Driving support device

Abstract

To provide a driving support device capable of preventing user's movement after getting off a vehicle from significantly inhibiting traveling of the vehicle while providing a parking space appropriate to the user.SOLUTION: A driving support device is configured to: acquire parking lot information about a parking lot belonging to a user's destination; acquire parking spaces where a vehicle can park in the parking lot; acquire a movement path for allowing the user to move to a destination after getting off the vehicle for each parking space where the vehicle can park; calculate movement cost required for the movement of the movement path on the basis of the parking lot information and the movement path; and select a parking space to park the vehicle by using the calculated movement cost; and meanwhile in the case that the movement path is a path that crosses an area where vehicles travel, acquire a congestion degree of vehicles at a crossing point and calculates movement cost by considering the congestion degree.SELECTED DRAWING: Figure 15

Description

[Technical Field]

[0001] The present invention relates to a driving assistance device that assists driving of a vehicle. [Background technology]

[0002] When a vehicle travels to a destination, it is generally necessary to drive to a parking lot attached to the premises of the destination or a parking lot in the vicinity of the destination, park the vehicle, and then walk or otherwise travel from the parking space in the parking lot to the destination. In particular, when there are multiple parking locations available within the parking lot, the burden on the user varies significantly depending on the parking location, so it is extremely important to select an appropriate parking location for the vehicle. For example, Japanese Patent Application Laid-Open No. 2009-92586 discloses a technology that, when a user inputs a destination, searches for parking lots with available parking spaces near the destination, and determines a recommended parking space for the vehicle by taking into account not only the cost of moving the vehicle to the available parking space but also the cost of walking from the available parking space to the destination. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2009-92586 A (paragraphs 0041-0050) Summary of the Invention [Problem to be solved by the invention]

[0004] Here, the walking route to the destination after parking the vehicle in a parking lot may cross an area where vehicles travel (such as a public road or an on-site passageway for vehicles to travel). In the above-mentioned Patent Document 1, the vehicle parking space is selected taking into consideration the burden on the user related to travel after getting off the vehicle, but does not take into consideration the crossing of an area where vehicles travel as described above. Therefore, if a parking space is available near the destination, that parking space will be given priority in guidance even if it requires the user to cross an area where vehicles travel to reach the destination after parking.

[0005] As a result, situations arise where pedestrians traveling to their destinations significantly impede vehicle movement, resulting in problems such as traffic jams at crossing points.

[0006] The present invention has been made to solve the above-mentioned problems in the conventional technology, and aims to provide a driving assistance device that, in cases where the route to the destination after disembarking the vehicle at a parking space crosses the area in which the vehicle is traveling, calculates the cost taking into account the degree of vehicle congestion at the crossing point, thereby providing an appropriate parking space for the user while preventing the vehicle's travel from being significantly hindered by the user's movement after disembarking the vehicle. [Means for solving the problem]

[0007] In order to achieve the above object, the driving assistance device of the present invention comprises: a parking lot information acquisition means for acquiring parking lot information relating to a parking lot belonging to a user's destination; a parking space acquisition means for acquiring parking spaces within the parking lot where a vehicle can be parked; a travel route acquisition means for acquiring, for each parking space where the vehicle can be parked, a travel route for the user to travel to the destination after getting off the vehicle; a cost calculation means for calculating a travel cost required to travel along the travel route based on the parking lot information and the travel route; and a parking space selection means for selecting a parking space where the vehicle will be parked using the travel cost calculated by the cost calculation means, When the travel route is a route that crosses an area in which the vehicle travels, the cost calculation means acquires a degree of traffic congestion for the vehicle at a crossing point, and calculates the travel cost taking the degree of traffic congestion into consideration. In addition, "parking lots belonging to the destination" includes dedicated parking lots attached to the premises of the destination, affiliated parking lots outside the premises of the destination, as well as parking lots that are not dedicated parking lots or affiliated parking lots but are located in the vicinity of the destination and allow transportation to the destination after parking there. [Effects of the Invention]

[0008] According to the driving assistance device of the present invention having the above configuration, if the route to the destination after disembarking the vehicle at a parking space is a route that crosses the area in which the vehicle is traveling, the cost is calculated taking into account the degree of vehicle congestion at the crossing point, and the calculated cost is used to select a parking space in which to park the vehicle.This makes it possible to provide an appropriate parking space for the user while preventing the vehicle's travel from being significantly hindered by the user's movement after disembarking the vehicle. [Brief explanation of the drawings]

[0009] [Figure 1] 1 is a schematic configuration diagram showing a driving assistance system according to an embodiment of the present invention; [Figure 2] 1 is a block diagram showing the configuration of a driving assistance system according to an embodiment of the present invention. [Figure 3] 1 is a block diagram showing a navigation device according to an embodiment of the present invention; [Figure 4] 4 is a flowchart of an autonomous driving assistance program according to the present embodiment. [Figure 5] FIG. 2 is a diagram showing an area for which high-precision map information is acquired. [Figure 6] FIG. 10 is a diagram showing an example of a static travel trajectory. [Figure 7] FIG. 10 is a diagram illustrating a method for calculating a dynamic traveling trajectory. [Figure 8] 10 is a flowchart of a sub-processing program of the parking position determination process. [Figure 9] FIG. 1 is a diagram illustrating an example of an in-facility network. [Figure 10] FIG. 1 is a diagram showing an example of a pedestrian network in a parking lot. [Figure 11] 10 is a diagram showing walking nodes and walking links set for a parking space. FIG. [Figure 12] FIG. 1 is a diagram illustrating an example of an in-facility walking network. [Figure 13] FIG. 10 is a diagram showing an example of an in-facility walking network constructed when the destination is one of the tenants in a commercial complex. [Figure 14] FIG. 1 is a diagram illustrating a traffic jam that occurs starting from a crossing point. [Figure 15] FIG. 10 is a diagram illustrating a method for identifying a parking space where parking is recommended. [Figure 16] 10 is a flowchart of a sub-processing program of the parking space selection reason presentation processing. DETAILED DESCRIPTION OF THE INVENTION

[0010] 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 below with reference to the drawings. First, a schematic configuration of a driving assistance system 2 including a navigation device 1 according to this embodiment will be described with reference to Fig. 1 and Fig. 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.

[0011] As shown in Fig. 1, a 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 autonomous driving of the vehicle 5. The server device 4 and the navigation device 1 are configured to be able to send and receive electronic data to and from 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.

[0012] Here, vehicle 5 is a vehicle capable of manual driving, in which the vehicle drives 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.

[0013] Furthermore, autonomous driving assistance may be provided for all road sections, or may be configured to 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 in which autonomous driving assistance is provided includes all road sections, including general roads and highways, as well as parking lots, and the explanation will be given assuming that autonomous driving assistance is basically provided from the time the vehicle starts traveling until it ends traveling (until the vehicle is parked). However, autonomous driving assistance is not always provided when the vehicle is traveling 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, vehicle 5 may be a vehicle capable of only assisted traveling using autonomous driving assistance.

[0014] In vehicle control in automated driving assistance, for example, the current position of the vehicle, the lane the vehicle is traveling on, and the positions of surrounding obstacles are detected at any time, and vehicle control such as steering, drive source, and braking is automatically performed so that the vehicle travels at a speed according to a speed plan generated along a travel trajectory generated by the navigation device 1, as will be described later. Note that in assisted driving by automated driving assistance in this embodiment, lane changes, right and left turns, and parking operations are also performed automatically by the automated driving assistance, but special driving such as lane changes, right and left turns, and parking operations may be performed by manual driving without automated driving assistance.

[0015] On the other hand, the navigation device 1 is an on-board device that is mounted on the vehicle 5 and displays a map of the area around the vehicle's position based on map data stored in 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 assistance information related to autonomous driving assistance are generated, particularly when the vehicle is performing assisted driving using autonomous driving assistance. Examples of assistance information include a recommended driving trajectory for the vehicle (including recommended lane movement patterns), selection of a parking space 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.

[0016] The server device 4 is also capable of executing a route search in response to a request from the navigation device 1. Specifically, information necessary for a route search, such as the departure point and destination, is transmitted 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 about the destination does not necessarily need to be transmitted). Upon receiving the route search request, the server device 4 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. The identified recommended route is then transmitted to the navigation device 1 that issued the request. The navigation device 1 can then provide the received information about the recommended route to the user, or use the recommended route to generate various types of assistance information related to autonomous driving assistance, as will be described later.

[0017] Furthermore, the server device 4 stores high-precision map information and facility information, which are more accurate map information, in addition to the normal map information used in the above-mentioned route search. The high-precision map information includes, for example, information on road lane shapes (road shapes and curvatures for each lane, lane width, etc.) and road markings (road center lines, lane boundaries, road outside lines, guiding lines, etc.). It also includes information on features such as traffic lights, crosswalks, and footbridges. It also includes information on intersections, etc. On the other hand, facility information is more detailed information on facilities stored separately from the information on facilities included in the map information, and includes, for example, a floor map of the facility, information on the entrance to the parking lot, layout information on the aisles and parking spaces provided in the parking lot, and the marking lines that divide the parking spaces. The high-precision map information includes information about the location of a parking lot, connection information indicating the connection between the entrance to the parking lot and the lanes, etc. The server device 4 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 assistance, as will be described later, using the high-precision map information and facility information distributed from the server device 4. Note that the high-precision map information is basically map information that covers only roads (links) and their surrounding areas, but it may also be map information that includes areas other than the areas around the roads.

[0018] However, the above-described route search process does not necessarily have to be performed by the server device 4, and may be performed by the navigation device 1 as long as the navigation device 1 has map information. Also, the high-precision map information and facility information may not be distributed from the server device 4, but may be stored in the navigation device 1 in advance.

[0019] 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 communications between communication companies, and are also end points of the communication network 6, and have the role of relaying communications between the navigation device 1 within the range (cell) of the base station's radio waves and the server device 4.

[0020] 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 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.

[0021] 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 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 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, which will be described later.

[0022] On the other hand, 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 includes 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, and search data for searching for points.

[0023] The high-precision map DB 13 is also 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 on roads and facilities on which vehicles travel, and in this embodiment, for roads, for example, it includes information on 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 of the road, guiding lines, etc.). When features such as traffic lights, crosswalks, and footbridges are installed, it also includes information specifying the type and position of the installed features. Furthermore, it includes data indicating road gradients, cants, banks, merging sections, areas where the number of lanes decreases, areas where the width narrows, railroad crossings, etc.; and for corners, data indicating the radius of curvature, intersections, T-junctions, entrances and exits of corners, etc. Regarding road attributes, data indicating downhill roads, uphill roads, etc. are recorded, and regarding road types, data indicating 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 are recorded. Furthermore, information regarding lane markings is stored that specifies which types of lane markings are arranged on the road. In particular, in this embodiment, in addition to the number of lanes on the road, information specifying the traffic divisions in the direction of travel for each lane and the connections between the roads (specifically, the correspondence between the lanes included in the road before passing through an intersection and the lanes included in the road after passing through the intersection) is also stored. Furthermore, the speed limit set for the road is also stored.

[0024] Meanwhile, 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, particularly for parking lots (including both parking lots attached to facilities and stand-alone parking lots) where vehicles are to be parked, information identifying the location of the parking lot entrances and exits, information identifying the layout of parking spaces within the parking lot, information on the demarcation lines separating the parking spaces, and information on the paths accessible by vehicles and pedestrians. For facilities other than parking lots, information identifying a floor map of the facility is also included. The floor map includes, for example, information identifying the locations of entrances and exits, paths, stairs, elevators, and escalators. Furthermore, in the case of a multi-tenant commercial complex, information identifying the location of each tenant occupying the facility is also included. The facility information 17 may be information generated using a 3D model of the parking lot or facility. Furthermore, the facility DB 14 also includes connection information 18 indicating the connection relationship between the lanes included in the approach road facing the parking lot entrance and the parking lot entrance, and road outline shape information 19 specifying the area accessible by vehicles between the approach road and the parking lot entrance. Details of the information stored in the facility DB 14 will be described later.

[0025] Although the high-precision map information 16 is basically map information that covers only roads (links) and their surrounding areas, it may also be map information that includes areas other than the surrounding areas of the roads. Furthermore, 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 also be part of the server-side map information. Furthermore, the high-precision map DB 13 and facility DB 14 may not be separated but may be a single database.

[0026] On the other hand, the server-side communication device 15 is a communication device for communicating with the navigation device 1 of each vehicle 5 via the communication network 6. In addition to the navigation device 1, it is also possible to receive traffic information including congestion information, regulation information, traffic accident information, etc. transmitted from the Internet network or a traffic information center, such as a VICS (registered trademark: Vehicle Information and Communication System) center.

[0027] 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.

[0028] 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 is 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 about the guide route (planned route of the vehicle) set in the navigation device 1, a speaker 36 that outputs audio guidance regarding the route guide, a DVD drive 37 that reads a DVD as a storage medium, and a communication module 38 that communicates with an information center such as a probe center or a VICS center. The navigation device 1 is also 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, which performs various controls for the vehicle in which the navigation device 1 is installed, so as to be able to carry out two-way communication.

[0029] Each of the components of the navigation device 1 will be explained 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 traveling speed, current time, etc. Here, the vehicle speed sensor 42 in particular is a sensor for detecting the vehicle's travel distance and speed, and generates pulses in response to the rotation of the vehicle's drive wheels and outputs the pulse signals to the navigation ECU 33. The navigation ECU 33 then calculates the rotation speed of the drive wheels and travel distance by counting the generated pulses. Note that the navigation device 1 does not need to be equipped with all four types of sensors described above, and the navigation device 1 may be configured to be equipped with only one or more of these types of sensors.

[0030] 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, predetermined programs, etc. recorded on the hard disk and writing predetermined data to the hard disk. Note that 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 addition, 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 needed.

[0031] 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 for processing related to route search and change, facility data related to facilities, map display data for displaying maps, intersection data related to each intersection, search data for searching for points, etc.

[0032] 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 exterior shape information 19 that have been distributed from the server device 4 in the past. The storage period can be set as appropriate, for example, it may be a predetermined period (e.g., one month) from the time of storage, or it may be until the vehicle's ACC power supply (accessory power supply) is turned off. Furthermore, once the amount of data stored in the cache 46 reaches an upper limit, the oldest data may be deleted sequentially. Then, the navigation ECU 33 generates various types of assistance information related to autonomous driving assistance using the high-precision map information 16, facility information 17, connection information 18, and road exterior shape information 19 stored in the cache 46. Details will be described later.

[0033] Meanwhile, the navigation ECU (Electronic Control Unit) 33 is an electronic control unit that controls the entire navigation device 1. It includes internal storage devices 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 and the like when a route is searched, a ROM 53 that stores control programs as well as an automated driving assistance program (see FIG. 4 ) described below, and a flash memory 54 that stores programs read from the ROM 53. The navigation ECU 33 also includes various processing algorithms. For example, a parking lot information acquisition means acquires parking lot information about parking lots belonging to the user's destination. A parking space acquisition means acquires parking spaces within the parking lot where the vehicle can be parked. A travel route acquisition means acquires, for each parking space where the vehicle can be parked, a travel route for the user to travel to the destination after getting off the vehicle. A cost calculation means calculates the travel cost for traveling along the travel route based on the parking lot information and the travel route. A parking space selection means selects a parking space where the vehicle will be parked using the travel cost calculated by the cost calculation means.

[0034] The operation unit 34 is operated when inputting a departure point as a starting point of a trip and a destination point as a destination of a trip, and has a plurality 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 surface of the liquid crystal display 35. It may also have a microphone and a voice recognition device.

[0035] 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.

[0036] The speaker 36 also outputs voice guidance for guiding the vehicle along a guide route (planned travel route) based on instructions from the navigation ECU 33, and traffic information guidance.

[0037] The DVD drive 37 is a drive that can read data recorded on a recording medium such as a DVD or CD. 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 data to a memory card may be provided.

[0038] The communication module 38 is a communication device for receiving traffic information, probe information, parking space availability 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.

[0039] The exterior camera 39 is composed of a camera using a solid-state image sensor such as a CCD, and is mounted above the vehicle's front bumper with its optical axis oriented downward at a predetermined angle from the horizontal. The exterior camera 39 captures images of the area ahead of the vehicle when the vehicle is traveling in an autonomous driving zone. The navigation ECU 33 processes the captured images to detect obstacles, such as lane markings on the road the vehicle is traveling on and other vehicles in the vicinity, and generates various assistance information related to autonomous driving assistance based on the detection results. For example, if an obstacle is detected, the navigation ECU 33 generates a new driving trajectory to avoid or follow the obstacle. The exterior camera 39 may be positioned at the rear or side of the vehicle, in addition to the front. Instead of a camera, sensors such as millimeter-wave radar or laser sensors, or vehicle-to-vehicle communication or road-to-vehicle communication may be used to detect obstacles.

[0040] The vehicle control ECU 40 is an electronic control unit that controls the vehicle equipped with the navigation device 1. The vehicle control ECU 40 is connected to each drive unit of the vehicle, such as the steering, brakes, and accelerator, and in this embodiment, after automatic driving assistance has started in the vehicle, the vehicle control ECU 40 controls each drive unit 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.

[0041] Here, after starting to drive, the navigation ECU 33 transmits various types of assistance information related to the automatic driving assistance generated by the navigation device 1 to the vehicle control ECU 40 via the CAN. Then, the vehicle control ECU 40 uses the received various types of assistance information to implement the automatic driving assistance after starting to drive. Examples of the assistance information include a recommended driving path for the vehicle, a driving route, and a driving direction. There are speed plans that show the actual vehicle speed.

[0042] Next, an 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 starts traveling with automatic driving assistance after the ACC power supply (accessory power supply) of the vehicle is turned on, 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 Figs. 4, 8, and 16 below are stored in the RAM 52 and ROM 53 provided in the navigation device 1, and are executed by the CPU 51.

[0043] First, in step (hereinafter abbreviated as S) 1 of the autonomous driving assistance program, the CPU 51 acquires the vehicle's destination. Essentially, the destination is set by a user's operation received by the navigation device 1. The destination may be a parking lot, a location other than a parking lot, or any location on a map. However, if the destination is a facility other than a parking lot, a parking lot belonging to the destination is also acquired as a parking lot where the user will park at the destination. The "parking lot belonging to the destination" may be a dedicated parking lot attached to the premises of the destination or an affiliated parking lot outside the premises of the destination, if such a parking lot is available. On the other hand, if there is no dedicated parking lot or affiliated parking lot, or if such a parking lot is full, a parking lot near the destination from which the user can park and then move to the destination is considered the "parking lot belonging to the destination." If there are multiple "parking lots belonging to the destination," all of the multiple parking lots may be acquired as parking lots where the user will park, or any parking lot selected by the user may be acquired as parking lots where the user will park.

[0044] Next, in S2, the CPU 51 acquires a driving route for reaching the destination from the current position of the vehicle. If the destination is a facility other than a parking lot, the CPU 51 acquires the driving route for reaching the parking lot where the user will park, which was acquired in S1. Multiple driving routes may be acquired. For large parking lots with multiple entrances, it is desirable to acquire multiple driving routes that reach each entrance. If multiple driving routes are acquired, they are compared when generating a static driving trajectory (S8), which will be described later, and ultimately identified as a single driving route.

[0045] In this embodiment, the driving route is searched for particularly by the server device 4. When searching for a driving route, the CPU 51 first transmits 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 location of the vehicle), the destination, and the parking lot where the user will park (the entrance to the parking lot, if it can be identified). The CPU 51 then receives searched route information transmitted 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 driving route) that identifies the driving route from the starting point to the destination or the parking lot where the user will park, which is searched for by the server device 4 using the latest version of map information based on the transmitted route search request. The searched route information is information that identifies the driving route (e.g., a series of links included in the driving route) for reaching the destination or the parking lot where the user will park, which is searched for by the server device 4 using the latest version of map information. For example, the search is performed using the well-known Dijkstra algorithm. However, the driving route may be searched for by the navigation device 1 instead of the server device 4.

[0046] In addition, the server device 4 refers to connection information 18 that indicates the connection relationship between the lanes included in the road facing the entrance to the parking lot where the user will park (hereinafter referred to as the access road) and the entrance to the parking lot, and if the possible directions of travel to enter the parking lot from the access road are limited (for example, only entry by turning left is possible), the server device 4 searches for the above-mentioned driving route while also taking into account the access direction.

[0047] Next, in S3, the CPU 51 acquires high precision map information 16 for an area including the vehicle travel route acquired in S2.

[0048] Here, the high precision map information 16 is divided into rectangular shapes (for example, 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 62 is acquired as the vehicle's driving route as shown in Fig. 5, high precision map information 16 is acquired for areas 63 to 66 that include the route 62. However, if the distance to the parking lot where the user will park 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 (for example, within 3 km) from the vehicle's current position.

[0049] The high-precision map information 16 includes, for example, information about the lane shapes of roads and the dividing lines painted on the roads (roadway center lines, lane boundaries, roadway outer lines, guiding lines, etc.). It also includes information about intersections, parking lots, etc. The high-precision map information 16 is basically acquired from the server device 4 in units of the rectangular areas described above, but if high-precision map information 16 for an area is already stored in the cache 46, it is acquired from the cache 46. The high-precision map information 16 acquired from the server device 4 is temporarily stored in the cache 46.

[0050] In S3, the CPU 51 also acquires facility information 17 for the destination and the parking lot where the user will park. In addition, the CPU 51 similarly acquires connection information 18 that indicates the connection relationship between the lanes included in the approach road facing the entrance of the parking lot where the user will park and the entrance of the parking lot, and road outer shape information 19 that specifies the area where a vehicle can pass between the approach road and the entrance of the parking lot where the user will park.

[0051] The facility information 17 includes, for example, information specifying the location of the entrance and exit of a parking lot, information specifying the layout of parking spaces within the parking lot, information about the lines dividing the parking spaces, and information about the paths that vehicles and pedestrians can use. For facilities other than parking lots, information specifying a floor map of the facility is included. The floor map includes, for example, information specifying the locations of entrances and exits, paths, stairs, elevators, and escalators. In addition, in a commercial complex with multiple tenants, information specifying the location of each tenant is included. The facility information 17 may be information generated using a 3D model of the parking lot or facility. Furthermore, the facility information 17, connection information 18, and road shape information 19 are basically acquired from the server device 4, but if the corresponding information is already stored in the cache 46, they are acquired from the cache 46. Furthermore, the facility information 17, connection information 18, and road shape information 19 acquired from the server device 4 are temporarily stored in the cache 46.

[0052] Next, in S4, the CPU 51 acquires the current position of the vehicle detected by the current position detection unit 31. It is desirable to identify the current position of the vehicle in detail using, for example, high-precision GPS information or high-precision location technology. Here, high-precision location technology is a technology that detects white lines and road paint information captured by a camera installed in the vehicle using image recognition, and further compares the detected white lines and road paint information with, for example, high-precision map information 16, thereby making it possible to detect the traveling lane and the vehicle position with high precision. Furthermore, if the vehicle is traveling on a road with multiple lanes, the lane in which the vehicle is traveling is also identified.

[0053] Next, in S5, the CPU 51 determines whether the destination of the vehicle acquired in S1 is a facility (excluding a parking lot). The destination is not a facility when, for example, a parking lot or an arbitrary point on a road is set as the destination.

[0054] If it is determined that the vehicle's destination acquired in S1 is a facility (S5: YES), the process proceeds to S6. On the other hand, if it is determined that the vehicle's destination acquired in S1 is not a facility (S5: NO), the process proceeds to S8. If the destination is a parking lot, the parking position determination process in S7, which will be described later, is not performed, and a parking space that is easy for the user to park in (for example, a parking space close to the parking lot entrance, a parking space with no other vehicles parked on either side, etc.) is determined as the parking position where the user will park.

[0055] In S6, the CPU 51 determines, based on the current vehicle position acquired in S4 and the facility information 17, whether the current vehicle position is located on a road within the facility that is the destination or in a parking lot where the user will park.

[0056] If it is determined that the current location of the vehicle is on a road within the facility that is the destination or in a parking lot where the user will park (S6: YES), the process proceeds to S7. On the other hand, if it is determined that the current location of the vehicle is not on a road within the facility that is the destination or in a parking lot where the user will park (S6: NO), the process proceeds to S8.

[0057] In S7, the CPU 51 executes a parking position determination process (FIG. 8) to be described later. The parking position determination process is a process for determining a parking position (parking space) recommended for the user to park in the parking lot where the user parks, obtained in S1, by taking into consideration the vehicle's driving route to the parking position, the route the user will take to move to the destination after parking the vehicle in the parking lot, and also the influence of other vehicles on the user's movement to the destination.

[0058] Then, in S8, the CPU 51 generates a static driving trajectory, which is a driving trajectory recommended for the vehicle when traveling along the driving route acquired in S2, based on the high-precision map information 16, facility information 17, connection information 18, and road exterior shape information 19 acquired in S3. The static driving trajectory includes a first driving trajectory recommended for the vehicle along the lane from the driving start point to the approach road facing the parking lot entrance, a second driving trajectory recommended for the vehicle from the approach road to the parking lot entrance, and a third driving trajectory recommended for the vehicle from the parking lot entrance to the parking space where the vehicle will be parked. In particular, the third driving trajectory is generated for the driving trajectory to the parking space determined in the parking position determination process in S7. Furthermore, the vehicle's driving route from the parking lot entrance to the parking space, which serves as the basis for generating the third driving trajectory, is determined in the parking position determination process in S7 along with the parking space where the vehicle will be parked. Therefore, only the first and second driving trajectories may be generated until the vehicle is located on a road within the facility that is the destination or in the parking lot where the user will be parking. Furthermore, if the distance to the parking lot where the user will park is particularly far, only the first driving trajectory may be generated for a section from the current position of the vehicle to a predetermined distance ahead in the direction of travel (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 area outside the range (detection range) where the road conditions around the vehicle can be detected by the external camera 39 or other sensors.

[0059] The static driving trajectory generated in S8 is not only information that identifies the road on which the vehicle will travel, but also information that specifically identifies which lane the vehicle will travel on and what driving trajectory it will travel on within the road (lane movement pattern). Figure 6 shows an example of the static driving trajectory generated in S8. The static driving trajectory shown in Figure 6 is a driving trajectory in which the vehicle travels straight from its current position, turns right at the next intersection 71, enters the right lane, then changes lanes to the right and moves into a right-turn-only lane, then turns right at the next intersection 72, enters the left lane, turns left into a parking lot 73 where parking is to be performed, and moves to a parking position 74.

[0060] In addition, the static driving trajectory generated in S8 also contains information specifying the specific location of the lane change if a lane change is required. For example, for a driving trajectory in a section requiring lane changes, the lane change location is set so that lane changes are minimized and performed as far away from intersections as possible. Furthermore, when generating a driving trajectory for turning right or left at an intersection or changing lanes, the lateral acceleration (lateral G) acting on the vehicle is calculated, and a trajectory that connects the forces as smoothly as possible is calculated using a clothoid curve or a circular arc, provided that the lateral G does not exceed an upper limit (e.g., 0.2 G) that does not interfere with automated driving assistance or cause discomfort to vehicle occupants. By performing the above processing, a static driving trajectory is generated, which is a driving trajectory recommended for the vehicle from its current position to the parking position determined in S7.

[0061] Next, in S9, the CPU 51 generates a speed plan for the vehicle when traveling along the static traveling track generated in S8, based on the high-precision map information 16 acquired in S3. For example, the CPU 51 calculates a recommended traveling speed for the vehicle when traveling along the static traveling track, taking into consideration speed limit information and speed change points (e.g., intersections, curves, railroad crossings, crosswalks, etc.) on the planned traveling route.

[0062] The speed plan generated in S9 is stored in the flash memory 54 or the like as support information to be used for the automatic driving support. In addition, an acceleration plan indicating the acceleration / deceleration of the vehicle required to realize the speed plan generated in S9 may also be generated as support information to be used for the automatic driving support.

[0063] Next, in S10, the CPU 51 performs image processing on the image captured by the exterior camera 39 to determine whether there are any factors, particularly factors around the vehicle, that may affect the vehicle's travel. The "factors that may affect the vehicle's travel" determined in S10 are dynamic factors that change in real time, excluding static factors based on road structure. For example, these factors include other vehicles traveling or parked ahead of the vehicle, pedestrians ahead of the vehicle, and construction zones ahead of the vehicle. On the other hand, intersections, curves, railroad crossings, merging sections, and lane-narrowing sections are excluded. Even if other vehicles, pedestrians, or construction zones exist, they are excluded from the "factors that may affect the vehicle's travel" if they are unlikely to overlap with the vehicle's future travel path (e.g., if they are located far from the vehicle's future travel path). Instead of cameras, sensors such as millimeter-wave radar or laser sensors, vehicle-to-vehicle communication, or road-to-vehicle communication may be used to detect factors that may affect the vehicle's travel.

[0064] 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 S10.

[0065] If it is determined that there is a factor in the vicinity of the host vehicle that may affect the running of the host vehicle (S10: YES), the process proceeds to S11. On the other hand, if it is determined that there is no factor in the vicinity of the host vehicle that may affect the running of the host vehicle (S10: NO), the process proceeds to S14.

[0066] In S11, the CPU 51 generates a new trajectory as a dynamic driving trajectory for returning from the current position of the vehicle to the static driving trajectory by avoiding or following the "factors that may affect the driving of the vehicle" detected in S10. The dynamic driving trajectory is generated for a section including the "factors that may 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 may affect the driving of the vehicle" is another vehicle (forward vehicle) driving in front of the vehicle, as shown in FIG. 7, the vehicle changes lanes to the right to overtake the forward vehicle 78, and then An avoidance trajectory, which is a trajectory in which the vehicle changes lanes to the left and returns to the original lane, is generated as the dynamic traveling trajectory 79. Note that a following trajectory, which is a trajectory in which the vehicle follows the vehicle 78 in front a predetermined distance behind the vehicle 78 in front (or travels parallel to the vehicle 78 in front) without overtaking the vehicle 78 in front, may be generated as the dynamic traveling trajectory.

[0067] To explain this using the calculation method of the dynamic driving trajectory 79 shown in Figure 7 as an example, the CPU 51 first calculates a first trajectory L1 required for the vehicle to start turning the steering wheel and move to the right lane, and then return the steering wheel position to a straight-ahead direction. The first trajectory L1 is calculated by calculating the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current speed, and then calculating a trajectory using a clothoid curve or a circular arc that is as smooth as possible and minimizes the distance required for changing lanes, under the condition 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. Another condition is that an appropriate inter-vehicle distance D or more must be maintained between the vehicle and the preceding vehicle 78. Next, a second trajectory L2 is calculated, which is the trajectory for traveling in the right lane at the upper limit of the speed limit to overtake the preceding vehicle 78 and maintain an appropriate inter-vehicle distance D or more between the preceding vehicle 78. The second trajectory L2 is basically a straight trajectory, and the length of the trajectory is calculated based on the speed of the preceding vehicle 78 and the speed limit of the road. Next, a third trajectory L3 is calculated, which is required to start turning the steering wheel and return to the left lane, and to return the steering position to a straight-ahead direction. The third trajectory L3 is calculated by calculating the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current speed, and using a clothoid curve or a circular arc, calculates a trajectory that is as smooth as possible and minimizes the distance required for the lane change, on the condition that the lateral G does not interfere with the automated driving assistance and does not exceed an upper limit (e.g., 0.2 G) that does not cause discomfort to the vehicle occupants. Another condition is that an appropriate inter-vehicle distance D or more must be maintained between the vehicle and the preceding vehicle 78. Furthermore, since the dynamic driving trajectory is generated based on the road conditions around the vehicle acquired 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.

[0068] Next, in S12, the CPU 51 reflects the dynamic driving trajectory newly generated in S11 on the static driving trajectory generated in S8. Specifically, the CPU 51 calculates the costs of the static driving trajectory and the dynamic driving trajectory from the current vehicle position to the end of the section including the "factors that affect the vehicle's driving," and selects the driving trajectory with the smallest cost. As a result, part of the static driving trajectory is replaced with the dynamic driving trajectory as needed. Note that, depending on the situation, the dynamic driving trajectory may not be replaced, i.e., the static driving trajectory generated in S8 may not change even if the dynamic driving trajectory is reflected. Furthermore, if the dynamic driving trajectory and the static driving trajectory are the same trajectory, the static driving trajectory generated in S8 may not change even if the dynamic driving trajectory is replaced.

[0069] Next, in S13, the CPU 51 corrects the vehicle speed plan generated in S9 based on the content of the reflected dynamic trajectory for the static trajectory after the dynamic trajectory has been reflected in S12. Note that if the static trajectory generated in S8 remains unchanged as a result of reflecting the dynamic trajectory, the process of S13 may be omitted.

[0070] Next, in S14, the CPU 51 calculates control amounts for the vehicle to travel on the static traveling trajectory generated in S8 (or the trajectory after reflection if the dynamic traveling trajectory has been reflected in S12) at a speed in accordance with the speed plan generated in S9 (or the revised plan if the speed plan has been revised in S13). Specifically, control amounts for the accelerator, brake, gear, and steering are calculated. Note that the processing of S14 and S15 may be performed by the vehicle control ECU 40 that controls the vehicle, rather than the navigation device 1.

[0071] Thereafter, in S15, the CPU 51 reflects the control amount calculated in S14. Specifically, the calculated control amount is transmitted to the vehicle control ECU 40 via the CAN. The vehicle control ECU 40 performs vehicle control of the accelerator, brake, gear, and steering based on the received control amount. As a result, driving assistance control is possible in which the vehicle travels along the static driving trajectory generated in S8 (or the trajectory after reflection if the dynamic driving trajectory has been reflected in S12) at a speed in accordance with the speed plan generated in S9 (or the revised plan if the speed plan has been modified in S13).

[0072] Next, in S16, the CPU 51 determines whether the vehicle has traveled a certain distance since the static travel trajectory was generated in S8. For example, the certain distance is 1 km.

[0073] If it is determined that the vehicle has traveled a certain distance since the static driving trajectory was generated in S8 (S16: YES), the process returns to S4. Then, the static driving trajectory is generated again for a section within a certain distance along the driving route from the vehicle's current position (S4 to S8). However, if it is determined that the vehicle has entered a road within a facility that is the destination or a parking lot where the user will park, the process from S4 onwards is performed exceptionally without waiting for the certain distance to be traveled. In this embodiment, the static driving trajectory is repeatedly generated for a section within a certain distance along the driving route from the vehicle's current position every time the vehicle travels a certain distance (for example, 1 km). However, 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.

[0074] 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 S8 (S16: NO), it is determined whether or not to end the assisted driving by autonomous driving assistance (S17). 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.

[0075] If it is determined that the assisted driving by the autonomous driving assistance should be ended (S17: YES), the autonomous driving assistance program is ended. On the other hand, if it is determined that the assisted driving by the autonomous driving assistance should be continued (S17: NO), the process returns to S10.

[0076] Next, the sub-processing of the parking position determination process executed in S7 will be described with reference to Fig. 8. Fig. 8 is a flowchart of the sub-processing program of the parking position determination process.

[0077] First, in S21, the CPU 51 targets the parking lot where the user will park, obtained in S1, and identifies how the parking spaces for parking the vehicle are arranged within the parking lot, based on the facility information 17 obtained in S3.

[0078] Next, in S22, the CPU 51 acquires the current availability of each parking space in the parking lot acquired in S21 by communicating with, for example, an external server that manages the parking lot, and as a result, identifies a parking space in the parking lot where the user will park that is currently available for parking the vehicle.

[0079] Next, in S23, the CPU 51 identifies roads and passages (areas) within the facility or parking lot where the vehicle can travel, based on the facility information 17 acquired in S3, for the destination acquired in S1 and the parking lot where the user will park. The roads and passages within the facility where the vehicle can travel include, for example, an internal road along which the vehicle travels to move from a public road into the facility to the parking lot, and passages within the parking lot for the vehicle to travel (between parking spaces, etc.). etc.) are included.

[0080] Thereafter, in S24, the CPU 51 constructs an intra-facility network for the facility that is the destination and the parking lot where the user will park. Specifically, using the information about the parking space acquired in S21 and the information identifying the roads and passages that the vehicle can travel within the facility and parking lot acquired in S23, routes that the vehicle can choose within the facility and parking lot are identified, and an intra-facility network is generated. The intra-facility network generated in S24 is a network that indicates routes that the vehicle can choose when traveling within the facility and parking lot.

[0081] FIG. 9 shows an example of the intra-facility network constructed in S24. As shown in FIG. 9, the intra-facility network is constructed using parking lot nodes 80 and parking lot links 81. As shown in FIG. 9, parking lot nodes 80 are set at the entrances and exits of the facility and parking lot, at intersections where vehicular passageways intersect, and at corners and end points of vehicular passageways. On the other hand, parking lot links 81 are set for passageways between parking lot nodes 80 that vehicles can travel. The parking lot links 81 also contain information specifying the directions in which vehicles can travel through passageways within the parking lot. For example, FIG. 9 shows an example in which the passageway from the public road to the parking lot is bidirectional, and also shows an example in which passageways within the parking lot are bidirectional. In the example shown in FIG. 9, parking lot nodes 80 are set at corners of vehicular passageways, but parking lot nodes 80 may be set only at points where there are multiple vehicle travel directions, such as passage intersections, rather than at corners.

[0082] Furthermore, for the in-facility network constructed as shown in Figure 9, costs and directions (directions that can pass through parking lot nodes) are set in the same way as for road links. For example, for each parking lot node 80 corresponding to an intersection or a parking lot entrance / exit, a cost is set according to the contents of the parking lot node 80, and the direction that a vehicle can pass through when passing through the parking lot node 80 is also set. Furthermore, costs are set for parking lot links 81 using the length or travel time as a reference value. In other words, the longer the link length or the longer the travel time required for a parking lot link 81, the higher the calculated cost. Furthermore, costs are added for parking lot links 81 that intersect with pedestrian passages such as crosswalks.

[0083] In this embodiment, the CPU 51 constructs an in-facility network, but the in-facility network may be constructed in advance for each facility or parking lot across the country and stored in the facility DB 14.

[0084] Then, in S25, the CPU 51 uses the Dijkstra algorithm to calculate and link the total cost from the parking spaces for each parking lot node 80, which is a connection point of the intra-facility network. The facility entrance / exit (or the parking lot entrance / exit if the parking lot entrance / exit is also the facility entrance / exit) is the end point of the cost calculation. For parking lots with multiple available parking spaces, the total cost from each parking space is calculated. Then, a route from the vehicle's current position to an available parking space is searched for for each parking space using the intra-facility network, and the searched route is stored as a route list together with the total cost value. Note that search methods other than the Dijkstra algorithm may also be used as a route search method. The total cost calculated in S25 is the sum of the cost set for the parking lot node 80 in S24 and the cost of the parking lot link 81.

[0085] Next, in S26, the CPU 51 targets the parking lot where the user acquired in S1 parks, and identifies the pedestrian entrance / exit of the parking lot and roads and passages (areas) within the parking lot that the user (i.e., pedestrian) can move through after getting off the vehicle, based on the facility information 17 acquired in S3. Note that roads and passages that pedestrians can move through include passages that are exclusively for pedestrians and also passages that vehicles can pass through. This may also include paths that pedestrians can walk on. Crosswalks and footbridges are also included in roads and paths that pedestrians can walk on. Furthermore, parking space dividing lines are also considered to be paths that users can walk on.

[0086] Thereafter, in S27, the CPU 51 constructs an in-parking lot pedestrian network for the parking lot where the user parks. Specifically, using the information about the parking space acquired in S21 and the information acquired in S26 specifying the roads and paths that the user (i.e., pedestrian) can move through within the parking lot after getting out of the vehicle, routes that pedestrians (including movement by means of transportation other than walking, such as wheelchairs; the same applies below) can choose within the parking lot, and an in-parking lot pedestrian network is generated. The in-parking lot pedestrian network generated in S27 is a network that shows routes that pedestrians can choose when moving through the parking lot.

[0087] An example of the parking lot pedestrian network constructed in S27 is shown in Figure 10. As shown in Figure 10, the parking lot pedestrian network is constructed using walking nodes 85 and walking links 86. As shown in Figure 10, walking nodes 85 are set at intersections where pedestrian-accessible paths intersect within the parking lot, at the end points and corners of pedestrian-accessible paths, and at pedestrian entrances and exits to the parking lot. Furthermore, using information on the demarcation lines that demarcate parking spaces in the parking lot where the user parks, the parking space demarcation lines are networked as one of the paths that the user can traverse. Specifically, as shown in Figure 11, the network is constructed by setting walking nodes 85 at the end points of the demarcation lines that demarcate parking spaces 84 (i.e., the four corners of the parking space 84), and setting walking links 86 between the walking nodes 85.

[0088] Here, the networking of parking space demarcation lines is set to the boundary (i.e., rectangular shape) surrounding a rectangular parking space 84, regardless of whether the demarcation lines are actually painted on the road surface, as shown in FIG. 11. For example, in the example shown in FIG. 11, demarcation lines are actually painted on the left, right, and rear boundaries of the parking space 84, but a walking link 86 is set on the front boundary of the parking space 84 as well, assuming that a demarcation line is also painted. However, walking links 86 may be set only to boundaries where demarcation lines are actually painted. Alternatively, each demarcation line in the parking lot may be associated in advance with an attribute that identifies whether or not pedestrians can walk over it, and in S27, a network may be built only for demarcation lines that pedestrians can walk over. Furthermore, the parking lot walking network also includes the location where the user gets on and off within that parking space, i.e., the starting point of the walking route, set for each parking space, as shown in FIG. 11.

[0089] Next, in S28, the CPU 51, targeting the destination acquired in S1, identifies entrances and exits of the destination facility and roads and passageways (areas) within the facility (including outdoors) that the user (i.e., pedestrian) can travel after disembarking, based on the facility information 17 acquired in S3. Roads and passageways that pedestrians can travel may include not only pedestrian-only passageways but also passageways that vehicles can pass through. Also, crosswalks and footbridges are included as roads and passageways that pedestrians can travel through. In particular, if the destination is a tenant in a commercial complex with multiple tenants, the location of the destination tenant within the commercial complex building is also acquired, and information on passageways, escalators, elevators, stairs, and the like that pedestrians can travel through throughout the entire commercial complex, including the destination, is acquired. The facility information 17 includes information that identifies a floor map of the facility, and the floor map includes information that identifies, for example, the locations of entrances and exits, passageways, stairs, elevators, and escalators. In a commercial complex with multiple tenants, information that identifies the location of each tenant is also included.

[0090] Thereafter, in S29, the CPU 51 constructs an in-facility walking network for the facility (including outdoors but excluding parking areas) that is the destination. Specifically, the information acquired in S28 specifies roads and paths that the user (i.e., pedestrian) can move through within the facility after getting off. The information is used to identify routes that pedestrians can choose within the facility, and an in-facility walking network is generated. The in-facility walking network generated in S29 is a network that shows routes that pedestrians can choose when moving within the facility.

[0091] An example of the in-facility walking network constructed in S29 is shown in Figure 12. As shown in Figure 12, the in-facility walking network is constructed using walking nodes 85 and walking links 86, just like the in-parking lot walking network. As shown in Figure 12, walking nodes 85 are set at intersections where pedestrian-accessible paths intersect within the facility, at the ends and corners of pedestrian-accessible paths, at pedestrian entrances and exits to the parking lot, and at entrances and exits to the facility.

[0092] In particular, if the destination is one tenant in a commercial complex with multiple tenants, an in-facility walking network will also be constructed for the building in which the destination tenant is located, as shown in Figure 13. On the other hand, if the destination is not one tenant in a commercial complex, the entrance to the building will be the destination (i.e., movement within the building will not be included in the route to the destination), so the in-facility walking network will basically be constructed for outdoors only.

[0093] Thereafter, in S30, the CPU 51 generates a walking network, which is the user's total network including the destination facility and the parking lot, by connecting the parking lot walking network (Fig. 10) generated in S27 with the facility walking network (Figs. 12 and 13) generated in S29 at connection points (pedestrian entrances and exits of the parking lot). The walking network generated in S30 is a network that shows routes the user can choose when moving within the facility and parking lot after getting off the vehicle.

[0094] In addition, for the walking network generated in S30, costs and directions (directions that can be passed through the walking nodes) are set in the same way as for road links. For example, for each walking node 85 corresponding to an intersection, a parking lot entrance / exit, or a facility entrance / exit, a cost is set according to the contents of the walking node 85, and the direction that a pedestrian can pass through when passing through the walking node 85 is also set. Furthermore, costs are set for walking links 86 using their length as a reference value. In other words, the longer the walking link 86, the higher the calculated cost.

[0095] In this embodiment, the CPU 51 constructs the walking network, but the walking network may be constructed in advance for each facility across the country and stored in the facility DB 14.

[0096] Thereafter, in S31, if the pedestrian network generated in S30 crosses an area where vehicles travel, the CPU 51 acquires congestion information that identifies the degree of vehicle congestion at the crossing point (point P in FIG. 12 ). The area where vehicles travel may be a public road or a passageway where vehicles travel within a facility or parking lot. The congestion degree may be information that identifies only whether or not congestion has occurred, or, if congestion has occurred, information that identifies the level of congestion (e.g., empty, crowded, or congested). In particular, in this embodiment, the number N of vehicles stopped in the congestion (the number of vehicles forming the congestion) or the average stop time T for vehicles stopped due to congestion is acquired. The direction of the congestion does not matter, but it may also be possible to acquire only the congestion degree in a specific direction of travel (e.g., the direction of entering the facility). If there are multiple crossing points, the congestion degree is acquired for each crossing point. Furthermore, in S31, only traffic jams occurring starting at crossing point P are considered, and traffic jams occurring starting at points other than crossing point P should desirably be considered not to be traffic jams even if they extend all the way to crossing point P.

[0097] Here, as shown in Fig. 14, if pedestrians frequently pass through crossing point P, which crosses the area where vehicles are traveling (in Fig. 14, the road within the facility leading to the parking lot), congestion will occur with crossing point P at the beginning. In S31, the CPU 51 obtains congestion information specifying the degree of congestion at the crossing point P, for example, from an external server that manages the parking lot, to determine whether or not congestion has occurred starting from the crossing point P due to pedestrians crossing as described above, and if so, the extent of the congestion. The external server that manages the parking lot determines whether or not congestion has occurred at the crossing point P by, for example, collecting speed information and camera images from vehicles traveling within or around the facility. Alternatively, a camera may be installed around the crossing point, and whether or not congestion has occurred at the crossing point P may be determined by analyzing the camera images.

[0098] Next, in S32, the CPU 51 corrects the cost of the walking link 86 based on the degree of congestion at the crossing point P acquired in S31. The cost correction in S32 is a process for reflecting in the cost the impact on other vehicles of the user's movement to the destination after getting off the vehicle, and a higher cost is set for a walking link 86 where the user's movement has a large impact on other vehicles. Specifically, the cost C calculated by the following formula (1) or formula (2) is added to the walking link 86 including the crossing point P. C=Number of stopped cars N×α...(1) C=average stopping time T×β...(2) α and β are predetermined coefficients.

[0099] The coefficients α and β can be set as appropriate, but in this embodiment they are particularly set as follows: First, the CPU 51 acquires the means for crossing the area where the vehicle is traveling at the crossing point P. For example, means for crossing the area where the vehicle is traveling include a "crosswalk," a "crosswalk with a traffic light (non-button type)," a "crosswalk with a traffic light (button type)," and a "pedestrian bridge (including an underground passage)." For example, at crossing point P where the means of crossing the area where vehicles are traveling is a "pedestrian bridge," even if pedestrians frequently cross the area, there is no risk of interfering with the traveling of vehicles, as shown in Figure 14. Therefore, the coefficients α and β are set to 0. Furthermore, for crossing point P where the means for crossing the area where vehicles are traveling is a "crosswalk with a traffic light (non-button type)," the movement of vehicles is not affected by pedestrians crossing (it is affected only by the lighting of the traffic light), so the coefficients α and β are also set to 0. On the other hand, for crossing points P where the means of crossing the area where vehicles are traveling is a "crosswalk," vehicles cannot pass through crossing point P as long as pedestrians are present, and since the movement of vehicles is greatly affected by pedestrians crossing, the coefficients α and β are set to larger values. Finally, for crossing point P where the means of crossing an area where vehicles are traveling is a "crosswalk with a traffic light (button type)," the impact is smaller than with a crosswalk, but if there are many pedestrians, the traffic light will often turn red and vehicle traffic will be affected to a certain extent by pedestrians crossing, so the coefficients α and β are set to values greater than 0 but smaller than in the case of a crosswalk.

[0100] If there is no congestion at the crossing point P, the cost correction in S32 is not generally performed.

[0101] Thereafter, in S33, the CPU 51 calculates and links the total cost from the entrance / exit of the facility (if the destination is a tenant in a commercial complex with multiple tenants, the location of the destination tenant) for each walking node 85 that is a connection point of the walking network using the Dijkstra algorithm. The boarding and alighting position of each parking space is the end point of the cost calculation. For parking lots with multiple available parking spaces, the total cost to each parking space is calculated. Then, routes from the boarding and alighting positions of available parking spaces to the entrance / exit of the facility are searched for for each parking space using the walking network, and the searched routes are stored as a route list together with the total cost value of the searched route. Note that search methods other than the Dijkstra algorithm may also be used as a route search method. The total cost calculated in S33 is used as the end point of the cost calculation in S33. If the cost is corrected in S32, the cost is calculated using the corrected cost of the walking link 86. In other words, if the searched route is a route that crosses an area where vehicles travel, the cost for that route is calculated taking into account the degree of vehicle congestion at the crossing points.

[0102] Next, in S34, the CPU 51 references the route list for driving the vehicle from the vehicle's current location to a parking space, generated in S25, and the route list for walking from the parking space to the facility entrance / exit, generated in S33, and selects a combination of routes that minimizes the total cost. Note that only routes that start or end at the same parking space can be combined. The route selected in S34 is a recommended route that reduces the burden of driving the vehicle from the current location to park in the parking space and the burden of traveling from the parking space to the destination after parking the vehicle, as well as the impact on other vehicles caused by the user's travel to the destination. Furthermore, the combination of routes selected in S34 determines the parking location for the vehicle. That is, the parking space where the vehicle is parked on the selected route is the recommended parking location. Furthermore, the selected route also determines the vehicle's driving route from the vehicle's current location to the determined parking location, and in S8, described below, a static driving trajectory to the parking location is generated according to the determined driving route.

[0103] Thereafter, in S35, the CPU 51 executes a parking space selection reason notification process (FIG. 16) to be described later. Here, the parking space selection reason notification process is a process for notifying the user of the reason for selecting the parking space in which to park the vehicle, as necessary.

[0104] Thereafter, the process proceeds to S8, where the vehicle's travel trajectory from the current position of the vehicle to the determined parking position is calculated, and driving assistance for the vehicle is provided according to the calculated travel trajectory (S8 to S15).

[0105] In this embodiment, in addition to the total cost of the in-facility network and the walking network, the cost is corrected based on the degree of congestion at the crossing point in S32, so the parking location for the vehicle is selected taking into consideration not only the burden of driving the vehicle to the parking location and the burden of traveling by the user to the destination after parking the vehicle in the parking lot, but also the impact on other vehicles caused by the user's movement to the destination. Specifically, even if the burden of traveling by the user is small, a parking space that is likely to obstruct the movement of other vehicles due to the user's movement to the destination after parking is unlikely to be selected as a parking location for the vehicle. For example, as shown in Figure 15, if there are two parking space candidates for parking a vehicle at a destination, parking space A and parking space B, comparing routes 91 and 92 for driving the vehicle from the vehicle's current location (assumed to be at the entrance to the facility) to the parking space and routes 93 and 94 for moving the vehicle after disembarking, routes 91 and 93 for parking at parking space A are shorter in driving distance to the parking space than routes 92 and 94 for parking at parking space B, and also shorter in driving distance to the entrance of the destination facility, parking space A can be said to be a more suitable parking space than parking space B. However, route 93 includes crossing point P, which crosses the area where the vehicle will be driving. If there is vehicle congestion at crossing point P, guiding the vehicle to parking space A may further worsen the congestion. Therefore, in this embodiment, the cost of route 93 is increased to make parking space B more likely to be selected as a parking space for parking.

[0106] In the above embodiment, the parking position is selected taking into consideration the burden on the user of traveling to the destination after parking. However, the burden on the user of traveling home from the destination may also be considered. For example, a route with the minimum cost may be searched for, including a route to the destination and a route back from the destination to the parking location, and a parking location may be selected.

[0107] Next, the sub-processing of the parking space selection reason presentation processing executed in S35 will be described with reference to Fig. 16. Fig. 16 is a flowchart of the sub-processing program of the parking space selection reason presentation processing.

[0108] First, in S41, the CPU 51 performs the same process as S34 described above. Referring to the route list for driving the vehicle from the current vehicle location to the parking space, generated in S25, and the route list for walking from the parking space to the facility entrance / exit, generated in S33, the CPU 51 selects a route combination with the lowest total cost. However, in S41, it is assumed that no traffic jam actually occurs at crossing point P, even if it does. That is, the route combination with the lowest total cost is selected without performing the cost correction in S32. The route selected in S41 is the route that minimizes the total burden associated with driving the vehicle from the current location to parking in the parking space and the burden associated with traveling from the parking space to the destination after parking the vehicle. However, the influence of other vehicles on the user's travel to the destination is not taken into consideration. Furthermore, the combination of routes selected in S41 determines the parking location for the vehicle, as in S34.

[0109] Next, in S42, the CPU 51 compares the parking space determined as the parking position where the vehicle is to be parked in S41 with the parking space determined as the parking position where the vehicle is to be parked in S34.

[0110] If it is determined in S41 that the parking space determined as the parking position where the vehicle will be parked in S34 matches the parking space determined as the parking position where the vehicle will be parked in S34 (S43: YES), the process ends without providing any guidance on the reason for selecting the parking space. If it is determined as YES in S43, this means that the same parking position is selected whether or not the impact of other vehicles on the user's movement to the destination is taken into consideration. In other words, the parking space determined as the parking position where the vehicle will be parked in S34 is presumed to be the optimal parking position for the user, minimizing the burden on the user in terms of movement to the parking position and movement after getting out of the vehicle, so there is no need to provide any explanation as to the reason for its selection.

[0111] On the other hand, if it is determined that the parking space determined in S41 as the parking position where the vehicle is to be parked does not match the parking space determined in S34 as the parking position where the vehicle is to be parked (S43: NO), guidance is provided regarding the reason for selecting the parking space (S44). Note that if it is determined as NO in S43, this is a case where a different parking position is selected when the impact of other vehicles due to the user's movement to the destination is taken into consideration and when it is not. In other words, the parking space determined in S34 as the parking position where the vehicle is to be parked is presumed to be a parking position that is different from the optimal parking position for the user, which places the least burden on the user in moving to the parking position and moving after getting out of the vehicle, and therefore it is necessary to explain the reason for the selection (why a parking position that is disadvantageous to the user was deliberately selected).

[0112] For example, in the case shown in Figure 15, if we only consider the burden on the user who parks, parking space A should be the parking location, but if we consider the impact of other vehicles on the user's journey to the destination, parking space B may be selected. Since the user may have doubts about the selection result, for example, if parking space B is selected as the parking location, the user may be told, "Although it is a long walk, there is traffic congestion, so I would like to use parking space B instead." A voice message saying "You have selected parking space B" is output from the speaker 36, and the location of parking space B that has been selected as the parking location is displayed on the liquid crystal display 35. This makes it possible to eliminate as much as possible any distrust the user may have.

[0113] Alternatively, the system may explain the reason for selecting the parking space and then ask the user whether it is OK to maintain the current parking space selection. If the user accepts the selection after the inquiry, the current parking space selection is maintained. On the other hand, if the user rejects the selection, the current parking space selection is temporarily discarded, and the user is prompted to change the conditions and select a parking space again. Alternatively, the parking space selected in S41 may be newly selected as the parking location for the vehicle.

[0114] As explained in detail above, the navigation device 1 and the computer program executed by the navigation device 1 according to this embodiment acquire parking lot information about a parking lot belonging to the user's destination (S3), acquire parking spaces within the parking lot where the vehicle can be parked (S21, S22), acquire a travel route for the user to travel to the destination after disembarking from the vehicle for each parking space where the vehicle can be parked (S33), calculate the travel cost for traveling along the travel route based on the parking lot information and the travel route (S33), and select a parking space in which to park the vehicle using the calculated travel cost (S34). Meanwhile, if the travel route crosses an area in which the vehicle is traveling, the degree of vehicle congestion at the crossing point is acquired (S31), and the travel cost is calculated taking the degree of congestion into consideration (S32). This makes it possible to provide a parking space that is appropriate for the user while preventing the vehicle's travel from being significantly hindered by the user's movement after disembarking from the vehicle. In addition, if there is a traffic jam of vehicles starting from a crossing point, the travel cost of the travel route including the crossing point is increased (S32). Therefore, by lowering the selection priority of parking locations where the user will cross the area where the vehicle is traveling after disembarking, it is possible to eliminate traffic jams of vehicles caused by the movement of users after disembarking. Furthermore, if the travel route is a route that crosses the area in which the vehicle is traveling, the means for crossing the area in which the vehicle is traveling is also obtained, and the travel cost is calculated taking into consideration the type of means for crossing the area in which the vehicle is traveling (S32).Therefore, it is possible to select a parking space in which to park the vehicle, taking into consideration whether or not crossing the area in which the vehicle is traveling after getting off the vehicle will hinder the vehicle's travel. Furthermore, a parking space for parking the vehicle is selected using the travel cost calculated without taking into account the degree of vehicle congestion at the crossing point (S41), and if the selected parking space differs from the parking space selected taking into account the degree of vehicle congestion at the crossing point, the user is informed of the reason for selecting the parking space (S44), thereby eliminating any distrust the user may have when a parking space different from the optimal parking space when only the burden on the user is taken into account is selected as the parking space for parking the vehicle.

[0115] The present invention is not limited to the above-described embodiment, and it goes without saying that various improvements and modifications are possible within the scope of the present invention. For example, in this embodiment, the parking location for the vehicle is determined by taking into consideration both the in-facility network that shows the vehicle's travel route constructed in S24 and the pedestrian network that shows the user's travel route after getting off the vehicle constructed in S30, but the parking location may also be determined by taking into consideration only the pedestrian network. That is, for each parking space where the vehicle can be parked, a travel route for the user to travel to the destination after getting off the vehicle may be obtained, and the parking space located at the starting point of the travel route with the smallest total cost may be selected as the parking location for the vehicle.

[0116] In this embodiment, after selecting a parking position where the vehicle is recommended to be parked (S7), a travel trajectory of the vehicle to the selected parking position is generated (S8), and the vehicle is driven along the generated travel trajectory. However, it is possible to omit the processing related to vehicle driving assistance from S8 onwards. For example, the navigation device 1 may be a device that only provides guidance on recommended parking positions, without generating a driving trajectory or controlling the vehicle based on the driving trajectory. In other words, the vehicle 5 may be a vehicle that does not perform automatic driving assistance and can be driven only by manual driving.

[0117] In this embodiment, a specific parking space where the vehicle will park is identified from among multiple parking spaces provided in the parking lot as the recommended parking location. However, a wider area may be identified. For example, if the parking lot consists of multiple areas, the area where the vehicle will park may be identified. Furthermore, if there are multiple parking lots available as parking locations, the parking lot may be identified.

[0118] In this embodiment, the static driving trajectory that is finally generated is information that identifies the specific trajectory (a set of coordinates or a line) on which the vehicle will travel, but information that can identify the roads and lanes on which the vehicle will travel without specifying the specific trajectory may also be used.Furthermore, it is also possible to specify only the roads on which the vehicle will travel and the parking position where the vehicle will be parked in a parking lot without specifying the specific driving trajectory.

[0119] In addition, in this embodiment, an in-facility network and a walking network are generated using high-precision map information 16 and facility information 17 (S24, S30), but each network targeting buildings and parking lots across the country may be stored in a database in advance and read out from the database as needed.

[0120] In addition, in this embodiment, the vehicle control ECU 40 has been described as controlling all of the accelerator operation, brake operation, and steering operation, which are operations related to the vehicle's behavior, as autonomous driving assistance for automatically driving the vehicle without the user's driving operation. However, the autonomous driving assistance may also be defined as the vehicle control ECU 40 controlling at least one of the accelerator operation, brake operation, and steering operation, which are operations related to the vehicle's behavior, as part of the vehicle operations. On the other hand, manual driving performed by the user's driving operation will be described as the user performing all of the accelerator operation, brake operation, and steering operation, which are operations related to the vehicle's behavior, as part of the vehicle operations.

[0121] Furthermore, 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 identified in S8 or the dynamic driving trajectory generated in S11 on a navigation screen, and to provide guidance using voice, a screen, or the like (for example, guidance on lane changes, guidance on recommended vehicle speeds, etc.). Furthermore, the static driving trajectory or the dynamic driving trajectory may be displayed on the navigation screen to assist the user's driving operation.

[0122] Furthermore, 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 acquire 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.

[0123] Furthermore, the present invention can be applied to devices other than navigation devices, such as mobile phones, smartphones, tablet terminals, and personal computers (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) can be implemented by a server. However, when the present invention is applied to a mobile terminal, etc., the vehicle capable of executing autonomous driving assistance and the mobile terminal, etc. must be connected to each other so that they can communicate with each other (whether wired or wireless). [Explanation of symbols]

[0124] 1...navigation device (driving assistance device), 2...driving assistance system, 3...information distribution center, 4...server device, 5...vehicle, 16...high-precision map information, 17...facility information, 18...connection information, 19...road exterior shape information, 33...navigation ECU, 40...vehicle control ECU, 51...CPU, 74...recommended parking position, 80...parking lot node, 81...parking lot link, 85...walking node, 86...walking link

Claims

1. a parking lot information acquisition means for acquiring parking lot information relating to parking lots belonging to the user's destination; a parking space acquisition means for acquiring a parking space in which a vehicle can be parked within the parking lot; a travel route acquisition means for acquiring a travel route for the user to travel to the destination after getting off the vehicle, for each parking space where the vehicle can be parked; a cost calculation means for calculating a travel cost required for travel along the travel route based on the parking lot information and the travel route; a parking space selection means for selecting a parking space in which to park a vehicle using the movement cost calculated by the cost calculation means, The cost calculation means If the travel route is a route that crosses an area in which the vehicle travels, a degree of traffic congestion of the vehicle at the crossing point is acquired; A driving assistance device that calculates the travel cost taking into account the degree of congestion.

2. The driving assistance device according to claim 1 , wherein the cost calculation means increases the travel cost of the travel route including the crossing point when there is a traffic jam of vehicles starting from the crossing point.

3. The cost calculation means If the travel route is a route that crosses an area where the vehicle travels, acquiring information about a means for crossing the area where the vehicle travels; The driving assistance device according to claim 1 , wherein the travel cost is calculated taking into consideration the type of means used to cross the area in which the vehicle is traveling.

4. a non-considered parking space selection means for selecting a parking space for parking a vehicle using a travel cost calculated without considering the degree of vehicle congestion at a crossing point; 4. A driving assistance device according to claim 1, wherein, when the parking space selected by the parking space selection means is different from the parking space selected by the non-consideration parking space selection means, the parking space selected by the parking space selection means is determined as the parking space in which the user will park, and the device provides the user with information on the reason for selecting the parking space.

Images