Navigation system, navigation method, and navigation program

Abstract

A processor of a navigation system for navigating a plurality of autonomous travel devices that travel autonomously using power supplied from a battery is configured so as to perform: optimization of a queue form on the basis of travel resistance, which varies during future travel, of at least one autonomous travel device among the autonomous travel devices that travel in the queue form; and navigating each autonomous driving device into the optimized queue form.

Description

[0001] Cross-references of related applications

[0002] This application is based on Japanese Patent Application No. 2022-133583 filed in Japan on August 24, 2022, and the entire contents of the basic application are incorporated by reference. Technical Field

[0003] The present disclosure relates to a navigation technology for navigating a plurality of autonomous driving devices. Background Art

[0004] The navigation technology disclosed in Patent Document 1 connects respective main driving devices that drive autonomously using power supplied from a battery, thereby minimizing the total power consumption of these devices.

[0005] Prior art literature

[0006] Patent Literature

[0007] Patent Document 1: U.S. Patent No. 10108202

[0008] In the navigation technology disclosed in Patent Document 1, the driving order of electrically connected respective main driving devices is adjusted in order to minimize the total electric energy. However, it has been found that the total electric energy is more affected by other driving factors than the driving order. Summary of the invention

[0009] The technical problem of the present disclosure is to provide a navigation system that suppresses power consumption. Another technical problem of the present disclosure is to provide a navigation method that suppresses power consumption. Another technical problem of the present disclosure is to provide a navigation program that suppresses power consumption.

[0010] Hereinafter, the technical means of the present disclosure for solving the technical problems will be described.

[0011] A first aspect of the present disclosure is a navigation system,

[0012] The navigation system includes a processor and performs navigation for a plurality of autonomous driving devices that autonomously drive using power supplied from a battery, wherein:

[0013] The processor is configured to perform:

[0014] Optimizing the platoon formation based on a driving resistance of at least one autonomous driving device among the respective autonomous driving devices traveling in the platoon formation that changes in future driving; and

[0015] Navigate each driver's vehicle into an optimized platoon formation.

[0016] A second aspect of the present disclosure is a navigation method,

[0017] The navigation method is executed by a processor and is used to navigate a plurality of autonomous driving devices that use power supplied from a battery to drive autonomously, and includes:

[0018] Optimizing the platoon formation based on a driving resistance of at least one autonomous driving device among the respective autonomous driving devices traveling in the platoon formation that changes in future driving; and

[0019] Navigate each driver's vehicle into an optimized platoon formation.

[0020] A third aspect of the present disclosure is a navigation program,

[0021] The navigation program includes commands stored in a storage medium and executed by a processor, and is used to navigate a plurality of autonomous driving devices that drive autonomously using power supplied from a battery, wherein:

[0022] The command contains:

[0023] Optimizing the platoon formation based on a driving resistance of at least one autonomous driving device among the respective autonomous driving devices traveling in the platoon formation that changes in future driving; and

[0024] Navigate each driver's vehicle into an optimized platoon formation.

[0025] According to the first to third aspects, the platoon formation is optimized based on the driving resistance of at least one autonomous driving device among the respective autonomous driving devices traveling in the platoon formation that changes in future travel. As a result, it is possible to provide a platoon formation that can reduce power consumption from the perspective of driving resistance affecting total power and navigate the respective autonomous driving devices. Therefore, it is possible to suppress total power consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a schematic diagram showing the navigation system according to the first embodiment.

[0027] Figure 2 It is a diagram showing the structure of the autonomous driving device according to the first embodiment.

[0028] Figure 3 This is a block diagram showing the autonomous driving device according to the first embodiment.

[0029] Figure 4 It is a block diagram showing the navigation system according to the first embodiment.

[0030] Figure 5 1 is a functional block diagram showing a processing device of the navigation system according to the first embodiment.

[0031] Figure 6This is a flowchart showing the navigation flow of the first embodiment.

[0032] Figure 7 It is a schematic diagram showing the running resistance according to the first embodiment.

[0033] Figure 8 It is a schematic diagram showing the running resistance according to the first embodiment.

[0034] Fig. 9 It is a schematic diagram showing the running resistance according to the first embodiment.

[0035] Fig.10 It is a schematic diagram showing the running resistance according to the first embodiment.

[0036] Fig.11 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0037] Fig.12 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0038] Fig.13 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0039] Fig.14 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0040] Fig.15 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0041] Fig.16 It is a schematic diagram showing the optimization of the queue form according to the first embodiment.

[0042] Fig.17 It is a schematic diagram showing the wind direction assumed in the first embodiment.

[0043] Fig.18 This is a schematic diagram showing optimization restrictions of the queue form according to the first embodiment.

[0044] Fig.19 This is a schematic diagram showing optimization restrictions of the queue form according to the first embodiment.

[0045] Fig. 20 This is a schematic diagram showing a use case of optimization of the queue form according to the first embodiment.

[0046] Fig.21 This is a flowchart showing the navigation flow of the second embodiment.

[0047] Fig. 22 It is a schematic diagram showing the optimization of the queue form according to the second embodiment.

[0048] Fig.23 It is a schematic diagram showing the optimization of the queue form according to the second embodiment.

[0049] Fig.24 It is a diagram showing the structure of an autonomous driving device according to a third embodiment.

[0050] Fig.25 It is a block diagram showing an autonomous driving device according to a third embodiment.

[0051] Fig.26 It is a schematic diagram showing the optimization of the queue form according to the third embodiment.

[0052] Fig. 27 It is a schematic diagram showing the optimization of the queue form according to the third embodiment.

[0053] Fig.28 This is a flowchart showing the navigation flow of the third embodiment.

[0054] Fig.29 It is a schematic diagram showing the optimization of the queue form according to the third embodiment.

[0055] Fig.30 This is a flowchart showing the navigation flow of the fourth embodiment. DETAILED DESCRIPTION

[0056] Hereinafter, a plurality of embodiments of the present disclosure will be described based on the accompanying drawings. In addition, sometimes the same symbols are used for corresponding constituent elements in each embodiment, thereby omitting repeated descriptions. In addition, when only a part of the composition is described in each embodiment, the composition of other embodiments described previously can be applied to the other parts of the composition. Furthermore, not only the combination of compositions clearly indicated in the description of each embodiment, but also the compositions of a plurality of embodiments can be partially combined with each other even if not clearly indicated, as long as there is no particular obstacle to the combination.

[0057] (First Embodiment)

[0058] Figure 1 The navigation system 10 of the first embodiment shown navigates a plurality of autonomous driving devices 1 that drive autonomously. Each autonomous driving device 1 that is the object of navigation by the navigation system 10 can drive autonomously in any direction of forward, backward, left, or right according to the navigation. The autonomous driving device 1 here can be a delivery vehicle that drives autonomously on the road and delivers goods to the delivery destination. The autonomous driving device 1 can also be a logistics vehicle that drives autonomously inside and outside a warehouse and transports goods. The autonomous driving device 1 can also be a disaster rescue robot that drives autonomously in a disaster area and transports supplies or collects information. The autonomous driving device 1 can of course also be other types.

[0059] like Figure 2 , 3 Each autonomous driving device 1 shown is configured to include: a vehicle body 2, a drive system 3, a sensor system 4, a communication system 5, a map database 6, an information display system 7, and a control system 8. The autonomous driving devices 1 may have completely or substantially the same configuration, or may have different configurations within the scope of the functions of the components 2 to 8.

[0060] The vehicle body 2 is formed into a hollow shape by metal, etc. The vehicle body 2 holds other components of the autonomous driving device 1 inside or from the inside to the outside. The vehicle body 2 and wheels 30 described later in the drive system 3 together form the external shape of the autonomous driving device 1.

[0061] The drive system 3 includes wheels 30, a battery 32, and an electric actuator 34. The plurality of wheels 30 are configured to be independently rotatable. Among the plurality of wheels 30, a pair of drive wheels 300, one each provided on the left and right sides of the vehicle body 2, are independently driven by separate electric actuators 34. In particular, in the present embodiment, the driving state of the autonomous driving device 1 is switched to one of forward driving and turning driving according to the rotation speed difference (i.e., the rotation speed difference per unit time) between the drive wheels 300.

[0062] Specifically, the autonomous driving device 1 is driven forward within a range where the rotation speed difference between the left and right driving wheels 300 is zero or can be virtually zero. On the other hand, within a range where the rotation speed difference between the left and right driving wheels 300 increases, the turning radius of the autonomous driving device 1 driven to turn decreases as the rotation speed difference increases. The turning radius here refers to the distance between the vertical center line of the vehicle body 2 and the turning center of the turning drive when viewed from above, so the turning drive in which the turning radius is substantially reduced to zero is particularly called a point turning drive.

[0063] like Figure 2 As shown, the plurality of wheels 30 may include at least one driven wheel 301 that rotates following the driving wheel 300. Here, in particular, in the present embodiment, there are one driven wheel 301 in front of each driving wheel 300, that is, two driven wheels 301 on the left and right.

[0064] Figure 2 , 3The battery 32 shown is mainly composed of a storage battery such as a lithium ion battery. The battery 32 uses external charging to store power supplied to the electrical components of the autonomous driving device 1 by discharging. The battery 32 can also recover and store regenerative power generated by the electric actuator 34 that can perform regenerative braking on the drive wheel 300. The battery 32 is connected to the electric actuator 34, the sensor system 4, the communication system 5, the map database 6, the information display system 7, and the control system 8 via a wiring harness, etc. so that power can be supplied.

[0065] Figure 2 , 3 The pair of electric actuators 34 shown are mainly composed of a motor and a motor drive circuit. Each electric actuator 34 independently drives the corresponding drive wheel 300 to rotate using the power supply from the battery 32, thereby allowing the autonomous driving device 1 to drive autonomously. Each electric actuator 34 may have a regenerative function of applying regenerative braking to the corresponding drive wheel 300 to generate regenerative power. Each electric actuator 34 may be provided with an electric brake unit 340 that mechanically brakes the corresponding drive wheel 300. Each electric actuator 34 may also be an electric locking unit that only mechanically locks the corresponding drive wheel 300.

[0066] The sensor system 4 obtains sensor information that can be used in navigation and autonomous driving of the autonomous driving device 1 by sensing the inner and outer worlds of the autonomous driving device 1. Specifically, the sensor system 4 includes at least one inner world sensor 40 and one outer world sensor 41. The inner world sensor 40 obtains inner world information as sensor information from the inner world that is the internal environment of the autonomous driving device 1. The inner world sensor 40 may also be a motion detection type that obtains the inner world information by detecting a specific motion physical quantity in the inner world of the autonomous driving device 1. The inner world sensor 40 of the motion detection type is, for example, at least one of a velocity sensor, an acceleration sensor, and a yaw rate sensor.

[0067] The external sensor 41 obtains external information as sensing information from the outside world which is the surrounding environment of the autonomous driving device 1. The external sensor 41 may also be an object detection type that obtains external information by detecting an object existing outside the autonomous driving device 1. The external sensor 41 of the object detection type is, for example, at least one of a camera, LiDAR (Light Detection and Ranging / Laser Imaging Detection and Ranging), radar, and sonar. The external sensor 41 is a positioning type that obtains external information by receiving a positioning signal from an artificial satellite of a GNSS (Global Navigation Satellite System) existing outside the autonomous driving device 1. The external sensor 41 of the positioning type is, for example, a GNSS receiver.

[0068] Figure 3 The communication system 5 shown sends and receives communication information related to navigation and autonomous driving of the autonomous driving device 1 through wireless communication with the outside world of the autonomous driving device 1. The communication system 5 may also be a V2X type that sends and receives communication information with a V2X system that exists outside the autonomous driving device 1. The V2X type communication system 5 is, for example, at least one of a DSRC (Dedicated Short Range Communications) communicator and a cellular V2X (C-V2X) communicator. The communication system 5 may also be a terminal communication type that sends and receives communication information with a mobile terminal that exists outside the autonomous driving device 1. The terminal communication type communication system 5 is, for example, at least one of a Bluetooth (registered trademark) device, a Wi-Fi (registered trademark) device, and an infrared communication device.

[0069] The map database 6 acquires map information that can be used in navigation and autonomous driving of the autonomous driving device 1 from the navigation system 10 through the communication system 5 and stores the map information. The map database 6 is mainly composed of at least one non-transitory tangible storage medium that can store map information, such as a semiconductor memory, a magnetic medium, and an optical medium.

[0070] The map information stored in the map database 6 is digitized in two or three dimensions as information representing the driving environment of the autonomous driving device 1. The map information may be road information including at least one of the position, shape, and road surface conditions of the road itself. The map information may also include marking information including at least one of the position and shape of signs and dividing lines attached to the road. The map information may also include structure information including at least one of the position and shape of buildings and traffic lights facing the road.

[0071] The information presentation system 7 presents notification information of the autonomous driving device 1 to the outside world in relation to the navigation and autonomous driving of the autonomous driving device 1. The information presentation system 7 may present the notification information by stimulating the vision of a person outside the autonomous driving device 1. The information presentation system 7 of the visual stimulation type is, for example, at least one of a monitoring unit and a light emitting unit. The information presentation system 7 may present the notification information by stimulating the hearing of a person outside the autonomous driving device 1. The information presentation system 7 of the auditory stimulation type is, for example, at least one of a speaker, a buzzer, and a vibration unit.

[0072] Figure 2 , 3 The control system 8 shown is mainly composed of at least one dedicated computer. The dedicated computer constituting the control system 8 has at least one memory 80 and a processor 81. The memory 80 is a non-transitory tangible storage medium (non-transitory tangible storage medium) such as a semiconductor memory, a magnetic medium, and an optical medium, which stores programs and data that can be read by the computer in a non-transitory manner. The processor 81 includes, for example, at least one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a RISC (Reduced Instruction Set Computer)-CPU, etc. and uses it as a core.

[0073] The control system 8 is connected to the battery 32, the electric actuator 34, the sensor system 4, the communication system 5, the map database 6, and the information display system 7 via at least one of a LAN (Local Area Network) line, a harness, and an internal bus. The control system 8 controls each connected object by executing a plurality of commands of a control program stored in a memory 80 by a processor 81, so that autonomous driving according to the navigation from the navigation system 10 is realized through the autonomous driving device 1.

[0074] Figure 1The navigation system 10 shown is constructed in a remote center that navigates a plurality of autonomous driving devices 1 through remote management. Figure 4 As shown, the navigation system 10 is, for example, at least one of a cloud server, an edge server, etc. that includes a map database 100 , a communication system 110 , and a processing device 120 .

[0075] The map database 100 updates the map information used for navigating each autonomous driving device 1 to the latest information at any time and stores it. The structure of the map database 100 in the navigation system 10 is based on the structure of the map database 6 in the autonomous driving device 1, but stores map information with a larger capacity than the latter that can cover the autonomous driving area (hereinafter referred to as the navigation area) of the fully autonomous driving device 1 that is the navigation target.

[0076] The communication system 110 is mainly composed of a communication device that assumes at least a part of the V2X system that can communicate with the communication system 5 of each master driving device 1. The processing device 120 is connected to the map database 100 and the communication system 110 via at least one of a wired communication line and a wireless communication line. With respect to the navigation area of ​​each master driving device 1, in addition to the map information of the map database 100, at least one environmental information such as traffic information, road information, weather information, and scene information obtained through the communication system 110 is provided to the processing device 120 at any time. With respect to the future travel of each master driving device 1, target travel information including, for example, destination information, travel route information, and planning information obtained through the communication system 110 is provided to the processing device 120 at any time or is planned by the processing device 120.

[0077] The processing device 120 is configured to include at least one dedicated computer. The dedicated computer constituting the processing device 120 has at least one memory 130 and a processor 131. The configuration of the memory 130 and the processor 131 in the processing device 120 is based on the configuration of the memory 80 and the processor 81 of the control system 8 in the autonomous driving device 1, but is a configuration with higher functions than the latter memory 80 and the processor 81.

[0078] In the navigation system 10, the processing device 120 executes a plurality of commands of the processing program stored in the memory 130 through the processor 131. Thus, the processing device 120 completes the navigation processing for navigating a plurality of (in this embodiment, a pair of two) autonomous driving devices 1 that drive autonomously using the power supply from the battery 32 into a platoon form. In such a processing device 120, a plurality of functional blocks for completing the navigation processing are constructed. Figure 5 As shown, the functional blocks constructed in this way include a planning block 150 , an optimization block 160 , and a navigation block 170 .

[0079] The processing device 120 performs navigation for the driving of each of the main driving devices 1 in a platoon configuration (hereinafter also referred to as platoon driving) by the cooperation of these blocks 150, 160, and 170 according to the navigation method Figure 6 The navigation process shown is executed. When a platoon travel request is generated for a pair of autonomous driving devices 1 during the activation of the navigation system 10, the navigation process is executed. In addition, each "S" in the navigation process means a plurality of steps executed according to a plurality of commands included in the navigation program.

[0080] In S100, the planning block 150 obtains route information as information related to the driving route for each autonomous driving device 1 to travel in a platoon. The route information may also include, for example, destination information and waypoint information to be reached by each autonomous driving device 1 through platoon driving. The route information may include path information that the autonomous driving device 1 explores through platoon driving according to the destination information and waypoint information. The route information may include driving road information, which indicates, for example, the top view shape of the driving road, the slope angle of the driving road, and the road friction coefficient of the driving road at each driving location or each driving section according to the route information. The route information may also include environmental information, which indicates, for example, wind direction and wind speed at each driving location according to the route information.

[0081] In S101, in order to select the autonomous driving device 1 to be the target of platoon driving based on the route information, the planning block 150 obtains device information from the autonomous driving device 1 that is the candidate for selection. The selected candidates may be set as at least two autonomous driving devices 1 that are not executing a task at a driving position that can participate in platoon driving according to the path information in the route information. The device information may include battery information indicating the state of the battery 32 of the autonomous driving device 1 that is the candidate for selection, such as the charging state and the degradation state. The device information may include actuator information indicating the state of each electric actuator 34 in the autonomous driving device 1 that is the candidate for selection, such as the degradation state and the regeneration characteristics due to braking. The device information may also include shape information indicating the external shape of the autonomous driving device 1 that is the candidate for selection. The device information may also include motion information indicating the motion physical quantity of the autonomous driving device 1 that is the candidate for selection, such as the driving speed.

[0082] In the next S102, the planning block 150 selects a pair of autonomous driving devices 1 to be the platooning target based on the route information, based on the device information obtained from each of the candidate selection master driving devices 1. When there are three or more selection candidates at this time, the respective master driving devices 1 to be the platooning target may be selected in order from the selection candidates with less degradation of the battery 32. When there are three or more selection candidates, the respective master driving devices 1 to be the platooning target may be selected in order from the selection candidates with less degradation of the electric actuator 34. When there are three or more selection candidates, the respective master driving devices 1 to be the platooning target may be selected in order from the selection candidates with less degradation of the electric actuator 34. When there are three or more selection candidates, the respective master driving devices 1 to be the platooning target may be selected in order from the selection candidates with less air resistance when traveling alone.

[0083] In the next S103, the optimization block 160 optimizes the platoon configuration of the platoon based on the driving resistance Rr that changes in the future driving of at least one of the respective autonomous driving devices 1 to be platooned. Specifically, based on the driving resistance Rr monitored by at least one autonomous driving device 1, Figures 7-10 The air resistance Rra and wind resistance Rrw shown complete the optimization of the queue shape.

[0084] The air resistance Rra here is the driving resistance Rr that depends on the driving speed Vr generated by the autonomous driving device 1. The air resistance Rra can be, for example, Figures 7-10 The drag value proportional to the driving direction projection area Ar and the driving speed Vr of the autonomous driving device 1 is calculated. The driving direction projection area Ar is defined as the projection area of ​​the external shape of the autonomous driving device 1 from the rear side to the front side in the driving direction. The driving direction projection area Ar is identified based on the shape information in the device information obtained in S101. The driving speed Vr is identified based on the motion information in the device information obtained in S101.

[0085] On the other hand, the wind resistance Rrw is a driving resistance Rr that depends on the wind speed Vw acting on the autonomous driving device 1. Figures 7-10 As shown in FIG. 1 , the wind resistance Rrw can be calculated as a resistance value proportional to the wind direction projection area Aw of the autonomous driving device 1 and the wind speed Vw. The wind direction projection area Aw here is the projection area of ​​the appearance of the autonomous driving device 1 projected in the opposite direction to the wind direction. Therefore, especially in the opposite direction to the driving direction, Fig. 9 The wind resistance Rrw in the tailwind state Wt (described later) is defined as a negative resistance that becomes a propulsion force for the autonomous driving device 1. The wind direction projection area Aw is identified based on the shape information in the device information obtained in S101. The wind direction and wind speed Vw are identified based on the environmental information in the route information obtained in S100.

[0086] In the optimization of S103, one of the longitudinal configuration Po and the parallel configuration Pa is selected at each driving location or each driving section. The longitudinal configuration Po is as follows: Figures 11 to 13 15, the autonomous driving devices 1 are arranged in a queue in the longitudinal direction Lo of the driving path, and the parallel configuration Pa is that the autonomous driving devices 1 are arranged in a queue in the transverse direction La of the driving path. Fig.14 , 16 That is, a longitudinal configuration Po in which the arrangement direction of each main driving device 1 is the longitudinal direction Lo and a parallel configuration Pa in which the arrangement direction of each main driving device 1 is the lateral direction La are assumed as the configuration of the selectively optimized queue each time the future driving is performed. In any of these longitudinal configurations Po and parallel configurations Pa, for each of the main driving devices 1, the front and rear of the driving direction along the longitudinal direction Lo of the driving road may be always fixed or may be switched according to the driving scene.

[0087] In the optimization of S103, the autonomous driving device 1 that is traveling at the head of the platoon in the assumption of the tandem configuration Po is defined as the head device 1h, and the autonomous driving device 1 that is traveling after the head device 1h in the assumption of the tandem configuration Po is defined as the following device 1s. Therefore, the optimization block 160 in S103 assumes that the distance in the longitudinal direction Lo of each of the main driving devices 1 of the platoon driving object is separated by a set distance or more. Fig.19 ) are compared with each other. Thus, the optimization block 160 allocates the respective master driving devices 1 of the platoon driving objects as the leading device 1h and the following devices 1s based on the comparison results of their respective driving resistances Rr. At this time, the autonomous driving device 1 with a smaller driving resistance Rr, such as air resistance Rra, can be allocated as the leading device 1h.

[0088] Furthermore, the optimization block 160 in S103 optimizes the queue shape based on the correlation between the air resistance Rra and the wind resistance Rrw, which is assumed to be the driving resistance Rr in the independent driving shape Ps of the subsequent device 1s. At this time, in contrast to the subsequent device 1s focusing on the air resistance Rra and the wind resistance Rrw, the leading device 1h traveling ahead can also be set to the side with smaller air resistance Rra based on the appearance shape based on the shape information in the device information obtained through S101. The leading device 1h traveling ahead can also be set to the side with more free charging capacity based on the charging state of the battery 32 based on the battery information in the device information obtained through S101.

[0089] In relation to the subsequent device 1s Figure 7In the case where the wind resistance Rrw is substantially zero and the air resistance Rra acts in the windless state Wn, in S103, regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra, the optimization block 160 optimizes the queue shape to Fig.11 The longitudinal column form Po shown. The windless state Wn here can be defined as a state where the wind speed Vw based on the environmental information in the route information obtained by S100 is zero or less than a wind judgment threshold value that can be virtually zero (e.g., 1.4 m / s, etc.). Therefore, in the windless state Wn where the wind resistance Rrw is zero or can be virtually zero, by selecting the longitudinal column form Po as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the longitudinal direction Lo.

[0090] In regard to the subsequent device 1s Figure 8 In the case where the wind resistance Rrw and the air resistance Rra act together in the windward state Wf, in S103, regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra, the optimization block 160 optimizes the queue shape to Fig.12 The windward state Wf here can be defined as, for example, a state where the wind speed Vw based on the environmental information obtained through S100 exceeds zero or exceeds the wind judgment threshold, and as Fig.17 As shown, the wind direction based on the same environmental information is within the windward judgment angle α (e.g., 10 degrees) on the left and right sides based on the driving direction. In other words, the windward state Wf can be set to a state in which the subsequent device 1s receives a longitudinal Lo component from the front or a wind that can be virtualized as the component. Therefore, in the windward state Wf in which the direction of action of the wind resistance Rrw is the opposite direction of the driving direction or can be virtualized as the opposite direction, by selecting the longitudinal column form Po as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the longitudinal Lo.

[0091] In connection with the subsequent device 1s Fig. 9 When the absolute value of the wind resistance Rrw acting in the tailwind state Wt is larger than the absolute value of the air resistance Rra, in S103, the optimization block 160 optimizes the queue shape to Fig.13 The downwind state Wt here can be defined as a state where the wind speed Vw based on the environmental information obtained through S100 exceeds zero or exceeds the wind judgment threshold, and Fig.17As shown, the wind direction based on the same environmental information is within the state of the downwind judgment angle β (for example, 10 degrees, etc.) on the left and right sides based on the opposite direction of the driving direction. In other words, the downwind state Wt can be set to a state in which the subsequent device 1s is subjected to the longitudinal Lo component or can be virtualized as the wind of this component. Therefore, in the downwind state Wt in which the direction of the wind resistance Rrw with an absolute value smaller than the air resistance Rra is in the opposite direction of the driving direction or can be virtualized as the reverse direction, by selecting the longitudinal column form Po as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the longitudinal Lo.

[0092] When the absolute value of the air resistance Rra is smaller than the absolute value of the wind resistance Rrw acting in the tailwind state Wt on the subsequent device 1s, in S103, the optimization block 160 optimizes the queue configuration to Fig.14 The parallel form Pa shown. The downwind state Wt here can be defined as the same as above. Therefore, in the downwind state Wt where the direction of the wind resistance Rrw, whose absolute value is greater than the air resistance Rra, is opposite to the direction of travel or can be virtualized as the opposite direction, by selecting the parallel form Pa as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the horizontal La.

[0093] When the air resistance Rra is substantially equal to the wind resistance Rrw in the tailwind state Wt, the queue shape can be optimized as follows: Fig.13 When the air resistance Rra is substantially equal to the wind resistance Rrw in the tailwind state Wt, the queue shape can be optimized as follows: Fig.14 The parallel form of Pa.

[0094] In connection with the subsequent device 1s to Fig.10 When the wind resistance Rrw acting on the crosswind state Wc is larger than the air resistance Rra, in S103, the optimization block 160 optimizes the queue shape to Fig.15 The crosswind state Wc here can be defined as a state where the wind speed Vw based on the environmental information obtained through S100 exceeds zero or exceeds the wind judgment threshold, and the wind direction based on the same environmental information is Fig.17 In other words, the crosswind state Wc can be set so that the subsequent device 1s is subjected to wind of at least the lateral La component outside the headwind judgment angle α and outside the downwind judgment angle β. Therefore, in the crosswind state Wc where the lateral La component of the wind resistance Rrw, which is smaller than the air resistance Rra, increases, by selecting the longitudinal column form Po as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the longitudinal Lo.

[0095] In the case where the air resistance Rra is smaller than the wind resistance Rrw acting on the subsequent device 1s in the crosswind state Wc, in S103, the optimization block 160 optimizes the queue configuration to Fig.16 The parallel form Pa shown. The crosswind state Wc here can be defined as the same as above. Therefore, in the crosswind state Wc where the lateral La component of the wind resistance Rrw that is larger than the air resistance Rra increases, by selecting the parallel form Pa as the queue form, it can be said that the arrangement direction of each device 1h, 1s is optimized to the lateral La. At this time, in particular, the queue form can be optimized so that along the lateral La component of the wind direction based on the environmental information obtained through S100, the representative points (such as the center point, etc.) of the longitudinal Lo of the head device 1h and the subsequent device 1s are as follows: Fig.16 In addition, it can also be optimized as a parallel form Pa in which the representative points of the longitudinal direction Lo of the leading device 1h and the subsequent devices 1s are arranged in reverse order along the lateral La component of the wind direction.

[0096] When the air resistance Rra is substantially equal to the wind resistance Rrw in the crosswind state Wc, the queue shape can be optimized as follows: Fig.15 When the air resistance Rra is substantially equal to the wind resistance Rrw in the crosswind state Wc, the queue shape can be optimized as follows: Fig.16 The parallel form of Pa.

[0097] However, even in Fig.14 , 19 In the case where the width of the lateral direction La of the travel path traveled by each device 1h, 1s is narrower than the width of the lateral direction La required for the parallel configuration Pa, the optimization block 160 in S103 restricts the optimization of the queue configuration to the parallel configuration Pa. Fig.18 The column shape Po shown as the queue shape can also be Fig.19 As shown, by canceling the platoon driving itself, a single driving mode Ps is selected in which the distance in the longitudinal direction Lo between the devices 1h and 1s is separated by a set distance or more. Fig.18 , 19 Both indicate Fig.14 An example corresponding to the situation.

[0098] Here, from another perspective, the width of the running road in the lateral direction La exceeds the necessary width of the parallel configuration Pa. Fig.14 , 16 In the case of , it can be said that the optimization to the parallel form Pa is achieved. Figures 11 to 13In the case of 15, it can be said that the longitudinal distance Lo is shortened to be smaller than the above-mentioned set distance between the devices 1h and 1s, and optimization toward the longitudinal shape Po is achieved. Fig. 20 As shown, when the devices 1h, 1s in the longitudinal form Po in the headwind state Wf turn right (example in the same figure) or left, the parallel form Pa (example in the same figure) or longitudinal form Po corresponding to the magnitude relationship between the air resistance Rra and the wind resistance Rrw in the crosswind state Wc is realized.

[0099] like Figure 6 As shown, in S104 following S103, the navigation block 170 navigates each device 1h, 1s to the queue form selected for each driving location or each driving section in S103 according to the path information in the route information obtained in S100. At this time, the navigation block 170 may also monitor the navigation status of each device 1h, 1s based on the device information of each device 1h, 1s obtained in S101. In addition, since S104 ends, the current execution of the navigation process also ends.

[0100] (Effect)

[0101] Next, the effects of the first embodiment described above will be described.

[0102] According to the first embodiment, the platoon formation is optimized based on the driving resistance Rr that changes in the future driving of at least one of the respective autonomous driving devices 1 traveling in the platoon formation. As a result, it is possible to provide a platoon formation that can reduce power consumption from the perspective of the driving resistance Rr of the total power and navigate the respective autonomous driving devices 1. Therefore, it is possible to suppress the consumption of the total power.

[0103] According to the first embodiment, the formation of the queue is optimized based on the air resistance Rra which is the running resistance Rr depending on the running speed Vr generated by the autonomous driving device 1, and the wind resistance Rrw which is the running resistance Rr depending on the wind speed Vw acting on the autonomous driving device 1. Thus, from the viewpoint of the air resistance Rra and the wind resistance Rrw which are particularly important for the total electric energy in the running resistance Rr, it is possible to provide a queue direction that can reduce power consumption and navigate each autonomous driving device 1. Therefore, it is possible to reliably suppress the consumption of total electric energy.

[0104] In the first embodiment, in the column configuration Po which is a queue configuration arranged in the longitudinal direction Lo, the autonomous driving device 1 traveling at the head of the queue and the autonomous driving device 1 traveling thereafter are defined as the head device 1h and the following device 1s, respectively. Therefore, according to the first embodiment, when the air resistance Rra of the following device 1s acts in the windless state Wn, the queue configuration is optimized to the column configuration Po arranged in the longitudinal direction Lo. Thus, in the windless state Wn where the total electric energy is only limited by the air resistance Rra, the air resistance Rra on the following device 1s side can be reduced as much as possible to reduce power consumption by utilizing the column configuration Po in which the devices 1h and 1s are arranged in the longitudinal direction Lo. Therefore, the accuracy of suppressing the consumption of the total electric energy can be improved.

[0105] According to the first embodiment, when the air resistance Rra of the subsequent device 1s acts in the windward state Wf, the queue shape is optimized to the longitudinal shape Po. Therefore, in the windward state Wf where the total electric energy is controlled by both the air resistance Rra and the wind resistance Rrw, the longitudinal shape Po in which the devices 1h and 1s are arranged in the longitudinal direction Lo can reduce the two resistances Rra and Rrw on the side of the subsequent device 1s as much as possible to reduce power consumption. Therefore, the accuracy of suppressing the consumption of the total electric energy can be improved.

[0106] According to the first embodiment, when the air resistance Rra of the subsequent device 1s is greater than the wind resistance Rrw (absolute value) in the downwind state Wt, the queue shape is optimized to the column shape Po. Thus, in the downwind state Wt where the total electric energy is more dominated by the air resistance Rra than the wind resistance Rrw, the column shape Po in which the devices 1h and 1s are arranged in the longitudinal direction Lo can reduce the air resistance Rra on the side of the subsequent device 1s as much as possible and reduce power consumption. Therefore, the accuracy of suppressing the consumption of total electric energy can be improved.

[0107] According to the first embodiment, when the air resistance Rra of the following device 1s is greater than the wind resistance Rrw in the crosswind state Wc, the queue shape is optimized to the longitudinal shape Po. Thus, in the crosswind state Wc where the total electric energy is more dominated by the air resistance Rra than the wind resistance Rrw, the longitudinal shape Po in which the devices 1h and 1s are arranged in the longitudinal direction Lo can reduce the air resistance Rra on the side of the following device 1s as much as possible and reduce the power consumption. Therefore, the accuracy of suppressing the consumption of the total electric energy can be improved.

[0108] According to the first embodiment, when the air resistance Rra of the following device 1s is less than the wind resistance Rrw (absolute value) in the downwind state Wt, the queue shape is optimized to the parallel shape Pa arranged in the horizontal direction La. Thus, in the downwind state Wt where the total electric energy is more dominated by the wind resistance Rrw than the air resistance Rra, the wind resistance Rrw on the side of the following device 1s can be used as a propulsion force to reduce power consumption by using the parallel shape Pa in which the devices 1h and 1s are arranged in the horizontal direction La. Therefore, the accuracy of suppressing the consumption of the total electric energy can be improved.

[0109] According to the first embodiment, when the air resistance Rra of the following device 1s is smaller than the wind resistance Rrw in the crosswind state Wc, the queue configuration is optimized to the parallel configuration Pa. Thus, in the crosswind state Wc where the total electric energy is more dominated by the wind resistance Rrw than the air resistance Rra, the wind resistance Rrw on the side of the following device 1s can be reduced as much as possible by using the parallel configuration Pa in which the devices 1h and 1s are arranged in the lateral direction La, thereby reducing the power consumption. Therefore, the accuracy of suppressing the consumption of the total electric energy can be improved.

[0110] According to the first embodiment, when the lateral width of the travel path on which each device 1h, 1s travels is narrower than the lateral width required for the parallel configuration Pa, optimization to the parallel configuration Pa is restricted. Thus, in a travel scenario where continuation of platoon travel should be prioritized over suppression of total electric energy consumption, priority continuation of the platoon travel can be achieved.

[0111] (Second Embodiment)

[0112] The second embodiment is a modification of the first embodiment.

[0113] like Fig.21 As shown, in the navigation process of the second embodiment, S2103 is executed instead of S103 of the first embodiment. Specifically, in S2103, when the air resistance Rra of the subsequent device 1s is less than the wind resistance Rrw in the crosswind state Wco including the longitudinal Lo component, as shown in FIG. Fig. 22 As shown, the optimization block 160 optimizes the formation into a goose-stack formation Pao. Here, the side wind state Wco including the longitudinal Lo component can be defined as a state where the wind direction based on the environmental information obtained by S100 is outside the side wind judgment angle γ (e.g., 10 degrees) before and after the lateral La as a reference. In other words, the side wind state Wco can be assumed to be a state where the subsequent device 1s is subjected to an oblique wind including the lateral La component and the longitudinal Lo component.

[0114] Such a goose-stack parallel configuration Pao optimized for the crosswind state Wco including the longitudinal Lo component is a parallel configuration in which the devices 1s and 1h arranged along the lateral direction La are staggered front and back in the driving direction along the longitudinal Lo. At this time, in particular, by arranging the representative points (such as the center point, etc.) of the longitudinal Lo of the leading device 1h and the subsequent devices 1s in sequence along the wind direction based on the environmental information obtained through S100, the queue configuration is optimized to the goose-stack parallel configuration Pao in which these representative points are staggered in the longitudinal Lo. In addition, it can also be optimized to the goose-stack parallel configuration Pao in which the representative points of the longitudinal Lo of the leading device 1h and the subsequent devices 1s are arranged in the opposite order along the wind direction.

[0115] However, in S2103, when the air resistance Rra of the subsequent device 1s is smaller than the wind resistance Rrw in the crosswind state Wc with the wind direction within the crosswind judgment angle γ, Fig.23 As shown, the optimization block 160 optimizes the queue configuration to a completely parallel configuration Pa. Therefore, in a crosswind state Wc where the wind resistance Rrw greater than the air resistance Rra acts in the lateral direction La or can be virtually the lateral direction La, it can be said that the queue configuration is optimized to a completely parallel configuration Pa with substantially no displacement in the traveling direction along the longitudinal direction Lo, similar to the case of the first embodiment.

[0116] When the air resistance Rra is substantially equal to the wind resistance Rrw in the crosswind state Wco and Wc, the queue shape can be optimized as follows: Fig. 22 , 23 The queue configuration in which the air resistance Rra is substantially equal to the wind resistance Rrw in the crosswind state Wco and Wc can be optimized as in the first embodiment. Fig.15 The parallel form Pa. In addition, except for the above-described points, S2103 is executed in the same manner as S103 of the first embodiment.

[0117] According to the second embodiment described above, when the air resistance Rra of the subsequent device 1s is less than the wind resistance Rrw in the side wind state Wco including the longitudinal Lo component, the queue form is optimized to a goose-step parallel form Pao arranged along the lateral La staggered on the longitudinal Lo in the parallel form. Thus, even in a scenario where the total electric energy is greatly influenced by the wind resistance Rrw of the side wind, especially the oblique wind, it is possible to realize a queue form in which each device 1h, 1s is staggered on the longitudinal Lo according to the ratio of the lateral La component to the longitudinal Lo component of the oblique wind. Therefore, the wind resistance Rrw of the oblique wind on the side of the subsequent device 1s can be reduced, power consumption can be reduced, and thus high accuracy in suppressing the consumption of total electric energy can be ensured.

[0118] (Third Embodiment)

[0119] The third embodiment is a modification of the first embodiment.

[0120] like Figures 24 to 27 As shown, the drive system 3003 of the third embodiment includes connection units 3036 and 3037. The longitudinal connection units 3036 are respectively held at the front and rear of the vehicle body 2 to connect the devices 1h and 1s arranged in the longitudinal direction Lo in the longitudinal configuration Po. The transverse connection units 3037 are respectively held at the left and right of the vehicle body 2 to connect the devices 1h and 1s arranged in the transverse direction La in the parallel configuration Pa.

[0121] Each connection unit 3036, 3037 is mainly composed of, for example, an electric connector that can mechanically connect and disconnect the units in a complementary relationship. Each connection unit 3036, 3037 is connected to the control system 8. Thus, the control system 8 controls each connection unit 3036, 3037 to connect and disconnect the devices 1h, 1s.

[0122] In the navigation process of the third embodiment, Fig.28 As shown, S3105 to S3109 are added between S103 and S104 described in the first embodiment. Specifically, in S3105, the optimization block 1600 determines whether there is a downhill section based on the driving road information in the route information obtained in S100, and the downhill section is a driving section where the driving road to be driven by each device 1h, 1s in the future becomes a downhill section. At this time, if there is a downhill section where the slope angle of the driving road is greater than the slope judgment threshold (for example, 3 degrees) on the downhill side, a positive determination is made, and on the other hand, a negative determination is made in other cases.

[0123] If the result of S3105 is a negative determination, the navigation flow skips S3106 to S3109 and moves to S104, thereby limiting the optimization of the mutual connection form Pc described later in S3109. On the other hand, if the determination is positive, the navigation flow moves to S3106.

[0124] In S3106 , the optimization block 160 estimates the regenerative power generated by the regenerative braking in the downhill section in the electric actuator 34 of each device 1 h , 1 s based on the actuator information in the device information acquired in S101 .

[0125] In parallel with S3106 or before or after S3106 ( Fig.28 In the example of S3107 executed in the optimization block 160, the one with the larger free capacity of the battery 32 in each device 1h, 1s is selected as Fig.26 , 27The recovery device 1c illustrated in FIG. Based on the battery information in the device information acquired in S101 and the route information in the route information acquired in S100, the remaining capacity of the battery 32 of each device 1h or 1s at that time is estimated for the downhill section.

[0126] In S3108 transferred after the execution of S3106 and S3107, the optimization block 160 determines whether the free capacity in the battery 32 of the recovery device 1c is insufficient relative to the total of the regenerative power generated by each device 1h, 1s. As a result, in the case of a positive determination, the navigation process skips S3109 and transfers to S104, thereby limiting the optimization to the interconnection form Pc through S3109. On the other hand, in the case of a negative determination, that is, when the total of the regenerative power generated by each device 1h, 1s exceeds the free capacity in the battery 32 of the recovery device 1c, the navigation process transfers to S3109.

[0127] In S3109, the optimization block 160 optimizes the queue configuration in the downhill section to an interconnected configuration Pc in which the regenerative power generated by each interconnected device 1h, 1s is recovered by the battery 32 of the recovery device 1c. In the interconnected configuration Pc at this time, Fig.26 , 27 , 29, the queue form optimized by S103 is maintained for the driving location or driving section corresponding to the downhill section. Therefore, the mutual connection form Pc is selected as a queue form in which the devices 1h and 1s are connected to each other by the single-side unit corresponding to the optimized form in S103 in the connection units 3036 and 3037. In addition, Fig.26 , 29 Indicates that the Fig.13 An example of recycling regenerative power in the interconnected form Pc of the optimized form of the column form Po. Fig. 27 Indicates that the Fig.14 An example of recovery of regenerative power in an interconnected form Pc of an optimized parallel form Pa.

[0128] Thus, when S3109 is finished, the navigation process shifts to S104. However, in S104 of the third embodiment, each device 1h, 1s is navigated to the queue form selected for each travel point or each travel section by the route steps in S103 and S3109.

[0129] According to the third embodiment described above, when each device 1h, 1s is traveling on a downhill section, the platoon configuration is optimized to an interconnected configuration Pc in which the regenerative power generated by each interconnected device 1h, 1s is recovered by the battery 32 of one of these devices 1h, 1s. Thus, in a scenario where each device 1h, 1s can generate regenerative power, the regenerative power can be efficiently recovered by sharing the battery 32 of one of the interconnected configurations Pc. Therefore, the total electric energy consumption suppressed by the optimization of the platoon configuration based on the air resistance Rra and the wind resistance Rrw can be further supplemented by regeneration, and the suppression effect can be significantly improved.

[0130] Here, in particular, in the third embodiment, the side with more free capacity in the battery 32 of the devices 1h and 1s is defined as the recovery device 1c that recovers the regenerative power. Therefore, according to the third embodiment, when the free capacity in the battery 32 of the recovery device 1c, which is one of the devices 1h and 1s, is insufficient relative to the total of the regenerative power generated by each device 1h and 1s, the optimization to the interconnected form Pc is restricted. As a result, in a scenario where the effect of recovering regenerative power is reduced due to insufficient free capacity on the side of the recovery device 1c, the optimization of the queue form from the perspective of air resistance Rra and wind resistance Rrw can be prioritized over the optimization to the interconnected form Pc. Therefore, in this case, while significantly suppressing the consumption of total electric energy, it is possible to suppress overcharging of the battery 32 in the recovery device 1c.

[0131] (Fourth Embodiment)

[0132] The fourth embodiment is a modification of the third embodiment.

[0133] In the navigation process of the fourth implementation mode, as Fig.30 As shown, S4108 replacing S3107 and S3108 of the third embodiment and S4109 replacing S3109 of the third embodiment are executed. Specifically, in S4108, the optimization block 160 determines whether the total of the free capacity in the battery 32 of each device 1h, 1s of the autonomous driving device 1 as the platoon driving object is insufficient relative to the total of the regenerative power generated by these devices 1h, 1s. Based on the battery information in the device information obtained in S101 and the path information in the route information obtained in S100, the free capacity in the battery 32 of each device 1h, 1s at this time is estimated for the downhill section.

[0134] If the result of S4108 is a positive determination, the navigation process skips S4109 and transfers to S104, thereby limiting the optimization of the interconnected form Pc described later through S4109. In addition, if the result of S3105 is a negative determination, the navigation process skips S3106, S4108, and S4109 and transfers to S104, thereby also limiting the optimization of the interconnected form Pc through S4109.

[0135] On the other hand, if the result of S4108 is a negative determination, that is, if the total of the free capacity in each battery 32 of these devices 1h, 1s exceeds the total of the regenerative power generated by each device 1h, 1s, the navigation process transfers to S4109. In S4109, the optimization block 160 optimizes the queue configuration in the downhill section to an interconnected configuration Pc in which the regenerative power generated by each interconnected device 1h, 1s is recovered by at least one battery 32 with free capacity among the batteries 32 of these devices 1h, 1s. At this time, the interconnected configuration Pc also becomes a configuration in which the devices 1h, 1s are connected to each other while maintaining the queue configuration optimized in S103 for the driving location or driving section corresponding to the downhill section.

[0136] Thus, when S4109 is finished, the navigation flow shifts to S104. However, in S104 of the fourth embodiment, each device 1h, 1s is navigated to the queue form selected for each travel point or each travel section by the route steps in S103 and S4109.

[0137] According to the fourth embodiment described above, when each device 1h, 1s is traveling on a downhill section, the platoon configuration is optimized to an interconnected configuration Pc in which the regenerative power generated by each interconnected device 1h, 1s is recovered by at least one battery 32 in these devices 1h, 1s. Thus, in a scenario where each device 1h, 1s can generate regenerative power, the regenerative power can be efficiently recovered by sharing at least one battery 32 using the interconnected configuration Pc. Therefore, the total electric energy consumption suppressed by the optimization of the platoon configuration based on the air resistance Rra and the wind resistance Rrw is further supplemented by regeneration, and the suppression effect can be significantly improved.

[0138] Here, in particular, according to the fourth embodiment, when the total of the free capacity in the battery 32 of each device 1h, 1s is insufficient relative to the total of the regenerative power generated by each device 1h, 1s, the optimization to the interconnected form Pc is restricted. Thus, in a scenario where the efficiency of recovering regenerative power is reduced due to the insufficient free capacity of the overall battery 32, the optimization of the queue form from the perspective of air resistance Rra and wind resistance Rrw can be prioritized over the optimization to the interconnected form Pc. Therefore, in this case, while significantly suppressing the consumption of total electric energy, it is possible to suppress overcharging of the battery 32 in the two devices 1h, 1s.

[0139] (Other embodiments)

[0140] Although a plurality of embodiments have been described above, the present disclosure is not to be construed as being limited to these embodiments, and various embodiments and combinations can be applied without departing from the gist of the present disclosure.

[0141] In a modified example, a dedicated computer constituting the control system 8 of the navigation system 10 and / or the processing device 120 of the autonomous driving device 1 has at least one of a digital circuit and an analog circuit as a processor. The digital circuit here is, for example, at least one of an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), an SOC (System on a Chip), a PGA (Programmable Gate Array), and a CPLD (Complex Programmable Logic Device). In addition, such a digital circuit may also have a memory for storing a program.

[0142] In the windless state Wn of the modified example, the parallel state Pa can also be selected. In the windless state Wn of the modified example, the individual driving state Ps of each device 1h, 1s can also be selected. In the windward state Wf of the modified example, the parallel state Pa can also be selected. In the windward state Wf of the modified example, the individual driving state Ps of each device 1h, 1s can also be selected.

[0143] In the tailwind state Wt of the modified example, it is also possible that the optimization of the queue form is limited to the longitudinal form Po regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra. In the tailwind state Wt of the modified example, it is also possible that the optimization of the queue form is limited to the parallel form Pa (including the switching between the fully parallel form Pa and the goose-step parallel form Pao of the second embodiment) regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra. In the tailwind state Wt of the modified example, it is also possible to select the separate driving form Ps of each device 1h, 1s instead of at least one of the longitudinal form Po and the parallel form Pa corresponding to the magnitude relationship between the wind resistance Rrw and the air resistance Rra.

[0144] In the crosswind state Wc of the modified example, it is also possible that the optimization of the queue form is limited to the longitudinal form Po regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra. In the crosswind state Wc of the modified example, it is also possible that the optimization of the queue form is limited to the parallel form Pa (including the switching between the full parallel form Pa and the goose-step parallel form Pao of the second embodiment) regardless of the magnitude relationship between the wind resistance Rrw and the air resistance Rra. In the crosswind state Wc of the modified example, it is also possible to select the single driving form Ps of each device 1h, 1s instead of at least one of the longitudinal form Po and the parallel form Pa corresponding to the magnitude relationship between the wind resistance Rrw and the air resistance Rra.

[0145] In a modified example, the formation of a platoon of more than three autonomous driving devices 1 may also be optimized. In addition to a two-wheel drive type that can turn according to a rotation speed difference, the autonomous driving device 1 of the modified example may also be a two-wheel drive type or a four-wheel drive type that can turn according to steering. Furthermore, in this modified example, at least one driven wheel 301 may be included.

[0146] In a variation, the second embodiment may be combined with the third and fourth embodiments. However, in this variation, the en-stack parallel configuration Pao that is about to become the mutually connected configuration Pc may be switched to the mutually connected configuration Pc of the completely parallel configuration Pa that is substantially not offset in the longitudinal direction Lo.

[0147] In addition to the above description, the above-mentioned embodiments and modifications may be implemented in the form of a processing circuit (e.g., a processing ECU, etc.) or a semiconductor circuit (e.g., a semiconductor chip, etc.) as a navigation system that can be mounted on the autonomous driving device 1 and replaces the function of the processing device 120 through the control system 8.

[0148] (P.S.)

[0149] In this specification, the following multiple technical concepts and multiple combinations thereof are disclosed.

[0150] (Technical Thought 1)

[0151] A navigation system having a processor (131) and navigating a plurality of autonomous driving devices (1) that autonomously drive using power supplied from a battery (32), wherein:

[0152] The processor is configured to execute:

[0153] Optimizing the platoon formation based on a driving resistance (Rr) that changes in future driving of at least one of the autonomous driving devices traveling in the platoon formation; and

[0154] Each of the autonomous driving devices is navigated into the optimized queue configuration.

[0155] Furthermore, the technical idea 1 and the technical ideas 2 to 10 described later can also be realized in the form of methods and programs.

[0156] (Technical Thought 2)

[0157] The navigation system described in technical concept 1, wherein:

[0158] The optimization of the queue form includes:

[0159] The queue shape is optimized based on air resistance (Rra) and wind resistance (Rrw), wherein the air resistance is the driving resistance depending on the driving speed generated by the autonomous driving device, and the wind resistance is the driving resistance depending on the wind speed acting on the autonomous driving device.

[0160] (Technical Thought 3)

[0161] The navigation system described in technical idea 2, wherein:

[0162] The optimization of the queue form includes:

[0163] In the column form (Po) as the column form arranged vertically, when the autonomous driving device traveling after the autonomous driving device traveling at the head of the column is defined as a subsequent device (1s),

[0164] In at least one of a case where the air resistance of the subsequent device acts in a headwind state and a case where the air resistance of the subsequent device acts in a windless state, the queue form is optimized to the vertical column form.

[0165] (Technical Thought 4)

[0166] The navigation system described in technical concept 3, wherein:

[0167] The optimization of the queue form includes:

[0168] In at least one of the cases where the air resistance of the subsequent device is greater than the wind resistance in a crosswind state and the case where the air resistance of the subsequent device is greater than the wind resistance in a tailwind state, the queue form is optimized to the vertical column form.

[0169] (Technical Thought 5)

[0170] The navigation system according to technical idea 3 or 4, wherein:

[0171] The optimization of the queue form includes:

[0172] In at least one of the cases where the air resistance of the subsequent device is smaller than the wind resistance in a crosswind state and the case where the air resistance of the subsequent device is smaller than the wind resistance in a tailwind state, the queue form is optimized into a horizontal row form (Pa) arranged laterally.

[0173] (Technical Thought 6)

[0174] The navigation system described in technical concept 5, wherein:

[0175] The optimization of the queue form includes:

[0176] When the air resistance of the subsequent device is less than the wind resistance in the crosswind state including the longitudinal component, the queue form is optimized to a goose-shaped parallel form (Pao) among the parallel forms, which are arranged laterally in a longitudinally staggered manner.

[0177] (Technical Thought 7)

[0178] The navigation system according to technical idea 5 or 6, wherein:

[0179] The optimization of the queue form includes:

[0180] When the lateral width of the travel path on which each of the autonomous driving devices travels is narrower than the lateral width required for the parallel configuration, optimization to the parallel configuration is restricted.

[0181] (Technical Thought 8)

[0182] The navigation system according to any one of technical concepts 1 to 7, wherein:

[0183] The optimization of the queue form includes:

[0184] When each of the autonomous driving devices is traveling on a downhill section, the platoon configuration is optimized to an interconnected configuration (Pc) in which the regenerative power generated by each of the interconnected autonomous driving devices is recovered by the battery of at least one of the autonomous driving devices.

[0185] (Technical Thought 9)

[0186] The navigation system described in technical idea 8, wherein:

[0187] The optimization of the queue form includes:

[0188] When the autonomous driving device having a larger free capacity in the battery is defined as a recovery device (1c) for recovering the regenerative power,

[0189] When the remaining capacity of the battery of the recovery device is insufficient relative to the total of the regenerative electric power generated by each of the autonomous driving devices, optimization to the interconnected state is restricted.

[0190] (Technical Thought 10)

[0191] The navigation system described in technical idea 8, wherein:

[0192] The optimization of the queue form includes:

[0193] When the total of the available capacities in the batteries of the autonomous driving devices is insufficient for the total of the regenerative electric power generated by the autonomous driving devices, optimization to the interconnected state is restricted.

Claims

1. A navigation system comprising a processor (131) and navigating a plurality of autonomous driving devices (1) that autonomously drive using power supplied from a battery (32), characterized in that: The processor is configured to execute: optimizing the platoon formation based on a driving resistance (Rr) that changes in future driving of at least one of the autonomous driving devices traveling in the platoon formation; as well as Each of the autonomous driving devices is navigated into the optimized queue configuration.

2. The navigation system according to claim 1, characterized in that: The optimization of the queue form includes: The queue shape is optimized based on air resistance (Rra) and wind resistance (Rrw), wherein the air resistance is the driving resistance depending on the driving speed generated by the autonomous driving device, and the wind resistance is the driving resistance depending on the wind speed acting on the autonomous driving device.

3. The navigation system according to claim 2, characterized in that: The optimization of the queue form includes: In the column form (Po) as the column form arranged vertically, when the autonomous driving device traveling after the autonomous driving device traveling at the head of the column is defined as a subsequent device (1s), In at least one of a case where the air resistance of the subsequent device acts in a headwind state and a case where the air resistance of the subsequent device acts in a windless state, the queue form is optimized to the vertical column form.

4. The navigation system according to claim 3, characterized in that: The optimization of the queue form includes: In at least one of the cases where the air resistance of the subsequent device is greater than the wind resistance in a crosswind state and the case where the air resistance of the subsequent device is greater than the wind resistance in a tailwind state, the queue form is optimized to the vertical column form.

5. The navigation system according to claim 3, characterized in that: The optimization of the queue form includes: In at least one of the cases where the air resistance of the subsequent device is smaller than the wind resistance in a crosswind state and the case where the air resistance of the subsequent device is smaller than the wind resistance in a tailwind state, the queue form is optimized into a horizontal row form (Pa) arranged laterally.

6. The navigation system according to claim 5, characterized in that: The optimization of the queue form includes: When the air resistance of the subsequent device is less than the wind resistance in the crosswind state including the longitudinal component, the queue form is optimized to a goose-shaped parallel form (Pao) among the parallel forms, which are arranged laterally in a longitudinally staggered manner.

7. The navigation system according to claim 5, characterized in that: The optimization of the queue form includes: When the lateral width of the travel path on which each of the autonomous driving devices travels is narrower than the lateral width required for the parallel configuration, optimization to the parallel configuration is restricted.

8. The navigation system according to any one of claims 1 to 7, characterized in that: The optimization of the queue form includes: When each of the autonomous driving devices is traveling on a downhill section, the platoon configuration is optimized to an interconnected configuration (Pc) in which the regenerative power generated by each of the interconnected autonomous driving devices is recovered by the battery of at least one of the autonomous driving devices.

9. The navigation system according to claim 8, characterized in that: The optimization of the queue form includes: When the autonomous driving device having a larger free capacity in the battery is defined as a recovery device (1c) for recovering the regenerative power, When the remaining capacity of the battery of the recovery device is insufficient relative to the total of the regenerative electric power generated by each of the autonomous driving devices, optimization to the interconnected state is restricted.

10. The navigation system according to claim 8, characterized in that: The optimization of the queue form includes: When the total of the available capacities in the batteries of the autonomous driving devices is insufficient for the total of the regenerative electric power generated by the autonomous driving devices, optimization to the interconnected state is restricted.

11. A navigation method, executed by a processor (131), for navigating a plurality of autonomous driving devices (1) that autonomously drive using power supplied from a battery (32), characterized in that: Include: optimizing the platoon formation based on a driving resistance (Rr) that changes in future driving of at least one of the autonomous driving devices traveling in the platoon formation; as well as Each of the autonomous driving devices is navigated into the optimized queue configuration.

12. A navigation program, comprising commands stored in a storage medium (130) and executed by a processor (131), for navigating a plurality of autonomous driving devices (1) that autonomously drive using power supplied from a battery (32), characterized in that: The command contains: optimizing the platoon formation based on a driving resistance (Rr) that changes in future driving of at least one of the autonomous driving devices traveling in the platoon formation; as well as Each of the autonomous driving devices is navigated into the optimized queue configuration.

Images