JP2024078764A - Driving assistance device and computer program - Google Patents

Abstract

[Problem] To provide a driving assistance device and computer program that make it possible to implement appropriate driving assistance that does not place a burden on vehicle occupants. [Solution] A turning section in which the vehicle travels while turning when traveling along a planned travel route is acquired, and based on the lane shape in which the vehicle travels in the turning section and regulation information, either a first driving trajectory candidate consisting of a trajectory in which the traveling position and direction of the traveling vehicle are continuous, or a second driving trajectory candidate consisting of a trajectory in which direction changes are continuous in addition to the traveling position and direction of the traveling vehicle, is generated as a recommended driving trajectory for the vehicle in the turning section, and driving assistance for the vehicle is performed based on the generated driving trajectory. [Selected Figure] Figure 20

Description

The present invention relates to a driving assistance device and a computer program that assists in driving a vehicle in a parking lot.

In recent years, in addition to manual driving, in which the vehicle is driven based on the user's driving operations, new autonomous driving assistance systems have been proposed that assist the user in driving the vehicle by having the vehicle perform some or all of the user's driving operations. In autonomous driving assistance systems, for example, the current position of the vehicle, the lane the vehicle is traveling in, and the positions of other vehicles in the vicinity are detected at any time, and the vehicle's steering, drive source, brakes, etc. are automatically controlled so that the vehicle travels along a preset route.

In addition, when driving with the above-mentioned automated driving assistance or when providing various driving assistance to other vehicles, a recommended driving trajectory is generated in advance on the road on which the vehicle is traveling based on the planned driving route of the vehicle and map information, etc. For example, International Publication No. 2021/059601 discloses a technology for generating a driving trajectory recommended for driving in the center of the lane on which the vehicle is traveling except within intersections and sections where lane changes are made, and controlling the vehicle to drive according to the generated driving trajectory.

International Publication No. 2021/059601 (paragraph 0081)

Here, the technology disclosed in the above Patent Document 1 generates a driving trajectory that is basically recommended to be driven in the center of the lane in which the vehicle is driving (the roadway in a parking lot) except for some sections such as within intersections. Therefore, a driving trajectory that is recommended to be driven in the center of the lane in which the vehicle is driving is generated even when driving on a curved road section or in a section in a parking lot where the vehicle is driving while turning, such as moving the road to park in a parking space (hereinafter referred to as a turning section). However, in such a turning section, a trajectory that runs in the center of the lane is not necessarily the driving trajectory recommended for the vehicle, and there is a possibility that the trajectory may involve, for example, a sharp turn or deceleration.

The present invention has been made to solve the above-mentioned problems in the conventional technology, and aims to provide a driving assistance device and computer program that can select a more appropriate driving trajectory from among multiple candidates that suppresses sudden turns and deceleration when traveling through a turning section, and generate the recommended driving trajectory for the vehicle, thereby enabling appropriate driving assistance to be implemented without imposing a burden on the vehicle occupants.

In order to achieve the above-mentioned object, a first driving assistance device according to the present invention has a planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel, a turning driving section acquisition means for acquiring a turning section along which the vehicle will travel while turning when traveling according to the planned driving route, a driving trajectory generation means for generating a driving trajectory along which the vehicle is recommended to travel in the turning section based on the lane shape along which the vehicle travels in the turning section and regulation information, and a driving assistance means for assisting the driving of the vehicle based on the driving trajectory generated by the driving trajectory generation means, and the driving trajectory generation means generates, as a driving trajectory along which the vehicle is recommended to travel, either a first driving trajectory candidate consisting of a trajectory along which the driving position and direction of the traveling vehicle are continuous, or a second driving trajectory candidate consisting of a trajectory along which directional changes are continuous in addition to the driving position and direction of the traveling vehicle, based on the lane shape along which the vehicle travels in the turning section and regulation information.
Note that the "turning section where the vehicle travels while turning" includes, for example, a section where the road turns in an arc shape with a specified curvature (including shapes where the road curvature changes), as well as a section where the road bends at a specified angle such as a right angle, and a section of an intersection (branch) where the vehicle must turn right or left. Furthermore, it also includes sections where the vehicle travels while turning not only on public roads but also within facilities such as parking lots, sections where the vehicle travels while turning in order to enter or exit a parking space, and sections where the vehicle travels while turning in order to enter a facility from a public road or enter a facility from a facility onto a public road.
In addition, the "shape of the lane on which the vehicle travels" refers to the shape of the area on the road on which the vehicle can travel, in the case of a road without lane divisions, or the shape of the roadway (passageway for vehicles) in the case of a parking lot.
In addition, "regulation information" includes information regarding the existence of things that regulate vehicle travel (more specifically, require vehicles to stop or slow down), such as speed limits set for roads or lanes, traffic lights, crosswalks, railroad crossings, and stop road signs.

The second driving assistance device according to the present invention includes a planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel, a turning driving section acquisition means for acquiring a turning section along which the vehicle will travel while turning when traveling along the planned driving route, a driving trajectory generation means for generating a driving trajectory along which the vehicle is recommended to travel in the turning section based on the lane shape along which the vehicle travels in the turning section and regulation information, and a driving assistance means for providing driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation means, and the driving trajectory generation means generates a first driving trajectory candidate consisting of a trajectory along which the driving position and direction of the traveling vehicle are continuous, and a second driving trajectory candidate consisting of a trajectory along which the direction changes in addition to the driving position and direction of the traveling vehicle are continuous, and selects one of the driving trajectories as the driving trajectory along which the vehicle is recommended to travel based on the lane shape along which the vehicle travels in the turning section and regulation information.

The first computer program according to the present invention is a program for generating support information used for driving support implemented in a vehicle. Specifically, the computer program is for making a computer function as a planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel, a turning driving section acquisition means for acquiring a turning section along which the vehicle will travel while turning when traveling along the planned driving route, a driving trajectory generation means for generating a driving trajectory along which the vehicle is recommended to travel in the turning section based on the lane shape along which the vehicle travels in the turning section and regulation information, and a driving support means for providing driving support for the vehicle based on the driving trajectory generated by the driving trajectory generation means, and the driving trajectory generation means generates, as a driving trajectory along which the vehicle is recommended to travel, either a first driving trajectory candidate consisting of a trajectory along which the driving position and direction of the traveling vehicle are continuous, or a second driving trajectory candidate consisting of a trajectory along which the direction change is continuous in addition to the driving position and direction of the traveling vehicle, based on the lane shape along which the vehicle travels in the turning section and regulation information.

The second computer program according to the present invention is a program for generating support information used for driving support implemented in a vehicle. Specifically, the computer program is for making a computer function as a planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel, a turning driving section acquisition means for acquiring a turning section along which the vehicle will travel while turning when traveling along the planned driving route, a driving trajectory generation means for generating a driving trajectory along which the vehicle is recommended to travel in the turning section based on the lane shape along which the vehicle travels in the turning section and regulation information, and a driving support means for providing driving support for the vehicle based on the driving trajectory generated by the driving trajectory generation means, in which the driving trajectory generation means generates a first driving trajectory candidate consisting of a trajectory along which the driving position and direction of the traveling vehicle are continuous, and a second driving trajectory candidate consisting of a trajectory along which the direction change is continuous in addition to the driving position and direction of the traveling vehicle, and selects one of the driving trajectories as the driving trajectory along which the vehicle is recommended to travel based on the lane shape along which the vehicle travels in the turning section and regulation information.

According to the first driving assistance device and computer program of the present invention having the above configuration, by taking into consideration the lane shape and regulation information on which the vehicle is traveling, it is possible to select a more appropriate driving trajectory from among a plurality of candidates that suppresses sudden turns and deceleration when traveling through a turning section, and generate the recommended driving trajectory for the vehicle. As a result, it is possible to provide appropriate driving assistance that does not burden the vehicle occupants.
In addition, according to the second driving assistance device and computer program of the present invention, by generating multiple candidates for a driving trajectory when traveling through a turning section, and then comparing the generated multiple candidates with the lane shape on which the vehicle is traveling and the regulation information in consideration, it is possible to select a more appropriate driving trajectory that suppresses sudden turns and deceleration when traveling through a turning section as a driving trajectory recommended for the vehicle. As a result, it is possible to implement appropriate driving assistance that does not burden the vehicle occupants.

1 is a schematic configuration diagram showing a driving assistance system according to an embodiment of the present invention; 1 is a block diagram showing a configuration of a driving assistance system according to an embodiment of the present invention. 1 is a block diagram showing a navigation device according to an embodiment of the present invention; 4 is a flowchart of an autonomous driving assistance program according to the present embodiment. FIG. 2 is a diagram showing an area for which high-precision map information is acquired. 11A and 11B are diagrams illustrating a method for calculating a dynamic traveling trajectory. 13 is a flowchart of a sub-processing program of a static travel trajectory generation process. FIG. 2 is a diagram showing an example of a planned driving route of a vehicle. FIG. 9 is a diagram showing an example of a lane network constructed for the planned travel route shown in FIG. 8 . 13 is a flowchart of a sub-processing program of a travel trajectory calculation process for a turning section. FIG. 2 is a diagram showing an example of a turning section for which a travel trajectory is calculated; FIG. 2 is a diagram showing an example of a turning section for which a travel trajectory is calculated; FIG. 2 is a diagram showing an example of a turning section for which a travel trajectory is calculated; FIG. 2 is a diagram showing an example of a turning section for which a travel trajectory is calculated; FIG. 4 is a diagram showing an example of a first running trajectory candidate. 11A and 11B are diagrams illustrating a comparison between a case where a first running trajectory candidate is generated and a case where it is not generated. FIG. 11 is a diagram showing an example of a second running trajectory candidate. 13A and 13B are diagrams illustrating a comparison between a case where a second running trajectory candidate is generated and a case where it is not generated. 13 is a diagram showing a speed plan for a first driving trajectory candidate and an example of calculation of a required time for driving. FIG. 13 is a diagram showing a speed plan for a second driving trajectory candidate and an example of calculation of a required time for driving. FIG.

Below, an embodiment in which a driving assistance device according to the present invention is embodied in a navigation device 1 will be described in detail with reference to the drawings. First, the schematic configuration of a driving assistance system 2 including a navigation device 1 according to this embodiment will be described with reference to Figs. 1 and 2. Fig. 1 is a schematic configuration diagram showing the driving assistance system 2 according to this embodiment. Fig. 2 is a block diagram showing the configuration of the driving assistance system 2 according to this embodiment.

As shown in FIG. 1, the driving assistance system 2 according to this embodiment basically includes a server device 4 provided in an information distribution center 3, and a navigation device 1 that is mounted on a vehicle 5 and provides various types of assistance related to the automatic driving of the vehicle 5. 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. Note that instead of the navigation device 1, other on-board devices mounted on the vehicle 5 or a vehicle control device that controls the vehicle 5 may be used.

Here, vehicle 5 is a vehicle capable of manual driving based on the user's driving operations, as well as assisted driving using automatic driving assistance, in which the vehicle automatically drives along a pre-set route or road without the user's driving operations.

Autonomous driving assistance may be provided for all road sections, or may be provided only while the vehicle is traveling on a specific road section (for example, a highway with a gate (manned or unmanned, toll or free) at the boundary). In the following explanation, the autonomous driving section where autonomous driving assistance is provided includes parking lots as well as all road sections including general roads and highways, and the autonomous driving assistance is basically provided from the time the vehicle starts traveling to the time it ends traveling (until the vehicle is parked). However, autonomous driving assistance is not always provided when the vehicle travels on an autonomous driving section, but is preferably provided only when the user selects to provide autonomous driving assistance (for example, by turning on the autonomous driving start button) and it is determined that autonomous driving assistance is possible. On the other hand, the vehicle 5 may be a vehicle that is only capable of assisted driving with autonomous driving assistance.

In the vehicle control in the automated driving assistance, for example, the current position of the vehicle, the lane on which the vehicle is traveling, and the positions of surrounding obstacles are detected at any time, and the vehicle control of the steering, drive source, brakes, etc. is automatically performed so that the vehicle travels along the travel trajectory generated by the navigation device 1 at a speed according to the speed plan generated as described below. Note that in the assisted driving by the automated driving assistance of this embodiment, lane changes, right and left turns, and parking operations are also performed by performing the vehicle control by the above-mentioned automated driving assistance, but special driving such as lane changes, right and left turns, and parking operations may be performed by manual driving without driving by the automated driving assistance.

On the other hand, the navigation device 1 is an in-vehicle device that is mounted on the vehicle 5 and displays a map of the area around the vehicle's position based on map data held by the navigation device 1 or map data acquired from an external source, allows the user to input a destination, displays the vehicle's current position on a map image, and provides travel guidance along a set guide route. In this embodiment, various types of support information related to the autonomous driving support are generated, particularly when the vehicle is performing assisted driving using autonomous driving support. Examples of the support information include a recommended driving trajectory for the vehicle (including a recommended lane movement pattern), the selection of a parking position for parking the vehicle at the destination, and a speed plan indicating the vehicle speed when driving. Details of the navigation device 1 will be described later.

The server device 4 also performs a route search in response to a request from the navigation device 1. Specifically, information required for route search, such as the departure point and destination, is sent from the navigation device 1 to the server device 4 along with a route search request (however, in the case of a re-search, information regarding the destination does not necessarily need to be sent). The server device 4, which receives the route search request, then performs a route search using map information held by the server device 4, and identifies a recommended route from the departure point to the destination. It then transmits the identified recommended route to the navigation device 1 that made the request. The navigation device 1 can then provide the user with information regarding the received recommended route, or use the recommended route to generate various types of support information related to autonomous driving support, as described below.

Furthermore, the server device 4 has high-precision map information and facility information, which are more accurate map information, in addition to the normal map information used in the above route search. The high-precision map information includes, for example, information on the lane shape of the road (road shape and curvature for each lane, bending angle, lane width, etc.) and dividing lines drawn on the road (center line, lane boundary line, outer line of the road, guiding line, etc.). It also includes information on intersections, etc. Furthermore, it also includes information on the types and positions of the regulated objects (hereinafter referred to as regulated objects) that regulate the travel of vehicles (more specifically, require stopping or deceleration) such as speed limits, traffic lights, crosswalks, railroad crossings, and stop road signs set on the road. On the other hand, the facility information is more detailed information on the facility stored separately from the information on the facility included in the map information, and includes, for example, a floor map of the facility, information on the entrance and exit of the parking lot, layout information of the passages (roadways) and parking spaces provided in the parking lot, information on the dividing lines that divide the parking spaces and roadways, and connection information indicating the connection relationship between the entrance and exit of the parking lot and the lanes. The server device 4 then distributes high-precision map information and facility information in response to a request from the navigation device 1, and the navigation device 1 generates various types of support information related to autonomous driving support, as described below, using the high-precision map information and facility information distributed from the server device 4. Note that while high-precision map information is basically map information that covers only roads (links) and their surrounding areas, it may also be map information that includes areas other than those around the roads.

However, the above-mentioned route search process does not necessarily have to be performed by the server device 4, and may be performed by the navigation device 1 if the navigation device 1 has map information. Also, high-precision map information and facility information may not be distributed from the server device 4, but may be stored in advance by the navigation device 1.

The communication network 6 includes numerous base stations located throughout the country and communication companies that manage and control each base station, and is configured by connecting the base stations and communication companies to each other via wire (optical fiber, ISDN, etc.) or wirelessly. Here, the base stations have transceivers (transmitters/receivers) and antennas that communicate with the navigation device 1. The base stations perform wireless communication between the communication companies, and are also at the end of the communication network 6, and have the role of relaying communications between the navigation device 1 that is within the range (cell) of the base station's radio waves and the server device 4.

Next, the configuration of the server device 4 in the driving assistance system 2 will be described in more detail with reference to FIG. 2. As shown in FIG. 2, the server device 4 includes a server control unit 11, a server-side map DB 12 as an information recording means connected to the server control unit 11, a high-precision map DB 13, a facility DB 14, and a server-side communication device 15.

The server control unit 11 is a control unit (MCU, MPU, etc.) that controls the entire server device 4, and includes a CPU 21 as an arithmetic device and control device, a RAM 22 used as a working memory when the CPU 21 performs various arithmetic processing, a ROM 23 in which control programs and the like are recorded, and an internal storage device such as a flash memory 24 for storing programs read from the ROM 23. The server control unit 11 has various means as processing algorithms together with the ECU of the navigation device 1 described below.

Meanwhile, the server-side map DB 12 is a storage means for storing server-side map information, which is the latest version of map information registered based on external input data and input operations. Here, the server-side map information is composed of various information necessary for route search, route guidance and map display, including the road network. For example, it is composed of network data including nodes and links indicating the road network, link data related to roads (links), node data related to node points, intersection data related to each intersection, point data related to points such as facilities, map display data for displaying the map, search data for searching for routes, search data for searching for points, etc.

The high-precision map DB 13 is a storage means for storing high-precision map information 16, which is map information with higher accuracy than the server-side map information. The high-precision map information 16 is map information that stores more detailed information, particularly about roads on which vehicles are traveling. In this embodiment, for example, the information includes information about lane shapes (road shapes and curvatures for each lane, lane width, etc.) and dividing lines drawn on the roads (center lines, lane boundaries, outer lines, guiding lines, etc.). In addition, data representing road gradients, cants, banks, merging sections, points where the number of lanes decreases, points where the width narrows, railroad crossings, etc., data representing the radius of curvature and bending angle of curves, data representing branch points such as intersections and T-junctions, data representing downhill roads, uphill roads, etc., regarding road attributes, and data representing general roads such as national highways, prefectural roads, and narrow streets, as well as toll roads such as national expressways, urban expressways, motorways, general toll roads, and toll bridges, regarding road types, are recorded. Furthermore, the information includes information on the speed limit, traffic lights, pedestrian crossings, railroad crossings, stop signs, and other road restrictions that restrict vehicle travel (restrictions), specifying the type and location of the restrictions. Information on the dividing lines includes information specifying which types of dividing lines are arranged on the road. In the following description, the term "curve" includes not only a shape in which the road bends in an arc shape with a specified curvature (including a shape in which the curvature of the road changes), but also a shape in which the road bends at a specified angle such as a right angle (for example, an L-shaped road). In addition to the number of lanes on the road, information is also stored that specifies the traffic divisions in the direction of travel for each lane and the connections of the roads (specifically, the correspondence between the lanes on the road before passing through the intersection and the lanes on the road after passing through the intersection).

On the other hand, the facility DB 14 is a storage means for storing more detailed facility information than the facility information stored in the server-side map information. Specifically, the facility information 17 includes information for parking lots (including both parking lots attached to facilities and independent parking lots) where vehicles are parked, such as information for specifying the location of the entrance and exit of the parking lot, information for specifying the layout of parking spaces in the parking lot, and information on the dividing lines that divide the parking spaces and the road. For roads, information for specifying the shape of the road (i.e., the area in the parking lot where vehicles can travel) and, if there are any restrictions on the travel of vehicles on the road, such as speed limits (restrictions), information for specifying the type and location of the restrictions. For facilities other than parking lots, information for specifying the floor map of the facility is included. The floor map includes information for specifying the locations of entrances, passages, stairs, elevators, and escalators, for example. In addition, in a commercial complex with multiple tenants, information for specifying the location of each tenant is included. The facility information 17 may be information generated by using a 3D model of the parking lot or facility. In addition, the facility DB 14 also includes connection information 18 that indicates the connection between the lanes included in the approach road facing the entrance/exit of the parking lot and the entrance/exit of the parking lot, and road outer shape information 19 that specifies the area between the approach road and the entrance/exit of the parking lot that vehicles can pass through.

Note that the high-precision map information 16 is basically map information that covers only roads (links) and their surroundings, but it may also be map information that includes areas other than the surroundings of roads. In the example shown in FIG. 2, the server-side map information stored in the server-side map DB 12 and the information stored in the high-precision map DB 13 and facility DB 14 are different map information, but the information stored in the high-precision map DB 13 and facility DB 14 may be part of the server-side map information. In addition, the high-precision map DB 13 and facility DB 14 may not be separated but may be a single database.

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. It is also possible to receive traffic information, such as congestion information, regulation information, and traffic accident information, sent from sources other than the navigation device 1, such as the Internet network and traffic information centers, for example, VICS (registered trademark: Vehicle Information and Communication System) centers.

Next, the schematic configuration of the navigation device 1 mounted on the vehicle 5 will be described with reference to FIG. 3. FIG. 3 is a block diagram showing the navigation device 1 according to this embodiment.

As shown in FIG. 3, the navigation device 1 according to this embodiment includes a current position detection unit 31 that detects the current position of the vehicle in which the navigation device 1 is installed, a data recording unit 32 in which various data are recorded, a navigation ECU 33 that performs various calculation processes based on input information, an operation unit 34 that accepts operations from the user, a liquid crystal display 35 that displays to the user a map of the area around the vehicle and information on the guide route (the planned route of the vehicle) set in the navigation device 1, a speaker 36 that outputs voice guidance regarding the route guide, a DVD drive 37 that reads a DVD, which is a storage medium, and a communication module 38 that communicates with an information center such as a probe center or a VICS center. In addition, the navigation device 1 is connected to an external camera 39 and various sensors installed in the vehicle in which the navigation device 1 is installed via an in-vehicle network such as a CAN. Furthermore, the navigation device 1 is also connected to a vehicle control ECU 40 that performs various controls on the vehicle in which the navigation device 1 is installed, so that bidirectional communication is possible.

Each of the components of the navigation device 1 will be described below in order.
The current position detection unit 31 is composed of a GPS 41, a vehicle speed sensor 42, a steering sensor 43, a gyro sensor 44, etc., and is capable of detecting the current vehicle position, direction, vehicle running speed, current time, etc. Here, the vehicle speed sensor 42 in particular is a sensor for detecting the travel distance and vehicle speed of the vehicle, and generates pulses in response to the rotation of the drive wheels of the vehicle and outputs the pulse signal to the navigation ECU 33. The navigation ECU 33 then calculates the rotation speed and travel distance of the drive wheels by counting the generated pulses. It is not necessary for the navigation device 1 to be equipped with all of the above four types of sensors, and the navigation device 1 may be configured to be equipped with only one or a plurality of these types of sensors.

The data recording unit 32 also includes a hard disk (not shown) as an external storage device and recording medium, and a recording head (not shown) which is a driver for reading the map information DB 45, cache 46, and predetermined programs recorded on the hard disk and writing predetermined data to the hard disk. The data recording unit 32 may include a flash memory, a memory card, or an optical disk such as a CD or DVD instead of a hard disk. In this embodiment, as described above, the server device 4 searches for a route to the destination, so the map information DB 45 may be omitted. Even if the map information DB 45 is omitted, it is possible to obtain map information from the server device 4 as necessary.

Here, the map information DB45 is a storage means that stores, for example, link data related to roads (links), node data related to node points, search data used in processes related to route search and change, facility data related to facilities, map display data for displaying the map, intersection data related to each intersection, search data for searching for locations, etc.

On the other hand, the cache 46 is a storage means for storing the high-precision map information 16, facility information 17, connection information 18, and road external shape information 19 that have been distributed from the server device 4 in the past. The storage period can be set as appropriate, and may be, for example, a predetermined period (e.g., one month) from the time of storage, or until the vehicle's ACC power source (accessory power supply) is turned off. In addition, after the amount of data stored in the cache 46 reaches an upper limit, the oldest data may be deleted in order. The navigation ECU 33 then generates various types of support information related to autonomous driving support using the high-precision map information 16, facility information 17, connection information 18, and road external shape information 19 stored in the cache 46. Details will be described later.

On the other hand, the navigation ECU (electronic control unit) 33 is an electronic control unit that controls the entire navigation device 1, and includes an internal storage device such as a CPU 51 as a calculation device and a control device, a RAM 52 that is used as a working memory when the CPU 51 performs various calculation processes and stores route data when a route is searched, a ROM 53 in which a control program and an automatic driving assistance program (see FIG. 4) described later are recorded, and a flash memory 54 that stores a program read from the ROM 53. The navigation ECU 33 has various means as processing algorithms. For example, the planned driving route acquisition means acquires a planned driving route along which the vehicle will travel. The turning driving section acquisition means acquires a turning section along which the vehicle will turn when traveling according to the planned driving route. The driving trajectory generation means generates a driving trajectory along which the vehicle is recommended to travel in the turning section based on the lane shape along which the vehicle travels in the turning section and the regulation information. The driving assistance means provides driving assistance for the vehicle based on the driving trajectory generated by the driving trajectory generation means.

The operation unit 34 is operated when inputting the departure point as the starting point of the journey and the destination as the ending point of the journey, and has a number of operation switches (not shown) such as various keys and buttons. The navigation ECU 33 controls the execution of various corresponding operations based on switch signals output by pressing each switch. The operation unit 34 may have a touch panel provided on the front side of the liquid crystal display 35. It may also have a microphone and a voice recognition device.

The LCD display 35 also displays map images including roads, traffic information, operation guidance, operation menus, key guidance, guidance information along the guided route (planned driving route), news, weather forecasts, time, emails, television programs, etc. Note that a HUD or HMD may be used instead of the LCD display 35.

In addition, the speaker 36 outputs voice guidance that guides the driver along the guided route (planned driving route) based on instructions from the navigation ECU 33, as well as traffic information.

The DVD drive 37 is a drive capable of reading data recorded on recording media such as DVDs and CDs. Based on the read data, music and video are played, and the map information DB 45 is updated. Instead of the DVD drive 37, a card slot for reading and writing to a memory card may be provided.

The communication module 38 is a communication device for receiving traffic information, probe information, weather information, etc. transmitted from a traffic information center, such as a VICS center or a probe center, and is, for example, a mobile phone or DCM. It also includes a vehicle-to-vehicle communication device for communicating between vehicles, and a road-to-vehicle communication device for communicating with roadside devices. It is also used to transmit and receive route information, high-precision map information 16, facility information 17, connection information 18, and road exterior shape information 19 searched by the server device 4 to and from the server device 4.

The exterior camera 39 is composed of a camera using a solid-state image sensor such as a CCD, and is attached to the top of the front bumper of the vehicle with the optical axis oriented downward at a predetermined angle from the horizontal. When the vehicle is traveling in an automatic driving section, the exterior camera 39 captures the area ahead of the vehicle in the direction of travel. The navigation ECU 33 performs image processing on the captured image to detect obstacles such as dividing lines drawn on the road on which the vehicle is traveling and other vehicles in the vicinity, and generates various support information related to automatic driving support based on the detection results. For example, when an obstacle is detected, a new driving trajectory is generated to avoid or follow the obstacle. The exterior camera 39 may be configured to be placed behind or to the side of the vehicle in addition to the front. Instead of a camera, a sensor such as a millimeter wave radar or a laser sensor, or vehicle-to-vehicle communication or road-to-vehicle communication may be used as a means for detecting obstacles.

The vehicle control ECU 40 is an electronic control unit that controls the vehicle in which the navigation device 1 is mounted. The vehicle control ECU 40 is also connected to each driving part of the vehicle, such as the steering, brakes, and accelerator, and in this embodiment, after automatic driving assistance is started in the vehicle, the vehicle control ECU 40 controls each driving part to implement automatic driving assistance for the vehicle. If an override is performed by the user during automatic driving assistance, the ECU 40 detects that an override has been performed.

Here, after starting to drive, the navigation ECU 33 transmits various types of support information related to the automatic driving support generated by the navigation device 1 to the vehicle control ECU 40 via the CAN. The vehicle control ECU 40 then uses the various types of support information received to implement the automatic driving support after starting to drive. Examples of support information include a recommended driving trajectory for the vehicle, a speed plan indicating the vehicle speed when driving, etc.

Next, the automatic driving assistance program executed by the CPU 51 in the navigation device 1 according to this embodiment having the above configuration will be described with reference to FIG. 4. FIG. 4 is a flowchart of the automatic driving assistance program according to this embodiment. Here, the automatic driving assistance program is executed when the vehicle's ACC power supply (accessory power supply) is turned on and the vehicle starts traveling with automatic driving assistance, and is a program that performs assisted traveling with automatic driving assistance in accordance with assistance information generated by the navigation device 1. The programs shown in the flowcharts in FIG. 4, FIG. 7, and FIG. 10 below are stored in the RAM 52 and ROM 53 provided in the navigation device 1, and are executed by the CPU 51.

First, in step (hereinafter abbreviated as S) 1 of the automated driving assistance program, the CPU 51 acquires the route along which the vehicle is scheduled to travel in the future (hereinafter referred to as the planned travel route). The planned travel route of the vehicle is, for example, a recommended route to a destination searched for by the server device 4 when the destination is set by the user. If a destination is not set, the route along which the vehicle travels from the current position of the vehicle may be set as the planned travel route.

When searching for a recommended route, the CPU 51 first sends a route search request to the server device 4. The route search request includes a terminal ID that identifies the navigation device 1 that sent the route search request, and information that identifies the starting point (e.g., the current position of the vehicle) and the destination. When re-searching, information that identifies the destination is not necessarily required. The CPU 51 then receives searched route information sent from the server device 4 in response to the route search request. The searched route information is information (e.g., a series of links included in the recommended route) that identifies a recommended route (center route) from the starting point to the destination that the server device 4 has searched for using the latest version of map information based on the sent route search request. For example, the search is performed using the well-known Dijkstra algorithm.

In addition, in the search for the recommended route, it is desirable to select a parking position (parking space) recommended for parking the vehicle in a parking lot at the destination, and search for a recommended route to the selected parking position. In other words, it is desirable that the recommended route to be searched for includes not only the route to the parking lot, but also the route showing the movement of the vehicle within the parking lot. For example, from among the parking spaces that are vacant in the parking lot, a parking space that is easy for the user to park in (for example, a parking space close to the entrance/exit of the parking lot, a parking space with no other vehicles parked on the left or right, etc.) is determined as a candidate parking position recommended for the user to park. In addition, when selecting a parking position, it is desirable to select a parking position that reduces the burden on the user by considering not only the movement of the vehicle to the parking position, but also the movement of the vehicle on foot after parking the vehicle and the movement of the vehicle when leaving the parking position on the way home.

In addition, multiple candidates for parking positions recommended for parking the vehicle may be selected. In addition, when multiple candidates for parking positions recommended for parking the vehicle are selected, the recommended route to each parking position is acquired as the planned driving route in S1, that is, multiple candidates for the planned driving route are acquired. Furthermore, even when only one recommended parking position is selected, multiple candidates for the planned driving route may be acquired if multiple recommended routes are possible for that parking position. In addition, when multiple candidates for the planned driving route are acquired in S1, the lane movement patterns are compared between the multiple planned driving routes in S25 described below, and the recommended lane movement pattern is determined as one, and the parking position and the planned driving route are also determined as one.

The server device 4 also refers to connection information 18 that indicates the connection relationship between the lanes included in the road (hereinafter referred to as the approach road) facing the entrance/exit of the parking lot where the user parks and the entrance/exit of the parking lot, and when the possible directions of travel to enter the parking lot from the approach road are limited (for example, only entry by turning left is possible), the server device 4 searches for the above-mentioned driving route while taking into account the direction of entry. Note that a search method other than the Dijkstra algorithm may be used as a route search method. Also, the search for the driving route in S1 may be performed by the navigation device 1 rather than the server device 4.

Next, in S2, the CPU 51 acquires high-precision map information 16 for an area including the planned driving route acquired in S1 from the current position of the vehicle.

Here, the high-precision map information 16 is divided into rectangular shapes (e.g., 500 m x 1 km) as shown in FIG. 5 and stored in the high-precision map DB 13 of the server device 4. Therefore, for example, when a route 61 is acquired as the vehicle's driving route as shown in FIG. 5, high-precision map information 16 is acquired for areas 62 to 65 including the route 61. However, when the distance to the destination is particularly long, high-precision map information 16 may be acquired for only the secondary mesh in which the vehicle is currently located, or high-precision map information 16 may be acquired for only the area within a predetermined distance (e.g., within 3 km) from the vehicle's current position.

The high-precision map information 16 includes, for example, information on the lane shape of the road and the dividing lines drawn on the road (center line, lane boundary line, outer lane line, guiding line, etc.). In addition, the information also includes information on speed limits set on roads and lanes, traffic lights, pedestrian crossings, railroad crossings, stop signs, and other objects that restrict the travel of vehicles (more specifically, require stopping or slowing down), and specifies the type and location of such objects. In addition, the information also includes information on intersections, parking lots, and the like. The high-precision map information 16 is basically acquired from the server device 4 in the above-mentioned rectangular area units, but if high-precision map information 16 for an area that is already stored in the cache 46 exists, it is acquired from the cache 46. In addition, the high-precision map information 16 acquired from the server device 4 is temporarily stored in the cache 46.

In addition, in S2, the CPU 51 also acquires connection information 18 that indicates the connection relationship between the lanes included in the approach road facing the entrance/exit of the parking lot where the user will park and the entrance/exit of the parking lot, and road outer shape information 19 that specifies the area through which vehicles can pass between the approach road and the entrance/exit of the parking lot where the user will park.

Then, in S3, the CPU 51 executes a static driving trajectory generation process (FIG. 7) to be described later. Here, the static driving trajectory generation process is a process for generating a static driving trajectory, which is a driving trajectory recommended for the vehicle on the roads included in the planned driving route, based on the planned driving route of the vehicle and the high-precision map information 16 acquired in S2. In particular, the CPU 51 not only identifies the lanes on which the vehicle is recommended to drive, but also generates a driving trajectory that identifies the specific driving position within the lane where driving is recommended as a static driving trajectory. Note that, if the distance to the destination is particularly long, only a static driving trajectory may be generated that targets a section from the current position of the vehicle to a predetermined distance ahead along the traveling direction (for example, within the secondary mesh where the vehicle is currently located). Note that the predetermined distance can be changed as appropriate, but the static driving trajectory is generated for an area that includes at least the outside of the range (detection range) where the road conditions around the vehicle can be detected by the exterior camera 39 or other sensors.

Next, in S4, the CPU 51 generates a speed plan for the vehicle when traveling along the static travel path generated in S3, based on the high-precision map information 16 acquired in S2. For example, the CPU 51 calculates the recommended travel speed for the vehicle when traveling along the static travel path, taking into account speed limit information and speed change points (e.g., intersections, curves, railroad crossings, crosswalks, etc.) on the planned travel route.

The speed plan generated in S4 is stored in the flash memory 54 or the like as support information to be used for autonomous driving support. In addition, an acceleration plan indicating the acceleration/deceleration of the vehicle required to realize the speed plan generated in S4 may also be generated as support information to be used for autonomous driving support.

Next, in S5, the CPU 51 performs image processing on the image captured by the external camera 39 to determine whether there are any factors that may affect the running of the vehicle, particularly around the vehicle, as the surrounding road conditions. Here, the "factors that may affect the running of the vehicle" to be determined in S5 are dynamic factors that change in real time, and static factors based on the road structure are excluded. For example, other vehicles running or parked ahead of the vehicle, vehicles in traffic jams, pedestrians ahead of the vehicle, and construction zones ahead of the vehicle. On the other hand, intersections, curves, railroad crossings, merging sections, lane narrowing sections, etc. are excluded. Even if other vehicles, pedestrians, or construction zones exist, they are excluded from the "factors that may affect the running of the vehicle" if they are not likely to overlap with the future running trajectory of the vehicle (for example, if they are located away from the future running trajectory of the vehicle). In addition, as a means for detecting factors that may affect the running of the vehicle, sensors such as millimeter wave radar and laser sensors, vehicle-to-vehicle communication, and road-to-vehicle communication may be used instead of cameras.

In addition, for example, the real-time positions of each vehicle traveling on roads across the country may be managed by an external server, and the CPU 51 may obtain the positions of other vehicles located around the vehicle from the external server and perform the determination process of S5.

If it is determined that there is a factor in the vicinity of the vehicle that may affect the running of the vehicle (S5: YES), the process proceeds to S6. On the other hand, if it is determined that there is no factor in the vicinity of the vehicle that may affect the running of the vehicle (S5: NO), the process proceeds to S9.

In S6, the CPU 51 generates a new trajectory as a dynamic driving trajectory for returning to the static driving trajectory by avoiding or following the "factors that affect the driving of the vehicle" detected in S5 from the current position of the vehicle. The dynamic driving trajectory is generated for a section including the "factors that affect the driving of the vehicle". The length of the section varies depending on the content of the factor. For example, if the "factors that affect the driving of the vehicle" are other vehicles (forward vehicles) traveling in front of the vehicle, an avoidance trajectory is generated as the dynamic driving trajectory 67, which is a trajectory in which the vehicle changes lanes to the right to overtake the forward vehicle 66 as shown in FIG. 6, and then changes lanes to the left to return to the original lane. The following trajectory, which is a trajectory in which the vehicle follows the forward vehicle 66 at a predetermined distance behind (or runs parallel to) the forward vehicle 66 without overtaking the forward vehicle 66, may be generated as the dynamic driving trajectory. Furthermore, multiple candidates may be generated as the dynamic driving trajectory, and in that case, the candidate with the lowest cost is selected from the multiple candidates in S7 described later.

To explain the calculation method of the dynamic driving trajectory 67 shown in Fig. 6 as an example, the CPU 51 first calculates a first trajectory L1 required for starting a steering wheel turn to move to the right lane and returning the steering wheel position to the straight direction. The first trajectory L1 is calculated by calculating the lateral acceleration (lateral G) generated when changing lanes based on the current vehicle speed of the vehicle, and calculating a trajectory that is as smooth as possible and requires as short a distance as possible to change lanes using a clothoid curve or a circular arc, under the conditions that the lateral G does not interfere with the automatic driving assistance and does not exceed an upper limit (e.g., 0.2 ^G ) that does not cause discomfort to the vehicle occupants, and that the change amount of the lateral G per unit time also does not exceed an upper limit (e.g., 0.6 m/s3). Another condition is that an appropriate inter-vehicle distance N or more is maintained between the vehicle and the vehicle ahead 66.
Next, a second trajectory L2 is calculated for traveling in the right lane at the upper limit of the speed limit to overtake the preceding vehicle 66 and to maintain an appropriate inter-vehicle distance N or more between the preceding vehicle 66. The second trajectory L2 is basically a straight trajectory, and the length of the trajectory is calculated based on the vehicle speed of the preceding vehicle 66 and the speed limit of the road.
Next, a third trajectory L3 is calculated that is required to start turning the steering wheel and return to the left lane, and to return the steering wheel position to the straight-ahead direction. The third trajectory L3 is calculated by calculating the lateral acceleration (lateral G) that occurs when changing lanes based on the current vehicle speed of the vehicle, and using a clothoid curve or a circular arc, a trajectory that is as smooth as possible and requires as short a distance as possible to change lanes, under the conditions that the lateral G does not interfere with the automatic driving assistance and does not exceed an upper limit (e.g., 0.2 G) that does not cause discomfort to the vehicle occupants, and that the change amount of the lateral G per unit time also does not exceed an upper limit (e.g., 0.6 m/s ³ ). Another condition is that an appropriate inter-vehicle distance N or more must be maintained between the vehicle 66 ahead.
Furthermore, since the dynamic driving trajectory is generated based on the road conditions around the vehicle obtained by the exterior camera 39 and other sensors, the area for which the dynamic driving trajectory is generated is at least within the range (detection range) in which the road conditions around the vehicle can be detected by the exterior camera 39 and other sensors.

Next, in S7, the CPU 51 reflects the dynamic driving trajectory newly generated in S6 to the static driving trajectory generated in S3. Specifically, the costs of the static driving trajectory and the dynamic driving trajectory (there may be multiple candidates for the dynamic driving trajectory) from the current position of the vehicle to the end of the section including the "factors that affect the driving of the vehicle" are calculated, and the driving trajectory with the smallest cost is selected. As a result, part of the static driving trajectory is replaced with the dynamic driving trajectory as necessary. Note that, depending on the situation, the dynamic driving trajectory may not be replaced, that is, even if the dynamic driving trajectory is reflected, there may be cases where the static driving trajectory generated in S3 does not change. Furthermore, if the dynamic driving trajectory and the static driving trajectory are the same trajectory, there may be cases where the static driving trajectory generated in S3 does not change even if the dynamic driving trajectory is replaced.

Next, in S8, the CPU 51 modifies the vehicle speed plan generated in S4 for the static driving trajectory after the dynamic driving trajectory is reflected in S7 based on the contents of the reflected dynamic driving trajectory. Note that if the static driving trajectory generated in S3 does not change as a result of reflecting the dynamic driving trajectory, the process of S8 may be omitted.

Next, in S9, the CPU 51 calculates the control amounts for the vehicle to travel on the static driving trajectory generated in S3 (the reflected trajectory if the dynamic driving trajectory has been reflected in S7) at a speed according to the speed plan generated in S4 (the revised plan if the speed plan has been modified in S8). Specifically, the control amounts for the accelerator, brake, gear, and steering are each calculated. Note that the processing of S9 and S10 may be performed by the vehicle control ECU 40 that controls the vehicle, rather than the navigation device 1.

Then, in S10, the CPU 51 reflects the control amount calculated in S9. Specifically, the calculated control amount is transmitted to the vehicle control ECU 40 via the CAN. The vehicle control ECU 40 controls the accelerator, brakes, gears, and steering of the vehicle based on the received control amount. As a result, driving assistance control is possible for driving the static driving trajectory generated in S3 (the reflected trajectory if the dynamic driving trajectory has been reflected in S7) at a speed according to the speed plan generated in S4 (the revised plan if the speed plan has been modified in S8).

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.

If it is determined that the vehicle has traveled a certain distance since the static driving trajectory was generated in S3 (S11: YES), the process returns to S2. After that, the static driving trajectory is generated again for a section within a certain distance from the vehicle's current position along the planned driving route (S2 to S4). Note that in this embodiment, the static driving trajectory is repeatedly generated for a section within a certain distance from the vehicle's current position along the driving route each time the vehicle travels a certain distance (for example, 1 km), but if the distance to the destination is short, the static driving trajectory to the destination may be generated all at once at the start of driving.

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: NO), it is determined whether or not to end the assisted driving by autonomous driving assistance (S12). Assisted driving by autonomous driving assistance can be ended not only when the vehicle has arrived at the destination, but also when the user intentionally cancels (overrides) the assisted driving by autonomous driving assistance by operating an operation panel provided in the vehicle, or by operating the steering wheel or brakes.

If it is determined that the assisted driving by the automated driving assistance should be terminated (S12: YES), the automated driving assistance program is terminated. On the other hand, if it is determined that the assisted driving by the automated driving assistance should be continued (S12: NO), the process returns to S5.

Next, the sub-processing of the static driving trajectory generation process executed in S3 will be described with reference to FIG. 7. FIG. 7 is a flowchart of the sub-processing program of the static driving trajectory generation process.

First, in S21, the CPU 51 acquires the current position of the vehicle detected by the current position detection unit 31. It is desirable to specify the current position of the vehicle in detail using, for example, high-precision GPS information or high-precision location technology. Here, the high-precision location technology is a technology that detects white lines and road paint information captured by a camera installed in the vehicle by image recognition, and furthermore, compares the detected white lines and road paint information with, for example, high-precision map information 16, thereby making it possible to detect the driving lane and the vehicle position with high precision. Furthermore, when the vehicle is traveling on a road consisting of multiple lanes, the lane in which the vehicle is traveling is also specified. Furthermore, when the vehicle is located in a parking lot, the specific position in the parking lot (for example, the parking space in which the vehicle is located) and the attitude of the vehicle (for example, the direction of travel of the vehicle, and when the vehicle is located in a parking space, the orientation of the vehicle relative to the parking space) are also specified.

Next, in S22, the CPU 51 acquires information on lane shape, dividing line information, intersections, etc., based on the high-precision map information 16 acquired in S2, particularly for the section in front of the vehicle in which a static driving trajectory is to be generated (for example, the planned driving route within a predetermined distance from the vehicle's current position). In addition, regulation information is acquired that identifies the type and location of regulated objects that regulate the vehicle's driving (more specifically, require stopping or deceleration) such as speed limits, traffic lights, crosswalks, railroad crossings, and stop signs set on roads and lanes. In addition, if the section in which the static driving trajectory is to be generated includes a parking lot, information is included that identifies the location of the entrance and exit of the parking lot, information that identifies the layout of parking spaces in the parking lot, and information on dividing lines that divide parking spaces and lanes (lanes). In addition, for lanes, information is also included that identifies the shape of the lane (i.e., the area in the parking lot where the vehicle can drive). The lane shape and dividing line information acquired in S22 includes information that specifies how the lanes that a vehicle can select as driving targets are arranged on the road, as well as the number of lanes, the type and arrangement of the dividing lines that divide the lanes, the curvature of the road (lanes), lane width, where and how the number of lanes increases or decreases if any, the traffic divisions in the direction of travel for each lane, and road connections (specifically, the correspondence between the lanes on the road before passing through the intersection and the lanes on the road after passing through the intersection), etc.

Next, in S23, the CPU 51 constructs a lane network for the section ahead in the vehicle's travel direction for which a static driving trajectory is to be generated, based on the lane shape and demarcation line information acquired in S22. Here, the lane network is a network that indicates the lane movements that the vehicle can select.

Here, as an example of constructing a lane network in S23, a case where a vehicle travels on a planned travel route shown in FIG. 8 will be described. The planned travel route shown in FIG. 8 is a route in which the vehicle travels straight from the current position of the vehicle, turns right at the next intersection 71, turns right at the next intersection 72, and turns left at the next intersection 73. In the planned travel route shown in FIG. 8, for example, when turning right at intersection 71, it is possible to enter 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 at the time of entering the intersection 72. Also, when turning right at intersection 72, it is possible to enter 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 at the time of entering the intersection 73. A lane network constructed for a section where such lane movement is possible is shown in FIG. 9.

As shown in FIG. 9, the lane network divides the section that generates the static driving trajectory ahead of the vehicle's direction of travel into multiple sections (groups). Specifically, the division is made with the entrance position of the intersection, the exit position of the intersection, and the positions where the lanes increase or decrease as boundaries. Then, node points (hereinafter referred to as lane nodes) 75 are set for each lane located at the boundary of each divided section. Furthermore, links (hereinafter referred to as lane links) 76 that connect the lane nodes 75 are set. Note that the lane links 76 are basically set in the center of the lane when there is no lane crossing.

The lane network also includes information that identifies 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 with respect to the lanes before the intersection, by connecting the lane nodes and lane links at the intersection in particular. Specifically, it indicates that a vehicle can move between the lanes that correspond to the lane nodes that are connected by lane links among the lane nodes set on the road before the intersection and the lane nodes set on the road after the intersection. In order to generate such a lane network, the high-precision map information 16 stores lane flags that indicate the correspondence between the lanes for each combination of roads entering and leaving the intersection for each road connected to the intersection. When constructing the lane network in S23, the CPU 51 forms the connection between the lane nodes and lane links at the intersection by referring to the lane flags.

Note that while Figure 9 shows an example of a lane network constructed for roads, if a parking lot is included in the section for generating the static driving trajectory, a similar network (hereinafter referred to as a parking lot network) can be constructed for the parking lot. The parking lot network consists of parking lot nodes and parking lot links, and parking lot nodes are set at the entrances and exits of the parking lot, intersections where passages through which vehicles can pass intersect, corners of passages through which vehicles can pass (i.e., connection points between passages), and end points of passages. Meanwhile, parking lot links are set for passages through which vehicles can pass between parking lot nodes.

If multiple candidates for the planned driving routes are obtained in S1, the lane network and parking lot network are constructed for the multiple planned driving routes.

Next, in S24, the CPU 51 sets a start lane (start node) for the lane network constructed in S23 (including the parking lot network if the section for generating the static driving trajectory includes the parking lot network; the same applies below) for the lane node located at the start of the lane network, from which the vehicle will start moving, and sets a target lane (destination node) for the lane node located at the end of the lane network, to which the vehicle will move. If the start of the lane network is a road with multiple lanes in each direction, the lane node corresponding to the lane in which the vehicle is currently located becomes the start lane. On the other hand, if the end of the lane network is a road with multiple lanes in each direction, the lane node corresponding to the leftmost lane (for left-hand traffic) becomes the target lane. If the start or end of the lane network is in the parking lot, the start lane is set to the parking space or passage in which the vehicle is currently located in the parking lot network, and the target lane is set to the parking space in which the vehicle will be parked or the passage through which the vehicle can enter the parking space.

Then, in S25, the CPU 51 refers to the lane network constructed in S23 and derives the route with the smallest lane cost (hereinafter referred to as the recommended route) from among the routes that continuously connect the start lane to the target lane. For example, the route is searched for from the target lane side using the Dijkstra algorithm. However, as long as it is possible to search for a route that continuously connects the start lane to the target lane, a search method other than the Dijkstra algorithm may be used. The derived recommended route becomes the lane movement mode of the vehicle that is recommended when the vehicle moves (information that specifies the lane in which it is recommended to travel and the recommended position for lane movement).

The lane cost used in the route search is assigned to each lane link 76. The lane cost assigned to each lane link 76 has the length of the lane link 76 or the time required for movement as a reference value. In particular, in this embodiment, the length of the lane link (in meters) is used as the reference value of the lane cost. For lane links involving lane changes, a lane change cost (e.g., 50) is added to the reference value. The lane change cost may be changed depending on the number of lane changes and the location of the lane change. For example, the lane change cost can be increased when a lane change is made near an intersection or when a lane change is made across two lanes.

If multiple candidates for the planned driving route are obtained in S1, the recommended route with the smallest lane cost is derived from the multiple planned driving routes. The planned driving route is also determined by the derived recommended route.

Next, in S26, the CPU 51 performs a driving trajectory calculation process for the turning section (FIG. 10) described later. The driving trajectory calculation process for the turning section is a process for generating a driving trajectory recommended for driving along the recommended route derived in S25, particularly for a turning section where the vehicle turns when driving according to the planned driving route, among the planned driving routes of the section for which a static driving trajectory is generated ahead of the vehicle's traveling direction. Here, the turning section includes, for example, a section where the road turns in an arc shape with a predetermined curvature (including a shape where the curvature of the road changes), a section where the road bends at a predetermined angle such as a right angle, and a section of an intersection (branch) where the vehicle turns right or left. Furthermore, it also includes a section where the vehicle turns not only on a public road but also in a facility such as a parking lot, a section where the vehicle turns to enter or exit a parking space, or a section where the vehicle turns to enter a facility from a public road or enter a facility from a facility to a public road. However, in this embodiment, lane changes for changing the driving lane are excluded from the above-mentioned turning targets, and a driving trajectory is generated for the section in which the lane change is performed in S27 described later. Note that, if the planned driving route includes multiple turning sections, a recommended driving trajectory is generated for each of the multiple turning sections.

After that, in S27, the CPU 51 generates a recommended driving trajectory when driving along the recommended route derived in S25 for the section other than the turning section. For example, for a driving trajectory in a section involving lane changing, the position of the lane change is set so that the lane change is not repeated as much as possible and is performed at a position far from the intersection. In addition, when generating a driving trajectory when changing lanes, the lateral acceleration (lateral G) generated in the vehicle is calculated, and a trajectory that connects as smoothly as possible is calculated using a clothoid curve under the conditions that the lateral G does not interfere with the automatic driving assistance and does not exceed an upper limit value (e.g., 0.2 G) that does not cause discomfort to the vehicle occupants, and the change amount of the lateral G per unit time also does not exceed an upper limit value (e.g., 0.6 m/s ³ ). By performing the above processing, a driving trajectory that is recommended for the vehicle to drive on roads included in the planned driving route is generated. Note that, for sections that are not turning sections or sections where lane changing is performed, a trajectory that passes through the center of the lane is set as the driving trajectory that is recommended for the vehicle to drive.

In S28, the CPU 51 generates a static driving trajectory, which is a driving trajectory that is recommended for the vehicle to drive on roads included in the planned driving route, by combining the driving trajectories calculated in S26 and S27. The static driving trajectory generated in S28 is stored in the flash memory 54 or the like as assistance information used for automatic driving assistance. Then, the process proceeds to S4, where various driving assistance is performed based on the generated static driving trajectory.

Next, we will explain the sub-processing of the driving trajectory calculation process for the turning section executed in S26. Figure 10 is a flowchart of the sub-processing program for the driving trajectory calculation process for the turning section.

In S31, the CPU 51 acquires route information for the route along which the vehicle will travel, based on the high-precision map information 16 acquired in S2, for the section ahead in the vehicle's direction of travel for which a static travel trajectory is to be generated. In particular, in S31, the lane along which the vehicle will travel (for roads without lane divisions, the area on the road where the vehicle can travel, or for a parking lot, the roadway) is identified, and the shape of the lane is acquired. In addition, for points where the vehicle moves between lanes, such as at intersections, the progression of changes (from which lane to which lane the vehicle moves before and after passing through the intersection) is also acquired.

Next, in S32, the CPU 51 determines whether or not there is at least one turning section in the section for generating the static driving trajectory ahead of the vehicle's traveling direction based on the route information acquired in S31. Here, the turning section includes, for example, a section where the road turns in an arc shape with a predetermined curvature (including a shape where the curvature of the road changes), a section where the road bends at a predetermined angle such as a right angle, and a section of an intersection (branch) where the vehicle turns right or left. Furthermore, it also includes a section where the vehicle travels not only on a public road but also within a facility such as a parking lot, a section where the vehicle travels with turning, a section where the vehicle travels to enter or exit a parking space, or a section where the vehicle travels to enter a facility from a public road or enter a facility from a facility onto a public road. However, in this embodiment, lane changes for changing the driving lane are excluded from the above-mentioned turning.

If it is determined that at least one turning section exists in the section for generating the static driving trajectory ahead of the vehicle's traveling direction (S32: YES), the process proceeds to S33. On the other hand, if it is determined that no turning section exists in the section for generating the static driving trajectory ahead of the vehicle's traveling direction (S32: NO), the process proceeds to S27, where a driving trajectory recommended for driving along the recommended route derived in S25 is generated.

From S33 onwards, the following process is carried out on the turning section included in the section for which the static driving trajectory is to be generated ahead of the vehicle's travel direction to generate a recommended driving trajectory for driving through the turning section. If multiple turning sections are included, the following process is carried out on all turning sections to generate a driving trajectory.

First, in S33, the CPU 51 acquires the lane in which the vehicle will travel in the turning section based on the route information acquired in S31 (the area on the road in which the vehicle can travel if the road does not have lane divisions, or the roadway if in a parking lot).

Next, in S34, the CPU 51 obtains a start vector that specifies the position and orientation of the vehicle at the start point of the turning section when the vehicle travels along the planned travel route according to the lane movement pattern selected in S25, based on the lane on which the vehicle is traveling obtained in S33, and an end vector that specifies the position and orientation of the vehicle at the end point of the turning section.

It is desirable to set the start and end points of the turning section based on the type of the turning section (the section for which the vehicle turns). For example, as shown in FIG. 11, for a section where the road turns in an arc shape with a predetermined curvature or a section where the road turns at a predetermined angle, the start point of the turning section is a point where the curvature is equal to or greater than a threshold value or a predetermined distance before the point where the road turns, and the end point of the turning section is a point where the curvature is less than the threshold value or a predetermined distance ahead of the point where the road turns. Also, as shown in FIG. 12, for a section of an intersection (branch) where the vehicle turns right or left, the start point of the turning section is the point where the vehicle starts entering the intersection (the stop line if there is one), and the end point of the turning section is the point where the vehicle completes exiting the intersection. Also, as shown in FIG. 13, for entering a parking space, the start point of the turning section is a point on the roadway a predetermined distance before the parking space to be parked, and the parking space to be parked is the end point of the turning section. In addition, when exiting a parking space, the parking space where the vehicle is parked is set as the start point of the turning section, and a point on the roadway a predetermined distance in the direction of travel from the parking space is set as the end point of the turning section. In addition, as shown in FIG. 14, when entering a facility from a public road, the start point of the turning section is on the public road a predetermined distance before the facility's location entrance, and the end point of the turning section is a point a predetermined distance into the facility from the facility's entrance. In addition, when exiting from the facility to a public road, the start point of the turning section is a point a predetermined distance into the facility from the facility's entrance, and the end point of the turning section is a point on the public road a predetermined distance in the direction of travel from the facility's location entrance.

Here, the positions of the start vector and the end vector along the traveling direction of the road or roadway (front-rear positions) correspond to the start point and end point of the turning section described above.
On the other hand, the positions of the start and end vectors in the road width direction are basically set to the center of the lane or road on which the vehicle is traveling (which also corresponds to the center of the road for one-lane roads and roads with no lane divisions).
Furthermore, the orientation of the start vector and the end vector is basically parallel to the traveling direction of the road or road (road length direction) on the premise that the vehicle orientation is parallel to the traveling direction of the road or road at the start point and end point of the turning section. Note that, as shown in Figure 13, when a parking space is the start point or end point of the turning section, the direction is parallel to the parking space.
However, this is not the case when a special vehicle operation such as a lane change is required before a turning section, and the positions 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, and the orientation may be set at an angle to the traveling direction of the road. Figures 11 to 14 show examples of the start vector 83 and the end vector 84 set for various turning sections.

Next, in S35, the CPU 51 generates candidates for driving trajectories (hereinafter referred to as driving trajectory candidates) for which the vehicle is recommended to drive in the turning section based on the lane shape on which the vehicle drives in the turning section acquired in S33 and the regulation information on the road and the roadway. Here, in this embodiment, as the driving trajectory candidates, two types are generated: a driving trajectory candidate consisting of a straight trajectory and an arc trajectory connected to the straight trajectory (hereinafter referred to as a first driving trajectory candidate), and a driving trajectory candidate consisting of a straight trajectory, a clothoid curve connected to the straight trajectory, and an arc trajectory further connected to the clothoid curve (hereinafter referred to as a second driving trajectory candidate). However, if both the first driving trajectory candidate and the second driving trajectory candidate can be generated, both the first driving trajectory candidate and the second driving trajectory candidate are generated, but if only one of them can be generated, only the driving trajectory candidate that can be generated is generated.

Specifically, based on the shape of the lane on which the vehicle is traveling in the turning section acquired in S33, the first driving trajectory candidate and the second driving trajectory candidate are generated based on the driving trajectory candidate that can be included in the lane on which the vehicle is traveling. An example of a method for calculating the first driving trajectory candidate and the second driving trajectory candidate is described below.

[First driving trajectory candidate]
First, as shown in FIG. 15, a radius of curvature R of the arc trajectory 92 included in the first travel trajectory candidate 91 is set. This radius of curvature R may be a fixed value or a variable value. If it is a fixed value, it is set to a value at least larger than the minimum turning radius of the vehicle, for example, 5 m. If it is a variable value, it can be set based on, for example, the speed limit of the road and the shape of the lane on which the vehicle is traveling (lane width, curvature of the road, etc.). As an example, it is possible to calculate an arc with a maximum radius of curvature that passes through the start vector 83 and the end vector 84 in the traveling direction of each vector (i.e., the tangent direction of the arc coincides with the traveling direction of each vector), and to set the radius of curvature of the arc or a radius of curvature smaller than the radius of curvature by a predetermined percentage (for example, 80%).
Next, as shown in Fig. 16, the generated arc trajectory 92 is compared with the lane shape on which the vehicle runs in the turning section obtained in S33, and if the arc trajectory 92 cannot be included in the lane on which the vehicle runs as shown in the left figure, the first running trajectory candidate is determined to be inappropriate as the running trajectory on which the vehicle runs in the turning section, and the generation of the first running trajectory candidate is stopped and the generation of the second running trajectory candidate is started. On the other hand, if the arc trajectory 92 can be included in the lane on which the vehicle runs as shown in the right figure, the generation of the first running trajectory candidate is continued. However, even if the arc trajectory 92 can be included in the lane, for example, if the distance between the arc trajectory 92 and the lane or road edge located on the inside is shorter than 1/2 the vehicle width, it is expected that the vehicle will run out of the lane or road, so it is desirable to consider that the arc trajectory 92 cannot be included in the lane on which the vehicle runs. For an intersection as shown in Fig. 12, although there are no lanes within the intersection, road markings on the road surface such as guiding lines (white guide lines) and diamond-shaped guide strips (diamond marks) placed in the center of the intersection, as well as structures such as poles, are regarded as the edge of the lane, and the above judgment is made. For entering or leaving a parking space as shown in Fig. 13, the above judgment is made by considering the dividing lines separating the parking spaces as well as the dividing lines of the road as the edge of the lane. For entering or leaving a facility from a public road as shown in Fig. 14, the above judgment is made by considering the edge of the entrance of the facility facing the public road (the edge of the area between the public road and the facility where vehicles can pass) as the edge of the lane. If the presence of an obstacle can be identified, it may be a condition that the arc trajectory 92 does not overlap the obstacle.
Next, the straight trajectories 93 and 94 connected to the arc trajectory 92 arranged so as to be included in the lane on which the vehicle is traveling are calculated. For example, the straight trajectory 93 is a straight trajectory connecting the start point of the turning section (start vector 83) to the start point of the arc trajectory 92, and the straight trajectory 94 is a straight trajectory connecting the end point of the arc trajectory 92 to the end point of the turning section (end vector 84). Then, the calculated straight trajectory 93, arc trajectory 92, and straight trajectory 94 are connected to generate the final first running trajectory candidate 91. Note that the first running trajectory candidate 91 is continuous in the running position and direction of the vehicle traveling on the running trajectory (i.e., the running trajectory is a continuous line without interruption and does not bend on the way). However, as shown in the graph of FIG. 15, the change in direction (curvature) of the traveling vehicle is not continuous, and specifically, the curvature does not match before and after the connection point of each trajectory of the straight trajectory 93 and the arc trajectory 92, and the arc trajectory 92 and the straight trajectory 94. In order for the vehicle to travel along the first travel trajectory candidate 91, it is necessary to stop the vehicle once at the connection point of each trajectory and perform steering (to change the direction of the vehicle). In addition, Fig. 15 is a first travel trajectory candidate 91 for passing through a section where the road turns in an arc shape with a predetermined curvature or a section where the road turns at a predetermined angle, as shown in Fig. 11, for example, but the shape of the first travel trajectory candidate 91 is changed appropriately depending on the type of turning section. For example, in the case of the first travel trajectory candidate 91 for entering a parking space, the straight trajectory 94 is basically unnecessary. In addition, it is also possible to use a trajectory excluding the straight trajectory 91 (a trajectory starting from a circular trajectory).

[Second driving trajectory candidate]
First, as shown in FIG. 17, a radius of curvature R of the arc trajectory 96 included in the second driving trajectory candidate 95 is set. This radius of curvature R may be a fixed value like the first driving trajectory candidate 91 described above, or may be a variable value. If it is a fixed value, it is set to a value at least larger than the minimum turning radius of the vehicle, for example, 5 m. If it is a variable value, it can be set based on, for example, the speed limit of the road and the shape of the lane on which the vehicle is traveling (lane width, curvature of the road, etc.). As an example, it is possible to calculate an arc with a maximum radius of curvature that passes through the start vector 83 and the end vector 84 in the traveling direction of each vector (i.e., the tangent direction of the arc coincides with the traveling direction of each vector), and set the radius of curvature of the arc or a radius of curvature smaller than the radius of curvature by a predetermined percentage (for example, 80%).
Next, a first clothoid curve 97 is calculated, which is drawn so as to connect from a trajectory proceeding in the vehicle's travel direction at the start point of the turning section to the arc trajectory 96 with the same curvature as the arc trajectory 96, and a second clothoid curve 98 is calculated, which is drawn so as to connect to the arc trajectory 96 with the same curvature as the arc trajectory 96 and to become a trajectory proceeding in the vehicle's travel direction at the end point of the turning section. The length Lc of each clothoid curve and the clothoid constant A can be set appropriately, but for example, Lc = 9.4 m and A = 6.85. The relationship between the radius of curvature R and the clothoid curve is R x Lc = ^A2 . The clothoid curve is a curve that is drawn when the curvature is changed at a constant rate with respect to the distance (for example, if the vehicle speed is fixed, the steering angle is changed at a constant angular velocity), and the clothoid curve can be calculated by, for example, calculating the Fresnel integral using the Simpson method or an approximation formula, or by replacing it with a complex plane. The method of calculating the clothoid curve is already known, so details will be omitted.
Next, the first clothoid curve 97, the arcuate trajectory 96, and the second clothoid curve 98 are connected, and the connected trajectory (hereinafter referred to as the connected trajectory 99) is compared with the lane shape on which the vehicle runs in the turning section obtained in S33 as shown in FIG. 18. If the connected trajectory 99 cannot be included in the lane on which the vehicle runs as shown in the left figure, the second running trajectory candidate is determined to be inappropriate as the running trajectory on which the vehicle runs in the turning section, the generation of the second running trajectory candidate is stopped, and the process proceeds to S36. On the other hand, if the connected trajectory 99 can be included in the lane on which the vehicle runs as shown in the right figure, the generation of the second running trajectory candidate is continued. However, even if the connected trajectory 99 can be included in the lane, for example, if the distance between the connected trajectory 99 and the lane or road edge located on the inside is shorter than 1/2 the vehicle width, it is expected that the vehicle will run out of the lane or road, so it is desirable to consider that the connected trajectory 99 cannot be included in the lane on which the vehicle runs. For an intersection as shown in Fig. 12, although there are no lanes within the intersection, the above judgment is made by regarding road markings on the road surface, such as guiding lines (white guide lines) and diamond-shaped guide strips (diamond marks) placed in the center of the intersection, as well as structures such as poles, as the edge of the lane. For entering or leaving a parking space as shown in Fig. 13, the above judgment is made by regarding the dividing lines separating the parking spaces as well as the dividing lines of the road as the edge of the lane. For entering or leaving a facility from a public road as shown in Fig. 14, the above judgment is made by regarding the edge of the entrance of the facility facing the public road (the edge of the area between the public road and the facility where vehicles can pass) as the edge of the lane. If the presence of an obstacle can be identified, it may be a condition that the connecting track 99 does not overlap the obstacle.
Next, straight trajectories 100, 101 are calculated to connect to the connecting trajectory 99 arranged so as to be included in the lane on which the vehicle is traveling. For example, the straight trajectory 100 is a straight trajectory connecting the start point of the turning section (start vector 83) to the start point of the connecting trajectory 99, and the straight trajectory 101 is a straight trajectory connecting the end point of the connecting trajectory 99 to the end point of the turning section (end vector 84). The calculated straight trajectory 100, connecting trajectory 99, and straight trajectory 101 are then connected and linked with the same curvature to generate the final second running trajectory candidate 95. The second running trajectory candidate 95 has a continuous running position and direction of the vehicle running on the running trajectory (i.e., the running trajectory is a continuous line without interruption and does not bend along the way). Furthermore, as shown in the graph of FIG. 17, the direction change (curvature) of the traveling vehicle is also continuous, and specifically, the curvatures before and after the connection points of the straight trajectory 100 and the first clothoid curve 97, the first clothoid curve 97 and the arc trajectory 96, the arc trajectory 96 and the second clothoid curve 98, and the second clothoid curve 98 and the straight trajectory 101 are consistent, resulting in a smooth trajectory. Also, FIG. 17 shows, for example, a second traveling trajectory candidate 95 for passing through a section where the road curves in an arc shape with a predetermined curvature or a section where the road curves at a predetermined angle, as shown in FIG. 11, but the shape of the second traveling trajectory candidate 95 is changed appropriately depending on the type of turning section. For example, in the case of the second traveling trajectory candidate 95 for entering a parking space, the second clothoid curve 98 is basically not necessary in addition to the straight trajectory 101. Also, it is possible to use a trajectory excluding the straight trajectory 100 (a trajectory starting from a clothoid curve).

Whether the first and second driving trajectory candidates can be generated is determined by considering whether the first and second driving trajectory candidates can be included in the lane on which the vehicle travels, as described above, as well as the regulation information. Here, the regulation information includes information that specifies the type and location of the regulating object (regulating object) that regulates the vehicle's travel (more specifically, requires stopping or deceleration), such as the speed limit set on the road, traffic lights, pedestrian crossings, railroad crossings, and stop road signs. For example, in the turning section in which the vehicle enters or exits the facility from the public road as shown in FIG. 14, it is necessary to stop once before entering the sidewalk, so the first driving trajectory candidate, which is based on the premise that the vehicle will stop once before turning, is appropriate, while the second driving trajectory candidate, which is based on the premise that the vehicle will travel smoothly without stopping, can be determined to be inappropriate as a driving trajectory on which the vehicle travels. The same applies to the turning section in which the vehicle turns at an intersection with a stop line.

The subsequent steps S36 to S49 are performed for each driving trajectory candidate generated in S35. That is, if only the first driving trajectory candidate has been generated, only the first driving trajectory candidate is processed; if only the second driving trajectory candidate has been generated, only the second driving trajectory candidate is processed; and if both the first and second driving trajectory candidates have been generated, both the first and second driving trajectory candidates are processed.

First, in S36, the CPU 51 acquires the distance (length of the trajectory) of the driving trajectory candidate to be processed. The CPU 51 separates the straight trajectory portion, the clothoid curve portion, and the arc trajectory portion, and acquires the distance for each portion.

Next, in S37, the CPU 51 acquires an initial vehicle speed _v1 when traveling on the travel trajectory candidate to be processed. The initial vehicle speed is the vehicle speed when traveling on the straight trajectory 93 or 100 continuing from the start point (start vector 83) of the turning section, and is basically the speed limit of the road. However, it may be a speed slower than the speed limit of the road. In this embodiment, the same initial vehicle speed _v1 is also used for the vehicle speed when traveling on the straight trajectory 94 or 101 connected to the end point (end vector 84) of the turning section.

Next, in S38, the CPU 51 determines whether the candidate running trajectory to be processed includes a portion of an arcuate trajectory. In this embodiment, as shown in Figures 15 and 17, both the first running trajectory candidate and the second running trajectory candidate basically include an arcuate trajectory.

If it is determined that the candidate driving trajectory to be processed contains an arcuate trajectory portion (S38: YES), the process proceeds to S39. On the other hand, if it is determined that the candidate driving trajectory to be processed does not contain an arcuate trajectory portion (S38: NO), the process proceeds to S40.

In S39, the CPU 51 calculates an upper limit speed v a at which the vehicle can travel when traveling on the arcuate trajectory portion of the travel trajectory candidate to be processed without causing any hindrance to the automatic driving assistance and without exceeding an upper limit value (e.g., 0.2 G) that does not cause discomfort to the vehicle occupants. For example, assuming that the radius of curvature of the arcuate trajectory is R and the upper limit value of the acceleration is Grmax, the upper limit speed v a is calculated by the following formula (1).
v = √(Grmax × R) ... (1)
Then, v calculated by the above formula (1) is determined as the vehicle speed _v2 traveling on the arcuate trajectory portion of the travel trajectory candidate to be processed. However, if v exceeds the speed limit of the road or lane, the speed limit of the road is set as _v2 .

Next, in S40, the CPU 51 determines whether the candidate running trajectory to be processed includes a portion of a trajectory consisting of a clothoid curve. In this embodiment, as shown in Figures 15 and 17, basically only the second running trajectory candidate includes a portion of a trajectory consisting of a clothoid curve.

If it is determined that the candidate driving trajectory to be processed includes a portion of a trajectory consisting of a clothoid curve (S40: YES), the process proceeds to S41. On the other hand, if it is determined that the candidate driving trajectory to be processed does not include a portion of a trajectory consisting of a clothoid curve (S40: NO), the process proceeds to S45.

In S41, the CPU 51 calculates the upper limit speed vb at which the vehicle can travel when traveling on the portion of the trajectory consisting of a clothoid curve of the candidate travel trajectory to be processed without causing any disruption to the automatic driving assistance with the lateral acceleration (lateral G) generated in the vehicle and without exceeding an upper limit value (e.g., 0.2 G) that does not cause discomfort to the vehicle occupants. As shown in the graph of FIG. 17, the minimum turning radius (maximum curvature) at which the lateral acceleration is the largest in the clothoid curve is the same as that of the circular arc trajectory, so the upper limit speed vb is calculated using the same formula (1) as va (i.e., va = vb).

Next, in S42, the CPU 51 calculates the upper limit speed vc at which the vehicle can travel when traveling on a portion of the trajectory candidate to be processed that is made of a clothoid curve, without the amount of change per unit time in the lateral acceleration (lateral G) generated in the vehicle interfering with the automatic driving assistance and without exceeding an upper limit value (e.g., 0.6 m/ ^s3 ) that does not cause discomfort to the vehicle occupants. For example, assuming that the amount of change per unit time in the acceleration (lateral G) when traveling on a clothoid curve is constant, and assuming that the maximum radius of curvature of the clothoid curve is Rs, the minimum radius of curvature of the clothoid curve is Re, the upper limit of the amount of change per unit time in acceleration is dGrmax, and the length of the trajectory of the clothoid curve is Lc, the upper limit speed vc is calculated by the following formula (2).
v < ^3√ (dGrmax × Lc/(1/Re-1/Rs)) ... (2)
For example, the value of the right hand side when 1/Rs=0 is set to vc.

Furthermore, in S43, the CPU 51 calculates an upper limit speed vd at which the occupant can operate the steering wheel in a reasonable and appropriate manner when traveling on a portion of the trajectory candidate to be processed that is made up of a clothoid curve. For example, if the steering wheel operation time (which also corresponds to the traveling time on the clothoid curve) is Tc and the length of the trajectory of the clothoid curve is Lc, the upper limit speed vd is calculated by the following formula (3).
v = L / T (3)
Furthermore, if the steering angle while traveling on a clothoid curve is θh and the angular velocity of the steering is ωh (for example, one rotation/second), then Tc=θh/ωh.
Furthermore, the relationship between the tire angle θt and the radius of curvature Rc in a clothoid curve is sinθt=Wb/Rc, where Wb is the wheelbase, and the tire angle θt and the steering angle θh are proportional, and when the steering angle is at its maximum θhmax, Rc has its minimum radius Rcmin. Therefore, the maximum tire angle θtmax=arcsin(Wb/Rcmin), and the steering operation time Tc is Tc=TstMax×dθt/θtmax. Note that TstMax is the maximum time to operate the steering wheel, and for example, if the angular velocity ωh of the steering wheel operation is one rotation/second and the vehicle model allows up to two rotations, then TstMax is 2 seconds. dθt is the amount of change in the tire angle.

Thereafter, in S44, the CPU 51 determines the slowest vehicle speed among vb, vc, and vd calculated in S41 to S43 as the vehicle speed _v3 for traveling on the portion of the trajectory consisting of the clothoid curve of the traveling trajectory candidate to be processed. However, if the slowest vehicle speed exceeds the speed limit of the road or roadway, the speed limit of the road is set as _v3 . Note that the vehicle speed _v3 corresponds to the upper limit vehicle speed when traveling on the portion of the trajectory consisting of the clothoid curve of the traveling trajectory candidate to be processed, which satisfies all of the following conditions: the lateral acceleration (lateral G) generated in the vehicle does not exceed the upper limit value, the amount of change per unit time of the lateral acceleration (lateral G) generated in the vehicle does not exceed the upper limit value, and further, the occupant can operate the steering wheel appropriately without strain.

Next, in S45, the CPU 51 determines whether there is a location where the direction change of the traveling vehicle is not continuous for the traveling trajectory candidate to be processed. The location where the direction change of the traveling vehicle is not continuous is a location where the curvature (steering angle) is not continuous, and it is determined whether there is a location where the curvature (steering angle) does not match before and after each connection point of the straight trajectory, the clothoid curve, and the circular trajectory. Here, as described above, for the second traveling trajectory candidate 95 shown in FIG. 17, the curvature is consistent before and after each connection point of the straight trajectory, the clothoid curve, and the circular trajectory. On the other hand, for the first traveling trajectory candidate 91 shown in FIG. 15, the curvature is different before and after the connection point of the straight trajectory and the circular trajectory. The location where the direction change of the traveling vehicle is not continuous (location where the curvature is not continuous) is a location where the vehicle needs to stop when changing the direction of the vehicle, that is, a location where the vehicle needs to stop once and operate the steering wheel (to change the direction of the vehicle).

If it is determined that the driving trajectory candidate to be processed has a location where the direction of the traveling vehicle does not change continuously (S45: NO), that is, if the driving trajectory candidate to be processed is the first driving trajectory candidate 91, the process proceeds to S46.

In S46, the CPU 51 adds the steering operation time to the connection points where the curvatures do not match. With regard to the steering operation time Ts, if the steering angle required to match the curvatures at the connection points is θh and the angular velocity of the steering operation is ωh (for example, one rotation/second), then Ts = θh/ωh.

On the other hand, if it is determined that there is no point in the driving trajectory candidate to be processed where the direction of the traveling vehicle does not change continuously (S45: YES), that is, if the driving trajectory candidate to be processed is the second driving trajectory candidate 95, the process proceeds to S47.

In S47, the CPU 51 creates a speed plan for traveling along the candidate traveling path based on the vehicle speeds v ₁ to v ₃ for traveling along the candidate traveling path calculated by the processes in S36 to S46.

19 shows an example of a speed plan created for the first running trajectory candidate that is a combination of a straight trajectory and an arcuate trajectory. For simplicity of explanation, the speed plan up to the end point of the arcuate trajectory 92 will be described.
As shown in FIG. 19 , the speed plan for the first driving trajectory candidate is a driving plan in which the vehicle travels along a continuous straight trajectory 93 from the start point of the turning section (start vector 83) at the initial vehicle speed _v1 calculated in S37, stops at a connection point between the straight trajectory 93 and a circular trajectory 92 for the steering operation time Ts calculated in S46, and then travels along the circular trajectory 92 at the vehicle speed _v2 calculated in S39.
In the next S48, the CPU 51 sets an upper limit of acceleration (e.g., 0.2 G) for the speed plan created in S47, thereby correcting the speed plan so that the acceleration is equal to or less than the upper limit. In S49, the CPU 51 calculates the required time to travel the first travel trajectory candidate using the corrected speed plan. Note that the calculation of the required time includes the stopping time at the connection point between the straight trajectory 93 and the arc trajectory 92. For example, in the example shown in FIG. 19, the required time to travel the first travel trajectory candidate is 8.5 seconds.

20 shows an example of a speed plan created for a second running trajectory candidate consisting of a combination of a straight trajectory, a clothoid curve, and a circular arc trajectory. For simplicity of explanation, the speed plan up to the end point of the circular arc trajectory 96 will be described.
As shown in Fig. 20, the speed plan of the second running trajectory candidate is a running plan in which the vehicle runs on a straight trajectory 100 continuing from the start point (start vector 83) of the turning section at the initial vehicle speed _v1 calculated in S37, runs on the first clothoid curve 97 at a vehicle speed v3 that is the slowest vehicle speed (vb in the example shown in Fig. 20) among vb, vc, and vd calculated in S41 to _S43 without stopping at the connection point between the straight trajectory 100 and the first clothoid curve 97, and then runs on the arc trajectory 96 at a vehicle speed _v2 calculated in S39 without stopping at the connection point between the first clothoid curve 97 and the arc trajectory 96. Note that, for the second running trajectory candidate, if _v2 and _v3 are different, a condition may be added to make the speed the slower one (i.e., make the running speeds on the first clothoid curve 97 and the arc trajectory 96 the same).
In the next step S48, the CPU 51 sets an upper limit of acceleration (e.g., 0.2 G) for the speed plan created in step S47, thereby correcting the speed plan so that the acceleration is equal to or less than the upper limit. Then, in step S49, the CPU 51 uses the corrected speed plan to calculate the time required to travel along the second running trajectory candidate. For example, in the example shown in FIG. 20, the time required to travel along the second running trajectory candidate is 5.2 seconds.

Then, in S50, the CPU 51 determines the recommended running track for the vehicle in the turning section from the first running track candidate and the second running track candidate generated in S35. Specifically, the required time required to run the first running track candidate calculated in S49 is calculated as the movement cost of the first running track candidate, and the required time required to run the second running track candidate calculated in S49 is calculated as the movement cost of the second running track candidate. Then, the calculated movement costs are compared and the running track candidate with the lower movement cost is selected as the running track for the vehicle in the turning section. For example, in the example shown in FIG. 19 and FIG. 20, the movement cost of the first running track candidate is 8.5 (seconds), and the movement cost of the second running track candidate is 5.2 (seconds). Therefore, the second running track candidate with the lower movement cost is selected as the running track for the vehicle in the turning section. A lower travel cost (time required) indicates a route that places less strain on vehicle occupants and allows for smoother travel.

Then, the process proceeds to S27, where a recommended driving trajectory is generated for sections other than the turning section when driving along the recommended route derived in S25. In addition, in the speed plan generation process executed in S4 thereafter, the speed plan created in S47 and S48 can be used for the speed plan in the turning section.

If only one of the first and second driving trajectory candidates is generated in S35, the generated driving trajectory candidate is used to determine the driving trajectory recommended for the vehicle in the turning section. In this case, there is no need to perform the processes in S36 to S49.

As described above in detail, the navigation device 1 according to the present embodiment and the computer program executed by the navigation device 1 acquire a turning section in which the vehicle turns when traveling according to a planned travel route (S31 to S33), and based on the lane shape in which the vehicle travels in the turning section and the regulation information, generate either a first travel trajectory candidate consisting of a trajectory in which the traveling position and direction of the traveling vehicle are continuous, or a second travel trajectory candidate consisting of a trajectory in which the traveling position and direction of the traveling vehicle are continuously changed in direction as well as the traveling position and direction of the traveling vehicle, as a recommended travel trajectory for the vehicle in the turning section (S35), and perform driving assistance for the vehicle based on the generated travel trajectory (S9, S10). Therefore, it is possible to select a more appropriate travel trajectory that suppresses sudden turns and deceleration when traveling in the turning section from among the multiple candidates and generate it as a recommended travel trajectory for the vehicle. As a result, it is possible to perform appropriate driving assistance that does not cause a burden on the vehicle occupants.
Furthermore, among the first driving trajectory candidate and the second driving trajectory candidate, a driving trajectory candidate that can be included in the lane in which the vehicle is traveling is generated as a driving trajectory on which the vehicle is recommended to travel, so that a driving trajectory on which the vehicle is capable of traveling in accordance with the lane shape can be selected from the multiple candidates and generated as a driving trajectory on which the vehicle is recommended to travel.
In addition, a turning section where the vehicle turns when traveling according to the planned travel route is acquired (S31 to S33), a first travel trajectory candidate consisting of a trajectory where the traveling position and direction of the traveling vehicle are continuous, and a second travel trajectory candidate consisting of a trajectory where the traveling position and direction of the traveling vehicle are continuous as well as direction changes are generated, and then one of them is selected as a recommended travel trajectory for the vehicle in the turning section based on the lane shape and regulation information on which the vehicle travels in the turning section, and driving assistance for the vehicle is performed based on the generated travel trajectory (S9, S10), so that a more appropriate travel trajectory that suppresses sudden turns and deceleration when traveling in the turning section can be selected as a recommended travel trajectory for the vehicle. As a result, it is possible to perform appropriate driving assistance that does not cause a burden on the vehicle occupants.
In addition, based on the lane shape and regulation information on the lane on which the vehicle travels in the turning section, the travel cost required for the vehicle to travel on the first travel path candidate and the second travel path candidate are calculated (S49), and the calculated travel costs are compared to select a travel path recommended for the vehicle to travel on (S50), so that a travel path on which the vehicle can travel more smoothly with less burden on the vehicle occupants can be selected as the recommended travel path for the vehicle to travel on. As a result, it is possible to implement appropriate driving assistance that does not cause a burden on the vehicle occupants.
In addition, the time required to travel the first driving path candidate is calculated as the travel cost of the first driving path candidate, the time required to travel the second driving path candidate is calculated as the travel cost of the second driving path candidate, and if a portion where the direction change of the traveling vehicle is not continuous (i.e., the curvature is not continuous) is included, the travel cost of the driving path candidate including the portion is added (S46), so that it is possible to select a driving path that allows the vehicle to travel more smoothly without decelerating or stopping as a driving path recommended for vehicle travel. As a result, it is possible to implement appropriate driving assistance that does not burden the vehicle occupants.
In addition, locations where the direction of the traveling vehicle does not change continuously are locations where the vehicle needs to stop when changing direction, so it is possible to calculate the travel cost taking into account stops for travel trajectories where the vehicle needs to stop along the trajectory when traveling along the trajectory.

Incidentally, the present invention is not limited to the above-described embodiment, and it is needless to say that various improvements and modifications are possible without departing from the spirit and scope of the present invention.
For example, in this embodiment, a recommended driving trajectory is generated for a turning section where the vehicle turns when traveling along a planned traveling route, and examples of the turning section include a section where the road turns in an arc shape with a predetermined curvature, a section where the road turns at a predetermined angle such as a right angle, a section at an intersection (branch) where the vehicle turns right or left, a section where the vehicle travels in a facility such as a parking lot, a section where the vehicle turns to enter or exit a parking space, or a section where the vehicle turns to enter a facility from a public road or enter a facility from a facility to a public road, but only some of the above may be targeted as turning sections. Alternatively, other sections may be included in the turning section.

In addition, in this embodiment, the clothoid curve is calculated so as to satisfy all of the following conditions: the lateral acceleration (lateral G) acting on the vehicle does not exceed an upper limit (e.g., 0.2 G) (S41), the amount of change per unit time of the lateral acceleration (lateral G) acting on the vehicle does not exceed an upper limit (e.g., 0.6 m/ ^s3 ) (S42), and the occupant is able to operate the steering wheel in an appropriate manner without straining themselves (S43). However, it is also possible to use only some of these conditions.

In addition, in this embodiment, an example is described in which the travel cost of a travel trajectory candidate is the time required for travel, but a travel cost other than the required time may be calculated. For example, the length of the trajectory may be used as the travel cost. However, even in this case, for a travel trajectory candidate that includes a portion where the curvature does not match, such as the first travel trajectory candidate shown in FIG. 15, the travel cost is added to that portion.

In this embodiment, the first driving trajectory candidate 91 shown in Figures 15 and 19 is a driving trajectory consisting of a straight trajectory and an arc trajectory connected to the straight trajectory, but it does not necessarily have to be a trajectory that is a combination of a straight trajectory and an arc trajectory. In particular, the arc trajectory may be a curve other than an arc. However, it is preferable that the driving position and direction of the vehicle traveling on the driving trajectory are continuous (i.e., the driving trajectory is a continuous line without interruption and does not bend along the way).

In this embodiment, the second driving trajectory candidate 95 shown in Figures 17 and 20 is a driving trajectory consisting of a straight trajectory, a clothoid curve connected to the straight trajectory, and an arc trajectory further connected to the clothoid curve, but it does not necessarily have to be a trajectory that is a combination of a straight trajectory, a clothoid curve, and an arc trajectory. In particular, the arc trajectory may be a curve other than an arc, and the clothoid curve may be a curve other than a clothoid curve. However, it is desirable to have a driving trajectory in which the driving position and direction of the vehicle traveling on the driving trajectory are continuous (i.e., the driving trajectory is a continuous line without interruption and does not bend along the way), and in addition, when the direction changes, the direction change is continuous (i.e., the curvature is continuous without jumps in value).

In addition, in this embodiment, after generating the driving trajectory, vehicle control is performed to drive according to the generated driving trajectory (S9, S10), but the processing related to vehicle control from S9 onwards may be omitted. For example, the navigation device 1 may be a device that guides the user to a recommended driving trajectory without controlling the vehicle based on the driving trajectory.

In addition, in this embodiment, the lane network and parking lot network are generated using high-precision map information 16 and facility information 17 (S23), but each network targeting roads and parking lots across the country can be stored in advance in a DB and read out from the DB as needed.

In this embodiment, the high-precision map information held by the server device 4 includes both information on the lane shape of the road (road shape and curvature for each lane, lane width, etc.) and information on the dividing lines drawn on the road (center line, lane boundary, outer lane line, guiding line, etc.), but may include only information on the dividing lines, or may include only information on the lane shape of the road. For example, even if only information on the dividing lines is included, it is possible to estimate information equivalent to information on the lane shape of the road based on the information on the dividing lines. Even if only information on the lane shape of the road is included, it is possible to estimate information equivalent to information on the dividing lines based on the information on the lane shape of the road. Furthermore, the "information on the dividing lines" may be information that specifies the type and arrangement of the dividing lines themselves that divide the lanes, information that specifies whether lane changes are possible between adjacent lanes, or information that directly or indirectly specifies the shape of the lanes.

In addition, in this embodiment, as a means of reflecting the dynamic driving trajectory in the static driving trajectory, a part of the static driving trajectory is replaced with the dynamic driving trajectory (S7), but instead of replacing it, the trajectory may be corrected so that the static driving trajectory approaches the dynamic driving trajectory.

In this embodiment, the vehicle control ECU 40 has been described as controlling all of the vehicle operations related to the vehicle's behavior, including accelerator operation, brake operation, and steering operation, as automatic driving assistance for automatically driving the vehicle without the user's driving operation. However, automatic driving assistance may also be defined as the vehicle control ECU 40 controlling at least one of the vehicle operations related to the vehicle's behavior, including accelerator operation, brake operation, and steering operation. On the other hand, manual driving by the user's driving operation is described as the user performing all of the vehicle operations related to the vehicle's behavior, including accelerator operation, brake operation, and steering operation.

The driving assistance of the present invention is not limited to automatic driving assistance related to automatic driving of a vehicle. For example, it is possible to display the static driving trajectory generated in S3 or the dynamic driving trajectory generated in S6 on the navigation screen, and to provide driving assistance by providing guidance using voice, a screen, etc. (e.g., guidance on lane changes, guidance on recommended vehicle speeds, etc.). In addition, the static driving trajectory or the dynamic driving trajectory may be displayed on the navigation screen to assist the user's driving operation.

In addition, in this embodiment, the automatic driving assistance program (FIG. 4) is configured to be executed by the navigation device 1, but it may also be configured to be executed by an in-vehicle device other than the navigation device 1 or the vehicle control ECU 40. In that case, the in-vehicle device or the vehicle control ECU 40 is configured to obtain the current position of the vehicle, map information, etc. from the navigation device 1 or the server device 4. Furthermore, the server device 4 may execute some or all of the steps of the automatic driving assistance program (FIG. 4). In that case, the server device 4 corresponds to the driving assistance device of the present application.

In addition to navigation devices, the present invention can also be applied to mobile phones, smartphones, tablet terminals, personal computers, etc. (hereinafter referred to as mobile terminals, etc.). It can also be applied to a system consisting of a server and a mobile terminal, etc. In that case, each step of the above-mentioned automatic driving assistance program (see FIG. 4) may be implemented by either the server or the mobile terminal, etc. However, when applying the present invention to a mobile terminal, etc., a vehicle capable of executing automatic driving assistance and the mobile terminal, etc. must be connected in a state in which they can communicate (either wired or wireless).

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, 83...start vector, 84...end vector, 91...first driving trajectory candidate, 92...circular trajectory, 93, 94...straight trajectory, 95...second driving trajectory candidate, 96...circular trajectory, 97...first clothoid curve, 98...second clothoid curve, 99...connecting trajectory, 100, 101...straight trajectory

Claims (8)

A planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel;
a turning travel section acquisition means for acquiring a turning section along which the vehicle travels while turning when traveling along the planned travel route;
a travel trajectory generating means for generating a travel trajectory along which a vehicle is recommended to travel in the turning section based on a lane shape along which the vehicle travels in the turning section and regulation information;
a driving assistance means for providing driving assistance for a vehicle based on the traveling trajectory generated by the traveling trajectory generating means,
The running trajectory generating means
Based on the lane shape in which the vehicle is traveling in the turning section and regulation information,
A driving assistance device that generates, as a recommended driving trajectory for a vehicle, either a first driving trajectory candidate consisting of a trajectory in which the driving position and direction of a traveling vehicle are continuous, or a second driving trajectory candidate consisting of a trajectory in which directional changes are continuous in addition to the driving position and direction of the traveling vehicle. The running trajectory generating means
The driving assistance device according to claim 1 , wherein, of the first driving trajectory candidate and the second driving trajectory candidate, a driving trajectory candidate that can be included within a lane in which the vehicle is traveling is generated as a driving trajectory recommended for driving of the vehicle. A planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel;
a turning travel section acquisition means for acquiring a turning section along which the vehicle travels while turning when traveling along the planned travel route;
a travel trajectory generating means for generating a travel trajectory along which a vehicle is recommended to travel in the turning section based on a lane shape along which the vehicle travels in the turning section and regulation information;
a driving assistance means for providing driving assistance for a vehicle based on the traveling trajectory generated by the traveling trajectory generating means,
The running trajectory generating means
A first travel trajectory candidate is generated, the first travel trajectory candidate being a trajectory in which the travel position and direction of the traveling vehicle are continuous, and a second travel trajectory candidate is generated, the second travel trajectory candidate being a trajectory in which the travel position and direction of the traveling vehicle as well as direction changes are continuous,
A driving assistance device that selects one of the lane shapes along which the vehicle is traveling in the turning section and regulation information as a recommended driving path for the vehicle. The running trajectory generating means
calculating a travel cost required for the vehicle to travel on the first travel trajectory candidate and the second travel trajectory candidate based on a lane shape on which the vehicle travels in the turning section and regulation information, respectively;
The driving support device according to claim 3 , further comprising: a step of comparing the calculated travel costs to select a recommended travel path for the vehicle. The running trajectory generating means
Calculating a required time required to travel along the first travel trajectory candidate as a travel cost of the first travel trajectory candidate;
Calculating a required time required to travel along the second travel trajectory candidate as a travel cost of the second travel trajectory candidate;
The driving support device according to claim 4 , wherein when a portion where the direction change of the traveling vehicle is not continuous is included, the movement cost of a candidate traveling trajectory including the portion is added. The driving assistance device according to claim 5, wherein the location where the direction change of the traveling vehicle is not continuous is a location where the vehicle needs to stop when changing direction. Computer,
A planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel;
a turning travel section acquisition means for acquiring a turning section along which the vehicle travels while turning when traveling along the planned travel route;
a travel trajectory generating means for generating a travel trajectory along which a vehicle is recommended to travel in the turning section based on a lane shape along which the vehicle travels in the turning section and regulation information;
A computer program for causing the computer to function as a driving assistance means for providing driving assistance for a vehicle based on the driving trajectory generated by the driving trajectory generating means,
The running trajectory generating means
Based on the lane shape in which the vehicle is traveling in the turning section and regulation information,
A computer program that generates, as a recommended driving trajectory for a vehicle, either a first driving trajectory candidate consisting of a trajectory in which the driving position and direction of a traveling vehicle are continuous, or a second driving trajectory candidate consisting of a trajectory in which directional changes are continuous in addition to the driving position and direction of a traveling vehicle. Computer,
A planned driving route acquisition means for acquiring a planned driving route along which the vehicle will travel;
a turning travel section acquisition means for acquiring a turning section along which the vehicle travels while turning when traveling along the planned travel route;
a travel trajectory generating means for generating a travel trajectory along which a vehicle is recommended to travel in the turning section based on a lane shape along which the vehicle travels in the turning section and regulation information;
A computer program for causing the computer to function as a driving assistance means for providing driving assistance for a vehicle based on the driving trajectory generated by the driving trajectory generating means,
The running trajectory generating means
A first travel trajectory candidate is generated, the first travel trajectory candidate being a trajectory in which the travel position and direction of the traveling vehicle are continuous, and a second travel trajectory candidate is generated, the second travel trajectory candidate being a trajectory in which the travel position and direction of the traveling vehicle as well as direction changes are continuous,
A computer program that selects, based on the shape of the lane on which the vehicle is traveling in the turning section and regulation information, one of the lane shapes as a recommended driving path for the vehicle.

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