Patent Application
20240416954
The present disclosure relates to a driving assistance device and a computer program that assist in vehicle's driving in a parking lot.
When a vehicle moves to a destination, generally, the vehicle moves to a parking lot belonging to the destination or a parking lot around the destination and is parked, and a user moves on foot, etc., to a point that is the destination from a parking space where the vehicle is parked in the parking lot, by which the movement is completed. In this case, when such movement to the destination is assisted, particularly, vehicle's travel in the parking lot is short in distance traveled compared to travel on a road, but has many candidates for a travel path that can be taken by the vehicle, and thus, it has been difficult to select an optimal travel path from among the candidates.
In view of this, for example, JP 2010-117864 A discloses a technique in which a network of routes on which a vehicle can travel in a parking lot is formed by nodes and links, and a recommended route from an entrance/exit of the parking lot to a parking space which is a candidate for parking in the parking lot is searched using the network.
Here, in the network disclosed in the above-described Patent Literature 1, a node is set at the center of a parking space where the vehicle can be parked, and a passage in the parking lot and the node set in the parking space are connected together at a right angle by a link which is a straight line representing the shortest distance. A route that is searched using such a network only indicates a course to a parking space (which parking space is used for parking by passing through which passage) and it has been unable to present what locations are taken for traveling on what path in actual vehicle's travel up to the point where the vehicle is parked in the parking space.
The aspects of the present disclosure are made to solve the above-described conventional problem and provides a driving assistance device and a computer program that enable, when a vehicle is parked in a parking lot, deriving of a travel path from an entrance/exit of the parking lot up to the point where the vehicle is parked in a parking space, the travel path identifying specific travel locations in the parking lot.
To provide the above-described driving assistance device, a first driving assistance device according to the present disclosure includes parking space information obtaining means for obtaining, when a vehicle is parked in a parking lot, layout information of parking spaces provided in the parking lot; parking location obtaining means for obtaining a parking location where a vehicle is parked, from among the parking spaces; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; travel path generating means for generating a travel path from an entrance to a parking lot up to a point where a vehicle is parked in the parking location, using the intra-parking-lot network and the layout information of parking spaces, the travel path identifying vehicle's travel locations in a parking lot; and driving assistance means for providing driving assistance based on the travel path.
In addition, a second driving assistance device according to the present disclosure includes parking space information obtaining means for obtaining, when a vehicle is parked in a parking lot, layout information of parking spaces provided in the parking lot; parking location obtaining means for obtaining a parking location where a vehicle is parked, from among the parking spaces; vehicle's posture selecting means for selecting a posture of a vehicle taken when the vehicle is parked in the parking location; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; travel path generating means for generating, using the intra-parking-lot network and the layout information of parking spaces, a vehicle's travel path from an entrance to a parking lot up to a point where a vehicle is parked in the parking location in the posture selected by the vehicle's posture selecting means; and driving assistance means for providing driving assistance based on the travel path.
In addition, a third driving assistance device according to the present disclosure includes parking space information obtaining means for obtaining, when a vehicle exits a parking lot where the vehicle is parked, layout information of parking spaces provided in the parking lot; parking location obtaining means for obtaining a parking location where a vehicle is parked, from among the parking spaces; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; exit travel path generating means for generating a travel path from the parking location to an exit of a parking lot, using the intra-parking-lot network and the layout information of parking spaces, the travel path identifying vehicle's travel locations in a parking lot; and driving assistance means for providing driving assistance based on the travel path.
In addition, a fourth driving assistance device according to the present disclosure includes parking space information obtaining means for obtaining, when a vehicle exits a parking lot where the vehicle is parked, layout information of parking spaces provided in the parking lot; parking location obtaining means for obtaining a parking location where a vehicle is parked, from among the parking spaces; vehicle's posture obtaining means for obtaining a posture of a vehicle parked in the parking location; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; exit travel path generating means for generating a vehicle's travel path from the parking location where a vehicle is parked in the posture obtained by the vehicle's posture obtaining means to an exit of a parking lot, using the intra-parking-lot network and the layout information of parking spaces; and driving assistance means for providing driving assistance based on the travel path.
In addition, a first computer program according to the present disclosure is a program that generates assistance information used for driving assistance provided in a vehicle. Specifically, the computer program causes a computer to function as parking location obtaining means for obtaining, when a vehicle is parked in a parking lot, a parking location where a vehicle is parked; vehicle's posture selecting means for selecting a posture of a vehicle taken when the vehicle is parked in the parking location; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; travel path generating means for generating, using the intra-parking-lot network, a vehicle's travel path from an entrance to a parking lot up to a point where a vehicle is parked in the parking location in the posture selected by the vehicle's posture selecting means; and driving assistance means for providing driving assistance based on the travel path.
In addition, a second computer program according to the present disclosure is a program that generates assistance information used for driving assistance provided in a vehicle. Specifically, the computer program causes a computer to function as parking location obtaining means for obtaining, when a vehicle is parked in a parking lot, a parking location where a vehicle is parked; intra-parking-lot network obtaining means for obtaining an intra-parking-lot network, the intra-parking-lot network being a network representing a route that can be selected by a vehicle in the parking lot; travel path generating means for generating a travel path from an entrance to a parking lot up to a point where a vehicle is parked in the parking location, using the intra-parking-lot network, the travel path identifying vehicle's travel locations in a parking lot; and driving assistance means for providing driving assistance based on the travel path.
According to the first driving assistance device and the first computer program according to the present disclosure that have the above-described configurations, when a vehicle is parked in a parking lot, it becomes possible to derive a travel path from an entrance to the parking lot up to the point where the vehicle is parked in a parking location, the travel path identifying specific travel locations in the parking lot. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
In addition, according to the second driving assistance device and the second computer program, by taking into account, particularly, a posture of a vehicle taken upon parking the vehicle in a parking location, when the vehicle is parked in a parking lot, it becomes possible to derive a more specific travel path from an entrance to the parking lot up to the point where the vehicle is parked in the parking location. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
In addition, according to the third driving assistance device, when a vehicle exits a parking lot, it becomes possible to derive a travel path from a parking location to an exit of the parking lot, the travel path identifying specific travel locations in the parking lot. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
In addition, according to the fourth driving assistance device, by taking into account, particularly, a posture of a vehicle parked in a parking location, when the vehicle exits a parking lot, it becomes possible to derive a more specific travel path from the parking location to an exit of the parking lot. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
One embodiment in which a driving assistance device according to the present disclosure is embodied into 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 navigation devices 1 according to the present embodiment will be described using
As shown in
Here, the vehicle 5 is a vehicle that can perform assistance travel by autonomous driving assistance in which the vehicle autonomously travels on a preset route or along a road independently of user's driving operations, in addition to manual driving travel in which the vehicle travels based on user's driving operations.
In addition, a configuration may be adopted in which autonomous driving assistance is provided for all road sections or is provided only while the vehicle travels on a specific road section (e.g., an expressway having a gate at a boundary (it does not matter whether or not there is a person or whether or not a toll is collected)). The following description is made assuming that autonomous driving sections in which autonomous driving assistance for the vehicle is provided also include parking lots in addition to all road sections including general roads and expressways, and autonomous driving assistance is basically provided during a period from when the vehicle starts traveling until the vehicle finishes traveling (until the vehicle is parked). Note, however, that it is desirable that instead of always providing autonomous driving assistance when the vehicle travels on an autonomous driving section, autonomous driving assistance be provided only in a situation in which a user selects provision of autonomous driving assistance (e.g., an autonomous driving start button is turned on) and it is determined that travel by autonomous driving assistance can be performed. On the other hand, the vehicle 5 may be a vehicle that can only perform assistance travel by autonomous driving assistance.
In vehicle control performed by autonomous driving assistance, for example, a current vehicle location, a lane in which the vehicle travels, and the location of an obstacle around the vehicle are detected whenever necessary, and vehicle control of steering, a drive source, a brake, etc., is autonomously performed so that the vehicle travels along a travel path generated by the navigation device 1 and at speeds in accordance with a speed plan created by the navigation device 1 as will be described later. Note that in assistance travel by autonomous driving assistance of the present embodiment, for a lane change, a left or right turn, and a parking operation, too, travel is performed by performing the above-described vehicle control by autonomous driving assistance, but a configuration may be adopted in which special travel such as a lane change, a left or right turn, and a parking operation is performed by manual driving instead of performing travel by autonomous driving assistance.
Meanwhile, the navigation device 1 is an in-vehicle device mounted on the vehicle 5 to display a map of an area around the location of the vehicle 5 based on map data included in the navigation device 1 or map data obtained from an external source, or to allow the user to input a destination, or to display a current vehicle location on a map image, or to provide guidance on movement along a set guidance route. In the present embodiment, particularly, when the vehicle performs assistance travel by autonomous driving assistance, various types of assistance information about the autonomous driving assistance are generated. The assistance information includes, for example, a travel path recommended for the vehicle to travel along (including a recommended way of moving into lanes), selection of a parking location where the vehicle is parked at a destination, and a speed plan indicating vehicle speeds at which the vehicle travels. Note that details of the navigation device 1 will be described later.
In addition, the server device 4 performs a route search in response to a request from a navigation device 1. Specifically, information required for a route search such as a point of departure and a destination is transmitted together with a route search request from the navigation device 1 to the server device 4 (note, however, that in a case of re-searching, information about the destination does not necessarily need to be transmitted). Then, the server device 4 having received the route search request performs a route search using map information included in the server device 4, to identify a recommended route from the point of departure to the destination. Thereafter, the identified recommended route is transmitted to the navigation device 1 which is a source of the request. The navigation device 1 can provide a user with information about the received recommended route, or can also generate, using the recommended route, various types of assistance information about autonomous driving assistance as will be described later.
Furthermore, the server device 4 has high-precision map information which is map information with higher precision and facility information, separately from normal map information used for the above-described route search. The high-precision map information includes, for example, information about the lane geometries of roads (lane-by-lane road geometries, curvatures, lane widths, etc.) and markings (centerlines, lane lines, edge lines, guidelines, etc.) painted on the roads. In addition to the information, information about intersections, etc., are also included. On the other hand, the facility information is more detailed information about facilities that is stored separately from information about facilities included in the map information. The facility information includes, for example, information about a facility floor plan and an entrance to a parking lot, layout information of passages and parking spaces provided in the parking lot, information on makings that mark off the parking spaces, and connection information indicating a connection relationship between the entrance to the parking lot and a lane. The server device 4 delivers high-precision map information and facility information in response to a request from a navigation device 1, and the navigation device 1 generates, as will be described later, various types of assistance information about autonomous driving assistance, using the high-precision map information and facility information delivered from the server device 4. Note that the high-precision map information is basically map information targeting only a road (link) and an area around the road, but may be map information that also includes an area other than the area around the road.
Note, however, that the above-described route search process does not necessarily need to be performed by the server device 4, and if a navigation device 1 has map information, then the navigation device 1 may perform the route search process. In addition, the high-precision map information and the facility information may be included in advance in the navigation device 1, instead of being delivered from the server device 4.
In addition, the communication network 6 includes multiple base stations disposed all over the country; and telecommunications companies that manage and control their base stations, and is formed by connecting the base stations to the telecommunications companies by wire (optical fiber, ISDN, etc.) or wirelessly. Here, the base stations each include a transceiver and an antenna that perform communication with navigation devices 1. While the base station performs radio communication with a corresponding telecommunications company, the base station serves as an end of the communication network 6 and plays a role in relaying communication of navigation devices 1 present in an area (cell) where radio waves from the base station reach, to the server device 4.
Next, a configuration of the server device 4 in the driving assistance system 2 will be described in more detail using
The server control part 11 is a control unit (an MCU, an MPU, etc.) that performs overall control of the server device 4, and includes a CPU 21 serving as a computing device and a control device; and internal storage devices such as a RAM 22 used as a working memory when the CPU 21 performs various types of arithmetic processing, a ROM 23 having recorded therein a program for control, etc., and a flash memory 24 that stores a program read from the ROM 23. Note that the server control part 11 has various types of means serving as processing algorithms with an ECU of a navigation device 1 which will be described later.
Meanwhile, the server-side map DB 12 is storage means for storing server-side map information which is the latest version of map information registered based on input data from an external source or based on input operations. Here, the server-side map information includes a road network and various types of information required for a route search, route guidance, and map display. For example, the server-side map information includes network data including nodes and links that indicate a road network, link data about roads (links), node data about node points, intersection data about each intersection, point data about points such as facilities, map display data for displaying a map, search data for searching for a route, retrieval data for retrieving a point, etc.
In addition, the high-precision map DB 13 is storage means for storing high-precision map information 16 which is map information with higher precision than the above-described server-side map information. The high-precision map information 16 is, particularly, map information that stores more detailed information about roads on which vehicles are to travel. In the present embodiment, the high-precision map information 16 includes, for example, for a road, information about a lane geometry (lane-by-lane road geometries, curvatures, lane widths, etc.) and markings (centerlines, lane lines, edge lines, guidelines, etc.) painted on the road. Furthermore, the high-precision map information 16 records data representing road gradients, cants, banks, merge areas, a location where the number of lanes decreases, a location where the road width becomes narrower, railroad crossings, etc., and records: for a corner, data representing the radius of curvature, an intersection, a T-junction, the entry and exit of the corner, etc.: for road attributes, data representing downhill slopes, uphill slopes, etc.; and for the types of road, data representing general roads such as national highways, prefectural highways, and narrow streets, and toll roads such as national expressways, urban expressways, automobile roads, general toll roads, and toll bridges. Particularly, in the present embodiment, the high-precision map information 16 also stores information that identifies, in addition to the number of lanes on a road, a passage segment in a traveling direction for each lane and a connection between roads for each lane (specifically, a correspondence between a lane included in a road before passing through an intersection and a lane included in a road after passing through the intersection). Furthermore, the high-precision map information 16 also stores speed limits set for roads.
Meanwhile, the facility DB 14 is storage means for storing more detailed information about facilities than information about facilities stored in the above-described server-side map information. Specifically, the facility DB 14 includes, as facility information 17, particularly, for a parking lot where a vehicle is to be parked (including both a parking lot belonging to a facility and an independent parking lot), information that identifies the location of an entrance/exit of the parking lot, information that identifies a layout of parking spaces in the parking lot, information about markings that mark off the parking spaces, information about passages through which vehicles and pedestrians can pass, and information about crosswalks in the parking lot and passage spaces provided for pedestrians. The facility DB 14 includes, for a facility other than a parking lot, information that identifies a floor plan of the facility. The floor plan includes, for example, information that identifies the locations of entrances and exits, passages, stairs, elevators, and escalators. In addition, the facility DB 14 includes, for a complex commercial facility having a plurality of tenants, information that identifies the location of each tenant that occupies the complex commercial facility. The facility information 17 may be, particularly, information generated by 3D modeling of a parking lot or a facility. Furthermore, the facility DB 14 also includes connection information 18 indicating a connection relationship between a lane included in an entry road facing an entrance to a parking lot and the entrance to the parking lot; and outside-the-road geometry information 19 that identifies a region between the entry road and the entrance to the parking lot, through which vehicles can pass. Details of each piece of information stored in the facility DB 14 will be described later.
Note that the high-precision map information 16 is basically map information targeting only a road (link) and an area around the road, but may be map information that also includes an area other than the area around the road. In addition, although in the example shown in
Meanwhile, the server-side communication device 15 is a communication device for performing communication with a navigation device 1 of each vehicle 5 through the communication network 6. In addition, besides the navigation devices 1, it is also possible to receive traffic information including pieces of information such as traffic congestion information, regulation information, and traffic accident information that are transmitted from an Internet network, traffic information centers, e.g., a VICS (registered trademark: Vehicle Information and Communication System) center, etc.
Next, a schematic configuration of the navigation device 1 mounted on the vehicle 5 will be described using
As shown in
The components included in the navigation device 1 will be described in turn below.
The current location detecting part 31 includes a GPS 41, a vehicle speed sensor 42, a steering sensor 43, a gyro sensor 44, etc., and can detect the current vehicle location and orientation, a vehicle's travel speed, a current time, etc. Here, particularly, the vehicle speed sensor 42 is a sensor for detecting a vehicle's moving distance and vehicle speed, and generates pulses according to the rotation of vehicle's drive wheels and outputs a pulse signal to the navigation ECU 33. Then, the navigation ECU 33 counts the generated pulses, thereby calculating the rotational speed of the drive wheels and a moving distance. Note that the navigation device 1 does not need to include all of the above-described four types of sensors, and may be configured to include only one or a plurality of types of sensors among these sensors.
In addition, the data recording part 32 includes a hard disk (not shown) serving as an external storage device and a recording medium; and a recording head (not shown) which is a driver for reading a map information DB 45 recorded on the hard disk, a cache 46, a predetermined program, etc., and for writing predetermined data to the hard disk. Note that the data recording part 32 may include a flash memory, a memory card, or an optical disc such as a CD or a DVD, instead of a hard disk. In addition, in the present embodiment, as described above, the server device 4 searches for a route to a destination, and thus, the map information DB 45 may be omitted. Even if the map information DB 45 is omitted, it is also possible to obtain map information from the server device 4 as necessary.
Here, the map information DB 45 is storage means having stored therein, for example, link data about roads (links), node data about node points, search data used in processes related to a route search or change, facility data about facilities, map display data for displaying a map, intersection data about each intersection, and retrieval data for retrieving a point.
Meanwhile, the cache 46 is storage means for saving high-precision map information 16, facility information 17, connection information 18, and outside-the-road geometry information 19 that have been delivered from the server device 4 in the past. A saving period can be set as appropriate, and may be, for example, a predetermined period (e.g., one month) after storage or a period until a vehicle's ACC power supply (accessory power supply) is turned off. In addition, after the amount of data stored in the cache 46 reaches an upper limit, the data may be sequentially deleted in order of oldest to newest. The navigation ECU 33 generates various types of assistance information about autonomous driving assistance, using the high-precision map information 16, facility information 17, connection information 18, and outside-the-road geometry information 19 stored in the cache 46. Details will be described later.
Meanwhile, the navigation ECU (electronic control unit) 33 is an electronic control unit that performs overall control of the navigation device 1, and includes a CPU 51 serving as a computing device and a control device; and internal storage devices such as a RAM 52 that is used as a working memory when the CPU 51 performs various types of arithmetic processing and that stores route data obtained when a route is searched, etc., a ROM 53 having recorded therein a program for control, an autonomous driving assistance program (see
The operating part 34 is operated, for example, upon inputting a point of departure which is a travel start point and a destination which is a travel end point, and includes a plurality of operating switches such as various types of keys and buttons (not shown). Based on a switch signal outputted by, for example, depression of a given switch, the navigation ECU 33 performs control to perform a corresponding one of various types of operation. Note that the operating part 34 may include a touch panel provided on the front of the liquid crystal display 35. Note also that the operating part 34 may include a microphone and a voice recognition device.
In addition, on the liquid crystal display 35 there are displayed a map image including roads, traffic information, operation guidance, an operation menu, guidance on keys, information on guidance along a guidance route (planned travel route), news, weather forecasts, time, e-mails, TV programs, etc. Note that instead of the liquid crystal display 35, a HUD or an HMD may be used.
In addition, the speaker 36 outputs voice guidance that provides guidance on travel along a guidance route (planned travel route) or guidance on traffic information, based on an instruction from the navigation ECU 33.
In addition, the DVD drive 37 is a drive that can read data recorded on a recording medium such as a DVD or a CD. Based on the read data, for example, music or video is played back or the map information DB 45 is updated. Note that instead of the DVD drive 37, a card slot for performing reading and writing on a memory card may be provided.
In addition, the communication module 38 is a communication device for receiving traffic information, probe information, weather information, etc., that are transmitted from traffic information centers, e.g., a VICS center and a probe center, and corresponds, for example, to a mobile phone or a DCM. In addition, the communication module 38 also includes a vehicle-to-vehicle communication device that performs communication between vehicles and a roadside-device-to-vehicle communication device that performs communication with a roadside device. In addition, the communication module 38 is also used to transmit and receive route information searched by the server device 4, high-precision map information 16, facility information 17, connection information 18, and outside-the-road geometry information 19 to/from the server device 4.
In addition, the exterior camera 39 includes, for example, a camera that uses a solid-state imaging device such as a CCD, and is attached to the upper side of a vehicle's front bumper and is placed such that its optical-axis direction faces downward at a predetermined angle relative to the horizontal. When the vehicle travels on an autonomous driving section, the exterior camera 39 captures an image of an area ahead in a vehicle's traveling direction. In addition, the navigation ECU 33 performs image processing on the captured image having been captured, thereby detecting markings painted on a road on which the vehicle travels, or obstacles such as other vehicles around the vehicle, and generates various types of assistance information about autonomous driving assistance, based on results of the detection. For example, when an obstacle has been detected, a new travel path in which the vehicle travels avoiding or following the obstacle is generated. Note that the exterior camera 39 may be configured to be disposed on the rear or side of the vehicle other than the front. Note also that for means for detecting obstacles, a sensor such as millimeter-wave radar or a laser sensor, vehicle-to-vehicle communication, or roadside-device-to-vehicle communication may be used instead of a camera.
In addition, the vehicle control ECU 40 is an electronic control unit that controls the vehicle having the navigation device 1 mounted thereon. In addition, vehicle's driving parts such as steering, a brake, and an accelerator are connected to the vehicle control ECU 40, and in the present embodiment, particularly, after the vehicle starts autonomous driving assistance, each driving part is controlled, by which autonomous driving assistance for the vehicle is provided. In addition, when an override has been performed by the user during autonomous driving assistance, the fact that the override has been performed is detected.
Here, the navigation ECU 33 transmits, after starting traveling, various types of assistance information about autonomous driving assistance generated by the navigation device 1 to the vehicle control ECU 40 through the CAN. Then, the vehicle control ECU 40 provides autonomous driving assistance to be provided after starting traveling, using the received various types of assistance information. The assistance information includes, for example, a travel path recommended for the vehicle to travel along and a speed plan indicating vehicle speeds at which the vehicle travels.
Next, an autonomous driving assistance program executed by the CPU 51 in the navigation device 1 according to the present embodiment that has the above-described configuration will be described based on
First, in the autonomous driving assistance program, at step (hereinafter, abbreviated as S) 1, the CPU 51 obtains a destination which is a user's movement target. Basically, the destination is set by a user's operation accepted by the navigation device 1. Note that the destination may be a parking lot or may be a point other than a parking lot. Note, however, that when a point other than a parking lot is the destination, a parking lot where the user parks the vehicle at the destination is also obtained together with the destination. When the destination has a dedicated parking lot or an associated parking lot, the parking lot is a parking lot where the user parks the vehicle. On the other hand, when there is no dedicated parking lot or associated parking lot, a parking lot present around the destination is a parking lot where the user parks the vehicle. Note that when there are a plurality of candidates for a parking lot, all parking lots which are the candidates may be obtained as a parking lot where the user parks the vehicle, or any one of the parking lots selected by the user may be obtained as a parking lot where the user parks the vehicle.
Then, at S2, the CPU 51 obtains a candidate for a parking location (parking space) that is recommended for the user to park the vehicle in the parking lot in which the user parks the vehicle and which is obtained at the above-described S1. Specifically, layout information of parking spaces provided in the parking lot where the user parks the vehicle is obtained from the server device 4, and furthermore, information on open parking spaces is obtained from a server that manages the parking lot, and a parking space that is easy for the user to stop the vehicle (e.g., a parking space near an entrance to the parking lot, a parking space near an entrance to the destination, or a parking space with no other vehicles parked on the left and right sides thereof) is determined to be a candidate for a parking location recommended for the user to park the vehicle, from among the open parking spaces in the parking lot. Note that all open parking spaces in the parking lot may be determined to be candidates for a parking location.
Subsequently, at S3, the CPU 51 searches for recommended travel routes for the vehicle to take from a current vehicle location to the candidate for a parking location obtained at the above-described S2 (hereinafter, referred to as candidate parking location). In the present embodiment, the search for travel routes at the above-described S3 is performed, particularly, by the server device 4. When a search for travel routes is performed, first, the CPU 51 transmits a route search request to the server device 4. Note that the route search request includes a terminal ID that identifies the navigation device 1 which is a sender of the route search request; and information that identifies a point of departure (e.g., a current vehicle location) and the candidate parking location obtained at the above-described S2. Thereafter, the CPU 51 receives searched-route information transmitted from the server device 4 in response to the route search request. The searched-route information is information that identifies recommended travel routes from the point of departure to the candidate parking location (e.g., a series of links included in the travel routes) that are searched by the server device 4 based on the transmitted route search request and using the latest version of map information. The search is performed using, for example, the publicly known Dijkstra's algorithm.
In addition, when the server device 4 searches for, particularly, a recommended travel route in the parking lot from the entrance to the parking lot to the candidate parking location at the above-described S3, the server device 4 constructs, using the facility information 17 stored in the facility DB 14, links and nodes (construction of an intra-parking-lot network), targeting within the parking lot where the user parks the vehicle, in the same manner as for roads. The facility information 17 includes information that identifies the location of an entrance/exit of the parking lot, information that identifies a layout of parking spaces in the parking lot, information about markings that mark off the parking spaces, information about passages through which the vehicle and pedestrians can pass, information about crosswalks and passage spaces provided for pedestrians, etc. Note that the facility information 17 may be, particularly, information generated by 3D modeling of the parking lot. Using those pieces of information, routes that can be selected by the vehicle in the parking lot are identified, by which an intra-parking-lot network is constructed. Note that the above-described intra-parking-lot network may be constructed in advance for each parking lot across the country and stored in the facility DB 14.
Here, an example of an intra-parking-lot network which is constructed for the parking lot at the above-described S3 is shown in
In addition, a cost and a direction (a direction in which the vehicle can pass through a parking lot node) are set for each of the parking lot nodes 58 and parking lot links 59 constructed as shown in
Furthermore, for a case in which the current vehicle location is, particularly, in the parking lot and the destination is outside the parking lot, when the server device 4 searches for a recommended travel route in the parking lot from the current vehicle location to an exit of the parking lot, too, the server device 4 constructs an intra-parking-lot network such as that shown in
Thereafter, the server device 4 calculates, using Dijkstra's algorithm, a total of costs to reach the candidate parking location from the current vehicle location via the entrance to the parking lot (also via the exit of the parking lot when the current vehicle location is in the parking lot and the destination is outside the parking lot), and determines a route with the smallest total value to be a vehicle's recommended travel route. Note, however, that instead of identifying only one recommended travel route, particularly, for a travel route in the parking lot, when there are a plurality of candidates, the plurality of candidates are obtained as vehicle's recommended travel routes. For example, as shown in
Note that for a case in which a traveling direction in which the vehicle can enter the parking lot from a road facing the entrance to the parking lot where the user parks the vehicle (hereinafter, referred to as entry road) is limited (e.g., only an entry by a left turn is allowed) which is found out by referring to connection information 18 indicating a connection relationship between a lane included in the entry road and the entrance to the parking lot, the server device 4 performs the above-described search for a travel route, taking also into account the entry direction. Note that for a method of searching for a route, search means other than Dijkstra's algorithm may be used. Note also that the search for a travel route at the above-described S3 may be performed by the navigation device 1 instead of the server device 4.
Then, at S4, the CPU 51 obtains high-precision map information 16, targeting areas including each of the vehicle's travel routes obtained at the above-described S3.
Here, the high-precision map information 16 is, as shown in
The high-precision map information 16 includes, for example, information about the lane geometries of roads and markings (centerlines, lane lines, edge lines, guidelines, etc.) painted on the roads. In addition to the information, the high-precision map information 16 also includes information about intersections, information about parking lots, etc. The high-precision map information 16 is basically obtained in units of the above-described rectangular areas from the server device 4, but when there is high-precision map information 16 for an area that is already stored in the cache 46, the high-precision map information 16 is obtained from the cache 46. In addition, the high-precision map information 16 obtained from the server device 4 is temporarily stored in the cache 46.
In addition, at the above-described S4, the CPU 51 also obtains facility information 17, targeting the parking lot in which the user parks the vehicle and which is identified at the above-described S1. Furthermore, the CPU 51 also likewise obtains connection information 18 indicating a connection relationship between a lane included in an entry road facing the entrance to the parking lot where the user parks the vehicle and the entrance to the parking lot, and outside-the-road geometry information 19 that identifies a region between the entry road and the entrance to the parking lot where the user parks the vehicle, through which the vehicle can pass.
The facility information 17 includes, for example, information that identifies the location of the entrance/exit of the parking lot, information that identifies a layout of parking spaces in the parking lot, information about markings that mark off the parking spaces, information about passages through which the vehicle and pedestrians can pass, and information about crosswalks in the parking lot and passage spaces provided for pedestrians. The facility information 17 may be, particularly, information generated by 3D modeling of the parking lot. In addition, the facility information 17, the connection information 18, and the outside-the-road geometry information 19 are basically obtained from the server device 4, but when corresponding information is already stored in the cache 46, the information is obtained from the cache 46. In addition, the facility information 17, connection information 18, and outside-the-road geometry information 19 obtained from the server device 4 are temporarily stored in the cache 46.
Thereafter, at S5, the CPU 51 performs a static travel path generating process (
Then, at S6, the CPU 51 creates a vehicle's speed plan used upon traveling along the static travel path generated at the above-described S5, based on the high-precision map information 16 obtained at the above-described S4. For example, vehicle's travel speeds recommended upon traveling along the static travel path are calculated taking into account speed limit information and speed change points (e.g., intersections, curves, railroad crossings, and crosswalks) present on a planned travel route.
Then, the speed plan created at the above-described S6 is stored in the flash memory 54, etc., as assistance information used for autonomous driving assistance. In addition, an acceleration plan indicating acceleration and deceleration of the vehicle required to implement the speed plan created at the above-described S6 may also be created as assistance information used for autonomous driving assistance.
Subsequently, at S7, the CPU 51 determines, as road conditions around the vehicle, particularly, whether or not a factor that affects vehicle's travel is present around the vehicle, by performing image processing on a captured image having been captured with the exterior camera 39. Here, the “factor that affects vehicle's travel” to be determined at the above-described S7 is a dynamic factor that changes in real time, and static factors based on road structures are excluded. The factor that affects vehicle's travel corresponds, for example, to another vehicle that travels or is parked ahead in a vehicle's traveling direction, a pedestrian located ahead in the vehicle's traveling direction, or a construction zone present ahead in the vehicle's traveling direction. On the other hand, intersections, curves, railroad crossings, merge areas, lane reduction areas, etc., are excluded. In addition, even if there is another vehicle, a pedestrian, or a construction zone, if there is no possibility of them overlapping a vehicle's future travel path (e.g., if they are located away from the vehicle's future travel path), then they are excluded from the “factor that affects vehicle's travel”. In addition, for means for detecting a factor that possibly affects vehicle's travel, a sensor such as millimeter-wave radar or a laser sensor, vehicle-to-vehicle communication, or roadside-device-to-vehicle communication may be used instead of a camera.
In addition, for example, the real-time locations of vehicles traveling on roads across the country, etc., may be managed by an external server, and the CPU 51 may obtain the location of another vehicle located around the vehicle from the external server to perform the determination process at the above-described S7.
If it is determined that a factor that affects vehicle's travel is present around the vehicle (S7: YES), then processing transitions to S8. On the other hand, if it is determined that a factor that affects vehicle's travel is not present around the vehicle (S7: NO), then processing transitions to S11.
At S8, the CPU 51 generates, as a dynamic travel path, a new path for the vehicle to travel from the current vehicle location, avoiding or following the “factor that affects vehicle's travel” detected at the above-described S7, and then travel back to the static travel path. Note that the dynamic travel path is generated targeting a section including the “factor that affects vehicle's travel”. Note also that the length of the section varies depending on what the factor is. For example, when the “factor that affects vehicle's travel” is another vehicle (vehicle ahead) traveling ahead of the vehicle, as shown in
A method of calculating the dynamic travel path 70 shown in
Then, a second path L2 is calculated in which the vehicle travels in the right lane with a speed limit being an upper limit, to pass the vehicle ahead 69 and travels until an appropriate vehicle-to-vehicle distance D or more is obtained between the vehicle and the vehicle ahead 69. Note that the second path L2 is basically a straight path, and the length of the path is calculated based on the vehicle speed of the vehicle ahead 69 and the speed limit for the road.
Subsequently, a third path L3 is calculated that is required for the vehicle to move back into the left lane by starting a turn of the steering and for the steering position to return to the straight-ahead direction. Note that for the third path L3, a path that is as smooth as possible and has the shortest possible distance required for a lane change is calculated using a clothoid curve or an arc on conditions that lateral acceleration (lateral G) occurring upon making a lane change does not interfere with autonomous driving assistance and does not exceed an upper limit value (e.g., 0.2 G) at which a vehicle's passenger is not given discomfort, the lateral G being calculated based on the current vehicle speed of the vehicle. In addition, another condition is that an appropriate vehicle-to-vehicle distance D or more is maintained between the vehicle and the vehicle ahead 69.
Note that a dynamic travel path is generated based on road conditions around the vehicle which are obtained using the exterior camera 39 and other sensors, and thus, a region for which a dynamic travel path is to be generated is at least within an area (detection range) in which road conditions around the vehicle can be detected using the exterior camera 39 and other sensors.
Subsequently, at S9, the CPU 51 reflects the dynamic travel path which is newly generated at the above-described S8 in the static travel path generated at the above-described S5. Specifically, a cost is calculated for a portion of each of the static travel path and the dynamic travel path from the current vehicle location to the end of a section including the “factor that affects vehicle's travel”, and a travel path with the lowest cost is selected. Consequently, a part of the static travel path is replaced by the dynamic travel path as necessary. Note that depending on the situation, replacement by the dynamic travel path may not be performed, i.e., even if reflection of the dynamic travel path is performed, there may be no change in the static travel path generated at the above-described S5. Furthermore, when the dynamic travel path and the static travel path are identical paths, even if replacement is performed, there may be no change in the static travel path generated at the above-described S5.
Then, at S10, the CPU 51 modifies, for the static travel path in which the dynamic travel path has been reflected at the above-described S9, the vehicle's speed plan created at the above-described S6, based on a change made by the reflected dynamic travel path. Note that when there is no change in the static travel path generated at the above-described S5 as a result of reflecting the dynamic travel path, the process at S10 may be omitted.
Subsequently, at S11, the CPU 51 computes the amounts of control for the vehicle to travel along the static travel path generated at the above-described S5 (when the dynamic travel path is reflected at the above-described S9, a path obtained after the reflection) at speeds in accordance with the speed plan created at the above-described S6 (when the speed plan is modified at the above-described S10, a plan obtained after the modification). Specifically, each of the amounts of control of an accelerator, a brake, a gear, and steering is computed. Note that the processes at S11 and S12 may be performed by the vehicle control ECU 40 that controls the vehicle, instead of the navigation device 1.
Thereafter, at S12, the CPU 51 reflects the amounts of control computed at S11. Specifically, the computed amounts of control are transmitted to the vehicle control ECU 40 through the CAN. The vehicle control ECU 40 performs vehicle control of each of the accelerator, the brake, the gear, and the steering based on the received amounts of control. As a result, it becomes possible to perform travel assistance control for traveling along the static travel path generated at the above-described S5 (when the dynamic travel path is reflected at the above-described S9, a path obtained after the reflection) at speeds in accordance with the speed plan created at the above-described S6 (when the speed plan is modified at the above-described S10, a plan obtained after the modification).
Then, at S13, the CPU 51 determines whether or not the vehicle has traveled a certain distance since the generation of a static travel path at the above-described S5. For example, the certain distance is 1 km.
If it is determined that the vehicle has traveled a certain distance since the generation of a static travel path at the above-described S5 (S13: YES), then processing returns to S4. Thereafter, a static travel path is generated again, targeting a section within the predetermined distance from a current vehicle location along the travel route (S4 to S6). Note that, in the present embodiment, every time the vehicle has traveled a certain distance (e.g., 1 km), a static travel path is repeatedly generated targeting a section within the predetermined distance from a current vehicle location along the travel route, but when the distance to the destination is short, static travel paths to the destination may be generated at a time at the time of starting traveling.
On the other hand, if it is determined that the vehicle has not traveled a certain distance since the generation of a static travel path at the above-described S5 (S13: NO), then it is determined whether or not to terminate the assistance travel by autonomous driving assistance (S14). A case of terminating the assistance travel by autonomous driving assistance includes a case in which the travel by autonomous driving assistance is intentionally canceled (override) by the user operating a control panel provided on the vehicle or by the user performing a steering wheel operation, a brake operation, etc., in addition to a case in which the vehicle has reached the destination.
If it is determined to terminate the assistance travel by autonomous driving assistance (S14: YES), then the autonomous driving assistance program is terminated. On the other hand, if it is determined to continue the assistance travel by autonomous driving assistance (S14: NO), then processing returns to S7.
Next, a subprocess of the static travel path generating process performed at the above-described S5 will be described based on
First, at S21, the CPU 51 obtains a current vehicle location detected by the current location detecting part 31. Note that it is desirable to specifically identify a current vehicle location using, for example, high-precision GPS information or a high-precision location technique. Here, the high-precision location technique is a technique in which white lines or road surface painting information that is/are captured with a camera installed on the vehicle is/are detected by image recognition, and furthermore, the detected white lines or road surface painting information is/are checked against, for example, high-precision map information 16, by which a driving lane or a high-precision vehicle location can be detected. Furthermore, when the vehicle travels on a road having a plurality of lanes, a lane in which the vehicle travels is also identified. In addition, for a case in which the vehicle is located in a parking lot, a specific location in the parking lot (e.g., a parking space where the vehicle is located) and a vehicle's posture (e.g., a vehicle's traveling direction or when the vehicle is located in a parking space, in which direction the vehicle is parked in the parking space) are also identified.
At and after the following S22, the CPU 51 calculates, for the vehicle's recommended travel route from the current vehicle location to the candidate parking location which is searched at the above-described S3, a travel path recommended upon traveling on the travel route. In addition, for a case in which, particularly, a plurality of routes are searched at the above-described S3 as candidates for a travel route recommended in the parking lot, a travel path is generated for each route, and a final travel route is also determined from among the plurality of routes by comparing the generated plurality of travel paths.
First, at S22, the CPU 51 obtains an intra-parking-lot network for the parking lot in which the user parks the vehicle and which is obtained at the above-described S1, and calculates, for each travel route searched at the above-described S3, a travel path (a candidate for a travel path) that can be taken by the vehicle from the entrance to the parking lot where the vehicle enters the parking lot at the destination up to the point where the vehicle is parked in the parking space which is a candidate parking location by moving along the route, using the intra-parking-lot network and the facility information 17 (including layout information of parking spaces in the parking lot). In addition, for a case in which the current vehicle location is in the parking lot, an intra-parking-lot network for the parking lot in which the user is located is obtained, and for each travel route searched at the above-described S3, a travel path that can be taken by the vehicle from the current vehicle location up to the point where the vehicle moves to the exit of the parking lot by moving along the route is also likewise calculated using the intra-parking-lot network and the facility information 17 (including layout information of parking spaces in the parking lot). Namely, at the above-described S22, a candidate for a travel path for a portion of the travel route searched at the above-described S3 in which the vehicle travels in the parking lot is calculated.
Note that the intra-parking-lot network is, as described above, a network that identifies routes that can be selected by the vehicle in the parking lot, and includes, as shown in
Here,
In addition, in the above-described implementation example, reverse parking is selected as a vehicle's posture taken when the vehicle is parked in the parking space, and a travel path that can be taken up to the point where the vehicle is parked in reverse parking in the parking space which is a candidate parking location is generated as a candidate for a travel path, but forward parking may be selected and a travel path that can be taken up to the point where the vehicle is parked in forward parking in the parking space which is a candidate parking location may be generated as a candidate for a travel path. In addition, each of a candidate for a travel path in which reverse parking is selected and a candidate for a travel path in which forward parking is selected may be generated, and a cost may be calculated for each travel path as will be described later to compare the costs, by which a vehicle's posture taken when the vehicle is finally parked may be determined.
At S23, the CPU 51 calculates a cost required for vehicle's travel, taking into account vehicle behavior taken when the vehicle travels along the candidate for a travel path generated at the above-described S22. For a case in which a plurality of candidates for a travel path are generated, a cost is calculated for each of the plurality of candidates for a travel path. A method of calculating a cost at the above-described S23 will be described in detail below.
Specifically, by adding together costs calculated based on the following elements (1) to (6), a final cost is calculated for each candidate for a travel path.
First, for (1), a cost is determined by a moving distance on a travel path. Specifically, a higher cost is calculated for the longer total length of a travel path. Namely, it can be seen that such a travel path is less likely to be selected as a recommended travel path.
On the other hand, for (2), a cost is determined by, particularly, a moving distance that the vehicle moves backward in a travel path. Specifically, a higher cost is calculated for a longer backing distance. Note that compared to (1), the coefficient is 10 times larger, and thus, there is a possibility that a travel path having a short total length but having a long backing distance has a higher cost than a travel path having a long total length.
In addition, for (3), a cost is determined based on the number of shifts from forward movement to backward movement and vice versa included in a travel path. Specifically, a higher cost is calculated for a larger number of shifts from forward movement to backward movement and vice versa. Namely, it can be seen that such a travel path is less likely to be selected as a recommended travel path.
In addition, for (4), a cost is determined based on the amount of vehicle's turning angle required upon traveling along a travel path. Specifically, a higher cost is calculated for a travel path having a larger amount of turning angle, i.e., having a larger amount of steering operation. Namely, it can be seen that such a travel path is less likely to be selected as a recommended travel path.
In addition, for (5), a cost is determined based on the number of changes in steering turning direction included in a travel path. Specifically, a higher cost is calculated for a larger number of changes in steering turning direction. Namely, it can be seen that such a travel path is less likely to be selected as a recommended travel path.
Finally, for (6), a cost is determined by, particularly, a distance that the vehicle travels in a conditional traveling-prohibited region in a travel path. Specifically, a higher cost is calculated for a longer distance that the vehicle travels in a conditional traveling-prohibited region. Note that basically, it is considered that the vehicle has traveled in a conditional traveling-prohibited region if even a part of the vehicle body has entered the conditional traveling-prohibited region. The term “conditional traveling-prohibited region” used here refers to a region that does not allow passage of the vehicle in a state in which there is an obstacle in the region while allowing passage of the vehicle if there is no obstacle in the region. Note that the obstacle is, for example, a pedestrian or a wheelchair. Namely, the “conditional traveling-prohibited region” specifically corresponds to a crosswalk provided in a parking lot or a passage space provided for pedestrians (note, however, that a passage dedicated for pedestrians where vehicle entry is prohibited is excluded). Information that identifies conditional traveling-prohibited regions is included in the facility information 17. For example, as shown in
Note that when a cost is calculated for a candidate for a travel path at the above-described S23, the cost may be calculated taking into account only some of the above-described elements (1) to (6), instead of taking into account all elements (1) to (6). For example, a total value of the costs (1), (2), (3), and (5) may be calculated.
Thereafter, at S24, the CPU 51 compares the costs for the respective candidates for a travel path calculated at the above-described S23, and selects a travel path for which the lowest cost is calculated among the candidates for a travel path from the entrance to the parking lot at the destination to the parking location where the vehicle is parked, as a vehicle's recommended travel path from the entrance to the parking lot at the destination to the parking location where the vehicle is parked. As a result, a parking location where the vehicle is parked is also determined from among the candidate parking locations obtained at the above-described S2. Specifically, a parking space located at an end point of the selected travel path serves as a parking location where the vehicle is parked. In addition, for a case in which the current vehicle location is in the parking lot, a travel path for which the lowest cost is calculated among candidates for a travel path from the current vehicle location in the parking lot to the exit of the parking lot is selected as a vehicle's recommended travel path from the current vehicle location in the parking lot to the exit of the parking lot.
As a result, when the travel path 71 shown in
In addition, in the above-described implementation example, a parking location where the vehicle is parked and a travel path are selected taking into account a burden on vehicle's travel to the destination, but a parking location where the vehicle is parked and a travel path may be selected taking also into account a burden on vehicle's travel upon going back home from the destination. For example, at the above-described S22, in addition to outward travel paths from the entrance to the parking lot to the candidate parking location, return travel paths from the candidate parking location to the exit of the parking lot are also obtained. Then, at the above-described S23, a cost may be calculated targeting each of the outward travel paths from the entrance to the parking lot to the candidate parking location and the return travel paths from the candidate parking location to the exit of the parking lot, and at the above-described S24, a travel path with the smallest total of costs may be selected. As a result, it become possible to select a parking location where the vehicle is parked and a travel path, taking also into account a burden on vehicle's travel upon going back home from the destination.
Then, at S25, the CPU 51 constructs a lane network, targeting a portion, where the vehicle travels on roads, of the vehicle's recommended travel route from the current vehicle location to the candidate parking location which is searched at the above-described S3, based on the high-precision map information 16 obtained at the above-described S4. The high-precision map information 16 includes lane geometries, marking information, and information about intersections, and furthermore, the lane geometries and the marking information include, for example, information that identifies the number of lanes, how and at which location the number of lanes increases or decreases when there is an increase or decrease in the number of lanes, a passage segment in a traveling direction for each lane, a connection between roads for each lane (specifically, a correspondence between a lane included in a road before passing through an intersection and a lane included in a road after passing through the intersection), and guidelines (white guidelines) at intersections. The lane network generated at the above-described S25 is a network representing lane-to-lane movements that can be selected by the vehicle when the vehicle travels on the candidate for a travel route searched at the above-described S3. When there are a plurality of candidates for a travel route searched at the above-described S3, the above-described lane network is constructed for the plurality of candidate routes. In addition, the lane network is constructed targeting a section from the current vehicle location (note, however, that for a case in which the current vehicle location is in the parking lot, an exit road facing the exit of the parking lot) to an entry road facing the entrance to the parking lot where the user parks the vehicle at the destination.
Here, as an example of constructing a lane network at the above-described S25, for example, a case in which the vehicle travels on a travel route shown in
As shown in
In addition, the above-described lane network includes information that identifies, particularly, by a connection of lane nodes with a lane link at an intersection, a correspondence between a lane included in a road before passing through the intersection and a lane included in a road after passing through the intersection, i.e., a lane into which the vehicle can move after passing through the intersection from a lane used before passing through the intersection. Specifically, the lane network indicates that the vehicle can move between lanes corresponding to lane nodes that are connected by a lane link among lane nodes set on a road used before passing through an intersection and lane nodes set on a road used after passing through the intersection. To generate such a lane network, the high-precision map information 16 stores, for each road connected to an intersection, lane flags indicating a correspondence between lanes and set for each combination of a road that enters the intersection and a road that exits the intersection. Upon constructing a lane network at the above-described S25, the CPU 51 forms a connection of lane nodes with a lane link at an intersection by referring to the lane flags.
Subsequently, at S26, the CPU 51 connects the lane network constructed at the above-described S25 to the intra-parking-lot network constructed at the above-described S22. Specifically, those networks are connected together by newly setting a node on the entry road facing the entrance to the parking lot and near the entrance to the parking lot where the vehicle is parked, with reference to the location of a node at the entrance to the parking lot which is set in the parking network, and connecting the newly set node to the node at the entrance to the parking lot by a link.
Thereafter, at S27, in the constructed lane network, the CPU 51 sets a movement start point, at which the vehicle starts moving, at a lane node located at a starting point of the lane network, and sets a movement target point, which is a target to which the vehicle moves, at an end point of the lane network, i.e., a lane node connected to the entrance to the parking lot (a lane node provided so as to correspond to the entry point). Then, the CPU 51 searches for a route that continuously connects the movement start point to the movement target point, by referring to the constructed lane network. For example, using Dijkstra's algorithm, a route with the smallest total value of lane costs is identified as a vehicle's way of moving into lanes which is recommended when the vehicle moves. Note that the lane cost is set, for example, using, as a reference value, the length of a lane link 86 or the time required for movement on the lane link 86, and taking into account whether or not there is a lane change and the number of lane changes. Note, however, that search means other than Dijkstra's algorithm may be used as long as a route that continuously connects the movement start point to the movement target point can be searched.
Thereafter, at S28, using the high-precision map information 16, facility information 17, connection information 18, and outside-the-road geometry information 19 obtained at the above-described S4, the CPU 51 generates a specific travel path for the vehicle to travel along the route identified in the above-described lane network. Note that for a travel path of a section involving lane changes, the locations of the lane changes are set such that the lane changes are not continuously made as much as possible and are made at recommended locations a predetermined distance away from an intersection. In addition, particularly, in a case of generating a travel path taken upon making a left or right turn at an intersection or making a lane change, lateral acceleration (lateral G) occurring in the vehicle is calculated, and paths that are connected as smoothly as possible are calculated using a clothoid curve or an arc on conditions that the lateral G does not interfere with autonomous driving assistance and does not exceed an upper limit value (e.g., 0.2 G) at which a vehicle's passenger is not given discomfort. On the other hand, for a section that is neither a section in which a lane change is made nor a section at an intersection, a path that passes through the center of a lane serves as a travel path recommended for the vehicle to travel along. Note, however, that for a curved corner that is curved at a substantially right angle, it is desirable to round a portion of a path corresponding to the corner. By performing the above-described process, a travel path is generated that is recommended for the vehicle to travel along from the current vehicle location to the entry point.
Subsequently, at S29, the CPU 51 calculates, particularly, a travel path recommended upon entering the parking lot from the entry road when the vehicle moves along the vehicle's recommended travel route from the current vehicle location to the candidate parking location which is searched at the above-described S3.
For example,
Thereafter, at S30, the CPU 51 connects together the travel paths calculated at the above-described S24, S28, and S29, thereby generating a static travel path which is a travel path recommended for the vehicle to travel along. The static travel path generated at the above-described S30 includes a first travel path recommended for the vehicle to travel along in lanes from the travel start point to the entry road facing the entrance to the parking lot; a second travel path recommended for the vehicle to travel along from the entry road to the entrance to the parking lot; and a third travel path recommended for the vehicle to travel along from the entrance to the parking lot to the parking location (parking space) where the vehicle is parked.
Then, the static travel path generated at the above-described S30 is stored in the flash memory 54, etc., as assistance information used for autonomous driving assistance. Thereafter, processing transitions to S6.
In addition, although, in the above-described implementation example, a travel path taken upon traveling in the parking lot, a travel path taken upon traveling on roads, and a travel path that enters the parking lot from a road are individually generated (S24, S28, and S29), travel paths including all vehicle's movements from a current vehicle location to a candidate parking location in the parking lot may be generated at once by connecting an intra-parking-lot network to a lane network.
As described in detail above, in the navigation device 1 and a computer program executed by the navigation device 1 according to the present embodiment, when a vehicle is parked in a parking lot, layout information of parking spaces provided in the parking lot is obtained and a parking location where the vehicle is parked is obtained from among the parking spaces (S2), an intra-parking-lot network which is a network representing routes that can be selected by the vehicle in the parking lot is obtained (S3), a travel path from an entrance to the parking lot up to the point where the vehicle is parked in the parking location is generated using the intra-parking-lot network and the layout information of parking spaces, the travel path identifying vehicle's travel locations in the parking lot (S5), and driving assistance based on the generated travel path is provided (S11 and S12), and thus, it becomes possible to derive, when the vehicle is parked in a parking lot, a travel path from an entrance to the parking lot up to the point where the vehicle is parked in a parking location, the travel path identifying specific travel locations in the parking lot. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
In addition, a posture of the vehicle taken when the vehicle is parked in the parking location is selected, and a vehicle's travel path from the entrance to the parking lot up to the point where the vehicle is parked in the selected posture is generated using the intra-parking-lot network and the layout information of parking spaces (S5), and thus, by taking into account the posture of the vehicle taken when the vehicle is parked, it becomes possible to derive a more specific travel path.
In addition, candidate entry paths which are candidates for a vehicle's travel path from the entrance to the parking lot up to the point where the vehicle is parked in the parking location are obtained (S22), and a moving cost required for the vehicle to travel along each candidate entry path is calculated taking into account vehicle behavior taken when the vehicle travels along the candidate entry path (S23), and furthermore, a recommended travel path is selected from among the candidate entry paths, using the calculated moving costs (S24), and thus, by reflecting various burdens or risks, which occur in the vehicle upon traveling in the parking lot, in costs, compared to conventional cases, it becomes possible to more appropriately derive a travel path recommended when the vehicle is parked in the parking lot.
In addition, a candidate exit path which is a candidate for a vehicle's travel path from the parking location where the vehicle is parked to an exit of the parking lot is obtained, and a moving cost required for the vehicle to travel along the candidate exit path is calculated taking into account vehicle behavior taken when the vehicle travels along the candidate exit path, and furthermore, a recommended travel path from the entrance to the parking lot to the parking location where the vehicle is parked is selected using the moving cost calculated by cost-for-exit calculating means in addition to the calculated moving costs (S24), and thus, by reflecting various burdens or risks, which occur in the vehicle upon return movement from a destination in addition to outward movement to the destination, in costs, compared to conventional cases, it becomes possible to more appropriately derive a travel path recommended when the vehicle is parked in the parking lot.
In addition, when there are a plurality of candidates for a parking location where the vehicle is parked in the parking lot, a candidate for a travel path is obtained for each candidate for a parking location (S22), and using the calculated moving costs, a parking location where the vehicle is parked is selected from among the candidates for a parking location, and a recommended travel path from the entrance to the parking lot to the selected parking location is selected (S24), and thus, by reflecting various burdens or risks, which occur in the vehicle upon traveling in the parking lot, in costs, it becomes possible to appropriately derive a parking location recommended when the vehicle is parked in the parking lot from among the plurality of candidates.
The vehicle behavior includes at least one or more of a distance traveled by the vehicle in the parking lot, a vehicle's backing distance, the number of shifts from forward movement to backward movement and vice versa, the number of changes in steering turning direction, and a distance traveled in a conditional traveling-prohibited region that conditionally allows passage of the vehicle in the parking lot, and thus, by reflecting various burdens or risks, which occur in the vehicle upon traveling in the parking lot, in costs, compared to conventional cases, it becomes possible to more appropriately derive a travel path recommended when the vehicle is parked in the parking lot.
In addition, the conditional traveling-prohibited region is a region that does not allow passage of the vehicle in a state in which there is an obstacle in the region while allowing passage of the vehicle if there is no obstacle in the region, and thus, by reflecting, particularly, the risk of traveling on a crosswalk, a passage space provided for pedestrians, etc., in costs, compared to conventional cases, it becomes possible to more appropriately derive a travel path recommended when the vehicle is parked in the parking lot.
In addition, when the vehicle exits the parking lot where the vehicle is parked, layout information of parking spaces provided in the parking lot is obtained and a parking location where the vehicle is parked is obtained from among the parking spaces (S21), an intra-parking-lot network which is a network representing routes that can be selected by the vehicle in the parking lot is obtained (S3), a travel path from the parking location to an exit of the parking location is generated using the intra-parking-lot network and the layout information of parking spaces, the travel path identifying vehicle's travel locations in the parking lot (S5), and driving assistance based on the generated travel path is provided (S11 and S12), and thus, it becomes possible to derive, when the vehicle exits the parking lot, a travel path from the parking location to the exit of the parking lot, the travel path identifying specific travel locations in the parking lot. By using the specific travel path, it becomes possible to provide more appropriate driving assistance compared to conventional cases.
In addition, a posture of the vehicle parked in the parking location is obtained, and a vehicle's travel path from the parking location where the vehicle is parked in the obtained posture to the exit of the parking location is generated using the intra-parking-lot network and the layout information of parking spaces (S5), and thus, it becomes possible to derive a more specific travel path by taking into account the posture of the parked vehicle.
Note that the present disclosure is not limited to the above-described embodiment, and it is, of course, possible to make various modifications and alterations thereto without departing from the spirit and scope of the present disclosure.
For example, in the present embodiment, a plurality of candidates for a parking location are obtained and a parking location is finally determined from among the plurality of candidates at timing at which a static travel path is generated at S5, but one parking location where the vehicle is parked may be determined first and then a travel path to the determined parking location may be generated.
In addition, in the present embodiment, a case is assumed in which a vehicle's travel start point is on a road, but the present disclosure can also be applied to a case in which the travel start point is in a parking lot. In that case, a travel path recommended for the vehicle to travel along from the travel start point to an exit of the parking lot is also derived at the above-described S24.
In addition, in the present embodiment, a cost for a travel path to a parking location is calculated targeting only vehicle's travel (S23), but a cost may be calculated taking also into account movement on foot to a destination made after getting out of the vehicle. Namely, a high cost may be calculated for a travel path to a parking location in which vehicle's travel movement to the parking location is easy but a burden on movement on foot to the destination made thereafter is great.
In addition, in the present embodiment, after generating a travel path to a parking location, vehicle control for traveling along the generated travel path is performed (S11 and S12), but it is also possible to omit processes related to vehicle control at and after S11. For example, the navigation device 1 may be a device that provides guidance on a parking location recommended for parking or provides guidance on a travel path to the user, without performing vehicle control based on the travel path.
In addition, in the present embodiment, a static travel path that is finally generated is information that identifies a specific path (a set of coordinates and lines) along which the vehicle travels, but the static travel path may be information that does not identify a specific path but can identify roads, lanes, and passages where the vehicle is to travel. In addition, instead of identifying a specific travel path, only roads on which the vehicle travels and a parking location where the vehicle is parked in a parking lot may be identified.
In addition, in the present embodiment, a lane network and an intra-parking-lot network are generated using high-precision map information 16 and facility information 17 (S3, S22, and S25), but networks that target roads and parking lots across the country may be stored in advance in a DB, and the networks may be read from the DB as necessary.
In addition, in the present embodiment, high-precision map information included in the server device 4 includes both pieces of information about the lane geometries of roads (lane-by-lane road geometries, curvatures, lane widths, etc.) and information about markings (centerlines, lane lines, edge lines, guidelines, etc.) painted on the roads, but may include only the information about markings or may include only the information about the lane geometries of roads. For example, even when only the information about markings is included, it is possible to estimate information corresponding to the information about the lane geometries of roads, based on the information about markings. In addition, even when only the information about the lane geometries of roads is included, it is possible to estimate information corresponding to the information about markings, based on the information about the lane geometries of roads. In addition, the “information about markings” may be information that identifies the types or layout of markings themselves that mark off lanes, or may be information that identifies whether or not a lane change can be made between adjacent lanes, or may be information that directly or indirectly identifies the geometries of lanes.
In addition, in the present embodiment, as means for reflecting a dynamic travel path in a static travel path, a part of the static travel path is replaced by the dynamic travel path (S9), but instead of replacement, the static travel path may be modified to approximate to the dynamic travel path.
In addition, the present embodiment describes that autonomous driving assistance for performing autonomous travel independently of user's driving operations refers to control, by the vehicle control ECU 40, of all of an accelerator operation, a brake operation, and a steering wheel operation which are operations related to vehicle behavior among vehicle's operations. However, the autonomous driving assistance may refer to control, by the vehicle control ECU 40, of at least one of an accelerator operation, a brake operation, and a steering wheel operation which are operations related to vehicle behavior among vehicle's operations. On the other hand, it is described that manual driving by user's driving operations refers to performing, by the user, of all of an accelerator operation, a brake operation, and a steering wheel operation which are operations related to vehicle behavior among vehicle's operations.
In addition, driving assistance of the present disclosure is not limited to autonomous driving assistance related to vehicle's autonomous driving. For example, it is also possible to provide driving assistance by displaying a static travel path identified at the above-described S5 or a dynamic travel path generated at the above-described S8 on a navigation screen and providing guidance using voice, a screen, etc. (e.g., guidance on a lane change or guidance on a recommended vehicle speed). In addition, user's driving operations may be assisted by displaying a static travel path or a dynamic travel path on a navigation screen.
In addition, in the present embodiment, a configuration is adopted in which the autonomous driving assistance program (
In addition, the present disclosure can also be applied to mobile phones, smartphones, tablet terminals, personal computers, etc. (hereinafter, referred to as portable terminals, etc.) in addition to navigation devices. In addition, the present disclosure can also be applied to a system including a server and a portable terminal, etc. In that case, a configuration may be adopted in which each step of the above-described autonomous driving assistance program (see
| Number | Date | Country | Kind |
|---|---|---|---|
| 2021-212531 | Dec 2021 | JP | national |
| 2022-045540 | Mar 2022 | JP | national |
This application is a National Stage of International Application No. PCT/JP2022/047397 filed Dec. 22, 2022, claiming priority based on Japanese Patent Application No. 2021-212531 filed Dec. 27, 2021 and Japanese Patent Application No. 2022-045540 filed Mar. 22, 2022, the entire contents of which are incorporated in their entirety.
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/JP2022/047397 | 12/22/2022 | WO |
