Travel energy estimating device, travel energy estimating method, and computer program

Abstract

A travel energy estimating device according to the present disclosure comprises: a route acquiring unit for acquiring a route comprising road links along which a target vehicle, being an electric automobile, is planning to travel; a route dividing unit for dividing the route into one or more sectors including a speed change expected location at which a traveling speed of the target vehicle is expected to change, each sector comprising one or a plurality of the road links; a speed model acquiring unit for acquiring a speed model representing a transition over time in the traveling speed of the target vehicle, for each sector; and a travel energy estimating unit for estimating travel energy of the target vehicle when traveling along the route, on the basis of the speed models acquired for each sector.

Description

Traveling energy estimation device, traveling energy estimation method, and computer program

[0001] This disclosure relates to a driving energy estimation device, a driving energy estimation method, and a computer program. This application claims priority to Japanese Application No. 2022-083504 filed on May 23, 2022, and incorporates by reference all of the contents of that application.

[0002] In recent years, electric vehicles have been attracting attention due to the constraints on natural resource production and growing concern about environmental issues. Electric vehicles run by driving an electric motor using power supplied from a battery such as a lithium-ion battery.

[0003] In addition, the use of green electricity generated using renewable energy sources such as solar and wind power is becoming increasingly important. In order to actively use green electricity to reduce CO2 emissions, it is necessary to strike a balance between green electricity and the energy required to run electric vehicles. Therefore, it is important not only to predict the amount of green electricity generated, but also to estimate the energy required to run electric vehicles with high accuracy.

[0004] Electric vehicles have a shorter range than gasoline-powered vehicles, which run on gasoline engines. Furthermore, once the battery runs out of power and the vehicle is no longer able to run (i.e., it is difficult to go to a charging station to purchase electricity, as is the case with gasoline). Therefore, it is important to maintain the operation of an electric vehicle while preventing the battery from running out of power.

[0005] Conventionally, a notification device has been proposed that determines whether charging is necessary and notifies the user of the result of the determination (see, for example, Patent Document 1). In this notification device, in order to prevent the user from running out of battery, charging stations along the route to the destination are displayed on a display screen.

[0006] In addition, a route search device has been proposed that estimates the amount of power consumed by an electric vehicle when traveling a searched route for each of multiple driving modes and displays an operation plan for each driving mode on a display device (see, for example, Patent Document 2).

[0007] JP 2018-77062 A JP 2014-35295 A

[0008] A traveling energy estimation device according to one aspect of the present disclosure includes a route acquisition unit that acquires a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; a route division unit that divides the route into one or more sections each consisting of one or more road links, the sections including predicted speed change points where a change in the traveling speed of the target vehicle is expected; a speed model acquisition unit that acquires a speed model that indicates the temporal progression of the traveling speed of the target vehicle for each section; and a traveling energy estimation unit that estimates the traveling energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0009] A driving energy estimation method according to another aspect of the present disclosure includes a step in which a driving energy estimation device acquires a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; a step in which the driving energy estimation device divides the route into one or more sections each consisting of one or more of the road links, the sections including predicted speed change points where a change in the driving speed of the target vehicle is expected; a step in which the driving energy estimation device acquires a speed model for each section that indicates the temporal progression of the driving speed of the target vehicle; and a step in which the driving energy estimation device estimates the driving energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0010] A computer program according to another aspect of the present disclosure causes a computer to function as a route acquisition unit that acquires a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; a route division unit that divides the route into one or more sections each consisting of one or more road links, the sections including predicted speed change points where a change in the travel speed of the target vehicle is expected; a speed model acquisition unit that acquires a speed model that indicates the temporal progression of the travel speed of the target vehicle for each section; and a travel energy estimation unit that estimates the travel energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0011] FIG. 1 is an overall configuration diagram of a traveling energy estimation system according to an embodiment of the present disclosure. FIG. 2 is a block diagram illustrating an example of the configuration of a traffic information providing server according to an embodiment of the present disclosure. FIG. 3 is a block diagram illustrating an example of the configuration of an in-vehicle device according to an embodiment of the present disclosure. FIG. 4 is a block diagram illustrating an example of the configuration of a traveling energy estimation server according to an embodiment of the present disclosure. FIG. 5 is a diagram illustrating an example of a speed model for a guide section in which an upstream guide is a right / left turn point. FIG. 6 is a diagram illustrating an example of a speed model for a guide section in which an upstream guide is a traffic signal installation point. FIG. 7 is a diagram illustrating an example of a speed model for a guide section in which neither the upstream guide nor the downstream guide is a right / left turn point or a traffic signal installation point. FIG. 8 is a diagram illustrating an example of a speed model in which the upstream guide is neither a right / left turn point nor a traffic signal installation point, and the downstream guide is a traffic signal installation point. FIG. 9 is a diagram illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. FIG. 10 is a diagram illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. FIG. 11 is a diagram illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. FIG. 12 is a sequence diagram showing an example of processing of the traveling energy estimation system according to an embodiment of the present disclosure. FIG. 13 is a diagram showing an example of a searched route searched by the traveling energy estimation server 5. FIG. 14 is an enlarged diagram of a portion of the searched route shown in FIG. 13 , surrounded by a dashed circle. FIG. 15 is a diagram showing an example of a guide set on the searched route by the guide section division process. FIG. 16 is a diagram showing guide section data generated by the guide section division process. FIG. 17 is a diagram showing an example of route information, traveling energy information, and electricity consumption information displayed on a display. FIG. 18 is a flowchart showing details of the speed model calculation process (step S17 in FIG. 12 ). FIG. 19 is a diagram showing speed changes based on a speed model calculated by the traveling energy estimation server when a target vehicle travels the searched route. FIG. 20 is a diagram showing speed changes when the target vehicle actually travels the same searched route as in FIG. 19 .

[0012] [Problem to be Solved by the Present Disclosure] As described above, from the perspective of proactively utilizing green power and preventing electric vehicles from running out of power while they are running, it is necessary to estimate the running energy while they are running with high accuracy.

[0013] The notification device described in Patent Document 1 does not specifically disclose a method for estimating the traveling energy.

[0014] In addition, the route search device described in Patent Document 2 assumes driving modes classified by upper limits of at least one of speed and acceleration, such as sports mode, eco mode, and normal mode, and estimates the amount of power consumption (driving energy) for each driving mode.

[0015] However, when an electric vehicle actually travels on a road, it may be difficult to travel in the pre-determined driving mode due to the influence of traffic conditions, etc. This may result in a discrepancy between the estimated driving energy and the actual driving energy.

[0016] In addition, conventional route search methods define costs in terms of distance and time for each road link, and calculate the route that minimizes the cost. Here, a road link is network data used to search for a vehicle's route, and is stored in a map database. Road links generally represent directional roads separated by points where road attributes change, such as intersections, transitions between expressways and ordinary roads, and tunnel entrances and exits.

[0017] Meanwhile, calculation of the energy consumed by an electric vehicle traveling along a route has also been considered, similar to route search, for each road link. In other words, it was thought that if the predicted traveling speed of an electric vehicle was calculated for each road link and the traveling energy was estimated using the predicted traveling speed, it would be possible to calculate the traveling energy with a certain degree of accuracy.

[0018] However, the method of estimating the driving energy for each road link does not provide the accuracy required for specific purposes, such as actively utilizing green power, such as supplying power from electric vehicles to a power grid.

[0019] After careful consideration, the inventors have concluded that, in order to estimate driving energy with higher accuracy, a method of estimating driving energy on a road link basis, assuming that acceleration and deceleration occur on a road link basis, is not appropriate.

[0020] For example, if the travel speed of an electric vehicle is predicted by averaging the travel speeds of multiple vehicles on a road link basis, acceleration and deceleration will be expressed by the speed difference between road links. However, this method of expression makes it difficult to accurately express acceleration and deceleration associated with stopping and starting, which are dominant factors in energy consumption.

[0021] Furthermore, even if acceleration and deceleration were expressed on a road link basis, stopping due to a red traffic light usually occurs after traveling multiple travel links, and expressing the situation on a road link basis would unnecessarily divide the expression, making it inefficient and cumbersome. Specifically, road links are created based on points between branches for route calculation purposes, and in urban areas with many branches, the distance between road links is often less than 100 meters. It takes about 12 seconds for a vehicle traveling at 30 km / h to travel 100 meters, but it is unlikely that the vehicle would stop every 12 seconds or so; instead, it is common for vehicles to stop due to a traffic light every few tens of seconds.

[0022] Therefore, the inventors discovered that since acceleration and deceleration, which have the greatest impact on the driving energy of an electric vehicle, do not occur on a road link basis, energy calculations can be performed efficiently and with high precision by setting a unit of acceleration and deceleration separate from the road link unit.

[0023] The present disclosure has been made in consideration of the above circumstances, and aims to provide a driving energy estimation device, a driving energy estimation method, and a computer program that can estimate with high accuracy the driving energy of an electric vehicle when traveling along a route.

[0024] Effect of the Present Disclosure According to the present disclosure, it is possible to estimate the traveling energy of an electric vehicle traveling along a route with high accuracy.

[0025] [Definition of Terms such as Processor] The embodiments of the present disclosure described below may be realized by an apparatus, a system, a method, an integrated circuit, a computer program, or a computer-readable non-transitory recording medium, or any combination thereof. The recording medium may be either volatile or non-volatile. The apparatus may be composed of multiple individual devices. When composed of multiple individual devices, they may be arranged in a single housing or may be arranged separately in two or more separate housings.

[0026] The processor (such as the control units 30, 50, and 80 described below) may be, for example, a semiconductor integrated circuit including a central processing unit (CPU). The processor may be realized by at least one microprocessor or microcontroller. Alternatively, the processor may be realized by a field programmable gate array (FPGA) equipped with a CPU, a graphics processing unit (GPC), an application specific integrated circuit (ASIC), an application specific standard product (ASSP), or a combination of two or more circuits selected from these.

[0027] A processor performs desired processing by loading a computer program, which contains instructions for at least one process stored in a read-only memory (ROM), into a random access memory (RAM) and executing the program. The RAM provides a working area for loading the control program stored in the ROM at boot time. The RAM does not need to be a single storage medium, but may be a collection of multiple storage media.

[0028] A processor can function as various functional units depending on the type of instructions (computer program) it executes. For example, when executing a program that calculates information X, it functions as a "calculation unit" of information X. When executing a program that acquires information X, it functions as an "acquisition unit" of information X. When executing a program that generates information X, it functions as a "generation unit" of information X.

[0029] The "acquisition unit" as a functional unit of a processor may calculate or generate information X by itself, or may receive information X as input from another integrated circuit that has calculated or generated the information. In other words, "acquisition" when a processor executes a predetermined set of instructions includes both a case in which one integrated circuit calculates or generates some information by itself, and a case in which another integrated circuit calculates or generates some information and the information is input to one integrated circuit. Therefore, the "acquisition unit" in this embodiment is a generic concept that encompasses a "calculation unit" and a "generation unit."

[0030] The ROM may be, for example, a writable memory (e.g., a PROM), a rewritable memory (e.g., a flash memory), or a read-only memory. The ROM stores a program that controls the operation of the processor. The ROM does not have to be a single storage medium, but may be a collection of multiple storage media. Part of the collection of multiple storage media may be removable memory.

[0031] [Outline of Embodiments of the Present Disclosure] First, an outline of embodiments of the present disclosure will be described. (1) A traveling energy estimation device according to one embodiment of the present disclosure includes a route acquisition unit that acquires a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel, a route division unit that divides the route into one or more sections each consisting of one or more road links, the sections including speed change prediction points where a change in the traveling speed of the target vehicle is predicted, a speed model acquisition unit that acquires a speed model indicating a change in the traveling speed of the target vehicle over time for each section, and a traveling energy estimation unit that estimates traveling energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0032] According to this configuration, the route is divided into one or more sections, each consisting of one or more road links, based on the predicted speed change points. Therefore, the section length is guaranteed to always be equal to or greater than the road link length, and the section can be configured to include the predicted speed change points. Therefore, the route can be divided into sections for which the travel energy can be estimated with high accuracy without dividing the route more than necessary. Furthermore, a speed model is provided for each section that includes a predicted speed change point. Therefore, speed change events, such as acceleration or deceleration of the target vehicle that occur at the relevant point or section, can be reflected in the speed model. By estimating the travel energy based on the speed model that reflects such speed change events, the travel energy of the target vehicle, which is an electric vehicle, traveling along the route can be estimated with high accuracy.

[0033] (2) In the above (1), the speed change predicted point may include a point that is to be notified of route guidance to the driver of the target vehicle.

[0034] For example, route guidance systems such as car navigation systems usually guide (notify) the driver of a point upstream of a point where a change in vehicle speed is expected by voice, etc. Therefore, by dividing the section so that it includes such a point, it is possible to estimate with high accuracy the traveling energy of the target vehicle while traveling the route.

[0035] (3) In the above (1) or (2), the speed change predicted point may include a traffic signal installation point.

[0036] At locations where traffic signals are installed, the target vehicle continuously decelerates, stops, and accelerates. Therefore, by using a speed model that models these events, the running energy can be estimated with high accuracy.

[0037] (4) In (3) above, the speed model acquisition unit may calculate a first speed model that represents the target vehicle starting off after stopping in the section that includes a traffic light installation location where a stop due to a red light is scheduled.

[0038] This configuration allows for generalized modeling of the speed change of a target vehicle in a section that includes a point where a traffic signal is installed, thereby enabling a simple method for estimating the running energy.

[0039] (5) In (4) above, the first speed model may represent that the target vehicle decelerates from a first speed to a speed of zero, then maintains the speed of zero for a predetermined period of time, and then accelerates from the speed of zero to a second speed after maintaining the speed of zero.

[0040] This configuration allows for generalized modeling of the speed change of a target vehicle in a section that includes a point where a traffic signal is installed, thereby enabling a simple method for estimating the running energy.

[0041] (6) In the above (5), at least one of the first speed and the second speed may indicate a representative traveling speed of a vehicle traveling in the section.

[0042] With this configuration, the speed model can be calculated using a statistically calculated representative traveling speed, such as the average speed of vehicles traveling in a section, etc. Therefore, a speed model that corresponds to the actual traveling speed can be calculated, and traveling energy can be estimated with high accuracy.

[0043] (7) In (5) or (6) above, the above-mentioned traveling energy estimation device may further include a speed correction unit that corrects at least one of the first speed and the second speed based on regulation information that regulates the traveling of the target vehicle on the route.

[0044] According to this configuration, each speed can be corrected when calculating the speed model based on the regulation information. Therefore, the speed model can be calculated taking regulation information into account, and the traveling energy can be estimated with high accuracy.

[0045] (8) In any of (4) to (7) above, the speed model acquisition unit may determine, in a plurality of sections each including a plurality of traffic signal installation points where a stop due to a red light is scheduled, based on parameters that define the signal display.

[0046] With this configuration, for example, it is possible to estimate the location of a traffic signal where the vehicle is scheduled to stop among multiple traffic signals with synchronized signal display offsets. Therefore, a speed model for stopping only at a traffic signal location where the vehicle is scheduled to stop can be calculated, and a speed model for passing through a traffic signal location where the vehicle is not scheduled to stop without stopping can be calculated. This allows for highly accurate estimation of driving energy. Note that instead of multiple traffic signals with synchronized offsets, it is also possible to use multiple traffic signals with synchronized signal parameters, such as signal display cycles.

[0047] (9) In any of the above (1) to (8), the speed change predicted point may include a right / left turning point where the target vehicle turns right or left.

[0048] At turning points, the target vehicle continuously decelerates and accelerates. Therefore, by using a speed model that models these events, the traveling energy can be estimated with high accuracy.

[0049] (10) In the above (9), the speed model acquisition unit may calculate a second speed model that represents deceleration and acceleration of the target vehicle in the section that includes a right or left turn point.

[0050] This configuration allows for generalized modeling of the speed change of the target vehicle in a section that includes a right or left turn, thereby enabling a simple method for estimating the traveling energy.

[0051] (11) In (10) above, the second speed model may represent that the target vehicle decelerates from a third speed to a fourth speed, and then accelerates from the fourth speed to a fifth speed.

[0052] This configuration allows for generalized modeling of the speed change of the target vehicle in a section that includes a right or left turn, thereby enabling a simple method for estimating the traveling energy.

[0053] (12) In the above (11), at least one of the third speed and the fifth speed may indicate a representative traveling speed of a vehicle traveling in the section.

[0054] With this configuration, the speed model can be calculated using a statistically calculated representative traveling speed, such as the average speed of vehicles traveling in a section, etc. Therefore, a speed model that corresponds to the actual traveling speed can be calculated, and traveling energy can be estimated with high accuracy.

[0055] (13) In (11) or (12) above, the above-mentioned traveling energy estimation device may further include a speed correction unit that corrects any of the third speed, the fourth speed, and the fifth speed based on regulation information that regulates the traveling of the target vehicle on the route.

[0056] According to this configuration, each speed can be corrected when calculating the speed model based on the regulation information. Therefore, the speed model can be calculated taking regulation information into account, and the traveling energy can be estimated with high accuracy.

[0057] (14) In any of (1) to (12) above, the speed model acquisition unit may calculate a third speed model including a temporal progression of the speed at which the target vehicle maintains the sixth speed in the section including a speed change prediction point that is neither a traffic signal installation point nor a right / left turn point where the target vehicle turns right or left.

[0058] This configuration makes it possible to generalize and model changes in traveling speed in sections that include points where caution is required when traveling, such as points where road types change, road junctions or forks, or sharp curves, and where there is a high possibility of sudden acceleration or deceleration occurring when passing through those points, thereby enabling a simple method of estimating traveling energy.

[0059] (15) In (14) above, the speed model acquisition unit may calculate the third speed model, which indicates that the target vehicle will stop at the end of a section that includes a traffic signal installation point and a speed change predicted point that does not correspond to either a traffic signal installation point or a right / left turn point where the target vehicle turns right or left, if the end of the section is a traffic signal installation point.

[0060] This configuration allows us to generalize and model the phenomenon of the speed change of the target vehicle when it stops due to a traffic signal at the end of a section, thereby enabling us to estimate the running energy in a simple manner.

[0061] (16) In (15) above, the third speed model may represent that the target vehicle decelerates from the sixth speed to speed 0 by the end of the section and then maintains speed 0 for a predetermined period of time.

[0062] With this configuration, when the target vehicle stops due to a traffic signal at the end of a section, the target vehicle continuously decelerates and stops. Therefore, the speed change phenomenon of the target vehicle in that section can be generalized and modeled. This allows for a simple method of estimating the driving energy.

[0063] (17) In the above (16), the sixth speed may indicate a representative traveling speed of a vehicle traveling in the section.

[0064] With this configuration, the speed model can be calculated using a statistically calculated representative traveling speed, such as the average speed of vehicles traveling in a section, etc. Therefore, a speed model that corresponds to the actual traveling speed can be calculated, and traveling energy can be estimated with high accuracy.

[0065] (18) In (17) above, the traveling energy estimation device may further include a speed correction unit that corrects the sixth speed based on regulation information that regulates traveling of the target vehicle on the route.

[0066] According to this configuration, each speed can be corrected when calculating the speed model based on the regulation information. Therefore, the speed model can be calculated taking regulation information into account, and the traveling energy can be estimated with high accuracy.

[0067] (19) In any of (7), (13) and (18) above, the restriction information may include at least one of information on events being held while the target vehicle is traveling, information on road restrictions, weather information, traffic congestion information, travel time information and map information.

[0068] This configuration allows the speeds used to calculate the speed model to be corrected in consideration of various specific regulation information, thereby allowing a more accurate speed model to be calculated.

[0069] (20) In any one of (1) to (19) above, the speed model acquisition unit may calculate the speed model for each section according to the type of road included in the section.

[0070] Since the number of acceleration / deceleration or stops, the traveling speed, etc. differ between ordinary roads and expressways, it is possible to calculate a speed model taking these into consideration.

[0071] (21) In any one of (14) to (19) above, the speed model acquisition unit may calculate the third speed model in the section including an expressway.

[0072] Since there are no traffic lights on expressways, the driving energy can be estimated with high accuracy by calculating the third speed model.

[0073] (22) In any one of (4) to (8) above, the speed model acquisition unit may calculate the first speed model in the section including an ordinary road.

[0074] On general roads, traffic signals are installed at certain points, so by calculating a speed model assuming the traffic signal installation points, it is possible to estimate the driving energy with high accuracy.

[0075] (23) In any of (1) to (22) above, the speed model acquisition unit may determine an acceleration when changing the speed of the target vehicle depending on the driver of the target vehicle, and acquire the speed model showing the time progression of the traveling speed of the target vehicle based on the determined acceleration.

[0076] The acceleration of the target vehicle when it stops and when it starts moving varies depending on the driver, such as a cautious driver generally driving at low acceleration without making many sudden accelerations or decelerations, etc. By obtaining a speed model based on the acceleration according to such driver characteristics, it is possible to estimate the driving energy for each driver with high accuracy.

[0077] (24) In any of (1) to (23) above, the route acquisition unit may calculate a route that minimizes the travel distance of the target vehicle from a first point to a second point as the planned route for the target vehicle.

[0078] According to this configuration, for example, it is possible to estimate with high accuracy the traveling energy when the target vehicle travels along a route that minimizes the travel distance from the departure point to the destination.

[0079] (25) In any of (1) to (23) above, the route acquisition unit may select one of multiple routes of the target vehicle from a first location to a second location based on the driving energy estimated by the driving energy estimation unit.

[0080] With this configuration, for example, it is possible to select the route from a plurality of routes that minimizes the travel energy from the departure point to the destination as the travel route of the target vehicle, thereby enabling the target vehicle to travel in an environmentally friendly manner.

[0081] (26) In any of (1) to (25) above, the speed model acquisition unit may acquire a speed model for the section including the predicted speed change point based on at least one of the direction of travel of the target vehicle at the predicted speed change point and the presence or absence of a traffic signal.

[0082] With this configuration, an appropriate speed model can be obtained for each section consisting of one or more road links, taking into account the target vehicle's traveling direction and the presence or absence of a traffic signal at the speed change prediction point. For example, at a point where a traffic signal is installed, a speed model that models the speed change due to a stop at the traffic signal can be obtained. Furthermore, at a point where a traffic signal is not installed but the traveling direction changes, a speed model that models the speed change due to a change in traveling direction can be obtained. In other words, the speed of the target vehicle can be modeled as a speed model for each section having one or more road links. Therefore, even when the target vehicle travels in a place where short road links are continuously connected, such as an urban area, it is possible to estimate the traveling energy in units of distance, where acceleration and deceleration, which have the greatest impact on traveling energy, occur. In other words, traveling energy can be estimated without overly subdividing the section unit (unit of distance). Furthermore, because the traveling speed of the target vehicle is expressed by a speed model, acceleration and deceleration, which have the greatest impact on traveling energy, can be appropriately expressed in a simple manner. This allows for accurate estimation of traveling energy based on a speed model modeled with few parameters.

[0083] (27) A driving energy estimation method according to another embodiment of the present disclosure includes the steps of: a driving energy estimation device acquiring a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; a driving energy estimation device dividing the route into one or more sections each consisting of one or more of the road links, the sections including predicted speed change points where a change in the driving speed of the target vehicle is expected; a driving energy estimation device acquiring a speed model for each section that indicates the temporal progression of the driving speed of the target vehicle; and a driving energy estimation device estimating the driving energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0084] This configuration includes the characteristic processing steps of the above-described traveling energy estimation device, and therefore can achieve the same functions and effects as the above-described traveling energy estimation device.

[0085] (28) A computer program according to another embodiment of the present disclosure causes a computer to function as a route acquisition unit that acquires a route consisting of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; a route division unit that divides the route into one or more sections each consisting of one or more road links, the sections including predicted speed change points where a change in the travel speed of the target vehicle is expected; a speed model acquisition unit that acquires a speed model that indicates the temporal progression of the travel speed of the target vehicle for each section; and a travel energy estimation unit that estimates the travel energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

[0086] According to this configuration, the computer can function as the above-described traveling energy estimation device, and therefore, the same functions and effects as those of the above-described traveling energy estimation device can be achieved.

[0087] [Details of the Embodiments of the Present Disclosure] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that each of the embodiments described below represents a specific example of the present disclosure. The mathematical formulas, numerical values, shapes, materials, components, component placement and connection configurations, steps, and step order shown in the following embodiments are examples and do not limit the present disclosure. Furthermore, among the components in the following embodiments, components not recited in independent claims are components that can be added arbitrarily. Furthermore, each figure is a schematic diagram and is not necessarily a precise illustration.

[0088] The same components are denoted by the same reference numerals, and their functions and names are also the same, so their explanations will be omitted as appropriate.

[0089] [Overall Configuration of Traveling Energy Estimation System] FIG. 1 is a diagram illustrating the overall configuration of a traveling energy estimation system according to an embodiment of the present disclosure.

[0090] The driving energy estimation system 10 according to the embodiment is a system for estimating the driving energy of an electric vehicle when driving along a predetermined route, and includes a detector 1, a target vehicle 2, a probe vehicle 9, a base station 4, a driving energy estimation server 5, and a traffic information providing server 8.

[0091] The detector 1 has a wireless communication function and includes various sensors such as an image vehicle detector or LiDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging) installed on a road.

[0092] The target vehicle 2 is an electric vehicle that runs by driving an electric motor using power supplied from a battery, and is a vehicle whose running energy is to be estimated.

[0093] The target vehicle 2 includes an in-vehicle device 3 having a wireless communication function. The detailed configuration of the in-vehicle device 3 will be described later.

[0094] The probe vehicle 9 is a vehicle having a wireless communication function, and has a function of transmitting probe information including information on the position of the vehicle itself and information on the time when the vehicle passed that position.

[0095] The target vehicle 2 and the probe vehicle 9 include not only ordinary passenger cars but also public vehicles such as route buses and emergency vehicles. Furthermore, the target vehicle 2 and the probe vehicle 9 may be not only four-wheeled vehicles but also two-wheeled vehicles (motorcycles).

[0096] The base station 4 connects devices that perform wireless communication (such as the detector 1, the target vehicle 2, and the probe vehicle 9) to the network 7.

[0097] The base station 4 and relay devices such as repeaters (not shown) are configured by transport equipment capable of, for example, SDN (Software-Defined Networking). The network virtualization technology represented by the above-mentioned SDN is a basic concept of 5G (fifth generation mobile communication system). Therefore, the wireless communication system of this embodiment is, for example, 5G. However, the wireless communication system is not limited to 5G, and may be an ITS (Intelligent Transport Systems) wireless communication system or the like.

[0098] The traveling energy estimation server 5 estimates the traveling energy of the target vehicle 2 when traveling along a predetermined route based on a speed model that represents the estimated traveling speed of the target vehicle 2, and transmits the estimation result to the target vehicle 2 via the network 7 and the base station 4. The detailed configuration of the traveling energy estimation server 5 will be described later.

[0099] The traffic information providing server 8 is a server installed in a traffic control center or the like, and calculates a typical traveling speed of the probe vehicle 9 based on the probe information of the probe vehicle 9 traveling on the route (road). The traffic information providing server 8 also detects traffic accidents and the like that have occurred on the route based on the detection information of the detectors 1. The detailed configuration of the traffic information providing server 8 will be described later.

[0100] [Configuration of Traffic Information Providing Server 8] FIG. 2 is a block diagram showing an example of the configuration of the traffic information providing server 8 according to an embodiment of the present disclosure.

[0101] 2 , the traffic information providing server 8 includes a control unit 80, which is a processor including a CPU (Central Processing Unit), a communication unit 81, and a storage device 82. The control unit 80, the communication unit 81, and the storage device 82 are connected to each other via a bus 87.

[0102] The communication unit 81 includes a communication module for communicating with other devices via the network 7. The communication unit 81 transmits information provided by the control unit 80 to other devices via the network 7, and provides information received via the network 7 to the control unit 80.

[0103] The storage device 82 is configured by a volatile memory element such as an SRAM (Static RAM) or a DRAM (Dynamic RAM), a non-volatile memory element such as a flash memory or an EEPROM (Electrically Erasable Programmable Read Only Memory), or a magnetic storage device such as a hard disk, etc. The storage device 82 stores computer programs executed by the control unit 80, data generated when the control unit 80 executes the computer programs, etc.

[0104] The control unit 80 includes functional processing units realized by reading and executing a computer program pre-stored in the storage device 82, including a probe information acquisition unit 83, a sensing information acquisition unit 84, a traffic condition identification unit 85, and a driving speed prediction unit 86.

[0105] The probe information acquisition unit 83 acquires probe information from a plurality of probe vehicles 9 via the communication unit 81. The probe information acquisition unit 83 writes the acquired probe information into the storage device 82.

[0106] The sensing information acquisition unit 84 acquires sensing information from the detector 1 via the communication unit 81. The sensing information acquisition unit 84 acquires sensing information indicating, for example, the speed, presence or absence, or position of a vehicle detected by the detector 1. The sensing information acquisition unit 84 writes the acquired sensing information to the storage device 82.

[0107] The traffic condition identification unit 85 acquires route information to the destination of the target vehicle 2 from the traveling energy estimation server 5 via the communication unit 81. The traffic condition identification unit 85 also reads sensed information from the storage device 82. The traffic condition identification unit 85 identifies the traffic conditions on the route indicated by the route information based on the route information and the sensed information. Specifically, the traffic condition identification unit 85 detects a traffic accident occurring on the route and identifies the details of the traffic accident, including the location, scope, and severity of the traffic accident. The traffic condition identification unit 85 can detect a traffic accident using, for example, image processing or the like.

[0108] The traffic condition identification unit 85 may identify the details of congestion, including the location, range, and degree of congestion, other than traffic accidents, or may detect the location where a sudden deceleration of a vehicle occurs. The traffic condition identification unit 85 may also detect the location of fallen objects, falling rocks, etc.

[0109] Furthermore, the traffic condition identification unit 85 may detect these using not only the sensed information but also the probe information.

[0110] The traffic condition identification unit 85 also reads information about traffic signals installed at intersections and other locations along the route, including their cycles and offsets, the road shape of each road (e.g., gradient, curvature of curves, etc.), and traffic rules such as speed limits for each road from the storage device 82 that stores this information in advance, or acquires it from another external server. The signal information includes information indicating a set of multiple traffic signals whose signal display offsets are synchronized. The signal information may also include information indicating a set of multiple traffic signals whose signal display cycles are synchronized.

[0111] The traffic condition identification unit 85 generates traffic condition information indicating details of traffic accidents, congestion, locations of sudden deceleration, locations of fallen objects, locations of fallen rocks, details of traffic signals, road shapes, or traffic regulations on the route. The traffic condition information is an example of regulation information that regulates the travel of the target vehicle 2 on the route.

[0112] The traffic condition identification unit 85 may include, in the traffic condition information, information on events such as concerts held near the route indicated by the route information, weather information for the area including the route, travel time information for the route, etc. The traffic condition identification unit 85 may acquire the event information and weather information from an external server. The travel time information is calculated by the traveling speed prediction unit 86, which will be described later.

[0113] The traffic condition identification unit 85 transmits the created traffic condition information to the traveling energy estimation server 5 via the communication unit 81.

[0114] The traveling speed prediction unit 86 reads the probe information acquired by the probe information acquisition unit 83 from the storage device 82 and predicts the vehicle's representative traveling speed based on the read probe information. The traveling speed is calculated for each predetermined road section (e.g., road link). For example, the traveling speed prediction unit 86 calculates the travel time for each road section for each vehicle based on the probe information, and calculates the vehicle's traveling speed in each road section from the travel time and the road section length. The traveling speed prediction unit 86 calculates the vehicle's representative traveling speed for each road section by statistically processing the traveling speeds of multiple vehicles for each road section (e.g., calculating the average or most frequent value of the traveling speeds). Note that road sections may be road links on a road map. Alternatively, road sections may be defined for sections of a predetermined distance on a road. Note that the traveling speed prediction unit 86 may predict the legal speed as the representative traveling speed for each road section. For example, when a traveling speed cannot be obtained by statistical processing for a road link with low traffic volume, the traveling speed prediction unit 86 may predict the legal speed as the representative traveling speed.

[0115] Furthermore, the traveling speed prediction unit 86 acquires route information to the destination of the target vehicle 2 from the traveling energy estimating server 5 via the communication unit 81, and determines the representative traveling speed of the vehicle for each road section on the route indicated by the route information as the predicted traveling speed when the target vehicle 2 travels along the route. The traveling speed prediction unit 86 transmits speed information indicating the predicted traveling speed of the target vehicle 2 for each determined road section to the traveling energy estimating server 5 via the communication unit 81.

[0116] [Configuration of In-Vehicle Device 3] FIG. 3 is a block diagram showing an example of the configuration of the in-vehicle device 3 according to the embodiment of the present disclosure.

[0117] 3 , the in-vehicle device 3 of the target vehicle 2 includes a control unit (ECU: Electronic Control Unit) 30, a communication unit 40, a storage device 41, a GPS (Global Positioning System) receiver 42, a vehicle speed sensor 43, a gyro sensor 44, a display 45, and an input device 46. These are interconnected via a bus 47. The bus 47 is configured by an in-vehicle communication network such as a CAN (Controller Area Network) or Ethernet (registered trademark), for example.

[0118] The communication unit 40 is, for example, a wireless communication device capable of 5G-compatible communication processing. The communication unit 40 may be a wireless communication device already installed in the target vehicle 2, or may be a mobile terminal such as a smartphone that a passenger brings into the target vehicle 2.

[0119] The storage device 41 is configured by a volatile memory element such as an SRAM or a DRAM, a non-volatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk. The storage device 41 stores computer programs executed by the control unit 30, data generated when the computer programs are executed by the control unit 30, etc. The storage device 41 also stores a map database. The map database includes road map data.

[0120] The GPS receiver 42 , the vehicle speed sensor 43 and the gyro sensor 44 are sensors that measure the current position, speed and direction of the target vehicle 2 .

[0121] The display 45 is an output device for notifying the user, who is a passenger of the in-vehicle device 3, of various information generated by the control unit 30. Specifically, the display 45 displays an input screen for route search, a map image of the area around the vehicle, route information to the destination, driving energy information, electricity consumption information, etc.

[0122] The input device 46 is a device for a passenger of the target vehicle 2 to perform various input operations. The input device 46 is composed of an operation switch provided on the steering wheel, a joystick, a touch panel provided on the display 45, and the like.

[0123] The control unit 30 includes an input data receiving unit 31, a route search request unit 32, an information providing unit 33, an information acquisition unit 34, and a display control unit 35 as functional processing units realized by executing a computer program stored in the memory device 41.

[0124] The input data receiving unit 31 receives various types of input data. The input data includes, for example, information indicating the destination of the target vehicle 2, the number of passengers in the target vehicle 2, and the load capacity of the target vehicle 2, which are input by a passenger in the target vehicle 2 using the input device 46. The input data also includes information about the driver of the target vehicle 2. The driver information may be input by a passenger in the target vehicle 2 using the input device 46, or the identification information of a smart key may be associated with the driver information, and the input data receiving unit 31 may acquire the driver information based on the identification information received from the smart key. The driver information may be identification information that identifies the driver, or may be information about the driver's attributes (gender, age, driving proficiency, etc.).

[0125] The route search request unit 32 determines the vehicle position of the subject vehicle based on GPS signals periodically received by the GPS receiver 42. The route search request unit 32 may also complement the GPS signals or correct the vehicle position of the subject vehicle by using GPS complement signals or GPS augmentation signals received by the receiver and transmitted from a quasi-zenith satellite (not shown). The route search request unit 32 also complements the vehicle position and direction based on input signals from the vehicle speed sensor 43 and the gyro sensor 44, and determines the accurate current position of the target vehicle 2.

[0126] The route search request unit 32 sends a route search request including information on the current location of the target vehicle 2 and information on the destination of the target vehicle 2 accepted by the input data acceptance unit 31 to the driving energy estimation server 5 via the communication unit 40.

[0127] The information providing unit 33 transmits the number of passengers information, load capacity information, and driver information of the target vehicle 2 received by the input data receiving unit 31, as well as the identification information of the target vehicle 2 (e.g., vehicle identification number or vehicle registration number) to the driving energy estimation server 5 via the communication unit 40.

[0128] The information acquisition unit 34 acquires route information indicating the travel route of the target vehicle 2 to the destination calculated in response to the route search request sent by the route search request unit 32 to the travel energy estimation server 5 from the travel energy estimation server 5 via the communication unit 40. The information acquisition unit 34 also acquires information on the travel energy and electricity cost consumed when the target vehicle 2 travels the travel route from the travel energy estimation server 5 via the communication unit 40.

[0129] The display control unit 37 causes the display 45 to display the route information, driving energy information, and electricity consumption information acquired by the information acquisition unit 34 .

[0130] [Configuration of Traveling Energy Estimation Server 5] FIG. 4 is a block diagram showing an example of the configuration of the traveling energy estimation server 5 according to an embodiment of the present disclosure.

[0131] 4 , the traveling energy estimation server 5 includes a control unit 50, which is a processor including a CPU, a communication unit 51, and a storage device 52. The control unit 50, the communication unit 51, and the storage device 52 are connected to each other via a bus 53.

[0132] The communication unit 51 includes a communication module for communicating with other devices via the network 7. The communication unit 51 transmits information provided by the control unit 50 to other devices via the network 7, and provides information received via the network 7 to the control unit 50.

[0133] The storage device 52 is composed of a volatile memory element such as an SRAM or a DRAM, a non-volatile memory element such as a flash memory or an EEPROM, or a magnetic storage device such as a hard disk. The storage device 52 stores computer programs executed by the control unit 50, data generated when the computer programs are executed by the control unit 50, and the like. The storage device 52 also stores a vehicle model information table, which is a data table indicating the correspondence between vehicle identification information and vehicle model information. The storage device 52 also stores a specific information table, which is a data table indicating the correspondence between vehicle model information and vehicle-specific information (e.g., the vehicle weight, the vehicle air resistance coefficient, the power consumption of a DC / DC converter connected to the vehicle battery, etc.). The storage device 52 also stores an air density table, which is a data table indicating the correspondence between air temperature and air density. The storage device 52 also stores a map database. The map database includes road map data. The map database also includes information indicating the gradient of each road and the rolling resistance coefficient of the road surface. The map database also includes information indicating the type of road (general road, expressway) for each road, and information indicating the direction of travel and whether or not there are traffic lights for each guide, which is a point on a road (described later).

[0134] The control unit 50 includes functional processing units that are realized by reading and executing a computer program pre-stored in the memory device 52, such as a route search unit 54, an information acquisition unit 55, a route division unit 56, a speed correction unit 57, a speed model calculation unit 58, a total weight acquisition unit 59, and a driving energy estimation unit 60.

[0135] The traveling energy estimation server 5 has the functionality of a so-called car navigation system. The route search unit 54 receives a route search request from the in-vehicle device 3 of the target vehicle 2 via the communication unit 51. The route search unit 54 searches for a travel route from the current position of the target vehicle 2 to a destination based on the received route search request. A known method can be used to search for the route. For example, the route search unit 54 searches for a travel route with the shortest travel distance from the current position to the destination. The route search unit 54 may search for a travel route with the shortest travel distance based on each of multiple conditions (e.g., whether or not a highway is used). The route search unit 54 may also search for a travel route with the shortest travel time from the current position to the destination. The route search unit 54 transmits route information indicating the searched travel route (hereinafter referred to as the "searched route") to the target vehicle 2 and the traffic information providing server 8 via the communication unit 51. The searched route is configured as a set of one or more road links.

[0136] The information acquisition unit 55 acquires speed information indicating the predicted traveling speed of the target vehicle 2 for each road section included in the search route of the target vehicle 2 from the traffic information providing server 8 via the communication unit 51.

[0137] In addition, the information acquisition unit 55 acquires traffic condition information on the searched route of the target vehicle 2 from the traffic information providing server 8 via the communication unit 51.

[0138] In addition, the information acquisition unit 55 acquires information on the number of passengers in the target vehicle 2, load capacity information of the target vehicle 2, identification information of the target vehicle 2, and driver information of the target vehicle 2 from the in-vehicle device 3 of the target vehicle 2 via the communication unit 51.

[0139] The route dividing unit 56 divides the travel route into one or more sections each consisting of one or more road links, each section including an expected speed change point, based on points (hereinafter also referred to as "expected speed change points") located on the travel route of the target vehicle 2 searched for by the route searching unit 54 where a change in the travel speed of the target vehicle 2 is expected. A section including an expected speed change point is a section divided by a speed change point. In addition, changes in travel speed may occur not only at an expected speed change point, but also in sections before and after the expected speed change point.

[0140] Upstream of the speed change predicted point, a guidance message is generally output by voice in a car navigation system, and therefore the point is referred to as a "guide." In other words, in the present disclosure, a guide refers to a target point where a route or driving operation guidance is notified to the driver of the target vehicle 2 by a route guidance system such as a car navigation system.

[0141] The guide is generated during route search by the route search unit 54. For example, the route search unit 54 determines whether an intersection that satisfies a predetermined condition (e.g., an intersection equipped with a specific type of traffic signal that is likely to cause traffic lights to stop) is installed at the end point of a road link on the searched route (hereinafter referred to as a "link end point") based on intersection type information indicating the presence or absence of a traffic signal at the intersection and the type of traffic signal, and sets the link end point at the intersection that satisfies the condition as a guide. Note that the route search unit 54 may set a guide for an intersection or other point using information other than intersection type information. For example, the route search unit 54 may extract, as a guide, a link end point where the road type changes on the searched route based on road type information. Furthermore, the route search unit 54 may extract, as a guide, a link end point where the target vehicle 2 changes direction by an angle within a predetermined angle range based on a map database. In addition, the route search unit 54 may set as guides link endpoints where the number of lanes changes, link endpoints where the legal speed changes, link endpoints where the road gradient changes, link endpoints where curves (especially sharp curves) occur, link endpoints where branching occurs, link endpoints where merging occurs, etc., based on registered information in a map database, etc.

[0142] Such guides may be registered in advance in a map database that the route search unit 54 refers to when searching for a route, or may be dynamically generated based on intersection type information, etc., as described above. Also, both guides registered in the map database and dynamically generated guides may be used as guides.

[0143] The section between a guide and its adjacent downstream guide will be referred to as the "guide section." Of the two guides that make up the guide section, the upstream guide will be referred to as the "upstream guide," and the downstream guide will be referred to as the "downstream guide."

[0144] The guide includes, for example, points where traffic signals are installed (hereinafter referred to as "traffic signal installation points") and points where the target vehicle 2 turns right or left (hereinafter referred to as "right / left turn points"). A right / left turn point specifically refers to a point where the target vehicle 2 changes direction by an angle within a predetermined angle range at a branch point or a point where the road type changes, or a point where the radius of curvature is equal to or less than a predetermined value. The guide also includes points where a road without traffic signals, such as an expressway, a motorway, or a bypass road, switches to a general road with traffic signals, and junctions where one expressway switches to another expressway. The guide also includes entrance and exit points of expressways, as well as entrance or exit points such as service areas, parking areas, interchanges, or toll booths. However, examples of the guide are not limited to those described above. The guide may include points where the number of lanes changes, points where the legal speed limit changes, points where the road gradient changes, road junctions or branching points, points on a single road where the target vehicle 2 changes direction by an angle within an angle range, or curve points where the radius of curvature is less than a predetermined value.

[0145] A guide section is made up of one or more road links. However, the positions of the end points (guides) of the guide section and the link end points do not need to be exactly the same, and some positional deviation is permissible as long as the guide section is considered to be essentially made up of one or more road links.

[0146] That is, the route dividing unit 56 divides the travel route into guide sections, each of which is made up of one or more road links.

[0147] The speed correction unit 57 corrects the predicted traveling speed indicated by the speed information based on the speed information and traffic condition information acquired by the information acquisition unit 55.

[0148] For example, first, when the speed information indicates a representative driving speed for each road link (hereinafter referred to as "representative driving speed"), the speed correction unit 57 calculates the representative driving speed for each guide section based on the representative driving speed for each road link.

[0149] When a single guide section is made up of a single road link, the speed correction unit 57 sets the representative traveling speed of that road link as the representative traveling speed of that guide section. Also, when a single guide section is made up of multiple road links, the speed correction unit 57 calculates the representative traveling speed of that guide section based on the representative traveling speeds of those multiple road links. For example, the average of the representative traveling speeds of the multiple road links may be set as the representative traveling speed of the guide section. Note that the average may be a weighted average according to the length of the road link.

[0150] Next, the speed correction unit 57 corrects the representative traveling speed for each guide section based on traffic condition information. For example, if a traffic accident has occurred in the guide section and the number of available lanes is restricted, the speed correction unit 57 corrects the representative traveling speed by lowering the representative traveling speed for that guide section according to a predetermined rule (for example, by multiplying it by a constant less than or equal to 1). The speed correction unit 57 may also correct the representative traveling speed in a similar manner if rain is forecast to fall in the guide section at the scheduled traveling time of the target vehicle 2. The speed correction unit 57 may also correct the representative traveling speed in a similar manner if an event is scheduled to be held near the guide section during a predetermined time period including the scheduled traveling time of the target vehicle 2 or if congestion occurs in the guide section. The speed correction unit 57 may also correct the representative traveling speed in a similar manner if the travel time for the guide section is longer than usual. The speed correction unit 57 may also correct the representative traveling speed in a guide section that includes steep slopes or sharp curves based on a map database stored in the storage device 52.

[0151] The speed model calculation unit 58 calculates a speed model that indicates the change over time in the predicted traveling speed of the target vehicle 2 in each guide section that includes each of the multiple guides provided on the searched route. Below, a specific description is given of the method for calculating the speed model for each type of guide section.

[0152] (Right / Left Turn Model) Figure 5 is a diagram showing an example of a speed model for a guide section where the upstream guide is a right / left turn point. In Figure 5, the horizontal axis represents time, and the vertical axis represents speed. Specifically, the speed model calculation unit 58 creates a speed model that shows the temporal progression of speed by decreasing the speed from a predetermined speed in the guide section (e.g., a representative traveling speed) to a predetermined speed (a predetermined lower limit speed) at a predetermined first acceleration, increasing the speed from the lower limit speed to the predetermined speed (e.g., the representative traveling speed) at a predetermined second acceleration, and maintaining the representative traveling speed until the downstream guide is reached. This speed model is called the "right / left turn model."

[0153] (Traffic Light Stop Model) FIG. 6 is a diagram showing an example of a speed model for a guide section where the upstream guide is a traffic light installation point. In FIG. 6, the horizontal axis represents time, and the vertical axis represents speed. Specifically, the speed model calculation unit 58 assumes that the stop time due to a red light is T1 seconds. It also assumes that the time required to pass the traffic light installation point is T2 seconds. The speed model calculation unit 58 creates a speed model that shows the temporal progression of speed by decreasing the speed from a predetermined speed (e.g., representative traveling speed) to speed 0 (stop) at a predetermined third acceleration, maintaining speed 0 for T1 seconds, and then increasing the speed from speed 0 (stop) to a predetermined speed (e.g., representative traveling speed) at a predetermined fourth acceleration, and maintaining the representative traveling speed until the downstream guide is reached. This speed model is called a "traffic light stop model."

[0154] (Dedicated section model (other than the end)) Figure 7 is a diagram showing an example of a speed model for a guide section in which the upstream guide and downstream guide do not correspond to either a right / left turn point or a traffic light installation point. In Figure 7, the horizontal axis represents time and the vertical axis represents speed. Specifically, the speed model calculation unit 58 creates a speed model that shows the temporal progression of speed at which a predetermined speed (e.g., a representative driving speed) is maintained throughout the guide section. This speed model is called the "dedicated section model (other than the end)." The dedicated section model (other than the end) is applied to road sections where no traffic lights are installed, such as expressways, motorways, and bypass roads.

[0155] In this speed model, there is no change in speed within the guide section. However, a step occurs due to the difference in speed between the speed in the downstream guide of the guide section adjacent to the main guide section upstream and the representative running speed in this guide section, and the speed change is expressed. Similarly, a step occurs due to the difference in speed between the speed in the upstream guide of the guide section adjacent to the main guide section downstream and the representative running speed in this guide section, and the speed change is expressed. However, during the processing process, there may be cases where there is almost no change in speed before and after the guide.

[0156] (Dedicated Section Model (End)) Figure 8 is a diagram showing an example of a speed model in which the upstream guide does not correspond to either a right / left turn point or a traffic signal installation point, and the downstream guide corresponds to a traffic signal installation point. In Figure 8, the horizontal axis represents time, and the vertical axis represents speed. Specifically, the speed model calculation unit 58 creates a speed model that shows the temporal change in speed by maintaining a predetermined speed (e.g., a representative driving speed) from the upstream guide, reducing the speed from the representative driving speed to a speed of 0 (stop) at a predetermined fifth acceleration, and maintaining the speed of 0 (stop) for T3 seconds. This speed model is called the "dedicated section model (end)." The dedicated section model (end) is applied to road sections where, for example, roads without traffic signals, such as expressways, motorways, and bypass roads, switch to general roads with traffic signals.

[0157] Before calculating the speed model, the speed model calculation unit 58 may determine the acceleration to be used when changing the speed of the target vehicle 2 based on the driver information of the target vehicle 2 acquired by the information acquisition unit 55. The speed model calculation unit 58 calculates the speed model based on the determined acceleration. Specifically, the speed model calculation unit 58 corrects the first and second accelerations of the right / left turn model ( FIG. 5 ), the third and fourth accelerations of the traffic light stop model ( FIG. 6 ), and the fifth acceleration of the dedicated section model (end) ( FIG. 7 ) based on the driver information. For example, if the driver's attributes are male, in their twenties, or high driving proficiency, the speed model calculation unit 58 may multiply the first to fifth accelerations by a predetermined coefficient of one or more to increase the absolute values ​​of the accelerations compared to before the correction. Furthermore, if the driver's attributes are female, aged 60 or older, or low driving proficiency, the speed model calculation unit 58 may multiply the first to fifth accelerations by a predetermined positive coefficient less than one to decrease the absolute values ​​of the accelerations compared to before the correction.

[0158] In addition, if a coefficient table showing the relationship between the driver's identification information and the coefficients is stored in advance in the storage device 52, the speed model calculation unit 58 may refer to the coefficient table to determine a coefficient corresponding to the driver's identification information, and correct the acceleration by multiplying the determined coefficient by each of the first acceleration to fifth acceleration.

[0159] Furthermore, the speed model calculation unit 58 can also create a speed model for one guide section by combining a plurality of models of the same or different types for that section.

[0160] 9A and 9B are diagrams illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. Fig. 9A shows the relationship between the guide section and road links, and is a diagram illustrating an example in which the guide section is divided into multiple sub-sections. Fig. 9B shows the generated speed model.

[0161] As shown in Figure 9(a), one guide section X includes, from the upstream side, link endpoints EX, EA, EB, EC, ED, EE, and EY. The guide section X also includes an upstream guide GX and a downstream guide GY. The link endpoint EX is the upstream guide GX, and the link endpoint EY is the downstream guide GY. In Figure 9(a), the link endpoints are indicated by black circles. The searched route is indicated by a thick solid line, and road links other than the searched route are indicated by thin solid lines.

[0162] Each of the upstream guide GX (link end point EX) and the downstream guide GY (link end point EY) is assumed to be a traffic signal installation point. Furthermore, each of the link end points EA, EB, EC, ED, and EE is assumed to be a traffic signal installation point but is not set as a guide. For example, each of the link end points EA, EB, EC, ED, and EE is an intersection that does not fall under the category of intersections that are set as guides (e.g., intersections where a specific type of traffic signal is installed).

[0163] The speed model calculation unit 58 divides the guide section X into sub-sections if the section length of the guide section X is greater than a predetermined distance threshold. For example, the speed model calculation unit 58 divides the guide section X into an upstream sub-section SA and a downstream sub-section SB at the position of link endpoint EC, which is closest to the midpoint of the guide section X among link endpoints EA, EB, EC, ED, and EE. By performing this process, the guide section X can be divided into sub-sections SA and SB having section lengths less than the distance threshold.

[0164] As shown in (b) of FIG. 9 , the speed model calculation unit 58 creates a speed model for the guide section X by combining multiple (here, two) speed models. That is, the speed model calculation unit 58 applies one speed model to the sub-section SA and one speed model to the sub-section SB to create a new speed model. Note that since the representative traveling speed is calculated for each guide section, the representative traveling speed of the speed model for the sub-section SA and the speed model for the sub-section SB are the same. However, when combining speed models for each sub-section, the representative traveling speed may be calculated for each sub-section. This allows for more accurate estimation of traveling energy than when the speed model for a long-distance guide section is defined by a single representative traveling speed.

[0165] For example, by defining a speed model for one guide section using speed models for multiple sub-sections in this way, it is possible to more accurately represent the traveling behavior of the target vehicle 2 in a simple manner, thereby enabling accurate estimation of traveling energy.

[0166] In addition, if the section length of a sub-section is greater than the distance threshold, the speed model calculation unit 58 may newly select link endpoints to divide the guide section X into sub-sections, and divide the guide section X so that the section length of the sub-section that is finally generated is equal to or less than the distance threshold.

[0167] Fig. 10 is a diagram illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. Fig. 10(a) shows the relationship between the guide section and road links, and is a diagram illustrating an example in which the guide section is divided into multiple sub-sections. Fig. 10(b) shows the relationship between the guide section and road links, and is a diagram illustrating another example in which the guide section is divided into multiple sub-sections. Fig. 10(c) shows the generated speed model.

[0168] The guide section X, upstream guide GX, downstream guide GY, and link end points EX, EA, EB, EC, ED, EE, and EY shown in Figures 10(a) and (b) are assumed to be the same as those shown in Figure 9(a).

[0169] 10A, the speed model calculation unit 58 divides the guide section X into sub-sections when the section length of the guide section X is greater than a predetermined distance threshold. For example, in the same manner as described with reference to FIG. 9A, the speed model calculation unit 58 divides the guide section X into an upstream sub-section SA and a downstream sub-section SB at the position of the link endpoint EC that is closest to the midpoint of the guide section X among the link endpoints EA, EB, EC, ED, and EE.

[0170] However, if the section length of at least one of the sub-sections SA and SB is greater than the distance threshold, the speed model calculation unit 58 divides the guide section X into even more sub-sections.

[0171] For example, as shown in Figure 10 (b), the speed model calculation unit 58 changes the number of divisions of the guide section X from 2 to 3, and divides the guide section X into three sub-sections SA, SB, and SC. Specifically, the speed model calculation unit 58 selects from link end points EA, EB, EC, ED, and EE the link end points that are closest to the two division points for dividing the guide section X into three sections with equal section lengths. Here, it is assumed that link end points EB and ED are selected. The speed model calculation unit 58 divides the guide section X at the positions of link end points EB and ED, and generates sub-sections SA, SB, and SC.

[0172] If the section length of at least one of the subsections SA, SB, SC is greater than the distance threshold, the speed model calculation unit 58 increases the number of divisions of the guide section X by one until the section lengths of all subsections are equal to or less than the distance threshold, and repeats the same process as above. However, if the speed model calculation unit 58 divides the guide section X at the positions of all link endpoints EA, EB, EC, ED, EE and still includes a subsection with a section length greater than the distance threshold, the speed model calculation unit 58 ends the division process of the guide section X at that point.

[0173] Here, it is assumed that the section lengths of all of the sub-sections SA, SB, and SC are equal to or shorter than the distance threshold. As shown in (c) of FIG. 10 , the speed model calculation unit 58 creates a speed model for the guide section X by combining multiple (here, three) speed models. That is, the speed model calculation unit 58 applies one speed model to the sub-section SA, one speed model to the sub-section SB, and one speed model to the sub-section SC to create a new speed model. Note that since the representative traveling speed is calculated for each guide section, the representative traveling speeds of the speed models for the sub-sections SA, SB, and SC are the same. However, when combining speed models for each sub-section, the representative traveling speed may be calculated for each sub-section. This allows for more accurate estimation of traveling energy compared to when the speed model for a long-distance guide section is defined by a single representative traveling speed.

[0174] 10, if the length of a subinterval is greater than the distance threshold, a new subinterval is set, ignoring previously created subintervals. Alternatively, if the length of a subinterval is greater than the distance threshold, a new subinterval may be set using previously created subintervals.

[0175] Fig. 11 is a diagram illustrating an example of a procedure for creating a speed model for one guide section by combining multiple speed models. Fig. 11(a) shows the relationship between the guide section and road links, and is a diagram illustrating an example in which the guide section is divided into multiple sub-sections. Fig. 11(b) shows the relationship between the guide section and road links, and is a diagram illustrating another example in which the guide section is divided into multiple sub-sections. Fig. 11(c) shows the generated speed model.

[0176] As shown in (a) of Figure 11, one guide section X includes, from the upstream side, link endpoints EX, EA, EB, EC, ED, and EY. The guide section X also includes an upstream guide GX and a downstream guide GY. The link endpoint EX is the upstream guide GX, and the link endpoint EY is the downstream guide GY. In (a) of Figure 11, the link endpoints are indicated by black circles. The searched route is indicated by a thick solid line, and road links other than the searched route are indicated by thin solid lines.

[0177] 11A, the speed model calculation unit 58 divides the guide section X into sub-sections when the section length of the guide section X is greater than a predetermined distance threshold. For example, the speed model calculation unit 58 divides the guide section X into an upstream sub-section SA and a downstream sub-section SB at the position of the link endpoint EC that is closest to the midpoint of the guide section X among the link endpoints EA, EB, EC, and ED.

[0178] Here, it is assumed that the section length of subsection SA is equal to or less than the distance threshold. Furthermore, it is assumed that the section length of subsection SB is greater than the distance threshold. In this case, the speed model calculation unit 58 determines subsection SA as a subsection of guide section X and further divides subsection SB into two subsections. The only link endpoint that can divide subsection SB is link endpoint ED. Therefore, the speed model calculation unit 58 divides subsection SB into subsections SB1 and SB2 at the position of link endpoint ED. Note that, if there are multiple link endpoints that can divide subsection SB, the speed model calculation unit 58 may divide subsection SB into two subsections at the position of the link endpoint closest to the midpoint of subsection SB. This process is repeated until the section lengths of all subsections are equal to or less than the distance threshold. However, if no link endpoint is included in a subsection whose section length is greater than the distance threshold, the speed model calculation unit 58 terminates the division process for that subsection at that point.

[0179] Here, it is assumed that the section lengths of all of the sub-sections SA, SB1, and SB2 are equal to or shorter than the distance threshold. As shown in (c) of FIG. 11 , the speed model calculation unit 58 creates a speed model for the guide section X by combining multiple (here, three) speed models. That is, the speed model calculation unit 58 applies one speed model to the sub-section SA, one speed model to the sub-section SB1, and one speed model to the sub-section SB2 to create a new speed model. Note that, because the representative traveling speed is calculated for each guide section, the representative traveling speeds of the speed models for the sub-sections SA, SB1, and SB2 are the same. However, when combining speed models for each sub-section, the representative traveling speed may be calculated for each sub-section. This allows for more accurate estimation of traveling energy compared to when the speed model for a long-distance guide section is defined by a single representative traveling speed.

[0180] 4 , the total weight acquisition unit 59 calculates the total weight of the target vehicle 2 based on the number of occupants information, load information, and identification information of the target vehicle 2 acquired by the information acquisition unit 55 from the in-vehicle device 3. Specifically, the total weight acquisition unit 59 refers to the vehicle model information table stored in the storage device 52 and identifies the vehicle model information of the target vehicle 2 from the identification information of the target vehicle 2. The total weight acquisition unit 59 also refers to the unique information table stored in the storage device 52 and identifies the vehicle weight of the target vehicle 2 from the identified vehicle model information of the target vehicle 2.

[0181] The total weight acquisition unit 59 also estimates the weight of the occupants from the information on the number of occupants of the target vehicle 2. For example, if two adults and two children are input as the number of occupants, the total weight acquisition unit 59 estimates the occupant weight as (adult weight x 2 + child weight x 2). Here, the adult weight and child weight indicate the average weight of adults and children set in advance. Note that the adult weight or child weight may be determined taking gender or age into consideration. In this case, the information on the number of occupants includes the gender or age of the occupants, and the occupant weight is estimated using the adult weight or child weight corresponding to the gender or age.

[0182] The total weight acquisition unit 59 calculates the total weight of the target vehicle 2 by adding the weight of the passengers in the target vehicle 2 and the load amount of the target vehicle 2 indicated by the load amount information to the vehicle weight of the target vehicle 2.

[0183] The total weight acquisition unit 59 may be configured to acquire the total weight of the target vehicle 2 from an external server or the in-vehicle device 3 .

[0184] The traveling energy estimation unit 60 estimates the traveling energy (amount of power consumption) and electricity consumption (amount of power consumption per unit distance: that is, the same as traveling energy per unit distance) of the target vehicle 2 when traveling along the searched route.

[0185] Specifically, the traveling energy estimation unit 60 refers to the vehicle model information table and identifies the vehicle model information of the target vehicle 2 from the identification information of the target vehicle 2 indicated in the route search request. The traveling energy estimation unit 60 also refers to the unique information table and identifies the unique information of the target vehicle 2 from the vehicle model information of the target vehicle 2. Details of the identified unique information will be described later.

[0186] The traveling energy estimation unit 60 calculates the traveling energy RE and electricity consumption EC of the target vehicle 2 when the target vehicle 2 travels the searched route searched by the route search unit 54, based on the unique information of the target vehicle 2, the speed model calculated by the speed model calculation unit 58, the total weight of the target vehicle 2 calculated by the total weight acquisition unit 59, and the traffic condition information acquired by the information acquisition unit 55, using the following equations 1 to 6. Note that equations 1 to 6 are merely examples. The traveling energy estimation unit 60 may calculate the traveling energy RE and electricity consumption EC of the target vehicle 2 using equations that can calculate the traveling energy RE and electricity consumption EC of the target vehicle 2 using the speed model calculated by the speed model calculation unit 58, instead of equations 1 to 6.

[0187]

[0188] Here, the definitions of each variable and each constant are as follows: EC: Electricity cost from the current position to the destination [Wh / km] RE: Travel energy from the current position to the destination [Wh] D: Travel distance from the current position to the destination [km] ts: Departure time from the current position (travel start time) te: Arrival time at the destination (travel end time) Fr: Rolling resistance [N] Fs: Gradient resistance [N] Fh: Acceleration resistance [N] Fa: Air resistance [N] V: Vehicle speed [m / s] η: System transmission efficiency [%] Cp: DC / DC converter power consumption [W] g: Gravitational acceleration [m / s ２ ] μ: Rolling resistance coefficient of the road surface W: Total weight of the vehicle [kg] θ: Gradient p: Air density [kg / m ３ ] Cd: Air resistance coefficient A: Frontal resistance area [m ２ ] α: Inertial mass dV / dt: Vehicle acceleration [m / s ２ ]

[0189] The travel distance D, the travel start time ts, and the travel end time te are obtained from the searched route searched by the route search unit 54. The vehicle speed V is the predicted travel speed indicated by the speed model created by the speed model calculation unit 58. The total vehicle weight W is the total weight of the target vehicle 2 calculated by the total weight acquisition unit 59.

[0190] Furthermore, the system transmission efficiency η, the DC / DC converter power consumption Cp, the air resistance coefficient Cd, the frontal resistance area A, and the inertial mass α are included in the specific information of the target vehicle 2. Furthermore, the gravitational acceleration g is a constant.

[0191] Furthermore, the traveling energy estimation unit 60 determines the gradient sin θ and the rolling resistance coefficient μ based on the searched route, traffic condition information, and the map database stored in the storage device 52 .

[0192] The traveling energy estimation unit 60 also references an air density table stored in the storage device 52 and estimates the air density from the temperature on the search route of the target vehicle 2. The temperature on the search route may be obtained from a weather server (not shown). For example, the traveling energy estimation unit 60 transmits route information to the weather server via the communication unit 51. The weather server identifies the temperature of the area to which the route of the target vehicle 2 belongs based on the route information, and transmits the identified temperature to the traveling energy estimation server 5. The traveling energy estimation unit 60 receives the temperature. The temperature at the current location measured by a temperature sensor mounted on the target vehicle 2 may also be used as the temperature on the search route. The traveling energy estimation unit 60 may also obtain the temperature from weather information included in the traffic condition information.

[0193] The traveling energy estimation unit 60 also acquires the vehicle acceleration dV / dt from the speed model. For example, the traveling energy estimation unit 60 acquires the first and second accelerations in the right / left turn model ( FIG. 5 ), the third and fifth accelerations in the traffic light stop model ( FIG. 6 ), and the fifth acceleration in the exclusive section model (end) ( FIG. 8 ) as the vehicle acceleration dV / dt.

[0194] The traveling energy estimation unit 60 transmits information on the estimated traveling energy RE and electricity consumption EC to the in-vehicle device 3 of the target vehicle 2 via the communication unit 51.

[0195] [Processing Flow of Traveling Energy Estimation System 10] FIG. 12 is a sequence diagram showing an example of processing of the traveling energy estimation system 10 according to an embodiment of the present disclosure.

[0196] 12 shows vehicle A and vehicle B as examples of probe vehicles 9. However, the number of probe vehicles 9 is not limited to two, and in reality there are many probe vehicles 9. Also, while FIG. 12 shows one detector 1, the number of detectors 1 is not limited to one, and in reality there are many detectors 1.

[0197] The in-vehicle device 3 of the target vehicle 2 (hereinafter simply referred to as "target vehicle 2") receives information on the destination of the target vehicle 2 input by the passenger of the target vehicle 2 (step S1).

[0198] The target vehicle 2 receives information input by the passenger indicating the number of passengers in the target vehicle 2 and the load capacity of the target vehicle 2 (step S2).

[0199] The target vehicle 2 determines its own position based on the GPS signals periodically received by the GPS receiver 42 (step S3).

[0200] The target vehicle 2 receives the information about the driver of the target vehicle 2 input by the passenger of the target vehicle 2 (step S4).

[0201] The target vehicle 2 sends a route search request including the current location of the target vehicle 2 and the destination of the target vehicle 2 to the driving energy estimation server 5, and the driving energy estimation server 5 receives the route search request (step S5).

[0202] The traveling energy estimation server 5 searches for a travel route from the current position to the destination based on the route search request (step S6).

[0203] Fig. 13 is a diagram showing an example of a searched route searched by the traveling energy estimation server 5. In Fig. 13, the searched route from the departure point (current location) to the destination is shown by a solid line on a map.

[0204] Referring again to FIG. 12, vehicle A transmits the probe information to traffic information providing server 8, and traffic information providing server 8 receives the probe information from vehicle A (step S7).

[0205] Vehicle B transmits the probe information to traffic information providing server 8, and traffic information providing server 8 receives the probe information from vehicle B (step S8). The probe information transmission process (steps S7 and S8) is executed periodically (regularly).

[0206] The detector 1 periodically transmits the detection information to the traffic information providing server 8, and the traffic information providing server 8 receives the detection information from the detector 1 (step S9).

[0207] The traveling energy estimation server 5 transmits route information indicating the searched route searched in the route search process (step S6) to the traffic information providing server 8, and the traffic information providing server 8 receives the route information (step S10).

[0208] The traffic information providing server 8 identifies traffic conditions such as traffic accidents and congestion occurring on the searched route based on the detection information received from the detector 1 and the route information received from the driving energy estimation server 5 (step S11).

[0209] The traffic information providing server 8 predicts the typical driving speed of the probe vehicle 9 for each road section included in the search route based on the probe information obtained from the probe vehicles 9 including vehicle A and vehicle B and the route information received from the driving energy estimation server 5 (step S12).

[0210] The traffic information providing server 8 transmits traffic condition information indicating details of traffic accidents, details of congestion, locations of sudden deceleration, locations of fallen objects or rocks, details of traffic signals, road shapes, and traffic rules on the searched route, as well as speed information indicating the predicted traveling speed of the target vehicle 2 for each road section on the searched route, to the traveling energy estimating server 5. The traveling energy estimating server 5 receives the traffic condition information and the speed information from the traffic information providing server 8 (step S13).

[0211] The traveling energy estimation server 5 divides the searched route into guide sections each consisting of one or more road links (step S14).

[0212] Figure 14 is an enlarged view of a portion of the searched route shown in Figure 13, surrounded by a dashed circle. For example, this portion of the searched route includes, from upstream to downstream, road links L1, L2, L3, L4, L5, and L6. In other words, the target vehicle 2 travels along road links L1, L2, L3, L4, L5, and L6 in this order. The target vehicle 2 also makes a left turn at link endpoint E4, which connects road link L3 and road link L4. In Figure 14, link endpoints are indicated by black circles. The searched route is indicated by a thick solid line, and road links other than the searched route are indicated by thin solid lines.

[0213] The traveling energy estimation server 5 determines whether the link endpoints E1 to E7 correspond to guides. The method of determination is as described above, and it may determine whether the link endpoints correspond to guides using guide information included in the map database, or it may dynamically determine whether the link endpoints correspond to guides using intersection type information, etc.

[0214] Here, it is assumed that the upstream link endpoint E1 of road link L1, the link endpoint E4 connecting road link L3 and road link L4, and the downstream link endpoint E7 of road link L6 are determined to be guides.

[0215] The traveling energy estimation server 5 divides the searched route into guide sections by determining sections separated by the determined guides as guide sections. Through this process, for example, the section consisting of road links L1 to L3 is determined as guide section A, and the section consisting of road links L4 to L6 is determined as guide section B. The upstream guide of guide section A, the downstream guide of guide section A (upstream guide of guide section B), and the downstream guide of guide section B are designated as guide G9, guide G10, and guide G11, respectively.

[0216] Fig. 15 is a diagram showing an example of guides set on the searched route by the guide section division process. In Fig. 15, the guides set on the searched route shown in Fig. 13 are indicated by white circles with guide numbers attached. In other words, Fig. 15 shows that the target vehicle 2 passes through guides G6 to G19 when traveling along the searched route toward the destination.

[0217] Fig. 16 is a diagram showing guide section data generated by the guide section division process. The data shown in Fig. 16 indicates the traveling direction, presence or absence of traffic lights, road type, and offset synchronization area for each guide on the searched route. The traveling direction indicates the traveling direction of the target vehicle 2 in the guide. The presence or absence of traffic lights indicates the presence or absence of traffic lights in the guide. The road type indicates the road type of the guide section. The offset synchronization area indicates the set of guide sections (set of traffic lights) whose traffic light offsets are synchronized.

[0218] The heading direction, traffic light presence / absence, and road type are generated by, for example, referencing map information contained in a map database. The offset synchronization area is generated by, for example, referencing intersection type information when the intersection type information contains information on traffic lights whose signal displays are synchronized.

[0219] For example, the direction of travel in guide G6 is straight ahead, traffic lights are installed in the guide, and the road type of the guide section from guide G6 to guide G7 is a general road. Furthermore, the direction of travel in guide G7 is straight ahead, traffic lights are not installed in the guide, and the road type of the guide section from guide G7 to guide G8 is an underpass. Furthermore, the offsets of the traffic lights in the road section from guide G6 to guide G9 are synchronized (offset synchronization area A) and are different from the offsets of the traffic lights in guide G10 (offset synchronization area B).

[0220] Because no traffic signals are installed in bypass sections, no offset synchronization area is defined. However, even in bypass sections, guides are set at points where road types change, right and left turns, road branching points such as parking lot entrances and bypass exits, and road merging points such as parking lot exits and bypass entrances. For example, guide G11 is a guide provided at a point where the road type changes from an ordinary road to a bypass. Guide G13 is a guide provided at a curve. Guides G12, G14 to G18 in the bypass driving section are guides provided at branching points or merging points.

[0221] The traveling energy estimation server 5 corrects the predicted traveling speed indicated by the speed information based on the received traffic condition information and speed information (step S15).

[0222] The target vehicle 2 transmits the driver information to the traveling energy estimating server 5, and the traveling energy estimating server 5 receives the driver information from the target vehicle 2 (step S16).

[0223] The traveling energy estimation server 5 calculates a speed model that indicates the time progression of the predicted traveling speed of the target vehicle 2 in each guide section that includes each of the multiple guides provided on the searched route, based on the route information, the map database, the corrected predicted traveling speed, and the driver information (step S17). Details of the speed model calculation process (step S17) will be described later.

[0224] The target vehicle 2 transmits the number of passengers information, payload information, and vehicle identification information of the target vehicle 2 to the traveling energy estimation server 5, and the traveling energy estimation server 5 receives this information (step S18).

[0225] The traveling energy estimation server 5 calculates the total weight of the target vehicle 2 based on the passenger number information, the load information, and the identification information (step S19).

[0226] The traveling energy estimation server 5 estimates the traveling energy and electricity consumption of the target vehicle 2 when traveling along the searched route based on the route information, the speed model, the traffic condition information, and the identification information and total weight of the target vehicle 2 (step S20).

[0227] The driving energy estimation server 5 transmits to the target vehicle 2 the route information of the target vehicle 2 searched in the route search process (step S6) and the driving energy information and electricity consumption information estimated in the estimation process (step S20), and the target vehicle 2 receives this information (step S21).

[0228] The target vehicle 2 displays the route information, the traveling energy information, and the electricity consumption information received from the traveling energy estimation server 5 on the display 45 (step S22).

[0229] 17 is a diagram showing an example of route information, driving energy information, and electricity consumption information displayed on the display 45. The display 45 shows the route from guide G6 to the destination via guide G19 in a solid line on a map, and also displays the driving energy "X [Wh]" and electricity consumption "Y [Wh / km]" when traveling to the destination.

[0230] This allows the user to be notified of the travel energy information and electricity cost information along with the searched route as shown in Fig. 15. Note that the travel energy estimation server 5 may calculate the travel energy and electricity cost for each guide section, and the target vehicle 2 may display the travel energy information and electricity cost information for each guide section.

[0231] 18 is a flowchart showing the details of the speed model calculation process (step S17 in FIG. 12). The speed model calculation process is executed by the speed model calculation unit 58 of the traveling energy estimating server 5.

[0232] The traveling energy estimation server 5 repeatedly executes the processes of steps S101 to S111 for each guide (loop A).

[0233] That is, the traveling energy estimation server 5 determines whether the road type of the guide section in which the guide of interest is an upstream guide is an expressway (step S101).

[0234] If the road type is not an expressway (NO in step S101), the traveling energy estimation server 5 determines whether the guide is a right or left turn point (step S102). That is, if there is no traffic signal installed in the guide and the traveling direction is a left turn or a right turn, the traveling energy estimation server 5 determines that the guide is a right or left turn point.

[0235] If it is determined that the guide is a right / left turn point (YES in step S102), the traveling energy estimation server 5 predicts the first acceleration and the second acceleration in the right / left turn model shown in Fig. 5 based on the driver information (step S103). For example, as described above, the traveling energy estimation server 5 predicts the first acceleration and the second acceleration by multiplying the predetermined first acceleration and the second acceleration by a coefficient based on the driver information.

[0236] The traveling energy estimation server 5 calculates the right / left turn model shown in Fig. 5 using the predicted first acceleration and second acceleration (step S104). For example, the speed model for the guide section with the guide G10 as the upstream guide is set as the right / left turn model.

[0237] If it is determined that the guide is not a right or left turn point (NO in step S102), the traveling energy estimation server 5 determines whether the guide is a traffic signal installation point (step S105).

[0238] If it is determined that the guide is a traffic signal installation point (YES in step S105), the traveling energy estimation server 5 predicts the third acceleration and the fourth acceleration in the traffic light stop model shown in Fig. 6 based on the driver information (step S106). For example, as described above, the traveling energy estimation server 5 predicts the third acceleration and the fourth acceleration by multiplying the predetermined third acceleration and the fourth acceleration by a coefficient based on the driver information.

[0239] The traveling energy estimation server 5 calculates the traffic light stop model shown in Fig. 6 using the predicted third acceleration and fourth acceleration (step S107). For example, the speed model of the guide section with guide G6 as the upstream guide is used as the traffic light stop model.

[0240] If the guide is neither a right / left turn point nor a traffic light installation point (NO in step S105) or if the road type of the guide is a highway (YES in step S101), the driving energy estimation server 5 determines whether the adjacent guide located downstream of the guide is a traffic light installation point (step S108).

[0241] If the adjacent guide is not a traffic signal installation point (NO in step S108), the traffic information providing server 8 calculates the dedicated section model (other than the last section) shown in Fig. 7 (step S109). For example, the speed model of the guide section with guide G11 as the upstream guide is set as the dedicated section model (other than the last section).

[0242] If the adjacent guide is a traffic signal installation point (YES in step S108), the traffic information providing server 8 predicts the fifth acceleration in the dedicated section model (last) shown in Fig. 8 (step S110). For example, as described above, the traveling energy estimation server 5 predicts the fifth acceleration by multiplying the predetermined fifth acceleration by a coefficient based on the driver information.

[0243] The traveling energy estimation server 5 calculates the dedicated section model (last) shown in Fig. 8 using the predicted fifth acceleration (step S111). For example, the speed model of the guide section with guide G18 as the upstream guide is set as the dedicated section model (last).

[0244] The traveling energy estimation server 5 may predict whether the target vehicle 2 will stop at a traffic signal installation point based on information about the offset synchronization area, and may set the traffic signal installation point as a right / left turn point or another point based on the prediction result. For example, the traveling energy estimation server 5 predicts a traffic signal installation point in the offset synchronization area A where the target vehicle 2 will stop at a red light based on the cycle and offset of the traffic signals installed in the offset synchronization area A and the predicted travel time in the offset synchronization area A. For example, if the predicted travel time in the offset synchronization area A includes a single red light cycle period, the traveling energy estimation server 5 predicts that the target vehicle 2 will stop at a red light at one traffic signal installation point randomly selected from the offset synchronization area A, and predicts that the target vehicle 2 will not stop at a red light at any other traffic signal installation points included in the offset synchronization area A.

[0245] If the traveling direction at a traffic signal installation point other than the traffic signal installation point where the vehicle is predicted to stop at a red light is a right turn or a left turn, the traveling energy estimation server 5 determines that point to be a right / left turn point. Also, if the traveling direction at a traffic signal installation point other than the traffic signal installation point where the vehicle is predicted to stop at a red light is a straight line, the traveling energy estimation server 5 determines that the point is neither a right / left turn point nor a traffic signal installation point. Then, the traveling energy estimation server 5 executes the process shown in FIG. 18 to calculate a speed model.

[0246] [Comparison between speed model and actual traveling speed] Fig. 19 is a diagram showing the speed change based on the speed model when the target vehicle 2 travels along the searched route calculated by the traveling energy estimation server 5. Fig. 20 is a diagram showing the speed change when the target vehicle 2 actually travels along the same searched route as in Fig. 19 .

[0247] The horizontal axis in Figures 19 and 20 indicates time, and the vertical axis indicates speed. For example, in Figure 19, driving models GA and GB, which are dedicated section models (other than the last one) with a constant driving speed, are arranged consecutively. This indicates that the target vehicle 2 is traveling on a bypass. However, the speed of driving model GB is significantly slower than the speed of driving model GA, and the speed changes stepwise between driving models GA and GB. This indicates that the vehicle is decelerating due to the curve in guide G13 corresponding to driving model GB.

[0248] As shown in Figures 19 and 20, the speed change of the target vehicle 2 indicated by the speed model is similar to the actual speed change of the target vehicle 2 from a general perspective. Because the traveling energy estimation server 5 represents the traveling speed of the target vehicle 2 as a model, there may be local differences in the magnitude of the numerical values ​​from the actual speed. However, by forming the speed model as described above, the presence or absence of dominant acceleration / deceleration in energy consumption is reproduced more simply and with relatively high accuracy. As a result, the estimated value and actual value of traveling energy are similar from a general perspective. In this way, according to the present disclosure, traveling energy can be estimated with high accuracy using relatively simple processing.

[0249] Effects of the Embodiments As described above, according to the embodiments of the present disclosure, a searched route is divided into one or more sections, each consisting of one or more road links, based on guides, which are predicted speed change points. This ensures that the length of the guide section is always equal to or greater than the length of the road link, and the guide section can be configured to include a predicted speed change point. This allows the searched route to be divided into guide sections that allow for highly accurate estimation of travel energy without dividing the route more than necessary. Furthermore, a speed model is provided for each guide section that includes a predicted speed change point (guide) of the target vehicle 2. This allows for speed change events, such as acceleration or deceleration of the target vehicle 2, that occur in the guide, to be reflected in the speed model. Estimating travel energy based on a speed model that reflects such speed change events allows for highly accurate estimation of travel energy when the target vehicle 2, an electric vehicle, travels along the route.

[0250] Furthermore, route guidance systems such as car navigation systems typically guide (notify) the driver of a point upstream of a point where a change in vehicle speed is expected by voice or the like. Therefore, by dividing the section so as to include such a point (guide), the traveling energy of the target vehicle 2 traveling along the route can be estimated with high accuracy.

[0251] Furthermore, at traffic signal installation locations, events of deceleration, stopping, and acceleration of the target vehicle 2 occur continuously. Therefore, by using a speed model that models such events (traffic signal stop model in FIG. 6), it is possible to estimate the running energy with high accuracy.

[0252] The traffic light stop model is a generalized model of the speed change of the target vehicle 2 in a guide section that includes a guide where a traffic light is installed, making it possible to estimate the running energy using a simple method.

[0253] Furthermore, the speed model is calculated using a statistically calculated representative traveling speed, such as the average speed of vehicles traveling in a guide section or road link, etc. Therefore, a speed model that corresponds to the actual traveling speed can be calculated, and traveling energy can be estimated with high accuracy.

[0254] Furthermore, each speed used in calculating the speed model is corrected based on regulation information (e.g., traffic condition information). This allows the speed model to be calculated taking regulation information into account, making it possible to estimate the traveling energy with high accuracy.

[0255] Furthermore, for multiple guide sections each including multiple traffic signal locations where traffic signal indications are synchronized (for example, where the signal offsets are synchronized), the guide section including the point where a red light stop is planned can be determined based on parameters that define the signal indication (traffic signal cycle and offset). This makes it possible to estimate the location of the traffic signal where the vehicle is scheduled to stop among multiple traffic signals with synchronized signal indications. Therefore, a speed model for stopping only at the traffic signal location where the vehicle is scheduled to stop can be calculated, and a speed model for passing through the traffic signal location where the vehicle is not scheduled to stop without stopping can be calculated. This allows for highly accurate estimation of driving energy.

[0256] Furthermore, at a turning point, deceleration and acceleration of the target vehicle 2 occur continuously. Therefore, by using a speed model that models such events (the turning model in FIG. 5), the traveling energy can be estimated with high accuracy.

[0257] The right / left turn model is a generalized model of the speed change of the target vehicle 2 in a guide section that includes a right / left turn point, which allows for a simple method of estimating the traveling energy.

[0258] Furthermore, it is possible to generalize and model the phenomenon of changes in traveling speed in a guide section that includes points where caution is required when traveling through the point, such as a point where road types change, or a road junction or branching point, which may affect the traveling of the target vehicle 2, and where there is a high possibility of sudden acceleration or deceleration occurring when passing through the point (dedicated section model (other than the end) in FIG. 7, dedicated section model (end) in FIG. 8). This makes it possible to estimate traveling energy using a simple method.

[0259] Furthermore, when the target vehicle 2 is stopped by a traffic light at the end of the guide section, the target vehicle 2 continuously decelerates and stops. Therefore, the speed change phenomenon of the target vehicle 2 in the guide section can be generalized and modeled (dedicated section model (end) in FIG. 8 ). This allows for a simple method of estimating the driving energy.

[0260] The regulation information includes at least one of information on events held while the target vehicle 2 is traveling, information on road travel restrictions, weather information, traffic congestion information, travel time information, and map information. Therefore, the speeds used to calculate the speed model can be corrected taking into account various specific regulation information. This allows for a more accurate speed model to be calculated.

[0261] Furthermore, since the number of acceleration / deceleration or stops, the traveling speed, etc. differ between ordinary roads and expressways, it is possible to calculate a speed model taking these into consideration.

[0262] Furthermore, since there are no traffic lights on the expressway, the travel energy can be estimated with high accuracy by calculating the dedicated section model (except for the last section) of FIG.

[0263] Furthermore, on general roads, there are all kinds of points, including traffic signal points, right and left turn points, and other points, so by assuming any of these points and calculating the speed model, it is possible to estimate the driving energy with high accuracy.

[0264] In addition, the acceleration when changing the speed model is determined based on the driver information. A careful driver generally drives at a low acceleration without making many sudden accelerations or decelerations, and the acceleration when the target vehicle 2 stops and starts to move varies depending on the driver. By calculating a speed model based on the acceleration according to such driver characteristics, it is possible to estimate the driving energy for each driver with high accuracy.

[0265] Furthermore, the searched route is calculated as a route that minimizes the travel distance of the target vehicle 2. Therefore, for example, it is possible to estimate with high accuracy the travel energy when the target vehicle 2 travels along a route that minimizes the travel distance from the departure point to the destination.

[0266] The route search unit 54 of the travel energy estimation server 5 may select one route from among multiple routes for the target vehicle 2 based on the travel energy estimated by the travel energy estimation unit 60. That is, when multiple search routes with the shortest travel distances are obtained based on multiple conditions (e.g., whether or not a highway is used), when a predetermined number of search routes are obtained in order from shortest travel distance, or when multiple search routes are obtained based on other criteria (e.g., travel time priority), the route search unit 54 may select one search route (e.g., a search route with the smallest travel energy) from among the multiple search routes based on the travel energy estimated by the travel energy estimation unit 60. The selection of the search route may also be performed by the user. For example, a route with the smallest travel energy does not necessarily have the shortest travel time. Therefore, the user may compare travel time and travel energy to select a route with the smallest travel energy within an acceptable travel time range.

[0267] In this way, the route that minimizes the travel energy from the departure point to the destination can be selected as the travel route for the target vehicle from among multiple routes. This enables the target vehicle to travel in an environmentally friendly manner. As mentioned above, travel energy refers to at least one of the travel energy (power consumption) itself and the travel energy (power consumption) per unit distance.

[0268] Furthermore, the speed model calculation unit 58 can acquire an appropriate speed model for each guide section consisting of one or more road links, taking into consideration the travel direction of the target vehicle and the presence or absence of traffic signals at the speed change predicted point. For example, at a point where a traffic signal is installed, a speed model that models the speed change due to stopping at the traffic signal can be acquired. Furthermore, at a point where a traffic signal is not installed but the travel direction changes, a speed model that models the speed change due to a change in travel direction can be acquired.

[0269] The present inventors have found that when estimating driving energy using a guide section, the traveling direction and the presence or absence of traffic signals are important factors in selecting a speed model. In other words, according to an embodiment of the present disclosure, the speed of a target vehicle can be modeled as a speed model for each guide section having one or more road links. Therefore, even when the target vehicle travels in a location where short road links are continuously connected, such as an urban area, it is possible to estimate driving energy in units of distance, at which acceleration and deceleration, which have the greatest impact on driving energy, occur. In other words, driving energy can be estimated without overly subdividing the section unit (unit of distance). Furthermore, because the driving speed of the target vehicle is expressed using a speed model based on the traveling direction and the presence or absence of traffic signals, acceleration and deceleration, which have the greatest impact on driving energy, can be appropriately expressed in a simple manner. This allows driving energy to be accurately estimated based on a speed model modeled with a small number of parameters.

[0270] [Modification] Although the traveling energy estimation system 10 according to the embodiment of the present disclosure has been described above, the present disclosure is not limited to this embodiment.

[0271] For example, in the above embodiment, the current position of the target vehicle 2 is set as the departure point of the target vehicle 2, but the departure point of the target vehicle 2 may be input by the user.

[0272] Furthermore, although the running energy estimation unit 60 of the running energy estimation server 5 is configured to estimate the vehicle acceleration based on the driver information, this process does not have to be performed. In other words, the running energy estimation unit 60 may calculate the speed model using a predetermined vehicle acceleration.

[0273] Furthermore, although the traveling energy estimation server 5 has a function as a so-called car navigation system that searches for a route to a destination, the traveling energy estimation server 5 may also have a function to search for a route for other purposes. Even when a route is searched for for other purposes, the traveling energy when the target vehicle 2 travels along the searched route is similarly estimated.

[0274] [Additional Notes] Some or all of the components constituting each of the above devices may be configured from one or more semiconductor devices such as system LSIs.

[0275] The computer program may be distributed by recording it on a computer-readable non-transitory recording medium, such as a HDD, a CD-ROM, or a semiconductor memory. The computer program may also be distributed by transmitting it via a telecommunications line, a wireless or wired communication line, a network such as the Internet, or data broadcasting. Each of the above devices may be realized by multiple computers or multiple processors.

[0276] In addition, some or all of the functions of each of the above devices may be provided by cloud computing. That is, some or all of the functions of each device may be realized by a cloud server. Furthermore, at least some of the above embodiments and modifications may be combined in any manner.

[0277] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present disclosure is defined by the claims, not by the above meaning, and is intended to include all modifications within the meaning and scope of the claims. In the above-described embodiment, the traveling energy estimating unit 60 may estimate at least one of traveling energy and traveling energy (electricity efficiency) per unit distance, or may particularly estimate only electricity efficiency. This is because the unit of electricity efficiency is traveling energy (amount of power consumed) per unit distance, and electricity efficiency is included in traveling energy in a broad sense.

[0278] REFERENCE SIGNS LIST 1 Detector 2 Target vehicle 3 In-vehicle device 4 Base station 5 Traveling energy estimation server 7 Network 8 Traffic information providing server 9 Probe vehicle 10 Traveling energy estimation system 30 Control unit 31 Input data receiving unit 32 Route search request unit 33 Information providing unit 34 Information acquisition unit 35 Display control unit 36 ​​Electricity cost acquisition unit 37 Display control unit 40 Communication unit 41 Storage device 42 GPS receiver 43 Vehicle speed sensor 44 Gyro sensor 45 Display 46 Input device 47 Bus 50 Control unit 51 Communication unit 52 Storage device 53 Bus 54 Route search unit (route acquisition unit) 55 Information acquisition unit 56 Route division unit 57 Speed ​​correction unit 58 Speed ​​model calculation unit (speed model acquisition unit) 59 Total weight acquisition unit 60 Traveling energy estimation unit 80 Control unit 81 Communication unit 82 Storage device 83 Probe information acquisition unit 84 Sensing information acquisition unit 85 Traffic condition identification unit 86 Traveling speed prediction unit 87 Bus

Claims

1. a route acquisition unit that acquires a route configured from road links that a target vehicle, which is an electric vehicle, is scheduled to travel; a route dividing unit that divides the route into one or more sections including speed change expected points where a change in the traveling speed of the target vehicle is expected, the one or more sections being each composed of one or more of the road links; a speed model acquisition unit that acquires, for each section, a speed model that indicates a change over time in the traveling speed of the target vehicle; and a traveling energy estimation unit that estimates traveling energy of the target vehicle when traveling on the route based on the speed model acquired for each section.

2. The traveling energy estimation device according to claim 1 , wherein the speed change predicted points include points to be notified in the route guidance to a driver of the target vehicle.

3. The travel energy estimation device according to claim 1 , wherein the speed change predicted points include traffic signal installation points.

4. The traveling energy estimation device according to claim 3 , wherein the speed model acquisition unit calculates a first speed model representing that the target vehicle starts after stopping in the section including a traffic signal installation point where the target vehicle is scheduled to stop due to a red light.

5. 5. The traveling energy estimation device according to claim 4, wherein the first speed model represents that the target vehicle decelerates from a first speed to a speed of zero, then maintains the speed of zero for a predetermined period of time, and then accelerates from the speed of zero to a second speed after maintaining the speed of zero.

6. The traveling energy estimation device according to claim 5 , wherein at least one of the first speed and the second speed indicates a representative traveling speed of a vehicle traveling in the section.

7. The traveling energy estimation device according to claim 5 , further comprising a speed correction unit that corrects at least one of the first speed and the second speed based on regulation information that regulates traveling of the target vehicle on the route.

8. 5. The traveling energy estimation device according to claim 4, wherein the speed model acquisition unit determines, in a plurality of sections each including a plurality of traffic signal installation points where a stop due to a red light is scheduled, based on parameters that define the traffic signal indications, in a plurality of sections each including a plurality of traffic signal installation points where a traffic signal indication is synchronized.

9. The traveling energy estimation device according to claim 1 , wherein the speed change predicted point includes a right / left turn point where the target vehicle turns right or left.

10. The traveling energy estimation device according to claim 9 , wherein the speed model acquisition unit calculates a second speed model that represents deceleration and acceleration of the target vehicle in the section that includes the right or left turn point.

11. The traveling energy estimation device according to claim 10 , wherein the second speed model represents that the target vehicle decelerates from a third speed to a fourth speed, and then accelerates from a fourth speed to a fifth speed.

12. The traveling energy estimation device according to claim 11 , wherein at least one of the third speed and the fifth speed indicates a representative traveling speed of a vehicle traveling in the section.

13. The traveling energy estimation device according to claim 11 , further comprising a speed correction unit that corrects any one of the third speed, the fourth speed, and the fifth speed based on regulation information that regulates traveling of the target vehicle on the route.

14. 2. The driving energy estimation device according to claim 1, wherein the speed model acquisition unit calculates a third speed model including a temporal change in the speed at which the target vehicle maintains a sixth speed in the section including a traffic light installation point and a speed change predicted point that does not correspond to either a right- or left-turn point where the target vehicle turns right or left.

15. The traveling energy estimation device of claim 14, wherein the speed model acquisition unit calculates the third speed model representing that the target vehicle will stop at an end of a section that includes the traffic signal installation point and the speed change predicted point that does not correspond to either the right / left turn point where the target vehicle turns right or left, when the end of the section is a traffic signal installation point.

16. The traveling energy estimation device according to claim 15 , wherein the third speed model represents that the target vehicle decelerates from the sixth speed to a speed of zero by the end of the section and then maintains the speed of zero for a predetermined period of time.

17. The traveling energy estimation device according to claim 16 , wherein the sixth speed indicates a representative traveling speed of a vehicle traveling in the section.

18. The traveling energy estimation device according to claim 17 , further comprising a speed correction unit that corrects the sixth speed based on regulation information that regulates traveling of the target vehicle on the route.

19. The traveling energy estimation device according to claim 7 , wherein the restriction information includes at least one of information on events held while the target vehicle is traveling, information on restrictions on traveling on roads, weather information, traffic congestion information, travel time information, and map information.

20. The traveling energy estimation device according to claim 1 , wherein the speed model acquisition unit calculates, for each of the sections, the speed model according to a type of road included in the section.

21. The traveling energy estimating device according to claim 14 , wherein the speed model acquiring unit calculates the third speed model in the section including an expressway.

22. The traveling energy estimating device according to claim 4 , wherein the speed model acquiring unit calculates the first speed model in the section including a general road.

23. 20. The traveling energy estimation device according to claim 1, wherein the speed model acquisition unit determines an acceleration when changing the speed of the target vehicle depending on a driver of the target vehicle, and acquires the speed model indicating a time-dependent change in the traveling speed of the target vehicle based on the determined acceleration.

24. 20. The traveling energy estimation device according to claim 1, wherein the route acquisition unit calculates a route that minimizes a travel distance of the target vehicle from a first point to a second point as a planned route for the target vehicle.

25. 20. The traveling energy estimation device according to claim 1, wherein the route acquisition unit selects one of a plurality of routes of the target vehicle from a first point to a second point based on the traveling energy estimated by the traveling energy estimation unit.

26. The travel energy estimation device according to claim 1 , wherein the speed model acquisition unit acquires a speed model for the section including the speed change predicted point based on at least one of a traveling direction of the target vehicle at the speed change predicted point and the presence or absence of a traffic signal.

27. A step in which a travel energy estimation device acquires a route composed of road links along which a target vehicle, which is an electric vehicle, is scheduled to travel; The travel energy estimation device divides the route into one or more sections including a speed change expected point where a change in the travel speed of the target vehicle is expected, and each section is composed of one or more of the road links; The traveling energy estimation device acquires a speed model indicating a change over time in the traveling speed of the target vehicle for each section; The traveling energy estimation method includes a step in which the traveling energy estimation device estimates the traveling energy of the target vehicle when traveling along the route based on the speed model acquired for each section.

28. Computer, a route acquisition unit that acquires a route configured from road links that a target vehicle, which is an electric vehicle, is scheduled to travel; a route dividing unit that divides the route into one or more sections including speed change expected points where a change in the traveling speed of the target vehicle is expected, the one or more sections being each composed of one or more of the road links; a speed model acquisition unit that acquires, for each section, a speed model that indicates a change over time in the traveling speed of the target vehicle; and A computer program for causing the target vehicle to function as a traveling energy estimation unit that estimates the traveling energy of the target vehicle when traveling on the route, based on the speed model acquired for each section.