Driving assistance device and computer program

Abstract

The present invention provides a driving assistance device and a computer program capable of generating a travel trajectory in which sudden turning or deceleration is suppressed when traveling in a curve section including a plurality of consecutive curves, as a travel trajectory for a recommended vehicle to travel. Specifically, the present invention is configured so as to: acquire a planned travel path on which a vehicle travels, and, in particular, when a plurality of continuous curves are included in the acquired planned travel path, set connection points of the plurality of curves for a curve section including the plurality of curves using map information including information relating to a division line; a curve section is taken as a target, a first half travel trajectory from a start vector to a connection point and a second half travel trajectory from the connection point to an end vector are combined to generate a travel trajectory for recommended vehicle travel, and driving assistance of the vehicle is performed on the basis of the generated travel trajectory.

Description

Technical Field

[0001] The present invention relates to a driving assistance device and a computer program for assisting driving of a vehicle in a parking lot. Background Art

[0002] In recent years, in addition to manual driving based on the user's driving operation, an automatic driving assistance system has been newly proposed as a driving method of a vehicle, which assists the user in driving the vehicle by performing part or all of the user's driving operation on the vehicle side. In the automatic driving assistance system, for example, the current position of the vehicle, the lane in which the vehicle is traveling, and the positions of other vehicles in the surrounding area are detected at any time, and the vehicle is driven along a pre-set path, and the steering device, drive source, brake, etc. are automatically controlled.

[0003] In addition, when driving based on the above-mentioned automatic driving assistance or performing various driving assistance for other vehicles, a recommended driving trajectory is pre-generated on the road where the vehicle is traveling based on the vehicle's scheduled driving path, map information, etc. For example, International Publication No. 2021 / 059601 discloses the following technology: for an intersection or a lane change section, a recommended driving trajectory relative to the center of the lane where the vehicle is traveling is generated, and the vehicle is controlled in a manner of traveling according to the generated driving trajectory.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: International Publication No. 2021 / 059601 (Paragraph 0081) Summary of the invention

[0007] Problems to be solved by the invention

[0008] Here, in the technology disclosed in the above-mentioned patent document 1, except for a part of the section such as the intersection, the driving trajectory recommended for driving is basically generated for the center of the lane where the vehicle is traveling. Therefore, even for a section including a road that is curved at a predetermined angle or curved in an arc shape with a predetermined curvature (hereinafter referred to as a curved section), a driving trajectory recommended for driving in the center of the lane where the vehicle is traveling is generated. However, especially in a curved section where multiple curves are continuous, such as a sharp turn or an S-shaped curve, the trajectory traveling in the center of the lane is not necessarily limited to being the driving trajectory recommended for the vehicle, and it may be a trajectory accompanied by a sharp turn or deceleration, for example.

[0009] The present invention is completed in order to solve the above-mentioned existing problems, and its purpose is to provide a driving assistance device and a computer program that can generate a driving trajectory that suppresses sharp turns or deceleration when driving in a curve section containing a plurality of consecutive curves, as a recommended driving trajectory for vehicle driving, and can implement appropriate driving assistance without placing a burden on the vehicle's occupants.

[0010] Technical means of solving problems

[0011] In order to achieve the above-mentioned object, the driving assistance device of the present invention comprises: a planned driving path acquisition unit, which acquires a planned driving path for a vehicle to travel; a connection point setting unit, which sets a plurality of connection points of the curves with respect to a curve section including the plurality of the curves when the planned driving path includes a plurality of continuous curves; a start vector acquisition unit, which acquires a start vector, which determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the planned driving path; an end vector acquisition unit, which acquires an end vector, which determines the position and orientation of the vehicle at the end point of the curve section when traveling along the planned driving path; a driving trajectory generation unit, which generates a driving trajectory for the recommended vehicle to travel by combining a first half driving trajectory from the start vector to the connection point and a second half driving trajectory from the connection point to the end vector with respect to the curve section as the object; and a driving assistance unit, which performs driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation unit.

[0012] The term “curve” includes a shape where the road curves at a predetermined angle such as a right angle (eg, an L-shaped road), in addition to a shape where the road curves in an arc shape at a predetermined curvature.

[0013] In addition, the computer program of the present invention is a program for generating auxiliary information used in driving assistance implemented in a vehicle. Specifically, the computer is made to function as the following units: a planned driving route acquisition unit that acquires a planned driving route for the vehicle to travel; a connection point setting unit that sets a plurality of connection points of the curves for a curve section including a plurality of the curves when the planned driving route includes a plurality of continuous curves; a start vector acquisition unit that acquires a start vector that determines the position and orientation of the vehicle at the start point of the curve section when traveling along the planned driving route; an end vector acquisition unit that acquires an end vector that determines the position and orientation of the vehicle at the end point of the curve section when traveling along the planned driving route; a driving trajectory generation unit that generates a driving trajectory for the recommended vehicle to travel by combining the first half driving trajectory from the start vector to the connection point and the second half driving trajectory from the connection point to the end vector for the curve section as the object; and a driving assistance unit that performs driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation unit.

[0014] Effects of the Invention

[0015] According to the driving assistance device and computer program of the present invention having the above-mentioned structure, the connection points of each curve when passing through a curve section including a plurality of continuous curves are set on the road according to the shape of the road or the dividing line, and a driving trajectory connecting the driving trajectories of each curve is generated at the connection point, so that a driving trajectory that suppresses sharp turns or deceleration when driving in a curve section including a plurality of continuous curves can be generated as a driving trajectory recommended for vehicle driving. As a result, appropriate driving assistance can be implemented without placing a burden on the occupants of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 1 is a diagram schematically showing the configuration of a driving assistance system according to the present embodiment.

[0017] Figure 2 It is a block diagram showing the configuration of the driving assistance system according to the present embodiment.

[0018] Figure 3 This is a block diagram showing a navigation device according to this embodiment.

[0019] Figure 4 This is a flowchart of the automatic driving assistance program of this embodiment.

[0020] Figure 5 This is a diagram showing an area for obtaining high-precision map information.

[0021] Figure 6 This is a diagram for explaining a method of calculating a dynamic driving trajectory.

[0022] Figure 7 This is a flowchart of a sub-processing procedure of a static driving trajectory generation process.

[0023] Figure 8 This is a diagram showing an example of a planned travel route of a vehicle.

[0024] Fig. 9 It means for Figure 8 FIG. 1 is a diagram showing an example of a lane network constructed according to a planned driving route.

[0025] Fig.10 This is a flowchart of a sub-processing routine of the processing for generating a driving trajectory in a curve section.

[0026] Fig.11 This is a flowchart of a sub-processing routine of the processing for generating a driving trajectory in a curve section.

[0027] Fig.12 This is a diagram showing an example of a curve section including discontinuous curves.

[0028] Fig.13 This is a diagram showing an example of a curve section including a plurality of continuous curves.

[0029] Fig.14 This is a diagram for explaining the method of setting the cropping points.

[0030] Fig.15 This is a diagram for explaining an example in which the start vector and the end vector are pluralized.

[0031] Fig.16 This is a diagram for explaining a case where an arc having the largest curvature radius passing through a start vector and an end vector in the direction of travel of each vector is included in a lane in which the vehicle is traveling.

[0032] Fig.17 This is a diagram for explaining a case where an arc having the largest curvature radius passing through a start vector and an end vector in the direction of travel of each vector is not included in the lane in which the vehicle is traveling.

[0033] Fig.18 This is a diagram showing candidates for travel trajectories generated for a curve section.

[0034] Fig.19 It is a diagram showing a method of generating the second driving locus and the third driving locus.

[0035] Fig. 20 This is a diagram showing how connection points are set for a curve section in which a plurality of curves having different bending directions are continuous.

[0036] Fig.21This is a diagram showing how connection points are set for a curve section in which a plurality of curves having the same bending direction are continuous.

[0037] Fig. 22 This diagram shows the start vector and the end vector set for each section when a curve section including a plurality of continuous curves having different curve directions is divided at an intermediate point.

[0038] Fig.23 This diagram shows the start vector and the end vector set for each section when a curve section including a plurality of continuous curves having the same bending direction is divided at an intermediate point.

[0039] Fig.24 This is a diagram for explaining an example in which the start vector and the end vector are pluralized.

[0040] Fig.25 It is a diagram showing a correction example for smoothing the travel trajectory. DETAILED DESCRIPTION

[0041] Hereinafter, an embodiment of the driving assistance device of the present invention as a navigation device 1 will be described in detail with reference to the accompanying drawings. Figure 1 and Figure 2 A schematic configuration of a driving support system 2 including a navigation device 1 according to the present embodiment will be described. Figure 1 1 is a diagram schematically showing the configuration of the driving assistance system 2 according to the present embodiment. Figure 2 It is a block diagram showing the configuration of the driving assistance system 2 according to the present embodiment.

[0042] like Figure 1 As shown, the driving assistance system 2 of this embodiment basically includes a server device 4 provided in an information distribution center 3 and a navigation device 1 mounted on a vehicle 5 to perform various assistance related to the automatic driving of the vehicle 5. In addition, the server device 4 and the navigation device 1 are configured to be able to transmit and receive electronic data to each other via a communication network 6. In addition, other vehicle-mounted devices mounted on the vehicle 5 and a vehicle control device that performs control related to the vehicle 5 may be used instead of the navigation device 1.

[0043] Here, the vehicle 5 is a vehicle that can be driven by an automated driving assist in addition to manual driving based on a user's driving operation, and can also be driven by an automated driving assist that automatically drives the vehicle along a predetermined path or road without depending on the user's driving operation.

[0044] In addition, the automatic driving assistance may be performed for all road sections, or may be configured to be performed only when the vehicle is traveling in a certain road section (for example, a highway with an entrance and exit (regardless of whether there are people or a toll) at the boundary). In the following description, the automatic driving section where the automatic driving assistance of the vehicle is performed includes parking lots in addition to all road sections including general roads and highways, and the automatic driving assistance is basically performed from the start of the vehicle to the end of the vehicle (until the vehicle stops). However, the automatic driving assistance is not necessarily performed when the vehicle is traveling in the automatic driving section. It is preferred that the automatic driving assistance is performed only when the user selects the automatic driving assistance (for example, the automatic driving start button is set to on) and it is determined that driving based on the automatic driving assistance can be performed. On the other hand, the vehicle 5 may also be a vehicle that can only perform assisted driving based on the automatic driving assistance.

[0045] Furthermore, in the vehicle control assisted by the automatic driving, for example, the current position of the vehicle, the lane in which the vehicle is traveling, and the positions of the surrounding obstacles are detected at any time, and the vehicle control of the steering device, the driving source, the brake, etc. is automatically performed so that the vehicle travels along the travel trajectory generated by the navigation device 1 as described later and at a speed that conforms to the generated speed plan. In addition, in the assisted driving based on the automatic driving assistance of the present embodiment, lane changes, left and right turns, and parking operations can also be driven by performing the vehicle control based on the automatic driving assistance, but it can also be configured so that special driving such as lane changes, left and right turns, and parking operations are not performed by driving based on the automatic driving assistance but by manual driving.

[0046] On the other hand, the navigation device 1 is a vehicle-mounted device mounted on the vehicle 5, and displays a map of the vicinity of the vehicle's position based on the map data possessed by the navigation device 1 or the map data obtained from the outside, or inputs the user's destination, or displays the current position of the vehicle on the map image, or provides movement guidance along the set guidance path. In this embodiment, in particular, when the vehicle is assisted in driving by automatic driving assistance, various auxiliary information related to automatic driving assistance is generated. As auxiliary information, for example, there is a recommended driving trajectory for the vehicle (including a recommended lane movement method), selection of a parking position for parking the vehicle at the destination, and a speed plan that displays the vehicle speed during driving. In addition, the details of the navigation device 1 will be described later.

[0047] In addition, the server device 4 performs a route search in accordance with the request of the navigation device 1. Specifically, the information required for the route search, such as the departure point and the destination, is sent from the navigation device 1 to the server device 4 together with the route search request (however, in the case of a re-search, it is not necessarily necessary to send information related to the destination). Then, the server device 4 that receives the route search request uses the map information possessed by the server device 4 to perform a route search and determine a recommended route from the departure point to the destination. Then, the determined recommended route is sent to the navigation device 1 that is the request source. Then, the navigation device 1 can provide the user with information related to the received recommended route, or use the recommended route to generate various auxiliary information related to automatic driving assistance as described later.

[0048] Furthermore, unlike the usual map information used in the above-mentioned route search, the server device 4 also has map information with higher accuracy, namely, high-precision map information and facility information. The high-precision map information, for example, includes information related to the lane shape of the road (road shape, curvature, bending angle, lane width, etc. in units of lanes) and the demarcation lines drawn on the road (lane center line, lane boundary line, lane outer line, guide line, etc.). In addition, it also includes information related to intersections, etc. On the other hand, the facility information is more detailed information related to the facility, and is stored separately from the information related to the facility included in the map information, such as the floor map of the facility, information related to the entrance of the parking lot, the passages provided by the parking lot, the configuration information of the parking space, the information of the demarcation lines that divide the parking space, and the connection information indicating the connection relationship between the entrance of the parking lot and the lane. In addition, the server device 4 distributes the high-precision map information and facility information according to the request from the navigation device 1, and the navigation device 1 uses the high-precision map information and facility information distributed from the server device 4 to generate various auxiliary information related to automatic driving assistance as described later. In addition, high-precision map information is basically map information that only targets roads (road links) and their surroundings, but it can also be map information that also includes areas other than the road surroundings.

[0049] However, the route search process described above does not necessarily have to be performed by the server device 4, and can be performed by the navigation device 1 if the navigation device 1 has map information. In addition, the high-precision map information and facility information may not be distributed from the server device 4, but may be pre-owned by the navigation device 1.

[0050] In addition, the communication network 6 includes a plurality of base stations arranged throughout the country, and a communication company that manages and controls each base station, and is formed by connecting the base stations and the communication company to each other by wire (optical fiber, ISDN, etc.) or wirelessly. Among them, the base station has a transceiver (transceiver) and an antenna for communicating with the navigation device 1. In addition, the base station performs wireless communication with the communication company, and on the other hand, has the following functions: as the end of the communication network 6, it relays the communication of the navigation device 1 located within the range (cell) reached by the radio wave of the base station with the server device 4.

[0051] Next, use Figure 2 The structure of the server device 4 in the driving assistance system 2 is described in more detail. Figure 2 As shown, the server device 4 includes a server control unit 11 , a server-side map DB 12 as an information recording unit connected to the server control unit 11 , a high-precision map DB 13 , a facility DB 14 , and a server-side communication device 15 .

[0052] The server control unit 11 is a control unit (MCU, MPU, etc.) that performs overall control of the server device 4, and includes an internal storage device such as a CPU 21 that serves as a computing device and a control device, a RAM 22 that serves as a working memory when the CPU 21 performs various computing processes, a ROM 23 that records control programs, and a flash memory 24 that stores programs read from the ROM 23. In addition, the server control unit 11 and the ECU of the navigation device 1 described later both have various units that serve as processing algorithms.

[0053] On the other hand, the server-side map DB 12 is a storage unit for storing server-side map information, which is the latest version of map information registered based on input data or input operations from the outside. Among them, the server-side map information is composed of various information required for path search, path guidance and map display represented by a road network. For example, it is composed of network data including nodes and sections of the road network, section data related to roads (sections), node data related to nodes, intersection data related to each intersection, location data related to facilities and other locations, map display data for displaying maps, search data for searching for paths, and search data for retrieving locations.

[0054] In addition, the high-precision map DB 13 is a storage unit for storing map information 16, which is map information with higher precision than the above-mentioned server-side map information. The high-precision map information 16 is map information that stores more detailed information about the road that is the driving object of the vehicle. In the present embodiment, for example, the road includes information related to the lane shape (road shape, curvature, lane width, etc. of the lane unit) and the demarcation lines drawn on the road (lane center line, lane boundary line, lane outer line, guide line, etc.). Furthermore, data indicating the slope, superelevation, embankment, merging section, place where the number of lanes is reduced, place where the width is narrowed, and road crossing are recorded; for curves, data indicating the radius of curvature and the angle of curvature are recorded; data indicating branch points such as intersections and T-roads are recorded; for road attributes, data indicating downhill roads, uphill roads, etc. are recorded; for road types, in addition to general roads such as national highways, county roads, and narrow streets, data indicating toll roads such as national expressways, urban expressways, motor vehicle-only roads, general toll roads, and toll bridges are recorded. In addition, as information related to the dividing lines, information is stored to determine which dividing lines are configured relative to the road. In addition, in the following description, the so-called "curve" includes shapes that are curved at a predetermined angle such as a right angle (for example, an L-shaped road) in addition to shapes where the road is curved into an arc with a predetermined curvature. In addition, in addition to the number of lanes on the road, information is also stored to determine the traffic division of the travel direction of each lane and the connection of the roads (specifically, the correspondence between the lanes included in the road before the intersection and the lanes included in the road after the intersection). Furthermore, the speed limit set for the road is also stored.

[0055] On the other hand, the facility DB 14 is a storage unit that stores more detailed facility-related information than the facility-related information stored in the above-mentioned server-side map information. Specifically, as the facility information 17, in particular, the parking lot (including parking lots attached to facilities and independent parking lots) as the parking object of the vehicle includes information that determines the location of the entrance and exit of the parking lot, information that determines the configuration of the parking space in the parking lot, information related to the demarcation lines that divide the parking space, information related to the passage, etc. For facilities other than the parking lot, it includes information that determines the floor map of the facility. The floor map includes, for example, information that determines the location of the entrance and exit, passage, stairs, elevator, and escalator. In addition, in a complex commercial facility with multiple tenants, it includes information for determining the location of each tenant who moves in. In particular, the facility information 17 may also be information that generates parking lots and facilities based on a 3D model. Furthermore, the facility DB 14 also includes: connection information 18 that indicates the connection relationship between the lanes included in the entrance road facing the entrance of the parking lot and the entrance of the parking lot; and road external shape information 19 that determines the area where vehicles can pass between the entrance road and the entrance of the parking lot.

[0056] In addition, the high-precision map information 16 is basically map information that only includes roads (road sections) and their surrounding areas, but it can also be map information that includes areas other than the road surrounding areas. Figure 2 In the example shown, the server-side map information stored in the server-side map DB 12 and the information stored in the high-precision map DB 13 or the facility DB 14 are different map information, but the information stored in the high-precision map DB 13 or the facility DB 14 may also be a part of the server-side map information. In addition, the high-precision map DB 13 and the facility DB 14 may not be separated but may be set as one database.

[0057] On the other hand, the server-side communication device 15 is a communication device for communicating with the navigation device 1 of each vehicle 5 via the communication network 6. In addition to the navigation device 1, traffic information consisting of congestion information, restriction information, traffic accident information, etc. transmitted from the Internet and traffic information centers such as VICS (registered trademark: Vehicle Information and Communication System) centers can also be received.

[0058] Next, use Figure 3 A schematic configuration of the navigation device 1 mounted on the vehicle 5 will be described. Figure 3 It is a block diagram showing the navigation device 1 according to the present embodiment.

[0059] like Figure 3 As shown, the navigation device 1 of this embodiment includes: a current position detection unit 31 for detecting the current position of the vehicle equipped with the navigation device 1; a data recording unit 32, which records various data; a navigation ECU 33, which performs various calculations based on the input information; an operation unit 34, which receives operations from the user; a liquid crystal display 35, which displays a map of the vehicle's surroundings, information related to the guidance route set by the navigation device 1 (the vehicle's scheduled travel route), etc. to the user; a speaker 36, which outputs voice guidance related to the route guidance; a DVD drive 37, which reads a DVD as a storage medium; and a communication module 38, which communicates with an information center such as a detection center and a VICS center. In addition, the navigation device 1 is connected to an external camera 39 and various sensors installed in the vehicle equipped with the navigation device 1 via an in-vehicle network such as CAN. In addition, it can also be connected to a vehicle control ECU 40 that performs various controls on the vehicle equipped with the navigation device 1 in a two-way communication manner.

[0060] Hereinafter, each component included in the navigation device 1 will be described in sequence.

[0061] The current position detection unit 31 is composed of GPS 41, a vehicle speed sensor 42, a steering sensor 43, a gyro sensor 44, etc., and can detect the current vehicle position, direction, vehicle speed, current time, etc. Among them, in particular, the vehicle speed sensor 42 is a sensor for detecting the moving distance and speed of the vehicle, generates pulses according to the rotation of the driving wheels of the vehicle, and outputs the pulse signal to the navigation ECU 33. Then, the navigation ECU 33 calculates the rotation speed and moving distance of the driving wheels by counting the generated pulses. In addition, the navigation device 1 does not need to have all of the above four sensors, and can also be configured as a structure in which the navigation device 1 only has one or more of the sensors.

[0062] In addition, the data recording unit 32 includes: a hard disk (not shown) as an external storage device and recording medium; and a recording head (not shown) as a driver for reading the map information DB45, cache 46, a specified program, etc. recorded in the hard disk and writing specified data to the hard disk. In addition, instead of the hard disk, the data recording unit 32 may also have a flash memory, a memory card, a CD, a DVD, or other optical disk. In addition, in the present embodiment, as described above, since the path to the destination is searched in the server device 4, the map information DB45 may also be omitted. Even in the case where the map information DB45 is omitted, the map information can be obtained from the server device 4 as needed.

[0063] Among them, the map information DB45 is a storage unit that stores, for example, section data related to roads (sections), node data related to nodes, search data for searching or changing paths, facility data related to facilities, map display data for displaying maps, intersection data related to each intersection, and retrieval data for retrieving locations.

[0064] On the other hand, the cache 46 is a storage unit that stores high-precision map information 16, facility information 17, connection information 18, and road shape information 19 that were distributed from the server device 4 in the past. The storage period can be set appropriately, for example, it can be a specified period from the start of storage (for example, one month), or it can be until the ACC power (accessory powersupply: auxiliary power supply) of the vehicle is turned off. In addition, the old data can be deleted in sequence after the amount of data stored in the cache 46 reaches the upper limit. In addition, the navigation ECU 33 uses the high-precision map information 16, facility information 17, connection information 18, and road shape information 19 stored in the cache 46 to generate various auxiliary information related to automatic driving assistance. The details will be described later.

[0065] On the other hand, the navigation ECU (electronic control unit) 33 is an electronic control unit that performs overall control of the navigation device 1, and includes: a CPU 51 as a computing device and a control device, and internal storage devices such as a RAM 52, a ROM 53, and a flash memory 54. The RAM 52 is used as a working memory when the CPU 51 performs various computing processes and stores route data when a route is searched, and the ROM 53 records an automatic driving assistance program described later in addition to a control program (see Figure 4 ), etc., the flash memory 54 stores the program read from the ROM 53. In addition, the navigation ECU 33 has various units as processing algorithms. For example, the planned driving route acquisition unit acquires the planned driving route for the vehicle to travel. In the case where the planned driving route includes a plurality of continuous curves, the connection point setting unit sets the connection points of the plurality of curves with the curve section including the plurality of curves as the object. The start vector acquisition unit acquires the start vector, which determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the planned driving route. The end vector acquisition unit acquires the end vector, which determines the position and orientation of the vehicle at the end point of the curve section when traveling along the planned driving route. The driving trajectory generation unit combines the first half of the driving trajectory from the start vector to the connection point and the second half of the driving trajectory from the connection point to the end vector with the curve section as the object, and generates a driving trajectory for the recommended vehicle to travel. The driving assistance unit performs driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation unit.

[0066] The operation unit 34 is operated when inputting a departure point as a starting point of driving and a destination as an end point of driving, and has a plurality of operation switches (not shown) such as various keys and buttons. Moreover, the navigation ECU 33 controls to perform various corresponding actions based on switch signals output by pressing each switch, etc. In addition, the operation unit 34 may also have a touch panel provided on the front surface of the liquid crystal display 35. In addition, a microphone and a voice recognition device may also be provided.

[0067] In addition, a map image including roads, traffic information, operation guidance, operation menu, key guidance, guidance information along the guidance route (planned driving route), news, weather forecast, time, email, TV programs, etc. are displayed on the liquid crystal display 35. In addition, HUD or HMD may be used instead of the liquid crystal display 35.

[0068] In addition, the speaker 36 outputs voice guidance for guiding the vehicle to travel along the guidance route (scheduled travel route) and guidance of traffic information based on the instruction from the navigation ECU 33 .

[0069] In addition, the DVD drive 37 is a drive that can read data recorded in a recording medium such as a DVD or CD. And, based on the read data, music or video playback, map information DB 45 update, etc. In addition, a card slot for reading and writing a memory card can also be provided instead of the DVD drive 37.

[0070] In addition, the communication module 38 is a communication device for receiving traffic information, detection information, weather information, etc. sent from a traffic information center such as a VICS center, a detection center, etc., such as a mobile phone, a DCM. In addition, it also includes a vehicle-to-vehicle communication device for communicating between vehicles and a road-to-vehicle communication device for communicating with a roadside device. In addition, it is also used to send and receive path information, high-precision map information 16, facility information 17, connection information 18, and road external shape information 19 searched by the server device 4.

[0071] In addition, the vehicle exterior camera 39 is composed of a camera using a solid-state imaging element such as a CCD, for example, and is installed above the front bumper of the vehicle and the optical axis direction is set to a predetermined angle from the horizontal to the bottom. Moreover, when the vehicle is traveling in the automatic driving zone, the vehicle exterior camera 39 takes a picture of the vehicle in front of the direction of travel. In addition, the navigation ECU 33 detects obstacles such as demarcation lines drawn on the road on which the vehicle is traveling and other surrounding vehicles by performing image processing on the captured images, and generates various auxiliary information related to automatic driving assistance based on the detection results. For example, when an obstacle is detected, a new driving trajectory is generated to avoid or follow the obstacle. In addition, the vehicle exterior camera 39 can also be configured to be arranged at the rear or side other than the front of the vehicle. In addition, as a unit for detecting obstacles, sensors such as millimeter wave radars, laser sensors, vehicle-to-vehicle communication, and road-to-vehicle communication can also be used instead of cameras.

[0072] In addition, the vehicle control ECU 40 is an electronic control unit that controls the vehicle equipped with the navigation device 1. In addition, the vehicle control ECU 40 is connected to each driving part of the vehicle such as the steering device, the brake, and the accelerator. In this embodiment, in particular, after the vehicle starts the automatic driving assistance, the automatic driving assistance of the vehicle is implemented by controlling each driving part. In addition, when the user performs an override during the automatic driving assistance, the overriding is detected.

[0073] Among them, the navigation ECU 33 sends various auxiliary information related to automatic driving assistance generated by the navigation device 1 to the vehicle control ECU 40 via the CAN after the start of driving. Then, the vehicle control ECU 40 uses the received various auxiliary information to implement automatic driving assistance after the start of driving. The auxiliary information includes, for example, a driving trajectory recommended for the vehicle, a speed plan indicating the vehicle speed during driving, and the like.

[0074] Next, based on Figure 4 The automatic driving support program executed by the CPU 51 in the navigation device 1 of the present embodiment having the above-described configuration will be described. Figure 4 is a flowchart of the automatic driving assistance program of this embodiment. The automatic driving assistance program is executed when the vehicle's ACC power supply (accessory power supply) is turned on and the vehicle starts to drive based on automatic driving assistance, and implements assisted driving based on automatic driving assistance based on the assistance information generated by the navigation device 1. In addition, the following Figure 4 , Figure 7 , Fig.10 and Fig.11 The program shown in the flowchart is stored in the RAM 52 and the ROM 53 included in the navigation device 1 , and is executed by the CPU 51 .

[0075] First, in the automatic driving assistance program, in step (hereinafter referred to as S) 1, the CPU 51 obtains the planned path for the vehicle to travel in the future (hereinafter also referred to as the planned travel path). In addition, the planned travel path of the vehicle is, for example, a recommended path to the destination searched by the server device 4 when the user sets the destination. In addition, when the destination is not set, the path along the road from the current position of the vehicle can also be used as the planned travel path.

[0076] In addition, when searching for a recommended route, first, the CPU 51 sends a route search request to the server device 4. In addition, the route search request includes the terminal ID of the navigation device 1 that determines the source of the route search request, and information that determines the departure point (for example, the current position of the vehicle) and the destination. In addition, the information that determines the destination is not necessarily required when searching again. Then, the CPU 51 receives the search route information sent from the server device 4 according to the route search request. The search route information is information that determines the recommended route (center route) from the departure point to the destination that the server device 4 searches for using the latest version of map information based on the route search request sent (for example, a list of sections included in the recommended route). For example, the search is performed using the well-known Dijkstra method.

[0077] Furthermore, in the search for the recommended route, it is preferred to select a parking position (parking space) recommended for parking the vehicle in the parking lot at the destination, and search for a recommended route to the selected parking position. That is, in addition to the route to the parking lot, the recommended route to be searched preferably includes a route indicating the movement of the vehicle in the parking lot. For example, a parking space that is easy for the user to park in the parking spaces that are vacant in the parking lot (for example, a parking space that is close to the entrance of the parking lot, a parking space that has no other vehicles parked on its left and right, etc.) is determined as a candidate for the parking position recommended for the user to park. In addition, regarding the selection of the parking position, in addition to the movement of the vehicle to the parking position, the movement on foot after the vehicle is parked and the movement of the vehicle when leaving the parking position on the return trip are also considered, and a parking position that reduces the burden on the user is preferably selected.

[0078] In addition, a plurality of candidates may be selected as the parking position recommended for parking the vehicle. In addition, when a plurality of candidates for the parking position recommended for parking the vehicle are selected, the recommended path to each parking position is obtained as the planned travel path in the above S1, that is, a plurality of candidates for the planned travel path are obtained. Furthermore, even when only one recommended parking position is selected, a plurality of candidates for the planned travel path may be obtained when a plurality of recommended paths are considered for the parking position. In addition, when a plurality of candidates for the planned travel path are obtained in the above S1, in S25 described later, lane movement modes are compared among the plurality of planned travel paths, and a recommended lane movement mode is determined, thereby determining a parking position and a planned travel path.

[0079] In addition, the server device 4 refers to the connection information 18, which indicates the connection relationship between the lanes included in the road facing the entrance of the parking lot where the user parks (hereinafter referred to as the entry road) and the entrance of the parking lot, and when the direction of travel that can enter the parking lot from the entry road is limited (for example, only by turning left), the above-mentioned driving route search is performed in consideration of the entry direction. In addition, as a route search method, a search method other than the Dijkstra method may be used. In addition, the above-mentioned driving route search of S1 may be performed by the navigation device 1 instead of the server device 4.

[0080] Next, in S2 , the CPU 51 acquires the high-precision map information 16 for the area starting from the current position of the vehicle and including the planned travel route acquired in S1 .

[0081] Here, if Figure 5As shown, the high-precision map information 16 is divided into rectangular shapes (e.g., 500 m×1 km) and stored in the high-precision map DB 13 of the server device 4. Therefore, for example, Figure 5 As shown, when the path 61 is obtained as the driving path of the vehicle, the areas 62 to 65 including the path 61 are taken as objects to obtain the high-precision map information 16. However, when the distance to the destination is particularly long, for example, only the secondary grid of the current position of the vehicle may be taken as an object to obtain the high-precision map information 16, or only the area within a specified distance (for example, within 3 km) from the current position of the vehicle may be taken as an object to obtain the high-precision map information 16.

[0082] The high-precision map information 16 includes, for example, information about the lane shape of the road and the demarcation lines (lane center line, lane boundary line, lane outer line, guide line, etc.) drawn on the road. In addition, it also includes information related to intersections, information related to parking lots, etc. The high-precision map information 16 is basically obtained from the server device 4 in units of the above-mentioned rectangular-shaped areas, but when the high-precision map information 16 of the area already stored in the cache 46 exists, it is obtained from the cache 46. In addition, the high-precision map information 16 obtained from the server device 4 is temporarily stored in the cache 46.

[0083] In addition, in the above S2, CPU51 also obtains connection information 18 and road external shape information 19, wherein the connection information 18 represents the connection relationship between the lanes included in the entrance road of the entrance of the parking lot where the user parks and the entrance of the parking lot; the road external shape information 19 determines the area where the vehicle can pass between the entrance road and the entrance of the parking lot where the user parks.

[0084] Then, in S3, the CPU 51 executes a static driving trajectory generation process ( Figure 7 ). Here, the static driving trajectory generation process is a process of generating a driving trajectory, i.e., a static driving trajectory, for the roads included in the planned driving route based on the vehicle's planned driving route and the high-precision map information 16 acquired in the above S2. In particular, the CPU 51 generates a driving trajectory as a static driving trajectory that not only determines the lane for the recommended vehicle to travel, but also determines the specific driving position recommended to travel in the lane. In addition, when the distance to the destination is particularly far, a static driving trajectory may be generated only for the section from the current position of the vehicle along the direction of travel to a specified distance ahead (for example, within the secondary grid where the vehicle is currently located). In addition, although the specified distance can be appropriately changed, the static driving trajectory is generated for at least an area outside the range (detection range) in which the road conditions around the vehicle can be detected using the external camera 39 or other sensors.

[0085] Next, in S4, the CPU 51 generates a speed plan for the vehicle when traveling on the static driving trajectory generated in S3 based on the high-precision map information 16 acquired in S2. For example, the recommended driving speed of the vehicle when traveling on the static driving trajectory is calculated by taking into account the speed limit information and the speed change locations (such as intersections, curves, road crossings, crosswalks, etc.) on the planned driving path.

[0086] Then, the speed plan generated in S4 is stored as auxiliary information used in automatic driving assistance in the flash memory 54, etc. In addition, a plan indicating the acceleration and deceleration of the vehicle required to implement the speed plan generated in S4 may be generated as auxiliary information for automatic driving assistance.

[0087] Next, in S5, the CPU 51 processes the captured image captured by the vehicle exterior camera 39 as the surrounding road conditions, in particular, determines whether there are factors affecting the driving of the vehicle around the vehicle. Here, the "factors affecting the driving of the vehicle" as the determination object in the above S5 are set as dynamic factors that change in real time, and static factors such as those based on road structures are excluded. For example, it can be other vehicles driving or parked in front of the vehicle in the direction of travel, congested vehicles, pedestrians located in front of the vehicle in the direction of travel, and construction sections located in front of the vehicle in the direction of travel. On the other hand, intersections, curves, road crossings, merging sections, lane reduction sections, etc. are excluded. In addition, even if there are other vehicles, pedestrians, and construction sections, the situation that they cannot overlap with the future driving trajectory of the vehicle (for example, the situation where they are located far away from the future driving trajectory of the vehicle) is also excluded from the "factors affecting the driving of the vehicle". In addition, as a means for detecting factors that may affect the driving of the vehicle, sensors such as millimeter wave radars, laser sensors, vehicle-to-vehicle communication, and road-to-vehicle communication may be used instead of cameras.

[0088] Alternatively, for example, the real-time position of each vehicle traveling on roads throughout the country may be managed by an external server, and the CPU 51 may obtain the positions of other vehicles around the own vehicle from the external server to perform the determination process of S5 .

[0089] Then, if it is determined that there are factors that affect the driving of the vehicle around the vehicle (S5 is "Yes"), the process proceeds to S6. On the other hand, if it is determined that there are no factors that affect the driving of the vehicle around the vehicle (S5 is "No"), the process proceeds to S9.

[0090] In S6, the CPU 51 generates a new trajectory as a dynamic driving trajectory for avoiding or following the "factors that affect the driving of the vehicle" detected in S5 and returning to the static driving trajectory from the current position of the vehicle. In addition, the dynamic driving trajectory is generated for the interval containing the "factors that affect the driving of the vehicle". In addition, the length of the interval varies according to the content of the factor. For example, in the case where the "factors that affect the driving of the vehicle" are other vehicles (front vehicles) driving in front of the vehicle, such as Figure 6 As shown, a trajectory that changes lanes to the right and passes the front vehicle 66, then changes lanes to the left and returns to the original lane, that is, an avoidance trajectory, is generated as a dynamic driving trajectory 67. In addition, a trajectory that does not pass the front vehicle 66 but follows the front vehicle 66 at a predetermined distance behind (or runs parallel to the front vehicle 66), that is, a following trajectory, may be generated as a dynamic driving trajectory. Furthermore, a plurality of candidates may be generated as dynamic driving trajectories, in which case the candidate with the smallest cost in S7 described later is selected from the plurality of candidates.

[0091] by Figure 6 The calculation method of the dynamic driving trajectory 67 shown in the figure is used as an example to illustrate that the CPU 51 first calculates the first trajectory L1, which is the trajectory required for the steering device to start turning and move to the lane on the right, and the position of the steering device to return to the straight direction. In addition, the first trajectory L1 calculates the lateral acceleration (lateral G) generated when changing lanes based on the current vehicle speed of the vehicle, and uses a clothoid curve or an arc to calculate a trajectory that is as smooth as possible and shortens the distance required for lane change as much as possible, under the condition that the lateral G does not hinder the automatic driving assistance and does not exceed the upper limit value (for example, 0.2G) that does not cause discomfort to the occupants of the vehicle. In addition, it is also set as a condition to maintain an appropriate inter-vehicle distance N or more from the vehicle in front.

[0092] Next, a second trajectory L2 is calculated, which is a trajectory that travels in the right lane at the speed limit as the upper limit, overtakes the front vehicle 66, and maintains an appropriate inter-vehicle distance N or more from the front vehicle 66. In addition, the second trajectory L2 is a substantially straight trajectory, and the length of the trajectory is calculated based on the speed of the front vehicle 66 and the speed limit of the road.

[0093] Next, the third trajectory L3 is calculated, which is the trajectory required for the steering device to start turning and return to the left lane, and the position of the steering device to return to the straight direction. In addition, the third trajectory L3 calculates the lateral acceleration (lateral G) generated when changing lanes based on the current vehicle speed of the vehicle, and uses a clothoid curve or an arc to calculate a trajectory that is as smooth as possible and shortens the distance required for lane change as much as possible, under the condition that the lateral G does not hinder the automatic driving assistance and does not exceed the upper limit value (for example, 0.2G) that does not cause discomfort to the occupants of the vehicle. In addition, it is also set as a condition to maintain an appropriate inter-vehicle distance N or more from the vehicle in front 66.

[0094] In addition, since the dynamic driving trajectory is generated based on the road conditions around the vehicle acquired by the external camera 39 or other sensors, the area that becomes the object of generating the dynamic driving trajectory is at least within the range (detection range) in which the road conditions around the vehicle can be detected by the external camera 39 or other sensors.

[0095] Next, in S7, the CPU 51 reflects the dynamic driving trajectory newly generated in the above S6 to the static driving trajectory generated in the above S3. Specifically, from the current position of the vehicle to the end of the interval including the "factors affecting the driving of the vehicle", the costs of the static driving trajectory and the dynamic driving trajectory (the dynamic driving trajectory can also be a plurality of candidates) are calculated, and the driving trajectory with the lowest cost is selected. As a result, a part of the static driving trajectory is replaced with the dynamic driving trajectory as needed. In addition, there is a case where the dynamic driving trajectory is not replaced depending on the situation, that is, there is a case where even if the dynamic driving trajectory is reflected, it will not change from the static driving trajectory generated in the above S3. Furthermore, there is also a case where the dynamic driving trajectory and the static driving trajectory are the same trajectory, and even if they are replaced, they will not change from the static driving trajectory generated in the above S3.

[0096] Next, in S8, the CPU 51 corrects the speed plan of the vehicle generated in S4 based on the content of the reflected dynamic driving trajectory for the static driving trajectory after the dynamic driving trajectory is reflected in S7. In addition, if the result of reflecting the dynamic driving trajectory is that there is no change from the static driving trajectory generated in S3, the processing of S8 may be omitted.

[0097] Next, in S9, the CPU 51 calculates the control amount for causing the vehicle to travel in the static driving trajectory generated in S3 (the reflected trajectory in the case of reflecting the dynamic driving trajectory in S7) at a speed according to the speed plan generated in S4 (the corrected plan in the case of correcting the speed plan in S8). Specifically, the control amounts of the accelerator, brake, transmission, and steering are calculated respectively. In addition, the processing of S9 and S10 may be performed by the vehicle control ECU 40 that controls the vehicle instead of the navigation device 1.

[0098] Then, in S10, the CPU 51 reflects the control amount calculated in S9. Specifically, the calculated control amount is sent to the vehicle control ECU 40 via the CAN. In the vehicle control ECU 40, each vehicle control of the accelerator, brake, transmission and steering device is performed based on the received control amount. As a result, it is possible to perform driving assist control in which the vehicle travels at a speed according to the speed plan generated in S4 (the corrected plan in S8) on the static driving trajectory generated in S3 (the reflected trajectory in the case of reflecting the dynamic driving trajectory in S7).

[0099] Next, in S11, the CPU 51 determines whether the vehicle has traveled a certain distance since the static travel trajectory was generated in S3. For example, the certain distance is 1 km.

[0100] Furthermore, when it is determined that the vehicle has traveled a certain distance since the static driving trajectory was generated in the above S3 (S11 is "Yes"), the process returns to S2. Then, the static driving trajectory is generated again for the section within the specified distance from the current position of the vehicle along the scheduled driving route (S2 to S4). In addition, in the present embodiment, the static driving trajectory is repeatedly generated for the section within the specified distance from the current position of the vehicle along the driving route every time the vehicle travels a certain distance (for example, 1 km), but when the distance to the destination is short, the static driving trajectory to the destination may be generated only once at the start of driving.

[0101] On the other hand, if it is determined that the vehicle has not traveled a certain distance since the static driving trajectory was generated in S3 (S11 is "No"), it is determined whether to terminate the assisted driving based on the automatic driving assistance (S12). As a case where the assisted driving based on the automatic driving assistance is terminated, in addition to the case where the destination is reached, there is also a case where the user operates the operation panel provided in the vehicle, or intentionally terminates (overrides) the driving based on the automatic driving assistance by operating the steering wheel, operating the brake, etc.

[0102] Then, if it is determined that the assisted driving by the automatic driving assist is to be terminated (S12 is "Yes"), the automatic driving assist program is terminated. On the contrary, if it is determined that the assisted driving by the automatic driving assist is to be continued (S12 is "No"), the process returns to S5.

[0103] Next, based on Figure 7 The sub-process of the static driving trajectory generation process executed in the above-mentioned S3 will be described. Figure 7 This is a flowchart of a sub-processing procedure of a static driving trajectory generation process.

[0104] First, in S21, the CPU 51 obtains the current position of the vehicle detected by the current position detection unit 31. In addition, the current position of the vehicle is preferably determined in detail using, for example, high-precision GPS information or high-precision positioning technology. Here, high-precision positioning technology refers to a technology that can detect the driving lane and the high-precision vehicle position by using image recognition to detect white lines and road surface spraying information taken from a camera installed on the vehicle, and then matching the detected white lines and road surface spraying information with, for example, high-precision map information 16. Furthermore, in the case where the vehicle is traveling on a road consisting of multiple lanes, the lane in which the vehicle is traveling is also determined. In addition, when the vehicle is located in a parking lot, the specific position in the parking lot (such as the parking space where the vehicle is located, etc.) and the posture of the vehicle (such as the direction of travel of the vehicle, and in what direction it is parked relative to the parking space when located in the parking space) are also determined.

[0105] Next, in S22, the CPU 51 obtains lane shape, demarcation line information, information related to intersections, etc. based on the high-precision map information 16 obtained in the above S2, especially for the section of the static driving trajectory ahead of the vehicle's traveling direction (for example, the planned driving path within a specified distance from the current position of the vehicle). In addition, the lane shape and demarcation line information obtained in the above S22 particularly include information for determining how the lanes that can be selected as the vehicle driving object are configured relative to the road, and also include information for determining the number of lanes, the type and configuration of the demarcation lines dividing the lanes, the lane width, how to increase or decrease the number of lanes at which position, the traffic division of each lane in the traveling direction, the connection of roads (specifically, the correspondence between the lanes included in the road before passing the intersection and the lanes included in the road after passing the intersection), etc.

[0106] Next, in S23, the CPU 51 constructs a lane network based on the lane shape and the dividing line information acquired in S22 to generate a static driving track ahead of the vehicle's traveling direction. Here, the lane network is a network indicating the lanes that the vehicle can select to move.

[0107] Here, as an example of constructing the lane network in S23, for example, a vehicle Figure 8 The following description will take the case where the vehicle travels along the planned travel route shown as an example. Figure 8 The planned travel route shown is a route that goes straight from the current position of the vehicle, then turns right at the next intersection 71, then turns right at the next intersection 72, and then turns left at the next intersection 73. Figure 8 In the planned driving route shown, for example, when turning right at intersection 71, the vehicle can enter either the right lane or the left lane. However, since it is necessary to turn right at the next intersection 72, it is necessary to move to the rightmost lane when entering intersection 72. In addition, when turning right at intersection 72, the vehicle can enter either the right lane or the left lane. However, since it is necessary to turn left at the next intersection 73, it is necessary to move to the leftmost lane when entering intersection 73. Fig. 9 A lane network constructed with such a lane movement enabled as the target is shown.

[0108] like Fig. 9 As shown, the lane network divides the interval for generating the static driving trajectory in front of the vehicle's traveling direction into a plurality of zones (groups). Specifically, the entry position of the intersection, the exit position of the intersection, and the position where the lane is increased or decreased are used as the boundary division. In addition, a node (hereinafter referred to as a lane node) 75 is set for each lane located at the boundary of each divided zone. Furthermore, a road section (hereinafter referred to as a lane section) 76 connecting the lane nodes 75 is set. In addition, in the case of not crossing the lane, the lane section 76 is basically set for the center of the lane.

[0109] In addition, the lane network particularly includes information on the correspondence between the lanes included in the road before the intersection and the lanes included in the road after the intersection, that is, the lanes that can be moved after the intersection relative to the lanes before the intersection, determined by connecting the lane nodes of the intersection with the road segments. Specifically, it indicates that the vehicle can move between lanes corresponding to the lane nodes set on the road before the intersection and the lane nodes set on the road after the intersection, which are connected by the road segments. In order to generate such a lane network, in the high-precision map information 16, for each road connected to the intersection, lane signs indicating the correspondence between the lanes are set and stored according to each combination of the road entering the intersection and the road leaving the intersection. When constructing the lane network in the above S23, the CPU 51 forms the connection between the lane nodes at the intersection and the road segments with reference to the lane signs.

[0110] In addition, although Fig. 9 , an example of a lane network constructed with roads as the object is shown in FIG. 1 . However, if a parking lot is included in the interval for generating a static driving trajectory, a similar network is constructed with the parking lot as the object (hereinafter referred to as a parking lot network). The parking lot network consists of parking lot nodes and parking lot segments. The parking lot nodes are set at the entrance and exit of the parking lot, at the intersection where vehicle-accessible passages intersect, at the corners of vehicle-accessible passages (i.e., the connection points between passages), and at the end of the passage. On the other hand, parking lot segments are set for vehicle-accessible passages between parking lot nodes.

[0111] Furthermore, when a plurality of candidates for the planned driving routes are acquired in the above-mentioned S1, the above-mentioned lane network and parking lot network are constructed for the plurality of planned driving routes.

[0112] Next, in S24, for the lane network constructed in the above S23 (if a parking lot is included in the interval for generating the static driving trajectory, the network in the parking lot is also included, the same below), the CPU 51 sets the starting lane (departure node) where the vehicle starts to move for the lane node located at the starting point of the lane network, and sets the target lane (destination node) that becomes the target of the vehicle's movement for the lane node located at the end point of the lane network. In addition, in the case where the starting point of the lane network is a road with multiple lanes on one side, the lane node corresponding to the lane where the vehicle is currently located becomes the starting lane. On the other hand, in the case where the end point of the lane network is a road with multiple lanes on one side, the lane node corresponding to the leftmost lane (in the case of left-hand traffic) becomes the target lane. In addition, in the case where the starting point and the end point of the lane network are in the parking lot, the starting lane is set in the parking space or passage where the vehicle is currently located in the network in the parking lot, and the target lane is set in the parking space where the vehicle is parked or the passage that can enter the parking space.

[0113] Then, in S25, the CPU 51 refers to the lane network constructed in the above S23, and derives a route with the minimum lane cost (hereinafter referred to as a recommended route) within the route that is continuously connected from the starting lane to the target lane. For example, the route is searched from the target lane side using the Dijkstra method. However, if a route that is continuously connected from the starting lane to the target lane can be searched, a search method other than the Dijkstra method may be used. The derived recommended route becomes the recommended lane movement method of the vehicle when the vehicle moves (information that determines the recommended lane for driving and the recommended position for lane movement).

[0114] In addition, a lane cost used in the search for the above-mentioned route is assigned to each lane segment 76. The lane cost assigned to each lane segment 76 is based on the length of each lane segment 76 or the time required for movement. In particular, in the present embodiment, the length of the lane segment (in m) is set as the reference value of the lane cost. In addition, for lane segments accompanied by lane changes, a lane change cost (e.g., 50) is added to the above-mentioned reference value. In addition, regarding the lane change cost, the value can also be changed according to the number of lane changes and the location of the lane change. For example, in the case of a lane change near an intersection or a lane change between two lanes, the value of the added lane change cost can be made higher.

[0115] Furthermore, when a plurality of planned travel route candidates are acquired in the above S1, a recommended route with the minimum lane cost is derived from the plurality of planned travel routes. One planned travel route is also determined based on the derived recommended route.

[0116] Next, in S26, the CPU 51 performs a driving trajectory generation process for a curve section described later ( Fig.10 , Fig.11 ). The calculation process of the driving trajectory of the curve section is a process of generating a recommended driving trajectory when driving along the recommended route derived in the above S25, within the planned driving path of the object section for generating a static driving trajectory in front of the vehicle's traveling direction, especially taking the curve section including a curve as the object. In addition, when the planned driving path includes a plurality of curve sections, a recommended driving trajectory is generated for each of the plurality of curve sections. Here, "curve" includes shapes that are curved at a specified angle such as a right angle (for example, an L-shaped road) in addition to shapes in which the road is curved into an arc with a specified curvature. On the other hand, in the present embodiment, it is assumed that the vehicle travels in the same lane of the road and passes through the curve, so the curves in the intersections where the lanes are interrupted, the surrounding areas of toll booths, and the entrances and exits of parking lots are excluded from the curves in the above S26.

[0117] Then, in S27, the CPU 51 generates a driving trajectory recommended when driving along the recommended route derived in S25 above, except for the above-mentioned curved section. For example, for the driving trajectory of the section accompanied by lane change, the position of the lane change is set in such a way that the lane change is as discontinuous as possible and the lane change is performed at a position away from the intersection. In addition, in particular, when generating a driving trajectory when making a left or right turn or changing lanes at an intersection, the lateral acceleration (lateral G) generated in the vehicle is calculated, and the connected trajectory is calculated as smoothly as possible using a clothoid curve under the condition that the lateral G does not hinder the automatic driving assistance and does not exceed the upper limit value (for example, 0.2G) that does not cause discomfort to the occupants of the vehicle. By performing the above-mentioned processing, a driving trajectory recommended for vehicle driving is generated for the roads included in the planned driving path. In addition, for a zone that is neither a curved section, nor a zone for lane change, nor a zone within an intersection, a trajectory passing through the center of the lane is used as a driving trajectory recommended for vehicle driving. In addition, when the object of generating a static driving trajectory includes entering or leaving a parking space, a driving trajectory for entering or leaving a parking space is generated.

[0118] In S28, the CPU 51 generates a recommended driving trajectory, i.e., a static driving trajectory, for the roads included in the planned driving route by combining the driving trajectories calculated in the above S26 and the above S27. The static driving trajectory generated in the above S28 is stored in the flash memory 54 or the like as auxiliary information used in the automatic driving assistance. Then, the process is transferred to S4 to perform various driving assistance based on the generated static driving trajectory.

[0119] Next, based on Fig.10 The sub-process of the curve section travel trajectory calculation process executed in the above-mentioned S26 will be described. Fig.10 This is a flowchart of a sub-processing routine for the processing of calculating the driving trajectory in a curve section.

[0120] First, in S31, the CPU 51 obtains information for determining the driving area of ​​the vehicle based on the high-precision map information 16 obtained in S2 above, with the section for generating the static driving trajectory ahead of the vehicle's traveling direction as the object. Specifically, the CPU 51 obtains information for determining the positions of the left and right dividing lines (the road edges for a one-lane road or a road without lane division) of the lane in which the vehicle is traveling when the vehicle is traveling according to the lane movement method selected in S25 above.

[0121] Next, in S32, the CPU 51 calculates the center line of the lane in which the vehicle is traveling based on the information of the driving area acquired in S31 above, with the section of the static driving trajectory in front of the vehicle's traveling direction as the object. For example, the center line located at the center can be calculated based on the position of the left and right dividing lines or the edge of the road in the driving area. However, the center line can also be calculated in advance for each lane and stored in the high-precision map DB 13 instead of being calculated based on the dividing lines.

[0122] Next, in S33, the CPU 51 calculates the moving average line of the lane in which the vehicle is traveling based on the center line calculated in the above S32, with the interval of the static driving trajectory in front of the vehicle's traveling direction as the object. In addition, the moving average line is a line connecting the average locations of a specified number of continuous coordinate points configured along the center line of the lane. More specifically, for each coordinate point set at a specified interval along the center line, the average location of the five coordinate points including the two coordinate points before and after it (the location where the longitude and latitude are averaged respectively) is calculated, and the line connecting the average location is set as the moving average line. However, the moving average line can also be calculated in advance for each lane and stored in the high-precision map DB 13 instead of being calculated based on the center line.

[0123] Furthermore, in S34, the CPU 51 compares the center line calculated in S32 with the moving average line calculated in S33, and detects the range where the center line and the moving average line do not match as the range where the curve exists. Fig.12 81 and the moving average line 82 calculated in S31 and S32. As described above, the moving average line 82 is a line that connects the average locations (average locations of longitude and latitude) of five coordinate points including the two coordinate points before and after the center line 81 for each coordinate point set at a predetermined interval. Therefore, in the section where the center line 81 is arranged in a straight line, the center line 81 and the moving average line 82 are consistent, but if Fig.12 As shown, where the road curves in an arc or at a predetermined angle, there is a range where the center line 81 and the moving average line 82 do not match. Therefore, in the above S34, the range where the center line 81 and the moving average line 82 do not match is detected as a range where a curve exists.

[0124] In addition, in the above S34, the CPU 51 detects the curve located in the section of the static driving trajectory ahead of the traveling direction of the vehicle by comparing the center line 81 and the moving average line 82, but the curve can also be detected based on the map information. In this case, the map information contains information that predetermines the position of the curve (for example, information that determines the road section equivalent to the curve, and the coordinates of the starting point and end point of the curve).

[0125] Next, in S35 , the CPU 51 determines whether or not there is at least one curve in the section where the static travel trajectory ahead in the traveling direction of the vehicle is generated, based on the detection result of S34 .

[0126] Then, if it is determined that there is at least one curve in the section for generating the static driving trajectory ahead of the vehicle in the traveling direction (S35: "Yes"), the process moves to S36. On the other hand, if it is determined that there is no curve in the section for generating the static driving trajectory ahead of the vehicle in the traveling direction (S35: "No"), the process moves to S27 to generate a driving trajectory recommended when traveling along the recommended route derived in S25.

[0127] In S36, the CPU 51 determines whether there are at least two or more curves in succession at intervals within a predetermined distance (for example, 30 m) in the section generating the static driving trajectory ahead of the vehicle's traveling direction based on the detection result of S34. Fig.13 As shown, the range where the center line 81 and the moving average line 82 are inconsistent is more than two places, and the center line 81 and the moving average line 82 between them are consistent (in the case of inconsistency, it is regarded as one curve, not a plurality of continuous curves), and the distance between them is within a specified distance. For example, when there is a sharp turn or an S-shaped curve in the section of the static driving trajectory in the forward direction of the vehicle, it is determined as "yes".

[0128] Furthermore, if it is determined that at least two or more curves exist continuously at intervals within a predetermined distance in the section generating the static driving trajectory ahead of the vehicle in the traveling direction (S36: Yes), the process moves to S50. On the other hand, if it is determined that two or more curves do not exist continuously at intervals within a predetermined distance (S36: No), the process moves to S37.

[0129] In S37 and below, the following processing is performed to generate a recommended driving trajectory when driving in the curve section, taking the curve section including the discontinuous curves detected as described above as the object. In addition, when multiple discontinuous curves are detected, the following processing is performed to generate a driving trajectory, taking each curve section corresponding to all the detected curves as the object.

[0130] First, in S37, CPU51 obtains a start vector and an end vector, respectively, wherein the start vector determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the predetermined path according to the lane movement method selected in the above S25, and the end vector determines the position and orientation of the vehicle at the end point of the curve section.

[0131] The positions of the starting point and the end point of the curve section can be appropriately changed according to the lane movement mode selected in the above S25, or can be set under fixed conditions regardless of the lane movement mode. For example, the starting point of the curve section can be a predetermined distance (e.g., 20 m) before the starting point of the section where the center line 81 and the moving average line 82 are inconsistent, and the end point of the curve section can be a predetermined distance forward of the end point of the section where the center line 81 and the moving average line 82 are inconsistent. In addition, when the current position of the vehicle is before the curve, the current position of the vehicle sometimes becomes the starting point of the curve section. In addition, the information for determining the curve section (e.g., information for determining the road section included in the curve section, the coordinates of the starting point and the end point of the curve section) can also be included in the map information in advance together with the curve, and the curve section can be set based on the map information.

[0132] Here, the positions of the start vector and the end vector along the traveling direction of the road (positions in the front-rear direction) are set to positions corresponding to the start point and the end point of the curve section described above.

[0133] On the other hand, the positions of the start vector and the end vector in the road width direction are basically set to the center of the lane where the vehicle is traveling (for a one-lane road or a road without lane division, this also corresponds to the center of the road).

[0134] Furthermore, the directions of the start vector and the end vector are basically set to be parallel to the traveling direction of the road (the longitudinal direction of the road).

[0135] However, for example, in cases where a special vehicle operation such as a lane change or left or right turn is requested before a curve section, the position of the start vector and the end vector in the road width direction may be set to the left or right of the center of the lane, or the direction may be set to be inclined relative to the direction of travel of the road.

[0136] Fig.12 FIG. 8 is a diagram showing an example of a start vector 83 and an end vector 84 set for a curve section including a curve bent at a right angle. Fig.12 In the example shown, a start vector 83 is set at the center of the lane a predetermined distance before the start point of the section where the center line 81 and the moving average line 82 do not match, and an end vector 84 is set at the center of the lane a predetermined distance ahead of the end point of the section where the center line 81 and the moving average line 82 do not match. In addition, the directions of the start vector 83 and the end vector 84 are both parallel to the direction of travel of the road (the longitudinal direction of the road).

[0137] Then, in S38, the CPU 51 sets a clipping point (passing point) 85 between the moving average line calculated in S33 and the inner dividing line of the curve. Here, the clipping point 85 can be appropriately set between each coordinate point arranged along the center line 81 and the inner dividing line of the curve, more specifically, between the moving average line and the inner dividing line of the curve, for example, Fig.14 As shown in FIG. 8 , the point where the inner dividing line 86 of the curve is closest to the moving average line 82 is used as the cutting point 85. Fig.12 As shown, the moving average line 82 is usually closer to the inner dividing line of the curve than the center line 81. Therefore, if a clipping point 85 is set between the moving average line 82 and the inner dividing line of the curve, the clipping point 85 is located between each coordinate point arranged along the center line 81 and the inner dividing line of the curve. Fig.14 The example shown is a case where the vehicle width is regarded as 0. If the vehicle width is taken into consideration, the trimming point 85 is preferably set at a position that is 1 / 2 of the vehicle width offset toward the center line side relative to the closest point in the inner dividing line 86 to the moving average line 82. Alternatively, taking errors into consideration, the trimming point 85 is preferably set at a position that is 1 / 2+α (e.g. 30 cm) of the vehicle width offset toward the center line side.

[0138] Next, in S39, the CPU 51 generates a new candidate for the start vector at the start point of the curve section for generating the driving trajectory, in addition to the start vector obtained in S37. Furthermore, at the end point of the curve section, in addition to the end vector obtained in S37, a new candidate for the end vector is generated. For example, Fig.15 In the example shown, a new start vector 91 is generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve from the initial start vector 83, and a new start vector 92 is further generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve. Similarly, a new end vector 93 is generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve from the initial end vector 84, and a new end vector 94 is further generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve. In addition, Fig.15 In the example shown, two new candidates for the start vector and the end vector are generated, but only one or three or more may be generated. In addition, they may be generated in the inner direction of the curve. If more new candidates for the start vector and the end vector are generated, the possibility of generating a more appropriate driving trajectory becomes higher, but on the other hand, since there are more candidates for the driving trajectory, the processing load for calculating the driving trajectory becomes larger.

[0139] The subsequent processing of S40 to S46 is performed according to the combination of the start vector and the end vector obtained in S37 and newly generated in S38. Fig.15 In the example shown, since there are three start vectors and three end vectors, the processing of S40 to S46 is performed for all nine combinations of 3×3. Then, after the processing of S40 to S46 is performed for all combinations of start vectors and end vectors, the process moves to S47.

[0140] First, in S40 , the CPU 51 calculates an arc of maximum curvature radius passing through the start vector and the end vector to be processed in the direction of travel of each vector (ie, the tangent direction of the arc coincides with the direction of travel of each vector).

[0141] Then, in S41 , the CPU 51 determines whether the arc calculated in S40 is included in the lane in which the vehicle is traveling between the start vector and the end vector (in the traveling area acquired in S31 ).

[0142] Then, if it is determined that the arc calculated in S40 is included in the lane where the vehicle is traveling between the start vector and the end vector (within the driving area acquired in S31 above) (S41: "Yes"), the process proceeds to S42. On the other hand, if it is determined that the arc calculated in S40 is not included in the lane where the vehicle is traveling between the start vector and the end vector (within the driving area acquired in S31 above) (S41: "No"), the process proceeds to S43.

[0143] In S42, the CPU 51 generates the arc between the start vector and the end vector calculated in S40 as the first driving trajectory. Fig.16 The example shown is an example in which the arc 95 calculated in the above S40 is included in the vehicle driving lane located between the start vector 83 and the end vector 84 (within the driving area acquired in the above S31), and the arc 95 is generated as the first driving track. Then, the process shifts to S44.

[0144] On the other hand, in S43, since the arc calculated in S40 is a trajectory beyond the driving area and cannot be used, the CPU 51 generates a new arc passing through the clipping point 85 set in S38, and further generates a driving trajectory in which the start vector and the end vector of the processing object are straight along the traveling direction of the road and connected to the new arc as the first driving trajectory. For example, Fig.17The example shown is an example of a case where the arc 95 calculated in the above S40 is not included in the vehicle driving lane located between the start vector 83 and the end vector 84 (in the driving area acquired in the above S31), and a trajectory 96 passing through the clipping point 85 is generated as the first driving trajectory. In addition, regarding the arc of the trajectory 96, the condition is to reduce the curvature as much as possible, and the condition is that the trajectory 96 does not switch the steering direction (does not include multiple steering actions).

[0145] Then, in S44, the CPU 51 generates a second driving trajectory for moving from the start vector acquired in S37 to the first driving trajectory generated in S42 or S43. Fig.16 , Fig.17 As shown in FIG. 1 , when the starting vector to be processed is the starting vector acquired in the above S37, the second driving track becomes a part of the first driving track, so the processing of S44 is not necessary. Fig.18 As shown, when the starting vector to be processed is not the starting vector acquired in S37 (the starting vector newly added in S39), a second driving trajectory is generated. Fig.18 In the example shown, the first driving track 96 is generated with the new start vector 92 set to the left of the lane center as the processing target, and a new second driving track 97 is generated that moves from the original start vector 83 to the first driving track 96 .

[0146] Next, in S45, the CPU 51 generates a third driving trajectory for moving from the first driving trajectory generated in S42 or S43 to the end vector acquired in S37. Fig.16 , Fig.17 As shown in FIG. 1 , when the end vector to be processed is the end vector acquired in the above S37, the third driving track becomes a part of the first driving track, so the processing of S45 is not required. Fig.18 As shown, when the end vector to be processed is not the end vector acquired in the above S37 (the end vector newly added in S39), a third driving trajectory is generated. Fig.18 In the example shown, the first driving trajectory 96 is generated with the new end vector 94 set to the left of the lane center as a processing target, and a new third driving trajectory 98 is generated that moves from the first driving trajectory 96 to the original end vector 84 .

[0147] Here, the vehicle driving trajectory recommended when the vehicle moves to the right or left in the lane, such as the second driving trajectory or the third driving trajectory, includes a clothoid curve with continuously changing curvature, or more specifically, a trajectory connecting a plurality of clothoid curves of different shapes. Fig.19 is a diagram showing, for example, a recommended vehicle driving trajectory when moving to the right in a lane (in addition, a symmetrical driving trajectory when moving to the left). Fig.19 As shown, the recommended driving trajectory of the vehicle when moving to the right in the lane includes: a first clothoid curve 101, which gradually turns the steering device to the right direction from the starting point P1 of the movement (that is, the curvature gradually changes to a larger value) and proceeds to the first relay point P2; a second clothoid curve 102, which gradually returns the steering device to the straight direction from the first relay point P2 (that is, the curvature gradually changes to a smaller value) and proceeds to the middle point P3; a third clothoid curve 103, which gradually turns the steering device to the left direction from the middle point P3 (that is, the curvature gradually changes to a larger value) and proceeds to the second relay point P4; a fourth clothoid curve 104, which then gradually returns the steering device to the straight direction from the second relay point P4 (that is, the curvature gradually changes to a smaller value) and proceeds to the end point P5 of the movement. In addition, regarding the lateral movement width based on the clothoid curves 101 to 104, if it is the second driving trajectory, it is set to the distance overlapping with the first driving trajectory at the time P5, and if it is the third driving trajectory, it is set to the distance overlapping with the initial end vector 84 at the time P5. Then, the CPU 51 calculates each clothoid curve 101 to 104 to obtain a trajectory that satisfies the following conditions: the acceleration (lateral G) generated when moving in the lane does not exceed the upper limit value (for example, 0.2G) that does not cause discomfort to the occupants of the vehicle, and the clothoid curve is used as smoothly as possible and as short as possible The distance required for lane change. Then, by connecting the calculated clothoid curves 101 to 104, the above-mentioned second driving trajectory and third driving trajectory are calculated.

[0148] Then, in S46, the CPU 51 connects the first driving trajectory generated in S42 or S43, the second driving trajectory generated in S44 (only when the second driving trajectory is generated), and the third driving trajectory generated in S45 (only when the third driving trajectory is generated) as one driving trajectory. The driving trajectory generated in S46 is a "candidate for a recommended driving trajectory when driving in a curved section" generated for a combination of a start vector and an end vector of the processing object. For example, Fig.18 , an example of “candidates of driving trajectories recommended when traveling in a curve section” in which the first driving trajectory 96 , the second driving trajectory 97 , and the third driving trajectory 98 are connected is shown.

[0149] Similarly, for each combination of the start vector and the end vector obtained in the above S37 and newly generated in the above S38, a "candidate for the recommended driving trajectory when driving in the curve section" is generated, and after the "candidate for the recommended driving trajectory when driving in the curve section" is generated for all combinations of the start vector and the end vector, transfer to S47.

[0150] Then, in S47, the CPU 51 calculates the cost of the vehicle's travel for each candidate of the plurality of travel trajectories generated in S46 above, taking into account the vehicle's behavior during travel. The cost indicates suitability as a travel trajectory, and the smaller the cost, the higher the suitability as a travel trajectory. An example of the cost calculation method in S47 above is described below.

[0151] Specifically, the final cost is calculated for each candidate of the driving trajectory by adding up the costs calculated based on the following elements (1) to (3).

[0152] (1) Moving time (or distance): Moving time [s] × 1.0

[0153] (2) Maximum curvature: Maximum curvature × 0.1

[0154] (3) Number of times the steering direction of the steering device is switched: times × 5.0

[0155] First, regarding (1), the cost is determined by the travel time of the driving trajectory. Specifically, it can be seen that the longer the time required to travel along the driving trajectory, the higher the cost calculated, that is, it is difficult to select the driving trajectory as the recommended one. In addition, assuming that the vehicle speed when traveling in the curve section is constant, the travel time of the driving trajectory is also equivalent to the length of the travel distance.

[0156] In addition, for (2), the maximum curvature of the curve included in the driving trajectory is calculated. Then, the cost is calculated based on the calculated maximum curvature. Specifically, it can be seen that the larger the maximum curvature of the driving trajectory, the greater the load on the occupants when making a sharp turn while driving on the driving trajectory, so a higher cost is calculated, that is, it is difficult to select the driving trajectory as the recommended one.

[0157] In addition, regarding (3), the cost is determined based on the number of times the steering direction of the steering device included in the driving trajectory is switched. Specifically, it can be seen that the more times the steering direction of the steering device is switched, the higher the cost is calculated, that is, it is difficult to select the recommended driving trajectory.

[0158] In addition, in the above S47, when calculating the cost for the candidate of the driving trajectory, it is also possible to calculate the cost by considering only a part of the above elements (1) to (3) instead of all the above elements (1) to (3). For example, the total value of the costs of (1) and (2) may be calculated. In addition, it is also possible to calculate the cost using elements other than the above elements (1) to (3) (for example, the presence or absence of acceleration and deceleration, the amount of rotation of the steering device, etc.).

[0159] Then, in S48, the CPU 51 compares the costs calculated in S47 and selects a recommended driving trajectory for traveling in the curved section from the plurality of driving trajectory candidates generated in S46. Basically, the candidate for the driving trajectory with the smallest calculated cost is selected as the recommended driving trajectory. Then, the process moves to S27 and generates a driving trajectory recommended for traveling along the recommended route derived in S25 for sections other than the curved section.

[0160] On the other hand, in the above S36, when it is determined that at least two or more curves are continuously present at intervals within a predetermined distance in the section for generating the static driving track ahead in the traveling direction of the vehicle (S36: "Yes"), the following processing is used to generate a driving track recommended for driving in the curved section, with the curved section including the detected continuous curves as the object. In addition, when a plurality of sets of continuous curves are detected, the following processing is performed with each curved section corresponding to all the detected curves as the object to generate a driving track. Furthermore, when both continuous curves and discontinuous curves are detected, in addition to the above-mentioned processing after S37, the following processing after S50 is performed.

[0161] First, in S50, the CPU 51 divides the continuous curves at the midpoint. Fig. 20 , Fig.21 As shown, in the range where the center line 81 and the moving average line 82 are inconsistent, that is, when there are two ranges detected as curves in the above S34 at intervals of a specified distance (for example, 30m), the curve is divided at a point (hereinafter referred to as the middle point) located in the middle (equal distance) of each range. In addition, at the middle point of the division, the center line 81 and the moving average line 82 are consistent (in the case of inconsistency, they are not continuous multiple curves but are regarded as one curve). In addition, Fig. 20 , Fig.21 , a case where two curves are continuous is shown, but when three or more curves are continuous, the curves are divided at the midpoints of the respective curves.

[0162] Next, in S51, the CPU 51 compares the curve directions of the plurality of curves divided in S50 to determine whether the curve directions are the same direction. Fig. 20It shows the situation where the curves with different bending directions are continuous. Fig.21 The case where curves with the same bending direction are continuous is shown.

[0163] Then, when it is determined that the bending directions of the plurality of curves divided in the above S50 are different directions (S51: "No"), a connection point of the plurality of curves is set at the middle point on the center line of the predetermined lane where the vehicle is traveling (S52). It should be noted that the connection point can be set at any location as long as it is located in the predetermined lane where the vehicle is traveling and on a line segment in the road width direction at the middle point of the curve. In the present embodiment, the connection point is specifically set at a position recommended for connecting the driving trajectory of the vehicle when traveling on each curve. For example, Fig. 20 It shows the situation where the curves with different bending directions are continuous, such as Fig. 20 As shown, the connection point 105 is set at the middle point (the dividing point of the curve) and is located on the center line of the predetermined lane in which the vehicle travels.

[0164] On the other hand, when it is determined that the bending directions of the plurality of curves divided in the above S50 are the same direction (S51: "Yes"), a plurality of connection points of the curves are set at the middle point on the outside of the curves than the center line of the lane where the vehicle is scheduled to travel (S53). It should be noted that, similar to S52, the connection points are set at positions recommended for connecting the driving trajectories of the vehicle when traveling on each curve. For example, Fig.21 The case where the bending direction is the same and the curves are continuous is shown in FIG. Fig.21 As shown, the connection point 105 is set at the middle point (the dividing point of the curve) and is located on the outside of the curve relative to the center line of the lane in which the vehicle is traveling. In addition, the degree to which the position of the connection point 105 is offset to the outside of the curve relative to the center line can be appropriately set, for example, set to 1 / 3 or 1 / 4 of the lane width.

[0165] Next, in S54, CPU51 obtains a start vector and an end vector, respectively, wherein the start vector determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the predetermined path according to the lane movement method selected in the above S25, and the end vector determines the position and orientation of the vehicle at the end point of the curve section.

[0166] The positions of the starting point and the end point of the curve section can be appropriately changed according to the lane movement mode selected in the above S25, or can be set under fixed conditions regardless of the lane movement mode. For example, the starting point of the curve section can be a predetermined distance (for example, 20m) before the starting point of the section where the center line 81 and the moving average line 82 of the curve located closest to the front side of the continuous curve are inconsistent, and the end point of the curve section can be set as the point that is a predetermined distance forward to the travel direction side relative to the end point of the section where the center line 81 and the moving average line 82 of the curve located most in the travel direction side are inconsistent. In addition, when the current position of the vehicle is before the continuous curve, the current position of the vehicle sometimes becomes the starting point of the curve section. In addition, the information for determining the curve section (for example, information for determining the road section included in the curve section, the coordinates of the starting point and the end point of the curve section) can also be included in the map information in advance together with the curve, and the curve section can be set based on the map information.

[0167] Here, the positions of the start vector and the end vector along the traveling direction of the road (positions in the front-rear direction) are set to positions corresponding to the start point and the end point of the curve section.

[0168] On the other hand, the positions of the start vector and the end vector in the road width direction are basically set to the center of the lane where the vehicle is traveling (for a one-lane road or a road without lane division, this also corresponds to the center of the road).

[0169] Furthermore, the directions of the start vector and the end vector are basically set to be parallel to the traveling direction of the road (the longitudinal direction of the road).

[0170] However, for example, in cases where a special vehicle operation such as a lane change or left or right turn is requested before a curve section, the position of the start vector and the end vector in the road width direction may be set to the left or right of the center of the lane, or the direction may be set to be inclined relative to the direction of travel of the road.

[0171] Fig. 20 8 is a diagram showing an example of a start vector 83 and an end vector 84 set for a curve section in which two curves with different curve directions are continuous. Fig. 20 In the example shown, a start vector 83 is set at the center of the lane a predetermined distance before the start point of the section where the center line 81 of the first curve and the moving average line 82 do not match, and an end vector 84 is set at the center of the lane a predetermined distance forward in the traveling direction from the end point of the section where the center line 81 of the second curve and the moving average line 82 do not match. The directions of the start vector 83 and the end vector 84 are both parallel to the traveling direction of the road (the road length direction).

[0172] in addition, Fig.21 8 is a diagram showing an example of a start vector 83 and an end vector 84 set for a curve section in which two curves are continuous in the same curve direction. Fig.21 In the example shown, a start vector 83 is set at the center of the lane a predetermined distance before the start point of the section where the center line 81 of the first curve and the moving average line 82 do not match, and an end vector 84 is set at the center of the lane a predetermined distance forward in the traveling direction from the end point of the section where the center line 81 of the second curve and the moving average line 82 do not match. The directions of the start vector 83 and the end vector 84 are both parallel to the traveling direction of the road (the road length direction).

[0173] Then, in S55, the CPU 51 adds a new start vector and an end vector to the connection point 105 set in S52 or S53. Fig. 22 As shown in FIG. 1 , for a curve section with two curves of different curvature directions, for the first half of the curve section after division, Fig. 20 The position of the connection point 105 shown in FIG. 1 (i.e., the center of the lane at the middle point) is used to set a new end vector 106. For the second half of the curve section, Fig. 20 The position of the connection point 105 shown (i.e., the center of the lane at the middle point) sets a new starting vector 107. Fig.23 As shown in FIG. 1 , for a curve section with two curves in the same bending direction, for the first half of the curve section after division, Fig.21 The position of the connection point 105 shown in FIG. 1 (i.e., the middle point closer to the outside of the curve than the center of the lane) is set to a new end vector 106. For the second half of the curve section, Fig.21 A new starting vector 107 is set at the position of the connection point 105 shown (i.e., the middle point is closer to the outside of the curve than the center of the lane). Fig. 22 In order to facilitate understanding, the state where the first half and the second half of the curve section are divided and separated at the midpoint is shown. In addition, the directions of the new start vector 107 and the end vector 106 are both parallel to the direction of travel of the road (road length direction).

[0174] Next, in S56, the CPU 51 generates a new candidate for the start vector at the starting point of the curve section that is the object of generating the driving trajectory, in addition to the start vector obtained in the above S54. Furthermore, at the end point of the curve section, in addition to the end vector obtained by the above S54, a new candidate for the end vector is also generated. In detail, similar to S39, a new start vector 91 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve compared to the initial start vector 83, and a new start vector 92 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve (refer to Fig.15 ). Similarly, a new end vector 93 is generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve compared to the initial end vector 84, and a new end vector 94 is further generated at a location that is moved a predetermined distance (e.g., 1 / 4 or 1 / 6 of the lane width) toward the outside of the curve.

[0175] In addition, in the above S56, the CPU 51 also generates new candidates for the start vector and the end vector added to the connection point in the above S55. Fig.24 As shown, for a curve section with two consecutive curves in the same curving direction, the end vector 106 or the start vector 107 has been configured to be closer to the outside of the curve than the center of the lane. Therefore, compared with the initial end vector 106 or the start vector 107, new start vector and end vector candidates are generated in the inner direction of the curve. Specifically, a new end vector 108 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) in the inner direction of the curve compared to the initial end vector 106, and further, a new end vector 109 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) in the inner direction of the curve. Similarly, a new start vector 110 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) in the inner direction of the curve compared to the initial start vector 107, and further, a new start vector 111 is generated at a location that is moved a specified distance (e.g., 1 / 4 or 1 / 6 of the lane width) in the inner direction of the curve. In addition, in Fig.24 In the example shown, two new candidates for the start vector and the end vector are generated, but only one or three or more may be generated. In addition, it is also possible to generate them toward the outer side of the curve. If more new candidates for the start vector and the end vector are generated, the possibility of generating a more appropriate driving trajectory becomes higher, but on the other hand, since there are more candidates for the driving trajectory, the processing load of calculating the driving trajectory becomes larger.

[0176] The subsequent processing of S57 to S63 is performed for each curve section divided in S50 and for each combination of the start vector and the end vector located at the start point and the end point of the divided curve section. Fig. 22 , Fig.23 In the example shown, the curve section is divided into two, and there are three start vectors and three end vectors located at the connection points in the first half of the curve section, and there are three start vectors and three end vectors located at the connection points in the second half of the curve section. Therefore, the processing of S57 to S63 is performed for all 27 combinations of 3×3×3. Then, after the processing of S57 to S63 is performed for all the divided curve sections and combinations of start vectors and end vectors, the process moves to S64.

[0177] First, in S57 , the CPU 51 calculates an arc of maximum curvature radius passing through the start vector and the end vector of the divided curve section to be processed in the traveling direction of each vector (ie, the tangent direction of the arc coincides with the traveling direction of each vector).

[0178] Then, in S58 , the CPU 51 determines whether the arc calculated in S57 is included in the lane in which the vehicle is traveling between the start vector and the end vector (in the traveling area acquired in S31 ).

[0179] Then, if it is determined that the arc calculated in S57 is included in the lane where the vehicle is traveling between the start vector and the end vector (within the driving area acquired in S31) (S58: "Yes"), the process moves to S59. On the other hand, if it is determined that the arc calculated in S57 is not included in the lane where the vehicle is traveling between the start vector and the end vector (within the driving area acquired in S31) (S58: "No"), the process moves to S60.

[0180] In S59, the CPU 51 generates the arc between the start vector and the end vector calculated in S57 as the first driving trajectory. Fig.16 ) is the same, so it is omitted. Then, transfer to S61.

[0181] On the other hand, in S60, since the arc calculated in S57 is a trajectory beyond the driving area and cannot be used, the CPU 51 generates a new arc passing through the clipping point, and further generates a driving trajectory connected to the new arc in the direction of travel of the road at the start vector and the end vector of the processing object, as the first driving trajectory. Fig.17 ) is the same, so it is omitted. In addition, the method of setting the clipping point is the same as S38. Then, transfer to S61.

[0182] In S61, the CPU 51 generates a second driving track for moving from the start vector obtained in S54 or S55 to the first driving track generated in S59 or S60. In addition, when the start vector to be processed is the start vector obtained in S54 or S55, the second driving track becomes a part of the first driving track, so the processing of S61 is not required. Fig.18 ) is the same, so it is omitted.

[0183] Next, in S62, the CPU 51 generates a third driving track for moving from the first driving track generated in S59 or S60 to the end vector obtained in S54 or S55. In addition, when the end vector to be processed is the end vector obtained in S54 or S55, the third driving track becomes a part of the first driving track, so the processing of S62 is not required. Fig.18 ) is the same, so it is omitted.

[0184] Then, in S63, the CPU 51 connects the first driving track generated in S59 or S60, the second driving track generated in S61 (only when the second driving track is generated), and the third driving track generated in S62 (only when the third driving track is generated) as one driving track. The driving track generated in S63 is a "candidate of a driving track recommended when driving in the divided curve section" generated by combining the start vector and the end vector of the divided curve section of the processing object.

[0185] Similarly, for each curve section divided in the above S50 and for each combination of the start vector and the end vector located at the starting point and the end point of the divided curve section, a "candidate for the recommended driving trajectory when traveling in the divided curve section" is generated. After generating "candidates for the recommended driving trajectory when traveling in the divided curve section" for all the divided curve sections and the combination of the start vector and the end vector, transfer to S64.

[0186] In S64, the CPU 51 combines and connects all the patterns that can be combined, including the candidates for the recommended driving trajectory when driving the first half of the curve section from the starting point of the curve section to the connection point (hereinafter referred to as the first half driving trajectory candidates) and the candidates for the recommended driving trajectory when driving the second half of the curve section from the connection point to the end point of the curve section (hereinafter referred to as the second half driving trajectory candidates), to generate the "candidates for the recommended driving trajectory when driving the curve section including continuous curves". However, the object of connection is a combination in which the end vector of the first half driving trajectory candidate and the start vector of the second half driving trajectory candidate are consistent, that is, a combination in which the trajectories are connected at the connection point. For example, if a curve section is divided into two, and there are three start vectors and three end vectors at the connection point in the first half of the curve section, and there are three start vectors and three end vectors at the connection point in the second half of the curve section, in this case, there are 27 combinations of 3×3×3, and a total of 27 "candidates of driving trajectories recommended when driving in a curve section including continuous curves" are generated. In addition, in the case where the curve section is divided into three or more, the candidates for driving trajectories recommended in each curve section are combined and connected at the connection point.

[0187] Furthermore, in the above S64, the CPU 51 smoothes the driving trajectory before comparing the costs in S65 and S66 described later, if the generated "candidates of the driving trajectory recommended when driving in a curve section including continuous curves" can be smoothed. Specifically, Fig.25 As shown, in particular, in the case where the curvature directions of a plurality of consecutive curves are different, that is, as a result of combining the first half driving trajectory candidate 115 and the second half driving trajectory candidate 116, in the case where the driving trajectory near the connection point 105 connecting the trajectory candidates is a repeated lateral movement and straight driving, in particular, the driving trajectory is smoothed by correcting the section before and after the connection point 105 so as not to include the section of straight driving along the center line 81 of the lane. That is, for the vehicle composed of Fig.25 The dotted line encloses the trajectory of "straight → lateral movement → straight → lateral movement → straight". By eliminating the central straight part, Fig.18 The clothoid curve of lateral movement shown connects the straight line portions at both ends to correct the vehicle to “straight travel → lateral movement → straight travel.” As a result, the vehicle can be corrected to a travel trajectory with a reduced maximum curvature and a reduced number of switching times of the steering direction of the steering device.

[0188] Then, in S65, the CPU 51 calculates the cost of the vehicle's travel for each candidate of the plurality of travel trajectories generated in S64 and modified as needed, taking into account the vehicle's behavior during travel. The cost indicates suitability as a travel trajectory, and the smaller the cost, the higher the suitability as a travel trajectory. In detail, similar to S47, the final cost is calculated for each candidate of the travel trajectory by adding the costs calculated based on the various elements (1) to (3).

[0189] Then, in S66, the CPU 51 compares the costs calculated in S65, and selects a recommended driving trajectory when traveling in a curve section including continuous curves from the candidates of the plurality of driving trajectories generated in S64. Basically, the candidate of the driving trajectory with the smallest calculated cost is selected as the recommended driving trajectory. Then, the process moves to S27, and for sections other than the curve section, a recommended driving trajectory is generated when traveling along the recommended route derived in S25.

[0190] As described in detail above, in the navigation device 1 of the present embodiment and the computer program executed by the navigation device 1, a planned driving path for a vehicle is obtained (S1); in particular, when the acquired planned driving path includes a plurality of continuous curves, connection points of a plurality of curves are set with respect to a curve section including the plurality of curves (S52, S53); a start vector and an end vector are respectively obtained, wherein the start vector determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the planned driving path, and the end vector determines the position and orientation of the vehicle at the end point of the curve section when traveling along the planned driving path (S54); a driving trajectory for the recommended vehicle travel is generated with respect to the curve section as the object, by combining the first half driving trajectory from the start vector to the connection point and the second half driving trajectory from the connection point to the end vector (S57~S66); and driving assistance for the vehicle is performed based on the generated driving trajectory (S9, S10). Therefore, a driving trajectory that suppresses sharp turns or deceleration when traveling in a curve section including a plurality of consecutive curves can be generated as a recommended driving trajectory for the vehicle. As a result, appropriate driving assistance can be implemented without placing a burden on the vehicle occupants.

[0191] In addition, using map information including information related to dividing lines, taking a curve section including a plurality of curves as an object, recommended locations for connecting the driving trajectory of a vehicle traveling on each curve are set between the plurality of curves as connection points. Therefore, based on the map information, a driving trajectory that suppresses sharp turns or deceleration when traveling on a curve section including a plurality of continuous curves can be generated as a recommended driving trajectory for the vehicle.

[0192] Furthermore, since the connection points are set based on the bending directions of a plurality of curves, the connection points can be set at appropriate positions based on the bending directions of the continuous curves.

[0193] In addition, when the bending directions of multiple curves are in the same direction, the connection point is set at the outside of the curve rather than the center line of the predetermined lane in which the vehicle is traveling (S53). Therefore, for a curve section in which multiple curves are continuous and have the same bending direction, the connection point can be set at an appropriate position.

[0194] In addition, when the bending directions of multiple curves are different, the connection point is set on the center line of the predetermined lane where the vehicle is traveling (S52). Therefore, for a curve section where multiple curves with different bending directions are continuous, the connection point can be set at an appropriate position.

[0195] In addition, a cost is calculated for a combination of a plurality of candidates for the first half of the driving trajectory and a plurality of candidates for the second half of the driving trajectory (S65), the calculated costs are compared, and then a combination of driving trajectories recommended for vehicle driving is selected and generated from the combination of a plurality of candidates for the first half of the driving trajectory and a plurality of candidates for the second half of the driving trajectory (S66). Therefore, by comparing the costs, a driving trajectory that is most recommended for vehicle driving can be appropriately selected from the combination of a plurality of candidates for the driving trajectory.

[0196] In addition, for a combination of a plurality of candidates for the first half of the driving trajectory and a plurality of candidates for the second half of the driving trajectory, a lower cost is calculated for a driving trajectory with a smaller curvature or a shorter moving time (S65). Therefore, taking into account the vehicle behavior during driving, a combination of candidates for driving trajectories that impose a smaller burden on the vehicle can be selected as the most recommended driving trajectory for the vehicle.

[0197] In addition, when the bending directions of multiple curves are in different directions, the driving trajectory that combines the first half of the driving trajectory and the second half of the driving trajectory is corrected so that it does not include the section of straight driving along the center line of the lane before and after the connection point (S64). Therefore, the maximum curvature can be reduced, the number of times the steering device is switched in direction can be reduced, and the driving trajectory can be corrected to the recommended one.

[0198] In addition, the present invention is not limited to the above-mentioned embodiment, and various improvements and modifications can be made without departing from the scope of the present invention.

[0199] For example, in this embodiment, if Fig.12 , Fig.13As shown, for roads without branches and lane additions and subtractions, a recommended driving trajectory is generated for a curved road with a predetermined curvature or a curved road with a predetermined angle, but as long as the vehicle is traveling in the same lane of the road and passes through the curve, there may be branches or lanes that increase or decrease in the middle. In addition, for roads without lane divisions (no dividing lines), a driving trajectory can also be generated by treating the entire road as a lane for the vehicle to travel.

[0200] In addition, in the present embodiment, the center line 81 and the moving average line 82 are determined based on the map information, and the existence of the curve is determined by comparing the center line 81 and the moving average line 82 (S34), but the existence of the curve may be determined by, for example, performing image recognition processing on the image captured by the camera outside the vehicle. Furthermore, the connection point 105 set in the curve section including a plurality of continuous curves may be determined by using the image captured by the camera outside the vehicle instead of the map information, and the middle point of the plurality of curves may be set.

[0201] In the present embodiment, the center line 81 is set to be the center line of the lane on which the vehicle is traveling, but in the case of a one-lane road or a road without lane division, it may be the center line of the road.

[0202] In addition, in the present embodiment, when generating a driving trajectory for a curve section with a plurality of continuous curves, the curve section is divided at the midpoint of each curve (S50), but the division does not necessarily need to be at the midpoint as long as it is between curves. The division position may also be changed according to the shape of each curve.

[0203] In addition, in the present embodiment, a driving trajectory for a curved section is generated using a plurality of modes that the vehicle can obtain, and the costs of each generated driving trajectory are compared to determine a final recommended driving trajectory. However, a driving trajectory for a curved section may be generated using only the most recommended mode based on consideration of the shape of the lane in which the vehicle is traveling, etc.

[0204] In addition, in the present embodiment, after the driving trajectory is generated, the vehicle control for driving according to the generated driving trajectory is performed (S9, S10), but the vehicle control processing after S9 may be omitted. For example, the navigation device 1 may be a device that guides the user to a recommended driving trajectory instead of controlling the vehicle based on the driving trajectory.

[0205] In addition, in this embodiment, high-precision map information 16 or facility information 17 is used to generate a lane network and a parking lot network (S23), but each network targeting roads and parking lots across the country can also be stored in the DB in advance and read from the DB as needed.

[0206] In addition, in the present embodiment, the high-precision map information possessed by the server device 4 includes both information related to the lane shape of the road (the road shape, curvature, lane width, etc. in units of lanes) and the demarcation lines drawn on the road (lane center line, lane boundary line, lane outer line, guide line, etc.), but it may include only information related to the demarcation lines, or only information related to the lane shape of the road. For example, even in the case where only information related to the demarcation lines is included, information equivalent to information related to the lane shape of the road can be inferred based on the information related to the demarcation lines. In addition, even in the case where only information related to the lane shape of the road is included, information equivalent to information related to the demarcation lines can be inferred based on the information related to the lane shape of the road. In addition, "information related to demarcation lines" can be information for determining the type and configuration of the demarcation lines themselves used to demarcate lanes, information for determining whether lane changes can be made between adjacent lanes, or information for directly or indirectly determining the shape of the lane.

[0207] In the present embodiment, as a method of reflecting the dynamic driving trajectory on the static driving trajectory, a part of the static driving trajectory is replaced with the dynamic driving trajectory ( S7 ). However, the trajectory may be corrected so that the static driving trajectory approaches the dynamic driving trajectory without replacement.

[0208] In addition, in the present embodiment, as an automatic driving assistance for automatically driving without relying on the user's driving operation, all operations related to the behavior of the vehicle among the operations of the vehicle control ECU 40 controlling the vehicle, i.e., the accelerator operation, the brake operation, and the steering wheel operation are described. However, the automatic driving assistance may also be at least one operation related to the behavior of the vehicle among the operations of the vehicle control ECU 40 controlling the vehicle, i.e., the accelerator operation, the brake operation, and the steering wheel operation. On the other hand, manual driving based on the user's driving operation means that the user performs all operations related to the behavior of the vehicle among the operations of the vehicle, i.e., the accelerator operation, the brake operation, and the steering wheel operation.

[0209] In addition, the driving assistance of the present invention is not limited to the automatic driving assistance involved in the automatic driving of the vehicle. For example, the static driving trajectory generated in the above S3 and the dynamic driving trajectory generated in the above S6 can be displayed on the navigation screen, and guidance (such as guidance on lane changes, guidance on recommended vehicle speeds, etc.) can be provided to provide driving assistance. In addition, the user's driving operation can be assisted by displaying the static driving trajectory and the dynamic driving trajectory on the navigation screen.

[0210] In addition, in this embodiment, although the automatic driving assistance program ( Figure 4 ) is executed by the navigation device 1, but can also be executed by a vehicle-mounted device other than the navigation device 1 or the vehicle control ECU 40. In this case, the vehicle-mounted device or the vehicle control ECU 40 obtains the current position of the vehicle, map information, etc. from the navigation device 1 or the server device 4. In addition, the server device 4 can also execute the automatic driving assistance program ( Figure 4 ) steps part or all. In this case, the server device 4 is equivalent to the driving assistance device of the present application.

[0211] In addition, in addition to navigation devices, the present invention can also be applied to mobile phones, smart phones, tablet terminals, personal computers, etc. (hereinafter referred to as mobile terminals, etc.). In addition, it can also be applied to a system composed of a server and a mobile terminal, etc. In this case, the above-mentioned automatic driving assistance program (refer to Figure 4 ) can also be implemented by any one of the server and the mobile terminal. However, when the present invention is applied to a mobile terminal, it is necessary to connect the vehicle capable of performing automatic driving assistance to the mobile terminal in a communicative manner (whether wired or wireless).

[0212] Description of Reference Numerals

[0213] 1…Navigation device (driving assistance device), 2…Driving assistance system, 3…Information distribution center, 4…Server device, 5…Vehicle, 16…High-precision map information, 33…Navigation ECU, 40…Vehicle control ECU, 51…CPU, 81…Center line, 82…Moving average line, 83…Start vector, 84…End vector, 85…Cut point (through point), 96…First driving trajectory, 97…Second driving trajectory, 98…Third driving trajectory, 105…Connection point, 115…First half driving trajectory candidate, 116…Second half driving trajectory candidate.

Claims

1. A driving assistance device, wherein: have: A planned driving path acquisition unit, which acquires a planned driving path for the vehicle; a connection point setting unit, which sets connection points of a plurality of the curves for a curve section including the plurality of the curves when the planned driving route includes a plurality of continuous curves; a start vector acquisition unit, which acquires a start vector, wherein the start vector determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the predetermined driving path; an end vector acquisition unit, which acquires an end vector, wherein the end vector determines the position and orientation of the vehicle at the end point of the curve section when traveling along the predetermined driving path; a driving trajectory generating unit, which generates a driving trajectory for recommended vehicle driving by combining a first half driving trajectory from the start vector to the connection point and a second half driving trajectory from the connection point to the end vector, taking the curve section as an object; as well as The driving assistance unit performs driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation unit.

2. The driving assistance device according to claim 1, wherein: The connection point setting unit uses map information including information related to the dividing lines, targets a curve section including a plurality of the curves, and sets recommended locations between the plurality of curves for connecting the driving tracks of the vehicle traveling on each curve as the connection points.

3. The driving assistance device according to claim 2, wherein: The connection point setting unit sets the connection points based on the bending directions of the plurality of curves.

4. The driving assistance device according to claim 3, wherein: When the curvature directions of the plurality of curves are the same direction, the connection point setting unit sets the connection point on the outside of the curves relative to a center line of a lane in which the vehicle is scheduled to travel.

5. The driving assistance device according to claim 3, wherein: When the plurality of curves have different bending directions, the connection point setting unit sets the connection point on a center line of a predetermined lane in which the vehicle travels.

6. The driving assistance device according to any one of claims 1 to 5, wherein: The driving trajectory generation unit calculates a cost for a combination of a plurality of first-half driving trajectory candidates and a plurality of second-half driving trajectory candidates. The driving trajectory generation unit compares the calculated costs and selects and generates a combination of driving trajectories for recommending vehicle driving from a combination of a plurality of first-half driving trajectory candidates and a plurality of second-half driving trajectory candidates.

7. The driving assistance device according to claim 6, wherein: The driving trajectory generation unit calculates a lower cost for a combination of a plurality of first-half driving trajectory candidates and a plurality of second-half driving trajectory candidates, for a combination of driving trajectories with a smaller curvature or a combination of driving trajectories with a shorter travel time.

8. The driving assistance device according to claim 5, wherein: The invention also comprises a driving trajectory correction unit, which, when the bending directions of the plurality of curves are different, corrects the driving trajectory combining the first half driving trajectory and the second half driving trajectory so as not to include a section of straight driving along the center line of the lane before and after the connection point.

9. A computer program, wherein: Make the computer function as the following unit: A planned driving path acquisition unit, which acquires a planned driving path for the vehicle; a connection point setting unit, which sets connection points of a plurality of the curves for a curve section including the plurality of the curves when the planned driving route includes a plurality of continuous curves; a start vector acquisition unit, which acquires a start vector, wherein the start vector determines the position and orientation of the vehicle at the starting point of the curve section when traveling along the predetermined driving path; an end vector acquisition unit, which acquires an end vector, wherein the end vector determines the position and orientation of the vehicle at the end point of the curve section when traveling along the predetermined driving path; a driving trajectory generating unit, which generates a driving trajectory for recommended vehicle driving by combining a first half driving trajectory from the start vector to the connection point and a second half driving trajectory from the connection point to the end vector, taking the curve section as an object; as well as The driving assistance unit performs driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation unit.

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