Route planning system, route planning method, and program

Abstract

To provide a technique for planning a travel route for more appropriately reducing a burden on a driver.SOLUTION: The route planning system includes an acquisition unit that acquires travel route information indicating a travel route during driving of a driver, road condition information indicating a road condition on the travel route, and biological information during driving, an estimation unit that estimates a section of the travel route in which a burden is imposed on the driver based on the travel route information, the road condition information, and the biological information, a specification unit that specifies a recommended route of the driver based on the section in which a burden is imposed on the driver, and an output unit that outputs information on the recommended route.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a route planning system, a route planning method, and a program. [Background technology]

[0002] There is technology to plan routes from a departure point to a destination. In addition, transportation companies are required to reduce the burden on drivers.

[0003] Patent Document 1 describes a technology that uses a multi-objective optimization algorithm to extract a driving route that takes into account the driver's level of fatigue from driving data regarding the driving route obtained when the driver drives the vehicle and physical condition data regarding changes in the driver's physical condition while driving. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Publication No. 2020-122682 Summary of the Invention [Problem to be solved by the invention]

[0005] Incidentally, factors that increase the burden on a driver include traffic restrictions due to construction work and road conditions such as congestion. Even if a driving route is extracted taking only the driver's fatigue level into consideration, as in Patent Document 1, the road conditions that cause the driver's burden vary from time to time, so a driving route that takes only the fatigue level into consideration may not be able to reduce the driver's burden. On the other hand, with a driving route that takes only the road conditions into consideration, the burden felt by drivers varies from person to person depending on the road conditions, so a driving route that takes only the road conditions into consideration may not be able to reduce the driver's burden.

[0006] An example of an objective of the present disclosure is to provide a technology for planning a driving route that more appropriately reduces the burden on the driver. [Means for solving the problem]

[0007] A route planning system in one aspect of the present disclosure includes an acquisition means for acquiring driving route information indicating the driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biometric information while driving, an estimation means for estimating sections of the driving route that place a burden on the driver based on the driving route information, road condition information, and biometric information, an identification means for identifying a recommended route for the driver based on the sections that place a burden on the driver, and an output means for outputting information regarding the recommended route.

[0008] A route planning method in one aspect of the present disclosure acquires driving route information indicating the driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biometric information while driving, estimates sections of the driving route that place a burden on the driver based on the driving route information, road condition information, and biometric information, identifies a recommended route for the driver based on the sections that place a burden on the driver, and outputs information regarding the recommended route.

[0009] A program in one aspect of the present disclosure causes a computer to perform the following process: acquire driving route information indicating the driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biometric information while driving; estimate sections of the driving route that placed a burden on the driver based on the driving route information, road condition information, and biometric information; identify a recommended route for the driver based on the sections that placed a burden on the driver; and output information related to the recommended route.

[0010] Each program may be stored in a non-transitory computer-readable recording medium. [Effects of the Invention]

[0011] One example of an effect of the present disclosure is that it is possible to plan a driving route that more appropriately reduces the burden on the driver. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a diagram illustrating a configuration of a system including a route planning device. [Figure 2] FIG. 2 is a block diagram showing the functional configuration of the route planning device. [Figure 3] FIG. [Figure 4] 4 is a flowchart showing the operation of the route planning device. [Figure 5] FIG. 1 is a diagram illustrating a hardware configuration for realizing a route planning device according to the present disclosure using a computer and its peripheral devices. DETAILED DESCRIPTION OF THE INVENTION

[0013] Embodiments of the present disclosure will be described in detail with reference to the drawings.

[0014] [Embodiment] FIG. 1 is a diagram illustrating an example of a system including a route planning device 100 according to the present disclosure.

[0015] In Fig. 1, the route planning device 100 is a device that plans a driving route that reduces the burden on the driver by using road conditions along the driving route driven by the driver and biometric information during driving. In Fig. 1, the route planning device 100 is illustrated as being configured by one server, but it may also be a route planning system realized by multiple devices.

[0016] In FIG. 1, the route planning device 100 is communicably connected to an in-vehicle device and a management device.

[0017] The in-vehicle device is an example of an information collection device that collects driving route information indicating the driving route of the vehicle, road condition information indicating the road conditions of the driving route driven by the driver, and biometric information of the driver. In Fig. 1, the in-vehicle device is communicably connected to a camera and a sensor. The in-vehicle device also acquires location information using known technology. The driving route information is identified based on a history of location information acquired by the in-vehicle device.

[0018] The camera is a camera that captures images of the driving route to identify the driving situation. Here, the road situation refers to road conditions that may affect the driver's driving. For example, road conditions include road congestion, road traffic restrictions due to construction or the like, on-street parking, and the status of pedestrians and oncoming vehicles when turning right or left. The road situation information may be identified from images captured by the camera using known image recognition technology or the like. Furthermore, the device that identifies the road situation information is not particularly limited, and may be another device communicably connected to the route planning device 100, or may be provided as a road situation identification unit inside the route planning device 100 or inside an in-vehicle device.

[0019] The sensor is a sensor that measures the driver's biometric information. The biometric information may be, for example, at least one of physiological information of a person, information representing the person's internal state, and information representing the person's mental state. The biometric information may be, for example, physiological information such as heart rate, respiratory rate, body temperature, and pupil dilation. Furthermore, for example, the biometric information may be a quantified version of the person's internal or mental state, such as stress level or tension level, estimated using various physiological information. The sensor for acquiring the person's biometric information is a sensor that measures the person's biometric information. The sensor for acquiring the person's biometric information may be provided, for example, in a wearable device. Furthermore, the sensor for acquiring the person's biometric information may be a camera that captures an image of the person. In this case, the biometric information may be extracted from an image of the person captured by the camera using known technology.

[0020] In addition, the cameras and sensors may be connected to the route planning device 100 so that they can communicate with each other without going through an in-vehicle device, as long as the route planning device 100 is able to acquire driving route information, road condition information, and biometric information.

[0021] The management device is an example of an output destination to which the route planned by the route planning device 100 is output. The management device is, for example, a terminal device used by an administrator who manages delivery vehicles and drivers at a delivery company that delivers packages. In this example, the administrator instructs the driver on the route that the driver should take.

[0022] The output destination of the route planned by the route planning device 100 is not limited to the management device. For example, the output destination of the route planned by the route planning device 100 may be a terminal device used by the driver or an in-vehicle device of the vehicle driven by the driver.

[0023] Next, the configuration of the route planning device 100 according to the embodiment will be described.

[0024] 2 is a block diagram showing the configuration of the route planning device 100. Referring to FIG. 2, the route planning device 100 includes an acquisition unit 101, an estimation unit 102, an identification unit 103, and an output unit 104.

[0025] Next, the configuration of the route planning device 100 in the first embodiment will be described in detail.

[0026] The acquisition unit 101 is an example of an acquisition means for acquiring driving route information indicating the driving route taken by the driver while driving, road condition information indicating the road conditions along the driving route, and biological information during driving. The acquisition unit 101 acquires each piece of information from, for example, the in-vehicle device described in FIG.

[0027] Each piece of information acquired by the acquisition unit 101 is information obtained while the driver was driving. The time of driving refers to, for example, past driving. The time of past driving may be determined as appropriate at a time before the processing of the route planning device 100 is performed, such as driving during a predetermined period in the past or the most recent driving time, such as the previous day. The acquisition unit 101 may also acquire each piece of information obtained while the driver is currently driving. The time of currently driving refers to the time when the driver is driving.

[0028] The estimation unit 102 is an example of an estimation means for estimating a section of a driving route that places a burden on the driver based on driving route information, road condition information, and biological information. The burden on the driver is at least one of physical burden and mental burden. The estimation unit 102 is mainly assumed to estimate a section that places a burden on the driver using various information from past driving, but may also estimate a section that places a burden on the driver while driving using various information acquired during the driver's current driving.

[0029] For example, the estimation unit 102 estimates a section where the driver is burdened based on the number of first locations that are identified from road condition information and that are burdensome to the driver, and the number of second locations that are identified from biometric information and that are burdensome to the driver. The first locations and the second locations will be described later. For example, the estimation unit 102 estimates that a section where the sum of values ​​obtained by weighting the number of first locations and the number of second locations exceeds a predetermined value is a section where the driver is burdened.

[0030] As described above, the first points are points identified from road condition information that place a burden on the driver. That is, the first points are points where it is estimated that road conditions will place a burden on the driver. For example, it is assumed that the driver will be unable to drive smoothly due to road conditions such as congestion, traffic restrictions, and on-street parking, and will feel physical fatigue and mental stress due to the increased driving time. For this reason, the estimation unit 102 estimates the section where the driver is burdened using the number of first points identified from the road condition information that place a burden on the driver. Note that the road condition information used to identify the first points is not particularly limited as long as it indicates road conditions that are considered to be factors that place a burden on the driver.

[0031] For example, the first point is at least one of a traffic control point, which is a point where traffic control is in place, and a congestion point, which is a point where traffic is congested. A traffic control point may be identified by, for example, including a sign indicating that traffic control is in place or a person enforcing the traffic control, in an image captured by a camera that captures the travel route. A congestion point may also be identified by, for example, including a number of vehicles in the same lane at a predetermined distance ahead of the vehicle that is equal to or greater than a predetermined value in an image captured by a camera that captures the travel route. The road condition information used to identify the first point and the method for identifying the first point are not limited to these examples.

[0032] In addition, in a business that delivers packages, an administrator may manage the drivers and driving routes for delivery. In this case, the administrator may decide on a driving route plan by the day before the delivery is to be made. In such a case, if the road condition information used to identify the first point is road condition information from the most recent driving time up to the previous day, it is possible to identify the first point according to the most recent road conditions up to the previous day and estimate the sections that placed a burden on the driver, and therefore it is possible to identify a recommended route according to the most recent road conditions up to the previous day.

[0033] As described above, the second location is a location identified from biometric information that places a burden on the driver. That is, the second location is a location where it is estimated that the driver has been burdened for some reason. For example, it is assumed that the driver may feel physical fatigue or mental stress due to detailed road conditions that are difficult to identify as road conditions or road conditions that are not expected to place a burden and were not used to identify the first location. For example, it is assumed that the driver has difficulty driving through certain sections of the road, although the driver may not be able to verbalize the reason. It is also assumed that the burden felt by the driver due to certain road conditions varies from driver to driver. For this reason, the estimation unit 102 estimates the section where the driver has been burdened using the number of second locations that place a burden on the driver that are identified from biometric information.

[0034] For example, the second location may be identified when the heart rate acquired by the acquisition unit 101 as the driver's biometric information becomes higher than the driver's normal heart rate by a reference value or more. Also, for example, the second location may be identified when the driver's facial expression based on the image acquired by the acquisition unit 101 as the driver's biometric information becomes tense. The biometric information used to identify the second location and the method for identifying the second location are not limited to these examples.

[0035] With reference to FIG. 3, an example of a section where a burden is placed on the driver will be described.

[0036] In Figure 3, a driver travels from a departure point to destination point B via destination point A. In Figure 3, the travel route during past driving is indicated by a black arrow. Furthermore, the travel route in Figure 3 shows one first point which is a restriction point, one first point which is a congestion point, and two second points. In Figure 3, the burdensome section is a section that includes one first point which is a restriction point, one first point which is a congestion point, and one second point. The burdensome section in Figure 3 is preferably avoided because it places a heavy burden on the driver. The one second point that is not included in the burdensome section is estimated to have placed a burden on the driver, but it is assumed that the burden of traveling through the section including that point is not heavy.

[0037] A specific example of estimating a section where a burden is placed on the driver in FIG. 3 will be described. The estimation unit 102 estimates that a section where a value calculated using an equation such as (number of restriction points × 1.0 + number of vehicles in the same lane as the vehicle captured in the image captured by the camera × 0.1 + number of second locations × 0.2) within a 1-kilometer range is 3.0 or greater is a section where a burden is placed on the driver. In this way, the estimation unit 102 may estimate that a section where a total value of weighted values ​​for the number of restriction points, the number of vehicles in the same lane as the vehicle captured in the image captured by the camera, and the number of second locations is greater than or equal to a reference value is a section where a burden is placed on the driver within a predetermined distance range. The weighted value may be set appropriately depending on the magnitude of the impact on the driver's burden, and may be set in advance or for each driver.

[0038] The method for estimating the section where the driver is under strain is not limited to these examples.

[0039] For example, if a predetermined period of time has passed since the traffic restriction point was identified, when it is assumed that the traffic restriction will be lifted, the estimation unit 102 may exclude the traffic restriction point and estimate the section where the driver was burdened. The period of time when the traffic restriction will be lifted may be set in advance, or may be identified from information on a construction sign captured by a camera that photographs the traffic restriction point.

[0040] Furthermore, for example, the estimation unit 102 may estimate stressful sections using the driver's biometric information, which is estimated by inputting the latest road condition information into a trained model that has learned the relationship between road condition information and biometric information during past driving. In this case, the latest road condition information may be road condition information from when the driver drove on the previous day, when the recommended route for the current day of driving is identified the previous day. The latest road condition information may also be real-time road condition information obtained from a database that stores road conditions based on images taken by other vehicles or the latest road conditions.

[0041] The identification unit 103 is an example of an identification means that identifies a recommended route for the driver based on the section that placed a burden on the driver estimated by the estimation unit 102. For example, the identification unit 103 identifies an optimal recommended route that avoids the section that placed a burden on the driver. Alternatively, for example, the identification unit 103 may identify an optimal recommended route that avoids at least a part of the section that placed a burden on the driver.

[0042] The identification unit 103 may use known technology to identify a recommended route that avoids sections that place a burden on the driver, based on the starting point and at least one destination point. In this case, the starting point and at least one destination point may be, for example, information entered by an administrator who manages the driver, information recorded in advance in a database that accumulates information about deliveries performed by drivers, or information entered by the driver.

[0043] Furthermore, the identification unit 103 may identify a recommended route that avoids a section that places a burden on the driver from a plurality of route candidates that have been identified in advance based on the departure point and at least one destination point. In this case, the process of identifying a plurality of route candidates based on the departure point and at least one destination point may be executed by a route candidate identification unit provided inside the route planning device 100, or may be executed by another device that is provided outside the route planning device 100 and is capable of communicating with the route planning device 100. Note that the identification unit 103 may identify a plurality of recommended routes.

[0044] An optimal recommended route is a route that is determined to be optimal based on predetermined criteria. An optimal recommended route is, for example, a route with the shortest distance or the shortest time. Furthermore, for example, an optimal recommended route may be a route that travels on as large roads as possible or a route with as few right and left turns as possible. In other words, the predetermined criteria may be a short route distance, a short route travel time, travel on as large roads as possible, or as few right and left turns as possible. Note that the predetermined criteria are not limited to these examples and may also be a combination of multiple criteria.

[0045] For example, the identification unit 103 determines an optimal driving route for traveling from a starting point to at least one destination point when the driver is driving on a certain day. If the driver drives the same starting point and destination point as on a certain day when driving the following day and a section that placed a burden on the driver is estimated, the identification unit 103 avoids the section that placed a burden on the driver and identifies a driving route that is next most optimal after the optimal driving route traveled on the certain day. Note that if the driving route that avoids the section that placed a burden on the driver and is next most optimal after the optimal driving route traveled on the certain day includes multiple destination points, the order in which the destination points are arrived at may be set in advance, or may not be set and may be changed to an order according to the route.

[0046] Furthermore, for example, if the estimation unit 102 does not estimate a section that places a burden on the driver, the identification unit 103 may identify an optimal recommended route for traveling from the departure point to at least one destination point.

[0047] The identification unit 103 may also identify that a section that puts a burden on the driver cannot be avoided. For example, if the section that puts a burden on the driver includes at least one destination point, the identification unit 103 may identify that the section that puts a burden on the driver cannot be avoided. For example, if an optimal route that avoids the section that puts a burden on the driver is a route with worse conditions than an optimal route that does not avoid the section that puts a burden on the driver, the identification unit 103 may identify that the section that puts a burden on the driver cannot be avoided. The worse conditions may be, for example, an increase in distance exceeding a predetermined standard, an increase in driving time exceeding a predetermined standard, traveling on roads narrower than a predetermined standard, making more right turns and left turns than a predetermined standard, etc., and may be set as appropriate.

[0048] The output unit 104 is an example of an output means that outputs information related to a recommended route. The output unit 104 outputs information related to the recommended route to, for example, a management device used by a driver and an administrator who manages the driver's driving route. Furthermore, for example, the output unit 104 may output information related to the recommended route to an in-vehicle device or a terminal device used by the driver.

[0049] The information regarding the recommended route may be, for example, information indicating the recommended route, information indicating that a recommended route exists, or information indicating that a recommended route that avoids sections that place a burden on the driver could not be identified.

[0050] The information indicating the recommended route may include information indicating characteristics of the recommended route. The information indicating characteristics of the recommended route may be the travel time or travel distance of the recommended route, the number of traffic lights or intersections to be passed, etc., and is not particularly limited as long as it is information that is expected to be used by a driver or a manager to consider whether to travel the recommended route. Furthermore, when multiple recommended routes are identified, the output unit 104 may output information indicating the multiple recommended routes.

[0051] Furthermore, the output unit 104 may output information regarding sections that placed a burden on the driver. The information regarding sections that placed a burden on the driver may be information indicating sections that placed a burden on the driver, information indicating whether or not there was a section that placed a burden on the driver, or the like. The information indicating sections that placed a burden on the driver may include information indicating the burden that is estimated to have been placed on the driver. For example, by outputting information indicating the burden that is estimated to have been placed on the driver to the administrator, the administrator can consider not only changing the driving route of the same driver, but also changing the driver.

[0052] The operation of the route planning device 100 configured as above will be described with reference to the flowchart of FIG.

[0053] The acquisition unit 101 acquires driving route information indicating the driving route taken by the driver while driving, road condition information indicating the road conditions along the driving route, and biological information during driving (step S101). The process of step S101 may be executed in real time while the driver is driving, or may be executed after the driver has finished driving. Furthermore, for example, the process of step S101 may be executed at a predetermined time.

[0054] Next, the estimation unit 102 estimates a section of the driving route where the driver was burdened, based on the driving route information, road condition information, and biological information acquired in step S101 (step S102).

[0055] Next, the identification unit 103 identifies a recommended route for the driver based on the section where the driver was burdened, which was estimated in step S102 (step S103).

[0056] Then, the output unit 104 outputs information about the recommended route identified in step S103 (step S104). The process of step S104 may be executed following the processes of steps S101 to S103, or may be executed at a predetermined time.

[0057] This completes the series of operations of the route planning device 100. Note that it is assumed that the processing of each step of the route planning device 100 is processing for planning a route for the next driving session mainly using each piece of information from past driving sessions, but it may also be used to plan a route that avoids sections that placed a strain on the driver while driving, using each piece of information acquired while the driver was driving.

[0058] The route planning device in the above-described embodiment includes an acquisition unit, an estimation unit, an identification unit, and an output unit. The acquisition unit acquires driving route information indicating the driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biometric information during driving. The estimation unit estimates sections of the driving route that place a burden on the driver based on the driving route information, road condition information, and biometric information. The identification unit identifies a recommended route for the driver based on the sections that place a burden on the driver. The output unit then outputs information related to the recommended route.

[0059] The route planning device of this embodiment can plan a recommended route based on sections that place a burden on the driver. As a result, the route planning device of this embodiment can plan a driving route that more appropriately reduces the burden on the driver.

[0060] [Hardware configuration] Some or all of the components of each device or system in each embodiment of the present disclosure described above are realized by any combination of an information processing device 1000 and a program, for example, as shown in Fig. 5. The information processing device 1000 includes, as an example, the following configuration.

[0061] ·CPU(Central Processing Unit)1001 ROM (Read Only Memory) 1002 ·RAM(Random Access Memory)1003 Program 1004 loaded into RAM 1003 A storage device 1005 for storing a program 1004 A drive device 1007 that reads and writes from and to the recording medium 1006 A communication I / F 1008 that connects to a communication network 1009 Input / output I / F 1010 for inputting and outputting data Bus 1011 connecting each component Note that I / F is an abbreviation for Interface.

[0062] Each component of each device or system in each embodiment is realized by CPU 1001 acquiring and executing a program that realizes the function of that component. The program that realizes the function of each component of each device is stored in storage device 1005 or RAM 1003 in advance, for example, and is read by CPU 1001 as needed. Note that program 1004 may be supplied to CPU 1001 via a communication network, or may be stored in recording medium 1006 in advance, and drive device 1007 may read the program and supply it to CPU 1001.

[0063] There are various variations in the method of realizing each device. For example, each device or system may be realized by any combination of a separate information processing device 1000 and a program for each component. Furthermore, multiple components included in each device may be realized by any combination of a single information processing device 1000 and a program.

[0064] Furthermore, some or all of the components of each device or system may be realized by general-purpose or dedicated circuits including a processor or a combination of these. Examples of circuits include a CPU, a GPU (Graphics Processing Unit), an FPGA (Field Programmable Gate Array), and an LSI (Large Scale Integration) for AI (Artificial Intelligence) processing. These may be configured by a single chip or by multiple chips connected via a bus. Some or all of the components of each device may be realized by a combination of the above-mentioned circuits and a program.

[0065] When some or all of the components of each device or system are realized by multiple information processing devices, circuits, etc., the multiple information processing devices, circuits, etc. may be centrally or decentralized. For example, the information processing devices, circuits, etc. may be realized as a client-server system, a cloud computing system, or the like, in which they are connected via a communication network.

[0066] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure.

[0067] Furthermore, although the operations are described in a sequential order in the form of a flowchart, the order of the description does not limit the order in which the operations are performed. Therefore, when implementing each embodiment, the order of the operations may be changed as long as it does not affect the content.

[0068] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0069] [Appendix 1] an acquisition means for acquiring driving route information indicating a driving route taken by a driver while driving, road condition information indicating road conditions along the driving route, and biological information taken while driving; an estimation means for estimating a section of the travel route in which a burden is placed on the driver based on the travel route information, the road condition information, and the biological information; A specifying means for specifying a recommended route for the driver based on the section; an output means for outputting information about the recommended route; A route planning system comprising:

[0070] [Appendix 2] the estimation means estimates the section based on the number of first points that impose a burden on the driver, which are identified from the road condition information, and the number of second points that impose a burden on the driver, which are identified from the biometric information. 10. The route planning system of claim 1.

[0071] [Appendix 3] the estimation means estimates the section in which a total value of weighted values ​​for the number of the first locations and the number of the second locations exceeds a predetermined value. 2. A route planning system as described in appendix 2.

[0072] [Appendix 4] The first point is at least one of a traffic control point where traffic regulation is implemented and a traffic congestion point where traffic is congested, the estimation means estimates the section by weighting the number of control points and the number of vehicles in the same lane at the congestion point, respectively. 4. A route planning system as described in Appendix 3.

[0073] [Appendix 5] the biological information is the driver's heart rate, The second point is a point where the heart rate becomes higher than the driver's normal heart rate by a reference value or more. 5. A route planning system according to any one of appendices 2 to 4.

[0074] [Appendix 6] the estimation means, when a predetermined period of time during which traffic restrictions are expected to be lifted has elapsed since the restriction point was identified, estimates the section excluding the restriction point; 5. A route planning system as described in appendix 4.

[0075] [Appendix 7] When a plurality of the recommended routes are identified, the output means outputs information relating to the plurality of the recommended routes. 7. A route planning system according to any one of appendices 1 to 6.

[0076] [Appendix 8] The acquisition means further acquires the road condition information during the driver's current driving, the estimation means estimates the section during which the driver is currently driving based on the road condition information during which the driver is currently driving, the specifying means specifies the recommended route that avoids the section; 8. A route planning system according to any one of appendices 1 to 7.

[0077] [Appendix 9] Acquire driving route information indicating a driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biological information taken by the driver while driving; estimating a section of the driving route that places a burden on the driver based on the driving route information, the road condition information, and the biological information; Identifying a recommended route for the driver based on the section; outputting information about the recommended route; Route planning methods.

[0078] [Appendix 10] Acquire driving route information indicating a driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biological information taken by the driver while driving; estimating a section of the driving route that places a burden on the driver based on the driving route information, the road condition information, and the biological information; Identifying a recommended route for the driver based on the section; outputting information about the recommended route; A program that causes a computer to perform a process.

[0079] Furthermore, some or all of the configurations described in Supplementary Notes 2 to 8 that are subordinate to Supplementary Note 1 (route planning system) described above may also be subordinate to Supplementary Note 9 (route planning method) and Supplementary Note 10 (program) in the same subordinate relationship as Supplementary Note 2 to Supplementary Note 8. Furthermore, not limited to Supplementary Note 1, Supplementary Note 9, and Supplementary Note 10, some or all of the configurations described as Supplements may be subordinate to various hardware, software, various recording means for recording software, or systems, within the scope of each of the above-mentioned embodiments. [Explanation of symbols]

[0080] 100 Route planning device 101 Acquisition Department 102 Estimation part 103 Specific part 104 Output section 1000 Information Processing Device 1001 CPU 1002 ROM 1003 RAM 1004 Program 1005 Storage device 1006 Recording media 1007 Drive device 1008 Communication I / F 1009 Communication Network 1010 Input / Output Interface 1011 Bus

Claims

1. an acquisition means for acquiring driving route information indicating a driving route taken by a driver while driving, road condition information indicating road conditions along the driving route, and biological information taken while driving; an estimation means for estimating a section of the travel route in which a burden is placed on the driver based on the travel route information, the road condition information, and the biological information; A specifying means for specifying a recommended route for the driver based on the section; an output means for outputting information about the recommended route; A route planning system comprising:

2. the estimation means estimates the section based on the number of first points that impose a burden on the driver, which are identified from the road condition information, and the number of second points that impose a burden on the driver, which are identified from the biometric information. The route planning system of claim 1 .

3. the estimation means estimates the section in which a total value of weighted values ​​for the number of the first locations and the number of the second locations exceeds a predetermined value. The route planning system of claim 2 .

4. The first point is at least one of a traffic control point where traffic regulation is implemented and a traffic congestion point where traffic is congested, the estimation means estimates the section by weighting the number of control points and the number of vehicles in the same lane at the congestion point, respectively. The route planning system of claim 3 .

5. the biological information is the driver's heart rate, The second point is a point where the heart rate becomes higher than the driver's normal heart rate by a reference value or more. The route planning system of claim 2 .

6. the estimation means, when a predetermined period of time during which traffic restrictions are expected to be lifted has elapsed since the restriction point was identified, estimates the section excluding the restriction point; The route planning system of claim 4 .

7. When a plurality of the recommended routes are identified, the output means outputs information relating to the plurality of the recommended routes. The route planning system of claim 1 .

8. The acquisition means further acquires the road condition information during the driver's current driving, the estimation means estimates the section during which the driver is currently driving based on the road condition information during which the driver is currently driving, the specifying means specifies the recommended route that avoids the section; The route planning system of claim 1 .

9. Acquire driving route information indicating a driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biological information taken by the driver while driving; estimating a section of the driving route that places a burden on the driver based on the driving route information, the road condition information, and the biological information; Identifying a recommended route for the driver based on the section; outputting information about the recommended route; Route planning methods.

10. Acquire driving route information indicating a driving route taken by the driver while driving, road condition information indicating road conditions along the driving route, and biological information taken by the driver while driving; estimating a section of the driving route that places a burden on the driver based on the driving route information, the road condition information, and the biological information; Identifying a recommended route for the driver based on the section; outputting information about the recommended route; A program that causes a computer to perform a process.

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