JP7517969B2 - Information processing device - Google Patents

Description

This disclosure relates to vehicle navigation technology.

There is technology for evaluating the ease of driving on roads based on probe data. For example, Patent Document 1 discloses a device that estimates the driving load on a route based on the driving history of a probe car, and identifies routes that drivers tend to avoid based on the estimated driving load.

JP 2011-022033 A JP 2004-347539 A

Conventional technology devices estimate the driving load to evaluate the ease of driving on a road. However, the load felt when driving on a certain road varies from driver to driver. In other words, if the load estimation criteria were set uniformly, there is a risk that the accuracy of the evaluation will decrease.

This disclosure was made in consideration of the above-mentioned problems, and aims to improve the evaluation accuracy in a device that evaluates the ease of driving on a road.

An information processing device according to a first aspect of the present disclosure includes:
The system has a control unit that performs the following operations: receives vehicle data from a vehicle traveling on a specified road link, the data including data related to the driving operation of the vehicle; acquires information regarding the frequency with which the vehicle that transmitted the vehicle data has traveled on the road link during a specified period in the past; and calculates an evaluation value for the road link based on the information regarding the frequency acquired for the vehicle and the vehicle data received from the vehicle.

Other aspects of the present disclosure are an information processing method executed by the above-mentioned information processing device, a program for causing a computer to execute the information processing method, or a computer-readable storage medium that non-temporarily stores the program.

This disclosure makes it possible to improve the evaluation accuracy of a device that evaluates the ease of driving on a road.

FIG. 1 is a diagram for explaining an outline of a navigation system. FIG. 2 shows the components of the navigation system in more detail. An example of probe data transmitted from an in-vehicle terminal. 4 shows an example of a probe data table stored in a storage unit. 4 is an example of a road link table stored in a storage unit. 4 is an example of a driving history table stored in a storage unit. FIG. 2 is a diagram showing the flow of data transmitted and received between modules. FIG. 4 is a diagram for explaining the processing executed by each module of the control unit.

An information processing device according to an embodiment of the present disclosure is a device that calculates a driving recommendation level for multiple road links based on data (probe data) transmitted from multiple vehicles (probe cars) under its management. Specifically, the information processing device determines the ease of driving for each road link based on the received probe data, and assigns a higher driving recommendation level to road links that can be evaluated as being easier to drive.

The information processing device has a control unit that executes the following: receiving vehicle data from a vehicle traveling on a specified road link, the vehicle data including data related to the driving operation of the vehicle; acquiring information related to the frequency with which the vehicle that transmitted the vehicle data traveled on the road link during a specified period of time in the past; and calculating an evaluation value for the road link based on the frequency information acquired for the vehicle and the vehicle data received from the vehicle.

The vehicle data includes data related to the driving operation of the vehicle, such as the amount of acceleration/deceleration, the amount of steering operation, and the like.
Based on such data related to driving operations, it is possible to estimate the ease of driving on a certain road link. For example, if the steering operation amount per unit time is large, it can be estimated that the driving behavior is to avoid an obstacle. Also, if the vehicle speed is not constant, it can be estimated that there is a factor that hinders smooth driving.

However, it is not desirable to use a uniform standard for evaluation based on this information. For example, if a vehicle driver lives near the target road or is accustomed to driving on that road, he or she may be able to pass through the target road more smoothly than other drivers. Therefore, when evaluating road links, it is preferable to take into account the driver's level of skill.

The information processing device according to this embodiment acquires information regarding the frequency with which a vehicle that transmitted vehicle data traveled on a target road link during a specified period in the past, and evaluates the road link taking that frequency into consideration. For example, a smaller weighting can be assigned to the evaluation of vehicles that are traveled more frequently. This configuration makes it possible to perform a more accurate evaluation.

Specific embodiments of the present disclosure are described below with reference to the drawings. Unless otherwise specified, the hardware configuration, module configuration, functional configuration, etc. described in each embodiment are not intended to limit the technical scope of the disclosure to only those.

(First embodiment)
An overview of a route guidance system according to a first embodiment will be described with reference to Fig. 1. The route guidance system according to the first embodiment is a system that assigns evaluation values to road links included in road map data based on information collected from a vehicle 200A, and provides route guidance to a vehicle 200B using the road map data to which the evaluation values have been assigned.

The route guidance system according to this embodiment includes a vehicle 200 and a server device 100 that generates evaluation information for road links based on probe data acquired by the vehicle 200.
In the following description, a vehicle (probe car) that generates probe data will be referred to as vehicle 200A, and a vehicle that receives road map data will be referred to as vehicle 200B, but the two vehicles may be the same. When there is no need to distinguish between the two, they will simply be referred to as vehicle 200.

The vehicle 200A is a vehicle that provides probe data to the server device 100. The vehicle 200A acquires data related to driving operation using an on-board sensor, and periodically transmits the data to the server device 100 as probe data.
In the first embodiment, the vehicle 200A acquires data on acceleration/deceleration per unit time and data on the amount of steering operation per unit time as data on driving operation.

The server device 100 stores road map data, and assigns a driving recommendation level to road links included in the road map data based on the probe data collected from the vehicle 200A. In this embodiment, the driving recommendation level is a value representing the ease of driving. For example, a higher driving recommendation level is assigned to a road link that is easier to drive on, and a lower driving recommendation level is assigned to a road link that is more difficult to drive on.
The server device 100 generates road map data reflecting the driving recommendation level, and transmits the generated road map data to the vehicle 200B upon a request from the vehicle 200B.

Vehicle 200B is a vehicle that searches for a route. Vehicle 200B downloads road map data reflecting the driving recommendation level from server device 100, and performs a route search using the road map data. This makes it possible to generate a route that is easier to drive.

Figure 2 shows in more detail the components of the navigation system according to this embodiment.

The vehicle 200 includes a control unit 201, a memory unit 202, a communication unit 203, an input/output unit 204, and a sensor 205.

The control unit 201 is a control device that controls the vehicle 200. The control unit 201 may be configured with a plurality of ECUs (Engine Control Units) that control the vehicle. In the following description, the control unit 201 refers to an ECU that executes the processing described in this embodiment among a plurality of ECUs mounted on the vehicle 200. Note that the control unit 201 may be an on-board computer other than an ECU.

The control unit 201 includes three functional modules: a data acquisition unit 2011, a data transmission unit 2012, and a navigation unit 2013. These functional modules may be realized by executing a program stored in the storage unit 202 (described later) by a CPU or an ECU.

The data acquisition unit 2011 generates data (probe data) related to driving operations performed on the vehicle. In this embodiment, the probe data includes data indicating the amount of acceleration/deceleration per unit time and the amount of steering operation per unit time. These data can be acquired using one or more sensors 205 (described later) that the vehicle 200 has.

The data transmission unit 2012 periodically transmits the probe data acquired by the data acquisition unit 2011 to the server device 100.

The navigation unit 2013 provides navigation functions to the vehicle occupants. Specifically, it provides route guidance, traffic information, and the like. The navigation unit 2013 may be configured to be able to communicate with a unit (such as a GPS module) for acquiring the current position of the vehicle, and a unit (such as a communication module) for acquiring traffic information from the outside.

The storage unit 202 includes a main storage device and an auxiliary storage device. The main storage device is a memory in which the programs executed by the control unit 201 and data used by the control programs are expanded. The auxiliary storage device is a device in which the programs executed by the control unit 201 and data used by the control programs are stored. The auxiliary storage device may store the programs executed by the control unit 201 packaged as applications. It may also store an operating system for executing these applications. The programs stored in the auxiliary storage device are loaded into the main storage device and executed by the control unit 201, thereby performing the processing described below.
Furthermore, the storage unit 202 may be configured to be capable of storing data for providing a navigation function (road map data), and the like.

The primary storage device may include a random access memory (RAM) or a read only memory (ROM). The secondary storage device may include an erasable programmable ROM (EPROM) or a hard disk drive (HDD). The secondary storage device may also include a removable medium, i.e., a portable recording medium.

The communication unit 203 is a wireless communication interface for connecting the vehicle 200 to a network. The communication unit 203 is configured to be able to communicate with the server device 100 via, for example, a wireless LAN or a mobile communication service such as 3G, LTE, or 5G.
The input/output unit 204 is a unit that accepts input operations performed by a user and presents information to the user. In this embodiment, it is made up of a single touch panel display. That is, it is made up of a liquid crystal display and its control means, and a touch panel and its control means.

The sensor 205 includes an acceleration sensor and a steering sensor. The acceleration sensor can obtain the amount of acceleration or deceleration performed per unit time. The steering sensor can obtain the amount of steering operation performed per unit time (for example, the total amount of angle). Note that, although an acceleration sensor is exemplified in this embodiment, acceleration can also be calculated using the value output by a speed sensor.

Next, the server device 100 will be described.
The server device 100 can be configured by a general-purpose computer. That is, the server device 100 can be configured as a computer having a processor such as a CPU or a GPU, a main storage device such as a RAM or a ROM, and an auxiliary storage device such as an EPROM, a hard disk drive, or a removable medium. The auxiliary storage device stores an operating system (OS), various programs, various tables, etc., and the programs stored therein are loaded into the working area of the main storage device and executed, and each component is controlled through the execution of the programs, thereby realizing each function that matches a predetermined purpose, as described below. However, some or all of the functions may be realized by hardware circuits such as ASICs and FPGAs.

The control unit 101 is a calculation device that is responsible for the control performed by the server device 100. The control unit 101 can be realized by a calculation processing device such as a CPU.
The control unit 101 is configured to have four functional modules: a data acquisition unit 1011, a vehicle evaluation unit 1012, a link evaluation unit 1013, and a map generation unit 1014. Each functional module may be realized by executing a stored program by a CPU or an ECU.

The data acquisition unit 1011 acquires probe data from the vehicle 200A under the control of the system. Fig. 3 shows an example of the probe data transmitted from the vehicle 200A. As shown in the figure, the probe data includes a vehicle identifier, information indicating the date and time when sensing was performed, information indicating the location where sensing was performed, and sensor data (amount of acceleration/deceleration and steering operation per unit time).

The data acquisition unit 1011 also assigns the acquired probe data to a road link. In this embodiment, the server device 100 divides roads on which vehicles can travel into multiple road links and manages them, and can associate a location corresponding to the probe data (i.e., a location where sensing was performed) with a specific road link.

The vehicle evaluation unit 1012 determines the frequency with which a vehicle that has transmitted probe data on a road link has traveled on that road link. If the frequency with which a vehicle has traveled on a particular road link is higher than a predetermined value, it can be determined that the vehicle is familiar with that road link. In such a case, it is preferable not to use the probe data transmitted from the vehicle in the evaluation, or to reduce the weighting when making the evaluation. In the server device according to this embodiment, the link evaluation unit 1013, which will be described later, performs the evaluation based on the frequency determined by the vehicle evaluation unit 1012.

The link evaluation unit 1013 evaluates the ease of driving for each road link based on the stored probe data.
Specifically, the link evaluation unit 1013 assigns a higher driving recommendation level to a road link that has a smaller total acceleration/deceleration amount per unit time and a smaller total steering operation amount per unit time contained in multiple probe data corresponding to the target road link.

At this time, the link evaluation unit 1013 performs the evaluation using one of the following methods.
(1) For a target road link, a greater weight is given to probe data transmitted from vehicles that are driven infrequently than to probe data transmitted from vehicles that are driven frequently. (2) For a target road link, evaluation is performed using only probe data transmitted from vehicles whose driving frequency is below a predetermined value. This makes it possible to minimize the influence of vehicles that are accustomed to driving the target road link.

The map generation unit 1014 generates road map data in which a driving recommendation level is assigned to the road links based on the results of the evaluation performed by the link evaluation unit 1013, and transmits the data to the vehicle 200B.

The storage unit 102 is composed of a main storage device and an auxiliary storage device. The main storage device is a memory in which the programs executed by the control unit 101 and the data used by the control programs are expanded. The auxiliary storage device is a device in which the programs executed by the control unit 101 and the data used by the control programs are stored.

Furthermore, the memory unit 102 stores a probe data table 102A, a road link table 102B, and a driving history table 102C.

The probe data table 102A is a table that stores probe data received from multiple vehicles 200A. FIG. 4 is an example of a probe data table. As shown, the probe data received from each of the multiple vehicles 200A is added to the probe data table as a separate record. The "Link ID" field stores the identifier of the road link corresponding to the point where the probe data was generated.

The road link table 102B is a table that defines road links. Fig. 5 shows an example of the road link table 102B. As shown in the figure, the table includes data for defining the geographical positions of the road links and calculated evaluation values (driving recommendation levels). The evaluation values are updated by the link evaluation unit 1013 as needed.

The driving history table 102C is a table that records the driving frequency of the vehicle 200 for each of multiple road links. FIG. 6 is an example of the driving history table 102C. The driving history table 102C includes a vehicle identifier, a road link identifier, the number of times the vehicle 200 has driven the road link, the update date and time, etc. These records are updated at any time by the vehicle evaluation unit 1012 based on the data recorded in the probe data table 102A.

The communication unit 103 is a communication interface for connecting the server device 100 to a network. The communication unit 103 includes, for example, a network interface board and a wireless communication module for wireless communication.

Note that the configuration shown in FIG. 2 is an example, and all or part of the functions shown may be executed using specially designed circuits. In addition, programs may be stored or executed using a combination of main memory and auxiliary memory other than those shown in the figure.

The processing performed by each module and the details of the data used will be explained with reference to Figure 7, which shows the data sent and received between modules.

The data acquisition unit 1011 receives probe data from the vehicle 200A. The data acquisition unit 1011 also refers to the road link table 102B, associates the location indicated by the newly acquired probe data with the road link, and stores the data in the probe data table 102A. The acquisition of probe data is performed periodically for each of the multiple vehicles 200 under management.

The vehicle evaluation unit 1012 calculates the number of times that the vehicle 200A has traveled on each road link during a specified period of time in the past (i.e., the travel frequency) based on the probe data stored in the probe data table 102A. The calculated number of travels is stored in the travel history table 102C.

The link evaluation unit 1013 evaluates the driving recommendation level for each road link based on the probe data stored in the probe data table 102A, and reflects the result in the road link table 102B. The driving recommendation level can be calculated, for example, by the following procedure.
(1) Calculate the average acceleration/deceleration amount per unit time of multiple vehicles on the target road link. (2) Calculate the average steering operation amount per unit time of multiple vehicles on the target road link. (3) Combine the above to calculate a value representing the frequency of driving operations. (4) The smaller the calculated frequency, the higher the driving recommendation level is given to the target road link.

In other words, the link evaluation unit 1013 calculates a lower driving recommendation level for a road link with a larger average acceleration/deceleration amount and a larger average steering operation amount. This allows a lower evaluation to be given to roads that are not suitable for smooth driving (for example, roads with many obstacles, frequent maneuvers to avoid oncoming vehicles, many bends, etc.).

Furthermore, the link evaluation unit 1013 refers to the driving history table 102C to obtain the driving frequency of the vehicle that transmitted the probe data on the road link, and uses the obtained driving frequency to calculate the driving recommendation level. For example, if there is a vehicle whose driving frequency on the target road link is higher than a predetermined value, the above processing may be performed by excluding the probe data transmitted from the vehicle. Also, if such a vehicle is present, a smaller weight may be assigned to the data corresponding to the vehicle in the calculation of the driving recommendation level.
This makes it possible to minimise the influence of probe data transmitted from vehicles that are familiar with the road link in question.

The map generation unit 1014 generates road map data in which a driving recommendation level is assigned to each road link based on the information stored in the road link table 102B. The generated road map data is transmitted to the vehicle 200B upon request from the vehicle 200B.

The vehicle 200B (navigation unit 2013) performs a route search based on the road map data received from the server device 100. In searching for a route, a route is generated that has a lower total cost (e.g., required time and congestion level) associated with the road links, as in the conventional technology. Furthermore, the navigation unit 2013 generates a route using the driving recommendation level generated by the link evaluation unit 1013 in addition to the cost. In other words, road links that require a shorter required time (lower congestion level) and are easier to drive are preferentially adopted as part of the route.

Figure 8 shows the processes executed by each module of the server device 100 (control unit 101). The dotted lines in the figure represent data references.

In step S11, the data acquisition unit 1011 receives probe data from the vehicle 200A. It also assigns road links to the received probe data (step S12) and stores the result in the probe data table 102A (step S13). The processing of steps S11 to S13 is executed when probe data is transmitted from each of the multiple vehicles 200A.

The vehicle evaluation unit 1012 refers to the probe data table 102A and acquires probe data for a specific vehicle (step S21). It then calculates the driving frequency for each of the multiple road links and reflects the results in the driving history table 102C (step S22). The processing of steps S21 to S22 is executed at a predetermined interval for each of the multiple vehicles 200 under the management of the system.

The link evaluation unit 1013 obtains data corresponding to a predetermined period in the past from the probe data table 102A (step S31). Similarly, it obtains data corresponding to a predetermined period in the past from the driving history table 102C (step S32). Then, using the method described above, it calculates a driving recommendation level for each of the multiple road links (step S33). The calculation results are reflected in the road link table 102B. The processing of steps S31 to S33 is executed at a predetermined cycle (for example, once a day).

The map generation unit 1014 acquires data from the road link table 102B (step S41) and generates road map data (step S42). As described above, a driving recommendation level is assigned to each road link in the road map data. The generated road map data is distributed in response to a request from the vehicle 200B. The processing of steps S41 to S42 may be performed at a predetermined interval, or may be performed when a request is made by the vehicle 200B.

As described above, the server device 100 according to the present embodiment assigns a higher driving recommendation level to a road link that can be passed through with simpler driving operations based on the probe data collected from the vehicle 200A. At this time, the server device 100 determines whether or not to adopt the data, or determines the weight of the data, based on the frequency with which the probe car travels on the road link. This makes it possible to evaluate the road link while taking into account the driver's level of skill.

In the description of the embodiment, the driving frequency is classified into two categories based on a threshold value, but other methods may be used. In calculating the driving recommendation level, it is preferable to use probe data transmitted from probe cars with similar driving frequencies. For this reason, the driving frequency may be classified into classes, and the driving recommendation level may be calculated using only probe data transmitted from probe cars that belong to a specified class.

(Variation 1 of the First Embodiment)
In the first embodiment, the driving recommendation level is determined based on the amount of acceleration/deceleration and the amount of steering operation, but the driving recommendation level may be determined using other data in combination.
For example, if the vehicle 200A has an image sensor, the driving recommendation level for the road link may be determined based on an image acquired by the vehicle 200A or data obtained by analyzing the image. Note that, since information obtained from an image (e.g., road width, road shape, presence or absence of street lights, etc.) is unrelated to the driver's skill level, it is preferable not to involve the driving frequency when using such information.

(Modification 2 of the First Embodiment)
In the first embodiment, the traveling frequency of the vehicle 200A is determined for each road link, but it may be determined whether "a certain vehicle is familiar with traveling on a target road link" based on other information. For example, the server device 100 may hold data on the home base (e.g., a parking lot at home) of each vehicle 200A, and may determine that the vehicle is familiar with traveling on road links within a predetermined range from the home base.
In this way, the server device 100 may indirectly estimate the travel frequency of the target road link.

(Modification 3 of the first embodiment)
In the first embodiment, the driving recommendation level is calculated uniformly for multiple road links, but the driving environment on the road may change depending on the time of day. For example, the number of bicycles and pedestrians may increase or decrease depending on the day of the week or the time of day. To deal with this, the server device 100 may calculate the driving recommendation level for each day of the week or each time of day. In this case, the server device 100 may generate multiple road map data for each day of the week or each time of day, and transmit the appropriate one of them to the vehicle 200B.

(Modification)
The above-described embodiment is merely an example, and the present disclosure can be modified and implemented as appropriate without departing from the spirit and scope of the present disclosure.
For example, the processes and means described in this disclosure can be freely combined and implemented as long as no technical contradiction occurs.

In addition, a process described as being performed by one device may be shared and executed by multiple devices. Or, a process described as being performed by different devices may be executed by one device. In a computer system, the hardware configuration (server configuration) by which each function is realized can be flexibly changed.

The present disclosure can also be realized by supplying a computer program that implements the functions described in the above embodiments to a computer, and having one or more processors of the computer read and execute the program. Such a computer program may be provided to the computer by a non-transitory computer-readable storage medium that can be connected to the system bus of the computer, or may be provided to the computer via a network. Non-transitory computer-readable storage media include, for example, any type of disk, such as a magnetic disk (floppy disk, hard disk drive (HDD), etc.), an optical disk (CD-ROM, DVD disk, Blu-ray disk, etc.), a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic card, a flash memory, an optical card, and any type of medium suitable for storing electronic instructions.

REFERENCE SIGNS LIST 100: Server device 101, 201: Control unit 102, 202: Storage unit 103, 203: Communication unit 200: Vehicle 204: Input/output unit 205: Sensor

Claims (1)

receiving vehicle data from each of a plurality of vehicles traveling on a predetermined road link, the vehicle data including data related to a driving operation of each of the plurality of vehicles;
acquiring information regarding a frequency of each of the plurality of vehicles traveling on the road link in a predetermined period of time in the past;
calculating an evaluation value for the road link from the information regarding the frequency acquired for each of the plurality of vehicles and the vehicle data received from each of the plurality of vehicles;
A control unit that executes
calculating the evaluation value includes increasing a weight of a vehicle that is less frequently detected among the plurality of vehicles and decreasing a weight of a vehicle that is more frequently detected among the plurality of vehicles, and calculating the evaluation value from the vehicle data of each of the plurality of vehicles.
Information processing device.

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