Map data generation method

Abstract

To provide a map data generation method capable of generating map data including detailed information.SOLUTION: A histogram is created for positions of a plurality of vehicles 2 in the width direction of a road, and normal traveling zone information and transient traveling zone information are generated based on a position where the maximum value is obtained and a variance σ which is dispersion. This allows the map data to include more detailed information than lane width information indicating whether or not the vehicle can travel.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present invention relates to a method for generating map data.

Background Art

[0002] Conventionally, for the purpose of providing a lot of information to passengers, an information processing apparatus has been proposed that includes a lane detection means for detecting a lane in which a vehicle is traveling and an adjacent lane, and an information presentation means capable of presenting information to a passenger of the vehicle (see, for example, Patent Document 1). In the information processing apparatus described in Patent Document 1, by presenting information indicating the positional relationship between the traveling lane and the adjacent lane to the passenger, the passenger can know that the lane detection is appropriately performed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, simply detecting lanes as described in Patent Document 1 may be insufficient as information for performing driving support or the like. For example, when detecting a lane and other moving objects, even if another moving object is traveling while wobbling within an adjacent lane, if it does not protrude from the lane, there is a possibility that this moving object will be judged to be normal. In addition, there are problems in supporting driving in accordance with the actual road conditions with only information such as width and the number of lanes.

[0005] Therefore, an example of the problem of the present invention is to provide a map data generation method capable of generating map data including detailed information.

Means for Solving the Problems

[0006] In order to solve the above-described problems and achieve the object, the map data generation method of the present invention according to claim 1 includes a calculation step of calculating the position of a moving object in the road width direction included in the peripheral information with respect to the road information by comparing the peripheral information measured by a measurement unit mounted on a measurement moving object and the road information stored in advance, an information generation step of generating at least one of first information indicating a range where the distribution density is equal to or greater than a predetermined value and second information indicating an outer range of the range of the first information based on the distribution of the positions of a plurality of moving objects in the road width direction with respect to the road information, and a map data generation step of generating map data including at least one of the first information and the second information.

Brief Description of the Drawings

[0007]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Modes for Carrying Out the Invention

[0008] Hereinafter, embodiments of the present invention will be described. The map data generation method according to the embodiments of the present invention includes a calculation step of calculating the position of a moving object in the road width direction included in the surrounding information with respect to the road information by comparing the surrounding information measured by a measurement unit mounted on a measurement moving object and the road information stored in advance, an information generation step of generating at least one of first information indicating a range where the distribution density is equal to or greater than a predetermined value and second information indicating an outer range of the range of the first information based on the distribution of the positions of a plurality of moving objects in the road width direction with respect to the road information, and a map data generation step of generating map data including at least one of the first information and the second information.

[0009] Since the first information and the second information are generated based on the distribution of the positions of a plurality of moving objects in the road width direction, the road width direction position corresponding to the first information has a high running frequency of the moving object, and the road width direction position corresponding to the second information has a low running frequency of the moving object. That is, it is possible to include in the map data information that is more detailed than the lane width information indicating simply whether a moving object can run or not.

[0010] By including the first information and the second information in the map data, the map data can be used as exemplified below. First, ordinary width information may include sidewalks and median strips, and the actually drivable area is unclear. On the other hand, by generating the first information and the second information based on the distribution of the positions of a plurality of moving objects in the road width direction, the actually drivable area can be grasped, and the moving object can be guided to the actually drivable area. In particular, in the case of autonomous driving, the moving object can be appropriately guided. Also, in manual driving, driving is performed according to road conditions and the like, and it is not always the case that the vehicle runs in the center of the width direction of each lane. Therefore, by using the first information and the second information based on the distribution of the positions of a plurality of moving objects in the road width direction for guidance, it is easy to realize driving in accordance with the actual road conditions even in autonomous driving. Further, it is possible to predict the behavior of other moving objects or moving objects based on the first information and the second information, and perform driving support based on the prediction results. Also, it is possible to analyze the driver's intention and driving behavior based on the first information and the second information.

[0011] Furthermore, such a map data generation method may be implemented, for example, by an external server that acquires information from a moving object. At this time, not all steps need to be implemented by the external server, and some or all steps may be implemented by a control unit mounted on the moving object. Also, when a plurality of moving objects are included in the surrounding information, the position in the road width direction may be calculated for each of the plurality of moving objects. Also, while a plurality of measurement moving objects are traveling and the external server collects information from these moving objects, the external server may also collect information from one moving object.

[0012] In the information generation step, it is preferable to generate a histogram for the positions of a plurality of moving objects in the road width direction, and generate at least one of the first information and the second information based on the position where the maximum value is obtained and the degree of variation. Thereby, information corresponding to the actual driving situation at each position of the road can be generated. That is, when the variation in the driving position of the moving object in the road width direction is small, the range corresponding to the first information becomes narrow, and when the variation is large, the range corresponding to the first information becomes wide.

[0013] The evaluation method according to an embodiment of the present invention generates map data including the second information by the above-described map data generation method, and evaluates the driving state of the driver of this moving object based on the behavior of the moving object at the road width direction position corresponding to the second information.

[0014] At the road width direction position corresponding to the second information, if the moving object suddenly brakes or suddenly changes the traveling direction (azimuth), for example, there is a possibility of attempting a lane change and failing. If the frequency of such behavior is high, it can be determined that the skill of the driver driving this moving object is low. Also, based on the behavior of the moving object at the road width direction position corresponding to the second information, it is possible to determine aggressive driving or random driving and evaluate the degree of safe driving. By evaluating the driving skill and the degree of safe driving, it can be used, for example, as a basis for determining insurance premiums for automobile insurance.

[0015] The driving support method according to an embodiment of the present invention generates map data including second information by the above-described map data generation method, predicts the subsequent behavior of another moving object based on the behavior of the other moving object at the road width direction position corresponding to the second information, and provides driving support to the moving object based on the predicted information.

[0016] Based on the behavior of another moving object at the road width direction position corresponding to the second information, for example, it is possible to determine that the other moving object is about to change lanes. That is, even before the other moving object gives an indication using a direction indicator, the other moving object may travel at the road width direction position corresponding to the second information, and based on this behavior, it is possible to determine that there is an intention to change lanes. Incidentally, when it is determined that the other moving object has an intention to change lanes, driving support may be provided by transmitting this fact to the driver of the moving object, or it may be reflected in the control of autonomous driving.

[0017] The driving support method according to an embodiment of the present invention generates map data including second information by the above-described map data generation method, and when the predicted collision degree with another moving object becomes equal to or greater than a predetermined value, guides the moving object to travel at the road width direction position corresponding to the second information.

[0018] The road width direction position corresponding to the second information is a position where travel is possible although the travel frequency of the moving object is low. Therefore, for example, when the predicted collision degree becomes equal to or greater than a predetermined value because an oncoming other moving object runs out of the lane, the moving object can be guided to travel at the road width direction position corresponding to the second information, thereby avoiding a collision with the other moving object. Incidentally, when the predicted collision degree becomes equal to or greater than a predetermined value, driving support may be provided by indicating the position to be traveled to the driver of the moving object, or it may be reflected in the control of autonomous driving.

[0019] The driving support method according to an embodiment of the present invention generates map data including first information and second information by the above-described map data generation method, detects a moving object located outside the road width direction range corresponding to the second information, and guides the moving body to travel at a road width direction position corresponding to the first information according to the detection situation of the moving object.

[0020] When the pedestrian traffic volume is large or the sidewalk width is narrow on the sidewalk, pedestrians may walk out of the sidewalk. On roads where such situations frequently occur, the road width direction position corresponding to the first information may be biased to the side opposite to the sidewalk with respect to the center in the width direction of the lane. On the other hand, when pedestrians do not protrude from the sidewalk, drivers often drive so that the moving body travels in the center of the lane width direction, and in the case of automatic driving, it may also be controlled to travel in the center of the width direction. In this way, when the moving body travels in the center of the lane width direction and a moving object (such as a pedestrian) located outside the road width direction range corresponding to the second information is detected, by guiding the moving body to travel at the road width direction position corresponding to the first information, even when the moving object enters the lane, it is easy to suppress a collision.

[0021] Also, it may be a map data generation program that causes a computer to execute the above-described map data generation method. By doing so, map data including detailed information can be generated using a computer.

[0022] Also, the above-described map data generation program may be stored in a computer-readable recording medium. By doing so, the program can be distributed not only when incorporated into a device but also alone, and version updates and the like can be easily performed.

Example

[0023] Hereinafter, embodiments of the present invention will be specifically described.

[0024] <First Embodiment> In this embodiment, map data is generated by a map data generation system 1 as shown in FIG. 1, and an evaluation system 10 as shown in FIG. 4 is used to evaluate the driving state of a driver using the map data.

[0025] [Map Data Generation System] The map data generation system 1 includes a plurality of vehicles (moving bodies) 2 and an external server (information processing device) 3. Note that the vehicle 2 may be a general vehicle or a measurement vehicle for the purpose of generating map data.

[0026] An information acquisition unit 20 is mounted on the vehicle 2, and the information acquisition unit 20 includes a position measurement unit 21, a measurement unit 22, a communication unit 23, a storage unit 24, and a vehicle-side control unit 25.

[0027] The position measurement unit 21 measures the current position (absolute position) of the vehicle 2, and for example, may be a GPS receiver that receives radio waves transmitted from a plurality of GPS (Global Positioning System) satellites. The position measurement unit 21 may acquire latitude and longitude information as the current position of the vehicle 2.

[0028] The measurement unit 22 is capable of measuring surrounding information, and for example, may be an optical sensor (so-called LIDAR; Light Detection and Ranging or Laser Imaging Detection and Ranging) that projects light and receives reflected light from an irradiation target. At this time, the surrounding information may be point cloud data obtained by the optical sensor. Note that a video camera or the like may be used as the measurement unit 22, and the surrounding information may be measured by (VSLAM; Visual Simultaneous Localization and Mapping).

[0029] The communication unit 23 is composed of circuits, antennas, etc. for communicating with networks such as the Internet and public lines, and communicates with the external server 3 to transmit and receive information. Note that the communication unit 23 may only transmit information to the external server 3. Alternatively, a detachable storage medium may be provided instead of the communication unit 23, and the operator can transfer data to the external server 3 by removing this storage medium.

[0030] The storage unit 24 is composed of, for example, a hard disk or a non-volatile memory, and stores self-position estimation information. That is, when the current position is measured by the position measurement unit 21, map matching can be performed using the self-position estimation information.

[0031] The vehicle-side control unit 25 is composed of, for example, a CPU (Central Processing Unit) equipped with memories such as a RAM (Random Access Memory) and a ROM (Read Only Memory), and is in charge of the overall control of the information acquisition unit 20.

[0032] The external server 3 includes a storage unit main body 31, a communication unit 32, and a server-side control unit 33. It is physically separated from the vehicle 2 and can communicate with the vehicle 2 via a network such as the Internet, and is configured to collect, process, and store information from the vehicle 2. Note that the part for storing information and the part for processing in the external server 3 may be physically separated.

[0033] The storage unit main body 31 is composed of, for example, a hard disk or a non-volatile memory, stores road information, and is read and written under the control of the server-side control unit 33. The road information includes matching information corresponding to point cloud data and road configuration information including the configuration information of the road in the width direction and the width information of each part.

[0034] The information for matching may include, for example, information on ground features and white lines. That is, by comparing the point cloud corresponding to the ground features and white lines among the point cloud data obtained by the optical sensor with the information for matching, it is possible to determine that the point cloud that does not overlap with the information for matching and is located on the lane corresponds to another vehicle (moving object).

[0035] An example of the road configuration information is shown in Table 1.

[0036]

Table 1

[0037] The road configuration information shown in Table 1 includes, for each road link ID, the start and end nodes, the lane link ID, and the width of the lane in each lane link. The number of lane link IDs corresponds to the number of lanes on the road.

[0038] The communication unit 32 is composed of circuits, antennas, etc. for communicating with networks such as the Internet and public lines, and communicates with the vehicle 2 to transmit and receive information.

[0039] The server-side control unit 33 is composed of a CPU (Central Processing Unit) equipped with a memory such as a RAM (Random Access Memory) and a ROM (Read Only Memory), controls the overall operation of the external server 3, processes the information acquired from the vehicle 2 as will be described later, and stores the processed information in the storage unit main body 31.

[0040] An example of a specific method for generating map data in the map data generation system 1 as described above will be described.

[0041] First, while the vehicle 2 is running, measurements are carried out by the measurement unit 22 to obtain surrounding information. The obtained surrounding information is combined with the current position information of the vehicle 2 at the time of measurement and transmitted to the external server 3 via the communication unit 23. By repeating the above, the external server 3 collects a plurality of pieces of surrounding information. Further, the external server 3 collects surrounding information from a plurality of vehicles 2.

[0042] For each of the collected pieces of surrounding information, the server-side control unit 33 extracts a point cloud corresponding to another vehicle and calculates the width-direction position of the other vehicle with respect to the reference position (calculation step). That is, the information at the position corresponding to the current position information among the information for matching is used and compared with the surrounding information which is point cloud data. Thereby, from the point cloud data, a point cloud corresponding to another vehicle and a point cloud serving as a reference position can be extracted. As the reference position, the position of a specific white line (for example, the white line closest to the sidewalk side) or the median strip etc. may be used. Based on the point cloud corresponding to the other vehicle and the point cloud serving as the reference position, the width-direction position of the other vehicle on the road can be calculated.

[0043] The width-direction position of the other vehicle is the range where the other vehicle exists. For example, in a lane with a width of 3 m, when the distance from the white line serving as the reference position (origin) to one end in the width direction of the other vehicle is 0.5 m and the distance to the other end in the width direction is 2.3 m (that is, when the width-direction dimension of the other vehicle is 1.8 m), the range from 0.5 to 2.3 m from the origin is the width-direction position of the other vehicle on the road.

[0044] When a plurality of point clouds of other vehicles are included in one piece of surrounding information, the width-direction position is calculated for each of the other vehicles.

[0045] For each road link, the server-side control unit 33 generates a histogram for the width-direction position of the other vehicle from the reference position, and generates normal driving lane information as the first information and transient driving lane information as the second information based on the position where the maximum value is obtained and the degree of variation (information generation step). The histogram is, for example, as shown in FIG. 2, with the horizontal axis divided into appropriate units as the width-direction position (m) from the origin, and the vertical axis as the distribution number (pieces).

[0046] For example, a lane with a width of 3 m is partitioned every 10 cm, and areas from the first to the thirtieth are defined starting from the origin. When the position of other vehicles in the road width direction is in the range of 0.5 to 2.3 m from the origin as described above, the distribution number is counted as 1 in each of the sixth to twenty-third areas.

[0047] When generating a histogram in this way, the distribution number becomes maximum near the center in the width direction of the lane. Also, as the variation in the position in the road width direction, the standard deviation σ can be calculated. With the position in the road width direction where the distribution number becomes the maximum value as the center, the range of ±2σ is defined as the normal driving band, and the range outside that and within the lane is defined as the transitional driving band. When there are multiple lanes, information on the normal driving band and the transitional driving band is generated for each lane. At this time, histograms may be generated independently for multiple lanes, or may be generated collectively.

[0048] In the example shown in FIG. 2, the range from 0.3 to 2.1 m from the origin becomes the normal driving band, and the ranges up to 0.3 m from the origin and from 2.1 to 3 m become the transitional driving bands. In this way, the range where the distribution density of the position of other vehicles in the road width direction is high becomes the normal driving band, and the range where the distribution density is low becomes the transitional driving band. A threshold value may be set for the distribution density, and the range where the distribution density is equal to or higher than the threshold value may be defined as the normal driving band. At this time, the threshold value of the distribution density may be set according to, for example, the width, and may be different for each road link.

[0049] In the method described above, when generating the histogram, the range where other vehicles exist is used as the position of other vehicles in the road width direction, but the center position of other vehicles in the road width direction may also be used. A histogram is generated using the center position, the range of the center position is calculated based on the position where the maximum value is obtained and the variation, and the normal driving band may be determined by appropriately adding the vehicle width to this range.

[0050] The server-side control unit 33 generates map data including normal driving lane information and transient driving lane information (map data generation step). First, by adding the normal driving lane information and the transient driving lane information to the road configuration information as shown in Table 1, detailed road configuration information as shown in Table 2 is generated.

[0051]

Table 2

[0052] The detailed road configuration information as shown in Table 2 includes not only the width of the lane but also information about the positions of the normal driving lane and the transient driving lane within the lane. As a result, the normal driving lane and the transient driving lane as shown in Figure 3 are defined. Incidentally, when executing various processes using the normal driving lane information and the transient driving lane information as described later, the width of the normal driving lane may be increased or decreased according to the vehicle class (vehicle width) of the target vehicle. That is, in the case of a large vehicle, it is likely to protrude from the normal driving lane even when driving normally, so the normal driving lane may be corrected to be wider. In addition, in Table 2 above, an example in the case where the number of lanes is 1 is shown, but when the number of lanes is plural, detailed road configuration information is generated for each lane.

[0053] The server-side control unit 33 generates map data including the detailed road configuration information and stores it in the main body 31 of the storage unit. Incidentally, the map data may include information about features around the road in addition to the detailed road configuration information.

[0054] [Evaluation System] As shown in Figure 4, the evaluation system 10 includes an evaluation target vehicle (moving body) 4 and an external server (information processing device) 3.

[0055] An information acquisition unit 40 is mounted on the evaluation target vehicle 4, and the information acquisition unit 40 includes a position measurement unit 41, a measurement unit 42, a communication unit 43, a storage unit 44, a vehicle-side control unit 45, and a behavior measurement unit 46. Each of the units 41 to 45 of the information acquisition unit 40 has the same configuration as each of the units 21 to 25 of the information acquisition unit 20 of the vehicle 2.

[0056] The behavior measurement unit 46 is for measuring the displacement amount as the behavior of the vehicle 4 to be evaluated. For example, it is composed of a vehicle speed pulse acquisition unit that acquires the vehicle speed pulse of the vehicle 4 to be evaluated, a gyro sensor for measuring the azimuth displacement amount of the vehicle 4 to be evaluated, and an acceleration sensor for acquiring the acceleration of the vehicle 4 to be evaluated. The behavior measurement unit 46 obtains the behavior information of the vehicle 4 to be evaluated.

[0057] When the vehicle 4 to be evaluated is running, the vehicle side control unit 45 combines the surrounding information and the behavior information with the current position information of the vehicle 4 to be evaluated at the time of measurement, and transmits it to the external server 3 by the communication unit 43.

[0058] In this embodiment, it is assumed that the external server 3 for generating map data and the external server 3 for evaluation are the same, but different external servers may be used.

[0059] An example of a specific method for evaluating the driving state of the driver of the vehicle 4 to be evaluated in the evaluation system 10 as described above will be described.

[0060] Based on the surrounding information measured by the measurement unit 42 and the matching information stored in the storage unit main body 31, the server side control unit 33 calculates the position of the vehicle 4 to be evaluated in the road width direction of each road link. Based on the position of the vehicle 4 to be evaluated in the road width direction and the normal driving zone information and the transient driving zone information in each road link, it is possible to determine which driving zone the vehicle 4 to be evaluated is driving in. Note that whether the vehicle 4 to be evaluated has driven in the transient driving zone may be determined based on whether at least a part of the vehicle 4 to be evaluated has entered the transient driving zone, or may be determined based on whether a specific part (for example, the center part in the vehicle width direction) of the vehicle 4 to be evaluated has entered the transient driving zone.

[0061] For the road link where the vehicle 4 to be evaluated has driven in the transient driving zone, the server side control unit 33 determines whether the behavior of the vehicle 4 to be evaluated satisfies a predetermined condition.

[0062] For example, when the acceleration of the vehicle 4 to be evaluated is a negative value and the absolute value thereof is equal to or greater than a predetermined value, it can be determined that the vehicle 4 to be evaluated is decelerating rapidly in the transient driving zone. Such rapid deceleration may occur when the driver attempts to change lanes but is likely to collide with surrounding vehicles. Therefore, when the frequency of rapid deceleration of the vehicle 4 to be evaluated in the transient driving zone is high, it can be determined that the driver has difficulty predicting the movement of surrounding vehicles and has poor driving skills.

[0063] Also, when the amount of azimuth displacement of the vehicle 4 to be evaluated is equal to or greater than a predetermined value, it can be determined that the vehicle 4 to be evaluated has changed its traveling direction by sudden steering in the transient driving zone. Such a change in the traveling direction may occur when the driver attempts to change lanes but is likely to collide with surrounding vehicles. Therefore, when the frequency of changing the traveling direction of the vehicle 4 to be evaluated in the transient driving zone is high, it can be determined that the driver has difficulty predicting the movement of surrounding vehicles and has poor driving skills.

[0064] In addition, when the frequency of entry and exit of the vehicle 4 to be evaluated from the normal driving zone to the transient driving zone (the number of times of entry and exit per predetermined time) is equal to or greater than a predetermined value, it can be determined that the vehicle 4 to be evaluated is performing aggressive driving or is performing driving that is recognized as aggressive driving from the surroundings. In such a case, it can be determined that the driver's safe driving level is low. Note that depending on the crosswind and road surface conditions, the vehicle body may shake unintentionally, and even if it is not aggressive driving, the vehicle may repeatedly enter and exit the transient driving zone from the normal driving zone. Therefore, the time of entering the transient driving zone may be measured, and when the entry time is equal to or greater than a threshold value, the aggressive driving may be determined.

[0065] In addition, when the time that the vehicle 4 to be evaluated is traveling in the transitional driving zone is equal to or longer than a predetermined value, or when the angle formed by the vehicle traveling direction and the road traveling direction in the transitional driving zone is equal to or less than a predetermined value, it can be determined that the driver's wakefulness is low. That is, when the driver feels sleepy or is driving absent-mindedly, there is a tendency to stay in the transitional driving zone for a long time. Also, when the driver feels sleepy or is driving absent-mindedly, the angle between the vehicle traveling direction and the road traveling direction when entering the transitional driving zone from the normal driving zone tends to be smaller compared to an intentional entry into the transitional driving zone such as a lane change. In such a case, it can be determined that the driver's safe driving level is low.

[0066] In addition, for each vehicle 4 to be evaluated, by collecting the behavior in the transitional driving zone, the driving tendency of the driver can be determined. For example, when there is a tendency for the frequency of entering the transitional driving zone to be high, it can be determined that the driver is prone to impatience.

[0067] As described above, the server-side control unit 33 can evaluate the driving state of the driver based on the behavior of the vehicle 4 to be evaluated in the transitional driving zone. Such information on the driving state is for evaluating the driver and can be used as a basis for judgment such as the insurance premium of automobile insurance, or in the case of an elderly person, as a basis for judgment of returning the driver's license. That is, normally, the transitional driving zone is an area where driving is performed as a preparatory or preliminary operation for the next action (such as a lane change or a right or left turn). If one stays in such an area for a long time or performs sudden acceleration or deceleration in such an area, there is a possibility of inducing an accident. Therefore, the driving state of the driver can be evaluated based on the behavior of the vehicle 4 to be evaluated in the transitional driving zone.

[0068] With the above configuration, by generating normal driving zone information and transitional driving zone information based on the distribution of the positions of the plurality of vehicles 2 in the road width direction, more detailed information than the lane width information indicating simply whether a vehicle can travel can be included in the map data.

[0069] In addition, by evaluating the driving state of the driver based on the behavior of the vehicle 4 to be evaluated in the transitional driving zone, the driving skills and safe driving level of this driver can be evaluated, and it can be used as a basis for judgment such as the insurance premium of automobile insurance.

[0070] <Second Embodiment> In this embodiment, map data is generated by the map data generation system 1 as shown in FIG. 1, and the driving state of the driver is evaluated using the map data by the driving support system 100 as shown in FIG. 5.

[0071] [Driving Support System] The driving support system 100 includes a support target vehicle (mobile body) 5 that is a manually driven vehicle and an external server (information processing device) 3.

[0072] The support target vehicle 5 is equipped with a driving support unit 50, and the driving support unit 50 includes a position measurement unit 51, a measurement unit 52, a communication unit 53, a storage unit 54, a vehicle-side control unit 55, and an information output unit 56. Each part 51-55 of the information acquisition unit 40 has the same configuration as each part 21-25 of the information acquisition unit 20 of the vehicle 2.

[0073] The information output unit 56 is composed of, for example, an audio output unit such as a speaker or a display unit such as a screen, and is configured to output information to the passengers. In addition, when the support target vehicle 5 is an autonomous driving vehicle, a driving control unit may be provided instead of the information output unit 56.

[0074] The vehicle-side control unit 55 acquires matching information and detailed road configuration information from the external server 3 via the communication unit 53 and stores them in the storage unit 54. The vehicle-side control unit 55 compares the surrounding information, which is the point cloud data measured by the measurement unit 52, with the matching information, and extracts the point cloud of the object not included in the matching information. Among the objects not included in the matching information, those located on the roadway can be determined as other vehicles, and those located on the sidewalk can be determined as pedestrians, bicycles, etc.

[0075] (Driving Support by Predicting the Behavior of Other Vehicles) When the point cloud corresponding to the other vehicle is extracted, the vehicle - side control unit 55 calculates the position of this other vehicle in the road width direction by comparing it with the reference position included in the matching information, and determines whether this other vehicle is traveling in the normal driving lane or the transitional driving lane. Further, the vehicle - side control unit 55 calculates the traveling direction of the other vehicle and calculates the distance in the road width direction between the other vehicle and the support target vehicle 5.

[0076] Based on the behavior of the other vehicle in the transitional driving lane, the vehicle - side control unit 55 predicts the subsequent behavior of this other vehicle. For example, when the other vehicle enters the transitional driving lane from the normal driving lane and the angle formed by the vehicle traveling direction and the road traveling direction is equal to or greater than a predetermined value, it can be determined that the other vehicle has intentionally entered the transitional driving lane. Therefore, it is predicted that the driver of the other vehicle has the intention to change lanes.

[0077] When the vehicle - side control unit 55 determines that the other vehicle intends to change lanes, it causes the information output unit 56 to output information. At this time, it may output that there is a possibility that the other vehicle will change lanes, or may instruct acceleration or deceleration so as not to interfere with the lane change or instruct to prohibit the lane change. For example, when it is determined that an adjacent vehicle in the road width direction is about to change lanes, it may instruct deceleration, and when it is determined that a following vehicle is about to change lanes, it may instruct to prohibit the lane change so as not to perform double overtaking.

[0078] In addition, when the support target vehicle 5 is an autonomous vehicle, the vehicle - side control unit 55 may send a command to the driving control unit to accelerate, decelerate, or prohibit overtaking as described above.

[0079] (Driving Support When Predicting Collision with Other Vehicles) The vehicle - side control unit 55 calculates the degree of collision prediction with an oncoming vehicle based on the distance in the road - width direction between the oncoming vehicle and the vehicle 5 to be supported. For example, when an emergency vehicle such as an ambulance protrudes from the center line for overtaking in the oncoming lane, the distance between the emergency vehicle and the vehicle 5 to be supported becomes narrow and the degree of collision prediction becomes high. In such a case, it is preferable for the vehicle 5 to be supported to avoid the emergency vehicle, giving priority to the travel of the emergency vehicle.

[0080] Therefore, when the degree of collision prediction with the oncoming vehicle becomes equal to or greater than a predetermined value, the vehicle - side control unit 55 outputs information to the information output unit 56 so as to travel in a transitional travel zone located on the side opposite to the oncoming vehicle. Incidentally, when the vehicle 5 to be supported is an autonomous vehicle, the vehicle - side control unit 55 may send a command to the driving control unit so as to travel in a transitional travel zone located on the side opposite to the oncoming vehicle.

[0081] (Driving support when there are pedestrians) When the traffic volume of pedestrians on the sidewalk is large or the sidewalk width is narrow, pedestrians may protrude from the sidewalk to pass. On roads where such situations frequently occur, the normal travel lane may be biased to the side opposite to the sidewalk with respect to the center in the width direction of the lane. On the other hand, when pedestrians do not protrude from the sidewalk, the driver often drives so that the vehicle 5 to be supported travels in the center of the lane in the width direction, and may inadvertently drive in the transitional travel zone.

[0082] When a point cloud located on the sidewalk is extracted and its density or absolute number is equal to or greater than a predetermined value, it is estimated that the number of pedestrians is large. In such a case, the vehicle - side control unit 55 outputs information to the information output unit 56 so as to travel in the normal travel lane. Incidentally, when the vehicle 5 to be supported is an autonomous vehicle, the vehicle - side control unit 55 may send a command to the driving control unit so as to travel in the normal travel lane.

[0083] (Driving support in case of snow) A driver who is aware of the road conditions when there is no snow drives to avoid the roadside ditches and the like that become invisible during snowfall. When there is a deviation between the normal driving lane and the center in the width direction of the lane, a driver who is not aware of the road conditions when there is no snow may not recognize the existence of the roadside ditches and the like and may try to drive in the center in the width direction of the total area of the lane and the roadside ditches. In such a case, the vehicle-side control unit 55 causes the information output unit 56 to output information so as to drive on the normal driving lane.

[0084] In addition, when the supported vehicle 5 is an autonomous vehicle, the vehicle-side control unit 55 may send a command to the driving control unit so as to drive on the normal driving lane. By doing so, the supported vehicle 5 can easily drive on the ruts formed by the driving of a driver who is aware of the road conditions when there is no snow.

[0085] With the above configuration, by providing driving support using map data including normal driving lane information and transient driving lane information, it is possible to suppress collisions with other vehicles, pedestrians, etc. Also, in autonomous driving, it is possible to drive at the same position in the road width direction as in manual driving, and the anxiety given to passengers can be reduced.

[0086] Note that the present invention is not limited to the above-described embodiments, and includes other configurations and the like that can achieve the object of the present invention, and modifications and the like as shown below are also included in the present invention.

[0087] For example, in the above-described embodiment, all of the calculation step, the information generation step, and the map data generation step for generating map data are executed on the external server 3 side, but a part or all of each step may be executed on the vehicle side.

[0088] Also, in the above-described embodiment, a histogram is generated for the positions in the road width direction of a plurality of vehicles 2, and a range of ±2σ from the position where the maximum value is obtained is determined as the normal driving lane, but it is not limited to such a determination method. For example, the range based on the position where the maximum value is obtained may be further narrowed or widened. Also, an absolute value of the distribution number may be determined, and a position exceeding this absolute value may be set as the normal driving lane.

[0089] In addition, the best configuration, method, etc. for implementing the present invention are disclosed in the above description, but the present invention is not limited thereto. That is, the present invention is mainly illustrated and described with respect to specific embodiments, but without departing from the scope of the technical idea and purpose of the present invention, those skilled in the art can make various modifications to the above-described embodiments in terms of shape, material, quantity, and other detailed configurations. Therefore, the descriptions that limit the shape, material, etc. disclosed above are exemplarily described for facilitating the understanding of the present invention and do not limit the present invention. Thus, the descriptions using the names of members with some or all of the limitations on those shapes, materials, etc. removed are included in the present invention.

Explanation of Reference Numerals

[0090] 1 Map data generation system 2 Vehicle 3 External server 4 Vehicle to be evaluated 5 Vehicle to be supported 10 Evaluation system 100 Driving support system

Claims

1. An evaluation method executed by a server, comprising: a calculation step of calculating the position of a moving object in the road width direction included in the peripheral information with respect to the road information by comparing the peripheral information measured by a measurement unit mounted on the measurement moving object with the road information stored in advance; based on the distribution of the positions of a plurality of moving objects in the road width direction with respect to the road information, an information generation step of generating at least one of first information indicating a range where the distribution density is equal to or greater than a predetermined value and second information indicating an outer range of the range of the first information; and a map data generation step of generating map data including at least one of the first information and the second information. The map data including the second information is generated by the map data generation method executed by the server, characterized in that the driving state of the driver of the moving object is evaluated based on the acceleration of the moving object or the traveling direction of the moving object at the position in the road width direction corresponding to the second information.

2. The evaluation method according to claim 1, wherein in the information generation step of the map data generation method, a histogram is generated for the positions of the plurality of moving objects in the road width direction, and at least one of the first information and the second information is generated based on the position where the maximum value is obtained and the degree of variation.

3. A driving support method executed by a server, comprising: a calculation step of calculating the position of a moving object in the road width direction included in the peripheral information with respect to the road information by comparing the peripheral information measured by a measurement unit mounted on the measurement moving object with the road information stored in advance; based on the distribution of the positions of a plurality of moving objects in the road width direction with respect to the road information, an information generation step of generating at least one of first information indicating a range where the distribution density is equal to or greater than a predetermined value and second information indicating an outer range of the range of the first information; and a map data generation step of generating map data including at least one of the first information and the second information. The map data including the second information is generated by the map data generation method executed by the server, characterized in that based on the behavior of another moving object at the position in the road width direction corresponding to the second information, it is predicted whether the other moving object will change lanes, and when it is predicted that the other moving object will change lanes, information for driving support is output to the moving object.

4. In the information generation step of the map data generation method, a histogram is generated for the positions of the plurality of moving objects in the road width direction, and at least one of the first information and the second information is generated based on the position where the maximum value is obtained and the degree of variation. The driving support method according to claim 3.

5. An evaluation method executed by a server, In a range where the distribution density based on the positions of a plurality of moving objects in the road width direction is equal to or less than a predetermined value, based on the acceleration of the moving object or the traveling direction of the moving object at the position in the road width direction corresponding to the range, the driving state of the driver of the moving object is evaluated. An evaluation method characterized by this.

6. The position of the plurality of moving objects in the road width direction is calculated by comparing the peripheral information measured by a measuring unit mounted on the measuring moving object with the road information stored in advance. The evaluation method according to claim 5.

7. A driving support method executed by a server, In a range where the distribution density based on the positions of a plurality of moving objects in the road width direction is equal to or less than a predetermined value, based on the behavior of other moving objects at the position in the road width direction corresponding to the range, it is predicted whether the other moving object will change lanes. When it is predicted that the other moving object will change lanes, information for driving support is output to the moving object. A driving support method characterized by this.

8. The position of the plurality of moving objects in the road width direction is calculated by comparing the peripheral information measured by a measuring unit mounted on the measuring moving object with the road information stored in advance. The driving support method according to claim 5.

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