JP7439529B2 - Driving support equipment and computer programs - Google Patents

Description

The present invention relates to a driving support device and a computer program that provide driving support for a vehicle.

In order to provide appropriate driving support when the road on which a vehicle is traveling consists of multiple lanes, it is necessary to identify in advance how the vehicle should move between lanes, that is, the recommended lane movement mode. It is important to keep For example, if a vehicle is to make a left turn at the next intersection, it is necessary to drive the vehicle in a lane marked for left-turn traffic before reaching the intersection. It is best to avoid changing lanes as much as possible. However, unless the recommended lane movement pattern is specified in advance, it will be impossible to determine the lane in which the vehicle should travel and the timing at which lane movement should be made to avoid such events. Driving support cannot be provided.

Therefore, as a means of specifying the recommended lane movement mode in advance, Japanese Patent Laid-Open No. 2018-87764 proposes to generate a lane network for the guidance route, and to create a lane network that connects the end of the lane network to the current position of the vehicle. A technology has been proposed for setting up a network as a lane-by-lane guidance route.

JP 2018-87764 (pages 6-8, Figure 2)

Here, in the technique of Patent Document 1, when tracing the lane network from the end of the lane network (that is, the destination) to the current position of the vehicle, first, from the lane network of the leftmost lane at the end, the direction of the current position of the vehicle is If the lane network is interrupted on the way, return to the end of the lane network from the interrupted point to the point where you can change lanes, then move one lane to the right. I'm following it. That is, the vehicle travels in the left lane as much as possible, and ultimately selects the lane network located in the leftmost lane.

However, depending on the road, it is not always appropriate to drive in the left lane, and in some cases undesirable lane movement may be involved in moving the vehicle to the left lane. Therefore, the technique disclosed in Patent Document 1 has a problem in that it is not possible to specify the most recommended lane movement mode.

The present invention has been made to solve the above-mentioned conventional problems, and it is possible to identify the most recommended lane movement mode using the cost added to the lane network when providing driving support for a vehicle. The object of the present invention is to provide a driving support device and a computer program that make it possible to appropriately implement driving support.

In order to achieve the above object, the driving support device according to the present invention uses a scheduled driving route acquisition means for acquiring a scheduled driving route for the vehicle to travel, and map information including the lane shape, so that the driving support device according to the present invention a lane network construction means for constructing a lane network that is a network indicating lane movements that can be selected by a vehicle; a start lane setting means for setting a starting lane in which a vehicle starts moving with respect to the lane network; Comparison is made using a cost added to the lane network with respect to a target lane setting means for setting a target lane in which a vehicle moves, and a route candidate connecting the starting lane and the target lane in the lane network. and a movement mode specifying means for specifying a lane movement mode recommended for the vehicle when the vehicle moves , and the lane network determines the planned travel route as an intersection entry position and an intersection exit position. , a network that divides the positions where the lanes increase or decrease as boundaries, sets nodes for each lane located at the boundaries of each divided section, and has links connecting the set nodes, Within each of the above-mentioned sections, the links connecting the front and rear nodes in a section including multiple lanes include links connecting nodes set along the same lane, as well as links connecting nodes set along different lanes. Contains links that connect .

Further, the computer program according to the present invention is a program that generates support information used for driving support performed in a vehicle. Specifically, the computer uses a planned driving route acquisition means that acquires the planned driving route for the vehicle to travel, and map information including lane shapes to determine the lane movement that the vehicle can select for the planned driving route. lane network construction means for constructing a lane network that is a network shown in FIG. A target lane setting means for setting a target lane with A computer program for functioning as a movement mode specifying means for specifying a lane movement mode of a vehicle recommended when the vehicle is moving in a lane, the lane network including the lane network that determines the planned travel route from an intersection entry position and an intersection exit position. It is a network that divides the locations and positions where the number of lanes increases or decreases as boundaries, sets nodes for each lane located at the boundaries of each divided section, and has links that connect the set nodes. , in each of the divided sections, links connecting the front and rear nodes in a section including multiple lanes are in addition to links connecting nodes set along the same lane, nodes set in different lanes. Contains links that connect between

According to the driving support device and computer program according to the present invention having the above configuration, when providing driving support for a vehicle, the most recommended lane movement mode is appropriately specified by using the cost added to the lane network. becomes possible. Then, by performing driving support based on the specified lane movement mode, it is possible to appropriately implement driving support.

FIG. 1 is a schematic configuration diagram showing a driving support system according to the present embodiment. FIG. 1 is a block diagram showing the configuration of a driving support system according to the present embodiment. FIG. 1 is a block diagram showing a navigation device according to the present embodiment. It is a flow chart of an automatic driving support program concerning this embodiment. FIG. 3 is a diagram showing areas from which high-precision map information is acquired. It is a flowchart of the sub-processing program of static travel trajectory generation processing. FIG. 2 is a diagram showing an example of a scheduled travel route for a vehicle. 8 is a diagram showing an example of a lane network constructed for the planned travel route shown in FIG. 7. FIG. FIG. 3 is a diagram showing an example of a lane flag indicating a correspondence relationship between a lane included in a road before passing through an intersection and a lane included in a road after passing through an intersection. It is a diagram showing a reference route and a candidate route. FIG. 3 is a diagram showing the relationship between the number of lane changes and lane cost. FIG. 3 is a diagram showing a relationship between a driving lane and a lane cost. FIG. 3 is a diagram showing the relationship between lane change positions and lane costs. FIG. 3 is a diagram illustrating a method for calculating a static travel trajectory in a travel section that involves a lane change. FIG. 3 is a diagram illustrating a method of calculating a static travel trajectory within an intersection. It is a flowchart of the sub-processing program of dynamic travel trajectory generation processing. FIG. 2 is a diagram showing an example of an avoidance trajectory, which is one of dynamic travel trajectories. FIG. 2 is a diagram showing an example of an avoidance trajectory, which is one of dynamic travel trajectories. FIG. 2 is a diagram showing an example of a follow-up trajectory, which is one of the dynamic running trajectories. FIG. 2 is a diagram showing an example of a follow-up trajectory, which is one of the dynamic running trajectories. It is a flowchart of the sub-processing program of travel trajectory reflection processing.

DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment in which a driving support 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 support system 2 including a navigation device 1 according to the present embodiment will be described using FIGS. 1 and 2. FIG. 1 is a schematic configuration diagram showing a driving support system 2 according to this embodiment. FIG. 2 is a block diagram showing the configuration of the driving support system 2 according to this embodiment.

As shown in FIG. 1, the driving support system 2 according to the present embodiment includes a server device 4 included in an information distribution center 3, a navigation device 1 that is installed in a vehicle 5 and provides various types of support related to automatic driving of the vehicle 5, basically has. Further, 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 the communication network 6. Note that instead of the navigation device 1, another on-vehicle device mounted on the vehicle 5 or a vehicle control device that performs control regarding the vehicle 5 may be used.

Here, the vehicle 5 is operated in a manual driving mode in which the vehicle travels based on the user's driving operation, as well as in an automatic driving mode in which the vehicle automatically travels along a preset route or road regardless of the user's driving operation. The vehicle should be capable of support driving.

Additionally, automatic driving support may be applied to all road sections, or if the vehicle is driving on a specific road section (for example, an expressway with gates (manned, unmanned, toll-free) at the boundaries). It is also possible to have a configuration in which it is performed only during the period. In the following explanation, the automated driving section where automatic driving assistance is provided includes all road sections including general roads and expressways, as well as parking lots, and the automated driving section where the automated driving assistance of the vehicle is provided includes parking lots as well as all road sections including general roads and expressways. The explanation will be based on the assumption that automatic driving support is basically provided during this period. However, when the vehicle travels in an automated driving zone, automated driving support is not always performed, but the user selects to perform automated driving support (for example, by turning on the automated driving start button), and the automated driving support is not always performed. It is desirable to do this only in situations where it has been determined that it is possible to run the vehicle. On the other hand, the vehicle 5 may be a vehicle capable of only assisting driving by automatic driving assistance.

In vehicle control in automatic driving support, for example, the current position of the vehicle, the lane in which the vehicle is traveling, and the positions of surrounding obstacles are detected at any time, and as described later, the vehicle is controlled along the travel trajectory generated by the navigation device 1. The steering, drive source, brakes, etc. of the vehicle are automatically controlled so that the vehicle travels at a speed according to the similarly generated speed plan. In addition, in the supported driving by the automatic driving support of this embodiment, the vehicle is controlled by the automatic driving support when changing lanes or turning left or right, but the automatic driving does not perform special driving such as changing lanes or turning left or right. A configuration may also be adopted in which driving is performed manually without assistance.

On the other hand, the navigation device 1 is installed in the vehicle 5, and displays a map around the vehicle's location based on map data possessed by the navigation device 1 or map data acquired from an external source, and displays the current location of the vehicle on a map image. This is an in-vehicle device that displays information and provides movement guidance along a set guidance route. In this embodiment, especially when the vehicle performs support travel using automatic driving support, various types of support information related to automatic driving support are generated. The support information includes, for example, a travel trajectory on which the vehicle is recommended to travel (including recommended lane movement modes), a speed plan indicating the vehicle speed at which the vehicle will travel, and the like. Note that details of the navigation device 1 will be described later.

Further, the server device 4 executes a route search in response to a request from the navigation device 1. Specifically, when a destination is set in the navigation device 1 or when a route is re-searched (rerouted), the navigation device 1 sends the information necessary for route search, such as the departure point and destination, to the server device 4. Information is sent along with the route search request (however, in the case of re-search, information regarding the destination does not necessarily need to be sent). Then, the server device 4 that has received the route search request performs a route search using the map information possessed by the server device 4, and specifies a recommended route from the departure point to the destination. Thereafter, the identified recommended route is transmitted to the navigation device 1 that made the request. The navigation device 1 then provides information regarding the received recommended route to the user, sets the recommended route as a guide route, and generates various types of support information related to automatic driving support according to the guide route. As a result, even if the map information held by the navigation device 1 at the time of route searching is an old version of map information or the navigation device 1 does not have the map information itself, the latest version of the map held by the server device 4 can be used. Based on this information, it is possible to provide a recommended route to an appropriate destination.

Furthermore, the server device 4 has high-precision map information, which is more accurate map information, in addition to the normal map information used for the route search. High-precision map information includes, for example, the shape of road lanes (road shape, curvature, lane width, etc. for each lane) and the division lines drawn on the road (roadway center line, lane boundary line, outer roadway line, guide line, etc.). Contains information. Additionally, information on intersections, information on parking lots, etc. is also included. Then, the server device 4 distributes high-precision map information in response to a request from the navigation device 1, and the navigation device 1 uses the high-precision map information distributed from the server device 4 to perform various functions related to automatic driving support, as described below. Generate support information. The high-precision map information is basically map information that covers only roads (links) and their surroundings, but it may also include map information that covers areas other than roads.

However, the above-mentioned route search process does not necessarily need to be performed by the server device 4, and may be performed by the navigation device 1 as long as it has map information. Further, the high-precision map information may also be stored in the navigation device 1 in advance, instead of being distributed from the server device 4.

The communication network 6 includes a large number of base stations located throughout the country and communication companies that manage and control each base station, and the base stations and communication companies are connected to each other by wire (optical fiber, ISDN, etc.) or wirelessly. It is configured by connecting. Here, the base station has a transceiver (transceiver) and an antenna for communicating with the navigation device 1. While the base station performs wireless communication between communication companies, it serves as the terminal end of the communication network 6 and relays communication between the navigation device 1 within the radio wave range (cell) of the base station and the server device 4. have a role to play.

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

The server control ECU 11 (electronic control unit) is an electronic control unit that controls the entire server device 4, and is used by the CPU 21 as an arithmetic device and a control device, and as a working memory when the CPU 21 performs various arithmetic processes. It is provided with an internal storage device such as a RAM 22 for storing control programs, 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. It should be noted that the server control ECU 11 has various means as a processing algorithm together with the ECU of the navigation device 1 which will be described later.

On the other hand, the server-side map DB 12 is a storage unit that stores server-side map information that is the latest version of map information registered based on input data and input operations from the outside. 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, network data including nodes and links indicating a 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 for displaying a map. data, search data for searching routes, search data for searching points, etc.

Further, the high-precision map DB 13 is a storage means in which high-precision map information 15, which is map information with higher precision than the server-side map information, is stored. The high-precision map information 15 is map information that stores more detailed information, especially regarding roads and parking lots on which vehicles drive. This information includes information about lane width, etc.) and division lines drawn on the road (roadway center line, lane boundary line, roadway outside line, guide line, etc.). In addition, the high-precision map DB 13 also includes the width, slope, cant, bank, road surface condition, and link shape between nodes (for example, in the case of a curved road, the shape of the link) Shape complement point data for specifying (shape), merging sections, road structure, number of lanes on the road, places where the number of lanes decreases, places where the width becomes narrow, railroad crossings, etc. , data representing entrances and exits of T-junctions, corners, etc. are used for road attributes, and data representing downhill roads, uphill roads, etc. are used for road types, such as general roads such as national highways, prefectural roads, and narrow streets, as well as highways. Data representing toll roads such as national highways, urban expressways, automobile-only roads, general toll roads, and toll bridges are recorded. In particular, in this embodiment, in addition to the number of lanes on the road, the traffic classification of each lane in the direction of travel and the connection of the road (specifically, the number of lanes included in the road before passing through the intersection and the road after passing through the intersection) Information specifying the correspondence relationship with the included lanes is also stored. Furthermore, speed limits set for roads are also stored. Further, although the high-precision map information is basically map information that targets only roads (links) and their surroundings, it may also include map information that includes areas other than roads and their surroundings. In addition, in the example shown in FIG. 2, the server-side map information stored in the server-side map DB 12 and the high-precision map information 15 are different map information, but the high-precision map information 15 may also be used as part of the server-side map information. good.

On the other hand, the server side communication device 14 is a communication device for communicating with the navigation device 1 of each vehicle 5 via the communication network 6. Additionally, in addition to the navigation device 1, traffic information including traffic congestion information, regulation information, traffic accident information, etc. transmitted from the Internet network and a traffic information center, such as a VICS (registered trademark: Vehicle Information and Communication System) center, etc. It is also possible to receive information.

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

As shown in FIG. 3, the navigation device 1 according to the present embodiment includes a current position detection unit 31 that detects the current position of the vehicle in which the navigation device 1 is mounted, a data recording unit 32 in which various data are recorded, Based on the input information, the navigation ECU 33 performs various arithmetic processing, the operation unit 34 receives operations from the user, and the navigation ECU 33 performs various arithmetic processing based on the input information. a liquid crystal display 35 that displays information regarding the route (planned route), a speaker 36 that outputs audio guidance regarding route guidance, a DVD drive 37 that reads a DVD as a storage medium, and an information center such as a probe center or a VICS center. and a communication module 38 that performs communication between the two. Further, the navigation device 1 is connected to an external camera 39 and various sensors installed in the vehicle in which the navigation device 1 is mounted via an in-vehicle network such as CAN. Furthermore, it is also connected to a vehicle control ECU 40 that performs various controls on the vehicle in which the navigation device 1 is mounted so as to be able to communicate bidirectionally.

Below, each component included in the navigation device 1 will be explained in order.
The current position detection unit 31 includes 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 speed, current time, etc. . Here, in particular, the vehicle speed sensor 42 is a sensor for detecting the travel distance and vehicle speed of the vehicle, generates pulses according to the rotation of the drive wheels of the vehicle, and outputs the pulse signal to the navigation ECU 33. Then, the navigation ECU 33 calculates the rotation speed and travel distance of the drive wheels by counting the generated pulses. Note that it is not necessary for the navigation device 1 to include all of the above four types of sensors, and the navigation device 1 may be configured to include only one or more types of sensors.

In addition, the data recording unit 32 reads a hard disk (not shown) as an external storage device and a recording medium, a map information DB 45, a cache 46, a predetermined program, etc. recorded on the hard disk, and writes predetermined data on the hard disk. The printer is equipped with a recording head (not shown) which is a driver for the recording. Note that the data recording section 32 may include a flash memory, a memory card, or an optical disk such as a CD or DVD instead of a hard disk. Furthermore, in this embodiment, as described above, since the route to the destination is searched in the server device 4, the map information DB 45 may be omitted.

Here, the map information DB 45 includes, for example, link data related to roads (links), node data related to node points, search data used for processing related to searching and changing routes, facility data related to facilities, and maps for displaying maps. This is a storage means in which display data, intersection data regarding each intersection, search data for searching for a point, etc. are stored.

On the other hand, the cache 46 is a storage means in which high-precision map information 15 distributed from the server device 4 in the past is stored. The storage period can be set as appropriate, for example, it may be a predetermined period (for example, one month) after being stored, or it may be until the ACC power supply (accessory power supply) of the vehicle is turned off. Alternatively, the oldest data may be deleted sequentially after the amount of data stored in the cache 46 reaches the upper limit. Then, the navigation ECU 33 uses the high-precision map information 15 stored in the cache 46 to generate various types of support information regarding automatic driving support. Details will be described later.

On the other hand, the navigation ECU (electronic control unit) 33 is an electronic control unit that controls the entire navigation device 1, and includes a CPU 51 as an arithmetic unit and a control device, and a working memory when the CPU 51 performs various arithmetic processes. The RAM 52 stores route data when a route is searched, and the ROM 53 stores control programs as well as automatic driving support programs (see Figure 4), which will be described later. It is equipped with an internal storage device such as a flash memory 54 for storing programs. Note that the navigation ECU 33 has various means as processing algorithms. For example, the scheduled driving route acquisition means acquires the scheduled driving route on which the vehicle will travel. The lane network construction means uses map information including lane shapes to construct a lane network that is a network indicating lane movements that the vehicle can select for the planned travel route. The starting lane setting means sets a starting lane in which the vehicle starts moving in the lane network. The target lane setting means sets a target lane in which the vehicle moves in the lane network. The movement mode identifying means searches for a route connecting the starting lane and the target lane using the cost added to the lane network, and determines a recommended lane movement mode of the vehicle when the vehicle moves along the searched route. Specify as.

The operation unit 34 is operated when inputting a departure point as a travel start point and a destination as a travel end point, and has a plurality of operation switches (not shown) such as various keys and buttons. Then, the navigation ECU 33 performs control to execute various corresponding operations based on switch signals output by pressing each switch. Note that the operation unit 34 may include a touch panel provided in front of the liquid crystal display 35. Further, it may include a microphone and a voice recognition device.

The liquid crystal display 35 also displays map images including roads, traffic information, operation guidance, operation menus, key guidance, guidance information along the guidance route (planned route), news, weather forecast, time, email, and television. Programs, etc. are displayed. Note that a HUD or HMD may be used instead of the liquid crystal display 35.

Further, the speaker 36 outputs audio guidance for guiding travel along a guide route (planned travel route) and traffic information based on instructions from the navigation ECU 33.

Further, the DVD drive 37 is a drive that can read data recorded on recording media such as DVDs and CDs. Then, based on the read data, music and video are played back, and the map information DB 45 is updated. Note that a card slot for reading and writing a memory card may be provided in place of the DVD drive 37.

Further, the communication module 38 is a communication device for receiving traffic information, probe information, weather information, etc. transmitted from a traffic information center, such as a VICS center or a probe center, and includes, for example, a mobile phone or a DCM. . It also includes a vehicle-to-vehicle communication device that communicates between vehicles and a road-to-vehicle communication device that communicates with a roadside device. It is also used to send and receive route information and high-precision map information 15 searched by the server device 4 to and from the server device 4 .

Further, the vehicle exterior camera 39 is constituted by a camera using a solid-state imaging device such as a CCD, and is installed above the front bumper of the vehicle, with its optical axis directed downward at a predetermined angle from the horizontal. The external camera 39 captures an image in front of the vehicle in the traveling direction when the vehicle travels in the automatic driving section. In addition, the navigation ECU 33 performs image processing on the captured image to detect obstacles such as lane markings drawn on the road on which the vehicle is traveling and other vehicles in the vicinity, and automatically Generates various support information related to driving support. For example, when an obstacle is detected, a new running trajectory is generated to avoid or follow the obstacle. Note that the external camera 39 may be arranged not only at the front of the vehicle but also at the rear or side. Further, as means for detecting obstacles, sensors such as a millimeter wave radar or a laser sensor, vehicle-to-vehicle communication, or road-to-vehicle communication may be used instead of a camera.

Further, the vehicle control ECU 40 is an electronic control unit that controls a vehicle in which the navigation device 1 is mounted. Further, the vehicle control ECU 40 is connected to each driving part of the vehicle such as steering, brake, accelerator, etc. In this embodiment, especially after automatic driving support is started in the vehicle, by controlling each driving part, the vehicle control ECU 40 Implement automated driving support. Furthermore, if the user performs an override during automatic driving support, the override is detected.

Here, the navigation ECU 33 transmits various types of support information related to automatic driving support generated by the navigation device 1 to the vehicle control ECU 40 via CAN after the start of travel. Then, the vehicle control ECU 40 uses the received various support information to implement automatic driving support after the start of travel. Examples of the support information include a travel trajectory on which the vehicle is recommended to travel, a speed plan indicating the vehicle speed at which the vehicle will travel, and the like.

Next, an automatic driving support program executed by the CPU 51 in the navigation device 1 according to the present embodiment having the above configuration will be described based on FIG. 4. FIG. 4 is a flowchart of the automatic driving support program according to this embodiment. Here, the automatic driving support program is executed after the vehicle's ACC power supply (accessory power supply) is turned on and when the vehicle starts traveling by automatic driving support, and is executed using the support generated by the navigation device 1. This is a program that implements automatic driving support based on information. Further, programs shown in flowcharts in FIGS. 4, 6, 16, and 21 below are stored in the RAM 52 and ROM 53 included in the navigation device 1, and are executed by the CPU 51.

First, in step (hereinafter abbreviated as S) 1 of the automatic driving support program, the CPU 51 acquires a route on which the vehicle is scheduled to travel in the future (hereinafter referred to as a planned travel route). Note that, if a guide route is set in the navigation device 1, the scheduled route for the vehicle to travel is a route from the current position of the vehicle to the destination among the guide routes currently set in the navigation device 1. This is the planned route. On the other hand, if a guide route is not set in the navigation device 1, a route along the road from the current position of the vehicle may be set as the planned route.

Further, the guide route is a recommended route from the departure point to the destination set by the navigation device 1, and is particularly searched by the server device 4 in this embodiment. When searching for a recommended route, the CPU 51 first sends a route search request to the server device 4. Note that the route search request includes a terminal ID that specifies the navigation device 1 that is the source of the route search request, and information that specifies the departure point (for example, the current position of the vehicle) and the destination. Note that information for specifying the destination is not necessarily required at the time of re-search. Thereafter, the CPU 51 receives search route information transmitted from the server device 4 in response to the route search request. The search route information is information that specifies the recommended route (center route) from the departure point to the destination that the server device 4 has searched based on the transmitted route search request using the latest version of map information (for example, information that specifies the recommended route (center route) (included link strings). For example, the search is performed using the well-known Dijkstra method. Then, the CPU 51 sets the received recommended route as a guide route for the navigation device 1.

Next, in S2, the CPU 51 acquires high-precision map information 15 for a section within a predetermined distance from the current position of the vehicle along the planned travel route acquired in S1. For example, high-precision map information 15 is acquired for the planned travel route included in the secondary mesh where the vehicle is currently located. However, the area from which the high-precision map information 15 is to be obtained can be changed as appropriate; for example, the high-precision map information 15 may be obtained for an area within 3 km from the vehicle's current position along the planned travel route. good. Alternatively, the high-precision map information 15 may be acquired for the entire planned travel route.

Here, the high-precision map information 15 is divided into rectangular shapes (for example, 500 m x 1 km) and stored in the high-precision map DB 13 of the server device 4, as shown in FIG. Therefore, for example, when a planned driving route 61 is acquired as shown in FIG. 15 is obtained. The high-precision map information 15 includes, for example, information regarding the lane shape of the road and the division lines drawn on the road (roadway center line, lane boundary line, roadway outside line, guide line, etc.). Additionally, information on intersections, information on parking lots, etc. is also included.

Furthermore, the high-definition map information 15 is basically acquired from the server device 4, but if there is high-definition map information 15 of an area already stored in the cache 46, it is acquired from the cache 46. Further, the high-precision map information 15 acquired from the server device 4 is temporarily stored in the cache 46.

After that, in S3, the CPU 51 executes a static travel trajectory generation process (FIG. 6), which will be described later. Here, the static travel trajectory generation process includes a recommended travel route for the vehicle on roads included in the planned travel route based on the scheduled travel route of the vehicle and the high-precision map information 15 acquired in S2. This process generates a static running trajectory. As will be described later, the static travel trajectory covers a section from the vehicle's current position to a predetermined distance ahead along the direction of travel (for example, within the secondary mesh where the vehicle is currently located, or the entire section to the destination). generated. Although the predetermined distance can be changed as appropriate, the static travel trajectory is designed to cover at least an area outside the range (detection range) in which the road conditions around the vehicle can be detected by the external camera 39 and other sensors. generate.

Next, in S4, the CPU 51 generates a speed plan for the vehicle when traveling on the static travel trajectory generated in S3, based on the high-precision map information 15 acquired in S2. For example, the recommended vehicle speed when traveling on a static trajectory is calculated by taking into account speed limit information and speed change points on the planned route (e.g. intersections, curves, railroad crossings, crosswalks, etc.) do.

Then, the speed plan generated in S4 is stored in the flash memory 54 or the like as support information used for automatic driving support. Further, an acceleration plan indicating acceleration/deceleration of the vehicle necessary to realize the speed plan generated in S4 may also be generated as support information used for automatic driving support.

Next, in S5, the CPU 51 performs image processing on the captured image taken by the external camera 39 to determine whether there are factors affecting the driving of the own vehicle, especially around the own vehicle, as surrounding road conditions. Determine whether or not to do so. Here, the "factors that affect the running of the host vehicle" to be determined in S5 are dynamic factors that change in real time, and static factors such as those based on the road structure are excluded. For example, this includes other vehicles driving or parking in front of the vehicle, pedestrians located in front of the vehicle, construction zones ahead of the vehicle, and the like. On the other hand, intersections, curves, railroad crossings, merging sections, lane reduction sections, etc. are excluded. In addition, even if other vehicles, pedestrians, or construction zones exist, there is no risk that they will overlap with the vehicle's future trajectory (for example, if they are located far away from the vehicle's future trajectory). cases) are excluded from "factors that affect the running of the own vehicle." Further, as means for detecting factors that may affect the running of the vehicle, sensors such as a millimeter wave radar or a laser sensor, vehicle-to-vehicle communication, or road-to-vehicle communication may be used instead of the camera.

If it is determined that there are factors around the host vehicle that affect the running of the host vehicle (S5: YES), the process moves to S6. On the other hand, if it is determined that there are no factors around the host vehicle that affect the running of the host vehicle (S5: NO), the process moves to S9.

In S6, the CPU 51 executes a dynamic traveling trajectory generation process (FIG. 16), which will be described later. Here, the dynamic traveling trajectory generation process generates a new trajectory from the current position of the vehicle to avoid or follow the "factors that affect the traveling of the own vehicle" detected in S5 and return to the static traveling trajectory. is generated as a dynamic running trajectory. Note that the dynamic travel trajectory is generated for a section that includes "factors that affect the travel of the own vehicle" as described later. Furthermore, the length of the section changes depending on the content of the factor. For example, if the "factor that affects the running of your own vehicle" is another vehicle traveling in front of your vehicle (vehicle ahead), for example, change lanes to the right to overtake the vehicle in front, and then change lanes to the left. The trajectory from changing to returning to the original lane is generated as a dynamic driving trajectory. Note that the dynamic traveling trajectory is generated based on the road conditions around the vehicle acquired by the external camera 39 and other sensors, so the area where the dynamic traveling trajectory is generated is at least based on the vehicle external camera 39 and other sensors. This is within the range (detection range) in which the road conditions around the vehicle can be detected by other sensors.

Subsequently, in S7, the CPU 51 executes a traveling trajectory reflection process (FIG. 21), which will be described later. Here, the traveling trajectory reflection process is a process of reflecting the dynamic traveling trajectory newly generated in S6 above to the static traveling trajectory generated in S3. Specifically, the cost of each of the static running trajectory and at least one or more dynamic running tracks is calculated from the current position of the vehicle to the end of the section that includes "factors that affect the running of the own vehicle," The travel trajectory with the minimum cost is selected. As a result, part of the static running track will be replaced by a dynamic running track if necessary. Note that depending on the situation, the dynamic traveling trajectory may not be replaced, that is, even if the dynamic traveling trajectory is reflected, there may be no change from the static traveling trajectory generated in S3. Furthermore, if the dynamic traveling trajectory and the static traveling trajectory are the same trajectory, even if the replacement is performed, there may be no change from the static traveling trajectory generated in S3.

Next, in S8, the CPU 51 calculates the vehicle speed plan generated in S4 based on the contents of the reflected dynamic trajectory for the static trajectory after the dynamic trajectory has been reflected in S7. Fix it. Note that if the reflection of the dynamic trajectory does not change from the static trajectory generated in S3, the process in S8 may be omitted.

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

Thereafter, in S10, the CPU 51 reflects the control amount calculated in S9. Specifically, the calculated control amount is transmitted to the vehicle control ECU 40 via CAN. The vehicle control ECU 40 performs vehicle control of accelerator, brake, gear, and steering based on the received control amount. As a result, the static traveling trajectory generated in S3 (the reflected trajectory if the dynamic traveling trajectory has been reflected in S7) is combined with the speed plan generated in S4 (the speed plan in S8). If the plan has been revised, driving support control that allows the vehicle to travel at a speed according to the revised plan becomes possible.

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

If it is determined that the vehicle has traveled a certain distance after the generation of the static travel trajectory in S3 (S11: YES), the process returns to S1. Thereafter, a static travel trajectory is generated again for a section within a predetermined distance along the planned travel route from the vehicle's current position (S1 to S4). Note that in this embodiment, each time the vehicle travels a certain distance (for example, 1 km), a static travel trajectory is repeatedly generated for a section within a predetermined distance from the vehicle's current position along the planned travel route. However, if the distance to the destination is short, the static travel trajectory to the destination may be generated all at once at the start of travel.

On the other hand, if it is determined in S3 that the vehicle has not traveled a certain distance since the generation of the static travel trajectory (S11: NO), it is determined whether or not to end the support driving by automatic driving support. A determination is made (S12). Autonomous Driving Assist may terminate the supported driving when the user operates the operation panel installed in the vehicle or performs steering wheel or brake operation, other than when the user reaches the destination. In some cases, the vehicle may have been intentionally canceled (overridden).

Then, when it is determined that the support driving by the automatic driving support is to be ended (S12: YES), the automatic driving support program is ended. On the other hand, if it is determined that the support driving by automatic driving support is to be continued (S12: NO), the process returns to S5.

Next, the sub-processing of the static traveling trajectory generation process executed in S3 will be explained based on FIG. 6. FIG. 6 is a flowchart of a sub-processing program for static travel trajectory generation processing.

First, in S21, the CPU 51 acquires the current position of the vehicle detected by the current position detection section 31. Note that it is desirable to specify the current position of the vehicle in detail using, for example, high-precision GPS information or high-precision location technology. Here, high-precision location technology involves detecting white lines and road surface paint information captured from a camera installed in a vehicle through image recognition, and then comparing the detected white lines and road surface paint information with, for example, high-precision map information 15. This technology makes it possible to detect driving lanes and highly accurate vehicle positions. Furthermore, when the vehicle travels on a road consisting of a plurality of lanes, the lane in which the vehicle travels is also specified.

Next, in S22, the CPU 51 determines a section (for example, within a secondary mesh including the current position of the vehicle) for generating a static travel trajectory ahead of the vehicle in the traveling direction, based on the high-precision map information 15 acquired in S2. Information on lane shapes, lane markings, intersections, etc. is acquired. Note that the lane shape and lane marking information acquired in S22 includes the number of lanes, where and how the number of lanes increases or decreases, the traffic classification of each lane in the direction of travel, and the road. Contains information that identifies connections (specifically, the correspondence between lanes included in the road before passing through the intersection and lanes included in the road after passing through the intersection), and guide lines (guide white lines) within the intersection. .

Subsequently, in S23, the CPU 51 constructs a lane network for a section in which a static traveling trajectory is generated in front of the vehicle in the traveling direction, based on the lane shape and marking line information acquired in S22. Here, the lane network is a network indicating lane movements that the vehicle can select.

Here, as an example of constructing the lane network in S23, a case will be described in which a vehicle travels on the planned travel route shown in FIG. 7, for example. The planned travel route shown in FIG. 7 is a route in which the vehicle goes straight from its current position, turns right at the next intersection 71, then turns right at the next intersection 72, and then turns left at the next intersection 73. In the planned travel route shown in FIG. 7, for example, when turning right at intersection 71, it is possible to enter the right lane, or it is also possible to enter the left lane. However, since it is necessary to turn right at the next intersection 72, it is necessary to move to the rightmost lane when entering the intersection 72. Furthermore, when turning right at the intersection 72, it is possible to enter the right lane, or it is also possible to enter the left lane. However, since it is necessary to turn left at the next intersection 73, it is necessary to move to the leftmost lane when entering the intersection 73. FIG. 8 shows a lane network constructed for sections where such lane movement is possible.

As shown in FIG. 8, the lane network divides a section that generates a static travel trajectory in the forward direction of the vehicle into a plurality of sections (groups). Specifically, the intersection entry position, the intersection exit position, and the position where the number of lanes increases or decreases are defined as boundaries. Node points (hereinafter referred to as lane nodes) 75 are set for each lane located at the boundary of each divided section. Furthermore, a link (hereinafter referred to as a lane link) 76 that connects the lane nodes 75 is set.

In addition, the lane network described above also establishes the correspondence relationship between the lanes included in the road before passing through the intersection and the lanes included in the road after passing through the intersection, especially by connecting lane nodes and lane links at intersections. Contains information that specifies the lane in which the vehicle can move after passing through the intersection, relative to the lane before passing through. Specifically, between the lane node set on the road before passing the intersection and the lane node set on the road after passing the intersection, the vehicle is between the lane nodes that are connected by lane links. Indicates that it is movable.

In order to generate such a lane network, the high-precision map information 15 includes lane flags that indicate the correspondence of lanes for each combination of roads that enter and exit the intersection, for each road that connects to the intersection. set and stored. For example, FIG. 9 shows lane flags when entering an intersection from the right road and exiting to the upper road, and lane flags when entering an intersection from the right road and exiting to the left road. Indicates the lane flag when entering an intersection from the road on the right and exiting to the road below. Then, among the lanes included in the road before passing through the intersection, the lane flag is set to "1", and among the lanes included in the road after passing through the intersection, the lane flag is set to "1". This indicates that the lanes correspond to the lanes indicated above, that is, the lanes can be moved before and after passing through the intersection. When constructing the lane network in S23, the CPU 51 refers to the lane flags and forms connections between lane nodes and lane links at intersections.

Next, in S24, the CPU 51 sets, for the lane network constructed in S23, a starting lane in which the vehicle starts moving with respect to the lane node located at the starting point of the lane network, and A target lane is set for the lane node where the vehicle moves. Note that when the starting point of the lane network is a road with multiple lanes on each side, the lane node corresponding to the lane in which the vehicle is currently located becomes the starting lane. On the other hand, when the end point of the lane network is a road with multiple lanes on each side, the lane node corresponding to the leftmost lane (in the case of left-hand traffic) becomes the target lane.

Thereafter, in S25, the CPU 51 refers to the lane network constructed in S23, searches for a route that continuously connects the starting lane to the target lane, and derives one route (hereinafter referred to as a reference route). For example, the route is searched from the target lane side using Dijkstra's algorithm. However, search means other than Dijkstra's method may be used as long as it is possible to search for a route that continuously connects the starting lane to the target lane. Note that the reference route derived in S25 does not necessarily have to be the optimal route, but may be any route that continuously connects the starting lane to the target lane.

Subsequently, in S26, the CPU 51 derives another route (hereinafter referred to as a candidate route) that continuously connects the starting lane to the target lane, based on the reference route specified in S25. For example, when a standard route is followed from the starting lane side and a lane change area or an intersection where a right or left turn is to be made is reached, a new route different from the standard route is generated by branching. As a result, one reference route and one or more candidate routes are generated as shown in Figure 10.

Thereafter, in S27, the CPU 51 calculates the total lane cost for each route, taking into account corrections based on conditions described below, for the reference route and candidate routes generated in S25 and S26. Note that if the route generated in S25 and S26 is a route that does not change lanes even once, the correction in the process of S27 may be omitted. Then, the total value of lane costs for each route is compared, and the route with the lowest total value of lane costs is specified as the recommended lane movement mode for the vehicle. Here, the lane cost is assigned to each lane link 76, and in S27, the total value of the lane costs of all lane links 76 included in each route is calculated and compared. Further, the lane cost given to each lane link 76 uses the length of each lane link 76 as a reference value. Then, the reference value is corrected under the following conditions (1) to (3). Note that lane links 76 within the same section (group) are basically considered to have the same length. Furthermore, the length of the lane link 76 within the intersection is assumed to be 0 or a fixed value.

(1) Lane cost is determined by multiplying the reference value by a lane change coefficient α corresponding to the number of lane changes required. Here, as shown in FIG. 11, the lane link 76 that requires more lane changes has a larger value. For example, since the lane link 76 moving from the lane 81 to the lane 82 requires one lane change, the reference value is multiplied by 1.2 as the lane change coefficient α. Furthermore, since the lane link 76 moving from the lane 81 to the lane 83 requires two consecutive lane changes, the reference value is multiplied by the larger 1.5 as the lane change coefficient α. On the other hand, the lane link 76 that maintains the lane 81 does not need to change lanes, so it is not multiplied by the lane change coefficient α. As a result, a route with a greater number of lane changes has a larger total lane cost calculated, and is therefore less likely to be selected as a recommended lane movement mode. Also, for routes that make multiple lane changes in the same section (that is, lane changes are made consecutively), the total lane cost will be higher than for routes that do not make consecutive lane changes, so it is recommended that This makes it difficult to select the lane movement mode.

(2) For the lane cost of a lane link that runs in the overtaking lane (for example, the rightmost lane when driving on the left) without changing lanes, a predetermined value is added to the reference value. For example, as shown in FIG. 12, "5" is added to the reference value for the lane link 76 traveling in lane 83, which is an overtaking lane. As a result, the longer the route requires traveling in the overtaking lane, the greater the total lane cost is calculated, making it less likely to be selected as the recommended lane movement mode.

(3) For the reference route and candidate routes that include sections (groups) in which lane changes are to be made, a plurality of patterns of candidates for lane change positions are generated, and the total lane cost is calculated for each of the plurality of patterns. Specifically, by referring to the lane change position for each pattern, (A) when the traveling distance in the overtaking lane before or after the lane change is longer than a threshold, (B) when changing lanes multiple times. Either the lane change interval is shorter than the threshold (that is, the lane changes are made continuously), or (C) the lane change is made within a predetermined distance before the intersection (for example, 700 m on the local road or 2 km on the expressway). For patterns corresponding to , a predetermined value is further added to the reference value for the lane cost of the lane link that changes lanes. For example, as shown in FIG. 13, for a pattern in which the vehicle moves from lane 81 to lane 82 from a predetermined distance before the intersection to the intersection, "5" is added to the reference value. Then, in S27, the total value of lane costs for each route (or each pattern for a route that includes multiple lane movement patterns) is compared, and the vehicle moves on the route and pattern that minimizes the total value of lane costs. By specifying the lane movement mode recommended for vehicles when changing lanes, not only the recommended section for changing lanes, but also the recommended position for changing lanes within the section can be specified. It happens. In addition, there are lane movement patterns in which lane changes occur continuously, lane movement patterns in which the vehicle travels a long distance in the overtaking lane before or after the lane change, and lane movement patterns in which the vehicle changes lanes from a predetermined distance before the intersection to the intersection. Since a lane movement pattern has a larger total lane cost than a pattern in which such a lane change is not performed, it is less likely to be selected as a recommended lane movement pattern.

Further, under the above condition (3), the same processing is performed especially when the reference route and the candidate route include a section (group) in which lane changes are made multiple times. For example, in FIG. 14, a reference route and a candidate route including a section (group) in which two lane changes are made from the leftmost lane will be described as an example. In the example shown in FIG. 14, the lane change positions include a first pattern in which the vehicle continues to drive in its current lane as much as possible and changes lanes twice near an intersection, and a pattern in which the vehicle changes lanes twice near an intersection. Possible candidates include a second pattern in which the vehicle changes lanes twice at equal intervals, and a third pattern in which the vehicle changes lanes at the earliest possible timing. Here, in the first pattern, lane changes are made successively at short intervals and lane changes are made near an intersection, so a high cost is calculated. Furthermore, in the third pattern, the traveling distance in the right overtaking lane is long, so a similarly high cost is calculated. On the other hand, in the second pattern, lane changes are not made at short intervals, lane changes are not made near intersections, and the travel distance in the right overtaking lane is relatively short, so the cost is calculated to be lower than in other patterns. be done. Therefore, in the example shown in FIG. 14, the second pattern has the lowest cost as a lane change position and is more likely to be selected as the recommended vehicle lane movement mode.

Next, in S28, the CPU 51 calculates a recommended travel trajectory, especially for a section (group) in which a lane change is to be made, when the vehicle moves along the route selected in S27. Incidentally, if the route selected in S27 is a route that does not change lanes even once, the process in S28 may be omitted.

Specifically, the CPU 51 calculates the travel trajectory using the map information of the lane change position specified in S27. For example, the lateral acceleration (lateral G) that occurs when a vehicle changes lanes is calculated from the vehicle speed (assumed to be the speed limit of the road) and the lane width, and the lateral acceleration (lateral G) that occurs when the vehicle changes lanes is calculated, and the lateral G that causes a problem with automatic driving assistance is calculated. The distance required for changing lanes is made as smooth as possible and as short as possible by using a clothoid curve, provided that it does not exceed the upper limit (for example, 0.2 G) that does not cause discomfort to the vehicle occupants. Calculate the trajectory. Note that the clothoid curve is a curve drawn by the locus of the vehicle when the vehicle is running at a constant speed and the steering wheel is turned at a constant angular velocity.

Next, in S29, the CPU 51 calculates a recommended travel trajectory, particularly for a section (group) within an intersection, when the vehicle moves in a lane according to the route selected in S27. Note that if the route selected in S27 is a route that does not pass through any intersections, the process in S29 may be omitted.

For example, in FIG. 15, a travel trajectory is calculated for a section (group) within an intersection in which a lane movement route is set, such as entering the intersection from the rightmost lane and then exiting to the leftmost lane. This will be explained using an example. First, the CPU 51 marks the position at which the vehicle should pass within the intersection. Specifically, markings are made for the entrance lane to the intersection, the approach position to the intersection, the guide line inside the intersection (only if there is a guide line), the exit position from the intersection, and the exit lane from the intersection. . Then, a curve that passes through all the marked marks is calculated as a traveling trajectory. More specifically, after connecting each mark with a spline curve, a clothoid curve that approximates the connected curves is calculated as the running trajectory. Note that the clothoid curve is a curve drawn by the locus of the vehicle when the vehicle is running at a constant speed and the steering wheel is turned at a constant angular velocity.

Thereafter, in S30, the CPU 51 generates a static travel trajectory, which is a travel trajectory recommended for the vehicle to travel on the roads included in the planned travel route, by connecting the respective travel trajectories calculated in S28 and S29. do. In addition, for a section that is neither a section where a lane change is to be made nor a section within an intersection, a trajectory that passes through the center of the lane is set as a travel trajectory on which the vehicle is recommended to travel.

Then, the static travel trajectory generated in S30 is stored in the flash memory 54 or the like as support information used for automatic driving support.

Next, the sub-processing of the dynamic traveling trajectory generation process executed in S6 will be explained based on FIG. 16. FIG. 16 is a flowchart of a sub-processing program of the dynamic traveling trajectory generation process.

First, in S41, the CPU 51 obtains the current position of the own vehicle detected by the current position detection section 31. Note that it is desirable to specify the current position of the vehicle in detail using, for example, high-precision GPS information or high-precision location technology. Here, high-precision location technology involves detecting white lines and road surface paint information captured from a camera installed in a vehicle through image recognition, and then comparing the detected white lines and road surface paint information with, for example, high-precision map information 15. This technology makes it possible to detect driving lanes and highly accurate vehicle positions. Furthermore, when the vehicle travels on a road consisting of a plurality of lanes, the lane in which the vehicle travels is also specified.

Next, in S42, the CPU 51 uses the static traveling trajectory generated in S3 (i.e., the trajectory on which the own vehicle is scheduled to travel) and the speed plan generated in S4 (i.e., the next trajectory of the own vehicle). (planned speed).

Next, in S43, the CPU 51 determines, based on the high-precision map information 15 acquired in S2, the factors that affect the running of the own vehicle (hereinafter referred to as influencing factors) detected in S5 in particular in the forward direction of the vehicle. Information on lane shapes, lane markings, etc. is acquired for the area around ``. The lane shape and marking line information acquired in S43 include information specifying the number of lanes and, if the number of lanes increases or decreases, where and how the number of lanes increases or decreases.

Subsequently, in S44, the CPU 51 acquires the current position of the influencing factor detected in S5, and if the influencing factor is moving, the movement status (moving direction, moving speed). Note that the position and movement status of the influencing factor are obtained, for example, by performing image processing on a captured image of a predetermined detection range around the vehicle using the camera 39 outside the vehicle.

Thereafter, in S45, the CPU 51 first predicts the future movement trajectory of the influencing factor based on the current position and movement status of the influencing factor acquired in S44. Note that when the influencing factor is another vehicle, the prediction may be made by considering the lighting status of the other vehicle's turn signals and brake lamps. Furthermore, if the future travel trajectory and speed plan of other vehicles can be obtained through vehicle-to-vehicle communication, predictions may be made taking these into consideration. Then, based on the predicted future movement trajectory of the influencing factor and the static traveling trajectory and speed plan of the own vehicle acquired in S42, it is determined more accurately whether the influencing factor will affect the running of the own vehicle. Judgment is made. Specifically, if the own vehicle and the influencing factor are located on the same lane at present or in the future, and the distance between them is predicted to be within the appropriate inter-vehicle distance D, the influencing factor will affect the driving of the own vehicle. It is determined that there is. Note that the appropriate inter-vehicle distance D is calculated using, for example, the following equation (1).
D = Vehicle speed of own vehicle x 2 sec + Braking distance of own vehicle - Braking distance of influencing factor (However, only when the influencing factor is a moving object)... (1)

If it is determined that the influencing factor has an influence on the running of the own vehicle (S45: YES), the process moves to S46. On the other hand, if it is determined that the influencing factor does not affect the running of the host vehicle (S45: NO), the process moves to S9 (S7 and S8 are omitted) without generating a dynamic running trajectory.

In S46, the CPU 51 determines whether it is possible to generate a new trajectory for the own vehicle to avoid the influencing factors and return to the static traveling trajectory (that is, to overtake). Specifically, if the influencing factor and the own vehicle are currently located in the same lane, the own vehicle changes lanes to the right, passes the influencing factor within a range that does not exceed the speed limit, and then changes lane to the left. If it is possible to draw a trajectory that maintains an appropriate inter-vehicle distance D or more based on the influencing factors, it is possible to draw a trajectory that allows the vehicle to avoid the influencing factors and return to the static traveling trajectory. It is determined that it is possible to generate a new trajectory. In addition, if the influencing factor and your vehicle are currently located in different lanes and then move to the same lane, your vehicle will overtake the influencing factor within the speed limit and then move to the same lane as the influencing factor. Regarding the trajectory before changing lanes, if it is possible to draw a trajectory that maintains an appropriate inter-vehicle distance D or more based on the influencing factors, a new trajectory will be created to allow the vehicle to avoid the influencing factors and return to the static traveling trajectory. It is determined that it is possible to generate a trajectory that The determination processing in S46 is performed based on the lane shape and marking line information in front of the vehicle in the traveling direction obtained in S43, the current position of the vehicle, the future movement trajectory of the influencing factors, and the speed limit of the road. be done.

If it is determined that it is possible to generate a new trajectory for the own vehicle to avoid the influencing factors and return to the static traveling trajectory (that is, to overtake) (S46: YES), the process moves to S47. do. On the other hand, if it is determined that it is not possible to generate a new trajectory for the own vehicle to avoid the influencing factors and return to the static running trajectory (that is, to overtake) (S46: NO), the process proceeds to S48. and transition.

In S47, the CPU 51 calculates a trajectory (hereinafter referred to as an avoidance trajectory) for the host vehicle to avoid the influencing factors and return to the static traveling trajectory (that is, to overtake). Specifically, if the own vehicle and the influencing factor are currently on the same lane, the own vehicle changes lanes to the right to overtake the influencing factor, then changes lane to the left, as shown in Figure 17. The trajectory until returning to the original lane corresponds to the avoidance trajectory. On the other hand, if the own vehicle and the influencing factor are currently on different lanes and it is necessary to move to the same lane later, the own vehicle passes the influencing factor and then changes lanes, as shown in Figure 18. The trajectory until the vehicle moves to the same lane as the influencing factor corresponds to the avoidance trajectory.

Here, FIG. 17 shows an example of an avoidance trajectory generated in S47 when the host vehicle 85 is traveling in the left lane on a road with two lanes on each side, and the influencing factor is the preceding vehicle 86 traveling in the same lane.
First, in the example shown in FIG. 17, the first trajectory L1 necessary for starting the steering wheel to move to the right lane and returning the steering wheel position to the straight direction is calculated. The first trajectory L1 calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current vehicle speed, and calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current speed. Using a clothoid curve, calculate a trajectory that is as smooth as possible and shortens the distance required to change lanes, provided that it does not exceed an upper limit that does not cause discomfort to the vehicle's occupants (e.g. 0.2G). . It is also a condition that an appropriate inter-vehicle distance D or more be maintained between the vehicle and the vehicle 86 in front.
Next, a second trajectory L2 is calculated in which the vehicle travels in the right lane at the speed limit, overtakes the vehicle 86 ahead, and maintains an appropriate inter-vehicle distance D or more between the vehicle 86 and the vehicle 86 ahead. The second trajectory L2 is basically a straight trajectory, and the length of the trajectory is calculated based on the vehicle speed of the preceding vehicle 86 and the speed limit of the road.
Next, a third trajectory L3 necessary for starting the steering wheel to return to the left lane and returning the steering wheel position to the straight direction is calculated. The third trajectory L3 calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current vehicle speed, and calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current speed. Using a clothoid curve, calculate a trajectory that is as smooth as possible and shortens the distance required to change lanes, provided that it does not exceed an upper limit that does not cause discomfort to the vehicle's occupants (e.g. 0.2G). . It is also a condition that an appropriate inter-vehicle distance D or more be maintained between the vehicle and the vehicle 86 in front.

Further, FIG. 18 shows that in a situation where the host vehicle 85 is traveling in the right lane on a road with two lanes on each side and needs to move to the left lane, the above S47 is performed when the influencing factor is the preceding vehicle 86 traveling in the left lane. An example of the generated avoidance trajectory is shown.
First, in the example shown in FIG. 18, the first trajectory L4 is to drive in the right lane at the speed limit, overtake the vehicle 86 ahead, and maintain an appropriate inter-vehicle distance D or more between the vehicle 86 and the vehicle ahead. Calculate. Note that the first trajectory L4 is basically a straight trajectory, and the length of the trajectory is calculated based on the vehicle speed of the preceding vehicle 86 and the speed limit of the road.
Next, a second trajectory L5 necessary for starting the steering wheel to move to the left lane and returning the steering wheel position to the straight-ahead direction is calculated. The second trajectory L5 calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the vehicle's current vehicle speed, and calculates the lateral acceleration (lateral G) that occurs when changing lanes based on the current vehicle speed. Using a clothoid curve, calculate a trajectory that is as smooth as possible and shortens the distance required to change lanes, provided that it does not exceed an upper limit that does not cause discomfort to the vehicle's occupants (e.g. 0.2G). . It is also a condition that an appropriate inter-vehicle distance D or more be maintained between the vehicle and the vehicle 86 in front.

Furthermore, in S47, the recommended speed of the host vehicle when traveling on the avoidance trajectory is also calculated. Regarding the recommended speed of the own vehicle, the upper limit is the speed limit, so that the lateral acceleration (lateral G) generated in the vehicle when changing lanes does not interfere with automatic driving assistance or cause discomfort to vehicle occupants. The recommended speed is a speed that does not exceed the upper limit (for example, 0.2G). For example, it is calculated based on the curvature of the avoidance trajectory, the speed limit, etc.

Thereafter, in S48, the CPU 51 calculates a trajectory (hereinafter referred to as a following trajectory) for the vehicle to follow (or run parallel to) the influencing factors. Specifically, if the own vehicle and the influencing factor are currently on the same lane, the own vehicle 85 continues traveling in the current lane without changing lanes, as shown in FIG. 19, and the influencing factor ( For example, a trajectory that follows the vehicle in front (86) corresponds to the following trajectory. Note that the follow-up trajectory is basically the same trajectory as the static running trajectory. However, since it is necessary to maintain an appropriate inter-vehicle distance between the vehicle and the influencing factor, the speed plan will be modified as described later (S8). On the other hand, if the host vehicle and the influencing factor are currently on different lanes and need to move to the same lane later, the host vehicle 85 can move to the current lane without changing lanes, as shown in FIG. A trajectory on which the vehicle continues to travel and runs parallel to an influencing factor (for example, the vehicle 86 in front) corresponds to a follow-up trajectory. In this case, the following trajectory is different from the static running trajectory.

Furthermore, in S48, the recommended speed of the own vehicle when traveling on the following trajectory is also calculated. Regarding the following speed of the host vehicle, the recommended speed is a speed that maintains an appropriate inter-vehicle distance D or more with respect to the inter-vehicle distance to the influencing factor in front, with the limit speed as the upper limit. Note that the appropriate inter-vehicle distance D is calculated based on the above-mentioned formula (1). However, as shown in Figure 20, when the subject vehicle and the influencing factor are located in different lanes, it is not necessarily necessary to maintain the inter-vehicle distance D or more, but the subject vehicle then needs to change lanes to the same lane as the influencing factor. Considering this, it is desirable to maintain the following distance D or more.

Thereafter, in S49, the CPU 51 adjusts the avoidance trajectory calculated in S47 (only when the avoidance trajectory has been calculated) and the follow-up trajectory calculated in S48 into the planned travel route, taking into account the surrounding road conditions. It is generated as a dynamic travel trajectory, which is a travel trajectory recommended for vehicles to travel on the included roads.

Then, the dynamic traveling trajectory generated in S49 is stored in the flash memory 54 or the like as support information used for automatic driving support.

Next, the sub-processing of the traveling trajectory reflection process executed in S7 will be explained based on FIG. 21. FIG. 21 is a flowchart of a sub-processing program of the traveling trajectory reflection process.

First, in S51, the CPU 51 reads the static traveling trajectory generated in S3 and the dynamic traveling trajectory generated in S6 from a storage medium such as the flash memory 54.

Subsequently, in S52, the CPU 51 calculates a path cost indicating the appropriateness of each travel trajectory as a vehicle travel trajectory for each travel trajectory read in S51. Here, the path cost is calculated taking into account at least one of (a) travel time (average vehicle speed), (b) number of lane changes, (c) location at which the lane change is made, and (d) travel lane. Specifically, it is calculated based on the following conditions.

(a) Regarding "travel time (average vehicle speed)", the longer the travel time (that is, the slower the average vehicle speed) on the travel trajectory, the higher the path cost is calculated. Note that the average vehicle speed on the static travel trajectory is specified based on the speed plan generated in S4. On the other hand, the dynamic traveling trajectory is specified based on the recommended speed calculated in S47 and S48.
(b) Regarding the "number of lane changes," the path cost is calculated to be higher for a travel trajectory with a greater number of lane changes.
(c) Regarding the "lane change position," when lane changes are made multiple times, the path cost is calculated to be higher as the travel trajectory becomes shorter at lane change intervals. In addition, a path cost is added for a travel trajectory in which a lane change is made within a predetermined distance on the near side of an intersection (for example, 700 m on a general road or 2 km on an expressway).
(d) Regarding the "driving lane", the longer the traveling distance in the overtaking lane is, the higher the path cost is calculated.

However, regardless of the conditions (a) to (d) above, the cost is set to be infinite for the traveling trajectory where it is determined that the host vehicle will come into contact with the influencing factor detected in S5.

Thereafter, in S53, the CPU 51 compares the path costs for each travel trajectory calculated in S52, and selects the travel trajectory with the smallest path cost value as the travel trajectory on which the vehicle is recommended to travel.

Next, in S54, the CPU 51 determines whether an avoidance trajectory or a follow-up trajectory, which is a dynamic traveling trajectory, was selected in S53.

If it is determined in S53 that the avoidance trajectory or follow-up trajectory, which is the dynamic traveling trajectory, is selected (S54: YES), the process proceeds to S55.

In S55, the CPU 51 replaces the static traveling trajectory with the dynamic traveling trajectory, targeting the section in which the selected dynamic traveling trajectory has been generated. Basically, when a static running trajectory is replaced with a dynamic running trajectory, the start and end points of the dynamic trajectory will be connected to the static running trajectory, but as an exception, the tracking shown in Figure 20 When a trajectory is selected, the end point of the dynamic trajectory may not connect to the static trajectory. In such a case, a new static travel trajectory may be generated using the end point of the dynamic travel trajectory as the starting point, or the generation of a dynamic travel trajectory may be repeated at regular intervals until it connects to the static travel trajectory. You can do it like this.

After that, support driving by automatic driving assistance is performed based on the static travel trajectory partially replaced with the dynamic travel trajectory (S9, S10)

On the other hand, if it is determined in S53 that the static traveling trajectory has been selected (S54: NO), the process proceeds to S8 without replacing with the dynamic traveling trajectory.

As described above in detail, the navigation device 1 according to the present embodiment and the computer program executed by the navigation device 1 acquire the planned travel route for the vehicle (S1), and acquire the high-precision map information 15 including the lane shape. A lane network is constructed, which is a network indicating lane movements that the vehicle can select for the planned travel route, using (S23), and a starting lane in which the vehicle starts moving is set for the constructed lane network. Each target lane is set as a target for the vehicle to move (S24), and a route connecting the starting lane and the target lane is searched for using the cost added to the lane network, and the vehicle follows the searched route. Since the recommended lane movement mode for the vehicle is specified when moving (S27), when providing driving support for the vehicle, the most recommended lane movement mode can be appropriately determined by using the cost added to the lane network. It becomes possible to specify. Then, by performing driving support based on the specified lane movement mode, it is possible to appropriately implement driving support.

It should be noted that the present invention is not limited to the embodiments described above, and it goes without saying that various improvements and modifications can be made without departing from the gist of the present invention.
For example, in this embodiment, when an influencing factor that affects the running of the vehicle is detected, an avoidance trajectory and a follow-up trajectory are respectively generated as dynamic running trajectories, but only one of them is generated. Also good.

In addition, in this embodiment, when searching for a recommended lane movement mode using a lane network, first a reference route connecting a starting lane to a target lane is searched, and then one or more routes are searched based on the reference route. The process generates candidate routes, compares the costs of each route, and identifies the route with the minimum cost (S25 to S27). You may search and identify the route.

In addition, in this embodiment, the high-precision map information held by the server device 4 includes road lane shapes (road shape, curvature, lane width, etc. for each lane) and division lines drawn on roads (roadway center line, lane width, etc.). Although the information includes both information related to boundary lines, road outside lines, guide lines, etc., it may also include only information related to partition lines, or only information related to road lane shapes. For example, even in the case where only information about the lane markings is included, it is possible to estimate information equivalent to information about the lane shape of the road based on the information about the lane markings. Further, even when only information regarding the lane shape of the road is included, it is possible to estimate information equivalent to information regarding the lane markings based on the information regarding the lane shape of the road. Furthermore, "information regarding lane markings" may be information that specifies the type and arrangement of the lane markings that separate lanes, or information that specifies whether or not it is possible to change lanes between adjacent lanes. It may also be information that directly or indirectly specifies the shape of the lane.

In addition, in this embodiment, a dynamic traveling trajectory is generated when an influencing factor that affects the running of the vehicle is detected, and the path costs of the existing static traveling trajectory and the newly generated dynamic traveling trajectory are (S52, S53), and only when it is determined that the dynamic traveling trajectory is recommended, the static traveling trajectory is replaced with the dynamic traveling trajectory (S55). If a static traveling trajectory is generated, the static traveling trajectory may be always replaced with a dynamic traveling trajectory.

In addition, in this embodiment, as a means for reflecting the dynamic traveling trajectory on the static traveling trajectory, a part of the static traveling trajectory is replaced with the dynamic traveling trajectory (S55), but instead of replacing it, the static traveling trajectory is replaced with the dynamic traveling trajectory. The trajectory may be modified so that it approaches the dynamic traveling trajectory.

Furthermore, in this embodiment, the vehicle control ECU 40 automatically controls all of the operations related to vehicle behavior, such as accelerator operation, brake operation, and steering wheel operation, among vehicle operations, without depending on the user's driving operation. It has been explained as an automatic driving support for driving. However, the automatic driving support may be performed by the vehicle control ECU 40 controlling at least one of the accelerator operation, brake operation, and steering wheel operation, which are operations related to the behavior of the vehicle. On the other hand, manual driving by the user's driving operations will be described as the user performing all of the operations related to the behavior of the vehicle, such as accelerator operation, brake operation, and steering wheel operation.

Further, the driving support of the present invention is not limited to automatic driving support related to automatic driving of a vehicle. For example, in addition to displaying the recommended lane movement mode, static travel trajectory, and dynamic travel trajectory identified in S27 above on the navigation screen, guidance using audio, screen, etc. (for example, lane change guidance, recommended vehicle speed It is also possible to provide driving support by providing guidance (guidance, etc.). Further, the user's driving operation may be supported by displaying recommended lane movement modes, static travel trajectories, and dynamic travel trajectories on the navigation screen.

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

In addition to navigation devices, the present invention can also be applied to mobile phones, smartphones, tablet terminals, personal computers, etc. (hereinafter referred to as mobile terminals, etc.). Furthermore, it is also possible to apply the present invention to a system composed of a server, a mobile terminal, etc. In that case, each step of the automatic driving support program (see FIG. 4) described above may be implemented by either the server or the mobile terminal. However, when the present invention is applied to a mobile terminal or the like, it is necessary that a vehicle capable of performing automatic driving assistance and the mobile terminal or the like are communicably connected (wired or wireless does not matter).

Moreover, although the embodiment embodying the driving support device according to the present invention has been described above, the driving support device can also have the following configuration, and in that case, the following effects are achieved.

For example, the first configuration is as follows.
Using a planned driving route acquisition means (51) that acquires a planned driving route for the vehicle (5) and map information (15) including lane shapes, lane movement that the vehicle can select for the planned driving route is performed. a lane network construction means (51) for constructing a lane network that is a network showing the lane network; a start lane setting means (51) for setting a starting lane in which a vehicle starts moving with respect to the lane network; a target lane setting means (51) for setting a target lane as a target for a vehicle to move; and a cost added to the lane network for a route candidate connecting the starting lane and the target lane in the lane network. and a movement mode specifying means (51) for specifying a lane movement mode recommended for the vehicle when the vehicle moves, by comparing the lane movement mode using the lane network. In addition to dividing the location, the exit position of an intersection, and the location where the number of lanes increases or decreases as boundaries, nodes are set for each lane located at the boundaries of each divided section, and links are provided to connect the set nodes. In a network that includes multiple lanes, the links that connect the front and rear nodes of each section include links that connect nodes set along the same lane, as well as links that connect nodes that are set along the same lane. Contains links that connect nodes set to .
According to the driving support device having the above configuration, when providing driving support for a vehicle, it is possible to appropriately specify the most recommended lane movement mode by using the cost added to the lane network. Then, by performing driving support based on the specified lane movement mode, it is possible to appropriately implement driving support.

Furthermore , according to the driving support device having the above configuration, a lane network is constructed that takes into consideration the increase/decrease of lanes, lane traffic classification, etc., and shows lane movements that can be selected when the vehicle travels on the planned travel route. It becomes possible to do so.

Further, the second configuration is as follows.
The movement mode specifying means (51) searches for a plurality of route candidates connecting the starting lane and the target lane in the lane network, calculates a total cost value for each of the plurality of routes, and selects a total cost value for each of the plurality of routes. A route with a smaller value is identified as the recommended vehicle lane movement mode when the vehicle moves.
According to the driving support device having the above configuration, by using the cost added to the lane network, it is possible to appropriately identify the most recommended lane movement mode from among multiple lane movement mode candidates. . Furthermore, since the costs are compared after first searching for candidate routes, the processing load associated with searching for routes can be reduced.

Moreover, the third configuration is as follows.
The movement mode specifying means (51) calculates a higher cost for a route with a greater number of lane changes.
According to the driving support device having the above configuration, it is possible to specify a route that requires fewer lane changes and is easier to travel as a recommended lane movement mode for the vehicle.

Further, the fourth configuration is as follows.
The movement mode specifying means (51) calculates a higher cost for a route in which lane changes are made consecutively than a route in which lane changes are not made consecutively.
According to the driving support device having the above configuration, it is possible to specify a route that is easy to drive without continuously changing lanes as a recommended lane movement mode for the vehicle when moving. .

Further, the fifth configuration is as follows.
The movement mode specifying means (51) calculates a higher cost for a route that requires a longer distance to travel in an overtaking lane.
According to the driving support device having the above configuration, it is possible to specify a route with a short distance of moving in an overtaking lane as much as possible as a recommended lane movement mode of the vehicle when the vehicle moves.

Further, the sixth configuration is as follows.
The movement mode specifying means (51) determines that a route in which a lane change is made between a predetermined distance before an intersection and the intersection is higher in cost than a route in which a lane change is not made between a predetermined distance before the intersection and the intersection. calculate.
According to the driving support device having the above configuration, it is possible to specify a route that is easy to drive without changing lanes immediately before an intersection as a recommended lane movement mode for the vehicle when moving. Become.

Moreover, the seventh configuration is as follows.
The lane network includes information indicating the correspondence between lanes included in the road before passing through the intersection and lanes included in the road after passing through the intersection.
According to the driving support device having the above configuration, selection is made when a vehicle passes through an intersection, taking into account the correspondence between the lane included in the road before passing through the intersection and the lane included in the road after passing through the intersection. It becomes possible to construct a lane network showing possible lanes.

Further, the eighth configuration is as follows.
The movement mode specifying means (51) searches for a route connecting the starting lane and the target lane from the target lane side.
According to the driving support device having the above configuration, it is possible to appropriately specify the most recommended lane movement mode for moving the vehicle to the target lane.

Further, the ninth configuration is as follows.
Automated vehicle driving assistance is performed in accordance with the lane movement mode specified by the movement mode specifying means (51).
According to the driving support device having the above configuration, when the vehicle is driven by automatic driving support, it is possible to appropriately identify the most recommended lane movement mode by using the cost added to the lane network. Become. Then, by performing automatic driving support based on the specified lane movement mode, it is possible to appropriately implement automatic driving support.

1 Navigation device 2 Driving support system 3 Information distribution center 4 Server device 5 Vehicle 15 High-precision map information 33 Navigation ECU
39 External camera 40 Vehicle control ECU
51 CPU
52 RAM
53 ROM
54 Flash memory 61 Scheduled travel route 75 Lane node 76 Lane link

Claims (10)

a scheduled driving route acquisition means for acquiring a scheduled driving route on which the vehicle will travel;
lane network construction means for constructing a lane network that is a network indicating possible lane movements for the vehicle with respect to the scheduled travel route using map information including lane shapes;
a starting lane setting means for setting a starting lane in which a vehicle starts moving in the lane network;
target lane setting means for setting a target lane in which a vehicle moves with respect to the lane network;
By comparing route candidates connecting the starting lane and the target lane in the lane network using the cost added to the lane network, a recommended lane movement mode of the vehicle is identified when the vehicle moves. a means for specifying a movement mode ;
The lane network is
The planned travel route is divided into intersection entry positions, intersection exit positions, and positions where lanes increase or decrease, respectively, and nodes are set for each lane located at the boundary of each divided section. A network with links connecting nodes,
Within each of the above-mentioned divided sections, links that connect the nodes before and after the sections that include multiple lanes include links that connect nodes that are set along the same lane, as well as links that connect nodes that are set along different lanes. A driving support device that includes links that connect . The movement mode specifying means includes:
searching for a plurality of route candidates connecting the starting lane and the target lane in the lane network;
Calculate the total cost for each route,
The driving support device according to claim 1 , wherein the route with the smallest total cost is specified as the lane movement mode recommended for the vehicle when the vehicle moves. 3. The driving support device according to claim 1, wherein the movement mode specifying means calculates a higher cost for a route with a greater number of lane changes. The driving support according to any one of claims 1 to 3 , wherein the movement mode specifying means calculates a higher cost for a route in which lane changes are made consecutively than a route in which lane changes are not made consecutively. Device. The driving support device according to any one of claims 1 to 4 , wherein the movement mode specifying means calculates a higher cost for a route that requires a longer distance to travel in an overtaking lane. The movement mode specifying means calculates a higher cost for a route in which a lane change is made between a predetermined distance before an intersection and the intersection, than a route in which a lane change is not made between a predetermined distance before the intersection and the intersection. The driving support device according to any one of claims 1 to 5 . The driving support according to any one of claims 1 to 6 , wherein the lane network includes information indicating a correspondence relationship between lanes included in the road before passing through the intersection and lanes included in the road after passing through the intersection. Device. 8. The driving support device according to claim 1, wherein the movement mode specifying means searches for a route connecting the starting lane and the target lane from the target lane side. The driving support device according to any one of claims 1 to 8 , wherein automatic driving support for a vehicle is provided in accordance with the lane movement mode specified by the movement mode specifying means. computer,
a scheduled driving route acquisition means for acquiring a scheduled driving route on which the vehicle will travel;
lane network construction means for constructing a lane network that is a network indicating possible lane movements for the vehicle with respect to the scheduled travel route using map information including lane shapes;
a starting lane setting means for setting a starting lane in which a vehicle starts moving in the lane network;
target lane setting means for setting a target lane in which a vehicle moves with respect to the lane network;
By comparing route candidates connecting the starting lane and the target lane in the lane network using the cost added to the lane network, a recommended lane movement mode of the vehicle is identified when the vehicle moves. a movement mode identifying means for
A computer program for functioning as
The lane network is
The planned travel route is divided into intersection entry positions, intersection exit positions, and positions where the number of lanes increases or decreases as boundaries, and a node is set for each lane located at the boundary of each divided section. A network with links connecting nodes connected to each other,
Within each of the above-mentioned sections, the links connecting the front and rear nodes in a section including multiple lanes include links connecting nodes set along the same lane, as well as links connecting nodes set along different lanes. A computer program that contains links that connect .