Travel control device, travel control method, and storage medium

Abstract

A driving control device, driving control method, and storage medium are provided that can detect road structures on a lane to change lanes. The driving control device (1) of the vehicle (2) includes: a lane detection unit (41) that detects the driving lane (101) in which the vehicle (2) is traveling based on image information obtained by a camera (13); a road structure detection unit (42) that detects road structures (103) stationary on the road surface based on sensor data containing the positions of various objects obtained by a radar (11) or a lidar (12); a vehicle position detection unit that detects the position of the vehicle (2); and a driving control unit (37) that causes the vehicle (2) to travel along the driving lane (101). When the driving control unit (37) detects a road structure (103) on the driving lane (101), it determines whether there is an alternative lane (105) connected to the driving lane (101) based on map information. If there is an alternative lane (105), it controls the steering device (5) to guide the vehicle (2) to the alternative lane (105).

Description

Technical Field

[0001] This invention relates to a driving control device, a driving control method, and a storage medium. Background Technology

[0002] In recent years, efforts to provide sustainable transportation systems that take into account vulnerable groups among transportation participants have become increasingly active. To achieve these goals, research and development related to driver assistance and autonomous driving technologies have been conducted to further improve transportation safety and convenience.

[0003] Patent Document 1 discloses a vehicle driving control device that performs lane keeping control to prevent the vehicle from leaving the lane. In lane keeping control, the driving control device detects left and right lane markings based on camera images and controls the steering device to keep the vehicle within the lane defined by the left and right lane markings.

[0004] [Existing technical documents]

[0005] [Patent Literature]

[0006] Patent Document 1: Japanese Patent Application Publication No. 2015-209129 Summary of the Invention

[0007] [The problem the invention aims to solve]

[0008] Sometimes, road structures are placed on the road to restrict traffic. Because road signs and other road structures are relatively small, they are sometimes difficult to detect with cameras. When road structures are present in the lane, vehicles may approach the road structures if lane keeping control is activated.

[0009] In view of the above background, one aspect of the present invention is to provide a driving control device, driving control method and control program capable of detecting road structures on a lane to perform lane changes.

[0010] [Methods used to solve problems]

[0011] To address the aforementioned issues, one aspect of the present invention is a vehicle driving control device comprising: a lane detection unit that detects the driving lane of the vehicle based on image information acquired by a camera; a road structure detection unit that detects stationary road structures on the road surface based on sensor data containing the positions of various objects acquired by radar or lidar; a vehicle position detection unit that detects the position of the vehicle; and a driving control unit that causes the vehicle to travel along the driving lane, wherein, if the driving control unit detects the road structure in the driving lane, it determines, based on map information, whether there is an alternative lane connecting to the driving lane, and if the alternative lane exists, it controls a steering device to guide the vehicle to the alternative lane.

[0012] Another aspect of the present invention is a vehicle driving control method executed by a computer, wherein the driving lane of the vehicle is detected from image information obtained by a camera, road structures stationary on the road surface are detected based on sensor data containing the positions of various objects obtained by radar or lidar, the position of the vehicle is detected, the vehicle is driven along the driving lane, if the road structure is detected in the driving lane, it is determined based on map information whether there is an alternative lane connecting to the driving lane, and if the alternative lane exists, the steering device is controlled to guide the vehicle to the alternative lane.

[0013] Another aspect of the invention is a storage medium storing a control program for causing a computer to execute a vehicle driving control method, wherein the control program causes the computer to perform the following steps: detecting the driving lane of the vehicle from image information obtained by a camera; detecting road structures stationary on the road surface based on sensor data containing the positions of various objects obtained by radar or lidar; detecting the position of the vehicle; causing the vehicle to drive along the driving lane; if the road structure is detected in the driving lane, determining whether there is an alternative lane connected to the driving lane based on map information; and if the alternative lane exists, controlling a steering device to guide the vehicle to the alternative lane.

[0014] [Invention Effects]

[0015] Based on the above methods, it is possible to provide a driving control device, driving control method, and control program that can detect road structures on the lane to change lanes. Attached Figure Description

[0016] Figure 1 This is a structural diagram of the vehicle control device according to the implementation method.

[0017] Figure 2 It is an explanatory diagram of the road on which vehicles travel.

[0018] Figure 3 This is an illustrative diagram showing an example of sensor data about a road obtained by radar.

[0019] Figure 4 This is a flowchart illustrating the steps of the driving control method according to an embodiment. Detailed Implementation

[0020] Hereinafter, with reference to the accompanying drawings, the implementation methods of the driving control device, driving control method, and control program will be described.

[0021] like Figure 1 As shown, the driving control device 1 is installed in vehicle 2. Vehicle 2 may be, for example, a four-wheeled vehicle. Vehicle 2 is an autonomous driving vehicle or a vehicle with driving assistance functions.

[0022] Vehicle 2 has a propulsion device 3, a braking device 4, and a steering device 5. The propulsion device 3 is a device that provides driving force to vehicle 2, and includes, for example, a power source and a transmission. The power source includes at least one of an internal combustion engine such as a gasoline engine or a diesel engine, and an electric motor. The braking device 4 is a device that applies braking force to vehicle 2, and includes, for example, a brake caliper that presses a pad against a brake disc and an electric cylinder that supplies hydraulic pressure to the brake caliper. The steering device 5 is a device for changing the steering angle of the wheels, and includes, for example, a rack and pinion mechanism that steers the wheels and an electric motor that drives the rack and pinion mechanism. The propulsion device 3, the braking device 4, and the steering device 5 are controlled by a driving control device 1.

[0023] Vehicle 2 includes an external detection device 7. The external detection device 7 is a device for detecting objects outside the vehicle. The external detection device 7 is a sensor that captures electromagnetic waves and light from the surroundings of vehicle 2 to detect objects outside the vehicle. The external detection device 7 includes radar 11, lidar 12 (LIDAR), and camera 13.

[0024] Radar 11 transmits radio waves around vehicle 2 and detects the position and speed of objects by receiving radio waves reflected from them. Radar 11 can be a millimeter-wave radar that uses millimeter waves as electromagnetic waves. Multiple radars 11 can be installed in vehicle 2. Radar 11 includes at least a front radar for detecting objects in the area in front of vehicle 2. Radar 11 may also include a rear radar for detecting obstacles in the area behind vehicle 2. Radar 11 may also include multiple corner radars for detecting obstacles in the areas to the right front, left front, right rear, and left rear of vehicle 2.

[0025] The front radar, one of the radars 11, can be positioned at the center of the front of the vehicle 2 in the left-right direction, transmitting radio waves forward. For example, the front radar can be positioned inside a sign located at the front of the vehicle 2. The sign can be formed of a resin material that allows radio waves to pass through. The front radar transmits radio waves to the left and right at a predetermined angle based on a centerline extending forward from the vehicle 2. The angle can be set, for example, to 20° or 15° to the left and right. For instance, the front radar can transmit radio waves 30m to the left and right from a distance of 150m in front. The front radar can also transmit radio waves vertically at a predetermined angle based on the centerline.

[0026] Radar 11 acquires sensor data containing the position (distance and direction) and reflection intensity of each object that reflects the radio waves emitted by radar 11. This sensor data is also known as point cluster data.

[0027] The lidar 12 illuminates infrared light or other light around the vehicle 2 and captures the reflected light, thereby detecting the position (distance and direction) of objects. The lidar 12 can detect obstacles in the area in front of the vehicle 2.

[0028] Camera 13 captures images of the area surrounding vehicle 2. These images include surrounding vehicles (moving objects), pedestrians, guardrails, curbs, walls, the median strip, the shape of the road, dividing lines 102, and road markings. Camera 13 may be, for example, a digital camera utilizing a solid-state imaging element such as CCD or CMOS. Camera 13 may include a front camera that captures at least the area in front of vehicle 2. Camera 13 may also include a rear camera that captures images of the rear of vehicle 2, and a pair of side cameras that capture images of the left and right sides of vehicle 2. Camera 13 may also be, for example, a stereo camera.

[0029] Vehicle 2 has vehicle sensor 15. Vehicle sensor 15 includes a vehicle speed sensor for detecting the speed of vehicle 2 and an acceleration sensor for detecting acceleration. Vehicle sensor 15 may also include a yaw rate sensor for detecting angular velocity about a vertical axis and an orientation sensor for detecting the orientation of vehicle 2, etc.

[0030] Vehicle 2 is equipped with a Global Navigation Satellite System (GNSS) receiver 16. The GNSS receiver 16 determines the position (latitude, longitude) of vehicle 2 based on signals received from artificial satellites (positioning satellites).

[0031] Vehicle 2 has a driving control device 17. The driving control device 17 accepts input operations from the occupant (driver) to control vehicle 2. The driving control device 17 includes a steering wheel, accelerator pedal, and brake pedal. Additionally, the driving control device 17 may also include a gearshift lever, parking brake lever, etc. Sensors for detecting the amount of operation are installed on each driving control device 17. The driving control device 17 outputs signals indicating the amount of operation to the driving control device 1.

[0032] Vehicle 2 is equipped with an HMI18 (Human Machine Interface). The HMI18 reports various information to the occupants through displays and sounds, and accepts input operations from the occupants. The HMI18 may include, for example, a touch panel display, speakers, etc.

[0033] The driving control device 1 is a computer having a processor 31 and a memory 32 communicatively connected to the processor 31. The processor 31 may include at least one of a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or a RISC (Reduced Instruction Set Computer) as its core. The memory 32 stores control programs and various data executed by the processor 31. The memory 32 may include at least one of volatile memory and non-volatile memory. Volatile memory may be, for example, dynamic random access memory (DRAM) or static random access memory (SRAM). Non-volatile memory may be an SSD (Solid State Drive), flash memory, disk storage device, or optical disk storage device. At least a portion of the driving control device 1 may be implemented in hardware such as LSI (Large Scale Integration), ASIC (Application Specific Integrated Circuit), or FPGA (Field-Programmable Gate Array), or may be implemented in a combination of software and hardware. The driving control device 1 can be composed of a single piece of hardware or multiple pieces of hardware capable of communicating with each other. A portion of the driving control device 1 can also be composed of an external server located outside the vehicle 2.

[0034] The processor 31 executes programs stored in the memory 32 to implement various applications. The programs can also be stored on removable recordable media such as DVDs and CD-ROMs, and installed in the memory 32 by a reading device. Alternatively, the programs can be downloaded and installed in the memory 32 via communication networks such as the Internet.

[0035] Map information is stored in memory 32. This map information can be high-precision. It includes road types such as highways, toll roads, national roads, and prefectural roads; the number of lanes; the center position of each lane (including three-dimensional coordinates of longitude, latitude, and altitude); the shape of road markings such as road dividing lines and lane boundaries; the presence or absence of sidewalks, curbs, and other road markings; the location of intersections; the location of lane merging and branching points; the area of ​​emergency stopping lanes; the width of each lane; and road signs. The map information may also include traffic restriction information, address information (address / postal code), facility information, and telephone number information.

[0036] The processor 31 executes programs stored in the memory 32 to function as the surrounding environment recognition unit 35, the vehicle position recognition unit 36, and the driving control unit 37. The surrounding environment recognition unit 35 includes a lane detection unit 41, a road structure detection unit 42, and an obstacle detection unit 43.

[0037] The surrounding environment recognition unit 35 recognizes the surrounding environment of the vehicle 2. Based on the detection results of the external recognition device 7, the surrounding environment 35 identifies the external environment (outside world), which includes obstacles around the vehicle 2, the shape of the road, the presence or absence of a sidewalk, road markings, etc. Obstacles include, for example, guardrails, utility poles, surrounding vehicles, pedestrians, and other people. The surrounding environment recognition unit 35 can obtain the position, speed, and acceleration of surrounding vehicles based on the detection results of the external recognition device 7.

[0038] The lane detection unit 41 of the surrounding environment recognition unit 35 detects the driving lane 101 of the vehicle 2 based on the image information acquired by the camera 13. Figure 2 This is an explanatory diagram of the road on which vehicle 2 travels. The lane detection unit 41 detects a pair of dividing lines 102 extending to the right and left of vehicle 2 based on the image information, and sets the area between the pair of dividing lines 102 as the driving lane 101.

[0039] The surrounding environment recognition unit 35's road structure detection unit 42 detects stationary road structures 103 on the road surface based on sensor data containing the positions of various objects obtained by radar 11 or lidar 12. Road structures 103 are structures disposed on the road surface, such as hangers (traffic cones), arrow slabs, buffer drums (safety drums), guardrails, concrete blocks, etc. Road structures 103 are disposed on the lanes to restrict traffic flow.

[0040] The road structure detection unit 42 can detect the road structure 103 based on sensor data acquired by the radar 11. The road structure detection unit 42 can extract data corresponding to the road structure 103 from the sensor data acquired by the radar 11 according to predetermined extraction conditions.

[0041] The extraction conditions may include a first condition such that the reflection intensity is above a predetermined first determination value. Noise is removed from the sensor data based on this first condition. Furthermore, the road structure 103 that is the target of detection is relatively small, so increasing the first determination value makes detection difficult. Therefore, the first determination value can be set to a value smaller than the reflection intensity when radio waves are reflected from a vehicle. Additionally, in order to detect road structures 103 located far from the vehicle 2, the first determination value is set to a relatively small value.

[0042] The extraction condition may include a second condition that the object's position falls within a specified height range. That is, the road structure detection unit 42 extracts sensor data that falls within the specified height range based on sensor data. According to the second condition, data corresponding to pedestrian entrances / exits or steps on the road surface, and data corresponding to overhead guidance signs separated from the road surface, can be removed from the sensor data.

[0043] The extraction conditions may include a third condition: when a linear structure 104 extending linearly in the horizontal direction is detected based on sensor data, the object's position is located on the side of vehicle 2, with reference to the linear structure 104. That is, the road structure detection unit 42 does not use sensor data from the side opposite to vehicle 2, with reference to the linear structure 104, for the detection of the road structure 103. The linear structure 104 is an object corresponding to walls, guardrails, median strips, etc. Figure 2The example described is of a linear structure 104 on the left being a guardrail and a linear structure 104 on the right being a central median strip. Based on the linear structure 104, the data of objects on the opposite side of vehicle 2 is highly likely to be noise. Furthermore, even if the data of objects on the opposite side of vehicle 2, based on the linear structure 104, is not noise, the probability of vehicle 2 traveling in that area is low, therefore the value of detecting road structures 103 in that area is low. Through this third condition, the data capacity of the sensor data is reduced, thus improving the processing efficiency of the processor 31 of the control device.

[0044] Figure 3 This is an explanatory diagram of an example of data extracted from sensor data by the road structure detection unit 42 based on the first to third conditions. Figure 3 The black circle 107 in the diagram represents the location where the radio wave is reflected, i.e., the location where the object exists. Because the extraction range is defined by the left and right linear structures 104, the data capacity is reduced.

[0045] The road structure detection unit 42 detects stationary road structures 103 by comparing data extracted based on extraction conditions frame by frame. Specifically, the road structure detection unit 42 compares the positions of each object contained in the data frame by frame, identifying objects whose positions have not changed as stationary road structures 103. Objects whose positions have changed may be surrounding vehicles or people.

[0046] The obstacle detection unit 43 of the surrounding environment recognition unit 35 identifies obstacles around the vehicle 2 based on the detection results of the external recognition device 7. Obstacles detected by the obstacle detection unit 43 include, for example, guardrails, utility poles, surrounding vehicles, pedestrians, and other people. The road structure detection unit 42 can detect road structures 103 based on sensor data acquired by the radar 11. The road structure detection unit 42 can determine objects with a reflectance intensity of a predetermined second determination value or higher as obstacles based on the sensor data acquired by the radar 11. The second determination value is set to a value greater than the first determination value. Therefore, objects with a reflectance intensity higher than that of the road structure 103 are identified as obstacles.

[0047] The vehicle location identification unit 36 ​​identifies the position of vehicle 2. The vehicle location identification unit 36 ​​can identify the position of vehicle 2 based on the GNSS signal received by GNSS receiver 16.

[0048] The driving control unit 37 directs the vehicle 2 to travel along the driving lane 101. The driving control unit 37 performs lane keeping assist control and controls the steering device 5. Alternatively, in lane keeping assist control, the driving control unit 37 can set a target track in the center of the driving lane 101 so that the vehicle 2 is positioned on the target track. Furthermore, in lane keeping assist control, the driving control unit 37 can also control the steering device 5 so that the closer the vehicle 2 gets to the left and right dividing lines 102 of the driving lane 101, the more it turns towards the center of the lane.

[0049] When the driving control unit 37 detects a road structure 103 in the driving lane 101, it determines, based on map information, whether there is an alternative lane 105 connecting to the driving lane 101. If an alternative lane 105 exists, it controls the steering device 5 to guide the vehicle 2 towards the alternative lane 105. Figure 3 As shown, when the road structure detection unit 42 detects a road structure 103 on the driving lane 101, the driving control unit 37 determines whether there is an alternative lane 105 connected to the driving lane 101 based on map information stored in the memory 32. The alternative lane 105 connected to the driving lane 101 includes lanes extending adjacent to and parallel to the driving lane 101, and lanes branching off from the driving lane 101. Figure 3 In the example, the lane that extends parallel to and adjacent to the driving lane 101 is equivalent to the alternative lane 105.

[0050] When an alternative lane 105 exists, the driving control unit 37 guides the vehicle 2 to the alternative lane 105 by, for example, setting a target track in the center of the alternative lane 105 and controlling the steering device 5 to position the vehicle 2 on the target track. The center of the alternative lane 105 can be set based on map information or based on image data obtained by the camera 13. When an alternative lane 105 does not exist, the driving control unit 37 can also control the propulsion device 3 and the braking device 4 to stop the vehicle 2.

[0051] Next, use Figure 4 The flowchart illustrating the steps of the driving control method explains the driving control performed by the driving control device 1. First, the driving control device 1 detects the driving lane 101 (ST1) in which the vehicle 2 is traveling based on image information acquired by the camera 13. As described above, the driving lane 101 can be detected by the lane detection unit 41.

[0052] Next, the driving control device 1 detects the road structure 103 (ST2) stationary on the road surface based on sensor data including the positions of various objects acquired by radar 11 or lidar 12. The road structure 103 can be detected by the road structure detection unit 42 as described above.

[0053] Next, the driving control device 1 determines whether there is a road structure 103 in the driving lane 101 (ST3). If there is no road structure 103 in the driving lane 101 (ST3: No), the driving control device 1 sets the track along the center of the driving lane 101 as the target track (ST4).

[0054] If a road structure 103 exists in the driving lane 101 (ST3: Yes), the driving control device 1 determines, based on map information, whether there is an alternative lane 105 connected to the driving lane 101 (ST5).

[0055] If an alternative lane 105 exists (ST5: Yes), the driving control device 1 will set the track along the center of the alternative lane 105 as the target track (ST6).

[0056] After the target track is set in step ST4 or ST6, the driving control device 1 controls the steering device 5 (ST7) to make the vehicle 2 travel along the target track. If there is no alternative lane 105 (ST5: No), the driving control device 1 controls the propulsion device 3 and the braking device 4 to stop the vehicle 2 (ST8).

[0057] According to the above implementation, the driving control device 1 can detect road structures 103 on the driving lane 101 and, when road structures 103 are present, cause the vehicle 2 to change lanes to the alternative lane 105.

[0058] In order to detect road structures 103, the driving control device 1 extracts sensor data acquired by the radar 11 using a first determination value that is set lower than a second determination value used for obstacle detection. Thus, the driving control device 1 can detect small and difficult-to-detect road structures 103 based on the sensor data acquired by the radar 11. By using a first determination value set lower than the second determination value, the data capacity of the sensor data can potentially be increased. Conversely, the driving control device 1 does not use sensor data from the side opposite to the vehicle 2, with the linear structure 104 as a reference, for detecting road structures 103, thereby reducing the data capacity of the sensor data.

[0059] The implementation method is not limited to the structure described above and can be widely modified. For example, the road structure detection unit 42 can also use a lidar 12 instead of a radar 11 to detect the road structure 103.

[0060] The above-described implementation method can be described as follows.

[0061] One embodiment is a driving control device 1 for a vehicle 2, comprising: a lane detection unit 41 that detects the driving lane 101 in which the vehicle 2 is traveling based on image information acquired by a camera 13; a road structure detection unit 42 that detects road structures 103 stationary on the road surface based on sensor data containing the positions of various objects acquired by a radar 11 or a lidar 12; a vehicle position detection unit that detects the position of the vehicle 2; and a driving control unit 37 that causes the vehicle 2 to travel along the driving lane 101. When the driving control unit 37 detects the road structure 103 in the driving lane 101, it determines, based on map information, whether there is an alternative lane 105 connected to the driving lane 101. If the alternative lane 105 exists, it controls a steering device 5 to guide the vehicle 2 to the alternative lane 105.

[0062] According to this method, a driving control device 1 can be provided that can detect road structures 103 on the lane to change lanes.

[0063] In the above embodiment, the road structure detection unit 42 can also detect the stationary road structure 103 by comparing the sensor data frame by frame.

[0064] According to this method, the road structure detection unit 42 is able to detect stationary road structures 103 on the driving lane 101.

[0065] In the above embodiments, the road structure detection unit 42 may also extract sensor data within a specified height range based on the sensor data, and detect the road structure 103 based on the extracted sensor data.

[0066] According to the scheme, it is possible to prevent structures such as entrances and exits, road surface bumps, and overhead directional signs from being mistakenly identified as road structures 103.

[0067] In the above-described embodiments, the road structure detection unit 42 may also detect the linear structure 104 extending in a straight line along the horizontal direction based on the sensor data, without using the sensor data from the side opposite to the vehicle 2 with the linear structure 104 as a reference for the detection of the road structure 103.

[0068] According to this method, the data capacity of the sensor data is reduced, and the processing efficiency of the control device is improved. Data from objects in the region opposite to the vehicle 2, with reference to the linear structure 104, is highly likely to be noise. Furthermore, even if the data is not noise, the likelihood of the vehicle 2 traveling in that region is low; therefore, detecting the road structure 103 in that region is of low value.

[0069] Another implementation is a vehicle 2 driving control method executed by a computer, which detects the driving lane 101 in which the vehicle 2 is traveling from image information obtained by camera 13, detects road structures 103 stationary on the road surface based on sensor data containing the positions of various objects obtained by radar 11 or lidar 12, detects the position of the vehicle 2, and causes the vehicle 2 to travel along the driving lane 101. If the road structure 103 is detected in the driving lane 101, it is determined based on map information whether there is an alternative lane 105 connected to the driving lane 101. If the alternative lane 105 exists, the steering device 5 is controlled to guide the vehicle 2 to the alternative lane 105.

[0070] According to this method, a driving control method can be provided that can detect road structures 103 on the lane to change lanes.

[0071] Another embodiment is a storage medium storing a control program for causing a computer to execute a driving control method for vehicle 2. The control program causes the computer to perform the following steps: detect the driving lane 101 of vehicle 2 from image information obtained by camera 13; detect a stationary road structure 103 on the road surface based on sensor data containing the positions of various objects obtained by radar 11 or lidar 12; detect the position of vehicle 2; cause vehicle 2 to drive along the driving lane 101; if the road structure 103 is detected in the driving lane 101, determine whether there is an alternative lane 105 connecting to the driving lane 101 based on map information; and if the alternative lane 105 exists, control the steering device 5 to guide vehicle 2 towards the alternative lane 105.

[0072] According to this method, a control program can be provided for executing a driving control method that can detect road structures 103 on the lane to perform lane changes.

[0073] Explanation of reference numerals in the attached figures

[0074] 1: Driving control device

[0075] 2: Vehicles

[0076] 3: Propulsion device

[0077] 4: Braking device

[0078] 5: Steering system

[0079] 7: External identification device

[0080] 11: Radar

[0081] 12: LiDAR

[0082] 13: Camera

[0083] 16: GNSS receiver

[0084] 17: Driving control device

[0085] 31: Processor

[0086] 32: Memory

[0087] 35: Surrounding Environment Identification Department

[0088] 36: Vehicle Position Recognition Unit

[0089] 37: Driving Control Unit

[0090] 41: Lane Inspection Department

[0091] 42: Road Structure Inspection Department

[0092] 43: Obstacle Detection Department

[0093] 101: Driving lane

[0094] 102: Dividing line

[0095] 103: Road Structures

[0096] 104: Linear Structure

[0097] 105: Alternative Lane

Claims

1. A driving control device, which is a driving control device for a vehicle, wherein, The driving control device has the following features: The lane detection unit detects the driving lane of the vehicle based on image information obtained from the camera; The road structure inspection unit detects road structures stationary on the road surface based on sensor data containing the position of each object obtained by radar or lidar. The vehicle position detection unit detects the position of the vehicle. as well as A driving control unit that directs the vehicle to travel along the driving lane. When the driving control unit detects the road structure in the driving lane, it determines, based on map information, whether there is an alternative lane connecting to the driving lane. If the alternative lane is available, control the steering device to guide the vehicle into the alternative lane.

2. The driving control device according to claim 1, wherein, The road structure detection unit detects stationary road structures by comparing sensor data frame by frame.

3. The driving control device according to claim 1, wherein, The road structure detection unit extracts sensor data within a specified height range based on the sensor data, and detects the road structure based on the extracted sensor data.

4. The driving control device according to claim 1, wherein, The road structure detection unit detects linear structures that extend in a straight line along the horizontal direction based on the sensor data, but does not use the sensor data from the side opposite to the vehicle with the linear structure as a reference for the detection of the road structure.

5. A driving control method, which is a vehicle driving control method executed by a computer, wherein, The vehicle's driving lane is detected from image information obtained from the camera. Detecting stationary road structures on the road surface using sensor data containing the positions of various objects, obtained by radar or lidar. Detect the position of the vehicle. The vehicle is to travel along the driving lane. If the road structure is detected in the driving lane, a determination is made based on map information to determine whether there is an alternative lane connecting to the driving lane. If the alternative lane is available, the steering device is controlled to guide the vehicle into the alternative lane.

6. A storage medium storing a control program for causing a computer to execute a vehicle driving control method, wherein, The control program causes the computer to perform the following steps: The vehicle's driving lane is detected from image information obtained from the camera. Detecting stationary road structures on the road surface using sensor data containing the positions of various objects, obtained by radar or lidar. Detect the position of the vehicle. The vehicle is to travel along the driving lane. If the road structure is detected in the driving lane, a determination is made based on map information to determine whether there is an alternative lane connecting to the driving lane. If the alternative lane is available, the steering device is controlled to guide the vehicle into the alternative lane.

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