a relationship between the reference speed and the average speed.The driving state prediction device according to claim 5, wherein the relationship is a ratio or a difference therebetween.The traveling state prediction device according to claim 2, wherein the traveling state prediction device includes a deceleration probability acquisition unit (632) that acquires a deceleration probability calculated based on a change in the average speed or a relationship between a reference speed, which is a moving speed of a vehicle during non-stopping, and the average speed; and the deceleration location prediction unit predicts the deceleration location based on the deceleration probability.The traveling state prediction device according to claim 7, wherein the deceleration location prediction unit predicts the deceleration location based on whether the deceleration probability is lower than a probability threshold.The driving state prediction device according to claim 7 or 8, wherein the deceleration probability is calculated based on history information of a result of a moving speed of one or more vehicles at a predetermined location.A method of predicting a traveling state of an own vehicle, comprising: acquiring speed result information as information related to a result of a moving speed of one or more vehicles; and predicting a deceleration location of the own vehicle based on the acquired speed result information.A traveling state prediction program executed by a traveling state prediction device (4) predicting a traveling state of an own vehicle, comprising: a moving speed acquisition process that acquires speed result information as information related to a result of a moving speed of one or more vehicles; and a deceleration location prediction process that predicts a deceleration location of the own vehicle based on the acquired speed result information.

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