Driving control device, driving control method, and control program

Abstract

The present invention provides a driving control device that can detect road structures on the lane and perform lane changes. [Solution] The vehicle 2's driving control device 1 includes a lane detection unit 41 that detects the driving lane 101 on which the vehicle 2 is traveling from image information acquired by a camera 13, a road structure detection unit 42 that detects stationary road structures 103 on the road surface based on sensor data including the positions of each object acquired by a radar 11 or lidar 12, a vehicle position detection unit that detects the position of the vehicle 2, and a driving control unit 37 that drives the vehicle 2 along the driving lane 101. When a road structure 103 is detected on the driving lane 101, the driving control unit 37 determines whether or not there is an alternative lane 105 adjacent to the driving lane 101 based on map information, and if an alternative lane 105 exists, it controls the steering device 5 to guide the vehicle 2 to the alternative lane 105.

Description

Technical Field

[0001] The present invention relates to a vehicle control device and a reinforcement learning method.

Background Art

[0002] In recent years, efforts have been actively made to provide a sustainable transportation system that takes into account people in vulnerable positions among traffic participants. In order to further improve traffic safety and convenience towards this realization, research and development on driving support technologies and autonomous driving technologies have been carried out.

[0003] Patent Document 1 discloses a vehicle running control device that executes lane keeping control to prevent a vehicle from deviating from a lane. In the lane keeping control, the running control device detects left and right lane dividing lines based on a camera image and controls a steering device so as to maintain the vehicle within the lane defined by the left and right lane dividing lines.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] There may be road structures for restricting passage placed on the road. Since road structures such as pylons are relatively small, they may be difficult to detect with a camera. When a road structure exists in a lane and lane keeping control is executed, there is a risk that the vehicle may approach the road structure.

[0006] In view of the above background, an aspect of the present invention aims to provide a running control device, a running control method, and a control program that can detect road structures on a lane and perform a lane change.

Means for Solving the Problems

[0007] To solve the above problems, one aspect of the present invention provides a vehicle driving control device comprising: a lane detection unit that detects the driving lane on which the vehicle is traveling from image information acquired by a camera; a road structure detection unit that detects stationary road structures on the road surface based on sensor data including the positions of each object acquired by radar or lidar; a vehicle position detection unit that detects the position of the vehicle; and a driving control unit that drives the vehicle along the driving lane, wherein when the road structure is detected on the driving lane, the driving control unit determines, based on map information, whether or not there is an alternative lane adjacent to the driving lane, and if the alternative lane exists, controls the steering device to guide the vehicle to the alternative lane.

[0008] Another aspect of the present invention is a vehicle driving control method performed by a computer, comprising: detecting the driving lane in which the vehicle is traveling from image information acquired by a camera; detecting stationary road structures on the road surface based on sensor data including the positions of each object acquired by radar or lidar; detecting the position of the vehicle; driving the vehicle along the driving lane; determining, based on map information, whether or not there is an alternative lane adjacent to the driving lane when a road structure is detected on the driving lane; and controlling the steering device to guide the vehicle to the alternative lane when an alternative lane exists.

[0009] Another aspect of the present invention is a control program for causing a computer to execute a vehicle driving control method, which causes the computer to detect the driving lane in which the vehicle is traveling from image information acquired by a camera, to detect stationary road structures on the road surface based on sensor data including the positions of each object acquired by radar or lidar, to detect the position of the vehicle, to cause the vehicle to travel along the driving lane, to determine whether or not there is an alternative lane adjacent to the driving lane based on map information when a road structure is detected on the driving lane, and to control the steering device to guide the vehicle to the alternative lane if an alternative lane exists. [Effects of the Invention]

[0010] According to the above embodiments, it is possible to provide a driving control device, a driving control method, and a control program that can detect road structures on a lane and perform lane changes. [Brief explanation of the drawing]

[0011] [Figure 1] Configuration diagram of a vehicle control device according to this embodiment [Figure 2] Diagram illustrating the roads on which vehicles travel. [Figure 3] An explanatory diagram showing an example of road sensor data acquired by radar. [Figure 4] Flowchart showing the procedure of the driving control method according to the embodiment. [Modes for carrying out the invention]

[0012] The following describes embodiments of the travel control device, travel control method, and control program with reference to the drawings.

[0013] As shown in Figure 1, the driving control device 1 is installed in the vehicle 2. The vehicle 2 may be, for example, a four-wheeled automobile. The vehicle 2 is an autonomous vehicle or a vehicle with driver assistance functions.

[0014] Vehicle 2 has a propulsion system 3, a braking system 4, and a steering system 5. The propulsion system 3 is a device that provides driving force to vehicle 2 and includes, for example, a power source and a transmission. The power source has at least one of an internal combustion engine such as a gasoline engine or a diesel engine and an electric motor. The braking system 4 is a device that provides braking force to vehicle 2 and includes, for example, a brake caliper that presses pads against a brake rotor and an electric cylinder that supplies hydraulic pressure to the brake caliper. The steering system 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 system 3, the braking system 4, and the steering system 5 are controlled by a driving control device 1.

[0015] Vehicle 2 has an external environment recognition device 7. The external environment recognition device 7 is a device that detects objects outside the vehicle. The external environment recognition device 7 is a sensor that detects objects outside the vehicle by capturing electromagnetic waves and light from the surroundings of Vehicle 2. The external environment recognition device 7 includes a radar 11, a LiDAR 12, and a camera 13.

[0016] Radar 11 detects the position and speed of an object by transmitting radio waves around the vehicle 2 and receiving radio waves reflected by the object. Radar 11 may be a millimeter-wave radar that utilizes millimeter waves for electromagnetic radiation. Multiple radars 11 may be installed on the vehicle 2. Radar 11 includes at least a forward radar that detects objects in the area in front of the vehicle 2. Radar 11 may also include a rear radar that detects obstacles in the area behind the vehicle 2. Radar 11 may also include a plurality of corner radars that detect obstacles in the areas to the right front, left front, right rear, and left rear of the vehicle 2.

[0017] One of the radars 11, the forward radar, is preferably located in the center of the front end of the vehicle 2 in the left-right direction and transmits radio waves forward. The forward radar may be located, for example, behind an emblem located on the front end of the vehicle 2. The emblem may be made of a resin material that transmits radio waves. The forward radar transmits radio waves to the left and right at a predetermined angular width with respect to a center line extending forward from the vehicle 2. The angular width may be set, for example, to 20° to the left and 15° to the right. For example, the forward radar may transmit radio waves within a range of 30m to the left and right at a distance of 150m ahead. The forward radar may also transmit radio waves vertically at a predetermined angular width with respect to the center line.

[0018] Radar 11 acquires sensor data, including the position (distance and direction) and reflection intensity of each object that reflects the radio waves transmitted by Radar 11. Sensor data is also called point cloud data.

[0019] The lidar 12 irradiates light such as infrared light around the vehicle 2 and captures the reflected light to detect the position (distance and direction) of an object. The lidar 12 may detect obstacles existing in the area in front of the vehicle 2.

[0020] The camera 13 images the surroundings of the vehicle 2 and acquires an image of the surroundings of the vehicle 2. The image of the surroundings of the vehicle 2 includes surrounding vehicles (surrounding moving objects), pedestrians, guardrails, curbs, walls, median strips, road shapes, lane lines 102, road signs drawn on the road, and the like existing around the vehicle 2. The camera 13 may be, for example, a digital camera using a solid-state imaging device such as a CCD or a CMOS. The camera 13 includes a front camera that images at least the area in front of the vehicle 2. The camera 13 may include a rear camera that images the rear of the vehicle 2 and a pair of side cameras that image the left and right sides of the vehicle 2. The camera 13 may be, for example, a stereo camera.

[0021] The vehicle 2 has a vehicle sensor 15. The vehicle sensor 15 includes a vehicle speed sensor that detects the speed of the vehicle 2 and an acceleration sensor that detects acceleration. The vehicle sensor 15 may further include a yaw rate sensor that detects the angular velocity around the vertical axis, a direction sensor that detects the direction of the vehicle 2, and the like.

[0022] The vehicle 2 has a GNSS (Global Navigation Satellite System) receiver 16. The GNSS receiver 16 identifies the position (latitude and longitude) of the vehicle 2 based on signals received from artificial satellites (positioning satellites).

[0023] The vehicle 2 has a driving operation device 17. The driving operation device 17 receives an input operation performed by an occupant (driver) to control the vehicle 2. The driving operation device 17 includes a steering wheel, an accelerator pedal, and a brake pedal. Further, the driving operation device 17 may include a shift lever, a parking brake lever, and the like. A sensor that detects the operation amount is attached to each driving operation device 17. The driving operation device 17 outputs a signal indicating the operation amount to the driving control device 1.

[0024] Vehicle 2 is equipped with an HMI18 (Human Machine Interface). The HMI18 provides various information to the occupants through displays and voice prompts, and also accepts input operations from the occupants. The HMI18 may include, for example, a touch panel display and speakers.

[0025] The vehicle control device 1 is a computer having a processor 31 and a memory 32 that is communicatively connected to the processor 31. The processor 31 may include at least one of the following as its core: a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), or a RISC (Reduced Instruction Set Computer). The memory 32 stores control programs executed by the processor 31 and various data. The memory 32 may include at least one of volatile memory and non-volatile memory. The volatile memory may be, for example, DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory). The non-volatile memory may be an SSD (Solid State Drive), flash memory, magnetic disk storage device, or optical disk storage device. At least a part of the vehicle control device 1 may be implemented by hardware such as an LSI (Large Scale Integration), ASIC (application specific integrated circuit), or FPGA (field-programmable gate array), or by a combination of software and hardware. The driving control device 1 may be composed of a single piece of hardware, or it may be composed of multiple pieces of hardware that can communicate with each other. Part of the driving control device 1 may be composed of an external server located outside the vehicle 2.

[0026] The processor 31 implements various applications by executing programs stored in memory 32. Programs may be stored on removable recordable media such as DVDs or CD-ROMs, and installed in memory 32 when the recordable media is read by a reader. Alternatively, programs may be downloaded to and installed in memory 32 via a communication network such as the internet.

[0027] Memory 32 stores map information. The map information should preferably be high-precision map information. The map information includes road type (such as expressways, toll roads, national roads, and prefectural roads), number of lanes, center position of each lane (including longitude, latitude, and height in 3D coordinates), shape of road markings such as road markings and lane boundaries, presence or absence of sidewalks, curbs, fences, etc., location of intersections, location of lane merging and branching points, area of ​​emergency parking zones, width of each lane, and road signs. The map information may also include traffic regulation information, address information (address and postal code), facility information, telephone number information, etc.

[0028] The processor 31 functions as a surrounding environment recognition unit 35, a vehicle position recognition unit 36, and a driving control unit 37 by executing a program stored in the memory 32. The surrounding environment recognition unit 35 includes a lane detection unit 41, a road structure detection unit 42, and an obstacle detection unit 43.

[0029] The surrounding environment recognition unit 35 recognizes the environment around the vehicle 2. Based on the detection results of the external environment recognition device 7, the surrounding environment recognition unit 35 recognizes the surrounding environment (external world), including obstacles located around the vehicle 2, the shape of the road, the presence or absence of sidewalks, road markings, etc. Obstacles include, for example, guardrails, utility poles, surrounding vehicles, and people such as pedestrians. From the detection results of the external environment recognition device 7, the surrounding environment recognition unit 35 can acquire the status of surrounding vehicles, such as their position, speed, and acceleration.

[0030] The lane detection unit 41 of the surrounding environment recognition unit 35 detects the driving lane 101 on which the vehicle 2 is traveling from the image information acquired by the camera 13. Figure 2 is an explanatory diagram of the road on which the vehicle 2 is traveling. The lane detection unit 41 detects a pair of lane markings 102 extending to the right and left sides of the vehicle 2 from the image information and sets the area between the pair of lane markings 102 as the driving lane 101.

[0031] The road structure detection unit 42 of the surrounding environment recognition unit 35 detects stationary road structures 103 on the road surface based on sensor data including the position of each object acquired by the radar 11 or lidar 12. The road structures 103 are structures placed on the road surface and include, for example, pylons (traffic cones), arrow signs, cushion drums (safety drums), guardrails, concrete blocks, etc. The road structures 103 are placed on lanes to restrict traffic in those lanes.

[0032] The road structure detection unit 42 may detect road structures 103 based on sensor data acquired by the radar 11. The road structure detection unit 42 may extract data corresponding to road structures 103 from the sensor data acquired by the radar 11 according to predetermined extraction conditions.

[0033] The extraction criteria may include a first condition that the reflection intensity is greater than or equal to a predetermined first judgment value. The first condition removes noise from the sensor data. Since the road structure 103 to be detected is relatively small, increasing the first judgment value will make detection difficult. Therefore, the first judgment value should be set to a value smaller than the reflection intensity value when radio waves are reflected from a vehicle. In addition, the first judgment value is set to a relatively small value in order to enable detection of road structures 103 located far from the vehicle 2.

[0034] The extraction criteria may include a second condition that the object's position falls within a predetermined height range. That is, the road structure detection unit 42 extracts sensor data that falls within a predetermined height range based on the sensor data. The second condition allows for the removal of data corresponding to manholes and steps on the road surface, as well as data corresponding to overhead guide signs positioned above the road surface, from the sensor data.

[0035] The extraction conditions may include a third condition: when a linear structure 104 extending horizontally in a straight line is detected based on sensor data, the object's position relative to the linear structure 104 is on the vehicle 2 side. In other words, the road structure detection unit 42 does not use sensor data on the opposite side of the vehicle 2 relative to the linear structure 104 to detect the road structure 103. The linear structure 104 is an object corresponding to a wall, guardrail, median strip, etc. In Figure 2, the linear structure 104 on the left is a guardrail, and the linear structure 104 on the right is a median strip. Data of objects on the opposite side of the vehicle 2 relative to the linear structure 104 is likely to be noise. Even if the data of objects on the opposite side of the vehicle 2 relative to the linear structure 104 is not noise, the vehicle 2 is unlikely to travel through that area, so there is little value in detecting the road structure 103 in that area. The third condition reduces the data capacity of the sensor data, thereby improving the efficiency of the processing of the control device's processor 31.

[0036] Figure 3 is an explanatory diagram illustrating an example of data extracted by the road structure detection unit 42 from sensor data based on the first to third conditions. The black circles 107 in Figure 3 represent the points where radio waves were reflected, i.e., the locations where objects exist. The extraction range is limited by the linear structures 104 on the left and right, thus reducing the data volume.

[0037] The road structure detection unit 42 detects stationary road structures 103 by comparing the data extracted based on the extraction conditions frame by frame. Specifically, the road structure detection unit 42 compares the position of each object included in the data frame by frame and recognizes those whose position has not changed as stationary road structures 103. Objects whose position has changed may be surrounding vehicles or people.

[0038] The obstacle detection unit 43 of the surrounding environment recognition unit 35 recognizes obstacles located around the vehicle 2 based on the detection results of the external environment recognition device 7. Obstacles detected by the obstacle detection unit 43 include, for example, guardrails, utility poles, surrounding vehicles, and people such as pedestrians. The road structure detection unit 42 may detect road structures 103 based on sensor data acquired by the radar 11. The road structure detection unit 42 may determine that objects with a reflectance intensity of 103 or higher than a predetermined second determination value are obstacles. The second determination value is set to a value greater than the first determination value. As a result, objects with a reflectance intensity higher than that of road structures 103 are recognized as obstacles.

[0039] The vehicle position recognition unit 36 ​​recognizes the position of vehicle 2. The vehicle position recognition unit 36 ​​may recognize the position of vehicle 2 based on the GNSS signal received by the GNSS receiver 16.

[0040] The driving control unit 37 drives the vehicle 2 along the driving lane 101. The driving control unit 37 performs lane keeping assist control and controls the steering device 5. In lane keeping assist control, the driving control unit 37 may set a target trajectory in the center of the driving lane 101 and control the steering device 5 so that the position of the vehicle 2 is on the target trajectory. Alternatively, in lane keeping assist control, the driving control unit 37 may control the steering device 5 so that the vehicle 2 steers towards the center of the lane as it approaches the left and right lane markings 102 of the driving lane 101.

[0041] When the driving control unit 37 detects a road structure 103 on the driving lane 101, it determines, based on map information, whether or not there is an alternative lane 105 adjacent to the driving lane 101, and if an alternative lane 105 exists, it controls the steering device 5 to guide the vehicle 2 to the alternative lane 105. As shown in Figure 3, when the road structure detection unit 42 detects a road structure 103 on the driving lane 101, the driving control unit 37 determines, based on map information stored in the memory 32, whether or not there is an alternative lane 105 adjacent to the driving lane 101. An alternative lane 105 adjacent to the driving lane 101 includes lanes that are adjacent to and run parallel to the driving lane 101, and lanes that branch off from the driving lane 101. In the example in Figure 3, the lane that is adjacent to and runs parallel to the driving lane 101 corresponds to the alternative lane 105.

[0042] If an alternative lane 105 exists, the driving control unit 37 may, for example, set a target trajectory in the center of the alternative lane 105 and control the steering device 5 so that the position of the vehicle 2 is located on the target trajectory in order to guide the vehicle 2 to the alternative lane 105. The center of the alternative lane 105 may be set based on map information or based on image data acquired by the camera 13. If an alternative lane 105 does not exist, the driving control unit 37 may control the propulsion device 3 and the braking device 4 to stop the vehicle 2.

[0043] Next, the driving control performed by the driving control device 1 will be explained using the flowchart in Figure 4, which shows the procedure of the driving control method. First, the driving control device 1 detects the driving lane 101 on which the vehicle 2 is traveling from the image information acquired by the camera 13 (ST1). The driving lane 101 is preferably detected by the lane detection unit 41 as described above.

[0044] Next, the driving control device 1 detects stationary road structures 103 on the road surface based on sensor data including the position of each object acquired by the radar 11 or lidar 12 (ST2). The road structures 103 may be detected by the road structure detection unit 42 as described above.

[0045] Next, the driving control device 1 determines whether or not a road structure 103 exists on the driving lane 101 (ST3). If no road structure 103 exists on 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).

[0046] If a road structure 103 exists on the driving lane 101 (ST3: Yes), the driving control device 1 determines, based on map information, whether or not there is an alternative lane 105 adjacent to the driving lane 101 (ST5).

[0047] If an alternative lane 105 exists (ST5: Yes), the driving control device 1 sets the target trajectory to be a trajectory that follows the center of the alternative lane 105 (ST6).

[0048] After the target trajectory is set in step ST4 or step ST6, the driving control device 1 controls the steering device 5 to make the vehicle 2 travel along the target trajectory (ST7). If there is no alternative lane 105 (ST5: No), the driving control device 1 controls the propulsion device 3 and braking device 4 to stop the vehicle 2 (ST8).

[0049] According to the above embodiment, the driving control device 1 can detect road structures 103 on the driving lane 101 and, if road structures 103 are present, can cause the vehicle 2 to change lanes to an alternative lane 105.

[0050] The driving control device 1 extracts sensor data acquired by the radar 11 using a first determination value set lower than a second determination value for detecting obstacles, in order to detect the road structure 103. This allows the driving control device 1 to detect the road structure 103, which is relatively small and difficult to detect, from the sensor data acquired by the radar 11. Using a first determination value set lower than the second determination value may increase the data size of the sensor data. However, the driving control device 1 does not use sensor data on the opposite side of the vehicle 2, using the linear structure 104 as a reference, to detect the road structure 103, thereby reducing the data size of the sensor data.

[0051] The embodiments are not limited to the above configuration and can be broadly modified. For example, the road structure detection unit 42 may use a lidar 12 instead of a radar 11 to detect road structures 103.

[0052] The above embodiments may also be described as follows:

[0053] One embodiment is a vehicle 2 driving control device 1, which includes a lane detection unit 41 that detects the driving lane 101 on which the vehicle 2 is driving from image information acquired by a camera 13, a road structure detection unit 42 that detects stationary road structures 103 on the road surface based on sensor data including the positions of each object acquired by a radar 11 or lidar 12, a vehicle position detection unit that detects the position of the vehicle 2, and a driving control unit 37 that drives the vehicle 2 along the driving lane 101. When the road structure 103 is detected on the driving lane 101, the driving control unit 37 determines, based on map information, whether or not there is an alternative lane 105 adjacent to the driving lane 101, and if the alternative lane 105 exists, controls the steering device 5 to guide the vehicle 2 to the alternative lane 105.

[0054] According to this embodiment, a driving control device 1 can be provided that can detect road structures 103 on the lane and perform a lane change.

[0055] In the above embodiment, the road structure detection unit 42 may detect the stationary road structure 103 by comparing the sensor data frame by frame.

[0056] According to this embodiment, the road structure detection unit 42 can detect stationary road structures 103 on the driving lane 101.

[0057] In the above embodiment, the road structure detection unit 42 may extract sensor data included in a predetermined height range based on the sensor data, and detect the road structure 103 based on the extracted sensor data.

[0058] According to this embodiment, it is possible to prevent structures such as manholes, uneven surfaces on the road, and overhead guide signs from being mistakenly identified as road structures 103.

[0059] In the above embodiment, the road structure detection unit 42 detects a linear structure 104 that extends in a straight line horizontally based on the sensor data, and does not need to use the sensor data on the opposite side of the vehicle 2 to detect the road structure 103 with respect to the linear structure 104.

[0060] According to this embodiment, the data capacity of the sensor data is reduced, and the efficiency of the control device's calculation processing is improved. Data from objects in the area opposite to the vehicle 2 with respect to the linear structure 104 is likely to be noise. Furthermore, even if the data is not noise, the vehicle 2 is unlikely to travel through that area, so there is little value in detecting the road structure 103 in that area.

[0061] Another embodiment is a computer-controlled method for driving a vehicle 2, which includes detecting a driving lane 101 on which the vehicle 2 is traveling from image information acquired by a camera 13, detecting stationary road structures 103 on the road surface based on sensor data including the positions of each object acquired by a radar 11 or lidar 12, detecting the position of the vehicle 2, driving the vehicle 2 along the driving lane 101, determining whether there is an alternative lane 105 adjacent to the driving lane 101 based on map information when the road structures 103 are detected on the driving lane 101, and controlling the steering device 5 to guide the vehicle 2 to the alternative lane 105 if the alternative lane 105 exists.

[0062] According to this embodiment, it is possible to provide a driving control method that can detect road structures 103 on the lane and perform lane changes.

[0063] Another embodiment is a control program for causing a computer to execute a driving control method for a vehicle 2, which causes the computer to detect the driving lane 101 on which the vehicle 2 is traveling from image information acquired by the camera 13, detect stationary road structures 103 on the road surface based on sensor data including the positions of each object acquired by the radar 11 or lidar 12, detect the position of the vehicle 2, cause the vehicle 2 to drive along the driving lane 101, and if the road structures 103 are detected on the driving lane 101, determine whether or not there is an alternative lane 105 adjacent to the driving lane 101 based on map information, and if the alternative lane 105 exists, control the steering device 5 to guide the vehicle 2 to the alternative lane 105.

[0064] According to this embodiment, it is possible to provide a control program for executing a driving control method that can detect road structures 103 on the lane and perform a lane change. [Explanation of symbols]

[0065] 1: Driving control device 2: Vehicles 3: Propulsion device 4: Braking device 5: Steering gear 7: External world recognition device 11: Radar 12: Rider 13: Camera 16: GNSS receiver 17: Operating device 31: Processor 32: Memory 35: Surrounding Environment Recognition Unit 36: Vehicle position recognition unit 37: Driving Control Unit 41: Lane detection unit 42: Road structure detection unit 43: Obstacle detection unit 101: Driving lane 102: Road markings 103: Road structures 104: Linear structure 105: Alternative lane

Claims

1. A vehicle driving control device, A lane detection unit that detects the lane in which the vehicle is traveling from image information acquired by a camera, A road structure detection unit that detects stationary road structures on the road surface based on sensor data including the position of each object acquired by radar or lidar, A vehicle position detection unit for detecting the position of the aforementioned vehicle, The vehicle has a driving control unit that causes the vehicle to travel along the driving lane, The aforementioned driving control unit, When the road structure is detected on the aforementioned driving lane, it is determined, based on map information, whether or not there is an alternative lane adjacent to the aforementioned driving lane. A driving control device that controls the steering device to guide the vehicle into the alternative lane when the alternative lane exists.

2. The road structure detection unit detects a stationary road structure by comparing the sensor data frame by frame, as described in claim 1.

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

4. The road structure detection unit detects a linear structure extending in a straight line horizontally based on the sensor data, and does not use the sensor data on the opposite side of the vehicle to detect the road structure, as described in claim 1.

5. A method for controlling the movement of a vehicle, which is performed by a computer, The lane in which the vehicle is traveling is detected from the image information acquired by the camera. Based on sensor data including the position of each object acquired by radar or lidar, stationary road structures on the road surface are detected. The position of the vehicle is detected, The vehicle is driven along the aforementioned lane. When the road structure is detected on the aforementioned driving lane, it is determined, based on map information, whether or not there is an alternative lane adjacent to the aforementioned driving lane. A driving control method that controls the steering device to guide the vehicle into the alternative lane when the alternative lane exists.

6. A control program that causes a computer to execute a vehicle driving control method, The camera uses image information to detect the lane in which the vehicle is traveling. Based on sensor data including the position of each object acquired by radar or lidar, stationary road structures on the road surface are detected. To detect the position of the aforementioned vehicle, The vehicle is driven along the aforementioned lane. When the road structure is detected on the aforementioned driving lane, the system determines, based on map information, whether or not there is an alternative lane adjacent to the aforementioned driving lane. A control program that controls the steering system to guide the vehicle into the alternative lane when the alternative lane exists.

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