JP2018185229A - Route search system, route search program and route search method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To search for a more appropriate travel route.SOLUTION: Provided is a route search system for searching for a travel route to a destination of a vehicle 10 capable of automatically executing a plurality of operations among acceleration, steering and braking without relying on manual driving, the route search system comprising: an evaluation unit 4A; a specification unit 4B; and a search unit 4C. The evaluation unit 4A evaluates a performance score Sp that represents the automatic travel capability of the vehicle 10 and a drive score Sd that represents the operation skill of a driver of the vehicle 10. Meanwhile, the specification unit 4B specifies from a plurality of candidate points on map data an avoidance point that the vehicle 10 should avoid, on the basis of both of the performance score Sp and drive score Sd evaluated by the evaluation unit 4A. Furthermore, the search unit 4C searches for a travel route that does not pass through the avoidance point specified by the specification unit 4B.SELECTED DRAWING: Figure 1

Description

  The present invention relates to a system, a program, and a method for searching a travel route to a destination of a vehicle that can automatically perform a plurality of operations of acceleration, steering, and braking.

  Conventionally, various methods for searching a travel route to a vehicle destination have been developed. For example, there are known techniques for searching for a travel route that requires the shortest time to the destination and a travel route that provides the shortest route to the destination. Further, based on vehicle characteristic information and road characteristic information, a method of searching for a travel route to a destination by excluding roads where it is difficult for the vehicle to pass is proposed (see Patent Document 1). ).

JP 2015-31533 A

  However, when the driver manually drives the vehicle, roads that can be safely passed and roads that are not safe are divided not only by the characteristics of the vehicle and the characteristics of the road but also by the driving skill of the driver. For this reason, with the technique as described in Patent Document 1, there is a possibility that a safe travel route cannot be searched when the driver manually operates the vehicle.

  In recent years, development of vehicles that can automatically perform a plurality of operations of acceleration, steering, and braking in place of a manual driving operation by a driver is underway. When such a vehicle is driven by an automatic driving operation, a road that can be safely passed and a road that is not so are separated according to the performance of an on-board sensor or communication device. For this reason, it is difficult to find an appropriate travel route in a vehicle route search that allows both manual driving operation and automatic driving operation.

  The present invention has been devised in view of such problems, and it is an object of the present invention to provide a route search system, a route search program, and a route search method capable of searching for a more appropriate travel route. I will. The present invention is not limited to this purpose, and is a function and effect derived from each configuration shown in the embodiment for carrying out the invention described later, and has another function and effect that cannot be obtained by conventional techniques. is there.

  (1) The route search system disclosed herein is a route search system that searches for a travel route to a vehicle destination that can automatically perform a plurality of operations of acceleration, steering, and braking without using a manual driving operation. And an evaluation unit for evaluating a performance score representing the automatic driving ability of the vehicle and a driving score representing a driving skill of the driver of the vehicle, and both the performance score and the driving score evaluated by the evaluation unit. Based on a plurality of candidate points on the map data, a specifying unit for specifying an avoidance point to be avoided by the vehicle, a search unit for searching for the travel route that does not pass the avoidance point specified by the specifying unit, It has.

  (2) It is preferable that a threshold value for specifying the avoidance point is set in advance for each of the candidate points. In this case, the evaluation unit evaluates the performance score higher as the automatic driving ability is higher, and evaluates the driving score higher as the driving skill is higher, and the specifying unit is evaluated by the evaluation unit. It is preferable that the candidate point having a total score that is a combination of the performance score and the driving score is less than the threshold is specified as the avoidance point.

(3) In the total score, it is preferable that a weight for the performance score and a weight for the driving score are equal to each other.
(4) Alternatively, in the total score, it is preferable that a weight for the performance score and a weight for the driving score are different from each other.
(5) It is preferable that the evaluation unit evaluates at least one of the performance score and the driving score for each candidate point.

(6) It is preferable that the route search system includes a learning unit that learns the driving skill, and the evaluation unit updates the driving score according to a learning result by the learning unit.
(7) The route search system includes an output unit that displays the avoidance point specified by the specifying unit and the travel route searched by the search unit on a display device mounted on the vehicle. preferable.

  (8) The route search program disclosed here executes a process of searching for a travel route to a vehicle destination where a plurality of operations of acceleration, steering, and braking can be automatically performed without using a manual driving operation. An evaluation step for evaluating a performance score representing an automatic driving ability of the vehicle and a driving score representing a driving skill of a driver of the vehicle, and the performance score and the driving evaluated in the evaluation step. Based on both of the scores, a specifying step for specifying an avoidance point to be avoided by the vehicle from a plurality of candidate points on map data, and a search for the travel route that does not pass through the avoidance point specified in the specifying step are performed. The search step is executed by a computer.

  (9) The route search method disclosed herein is a route search method for searching for a travel route to a vehicle destination where a plurality of operations of acceleration, steering, and braking can be automatically performed without using a manual driving operation. And an evaluation step for evaluating a performance score representing the automatic driving ability of the vehicle and a driving score representing a driving skill of the driver of the vehicle, and both the performance score and the driving score evaluated in the evaluation step. A step of specifying an avoidance point that the vehicle should avoid from a plurality of candidate points on map data, and a search step of searching for the travel route that does not pass through the avoidance point specified in the specification step; It has.

  In order to identify the avoidance point that the vehicle should avoid based on both the performance score representing the automatic driving ability of the vehicle and the driving score representing the driving skill of the driver, and to search for a travel route that does not pass the identified avoidance point, An appropriate driving route can be searched.

It is a block diagram which illustrates the whole structure of a route search system with a vehicle. It is a flowchart which illustrates the procedure of control implemented with a vehicle. It is a flowchart which illustrates the procedure of the route search method. 6 is a flowchart (sub-flowchart in FIG. 3) illustrating a performance score evaluation procedure. It is a flowchart (sub-flowchart of FIG. 3) illustrating the evaluation procedure of the driving score.

  A route search system, a route search program, and a route search method as embodiments will be described with reference to the drawings. The embodiment described below is merely an example, and there is no intention of excluding various modifications and technical applications that are not explicitly described in the following embodiment.

[1. overall structure]
The route search system according to the present embodiment searches for a travel route to the destination of the vehicle 10 shown in FIG. In the present embodiment, a case where the route search system includes a cloud server 4 that can search the travel routes of a large number of vehicles is illustrated. FIG. 1 illustrates one vehicle 10 whose travel route is searched by the cloud server 4.

  The vehicle 10 is configured to be able to travel by a manual driving operation by a driver and to automatically perform a plurality of operations among acceleration, steering, and braking without depending on the manual driving operation. That is, the vehicle 10 can automatically perform part or all of the operations required for traveling. Hereinafter, a state in which all operations of acceleration, steering, and braking of the vehicle 10 are manually performed by the driver is referred to as a “manual traveling state”, and one or more operations are automatically performed regardless of the driver. This state is called “automatic running state”.

  The vehicle 10 includes sensors 11 to 19 that detect information related to the vehicle 10, an operation screen 20 that can be operated by a driver of the vehicle 10, and devices 21 to 23 that actuate (accelerate, brake, and steer) the vehicle 10. Installed. Further, the vehicle 10 is provided with a control device 1 for controlling the operating state of the vehicle 10, and a communication device 2 and a navigation system 3 for acquiring information other than the vehicle 10.

  The vehicle speed sensor 11 and the acceleration sensor 12 detect the vehicle speed and the acceleration of the vehicle 10, respectively. The steering angle sensor 13 detects the steering angle of the steering. The brake sensor 14 and the accelerator sensor 15 detect the depression amounts of the brake pedal and the accelerator pedal. The front sensor 16 is, for example, a camera, a radar, an ultrasonic sensor, or the like, and acquires all information in front of the vehicle 10. The side sensor 17 is also a camera, a radar, an ultrasonic sensor, or the like, for example, and acquires all information on the side and rear of the vehicle 10.

  The in-vehicle camera 18 is for identifying the driver of the vehicle 10 and photographs the face of a person seated in the driver's seat of the vehicle 10. Information acquired by these sensors 11 to 18 is transmitted to the control device 1. The vehicle 10 only needs to be provided with at least a device that can identify the driver. For example, a sensor for detecting the fingerprint of the driver is incorporated in the steering of the vehicle 10 instead of the above-described camera 18 inside the vehicle. The driver may be identified from the fingerprint detected in step.

  The mode selection switch 19 is operated when the driver of the vehicle 10 sets and cancels the automatic driving mode. The automatic driving mode is one of the driving modes of the vehicle 10 and is a mode for setting the vehicle 10 in an automatic driving state. The mode selection switch 19 according to the present embodiment includes a switch unit disposed in a vehicle interior (for example, an instrument panel) and a detection unit that detects an operation on the switch unit. When the detection unit detects an operation (on operation, off operation) on the switch unit, the mode selection switch 19 transmits the operation content to the control device 1.

  The operation screen (display device) 20 is one of the elements constituting the navigation system 3 and is provided in the vehicle interior. The navigation system 3 contains detailed map data, and uses the signal from the GPS satellite and map data received by the communication device 2 to detect (recognize) the current position of the vehicle 10 and return to the destination. Route guidance is performed. On the operation screen 20, for example, a video (map information) in which a current position of the vehicle 10, a travel route to the destination (scheduled travel route) and the like are superimposed on a map, a destination list (character information), and the like are displayed. For example, when a destination is selected (input) by manual operation from information displayed on the operation screen 20, the destination information is transmitted to the navigation system 3. That is, the operation screen 20 is configured to be able to input a destination by manual operation.

  The drive device 21 is a drive source (engine or electric motor) of the vehicle 10 or a transmission mechanism. The brake device 22 is a brake device or a regenerative brake system that applies a braking force to the vehicle 10. The steering device 23 is an electric power steering device that assists the steering operation by the driver.

  The communication device 2 is an electronic control device that transmits and receives information by communicating with a communicable target other than the vehicle 10. Examples of objects with which the communication device 2 communicates include a GPS satellite, a cloud server 4, a roadside device arranged on a road, an external engine, a facility, and other vehicles. The communication device 2 transmits the received information to the control device 1 and transmits information corresponding to a command from the control device 1 to each target.

  The control device 1 is an electronic control device that performs integrated control of various devices mounted on the vehicle 10. The control device 1 is configured, for example, as an LSI device or an embedded electronic device in which a microprocessor, ROM, RAM, and the like are integrated, and is connected to a communication line of an in-vehicle network provided in the vehicle 10. When the automatic operation mode is set by the mode selection switch 19, the control device 1 of the present embodiment controls the devices 21 to 23 so that the vehicle 10 is in an automatic travel state. In addition, when the destination of the vehicle 10 is input to the operation screen 20, the control device 1 causes the cloud server 4 to search for a travel route to the destination, receives the search result, and displays it on the operation screen 20. Implement control.

  The control device 1 stores a vehicle ID and an automation level of the vehicle 10 in advance. The vehicle ID is for identifying each vehicle 10, and is, for example, a chassis number (frame number), a vehicle number (number plate number), or a vehicle identification number (VIN; Vehicle Identification Number). The automation level corresponds to the ability of each vehicle 10 to automatically run regardless of manual driving operation (automatic running ability), and depends on the performance of various sensors 11 to 17 and the communication device 2. Determined. Note that these vehicle IDs and automation levels are unique to each vehicle 10.

  The cloud server 4 is a computer that integrally manages information transmitted from each vehicle 10, and is provided outside the vehicle 10. The cloud server 4 is configured as, for example, an LSI device or an embedded electronic device in which a microprocessor, ROM, RAM, and the like are integrated, and is provided so as to be able to communicate with the communication device 2 of each vehicle 10 via the wireless network 5.

  The cloud server 4 of the present embodiment can execute a route search computer program (route search program) 6. The cloud server 4 retrieves and executes the computer program 6 to retrieve a travel route to the destination of the vehicle 10 and transmits the retrieval result to the communication device 2. The computer program 6 only needs to be provided so as to be executable by the cloud server 4. For example, the computer program 6 is stored in a storage device such as an HDD (Hard Disk Drive) or an SSD (Solid State Drive) in the cloud server 4. Or may be recorded in a medium readable by the cloud server 4 or an online storage on a network to which the cloud server 4 can be connected.

[2. System configuration]
The route search system searches for a travel route that allows the vehicle 10 to reach the destination more safely when the destination of the vehicle 10 is designated. In the route search system, a point to be avoided by the vehicle 10 (hereinafter referred to as an avoidance point) is specified on the map data based on both the automatic driving ability of the vehicle 10 and the driving skill of the driver, and the specified avoidance point. A travel route that does not pass (hereinafter referred to as an optimal route) is searched.

  The avoidance point is a point that is determined to be difficult to pass in the manual driving state or the automatic driving state, and is specified (specified) from the points that require special attention when passing. Hereinafter, “locations requiring special attention when passing” are referred to as candidate locations. Specific examples of candidate points include railroad crossings, narrow roads, sharp curves, accident-prone locations, and the like. The route search system searches for a route that bypasses an avoidance point specified from a plurality of candidate points, thereby enabling the vehicle 10 to travel more safely to the destination.

  The route search system according to this embodiment includes a control device 1, a communication device 2, and a cloud server 4 in addition to the navigation system 3. In the route search system, as described above, the learning unit 1A, the output unit 1B, the GPS receiving unit 2A, the inter-vehicle communication unit 2B, the road-to-vehicle communication unit 2C, the cloud communication unit 2D, An evaluation unit 4A, a specifying unit 4B, and a search unit 4C are provided. In the present embodiment, the learning unit 1A and the output unit 1B are provided in the control device 1, the GPS receiving unit 2A and the communication units 2B to 2D are provided in the communication device 2, and the evaluation unit 4A and the specifying unit 4B are provided in the cloud server 4. And the case where the search part 4C is provided is illustrated.

  Instead of the configuration described above, the function of the learning unit 1A may be provided in the cloud server 4, or the function of the GPS receiving unit 2A and the communication units 2B to 2D may be provided in the control device 1. Good. Alternatively, the functions of all the elements may be provided in the control device 1. In the present embodiment, each element described above is realized by software. However, part or all of the function of each element may be realized by hardware (electronic circuit), or software and hardware. And may be used in combination.

  In the present embodiment, each element 4 </ b> A to 4 </ b> C of the cloud server 4 is provided as a function of the computer program 6. In the route search system according to the present embodiment, the travel route to the destination of each vehicle 10 is searched by the cloud server 4 executing the computer program 6. In the cloud server 4, each piece of information processed by the control device 1 and the communication device 2 is referred to in order to search for a more appropriate travel route.

  The learning unit 1A learns the driving skill of the driver. The driving skill corresponds to the driving ability of the driver, such as the number and frequency of crossing the lane, the number and frequency of approaching obstacles, and the degree of deceleration at the intersection. The driving skill can be acquired from various information detected by the sensors 11 to 17, for example. The learning unit 1A of the present embodiment first identifies a driver based on information transmitted from the in-vehicle camera 18, and learns (monitors and stores) the driving skill for each driver. Each driver can be identified, for example, by comparing an image photographed by the in-vehicle camera 18 with preset user data.

  The output unit 1 </ b> B displays the travel route searched by the cloud server 4 on the operation screen 20 of the vehicle 10. The output unit 1 </ b> B of the present embodiment displays the avoidance point and the optimum route on the operation screen 20 based on the information received from the cloud server 4 via the communication device 2. That is, the output unit 1 </ b> B outputs a control signal for displaying the avoidance point and the optimum route on the operation screen 20.

  The GPS receiver 2A is an information terminal of the satellite positioning system, and acquires information on the current position of the vehicle 10 from the GPS satellite. The inter-vehicle communication unit 2 </ b> B communicates with other vehicles existing around the vehicle 10 to transmit / receive information to / from each other. For example, vehicle speed information and position information of each vehicle, road traffic information that each vehicle has known so far, and the like are transmitted to each other.

  The road-to-vehicle communication unit 2C communicates with roadside devices such as optical beacons and wireless communication devices installed in advance on roads and tracks, and road traffic information (for example, road construction information and level crossing information). Is received (acquired) and information related to the vehicle 10 (for example, information on the current position of the vehicle 10) is transmitted.

  The cloud communication unit 2D communicates with the cloud server 4 via the wireless network 5, receives (acquires) information stored (accumulated) in the cloud server 4, and transmits information related to the vehicle 10. Information received by the cloud communication unit 2D from the cloud server 4 includes information on the avoidance point specified by the cloud server 4, information on the optimum route searched by the cloud server 4, and the like. The information transmitted to the cloud server 4 by the cloud communication unit 2D includes the current location of the vehicle 10, the destination input on the operation screen 20, the vehicle ID and the automation level, the driver identification information, the learning result by the learning unit 1A, and the like. Information is included.

Hereinafter, the processing content of each element 4A-4C provided in the cloud server 4 is demonstrated.
Based on the information transmitted from the communication device 2, the evaluation unit 4 </ b> A (evaluation step) evaluates the performance score Sp that represents the automatic traveling ability of the vehicle 10 and the driving score Sd that represents the driving skill of the driver of the vehicle 10. Is. The performance score Sp is an index of the ability of the vehicle 10 to automatically travel by controlling at least one of the devices 21 to 23 by the control device 1 regardless of the manual driving operation of the driver. The driving score Sd is an index indicating the level of driving technology (capability) of a driver that drives the vehicle 10 by a manual driving operation regardless of the automatic driving capability of the vehicle 10.

  When the destination of the vehicle 10 is designated from the operation screen 20 by manual operation, the evaluation unit 4A of the present embodiment is configured for each candidate point existing on a normal travel route from the current position of the vehicle 10 to the destination. The performance score Sp and the driving score Sd are evaluated. Here, the “normal travel route” is a travel route that does not consider the above-described avoidance points, and includes, for example, a travel route that requires the shortest time and a travel route that has the shortest route. The normal travel route is searched by the search unit 4C, for example.

The evaluation unit 4A of the present embodiment evaluates both the performance score Sp and the driving score Sd for each candidate point. That is, two types of values, the performance score Sp and the driving score Sd, are set for each candidate point.
First, the performance score Sp evaluation process will be described. The evaluation unit 4A evaluates the performance score Sp based on the automation level of the vehicle 10. As described above, the automation level corresponds to the automatic travel capability, and is determined according to each performance of the sensors 11 to 17 and the communication device 2. Further, the automatic traveling ability varies depending on the road on which the vehicle travels. For example, the automatic driving ability at a level crossing is mainly determined according to the ability to recognize a level crossing existing ahead, whereas the automatic driving ability on a narrow road mainly depends on the ability to recognize an obstacle present on the side. Determined.

  For this reason, the evaluation unit 4A evaluates the performance score Sp according to the ability required for the vehicle 10 in the automatic traveling state to pass for each candidate point. For example, when the candidate point is a railroad crossing, the evaluation unit 4A includes the performances of the front sensor 16 and the road-vehicle communication unit 2C mounted on the vehicle 10 and the performance (capability) necessary for safely passing the railroad crossing. Are compared (determined), and the performance score Sp at the level crossing is determined (evaluated) according to the comparison result. Similarly, when the candidate point is a narrow road, the evaluation unit 4A performs the performances of the side sensor 17 and the road-to-vehicle communication unit 2C mounted on the vehicle 10 and the performance necessary for safely passing the narrow road. (Ability) is compared (determined), and a performance score Sp on a narrow road is determined (evaluated) according to the comparison result. As described above, the evaluation unit 4A according to the present embodiment determines and determines the performance score Sp for each candidate point based on the predetermined automation level of the vehicle 10.

  Next, the evaluation process of the driving score Sd will be described. The evaluation unit 4A evaluates the driving score Sd for each driver. That is, the evaluation unit 4A first identifies the driver and evaluates the driving skill of the identified driver. As a driver identification method, for example, a method similar to the driver identification method in the learning unit 1A described above can be applied.

  Here, the driving skill of each driver differs according to the road on which the vehicle travels, as in the above-described automatic travel capability. For example, although some drivers are good at driving a sharp curve by a manual driving operation, they may not be good at driving a narrow road by a manual driving operation. Therefore, the evaluation unit 4A evaluates the driving score Sd according to the experience of the driver traveling the vehicle 10 by manual driving operation for each candidate point. For example, when the candidate point is a sharp curve, the evaluation unit 4A determines that the driving skill is higher as the number or frequency of straddling the lane during the past sharp curve traveling is lower, and according to the determination result, The driving score Sd is determined (evaluated). Similarly, when the candidate point is a narrow road, the evaluation unit 4A determines that the driving skill is higher as the number of times and the frequency of approaching the obstacle when traveling on a narrow road in the past is smaller, and according to this determination result, Determine (evaluate) the driving score Sd on a narrow road.

  In addition, the evaluation unit 4A of the present embodiment updates the driving score Sd for each driver according to the learning result by the learning unit 1A. That is, the evaluation unit 4A changes the evaluation result of the driving score Sd in accordance with the change in the driving skill of the driver. Note that the evaluation unit 4A sets the driving score Sd to a predetermined initial value for a driver driving the vehicle 10 for the first time. Examples of the initial value include the lowest value of the driving score Sd (“1” in the present embodiment).

  The evaluation unit 4A of the present embodiment evaluates the performance score Sp higher as the automatic traveling ability of the vehicle 10 is higher, and evaluates the driving score Sd higher as the driver's driving skill is higher. In the present embodiment, a case will be described in which the evaluation unit 4A evaluates the performance score Sp and the driving score Sd in five stages using integers of 1 to 5. That is, the evaluation unit 4A evaluates the performance score Sp and the driving score Sd with the same scale (weighting).

  The specifying unit 4B (specifying step) specifies an avoidance point from among a plurality of candidate points on the map data based on both the performance score Sp and the driving score Sd evaluated by the evaluation unit 4A. The specifying unit 4B of the present embodiment calculates a total score S that combines the performance score Sp and the driving score Sd, and avoids candidate points where the calculated total score S is less than a preset threshold value Sth (S <Sth) Specify as a point. In this embodiment, in the total score S, a case where the weighting for the performance score Sp and the weighting for the driving score Sd are set to be equal to each other (S = Sp + Sd) is exemplified.

  Here, the threshold value Sth is a value for specifying the avoidance point, and is set in advance for each candidate point. The threshold value Sth is set according to, for example, an accident risk (possibility of an accident) for each candidate point. For example, in this embodiment, it is determined that the accident risk at a high accident location is higher than the accident risk at a level crossing. For this reason, in the following example, the crossing threshold value Sth is set to “5”, whereas the threshold value Sth for frequent accidents is set to “9”.

  Table 1 below shows each value of the performance score Sp and the driving score Sd for specifying the level crossing as an avoidance point. Similarly, Table 2 below shows each value of the performance score Sp and the driving score Sd for specifying the accident-prone location as an avoidance point. In these Tables 1 and 2, “x” indicates a case where it is specified as an avoidance point, and “◯” indicates a case where it is not specified as an avoidance point.

  As shown in Table 1, a level crossing is specified as an avoidance point when the total score S obtained by adding each value of the performance score Sp and the driving score Sd is less than “5” (see “X” in Table 1). Otherwise, it is not specified as an avoidance point (see ○ in Table 1). In other words, a level crossing is a safe passage point if at least one of the performance score Sp and the driving score Sd is high (for example, 4 or more), and the other is low (even 1). It is determined and is not excluded in the optimum route search process. In other words, there is a possibility that the route passing through the railroad crossing is searched as the optimum route.

  On the other hand, as shown in Table 2, accident-prone locations are identified as avoidance points when the total score S is less than 9 (see x in Table 2), and are not identified as avoidance points otherwise ( (See ○ in Table 2). That is, the accident-prone location is determined to be a safe place on the condition that both the performance score Sp and the driving score Sd are high, and is not excluded in the optimum route search process. In addition, although description is abbreviate | omitted here, threshold value Sth is similarly set also about candidate points other than a level crossing and an accident frequent occurrence location.

  In the present embodiment, it is assumed that the position information of each candidate point and the threshold value Sth information set for each candidate point are both stored in the storage device in the cloud server 4. However, the position information of each candidate point and the information on the threshold Sth need only be referred to at least by the specifying unit 4B and may not be stored in the cloud server 4. In addition, each information of the candidate point and the threshold value Sth may be updated as appropriate.

  The search unit 4C (search step) searches for the optimum route described above. A well-known method can be applied to the search by the search unit 4C. The search unit 4C may search for a plurality of optimum routes. For example, the search unit 4C may search for two of the optimum routes, the route that takes the shortest time to the destination and the route that takes the shortest way to the destination. In this case, both of these optimum routes may be displayed on the operation screen 20 by the output unit 1B, and the driver may select which optimum route to use.

[3. flowchart]
2 and 3 are flowcharts for explaining the control contents implemented in the above-described route search system. The flow of FIG. 2 is performed by the vehicle 10, and the flow of FIG. 3 is performed by the cloud server 4. . FIG. 3 shows a procedure (route search method) when the cloud server 4 executes the computer program 6, and FIGS. 4 and 5 are sub-flowcharts of FIG.

  The flow of FIG. 2 is started when the power of the vehicle 10 is turned on (when the navigation system 3 starts to operate) and is executed at a predetermined calculation cycle. Further, the flow of FIG. 3 is performed at a predetermined calculation cycle while the cloud server 4 is powered on. In the flow of FIG. 2, it is assumed that various types of information of the communication device 2 and the sensors 11 to 20 are acquired as needed.

  First, the flow performed in the vehicle 10 will be described. As shown in FIG. 2, in step A1, it is determined whether or not a new destination has been input on the operation screen 20. If a new destination has been input, a search request for a travel route and a vehicle in step A2 Various types of information related to 10 are transmitted from the communication device 2 to the cloud server 4. Thereby, the cloud server 4 starts searching for the optimum route. And it waits until the search result by the cloud server 4 is received (step A3), and when the search result is received, the optimum route and the avoidance point are displayed on the operation screen 20 by the output unit 1B (step A4). Return this flow.

  On the other hand, if a new destination is not input in step A1, it is determined in step A5 whether or not the vehicle 10 is in a manual travel state. If the vehicle 10 is in the manual travel state, the driving skill of the driver is learned by the learning unit 1A (step A6), and this flow is returned. If the vehicle 10 is not in the manual travel state in step A5, the flow is returned as it is (without learning the driving skill).

  Next, a flow executed in the cloud server 4 will be described. As shown in FIG. 3, in step B1, it is determined whether or not a search request from the communication device 2 has been received. If there is a search request from the vehicle 10, the process proceeds to step B2, otherwise this flow. To return. In step B2, for example, the search unit 4C searches for a normal travel route to the destination.

  Subsequent steps B3 and B4 are processes (evaluation steps) executed by the evaluation unit 4A. In Steps B3 and B4, each of the performance score Sp and the driving score Sd is evaluated for each candidate point on the normal travel route searched in Step B2. FIG. 3 illustrates the case where the performance score Sp evaluation process (step B3) is performed before the driving score Sd evaluation process (step B4). There is no particular limitation.

  As shown in FIG. 4, in the performance score Sp evaluation process (step B3), first, the automation level of the vehicle 10 is referred to from the information transmitted from the communication device 2 (step B11). Next, based on the automation level of the vehicle 10, the performance score Sp of the vehicle 10 is evaluated for each candidate point existing on the normal travel route (step B12), and this flow ends and the process proceeds to step B4.

  Further, as shown in FIG. 5, in the evaluation process (step B4) of the driving score Sd, first, a driver is identified based on information transmitted from the communication device 2 (step B21), and the identified driver is the first driver. Is determined (step B22). That is, in step B22, it is determined whether or not the driver who drives the vehicle 10 from here to the destination has experience of performing the manual driving operation of the vehicle 10.

  If the identified driver is the first driver, the driving score Sd is set to “1” at any candidate point (step B23). On the other hand, if the identified driver has traveling experience by manual driving operation of the vehicle 10, the past driving skill learning result (learning result in step A6) is referred to (step B24), and according to the learning result, The past driving score Sd is updated for each candidate point (step B25). Then, this flow is finished and the process proceeds to Step B5.

  As shown in FIG. 3, step B5 is a process (specific step) executed by the specifying unit 4B. In step B5, an avoidance point is specified from candidate points on a normal travel route based on both the performance score Sp and the driving score Sd evaluated in each of steps B3 and B4. That is, for each candidate point, the magnitude relationship between the total score S obtained by summing the performance score Sp and the driving score Sd and the threshold value Sth is determined, and all candidate points satisfying “S <Sth” are specified as avoidance points. When all candidate points do not satisfy “S <Sth”, it is determined that there is no avoidance point.

  Subsequent steps B6 to B8 are processes (search steps) executed by the search unit 4C. In Step B6, it is determined whether there is an avoidance point on the normal travel route. If there is an avoidance point, the process proceeds to step B7, and the optimum route is searched. On the other hand, if there is no avoidance point, the process proceeds to step B8, and the normal travel route is searched (set) as the optimum route. In step B9, the avoidance point specified in step B5 and the optimum route searched in step B7 or step B8 are transmitted to the control device 1 via the communication device 2, and this flow is returned.

[4. effect]
(1) In the route search system, the computer program 6 and the route search method described above, an avoidance point is specified based on both the performance score Sp and the driving score Sd, and a travel route that does not pass through the specified avoidance point (optimum route) Is searched. For this reason, an avoidance point can be specified more appropriately than when an avoidance point is specified based on one of the performance score Sp and the driving score Sd, and a more appropriate travel route can be searched.

  For example, if the driving score Sd is high even if the performance score Sp is low, the vehicle 10 can be safely driven by a manual driving operation by the driver. be able to. Further, for example, since accidents frequently occur at a high risk of accidents, safety can be improved by specifying them as avoidance points unless both the performance score Sp and the driving score Sd are high. Thus, according to the route search system, the computer program 6 and the route search method described above, a more appropriate travel route can be found while ensuring safety.

(2) In the specifying unit 4B described above, an avoidance point is specified based on the total score S that is a combination of the performance score Sp and the driving score Sd. Specifically, the total score S is compared with a threshold value Sth set in advance for each candidate point, and a candidate point having a total score S less than the threshold value Sth is specified as an avoidance point. By using the total score S as described above, the avoidance point is specified based on the comprehensive index of the automatic traveling ability of the vehicle 10 and the driving skill of the driver, and thus a more appropriate traveling route can be searched.
(3) At this time, as described above, by making the weighting of the performance score Sp and the driving score Sd in the total score S equal to each other, it is possible to reduce the calculation load for calculating the total score S, contributing to cost reduction. can do.

  (4) Since each of the performance score Sp and the driving score Sd is evaluated for each candidate point in the evaluation unit 4A described above, the performance score Sp and the driving score Sd are more appropriately evaluated according to the characteristics of each candidate point. be able to. For example, when there is a difference in performance between the front sensor 16 and the side sensor 17, there is a difference between the automatic traveling ability at a level crossing and the automatic traveling ability on a narrow road. By evaluating Sp, it is possible to set a more accurate performance score Sp. Similarly, depending on the driver, there may be a difference in driving skill between sharp curves and narrow roads. By evaluating the driving score Sd separately on sharp curves and narrow roads, a more accurate driving score Sd can be obtained. Can be set. As described above, since the more accurate performance score Sp and driving score Sd are set, the avoidance point can be more appropriately specified, and thus a more appropriate travel route can be found.

  (5) In the evaluation part 4A mentioned above, since the driving score Sd is updated according to the driving skill of the driver learned in the learning part 1A, a more accurate driving score Sd can be set. That is, since the driving skill of the driver can change according to experience, aging, etc., the driving score Sd is updated even if the driving skill changes by updating the driving score Sd according to the learning result by the learning unit 1A. Can be evaluated appropriately. Thereby, since an avoidance point can be specified more appropriately, a more appropriate travel route can be found.

  (6) Since the output unit 1B displays the avoidance point and the optimum route on the operation screen 20, the driver of the vehicle 10 can visually confirm the avoidance point and the travel route to the destination. Therefore, it is possible to improve convenience, and even when driving away from the optimum route at the discretion of the driver, it is possible to avoid the avoidance point (or pass carefully) and to improve safety. Can do. In addition, by displaying the avoidance point together with the optimum route, even if the optimum route is a detour route, it is possible to make it difficult for the driver to feel uncomfortable.

[5. Others]
Regardless of the embodiment described above, various modifications can be made without departing from the spirit of the invention. Each structure of this embodiment can be selected as needed, or may be combined appropriately.

  In embodiment mentioned above, although the case where the route search system included the cloud server 4 which can search the driving route of many vehicles was illustrated, it replaced with this and the function of each part 4A-4C of the cloud server 4 is carried out for every vehicle. The cloud server 4 may be omitted from the route search system. That is, the route search system described above may be provided exclusively for one vehicle 10, for example.

  Moreover, each evaluation method of the performance score Sp and the driving score Sd described above is an example. The driving score Sd of each driver may be evaluated in consideration of not only the vehicle 10 but also manual driving experience in vehicles other than the vehicle 10. Specifically, in the cloud server 4, regardless of the type of vehicle, the cumulative travel distance traveled by the manual driving operation is managed for each driver, and the longer the cumulative travel distance is, the higher the driving skill is. The score Sd may be evaluated. Alternatively, the cloud server 4 may grasp the accident experience of each driver in the manual driving state and evaluate the driving score Sd based on the accident experience. Further, the driving score Sd may be estimated based on the accumulated travel distance in the vehicle 10 of the driver. Specifically, it may be estimated that the driving skill of the driver is higher as the accumulated traveling distance in the vehicle 10 is longer, and the driving score Sd may be evaluated according to the estimation result.

Further, the driving score Sd may not be updated. In this case, since the driving score Sd is set as a fixed value for each driver, the evaluation process of the driving score Sd can be simplified, which can contribute to cost reduction.
Further, since the automation level does not change for each vehicle, the performance score Sp may be set as a fixed value for each vehicle. In this case, for example, the evaluation result of the performance score Sp of each vehicle may be stored in the cloud server 4, and the stored performance score Sp may be referred to based on the vehicle ID. Thereby, the evaluation process of the performance score Sp can be simplified, and it can contribute to cost reduction.

  In the embodiment described above, the case where each of the performance score Sp and the driving score Sd is evaluated for each candidate point has been described, but instead, either one of the performance score Sp or the driving score Sd is set for each candidate point. It may be evaluated. Also in this case, since one of the performance score Sp and the driving score Sd can be set more accurately, the avoidance point can be specified more appropriately, and a more appropriate travel route can be found. Instead of the configuration in which the performance score Sp and the driving score Sd are evaluated for each candidate point, the same performance score Sp and driving score Sd may be set for each candidate point. In this case, each evaluation process of the performance score Sp and the driving score Sd can be simplified, which can contribute to cost reduction.

  In the above-described embodiment, the case where the weights of the performance score Sp and the driving score Sd in the total score S are set to be equal to each other is illustrated. However, the weighting of the performance score Sp and the driving score Sd in the total score S is different from each other. May be. For example, in the total score S, the weight for the performance score Sp may be twice the weight for the driving score Sd. Specifically, the evaluation unit 4A may evaluate the performance score Sp in ten levels using integers of 1 to 10, and may evaluate the driving score Sd in five levels using integers of 1 to 5.

  In this case, the maximum value of the performance score Sp is “10”, whereas the maximum value of the driving score Sd is “5”, so the contribution of the performance score Sp to the total score S is Double the contribution. Further, even in the same five-level evaluation, for example, the performance score Sp is an even value (ie, 2, 4, 6, 8, 10), and the driving score Sd is increased by 1 as described above (1, 2, 3) , 4, and 5), the weighting of the performance score Sp and the driving score Sd in the total score S may be different from each other. Thus, by appropriately setting the contribution of the performance score Sp and the contribution of the driving score Sp to the total score S, the automatic driving ability of the vehicle 10 and the driving skill of the driver can be combined more appropriately. Therefore, an avoidance point can be specified more appropriately.

  Note that the method of specifying the avoidance point is not limited to the method based on the magnitude relationship between the total score S and the threshold value Sth described above. For example, instead of using the total score S described above, two threshold values for the performance score Sp and the driving score Sd are set at each candidate point, and the performance score Sp and the driving score Sd are set for each threshold value. You may specify an avoidance point by comparing individually. Alternatively, instead of using the threshold value Sth, the avoidance point may be specified based on the type of candidate point (whether it is a railroad crossing or a frequent accident location). Further, the initial value of the driving score Sd described above is not limited to the lowest value, and may be an average value, for example.

DESCRIPTION OF SYMBOLS 1 Control apparatus 1A Learning part 1B Output part 2 Communication apparatus 4 Cloud server 4A Evaluation part 4B Identification part 4C Search part 6 Computer program (route search program)
10 vehicle 20 operation screen (display device)
S total score
Sd driving score
Sp performance score
Sth threshold

Claims (9)

A route search system for searching a travel route to a destination of a vehicle capable of automatically performing a plurality of operations of acceleration, steering and braking without depending on a manual driving operation,
An evaluation unit that evaluates a performance score representing the automatic driving ability of the vehicle and a driving score representing the driving skill of the driver of the vehicle;
Based on both the performance score and the driving score evaluated by the evaluation unit, a specifying unit that specifies an avoidance point that the vehicle should avoid from a plurality of candidate points on map data;
A route search system, comprising: a search unit that searches for the travel route that does not pass through the avoidance point specified by the specification unit. Each of the candidate points has a preset threshold value for specifying the avoidance point,
The evaluation unit evaluates the performance score higher as the automatic driving ability is higher, and evaluates the driving score higher as the driving skill is higher.
The said specific | specification part specifies the said candidate point whose sum total score which combined the said performance score evaluated by the said evaluation part and the said driving score is less than the said threshold value as the said avoidance point, The characterized by the above-mentioned. The described route search system. 3. The route search system according to claim 2, wherein, in the total score, a weight for the performance score and a weight for the driving score are equal to each other. The route search system according to claim 2, wherein, in the total score, a weight for the performance score and a weight for the driving score are different from each other. 5. The route search system according to claim 1, wherein the evaluation unit evaluates at least one of the performance score and the driving score for each candidate point. A learning unit for learning the driving skill;
The route evaluation system according to claim 1, wherein the evaluation unit updates the driving score according to a learning result by the learning unit. The output part which displays the said avoidance point specified by the said specific part and the said driving | running route searched by the said search part on the display apparatus mounted in the said vehicle is characterized by the above-mentioned. 7. The route search system according to any one of 6 above. A route search program for executing a process of searching for a travel route to a vehicle destination capable of automatically performing a plurality of operations of acceleration, steering and braking independently of a manual driving operation,
An evaluation step for evaluating a performance score representing the automatic driving ability of the vehicle and a driving score representing the driving skill of the driver of the vehicle;
Based on both the performance score and the driving score evaluated in the evaluation step, a specifying step of specifying an avoidance point that the vehicle should avoid from a plurality of candidate points on map data;
A route search program that causes a computer to execute a search step of searching for the travel route that does not pass through the avoidance point specified in the specifying step. A route search method for searching for a travel route to a vehicle destination capable of automatically performing a plurality of operations of acceleration, steering and braking independently of a manual driving operation,
An evaluation step for evaluating a performance score representing the automatic driving ability of the vehicle and a driving score representing the driving skill of the driver of the vehicle;
Based on both the performance score and the driving score evaluated in the evaluation step, a specifying step of specifying an avoidance point that the vehicle should avoid from a plurality of candidate points on map data;
A route search method comprising: a search step of searching for the travel route that does not pass through the avoidance point specified in the specification step.

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