Vehicle driving control device and vehicle

Abstract

To estimate a size or a type of a vehicle not having a position detection function or its position on a road for traveling control of the vehicle.MEANS FOR SOLVING THE PROBLEM: A vehicle 1 includes: a communication unit 17 that can receive information on positions of portable terminals 40 of a plurality of occupants who are moving on other vehicles 2; and a control unit 94 that can execute traveling control of the vehicle. The control unit 94 acquires position information for the portable terminals 40 of the plurality of occupants moving on the other vehicles 2, and based on their respective movement speeds or a degree of correlation of change in the movement speed among them, extracts the portable terminals 40 of a plurality of occupants riding on the same other vehicle 2. The control unit 94 estimates a size or a type of the other vehicle 2 on the basis of a difference in the positions of the portable terminals 40 of the plurality of occupants extracted as occupants who are riding on the other vehicle 2 together. The control unit 94 estimates the position of the other vehicle 2 on a road on the basis of the estimated size or type of the other vehicle 2 and the extracted position information, and controls the traveling of the vehicle.SELECTED DRAWING: Figure 8

Description

[Technical Field]

[0001] The present invention relates to a vehicle driving control device and a vehicle. [Background technology]

[0002] 2. Description of the Related Art Developments are underway for vehicles such as automobiles that can run using driving assistance to assist the driver, or autonomous driving that does not require driver operation. In automated driving, including driving assistance for vehicles, the minimum information required to control the vehicle's driving is the current location of the vehicle, information about the vehicle's driving status, etc. Furthermore, information about the locations of other vehicles is essential to prevent one vehicle from interfering with another. It is believed that a server device for automatic driving of a vehicle or each vehicle can collect this information about multiple vehicles, thereby controlling the driving of the vehicles so as to reduce interference between the multiple vehicles. Patent Documents 1 to 3 disclose technologies for generating vehicle position information. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-021273 [Patent Document 2] Japanese Patent Application Publication No. 2018-106701 [Patent Document 3] Japanese Patent Application Laid-Open No. 2005-227086 Summary of the Invention [Problem to be solved by the invention]

[0004] However, some vehicles traveling on actual roads do not have a GNSS receiver or the like for detecting the vehicle's position. In particular, recent vehicles can be connected to mobile devices, so the vehicle itself may not have a GNSS receiver or the like. In this case, the server device for automatic driving of the vehicle or each vehicle cannot obtain position information about the vehicle itself traveling on an actual road. When position information about a vehicle traveling on an actual road cannot be obtained, the server device or the vehicle can execute control corresponding to the vehicle only when the vehicle is visible. Even if a vehicle is capable of automatic driving that can control its own driving with high precision, it can only execute control corresponding to other vehicles that do not have a position detection function after the other vehicles become visible. Even if a vehicle is capable of automatic driving that can control its own driving with high precision, it may be forced to perform relatively sudden driving control to avoid interference with other vehicles that do not have a position detection function. For example, if another vehicle without a position detection function is traveling at a merging point, the autonomously driving vehicle cannot determine the location of the other vehicle traveling in the lane where the vehicle is merging unless it can capture an image of the other vehicle using an external camera or the like. Even if the autonomously driving vehicle is traveling in an adjacent lane next to the lane where the vehicle is merging, there is a possibility that the other vehicle without a position detection function will stray from the lane where the vehicle is merging into the adjacent lane when merging. In this case, the autonomously driving vehicle must perform avoidance control in response to the straying vehicle after capturing an image of the straying vehicle.

[0005] In this way, in vehicle driving control, it is required to be able to estimate the size, type, or location on the road of a vehicle that does not have a location detection function. [Means for solving the problem]

[0006] A vehicle driving control device according to one embodiment of the present invention is a vehicle driving control device having a communication unit capable of communicating with mobile devices of multiple occupants traveling in the vehicle, and a control unit capable of executing control using information received from the mobile devices, wherein the control unit acquires multiple pieces of location information including location information received from the mobile devices of the multiple occupants traveling in the vehicle, generates each moving speed or change in moving speed from the acquired location information of the multiple mobile devices, extracts the mobile devices of multiple occupants traveling in the same vehicle based on the correlation between the moving speed or change in moving speed based on the location information of the multiple mobile devices, estimates the size or type of the vehicle based on the difference in positions of the mobile devices of the multiple occupants extracted as being traveling in the vehicle, and estimates the position of the vehicle on the road based on the estimated size or type of the vehicle and the extracted location information, thereby controlling the driving of the vehicle.

[0007] A vehicle according to one embodiment of the present invention has a communication unit capable of receiving, via communication, information on the location of mobile devices of multiple occupants traveling in another vehicle, and a control unit capable of controlling the vehicle's driving based on the received information on the location of the mobile devices, wherein the control unit of the vehicle executes at least the fifth process among a first process of acquiring multiple pieces of location information including the location information received from the mobile devices of the multiple occupants traveling in the other vehicle; a second process of generating each of the acquired location information of the multiple mobile devices to determine the movement speed or change in movement speed of each of the multiple mobile devices; a third process of extracting the mobile devices of multiple occupants traveling in the same other vehicle based on the correlation between the movement speed or change in movement speed based on the location information of the multiple mobile devices; a fourth process of estimating the size or type of the other vehicle based on the difference in the positions of the mobile devices of multiple occupants extracted as being passengers in the other vehicle; and a fifth process of estimating the position of the other vehicle on the road based on the estimated size or type of the other vehicle and the extracted location information, and controlling the driving of the vehicle. [Effects of the Invention]

[0008] In the present invention, the communication unit communicates with the mobile devices of multiple occupants traveling in a vehicle to acquire multiple pieces of location information.The control unit then generates each of the acquired mobile device location information and calculates the movement speed or change in movement speed, and extracts the mobile devices of multiple occupants traveling in the same vehicle based on the correlation between the movement speeds.The control unit also estimates the size or type of the vehicle based on the difference in the positions of the mobile devices of the multiple occupants extracted as traveling in the same vehicle. In this way, for the purpose of vehicle travel control, the present invention can estimate the size and type of a vehicle that does not have a position detection function based on the position information of a mobile device ridden in the vehicle. Furthermore, the present invention can estimate the vehicle's position on a road based on the estimated size or type of the vehicle and its position information. Furthermore, the present invention can control the travel of a vehicle that does not have a position detection function by using the estimated position on a road of the vehicle. The present invention makes it possible to reliably estimate the size, type, or location on a road of a vehicle that does not have a location detection function, so that the estimation can be used for, for example, vehicle travel control. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is an explanatory diagram of a driving state of an automobile to which the present invention can be applied. [Figure 2] FIG. 2 is an explanatory diagram of the control system of the automobile of FIG. [Figure 3] FIG. 3 is an explanatory diagram of a server device that controls the running of an automobile. [Figure 4] FIG. 4 is a timing chart of information collection and driving control by the server device of FIG. 3 that controls vehicle driving in the first embodiment of the present invention. [Figure 5] FIG. 5 is a flowchart of the driving control by the server device of FIG. [Figure 6] FIG. 6 is an explanatory diagram of a mobile terminal capable of communicating with a server device. [Figure 7]FIG. 7 is an explanatory diagram of the position of an automobile on the road surface, which is one of the vehicle information that can be estimated based on one mobile terminal. [Figure 8] FIG. 8 is a flowchart of the estimation control of the vehicle in the first embodiment of the present invention. [Figure 9] FIG. 9 is an explanatory diagram of determining the correlation degree and grouping based on the position information of a plurality of mobile terminals. [Figure 10] FIG. 10 is a flowchart of the vehicle information estimation control. [Figure 11] FIG. 11 is a table showing the correspondence between vehicle types and vehicle sizes for each type. [Figure 12] FIG. 12 is an explanatory diagram of a method for estimating the size of a vehicle based on the difference in positions of a plurality of mobile terminals. [Figure 13] FIG. 13 is a diagram illustrating a first example of the position of an automobile on the road surface estimated based on the difference in positions of a plurality of mobile terminals. [Figure 14] FIG. 14 is a diagram illustrating a second example of the position of an automobile on the road surface estimated based on the differences in the positions of a plurality of mobile terminals. [Figure 15] FIG. 15 is a diagram illustrating a third example of the position of an automobile on the road surface estimated based on the difference in positions of a plurality of mobile terminals. [Figure 16] FIG. 16 is a diagram illustrating a fourth example of the position of the vehicle on the road surface estimated based on the difference between the position of the vehicle itself and the position of the mobile terminal. [Figure 17] FIG. 17 is a diagram illustrating a fifth example of the position of the vehicle on the road surface estimated based on the difference between the position of the vehicle itself and the position of the mobile terminal. [Figure 18] FIG. 18 is a diagram illustrating a sixth example of the position of the vehicle on the road surface estimated based on the difference between the position of the vehicle itself and the position of the mobile terminal. [Figure 19] FIG. 19 is an explanatory diagram of a vehicle driving control device according to the second embodiment of the present invention. [Figure 20] FIG. 20 is a flowchart of the host vehicle driving control by the driving control device of FIG. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described with reference to the drawings.

[0011] [First embodiment] FIG. 1 is an explanatory diagram of a traveling state of an automobile 1 to which the present invention can be applied. FIG. 1 illustrates a merging section where a one-lane side road L3 merges with a two-lane road. An automobile 1 is traveling in an overtaking lane L1 adjacent to a merging side lane L2 connected to the side road L3 of the two-lane road, and is attempting to pass through the merging section. The automobile 1 is an example of a vehicle. Other examples of vehicles include motorcycles, personal mobility vehicles, buses, and trucks. A vehicle is equipped with a driving source such as an engine or a motor, and travels using the driving force generated by the driving source. A vehicle can basically be driven by a driver, but may also be driven with assistance from a driver, or may be driven by autonomous driving without a driver's operation. Hereinafter, driving control by autonomous driving may include driving control by driving assistance. Also, in Figure 1, another vehicle 2 is traveling on side road L3. After this, the other vehicle 2 travels from side road L3 toward merging lane L2 of the two-lane road and merges. Basically, the other vehicle 2 may be one that can be driven by the driver.

[0012] FIG. 2 is an explanatory diagram of the control system 10 of the automobile 1 of FIG. The control system 10 of the automobile 1 in FIG. 2 has multiple control devices, including a cruise control device 15 that performs autonomous driving. FIG. 2 shows multiple control devices, such as a drive control device 11, a steering control device 12, a braking control device 13, an operation detection device 14, a cruise control device 15, a detection control device 16, and an external communication control device 17. The control system 10 of the automobile 1 may also include other control devices, such as an air conditioning control device, an occupant monitoring device, a short-range communication device, and an alarm device. The multiple control devices are connected by cables to a central gateway device (CGW) 18 that constitutes a vehicle network. Multiple cables are connected to the central gateway device 18. The multiple control devices may be connected to the central gateway device 18 in a star or bus configuration. The vehicle network may conform to standards such as CAN (Controller Area Network) or LIN (Local Interconnect Network). The vehicle network may also conform to other standards, such as a general-purpose wired communication standard such as a LAN, a wireless communication standard, or a combination of these. Each control device is assigned an ID to distinguish it from other control devices. Each control device may input and output various information using packets with the destination ID and source ID attached. The central gateway device 18 monitors and routes packets on the vehicle network. The central gateway device 18 may check the list and control routing.

[0013] The drive control device 11 controls the drive source and drive force transmission mechanism of the automobile 1. The drive force transmission mechanism may be, for example, a reduction gear, a center differential, etc. The drive force transmission mechanism may be one that individually controls the magnitude of the drive force transmitted to each of the multiple wheels of the automobile 1. The steering control device 12 controls a steering device that changes the direction of a plurality of wheels on the front side of the automobile 1. The traveling direction of the automobile 1 changes according to the direction of the wheels. The brake control device 13 controls a braking device that individually brakes the plurality of wheels of the automobile 1. The braking device may be one that individually controls the magnitude of the braking force that acts on the plurality of wheels of the automobile 1.

[0014] The operation detection device 14 is connected to a plurality of operating members provided on the automobile 1 for the occupant to operate the traveling of the automobile 1. The plurality of operating members include, for example, a steering wheel 21, an accelerator pedal 22, a brake pedal 23, and a shift lever 24. The operation detection device 14 detects whether or not each of the operating members 21 to 24 is operated, the amount of operation, etc., and outputs the operation information to the vehicle network.

[0015] A plurality of vehicle sensors for detecting the driving state and driving environment of the automobile 1 are connected to the detection control device 16. The plurality of vehicle sensors include, for example, a GNSS receiver 25, an exterior camera 26, a lidar 27, and an acceleration sensor 28. The GNSS receiver 25 receives radio waves from multiple GNSS satellites (not shown) and generates information on the current position and current time of the automobile 1 equipped with the GNSS receiver 25. The GNSS receiver 25 may be one that can receive radio waves from terrestrial waves and zenith satellites and generate highly accurate information on the current position and current time. The exterior camera 26 captures images of the outside of the automobile 1, which is capable of traveling on roads, etc. The automobile 1 may be provided with multiple exterior cameras 26. The multiple exterior cameras 26 may capture images of the front, rear, left, and right sides of the automobile 1 separately to capture images of the surroundings of the automobile 1. Images captured by the exterior camera 26 include images of other automobiles 2 and the like that are around the automobile 1. For example, as shown in the figure, the automobile 1 should capture images of at least the area ahead in the direction in which the automobile 1 is traveling. The lidar 27 uses a laser to scan the exterior of the automobile 1, which can travel on roads, and generates spatial information about the exterior of the automobile based on reflected laser waves. The spatial information about the exterior of the automobile includes images of other automobiles 2 and the like around the automobile 1. The exterior camera 26 and the lidar 27 are sensors that detect other automobiles 2 around the automobile 1. The acceleration sensor 28 may be one that detects acceleration in the axial directions of the front-rear, left-right, and up-down directions of the automobile 1. In this case, the acceleration sensor 28 can detect acceleration in the yaw, roll, and pitch directions of the automobile 1. The detection control device 16 outputs the detection information from the various vehicle sensors 25 to 28 provided on the vehicle to the vehicle network. The detection control device 16 may generate information based on the detection information, for example, detection information of other vehicles 2 around the vehicle, and output the information to the vehicle network.

[0016] The external communication control device 17 establishes a wireless communication path with a base station 30 located outside the automobile 1, for example, near a road. The base station 30 may be a carrier-based one or one for advanced traffic information. The external communication control device 17 transmits and receives information via the base station 30 to and from a server device 31 connected to the base station 30. The server device 31 may be provided corresponding to the base station 30. By providing the base station 30 for 5G communication with the function of the server device 31, the external communication control device 17 of the automobile 1 can perform high-speed, large-capacity communication with the server device 31 of the base station 30. Furthermore, the external communication control device 17 may establish a wireless communication path with another moving body such as another automobile 2 by V2X communication.

[0017] The driving control device 15 controls the driving of the automobile 1 . The driving control device 15 may perform driving control of the automobile 1 based on the driver's operation, driving control of the automobile 1 that supports the driver's operation, and driving control in an automatic driving mode that does not depend on the driver's operation. For example, the driving control device 15 may generate a control value that assists the driver's operation based on information from the operation detection device 14 and output it to the drive control device 11, the steering control device 12, and the braking control device 13. The driving control device 15 may perform lane keeping control to maintain the driving lane and preceding vehicle following control based on information from the detection control device 16 and high-precision map data, and generate and output control values ​​for automatic driving. In this way, the driving control device 15 can function as a driving control unit that controls the driving of the automobile 1 using at least the detection results of the vehicle sensors 25 to .

[0018] FIG. 3 is an explanatory diagram of a server device 31 that controls the running of the automobile 1. As shown in FIG. The server device 31 in FIG. 3 includes a server communication device 51, a server timer 52, a server memory 53, a server CPU 54, and a server bus 55 to which these are connected.

[0019] The server communication device 51 is connected to a communication network such as the Internet. The server communication device 51 transmits and receives information to and from the automobile 1 traveling on a road, for example, via a base station 30 connected to the communication network. The server communication device 51 is a communication unit capable of communicating with the automobile 1 to remotely control or assist the traveling of the automobile 1. The server timer 52 measures the time or duration. The time of the server timer 52 may be calibrated, for example, based on the time based on radio waves from a GNSS satellite (not shown). In this case, the time of the server timer 52 is synchronized with the time of the automobile 1. The server memory 53 stores programs and data executed by the server CPU 54. The server memory 53 may be configured, for example, with a non-volatile semiconductor memory, a HDD, a RAM, or the like. The server CPU 54 reads and executes the program recorded in the server memory 53. This realizes a server control unit. The server CPU 54 as the server control unit manages the operation of the server device 31. For example, the server CPU 54 may use the received information to execute vehicle driving control for remotely controlling the driving of the automobile 1. In this case, the server CPU 54 may collect information about road driving regarding vehicles on the road, and control the driving of the communicating automobile 1 based on the collected information so that each automobile 1 can drive safely and securely. In controlling each automobile 1, the server CPU 54 may use information about the driving status of other automobiles 2. In addition, pedestrians and the like may also be present on the road. It is desirable that the server CPU 54 collect and estimate as much information as possible about automobiles 1 that are not communicating, and use the estimated information about those automobiles 1 to control the driving of the communicating automobile 1.

[0020] FIG. 4 is a timing chart of information collection and driving control by the server device 31 of FIG. 3 that controls vehicle driving in the first embodiment of the present invention. 4 shows a first automobile 71, a second automobile 72, a first mobile terminal 73, and a second mobile terminal 74, along with the server device 31. Time flows from top to bottom.

[0021] As shown in steps ST1 and ST6 in the figure, the first vehicle 71 periodically transmits vehicle information of its own vehicle to the server device 31. The vehicle information of the first vehicle 71 may include, for example, the current position, speed, time, etc. of the first vehicle 71, as well as images of the outside of the first vehicle 71 captured by the first vehicle 71, information on the space outside the vehicle, and information on other vehicles 2 detected around the first vehicle 71, which is its own vehicle. As shown in steps ST3 and ST8 in the figure, the second vehicle 72 periodically transmits vehicle information of its own vehicle to the server device 31. The vehicle information of the second vehicle 72 may include, for example, the current position, speed, time, etc. of the second vehicle 72, as well as images of the outside of the second vehicle 72 captured by the second vehicle 72, information on the space outside the vehicle, and information on other vehicles 2 detected around the second vehicle 72, which is its own vehicle. Then, the server device 31 stores the vehicle information received from each automobile 1 so as to accumulate it in the server memory 53 (steps ST2, ST2, ST4, ST7, and ST8). Furthermore, the server device 31 executes server-based driving control using information stored in the server memory 53 at each predetermined control period TP, generates driving control values ​​as driving control information for each vehicle 1, and transmits these to the first vehicle 71 and the second vehicle 72. The first vehicle 71 controls the driving of its own vehicle using the driving control values ​​for its own vehicle that it periodically receives from the server device 31. The second vehicle 72 controls the driving of its own vehicle using the driving control values ​​for its own vehicle that it periodically receives from the server device 31. As a result, the first vehicle 71 and the second vehicle 72, which are driving while communicating with the server device 31, can continue to drive safely and securely, for example, without interfering with other vehicles 2, thanks to the driving control by the server device 31.

[0022] FIG. 5 is a flowchart of the driving control by the server device 31 of FIG. The server CPU 54 of the server device 31 may repeatedly execute the travel control of FIG. 5 at predetermined control cycles TP.

[0023] In step ST21, the server CPU 54 determines whether it is control timing according to a predetermined control cycle TP. If it is not control timing, the server CPU 54 repeats this process. When it is control timing, the server CPU 54 advances the process to step ST22.

[0024] In step ST22, the server CPU 54 uses the vehicle information of the multiple automobiles 1 with which the server communication device 51 is communicating to map the traveling positions of the automobiles 1 that are determined from the collected information. At this time, the server CPU 54 may read high-precision map data together with the vehicle information and the like from the server memory 53. In this case, the server CPU 54 may generate a diagram for each road or lane included in the high-precision map data for the assigned area and map the current position of each automobile 1. The server CPU 54 may also map the future traveling positions of each automobile 1 according to its speed onto the diagram.

[0025] In step ST23, the server CPU 54 selects one vehicle 1 with which the server device 31 is communicating from the vehicles 1 mapped onto the diagram.

[0026] In step ST24, the server CPU 54 generates a driving control value for controlling the driving of the selected automobile 1. Here, the driving control value may, for example, instruct or request to continue the current driving, or may instruct or request to accelerate or decelerate, change lanes, etc. The driving control value may, for example, generate a driving control value for acceleration or deceleration so that a predetermined distance is maintained between the selected automobile 1 and another automobile 2 ahead on the same diagram.

[0027] In step ST25, the server CPU 54 transmits the driving control values ​​generated in step ST24 to the selected automobile 1. The driving control values ​​are transmitted from the server communication device 51 of the server apparatus 31 to the external communication control device 17 of the selected automobile 1 via the base station 30. For example, if the driving control value is to maintain a predetermined distance from another automobile 2 ahead, the automobile 1 that receives the driving control value controls the driving of its own automobile so that it follows the other automobile 2 ahead while maintaining a certain distance between them.

[0028] In step ST26, the server CPU 54 determines whether there are any remaining vehicles that have not yet been processed. If there are any remaining vehicles, the server CPU 54 returns the process to step ST23. The server CPU 54 repeats the processes from step ST23 to step ST26 for all of the multiple vehicles 1 with which the server communication device 51 is communicating. When there are no remaining vehicles that have not yet been processed, the server CPU 54 ends this control. The server CPU 54 pauses until the next control cycle TP.

[0029] In this way, the automobile 1 traveling in an autonomous driving mode including driving assistance can periodically transmit the current position, speed, images, etc. detected by the vehicle sensors 25 to 28 to the server device 31, and periodically receive driving control values ​​from the server device 31, thereby controlling the driving of the automobile 1.

[0030] However, if the other automobiles 2 traveling on the side road L3 in FIG. 1 do not communicate with the server device 31, or if they can only travel based on the driver's operation, it is difficult for the server device 31 to collect vehicle information from the other automobiles 2 traveling on the side road L3. Furthermore, some automobiles 1 actually traveling on roads do not have a GNSS receiver 25 or the like for detecting their own position. In particular, recent automobiles 1 can be connected to a mobile terminal 40, so the automobiles 1 themselves may not be equipped with a GNSS receiver 25 or the like. In these cases, the server device 31 for automatic driving of the automobiles 1 cannot obtain the position information of all automobiles 1 traveling on actual roads. On the other hand, the current positions of all automobiles 1 that are actually traveling on roads are required to improve the safety of the driving control of the automobile 1. If an automobile 1 that is not recognized by the server device 31 is actually traveling on a road, it is not necessarily possible to realize a sufficiently safe and secure driving of the automobile 1 that is traveling based on the driving control of the server device 31. For example, if another vehicle 2 without a position detection function is attempting to merge from side road L3 in Figure 1, the autonomously driving vehicle 1 must first be able to capture an image of the other vehicle 2 using the exterior camera 26 or the like. Even if the autonomously driving vehicle 1 is traveling in the passing lane L1 adjacent to the lane into which it is merging, there is a non-zero possibility that the other vehicle 2 without a position detection function will stray from the merging lane L2 into the passing lane L1 when merging. In this case, the autonomously driving vehicle 1 must perform emergency avoidance control to respond to the straying vehicle 2 after capturing an image of the straying vehicle 2. In this way, even if the vehicle 1 is capable of highly accurate automatic driving, it can only execute control corresponding to the other vehicle 2 that does not have a position detection function once the other vehicle 2 becomes recognizable from the vehicle 1. Even if the vehicle 1 is capable of automatic driving that can control the driving of the vehicle with high accuracy, there is a possibility that the vehicle 1 may be forced to perform relatively sudden driving control to avoid interference with the other vehicle 2 that does not have a position detection function. In this way, when controlling the driving of automobile 1, it is necessary to estimate the size, type, or position on the road of automobile 1 that does not have a position detection function so that it can be used to control the driving of automobile 1.

[0031] For this reason, it is conceivable that the position information of the portable terminal 40 carried by the occupant may be utilized for vehicle driving control.

[0032] FIG. 6 is an explanatory diagram of a mobile terminal 40 that can communicate with the server device 31. The mobile terminal 40 in FIG. 6 includes a terminal communication device 41, a terminal GNSS receiver 42, a terminal memory 43, a terminal CPU 44, and a terminal bus 45 to which these are connected.

[0033] The terminal communication device 41 establishes a wireless communication path with the base station 30. The terminal communication device 41 transmits and receives information to and from the server device 31 and the like through a communication network connected to the base station 30. The terminal GNSS receiver 42 receives radio waves from multiple GNSS satellites (not shown) and generates information about the current position and current time of the mobile terminal 40 equipped with the receiver. The mobile terminal 40 may have a detection function with the same position accuracy as the GNSS receiver installed in the automobile 1. In this case, the position accuracy of the mobile terminal 40 is improved. The terminal memory 43 stores programs and data executed by the terminal CPU 44. The terminal memory 43 may be configured, for example, by a non-volatile semiconductor memory, a HDD, a RAM, or the like. The terminal CPU 44 reads and executes the program recorded in the terminal memory 43. This realizes a terminal control unit. The terminal CPU 44 as the terminal control unit manages the operation of the mobile terminal 40.

[0034] Such a mobile terminal 40 is brought into the passenger compartment of the automobile 1 by a passenger, including the driver, of the automobile 1. The mobile terminal 40 can transmit its position information to the server device 31 by executing a predetermined program with the terminal CPU 44. In steps ST11 to ST14 of FIG. 4, the first mobile terminal 73 and the second mobile terminal 74 transmit information such as the position of the mobile terminal 40 to the server device 31, and the server device 31 saves and stores the information. In this case, the server device 31 for the vehicle driving control device receives and stores vehicle information from each automobile 1 and also receives and stores position information from each mobile terminal 40. The server device 31 communicates with the mobile terminal 40 of the passenger traveling in the automobile 1 via the server communication device 51 as a communication unit, and can perform control using information such as the position of the mobile terminal 40 received from the mobile terminal 40.

[0035] FIG. 7 is an explanatory diagram of the position of an automobile 60 on the road surface, which is one of the vehicle information that can be estimated based on one mobile terminal 40.

[0036] As shown by the dashed line in FIG. 7 , automobile 60 is traveling in the right lane of a two-lane road while crossing into the left lane. A passenger compartment 61 of automobile 60 has multiple seats, including a driver's seat 62 and a passenger seat 63 in the front, and a rear seat 64 in the rear. The driver sits in driver's seat 62 holding his / her mobile terminal 40. With automobile 60 traveling in this state, mobile terminal 40 detects its own position and transmits it to server device 31. Server CPU 54 of server device 31 estimates the size and location of automobile 60 on the road based on the location information of mobile terminal 40. As a result, server device 31 may estimate automobile 60 as traveling in the right lane, as indicated by a dashed-dotted frame 65 in the figure. In this case, server CPU 54 estimates the location of automobile 60 on the road, assuming that mobile terminal 40 is located at the center of automobile 60. The size and location on the road of the automobile 60 that the server CPU 54 can estimate based on the location information of one mobile terminal 40 are likely to have large errors in the width and length of the road compared to the actual location of the automobile 60. Moreover, many mobile terminals 40 cannot achieve the same positional accuracy as the highly accurate GNSS receiver 25 used in the autonomously driven automobile 1. If the server device 31 performs driving control for, for example, an unillustrated automobile 1 traveling in the left lane based on such an estimation, there is a possibility that even if the automobile 1 stays in the lane, it may interfere with an automobile 60 traveling outside the right lane. In this way, the estimated vehicle information is likely to contain errors when the vehicle information is estimated based on one mobile terminal 40. The vehicle information based on the position information of the mobile terminal 40 needs to be estimated more reliably.

[0037] FIG. 8 is a flowchart of the estimation control of the vehicle in the first embodiment of the present invention. The server CPU 54 may repeatedly execute the estimation control of the vehicle shown in FIG. 8, for example, as part of step ST22 in FIG.

[0038] In step ST31, the server CPU 54 determines whether or not information such as location information has been received from a mobile terminal 40, for example, based on information accumulated and saved in the server memory 53. If information has been received from at least one mobile terminal 40, the server CPU 54 proceeds to step ST32. If information has not been received from a mobile terminal 40, the server CPU 54 ends this control.

[0039] In step ST32, the server CPU 54 generates the moving speeds and changes of the mobile terminal 40 and the vehicle based on the information received and stored by the server device 31. The information received by the server device 31 includes vehicle information from the automobile 1, as well as information such as the location of the mobile terminal 40. The vehicle information includes location information of the vehicle itself detected by the automobile 1. The server CPU 54 generates information indicating the moving speed of the mobile terminal 40 and changes of the moving speed based on the location information of the mobile terminal 40 stored for each mobile terminal 40. The server CPU 54 also generates information indicating the moving speed of the automobile 1 and changes of the moving speed based on the location information of the automobile 1 stored for each automobile 1. In this way, the server CPU 54 can generate the moving speed or changes of the moving speed of each mobile terminal 40 from the location information of the multiple mobile terminals 40 it has acquired. The server CPU 54 may receive the velocity measured by the terminal GNSS receiver 42 of the mobile terminal 40 and perform similar processing. Furthermore, some terminal GNSS receivers 42 are capable of not only calculating the position based on the received GNSS radio waves but also obtaining the velocity of the mobile terminal 40 according to the degree of the Doppler effect occurring in the received GNSS radio waves. In this case, the mobile terminal 40 may transmit information on the velocity based on the Doppler effect together with the position information to the server device 31. In this case, the server device 31 can obtain the velocity of the terminal GNSS receiver 42 without differentiating the position and use it for processing.

[0040] In step ST33, the server CPU 54 selects one mobile terminal 40.

[0041] In step ST34, the server CPU 54 determines the degree of movement correlation between the selected mobile terminal 40 and the other mobile terminals 40 and the automobile 1. In step ST32, the server CPU 54 generates information indicating the movement speed and its changes for each mobile terminal 40 and each automobile 1. When the movement speeds and their changes overlap, the degree of movement correlation is highest. When the envelope shapes resulting from speed changes are similar, the degree of movement correlation is medium. Furthermore, when the timing of the peaks included in the envelope shapes coincide, the degree of movement correlation is high. Conversely, when the timing of the peaks included in the envelope shapes differ significantly, the degree of movement correlation is low. When the envelope shapes differ, the degree of movement correlation is lowest. The server CPU 54 may determine the degree of movement correlation between the selected mobile terminal 40 and the other mobile terminals 40 and the automobile 1 based on the movement speed and its changes. Multiple mobile terminals 40 with a high degree of movement correlation can be considered to be riding in the same automobile 1. The server CPU 54 may select only other mobile terminals 40 whose difference in position, i.e., distance, is equal to or less than a predetermined threshold, as targets for determining the degree of correlation of movement with the selected mobile terminal 40. This eliminates the need for the server CPU 54 to determine the degree of correlation between the selected mobile terminal 40 and all other mobile terminals 40. Furthermore, the server CPU 54 may compare envelopes according to changes in position, rather than comparing envelopes according to changes in speed, or may compare a combination of these. However, there are many mobile terminals 40 whose absolute position accuracy is lower than that of the GNSS receiver installed in the automobile 1. For this reason, when determining the similarity of movement between mobile terminals 40 or between the automobile 1, it is desirable to determine not only the similarity of the positions of the mobile terminals 40 but also the similarity of the speed of movement. Even if the positions of multiple mobile terminals during movement continue to contain errors, it is expected that the errors can be suppressed by determining the speed of movement between them.

[0042] In step ST35, the server CPU 54 determines whether there is a correlation. Multiple mobile terminals 40 that are thought to be in the same automobile 1 may be determined to be correlated. Multiple mobile terminals 40 that are separately in multiple automobiles 1 traveling side by side may be determined to have no correlation because the timing of the envelope poles will be different. If the server CPU 54 finds another mobile terminal 40 or automobile 1 that can be determined to be correlated with the selected mobile terminal 40, it proceeds to step ST36. Otherwise, the server CPU 54 skips step ST36 and proceeds to step ST37.

[0043] In step ST36, the server CPU 54 groups multiple mobile terminals 40 or automobiles 1 that are considered to be correlated. This extracts multiple mobile terminals 40 that are considered to be in the same automobile 1. The automobiles 1 in which these mobile terminals 40 are in are also extracted. The server CPU 54 records group information of the extracted multiple mobile terminals 40 and automobiles 1 in the server memory 53 so that the group information can be distinguished from other groups.

[0044] In step ST37, the server CPU 54 determines whether or not there is an unprocessed mobile terminal 40. If there is an unprocessed mobile terminal 40, the server CPU 54 returns the process to step ST33. The server CPU 54 repeats the processes from step ST33 to step ST37 until there are no more unprocessed mobile terminals 40. When there are no more unprocessed mobile terminals 40, the server CPU 54 proceeds to step ST38. At this point, information of multiple groups can usually be recorded in the server memory 53 in a manner that allows them to be distinguished from one another.

[0045] In step ST38, the server CPU 54 estimates and generates vehicle information for each group. The generated vehicle information includes, for example, information about the type, size, and location on the road of the automobile 1 in which the mobile terminals 40 of the group are riding. The server CPU 54 selects information about each group from the server memory 53, and estimates and generates vehicle information for each group. The server CPU 54 may record the generated vehicle information in the server memory 53 in association with the group. Thereafter, the server CPU 54 ends this control. As a result, information about the vehicle type, size, and location on the road of the automobile 1 estimated based on the information received from the multiple mobile terminals 40 is recorded in the server memory 53. The server CPU 54 performs mapping using this information as the vehicle information of the automobile 1 estimated based on the mobile terminal 40, as well as the vehicle information received from the automobile 1 and stored in the server memory 53. As a result, automobiles 1 for which the server device 31 has not received vehicle information are mapped in the diagram based on the likelihood estimated based on the multiple mobile terminals 40. Based on the mapping, the server CPU 54 becomes able to generate driving control values ​​that can ensure safety and security, including for automobiles 1 for which the server device 31 has not received vehicle information.

[0046] FIG. 9 is an explanatory diagram of determining the correlation degree and grouping based on the position information of a plurality of mobile terminals 40. In FIG. The server CPU 54 determines the degree of correlation based on the position information of the plurality of mobile terminals 40, for example, in step ST34 of FIG. 9 shows the envelope of speeds based on the location information of four mobile terminals 40, A to D. The horizontal axis represents time.

[0047] Envelopes A to C in Figure 9 accelerate, then move at a constant speed, and then decelerate slightly. In contrast, envelope D simply accelerates and then moves at a constant speed. For this reason, it can be determined that envelope D is in a different car 1 from envelopes A to C, and that the degree of correlation is low. Furthermore, the deceleration timing T2 of envelope C is different from the deceleration timing T1 of envelope A and envelope B. For this reason, it can be determined that envelope C is traveling in a different car 1 from envelope A and envelope B, and the degree of correlation is relatively low. In contrast, the deceleration timing T1 of envelope B coincides with the deceleration timing T1 of envelope A. Therefore, it can be determined that envelope B is traveling in the same car 1 as envelope A, and that there is a high degree of correlation. The server CPU 54 can determine whether or not a plurality of mobile terminals 40 are riding in the same car 1 by comparing such moving speeds and their changes and determining the degree of correlation. Then, the server CPU 54 can determine that the mobile terminal 40 of the envelope A, which is determined to have a high degree of correlation, and the mobile terminal 40 of the envelope B are correlated, and group them together.

[0048] Note that, although the description here assumes that all of envelopes A to D are generated by mobile terminal 40, the same applies if some of envelopes A to D are generated by automobile 1. It can be determined that automobile 1 and mobile terminal 40 riding therein are correlated, and they can be grouped. In this case, server CPU 54 can extract automobile 1 in which an occupant of mobile terminal 40 rides, based on the degree of correlation between the moving speed or change in moving speed in the position information of automobile 1.

[0049] FIG. 10 is a flowchart of the vehicle information estimation control. The server CPU 54 may repeatedly execute the vehicle information estimation control of FIG. 10 for each group in order to estimate the vehicle information for each group in step ST38 of FIG. 8, for example.

[0050] In step ST41, the server CPU 54 acquires group information from the server memory 53. In the server memory 53, for example, information on a group of a plurality of mobile terminals 40 that have a degree of correlation is recorded.

[0051] In step ST42, the server CPU 54 calculates and estimates the reference position of the vehicle for each group. The server CPU 54 may calculate the reference position of the vehicle for each group based on, for example, the difference in positions of the multiple mobile terminals 40 included in the group. The multiple mobile terminals 40 are, for example, in the passenger compartment 61 of the automobile 1. The multiple mobile terminals 40 can be considered to be distributed by seat in the passenger compartment 61 of the automobile 1. In this case, the difference in positions of the multiple mobile terminals 40 corresponds to the distribution of seats provided in the passenger compartment 61 of the automobile 1. The server CPU 54 may, for example, calculate the average value of the positions of all the multiple mobile terminals 40 included in the group to estimate the reference position of the vehicle. The reference position of such a vehicle is likely to be a position within the passenger compartment 61 of the automobile 1. The reference position can be used as the center position of the automobile 1.

[0052] In step ST43, the server CPU 54 determines whether or not a vehicle such as the automobile 1 is included in the group. An automobile 1 having a high degree of correlation between the group and the mobile terminal 40 in terms of speed and its change is included in the group. If information on such an automobile 1 is included, the server CPU 54 determines that a vehicle is included and proceeds to step ST44. If a vehicle is not included, the server CPU 54 proceeds to step ST45.

[0053] In step ST44, the server CPU 54 estimates the type and size of the vehicle in which the mobile terminal 40 is riding, based on the vehicle information included in the group. For driving control, the server device 31 needs to distinguish each vehicle 1 that can communicate with it from other vehicles 2. For this reason, the server device 31 stores information about the type, shape, and size of each vehicle 1 as information about each vehicle 1 that can communicate with it in the server memory 53. In this case, the server device 31 can obtain the type and size of the vehicle from the server memory 53 using the vehicle information included in the group. Thereafter, the server CPU 54 proceeds to step ST46.

[0054] In step ST45, the server CPU 54 estimates the type and size of the vehicle in which the multiple mobile terminals 40 are riding, based on the difference in positions of the multiple mobile terminals 40 included in the group. In this case, the group does not include vehicles such as the automobile 1. The server CPU 54 can estimate the range of the cabin 61 of the automobile 1 based on the difference in positions of the multiple mobile terminals 40 included in the group, and can further estimate the size of the automobile 1 based on the cabin 61. The estimated cabin 61 and size of the automobile 1 in this case can be closer to reality than those that can be estimated when only one mobile terminal 40 is riding in the automobile 1. The estimated size of the automobile 1 here corresponds to the type of automobile 1 extracted. The server CPU 54 then proceeds to step ST46.

[0055] In step ST46, the server CPU 54 estimates the road position of the vehicle associated with the group. Through the processes described above, the server CPU 54 has estimated the reference position of the vehicle and the type and size of the vehicle. For example, the server CPU 54 may estimate the road position of the estimated vehicle by assuming that the center of a vehicle of the estimated size is at the reference position. This allows the server CPU 54 to estimate the size and type of the vehicle 1 and the road position of the vehicle 1 based on the difference in the positions of the mobile terminals 40 of multiple occupants extracted as being passengers in the vehicle 1. The estimated road position of the vehicle 1 is a position where the extracted mobile terminal 40 can be accommodated, and is more likely to be closer to reality than an estimate based on the position of a single mobile terminal 40.

[0056] FIG. 11 is a table 80 showing the correspondence between vehicle types and vehicle sizes for each type.

[0057] FIG. 11 shows vehicle types as "passenger car," "truck," and "motorcycle." For reference, FIG. 11 also shows "pedestrian." Each vehicle type is associated with information on vehicle width and longitudinal length. For example, a "passenger car" is associated with a vehicle width of "1.8 meters" and a longitudinal length of "4 meters." Such a correspondence table 80 may be stored in the server memory 53. The server CPU 54 may read the correspondence table 80 from the server memory 53 and estimate the size based on the vehicle type, for example, in the process of step ST44 of FIG. 10. Note that the vehicle types may be classified by vehicle model, rather than by vehicle classification as in FIG. 11. The vehicle sizes included in the correspondence table 80 may be larger than the width and longitudinal length of the corresponding actual vehicle.

[0058] FIG. 12 is an explanatory diagram of a method for estimating the size of the automobile 1 based on the difference in the positions of a plurality of mobile terminals 40. In FIG. The server CPU 54 may estimate the size of the automobile 1 by the method of FIG. 12, for example, in the process of step ST45 of FIG.

[0059] The horizontal axis of Fig. 12 is the width direction of the road, which corresponds to the width of the automobile 1. The vertical axis is the extension direction of the road, which corresponds to the front-to-rear length of the automobile 1. Fig. 12 also shows the positions of two mobile terminals 40 that belong to the same group. Here, the server CPU 54 calculates the average value of the positions (x1 and x2) of the two mobile terminals 40 in the vehicle width direction as the reference position 66 of the automobile 1 in the road width direction. The server CPU 54 also calculates the average value of the positions (y1 and y2) of the two mobile terminals 40 in the extension direction as the reference position 66 of the automobile 1 in the road extension direction.

[0060] Furthermore, the server CPU 54 sets the margin value of the vehicle width of the automobile 1 to, for example, 0.5 meters, and the margin value of the front-rear length to, for example, 3 meters. The server CPU 54 then determines the position of the left side of the automobile 1 as the position of the value obtained by subtracting the vehicle width margin value from the value (x1) that is the smallest (left side) of the positions of the two mobile terminals 40 in the vehicle direction of the road. The server CPU 54 determines the position of the right side of the automobile 1 as the position of the value obtained by adding the vehicle width margin value to the value (x2) that is the largest (right side) of the positions of the two mobile terminals 40 in the vehicle direction of the road. The server CPU 54 determines the position of the front of the automobile 1 as the value obtained by adding a vehicle width margin value to the value (y1) that is the largest (front side) among the positions of the two mobile terminals 40 in the direction of extension of the road. The server CPU 54 determines the position of the rear of the automobile 1 as the value obtained by subtracting a vehicle width margin value from the value (y2) that is the smallest (rear side) among the positions of the two mobile terminals 40 in the direction of extension of the road. As a result, the server CPU 54 can calculate and estimate the size and position of the automobile 1 from front to back, left to right, and its position on the road, as shown by the dashed frame in the figure. The estimated size of the automobile 1 is an area that surrounds the two mobile terminals 40 in Figure 12 and is expanded from that area by a predetermined margin.

[0061] Next, specific examples of estimation of vehicle information will be described with reference to Figures 13 to 18. These figures correspond to Figure 7. 13 to 15 show examples in which a group is made up of only a plurality of mobile terminals 40. In this case, the server CPU 54 determines in step ST43 of Fig. 10 that vehicle position information is not included, and advances the process to step ST45. 16 to 18 show an example in which a group is made up of a mobile terminal 40 and an automobile 1. In this case, the server CPU 54 determines in step ST43 of Fig. 10 that the information includes vehicle position information, and advances the process to step ST44.

[0062] FIG. 13 is a diagram illustrating a first example of the position of the automobile 1 on the road surface estimated based on the differences in the positions of a plurality of mobile terminals 40. In FIG. In the automobile 1 of FIG. 13 , the server device 31 acquires information on the location of the mobile terminal 40 of the passenger in the driver's seat 62 and information on the location of the mobile terminal 40 of the passenger in the passenger's seat 63. In this case, the server CPU 54 estimates the type and size of the vehicle in which the two mobile terminals 40 are riding based on the difference in location between the two mobile terminals 40 included in the group by processing step ST45 of FIG. 10 . The server CPU 54 estimates, for example, the position between the driver's seat 62 and the passenger's seat 63 as the reference position of the vehicle. Furthermore, the server CPU 54 estimates, using the method of FIG. 12 , the size and location of the vehicle on the road as an area that surrounds the two mobile terminals 40 and is expanded by a predetermined margin. The estimated location of the automobile 1 on the road is a location where the automobile 1 is traveling in the right lane on a two-lane road without crossing into the left lane. The estimated location of the automobile 1 on the road can closely correspond to the actual location of the automobile 1, at least in the width direction of the road.

[0063] FIG. 14 is an explanatory diagram of a second example of the position of the automobile 1 on the road surface estimated based on the differences in the positions of a plurality of mobile terminals 40. In FIG. In the automobile 1 of FIG. 14 , the server device 31 acquires information on the location of the mobile terminal 40 of the passenger in the driver's seat 62 and information on the location of the mobile terminal 40 of the passenger in the rear seat 64. In this case, the server CPU 54 estimates the type and size of the vehicle in which the two mobile terminals 40 are riding based on the difference in location between the two mobile terminals 40 included in the group by processing step ST45 of FIG. 10 . The server CPU 54 estimates, for example, the position between the driver's seat 62 and the rear portion of the rear seat 64 behind the driver's seat 62 as the reference position of the vehicle. Furthermore, the server CPU 54 estimates, using the method of FIG. 12 , the size and location of the vehicle on the road as an area that surrounds the two mobile terminals 40 and is expanded by a predetermined margin. The estimated location of the automobile 1 on the road is a location where the automobile 1 is traveling in the right lane on a two-lane road without crossing into the left lane. The estimated position of the automobile 1 on the road can then correspond well to the actual position of the automobile 1 at least in the direction in which the road extends.

[0064] FIG. 15 is an explanatory diagram of a third example of the position of the automobile 1 on the road surface estimated based on the differences in the positions of a plurality of mobile terminals 40. In FIG. In the automobile 1 of FIG. 15 , the server device 31 acquires information on the location of the mobile terminal 40 of the passenger in the driver's seat 62 and information on the location of the mobile terminal 40 of the passenger in the opposite rear seat 64. In this case, the server CPU 54 estimates the type and size of the vehicle in which the two mobile terminals 40 are riding based on the difference in location between the two mobile terminals 40 included in the group through the processing of step ST45 of FIG. 10 . The server CPU 54 estimates, for example, the position between the driver's seat 62 and the passenger seat 63 side of the rear seat 64 as the reference position of the vehicle. Furthermore, the server CPU 54 estimates, using the method of FIG. 12 , an area that surrounds the two mobile terminals 40 and is expanded by a predetermined margin width as the size and location of the vehicle on the road. The estimated location of the automobile 1 on the road is a position where the automobile 1 is traveling in the right lane on a two-lane road without crossing into the left lane. The estimated position of the automobile 1 on the road can then correspond well to the actual position of the automobile 1 in the width direction and extension direction of the road.

[0065] FIG. 16 is an explanatory diagram of a fourth example of the position of the automobile 1 on the road surface estimated based on the difference between the position of the GNSS receiver 25 of the automobile 1 itself and the position of the mobile terminal 40. In FIG. In the automobile 1 of FIG. 16 , the server device 31 acquires information on the location of the mobile terminal 40 of the occupant in the driver's seat 62 and information on the location of the GNSS receiver 25 of the automobile 1. In this case, the server CPU 54 estimates the type and size of the vehicle in which the mobile terminal 40 is a passenger, based on the information of the automobiles 1 included in the group, by processing step ST44 of FIG. 10 . The installation position of the GNSS receiver 25 in the automobile 1 is often determined when the automobile 1 is manufactured. In this case, the server CPU 54 may estimate the location of the mobile terminal 40 as the location of the driver's seat 62. In this case, the location of the driver's seat 62 may be set as the reference position of the vehicle. Alternatively, the server CPU 54 may estimate the reference position of the vehicle based on the installation position of the GNSS receiver 25 in the automobile 1. Alternatively, the server CPU 54 may estimate the location of the automobile 1 on the road so that the driver's seat 62 of the automobile 1, estimated based on the type of automobile 1, overlaps with the location of the mobile terminal 40. When the position information of automobile 1 is obtained in this way, even if the group contains only one mobile terminal 40, it is possible to estimate the position of automobile 1 on the road that is more likely than that shown in Figure 7. Then, on a two-lane road, the estimated position of automobile 1 is a position where automobile 1 is traveling in the right lane without crossing into the left lane. Furthermore, the estimated position of automobile 1 on the road can well correspond to the actual position of automobile 1 in the width direction and extension direction of the road.

[0066] FIG. 17 is an explanatory diagram of a fifth example of the position of the automobile 1 on the road surface estimated based on the difference between the position of the GNSS receiver 25 of the automobile 1 itself and the position of the mobile terminal 40. In FIG. In the automobile 1 of FIG. 17 , the server device 31 acquires information on the locations of the two mobile terminals 40 of the two passengers in the rear seat 64 and information on the location of the GNSS receiver 25 of the automobile 1. For an automobile 1 traveling with level 5 autonomous driving, a driver in the driver's seat 62 is not required. In this case, the server CPU 54 estimates the type and size of the vehicle in which the mobile terminal 40 is a passenger, based on the information about the automobiles 1 included in the group, by processing step ST44 of FIG. 10 . Furthermore, the server CPU 54 may estimate that the two mobile terminals 40 are in the rear seat 64 based on the fact that the difference between the location of the GNSS receiver 25 of the automobile 1 and the locations of the two mobile terminals 40 is greater than the distance from the location of the GNSS receiver 25 of the automobile 1 to the driver's seat 62 and the passenger seat 63 in the vehicle information. The server CPU 54 may then estimate the location of the automobile 1 on the road so that the rear seat 64 of the automobile 1 estimated based on the type of automobile 1 overlaps with the locations of the two mobile terminals 40. When the position information of the automobile 1 is obtained in this way, the position in the passenger compartment 61 of each mobile terminal 40 included in the group can be estimated with high accuracy. As a result, the position of the automobile 1 on the road can be more likely than that shown in FIGS. 13 and 14. On a two-lane road, the estimated position of the automobile 1 is a position where the automobile 1 is traveling in the right lane without crossing into the left lane. Furthermore, the estimated position of the automobile 1 on the road can correspond well to the actual position of the automobile 1 in the width direction and extension direction of the road.

[0067] FIG. 18 is an explanatory diagram of a sixth example of the position of the automobile 1 on the road surface estimated based on the difference between the position of the GNSS receiver 25 of the automobile 1 itself and the position of the mobile terminal 40. In FIG. In the automobile 1 of FIG. 18 , the server device 31 acquires information on the locations of the four mobile terminals 40 of the four occupants seated in the driver's seat 62, passenger seat 63, and rear seat 64, as well as information on the location of the GNSS receiver 25 of the automobile 1. In this case, the server CPU 54 estimates the type and size of the vehicle in which the mobile terminals 40 are riding based on the information of the automobiles 1 included in the group, by processing step ST44 of FIG. 10 . The server CPU 54 may also estimate the location of the automobile 1 on the road so that the driver's seat 62, passenger seat 63, and rear seat 64 of the automobile 1 estimated based on the type of automobile 1 overlap with the locations of the four mobile terminals 40. When the location information of the automobile 1 and the locations of the mobile terminals 40 for all seats are acquired in this way, it is possible to estimate a more likely location of the automobile 1 on the road than those shown in FIGS. 13 to 17 . The estimated location of the automobile 1 on the road is a location in the right lane of a two-lane road without crossing into the left lane. Furthermore, the estimated position of the automobile 1 on the road can correspond well to the actual position of the automobile 1 in the width direction and extension direction of the road.

[0068] In this way, when there is a difference in the road width direction between the position information of the mobile terminals 40 of multiple occupants extracted as riding in the automobile 1, the server CPU 54 can estimate that the type of automobile 1 is an automobile 1 having a cabin 61 in which multiple occupants can ride side by side in the vehicle width direction. In addition, the server CPU 54 can estimate the size or type of automobile 1 or the position of automobile 1 on the road, assuming that automobile 1 is an automobile 1 of a certain type having a cabin 61 and a certain width.

[0069] For example, if the position information of the mobile devices 40 of multiple occupants included in a group has a difference in the road extension direction but not in the road width direction, as shown in FIG. 14, the server CPU 54 may determine that the vehicle is a motorcycle based on FIG. 11. In this case, the server CPU 54 may determine whether the difference in the road extension direction between the positions of two mobile devices 40 on which multiple occupants are lined up in the front-to-back direction is equal to or less than a proximity threshold, such as 0.4 meters. If the difference in the positions of the two mobile devices 40 is equal to or less than the proximity threshold, the server CPU 54 may determine that the vehicle is a motorcycle rather than a passenger car based on FIG. 11. A motorcycle is a type of vehicle that is small in the road width direction and has a certain width, allowing multiple occupants to ride closely side by side in the front-to-back direction. In this case, the CPU estimates the motorcycle's position on the road based on the vehicle width and width shown in FIG. 11.

[0070] Furthermore, the mobile terminals 40 carried by the passengers of the automobile 1 may move within the passenger compartment 61. When the mobile terminal 40 moves within the automobile 1 while it is moving, the position of the mobile terminal 40 includes an error due to the movement within the automobile. Even in such a case, the server CPU 54 can determine a change in the position of the mobile terminal 40 itself within the automobile, using the positions of the other mobile terminals 40 in the group as a reference. The server CPU 54 can distinguish a change in the position of the mobile terminal 40 itself within the automobile from a change in the position of the mobile terminal 40 due to other causes. In this case, the server CPU 54 only needs to determine whether the relative positions of the position information of the mobile terminals 40 of multiple passengers in the group riding in the automobile 1 have changed relative to one mobile terminal 40. If such a position change is detected, the server CPU 54 can estimate that the automobile 1 has a passenger compartment 61 wide enough to accommodate multiple passengers in the direction of the change in relative position. As a result, the server CPU 54 can improve the accuracy of the position of the automobile 1 on the road based on the movement of the mobile terminal 40 in the passenger compartment 61.

[0071] As described above, in this embodiment, the server communication device 51 communicates with the mobile terminals 40 of multiple occupants traveling in the automobile 1 to acquire location information for the multiple mobile terminals 40. In the server device 31 as a vehicle travel control device, the server CPU 54, as a control unit, generates the travel speed or travel speed change of each of the multiple mobile terminals 40 from the acquired location information. The server CPU 54 also extracts the mobile terminals 40 of multiple occupants traveling in the same automobile 1 based on the correlation between the speed changes. The server CPU 54 also estimates the size or type of automobile 1 based on the difference in the locations of the mobile terminals 40 of the multiple occupants extracted as traveling in the same automobile 1. In this way, in this embodiment, for example, the size and type of automobile 1 that does not have a position detection function can be estimated based on the position information of the mobile terminal 40 in the automobile 1, in order to control the traveling of the automobile 1. Also, in this embodiment, the position of the automobile 1 on the road can be estimated based on the estimated size or type of automobile 1 and the position information of the automobile 1. Furthermore, in this embodiment, it becomes possible to control the traveling of the automobile 1 so as not to interfere with the automobile 1, for example, by using the estimated position on the road of the automobile 1 that does not have a position detection function. In particular, in this embodiment, the above-mentioned information about the automobile 1 is not estimated based on the location information of one mobile terminal 40, but is estimated based on the location information of multiple mobile terminals 40. In this embodiment, the difference in the locations of the multiple mobile terminals 40 is used to estimate the range in which an occupant can ride in the automobile 1, and the type and size of the automobile 1 are estimated accordingly. The estimated type and size of the automobile 1 do not need to be fixed. In contrast, if the information about the automobile 1 is estimated based on the location information of one mobile terminal 40, for example, the type and size of the automobile 1 basically need to be fixed. The same is true for the position of the automobile 1 on the road. If these fixed values ​​are used, the accuracy of the type and size of the automobile 1 or its position on the road may decrease. As a result, in this embodiment, the size, type, or location on the road of an automobile 1 that does not have a location detection function can be estimated with sufficient accuracy to be usable for controlling vehicle travel, for example.

[0072] 1, another vehicle 1 merging from a side road L3 basically merges into the merging lane L2. In this case, if the server device 31 simply knows that another vehicle 1 is on the side road L3, the server CPU 54 basically just sets a merging range 3 for the other vehicle 1 merging in the merging lane L2. In contrast, the server device 31 of this embodiment continuously acquires the position and movement of another vehicle 1 merging from the side road L3 as changes in the position of the mobile terminal carried by the vehicle. As a result, the server CPU 54 can estimate, based on the change in position (movement) of the mobile terminal, that the other merging vehicle 1 is at or may be at a position 4 where it has strayed from the merging lane L2 into the passing lane L1. The server CPU 54 can control the driving of the vehicle 1 traveling in the passing lane L1 so as to avoid interference with the other vehicle 1 that may stray from the merging lane L2.

[0073] Furthermore, in this embodiment, location information about not only the mobile terminal 40 but also the automobile 1 is acquired, and the automobile 1 in which the occupant of the mobile terminal 40 is riding is extracted based on the correlation between the moving speed or change in moving speed in the location information of the automobile 1. In this case, in this embodiment, the type and size of the automobile 1 are selected based on the extracted information about the automobile 1, rather than simply based on the difference in the positions of multiple mobile terminals 40. This can make the estimated type and size of the automobile 1 more likely.

[0074] In the above-described embodiment, the vehicle estimation control of FIG. 8 and the driving control of FIG. Alternatively, for example, part of the vehicle estimation control in Fig. 8 and part of the driving control in Fig. 5 may be executed by, for example, the driving control device 15 of the automobile 1. In this case, the server device 31 and the automobile 1 cooperate to execute the vehicle estimation control in Fig. 8 and the driving control in Fig. 5.

[0075] 8 and the driving control of the vehicle in Fig. 5 may be executed by a plurality of server devices 31 in a distributed manner, rather than by a single server device 31. Such a plurality of server devices 31 may be distributed and arranged corresponding to a plurality of 5G communication base stations 30 provided along the road.

[0076] [Second embodiment] Next, a second embodiment of the present invention will be described. In the above-described embodiment, the server CPU 54 of the server device 31 executes the vehicle estimation control shown in FIG. 8 as part of the driving control shown in FIG. In this embodiment, the driving control device 15 of the automobile 1 executes the estimation control of the vehicle shown in FIG. 8 as part of the driving control of the own vehicle. The following mainly describes the differences from the above-described embodiment, and the same features as those in the above-described embodiment are designated by the same reference numerals and will not be described again.

[0077] FIG. 19 is an explanatory diagram of a cruise control device 15 for an automobile 1 according to a second embodiment of the present invention. The driving control device 15 of the automobile 1 in FIG. 19 includes an input / output unit 91, a timer 92, a memory 93, an ECU 94, and an internal bus 95 to which these are connected.

[0078] The input / output unit 91 is connected to the vehicle network of the control system 10 of the automobile 1. The input / output unit 91 inputs and outputs information to and from other control devices connected to the vehicle network. The timer 92 measures the time or duration. The time of the timer 92 may be calibrated based on the time based on radio waves from GNSS satellites, for example. The memory 93 stores programs and data executed by the ECU 94. The memory 93 may be configured, for example, by a non-volatile semiconductor memory, a HDD, a RAM, or the like. The ECU 94 reads and executes a program recorded in the memory 93. This realizes a control unit that controls the running of the automobile 1. The various control devices provided in the control system 10 of the automobile 1 shown in FIG. 2 may have the same configuration as that shown in FIG.

[0079] FIG. 20 is a flowchart of the host vehicle driving control by the driving control device 15 of FIG. The ECU 94 of the driving control device 15 of FIG. 19 may repeatedly execute the host vehicle driving control of FIG. Note that various control devices provided in the control system 10 of the automobile 1 may cooperate to repeatedly execute the vehicle travel control of FIG.

[0080] In step ST51, the ECU 94 acquires setting information for the vehicle's driving control. Here, the vehicle 1 is assumed to be capable of controlling the driving by the driver's operation, controlling the driving by assisting the driver's operation, or controlling the driving by automatic driving without the driver's operation. The ECU 94 acquires the setting information for these driving controls from, for example, the memory 93.

[0081] In step ST52, the ECU 94 determines whether the setting information for the driving control of the host vehicle indicates automatic driving. If automatic driving is set, the ECU 94 proceeds to step ST54. Otherwise, the ECU 94 proceeds to step ST53.

[0082] In step ST53, the ECU 94 determines whether the setting information for the driving control of the host vehicle is driving assistance. If driving assistance is set, the ECU 94 proceeds to step ST56. Otherwise, that is, if manual driving by the driver is set, the ECU 94 proceeds to step ST58.

[0083] In step ST54, the ECU 94 receives and acquires information that can be used for the automatic driving control from the server device 31 in order to start the automatic driving control. At this time, the ECU 94 may receive and acquire from the server device 31, information such as the location of the mobile terminal 40 collected by the server device 31. The server device 31 may transmit to the requesting vehicle 1, location information of multiple mobile terminals 40 having location information within a predetermined range from the vehicle 1 that requested the information. The acquired information is recorded in the memory 93. The acquired information may also include location information about other vehicles 2 within the predetermined range. The predetermined range should be wider than the range outside the vehicle that can be detected by the vehicle sensors 25 to 28 of the vehicle 1. The ECU 94 may also receive and acquire information such as location information about the vehicle 1 from other vehicles 2 capable of V2X communication, in addition to information from the server device 31.

[0084] In step ST55, the ECU 94 generates cruise control values ​​for automatic driving based on the detection information from the host vehicle sensors 25 to 28, and executes cruise control of the host vehicle using the generated cruise control values. At this time, the ECU 94 may generate cruise control values ​​for autonomous driving by also using information acquired from the server device 31. The ECU 94 executes the vehicle estimation control of FIG. 8 using, for example, information on the location of the mobile terminal 40 acquired from the server device 31. As a result, the ECU 94 can generate information on the type, size, and location on the road of other automobiles 2 around the host vehicle that do not have a communication function with the server device 31. The ECU 94 may then generate cruise control values ​​for autonomous driving that avoid the generated locations on the road of the other automobiles 2, and control the driving of the host vehicle. As a result, the autonomously driven automobile 1 can travel in a manner that is less likely to interfere with other automobiles 2 that do not have a communication function with the server device 31. The ECU 94 may also receive cruise control values ​​for its own vehicle from the server device 31 in step ST54. Even in this case, the ECU 94 may execute the vehicle estimation control shown in FIG. 8 using the information on the location of the mobile terminal 40 that it has acquired. This allows the ECU 94 to update and generate cruise control values ​​used for its own cruise control without performing all the processing required to generate the cruise control values. For example, the ECU 94 can update the cruise control values ​​used for its own cruise control so as to avoid the latest positions of other vehicles 2 that were not taken into account when the server device 31 generated the cruise control values.

[0085] In step ST56, the ECU 94 receives and acquires information that can be used for driving control by driving assistance from the server device 31 in order to start driving control by driving assistance. At this time, the ECU 94 may receive and acquire from the server device 31, information such as the location of the mobile terminal 40 collected by the server device 31. The server device 31 may transmit to the requesting vehicle 1, location information of multiple mobile terminals 40 having location information within a predetermined range from the vehicle 1 that requested the information. The acquired information is recorded in the memory 93. The acquired information may also include location information about other vehicles 2 within the predetermined range. The predetermined range should be wider than the range outside the vehicle that can be detected by the vehicle sensors 25 to 28 of the vehicle 1. The ECU 94 may also receive and acquire information such as location information about the vehicle 1 from other vehicles 2 capable of V2X communication, in addition to information from the server device 31. Thereafter, the ECU 94 ends this control.

[0086] In step ST57, the ECU 94 generates driving control values ​​for driving assistance based on the driver's operation and the detection information of the vehicle's sensors 25 to 28, and executes driving control of the vehicle using the generated driving control values. At this time, the ECU 94 may generate cruise control values ​​for driving assistance using information acquired from the server device 31. The ECU 94 executes the vehicle estimation control of FIG. 8 using, for example, information on the location of the mobile terminal 40 acquired from the server device 31. As a result, the ECU 94 can generate information on the type, size, and location on the road of other automobiles 2 around the host vehicle that do not have a communication function with the server device 31. The ECU 94 may then generate cruise control values ​​for driving assistance that avoid the generated locations on the road of the other automobiles 2, and control the driving of the host vehicle. As a result, the vehicle 1 traveling with driving assistance can travel in a manner that is less likely to interfere with other automobiles 2 that do not have a communication function with the server device 31, while basically following the driver's operation. The ECU 94 may also receive cruise control values ​​for its own vehicle from the server device 31 in step ST54. Even in this case, the ECU 94 may execute the vehicle estimation control shown in FIG. 8 using the information on the location of the mobile terminal 40 that it has acquired. This allows the ECU 94 to update and generate cruise control values ​​used for its own cruise control without performing all the processing required to generate the cruise control values. The ECU 94 can update the cruise control values ​​used for its own cruise control so as to avoid the latest positions of other vehicles 2 that were not taken into account when the server device 31 generated the cruise control values. Thereafter, the ECU 94 ends this control.

[0087] In step ST58, the ECU 94 generates driving control values ​​based only on the driver's operation information, and executes driving control of the vehicle using the generated driving control values. Thereafter, the ECU 94 ends this control.

[0088] As described above, in the automobile 1 of this embodiment, the ECU 94 of the cruise control device 15 uses the external communication control device 17 to receive and acquire location information of the mobile terminals 40 of multiple occupants traveling in the other automobile 2. Then, the ECU 94 of the cruise control device 15 executes the vehicle estimation control of FIG. 8 based on the location information of the multiple mobile terminals 40 traveling in the other automobile 2, and generates cruise control values ​​to be used for cruise control of the host vehicle. In the vehicle estimation control of FIG. 8, the ECU 94 extracts the mobile terminals 40 of multiple occupants traveling in the same other automobile 2 based on the correlation between the travel speeds or changes in travel speeds in the acquired location information of the multiple mobile terminals 40. Furthermore, the ECU 94 estimates the size or type of the other automobile 2 based on the difference in the locations of the mobile terminals 40 of the multiple occupants extracted as traveling in the other automobile 2. Furthermore, the ECU 94 estimates the position of the other vehicle 2 on the road based on the estimated size or type of the other vehicle 2 and the extracted position of the other vehicle 2, and generates a driving control value to be used for driving control of the host vehicle so as not to interfere with the other vehicle 2. The ECU 94 then controls the driving of the host vehicle using the generated driving control value. In this way, in this embodiment, for example, the size and type of automobile 1 that does not have a position detection function can be estimated based on the position information of the mobile terminal 40 in the automobile 1, in order to control the traveling of the automobile 1. Also, in this embodiment, the position of the automobile 1 on the road can be estimated based on the estimated size or type of automobile 1 and the position information of the automobile 1. Furthermore, in this embodiment, it becomes possible to control the traveling of the automobile 1 so as not to interfere with the automobile 1, for example, by using the estimated position on the road of the automobile 1 that does not have a position detection function. In particular, in this embodiment, the above-mentioned information about the automobile 1 is not estimated based on the location information of one mobile terminal 40, but is estimated based on the location information of multiple mobile terminals 40. In this embodiment, the difference in the locations of the multiple mobile terminals 40 is used to estimate the range in which an occupant can ride in the automobile 1, and the type and size of the automobile 1 are estimated accordingly. The estimated type and size of the automobile 1 do not need to be fixed. In contrast, if the information about the automobile 1 is estimated based on the location information of one mobile terminal 40, for example, the type and size of the automobile 1 basically need to be fixed. The same is true for the position of the automobile 1 on the road. If these fixed values ​​are used, the accuracy of the type and size of the automobile 1 or its position on the road may decrease. As a result, in this embodiment, the size, type, or location on the road of an automobile 1 that does not have a location detection function can be estimated with sufficient accuracy to be usable for controlling vehicle travel, for example.

[0089] Furthermore, the automobile 1 of this embodiment can acquire not only the location information of the mobile terminal 40 but also the location information of the automobile 1 from the server device 31 or the like. Then, the ECU 94 extracts the automobile 1 in which the occupant of the mobile terminal 40 is riding, based on the correlation between the moving speed or the change in moving speed in the location information of the automobile 1. In this case, in this embodiment, the type and size of the automobile 1 are selected based on the extracted information of the automobile 1, rather than simply based on the difference in the positions of the multiple mobile terminals 40. This can make the estimated type and size of the automobile 1 more likely.

[0090] In the above-described embodiment, the vehicle estimation control shown in FIG. Alternatively, for example, part of the estimation control of the vehicle in Fig. 8 may be executed by the ECUs 94 of various control devices included in the control system 10 of the automobile 1. Furthermore, the ECUs 94 of multiple control devices included in the control system 10 of the automobile 1 may cooperate to execute the estimation control of the vehicle in Fig. 8.

[0091] The above-described embodiment is an example of a preferred embodiment of the present invention, but the present invention is not limited to this, and various modifications and changes are possible within the scope of the gist of the invention.

[0092] In the above-described embodiment, the automobile 1 traveling in an autonomous driving mode including driving assistance estimates information such as the position of the other automobile 2 based on the position information of the mobile terminal 40 in order to perform driving control that avoids interference with the other automobile 2 that does not have a position detection function. In addition, for example, information such as the position of another automobile 2 estimated based on the position information of the mobile terminal 40 can be used to control the driving of the automobile 1 in which the mobile terminal 40 is riding. Even in this case, it is expected that the other automobile 2 will be able to perform highly accurate driving control based on a more probable position compared to when driving is controlled based only on the position determined by its own position detection function. By improving the position accuracy of the own automobile, it is possible to increase the possibility of avoiding interference with surrounding automobiles 1.

[0093] As described above, the above-described embodiment discloses a vehicle driving control device. In the vehicle driving control device, the server CPU 54 or ECU 94, which serves as a control unit capable of executing control using information received from the mobile terminal 40, may execute various processes for controlling the vehicle driving described above. In this case, the automobile 1 or the server device 31 can also function as a vehicle information estimation device. For example, when the relative positions of the position information of the mobile terminals 40 of multiple occupants extracted as riding in the automobile 1 as a vehicle are changing, the server CPU 54 or ECU 94 may estimate that the vehicle is a type of vehicle that can accommodate multiple occupants in the direction of change in the relative positions. In this case, the server CPU 54 or ECU 94 may estimate the size or type of the vehicle or the position of the vehicle on the road by assuming that the vehicle is a type of vehicle that has a width in the direction of change in the relative positions. Furthermore, the server CPU 54 or the ECU 94 may execute only some of the various processes described above for controlling vehicle driving, rather than all of them, and in this case, the other of the server CPU 54 and the ECU 94 may execute the remaining processes. For example, the server CPU 54 may perform at least one of the following processes: acquiring multiple pieces of location information, including location information received from mobile devices of multiple occupants traveling in a vehicle; extracting the mobile devices of multiple occupants in the same vehicle based on the correlation between the travel speed or changes in travel speed in the acquired location information of the multiple mobile devices; estimating the size or type of the vehicle based on the difference in the positions of the mobile devices of multiple occupants extracted as being passengers in the vehicle; and estimating the position of the vehicle on the road based on the estimated size or type of the vehicle and the extracted location information, and controlling the vehicle's travel. [Explanation of symbols]

[0094] 1...automobile (vehicle), 2...other automobile (vehicle), 3...merging area, 4...position of deviation, L1...passing lane, L2...merging side lane, L3...side road, 10...control system, 11...drive control device, 12...steering control device, 13...braking control device, 14...operation detection device, 15...travel control device, 16...detection control device, 17...external communication control device (communication unit), 18...central gateway device, 21...steering (operating member), 22...accelerator pedal (operating member), 23...brake pedal (operating member), 24...shift lever (operating member), 25...GNSS receiver (host vehicle sensor), 26...external camera (host vehicle sensor), 27...Lidar (host vehicle sensor), 28...acceleration sensor Sensor (vehicle sensor), 30...base station, 31...server device, 40...mobile terminal, 41...terminal communication device, 42...terminal GNSS receiver, 43...terminal memory, 44...terminal CPU, 45...terminal bus, 51...server communication device (communication unit), 52...server timer, 53...server memory, 54...server CPU (control unit), 55...server bus, 60...vehicle, 61...vehicle compartment, 62...driver's seat, 63...passenger seat, 64...rear seat, 65...frame, 66...reference position, 71...first vehicle, 72...second vehicle, 73...first mobile terminal, 74...second form terminal, 80...correspondence relationship table, 91...input / output unit, 92...timer, 93...memory, 94...ECU (communication unit), 95...internal bus

Claims

1. A vehicle travel control device having a communication unit capable of communicating with mobile devices of a plurality of occupants traveling in a vehicle, and a control unit capable of executing control using information received from the mobile devices, The control unit acquire a plurality of pieces of location information including location information received from the mobile terminals of a plurality of occupants who are traveling in the vehicle; generating a moving speed or a change in moving speed of each of the plurality of mobile terminals from the acquired position information; extracting the portable devices of a plurality of occupants in the same vehicle based on a correlation between the moving speed or the change in the moving speed based on the position information of the plurality of portable devices; Estimating the size or type of the vehicle based on differences in the positions of the mobile devices of a plurality of occupants extracted as being in the vehicle; estimating the position of the vehicle on the road based on the estimated size or type of the vehicle and the extracted position information, and controlling the traveling of the vehicle; Vehicle driving control device.

2. The control unit When the vehicle location information is acquired, the vehicle in which the occupant of the mobile terminal is riding is extracted based on the correlation between the vehicle location information and the moving speed or the change in the moving speed; Selecting a size of the vehicle according to the extracted type of vehicle; estimating a position of the selected vehicle on a road, assuming that the occupant of the mobile device is in the vehicle; 2. The vehicle driving control device according to claim 1.

3. The control unit If the position information of the mobile devices of the multiple occupants extracted as being on board the vehicle has a difference in the road width direction, it is estimated that the type of the vehicle is a vehicle in which multiple occupants can ride side by side in the vehicle width direction, Assuming that the vehicle is a certain type of vehicle, estimate the size or type of the vehicle or the position of the vehicle on the road.

3. A vehicle driving control device according to claim 1 or 2.

4. The control unit If the position information of the mobile devices of the multiple occupants extracted as being on board the vehicle has a difference in the direction of extension of the road, it is estimated that the type of the vehicle is a vehicle in which multiple occupants can ride side by side in a front-to-rear direction, Assuming that the vehicle is a type of vehicle with a certain front-to-rear width, estimate the size or type of the vehicle or the position of the vehicle on the road. The vehicle travel control device according to any one of claims 1 to 3.

5. A vehicle having a communication unit capable of receiving, by communication, information on the positions of mobile devices of a plurality of occupants traveling in other vehicles, and a control unit capable of executing vehicle travel control based on the received information on the positions of the mobile devices, The control unit of the vehicle a first process of acquiring a plurality of pieces of position information including position information received from the mobile devices of a plurality of occupants traveling in the other vehicle; a second process of generating a moving speed or a change in moving speed of each of the plurality of mobile terminals from the acquired position information; a third process of extracting the portable devices of a plurality of occupants in the same vehicle based on a correlation between the moving speed or the change in the moving speed based on the position information of the plurality of portable devices; a fourth process of estimating a size or a type of the other vehicle based on differences in positions of the mobile devices of a plurality of occupants extracted as being occupants of the other vehicle; a fifth process of estimating the position of the other vehicle on the road based on the estimated size or type of the other vehicle and the extracted position information, and controlling the traveling of the other vehicle; A vehicle that performs at least the fifth process.

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