Patent Publication Number: US-2022234572-A1

Title: Automated valet parking system

Description:
TECHNICAL FIELD 
     The present disclosure relates to an automated valet parking system. 
     CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims the benefit of priority from Japanese Patent Application No. 2021-009428, filed on. Jan. 25, 2021, the entire contents of which are incorporated herein by reference. 
     BACKGROUND 
     Japanese Unexamined Patent Publication No. 2020-131787 discloses a control device for causing a vehicle to autonomously travel to a target location. Instruction information generated based on obstacle information, vehicle information, and map information is transmitted to the vehicle. 
     SUMMARY 
     In this technical field, an in-vehicle external sensor of an autonomous driving vehicle traveling on a runway may recognize an object for recognizing an entrance of a target parking space facing the runway. An object recognition range in which an object is recognized with at least a certain accuracy using the external sensor is determined in advance based on specifications of the external sensor, the vehicle-mounted position, and the like. Therefore, there is a possibility that the object to be recognized is located outside the object recognition range, for example, on a wide runway. 
     An object of the present disclosure is to provide an automated valet parking system for ensuring object recognition for recognizing an entrance of a target parking space. 
     According to one aspect of the present disclosure, there is provided an automated valet parking system in which a parking lot management server that manages a parking lot gives an instruction to an autonomous driving vehicle in the parking lot to cause the autonomous driving vehicle to be automatically parked in a target parking space in the parking lot. The system includes a traveling coordinate acquisition unit configured to acquire information on a plurality of traveling coordinates arranged along a runway of the parking lot to an entrance of the target parking space based on a vehicle position of the autonomous driving vehicle, a position of the target parking space, and parking lot map information, and a trajectory generation unit configured to generate a trajectory of the autonomous driving vehicle based on the information on the traveling coordinates and a result of detection from an in-vehicle external sensor. The trajectory generation unit is configured to determine whether or not the entrance of the target parking space is recognizable based on an object recognition range that is a range in which an object is recognized with at least a certain accuracy using the external sensor and is a range based on a predetermined position of the autonomous driving vehicle, the information on the traveling coordinates, and the position of the target parking space, and generate the trajectory that brings the autonomous driving vehicle closer to the target parking space on the runway so that the object for recognizing the entrance of the target parking space is included in the object recognition range when it is determined that the entrance of the target parking space is not recognizable. 
     With the automated valet parking system according to one aspect of the present disclosure, whether or not the entrance of the target parking space can be recognized is determined based on the object recognition range, the information on the traveling coordinates, and the position of the target parking space. the trajectory that brings the autonomous driving vehicle closer to the target parking space on the runway is generated so that the object for recognizing the entrance of the target parking space is included in the object recognition range when the entrance of the target parking space is determined to be unrecognizable, for example, when there is a possibility that the object to be recognized is located outside the object recognition range. Thereby, it is possible to prevent the object to be recognized from being located outside the object recognition range. Therefore, it is possible to ensure the recognition of the object for recognizing the entrance of the target parking space. 
     In one embodiment, the traveling coordinates may include a first coordinate that is a coordinate constituting the trajectory and is located on the runway facing the target parking space, and the trajectory generation unit may generate the trajectory for bringing the autonomous driving vehicle closer to the target parking space on the runway in advance before the autonomous driving vehicle reaches the first coordinate. 
     In one embodiment, the traveling coordinates may include a first coordinate that is a coordinate constituting the trajectory and is located on the runway facing the target parking space, and a second coordinate that is a coordinate constituting the trajectory and is located behind the first coordinate by a predetermined number in an advancing direction of the autonomous driving vehicle, and the trajectory generation unit may generate the trajectory to bring the autonomous driving vehicle closer to the target parking space in a section ahead of the second coordinate. 
     With the automated valet parking system according to one aspect of the present disclosure, it is possible to ensure the recognition of the object for recognizing the entrance of the target parking space. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a plan view illustrating an example of a parking lot where automated valet parking is performed. 
         FIG. 2  is a block diagram illustrating an automated valet parking system according to an embodiment. 
         FIG. 3  is a block diagram illustrating an example of a hardware configuration of a parking lot management server. 
         FIG. 4  is a plan view illustrating an example of a case where an entrance of a target parking space is determined to be unrecognizable. 
         FIG. 5  is a plan view illustrating an example of a trajectory that brings an autonomous driving vehicle closer to the target parking space on a runway. 
         FIG. 6  is a plan view illustrating another example of a case where the entrance of the target parking space is determined to be unrecognizable. 
         FIG. 7  is a plan view illustrating another example of a trajectory that brings the autonomous driving vehicle closer to the target parking space on a runway. 
         FIG. 8  is a flowchart illustrating instruction processing of the parking lot management server. 
         FIG. 9  is a flowchart illustrating traveling trajectory generation processing of an autonomous driving ECU. 
         FIG. 10  is a flowchart illustrating a specific example of the traveling trajectory generation processing of  FIG. 9 . 
     
    
    
     DETAILED DESCRIPTION 
     Hereinafter, an embodiment of the present disclosure will be described with reference to the drawings. 
       FIG. 1  is a plan view illustrating an example of a parking lot where automated valet parking is performed. The automated valet parking is a service that causes a driverless autonomous driving vehicle  2 , after a user (occupant) has got out of the vehicle at a drop-off area in a parking lot [parking place], to travel along a target route according to an instruction from the parking lot side, and that automatically parks the vehicle in a target parking space in the parking lot. The target parking space is a parking space preset as a parking position of the autonomous driving vehicle  2 . The target route is a route in the parking lot where the autonomous driving vehicle  2  travels to reach the target parking space. The target route at the time of pick-up is a route on which the vehicle travels to reach a pick-up space to be described later. 
     The parking lot may be a parking lot dedicated to automated valet parking, or may also serve as a parking lot for general vehicles that are not subject to automated valet parking. A part of the parking lot for general vehicles may be used as an area dedicated to automated valet parking. In the present embodiment, a parking lot dedicated to automated valet parking will be used as an example for description. 
     As illustrated in  FIG. 1 , a parking lot  50  for automated valet parking includes a parking area  51 , a drop-off area  52 , a pick-up area  53 , and runways  54 . In the example of  FIG. 1 , the drop-off area  52  and the pick-up area  53  are provided separately, but they may be provided integrally. A position reference (for example, a marker) for the autonomous driving vehicle  2  to recognize the vehicle position may be installed on the runways  54 . 
     The parking area  51  is a place where parking spaces (parking frames)  61  in which the autonomous driving vehicle  2  is parked by the automated valet parking are formed. In  FIG. 1 , the plurality of parking spaces  61  are formed to be arranged in one direction (the width direction of the parked vehicle) as an example. The drop-off area  52  is provided near the exit and entrance of the parking lot  50 , and is a place where an occupant including a user gets out of the autonomous driving vehicle  2  before entering the parking space. The drop-off area  52  is formed with drop-off spaces  62  for the autonomous driving vehicle  2  to stop when the occupant gets out of the vehicle. The pick-up area  53  is provided near the exit and entrance of the parking lot  50 , and is a place where the occupant gets on the autonomous driving vehicle  2  that has been picked up. The pick-up area  53  is formed with pick-up spaces  63  where the autonomous driving vehicle  2  waits for the occupant to get on the vehicle. 
     [Configuration of Automated Valet Parking System] 
     Hereinafter, the configuration of the automated valet parking system  100  will be described with reference to the drawings.  FIG. 2  is a block diagram illustrating an automated valet parking system  100  according to an embodiment. The automated valet parking system (AVPS)  100  illustrated in  FIG. 2  is a system for performing automated valet parking of an autonomous driving vehicle  2  in a parking lot. In the automated valet parking system  100 , a parking lot management server  1  that manages the parking lot  50  gives an instruction to the autonomous driving vehicle  2  in the parking lot  50  to cause the autonomous driving vehicle  2  to be automatically parked in a target parking space in the parking lot  50 . In the following description, the autonomous driving vehicle  2  that is the target of automated parking may be referred to as a “target vehicle  2 X”. 
     In the automated valet parking system  100 , for example, after the target vehicle  2 X that has entered the parking lot  50  drops off the occupant in the drop-off space  62 , the automated valet parking is started by obtaining an instruction authority of the target vehicle  2 X. The automated valet parking system  100  causes the target vehicle  2 X to travel toward a target parking space in the parking area  51 , and parks the target vehicle  2 X in a target parking space. The automated valet parking system  100  causes the target vehicle  2 X that is parked to travel toward the pick-up area  53  in response to a pick-up request, and causes the target vehicle  2 X to wait for the occupant to arrive in the pick-up space  63 . 
     The automated valet parking system  100  herein is, as an example, configured to execute “autonomous traveling control” for causing the autonomous driving vehicle  2  to autonomously drive to an entrance of the target parking space along the runway  54  and “automated parking control” for causing the autonomous driving vehicle  2  that has reached the entrance of the target parking space to be automatically parked in the target parking space. The autonomous traveling control is performed by an autonomous driving electric control unit (ECU)  20  mounted on the autonomous driving vehicle  2  based on traveling map information transmitted from the parking lot management server  1  to the target vehicle  2 X. 
     As illustrated in  FIG. 2 , the automated valet parking system  100  includes the parking lot management server  1 . The parking lot management server  1  is a server for managing the parking lot and functions as a control center. 
     The parking lot management server  1  is configured to communicate with the autonomous driving vehicle  2 . The parking lot management server  1  may be configured to communicate with a user frontend  3 . The details of the autonomous driving vehicle  2  and the user frontend  3  will be described later. The parking lot management server  1  may be provided in the parking lot or may be provided in a facility away from the parking lot. The parking lot management server  1  may include a plurality of computers provided at different places. The automated valet parking system  100  does not necessarily include the user frontend  3 . 
     The parking lot management server  1  is connected to a parking lot sensor  4  and a parking lot map database  5 . The parking lot sensor  4  is a parking lot infrastructure sensor for recognizing the status in the parking lot  50 . The parking lot sensor  4  includes a fixed camera that captures an obstacle present in the parking lot  50 . Examples of obstacles include vehicles other than the target vehicle  2 X, pillars of the parking lot  50 , gates of the parking lot  50 , walls of the parking lot  50 , poles, safety cones, falling articles on the runway  54 , and the like. The fixed camera may be installed on the ceiling or wall of the parking lot  50 . The fixed camera transmits the captured image to the parking lot management server  1 . 
     The parking lot sensor  4  may include an empty vehicle sensor for detecting whether or not a parked vehicle is present in each parking space (whether each parking space is occupied or empty). As the empty vehicle sensor, a sensor having a known configuration can be used. The above-mentioned fixed camera may be used as an empty vehicle sensor. 
     The parking lot map database  5  is a database that stores parking lot map information. The parking lot map information includes position information on the parking space in the parking lot  50 , position information on the drop-off space, position information on the pick-up space, and information on the runway  54  in the parking lot  50 . The parking lot map information includes the position information on the object used for recognizing the vehicle position of the autonomous driving vehicle  2 . The parking lot map information may include position information on a driving boundary used for the autonomous driving of the autonomous driving vehicle  2 . 
     The object means an article serving as a reference of a relative position for recognizing the position of the autonomous driving vehicle  2  in the parking lot  50 . As the object, the article provided in the parking lot  50  can be used. The object may divide the parking space  61 . As the object that divides the parking space  61 , for example, at least one of a lane marking that divides the parking space  61 , a pole that divides the parking space  61 , a road stud that divides the parking space  61 , a pillar of the parking lot  50 , a wall of the parking lot  50 , a safety cone that divides the parking space  61 , and the like is used. Position information on the object detected by an external sensor  22  described later is used, in addition to the position information on the object included in the parking lot map information, or instead of the position information on the object included in the parking lot map information, in order to execute automated parking with high accuracy. 
     The driving boundary means an object that can define a travelable range when the autonomous driving vehicle  2  travels in autonomous driving. As the driving boundary, a position on the object fixedly provided in the parking lot  50  can be used. As the driving boundary, for example, at least one of a predetermined position (for example, an apex) on the surface of a pillar of the parking lot  50 , a predetermined position on a wall surface of the parking lot  50 , an installation position of a pole, an installation position of a safety cone, an installation position of a road stud, and the like is used. 
     Further, the parking lot map information may include position information on a plurality of nodes  64  preset corresponding to a plurality of runways  54  in the parking lot  50 , a portion where the runway  54  curves, and the radius of curvature thereof. The position information on the node  64  can be, for example, coordinates on a two-dimensional map coordinate system. The two-dimensional coordinate system may be, for example, an X axis and a Y axis that are orthogonal to each other along the horizontal plane with any corner of the parking lot  50  as the origin. A Z axis orthogonal to the X axis and the Y axis may be defined, and the Z-coordinates may correspond to the first floor, the second floor, and the like of a multi-story car park. 
     In  FIG. 1 , a plurality of nodes  64  preset corresponding to a plurality of runways  54  in the parking lot  50  are illustrated by circles. As an example, some of the plurality of nodes  64  are arranged apart from one another at predetermined intervals on an imaginary line extending along the plurality of runways  54  in the parking lot  50 . In the example of  FIG. 1 , an imaginary line extending along the plurality of runways  54  in the parking lot  50  is indicated by a one-dot chain line. The predetermined interval does not necessarily have to be constant. In the lane width direction of the runway  54 , the plurality of nodes  64  are located near the center of the runway  54  in the lane width direction, for example. 
     For example, in a straight-line section of the runway  54 , a pair of nodes  64  are set at end points (start point and ending point) of the straight-line section. The nodes  64  may be further set in the section sandwiched between the end points of the straight-line section of the runway  54 . The start point and the ending point of the curve section of the runway  54  are defined by the nodes  64  located at the end points on the curve section side of the end points of the straight-line section sandwiching the curve section. These nodes  64  are used as traveling coordinates (described later) that constitute a traveling map for the autonomous driving vehicle  2  to autonomously drive along the runway  54 . The node located in front of the parking space  61  may be given a type of, for example, “in front of the parking space”. 
     The node  64  may be set at the entrance of each parking space  61  if an entrance of each parking space  61  faces the runway  54 . In the example of  FIG. 1 , the node  64  is set on the front frame line corresponding to the entrance of the parking space  61 . These nodes may be used when the autonomous driving vehicle  2  performs the automated parking control to the target parking space  61 . The nodes may be further set around the parking space  61 . 
     A hardware configuration of the parking lot management server  1  will be described.  FIG. 3  is a block diagram illustrating an example of a hardware configuration of the parking lot management server. As illustrated in  FIG. 3 , the parking lot management server  1  is configured as a general computer including a processor  40 , a memory  41 , a storage  42 , a communication interface  43 , and a user interface  44 . 
     The processor  40  operates various operating systems to control the parking lot management server  1 . The processor  40  is an arithmetic logic unit such as a central processing unit (CPU) including a control device, an arithmetic device, a register, and the like. The processor  40  centrally controls the memory  41 , the storage  42 , the communication interface  43 , and the user interface  44 . The memory  41  is a recording medium such as a read only memory (ROM), and a random access memory (RAM). The storage  42  is a recording medium such as a hard disk drive (HDD). 
     The communication interface  43  is a communication device for performing wireless communication through a network. As the communication interface  43 , a network device, a network controller, a network card, or the like can be used. The parking lot management server  1  communicates with the autonomous driving vehicle  2  and the user frontend  3  using the communication interface  43 . The user interface  44  is an input/output unit of the parking lot management server  1  for an administrator of the parking lot management server  1  or the like. The user interface  44  includes an output device such as a display and a speaker, and an input device such as a touch panel. 
     Next, a functional configuration of the parking lot management server  1  will be described. As illustrated in  FIG. 2 , the parking lot management server  1  includes a vehicle information acquisition unit  11 , a traveling map information acquisition unit (traveling coordinate acquisition unit)  12 , and a vehicle instruction unit  13 . 
     The vehicle information acquisition unit  11  acquires vehicle information on the autonomous driving vehicle  2  through communication with the autonomous driving vehicle  2 . The vehicle information includes identification information on the autonomous driving vehicle  2 , and vehicle position information on the autonomous driving vehicle  2  and information on the target parking space in the parking lot. The vehicle position information is information about the vehicle position which is the position of the autonomous driving vehicle  2  on the parking lot map. The identification information may be any information as long as it can specify each of the autonomous driving vehicles  2 . The identification information may be an identification number (ID number), a vehicle number, a reservation number for automated valet parking, or the like. 
     The vehicle information includes an object recognition range (details will be described later) of an external sensor  22  of the autonomous driving vehicle  2 . The vehicle information may include the vehicle type of the autonomous driving vehicle  2 . The vehicle information may include vehicle body information such as a turning radius, a total length, a vehicle width, and a total height of the autonomous driving vehicle  2 . The vehicle information may include information representing the vehicle class of the autonomous driving vehicle  2  as vehicle body information. 
     The vehicle information may include recognition results of a traveling state of the autonomous driving vehicle  2  and an external environment. In addition, the vehicle information may include a vehicle number in addition to the identification information. Information regarding an autonomous driving function may include version information on the autonomous driving. The vehicle information may include vehicle entrance reservation information such as a vehicle entrance reservation time, or may include a scheduled pick-up time. Information regarding an autonomous driving function of the autonomous driving vehicle  2  may be included. 
     The traveling map information acquisition unit  12  acquires traveling map information based on, for example, the vehicle position of the target vehicle  2 X, the position of the target parking space, the map information on the parking lot  50 , and the status of the parking lot  50  before the start of the autonomous traveling control of the target vehicle  2 X. The traveling map information is information regarding a traveling map. The traveling map means a traveling path on the parking lot map for the target vehicle  2 X to autonomously travel along the runway  54  from a starting location (vehicle position) to a destination location (target parking space) in the parking lot  50 . 
     The traveling map is composed of a plurality of traveling coordinates. As the positions of the plurality of traveling coordinates, for example, the positions of the plurality of nodes  64  arranged along the runway  54  from the vehicle position of the target vehicle  2 X to the entrance of the target parking space can be used. 
     Information on the traveling coordinates can include information on a first coordinate and information on a second coordinate, in addition to the position information on the parking lot map of the plurality of traveling coordinates. The first coordinate is a traveling coordinate located on the runway facing the target parking space. The second coordinate is a traveling coordinate located behind the first coordinate by a predetermined number in an advancing direction of the autonomous driving vehicle  2 . The advancing direction is a direction in which the target vehicle  2 X advances when the autonomous driving vehicle  2  autonomously travels as the target vehicle  2 X. The “behind” means a direction opposite to the advancing direction. The predetermined number is not particularly limited, but may be, for example, one. The predetermined number may be an integer of two or more. The number can be selected for the predetermined number, for example, according to the appropriate path change timing in consideration of the width alignment amount and the expected behavior of the target vehicle  2 X, when the target vehicle  2   x  is aligned closer to the target parking space. 
     In the example of  FIG. 1 , among the traveling coordinates  65 ,  66 , and  67  located on the runway  54  facing a target parking space  61 T, the traveling coordinate  65  closest to the target parking space  61 T can be set as the first coordinate. Further, in the example of  FIG. 1 , among the traveling coordinates  65 ,  66 , and  67  located on the runway  54  facing the target parking space  61 T, the traveling coordinate  66  located behind the first coordinate by one can be set as the second coordinate. The plurality of traveling coordinates  65 ,  66 , and  67  included in the traveling map constitute a trajectory generated by a traveling trajectory generation unit  34  to be described later. 
     The traveling map information acquisition unit  12  acquires information on a plurality of traveling coordinates arranged along the runway  54  of the parking lot  50  to the entrance of the target parking space based on the vehicle position of the autonomous driving vehicle  2 , the position of the target parking space, and the map information on the parking lot  50 . The traveling map information acquisition unit  12  acquires a traveling path obtained by connecting a plurality of acquired traveling coordinates to each other as a traveling map. 
     The vehicle instruction unit  13  instructs the autonomous driving vehicle  2  to perform automated valet parking. The vehicle instruction unit  13  uses the traveling map acquired by the traveling map information acquisition unit  12  as a target route for the target vehicle  2 X to reach a destination location such as a target parking space. The vehicle instruction unit  13  distributes the traveling map information acquired by the traveling map information acquisition unit  12 , the target vehicle speed of the target vehicle  2 X, and the like to the target vehicle  2 X as traveling instruction information. 
     Subsequently, the autonomous driving vehicle  2  and the user frontend  3  that communicate with the parking lot management server  1  will be described. 
     As illustrated in  FIG. 2 , the autonomous driving vehicle  2  includes an autonomous driving ECU  20  as an example. The autonomous driving ECU  20  is an electronic control unit including a CPU, a ROM, a RANI, and the like. In the autonomous driving ECU  20 , for example, a program recorded in the ROM is loaded into the RANI, and various functions are implemented by the CPU executing the program loaded into the RANI. The autonomous driving ECU  20  may include a plurality of electronic units. 
     The autonomous driving ECU  20  is connected to a communication unit  21 , an external sensor  22 , an internal sensor  23 , and an actuator  24 . 
     The communication unit  21  is a communication device that controls wireless communication with the outside of the autonomous driving vehicle  2 . The communication unit  21  transmits and receives various types of information through communication with the parking lot management server  1 . The communication unit  21  transmits, for example, vehicle information to the parking lot management server  1  and acquires information (for example, traveling map information) needed for automated valet parking from the parking lot management server  1 . In addition, the communication unit  21  may perform communication with the user frontend  3  associated with the autonomous driving vehicle  2 . 
     The external sensor  22  is an in-vehicle sensor that detects an external environment of the autonomous driving vehicle  2 . The external sensor  22  includes at least a front camera. The front camera is an imaging device that captures an image of an external environment of the autonomous driving vehicle  2 . The front camera is provided, for example, behind a windshield of the autonomous driving vehicle  2  and captures an image in front of the vehicle. The front camera transmits imaging information regarding the external environment of the autonomous driving vehicle  2  to the autonomous driving ECU  20 . The front camera may be a monocular front camera or a stereo front camera. A plurality of front cameras may be provided, and in addition to the front of the autonomous driving vehicle  2 , the right and left sides and the rear may be imaged. 
     The external sensor  22  may include a radar sensor. The radar sensor is a detection device that detects an object around the autonomous driving vehicle  2  using radio waves (for example, millimeter waves) or light. The radar sensor includes, for example, a millimeter wave radar or a light detection and ranging (LiDAR). The radar sensor transmits radio waves or light to the vicinity of the autonomous driving vehicle  2  and detects the object by receiving the radio waves or light reflected by the object. The radar sensor transmits the detected object information to the autonomous driving ECU  20 . In addition, the external sensor  22  may include a sonar sensor that detects a sound outside the autonomous driving vehicle  2 . 
     The external sensor  22  may include a side camera. The side camera is an imaging device that captures an image of an external environment on one or more sides of the autonomous driving vehicle  2 . The side cameras are provided, for example, on the lower end sides of right and left door mirrors of the autonomous driving vehicle  2  to face downward, and captures an image of a predetermined range extending in the front-rear direction on the side of the vehicle. The captured image of a predetermined range is used for recognizing the object used for recognizing the vehicle position of the autonomous driving vehicle  2 . The captured image of a predetermined range may be used for other purposes such as a panoramic view monitor function. The side camera transmits imaging information regarding the external environment on the side of the autonomous driving vehicle  2  to the autonomous driving ECU  20 . 
     An object recognition range is predetermined for the external sensor  22 . The object recognition range is a range in which an object is recognized with at least a certain accuracy using the external sensor  22 . The “object recognition using the external sensor  22 ” means recognizing an object for recognizing the entrance of the target parking space using the external sensor  22 . As the object for recognizing the entrance of the target parking space, at least one of a lane marking that divides the parking space  61 , a pole that divides the parking space  61 , a road stud that divides the parking space  61 , a pillar of the parking lot  50 , a wall of the parking lot  50 , a safety cone that divides the parking space  61 , and the like is used. The object for recognizing the entrance of the target parking space may be the same as the object that divides the parking space  61 , and may be used as a basis for recognizing the vehicle position of the autonomous driving vehicle  2 . The object recognition range may be defined for the sensor used for recognizing the entrance of the target parking space in the external sensors  22 . 
     The object recognition range is defined as, for example, a predetermined range extending around the autonomous driving vehicle  2  based on a predetermined position of the autonomous driving vehicle  2  (for example, the vehicle center of the autonomous driving vehicle  2 ) in plan view. Such a predetermined range can be determined based on the specifications (vehicle width and total length) of the autonomous driving vehicle  2 , the mounting position of the external sensor  22  in the autonomous driving vehicle  2 , and the range in which the object can be recognized from the mounting position with at least a certain accuracy using the external sensor  22 . As an example, when the external sensor  22  is a side camera, a rectangular area of about 5 m to 6 m in the vehicle width direction and about 8 m in the vehicle front-rear direction can be used as an object recognition range SR in vehicle plan view (see  FIGS. 4 to 7 ). The object recognition range is not limited to this example. 
     The internal sensor  23  is an in-vehicle sensor that detects a traveling state of the autonomous driving vehicle  2 . The internal sensor  23  includes a vehicle speed sensor, an acceleration sensor, and a yaw rate sensor. The vehicle speed sensor is a detector that detects the speed of the autonomous driving vehicle  2 . As the vehicle speed sensor, wheel speed sensors that are provided for wheels of the autonomous driving vehicle  2  or for drive shafts that rotate integrally with the wheels and that detect rotation speeds of the respective wheels can be used. The vehicle speed sensor transmits the detected vehicle speed information (wheel speed information) to the autonomous driving ECU  20 . 
     The acceleration sensor is a detector that detects the acceleration of the autonomous driving vehicle  2 . The acceleration sensor includes, for example, a longitudinal acceleration sensor that detects the longitudinal acceleration of the autonomous driving vehicle  2 . The acceleration sensor may include a lateral acceleration sensor that detects the lateral acceleration of the autonomous driving vehicle  2 . The acceleration sensor transmits, for example, acceleration information of the autonomous driving vehicle  2  to the autonomous driving ECU  20 . The yaw rate sensor is a detector that detects a yaw rate (rotational angular velocity) of the center of gravity of the autonomous driving vehicle  2  around a vertical axis. As the yaw rate sensor, for example, a gyro sensor can be used. The yaw rate sensor transmits the detected yaw rate information of the autonomous driving vehicle  2  to the autonomous driving ECU  20 . 
     The actuator  24  is a device used for controlling the autonomous driving vehicle  2 . The actuator  24  includes at least a drive actuator, a brake actuator, and a steering actuator. The drive actuator controls a supply amount of air to the engine (throttle opening degree) according to a control signal from the autonomous driving ECU  20  to control a driving force of the autonomous driving vehicle  2 . When the autonomous driving vehicle  2  is a hybrid vehicle, the control signal from the autonomous driving ECU  20  is input to a motor as a power source in addition to the supply amount of air to the engine, so that the driving force of the autonomous driving vehicle  2  is controlled. When the autonomous driving vehicle  2  is an electric vehicle, the control signal from the autonomous driving ECU  20  is input to a motor as a power source, so that the driving force of the autonomous driving vehicle  2  is controlled. The motor as the power source in these cases constitutes the actuator  24 . 
     The brake actuator controls a brake system according to the control signal from the autonomous driving ECU  20  to control a braking force applied to the wheels of the autonomous driving vehicle  2 . As the brake system, for example, a hydraulic brake system can be used. The steering actuator controls driving of an assist motor for controlling a steering torque in an electric power steering system according to the control signal from the autonomous driving ECU  20 . Thereby, the steering actuator controls the steering torque of the autonomous driving vehicle  2 . 
     Next, an example of a functional configuration of the autonomous driving ECU  20  will be described. The autonomous driving ECU  20  includes an external environment recognition unit  31 , a traveling state recognition unit  32 , a vehicle position recognition unit  33 , a traveling trajectory generation unit (trajectory generation unit)  34 , a parking trajectory generation unit  35 , and a vehicle controller  36 . 
     The external environment recognition unit  31  recognizes the external environment of the autonomous driving vehicle  2  based on the result of detection from the external sensor  22 . The result of detection from the external sensor  22  includes an image captured by the side camera. The result of detection from the external sensor  22  may include at least one of an image captured by the front camera and object information detected by the radar sensor. 
     The external environment includes the position information on the object detected by the external sensor  22 . The object herein includes an object for recognizing the entrance of the target parking space facing the runway  54 . The external environment recognition unit  31  recognizes an object for recognizing the entrance of the target parking space by white line recognition, pattern matching, or the like. The object detected by the external sensor  22  may be an article whose position information is included in the parking lot map information. 
     The external environment includes a relative position of surrounding obstacles with respect to the autonomous driving vehicle  2 . The external environment may include a relative speed and a moving direction of surrounding obstacles with respect to the autonomous driving vehicle  2 . Examples of such obstacles include vehicles other than the target vehicle  2 X, gates of the parking lot, falling articles on the runway  54 , and the like. The external environment recognition unit  31  recognizes an article that becomes an obstacle by pattern matching or the like. 
     The traveling state recognition unit  32  recognizes the traveling state of the autonomous driving vehicle  2  based on the result of detection from the internal sensor  23 . The traveling state includes the vehicle speed of the autonomous driving vehicle  2 , the acceleration of the autonomous driving vehicle  2 , and the yaw rate of the autonomous driving vehicle  2 . Specifically, the traveling state recognition unit  32  recognizes the vehicle speed of the autonomous driving vehicle  2  based on the vehicle speed information of the vehicle speed sensor. The traveling state recognition unit  32  recognizes the acceleration of the autonomous driving vehicle  2  based on the vehicle speed information of the acceleration sensor. The traveling state recognition unit  32  recognizes the direction of the autonomous driving vehicle  2  based on the yaw rate information of the yaw rate sensor. The traveling state recognition unit  32  may recognize vehicle information on the target vehicle  2 X (vehicle type of the autonomous driving vehicle  2 , and vehicle body information such as turning radius, total length, total height, and vehicle width of the autonomous driving vehicle  2 ) as the vehicle characteristics of the host vehicle. These pieces of vehicle information may be stored in advance in the ROM of the autonomous driving ECU  20 . 
     The vehicle position recognition unit  33  recognizes the vehicle position of the autonomous driving vehicle  2  based on the external environment recognized by the external environment recognition unit  31 . The vehicle position recognition unit  33  recognizes the vehicle position of the autonomous driving vehicle  2  based on the relative position of the object with respect to the autonomous driving vehicle  2  recognized by the external environment recognition unit  31 . Such a vehicle position recognized by using the external sensor  22  is used in the automated parking control of the autonomous driving vehicle  2 . 
     The vehicle position recognition unit  33  may recognize the vehicle position of the autonomous driving vehicle  2  based further on the parking lot map information acquired from the parking lot management server  1  through the communication unit  21 . The vehicle position recognition unit  33  may recognize the vehicle position of the autonomous driving vehicle  2  by further using the position information on the object in the parking lot included in the parking lot map information, for example. The vehicle position recognition unit  33  may recognize the position of the autonomous driving vehicle  2  by dead reckoning based further on the result of detection from the internal sensor  23 . In addition, the vehicle position recognition unit  33  may recognize the position of the autonomous driving vehicle  2  by further communicating with a beacon provided in the parking lot. Such a vehicle position recognized by using the parking lot map information may be used in the autonomous traveling control of the autonomous driving vehicle  2 . 
     The traveling trajectory generation unit  34  generates a trajectory of the autonomous driving vehicle  2  based on the information on the traveling coordinates and the result of detection from the in-vehicle external sensor  22 . The traveling trajectory generation unit  34  generates a trajectory of the target vehicle  2 X based on, for example, the traveling map (target route), the position of the target vehicle  2 X, the external environment of the target vehicle  2 X, and the traveling state of the target vehicle  2 X. The trajectory corresponds to a traveling plan for autonomous driving. The trajectory includes a path along which the vehicle travels by autonomous driving and a vehicle speed plan in autonomous driving. 
     The traveling trajectory generation unit  34  generates a path of the target vehicle  2 X along a plurality of traveling coordinates from the starting location to the destination location based on the distributed traveling map information. For example, the traveling trajectory generation unit  34  may sequentially generate paths from the current vehicle position of the target vehicle  2 X to the traveling coordinates located several (for example, three) points ahead of the plurality of traveling coordinates included in the traveling map. The trajectory may include information on a deflection angle that determines the posture of the target vehicle  2 X in the yaw direction when passing through each traveling coordinate (each node  64 ) included in the traveling map. The deflection angle is, for example, an angle in which the direction parallel to the positive direction of the X axis is 0 deg and the counterclockwise direction is positive. The trajectory may include information such as the order in which the target vehicle  2 X passes through each traveling coordinate included in the traveling map and the time when the target vehicle  2 X can pass. 
     The traveling trajectory generation unit  34  determines whether or not the entrance of the target parking space  61 T can be recognized based on the object recognition range SR of the external sensor  22 , the information on the traveling coordinate, and the position of the target parking space  61 T. For example, assuming that the target vehicle  2 X is located in front of the target parking space  61 T, the traveling trajectory generation unit  34  determines whether or not an object for recognizing the entrance of the target parking space is included in the object recognition range SR of the external sensor  22 . 
     Specifically, assuming that the position of the vehicle center of the target vehicle  2 X coincides with the position of the first coordinate, the traveling trajectory generation unit  34  determines whether or not the entrance of the target parking space  61 T can be recognized by determining whether or not the object is included in a range of a distance from the vehicle center of the target vehicle  2 X in which the object is recognized with at least a certain accuracy using the external sensor  22  in the direction toward the position of the object for recognizing the entrance of the target parking space when viewed from the vehicle center of the target vehicle  2 X. 
     The determination of whether or not the entrance of the target parking space  61 T can be recognized is executed, for example, before the automated valet parking is started. Alternatively, the determination of whether or not the entrance of the target parking space  61 T can be recognized may be executed after the automated valet parking is started and before the target vehicle  2 X reaches the second coordinate. In this case, the determination may be executed together with sequentially generating paths from the current vehicle position of the target vehicle  2 X to the traveling coordinates located several points ahead. The determination of whether or not the entrance of the target parking space  61 T can be recognized is executed at least before the target vehicle  2 X reaches the first coordinate. That is, the traveling trajectory generation unit  34  generates in advance a trajectory for bringing the autonomous driving vehicle  2  closer to the target parking space  61 T on the runway  54  before the autonomous driving vehicle  2  reaches the first coordinate. 
       FIG. 4  is a plan view illustrating an example of a case where an entrance of a target parking space is determined to be unrecognizable.  FIG. 4  is a plan view on the assumption that the target vehicle  2 X autonomously travels along a trajectory T 1  to a coordinate (first coordinate)  65 A located on a runway RW 1  facing a target parking space  61 A in order to automatically park the target vehicle  2 X in the target parking space  61 A located on the left side in the advancing direction of the target vehicle  2 X. The trajectory T 1  is a trajectory generated as a path extending along coordinates  65 A,  66 A,  67 A, and  68 A. The coordinates  65 A,  66 A,  67 A, and  68 A are arranged along the runway RW 1 . It is assumed that the coordinate  66 A is the second coordinate. 
     In the example of  FIG. 4 , the position of the vehicle center of the target vehicle  2 X coincides with the position of the coordinate  65 A. In order to recognize an entrance of the target parking space  61 A located on the left side of the target vehicle  2 X, a lane marking L 2  extending to the left side of the target vehicle  2 X is set as the object to be recognized by the external sensor  22 . The runway RW 1  is a straight-line section extending between a pair of lane markings L 1  and L 2 . 
     In the example of  FIG. 4 , the traveling trajectory generation unit  34  determines whether or not the lane marking L 2  is included in a range of a distance D 2  in the direction toward the position of the lane marking L 2  (on the left side in the advancing direction) for recognizing the entrance of the target parking space  61 A when viewed from the vehicle center (coordinate  65 A) of the target vehicle  2 X. The distance D 2  is a distance from the vehicle center of the target vehicle  2 X in which the object is recognized with at least a certain accuracy using the external sensor  22  on the left side in the advancing direction. The distance D 1  is a distance from the vehicle center of the target vehicle  2 X to the lane marking L 2  on the left side in the advancing direction. The distance D 1  can be calculated based on vehicle position information on the target vehicle  2 X and parking lot map information (position information on the lane marking L 2 ). 
     In  FIG. 4 , since the lane marking L 2  is not included in the range of the distance D 2 , the traveling trajectory generation unit  34  determines that the entrance of the target parking space  61 A cannot be recognized. When it is determined that the entrance of the target parking space  61 A cannot be recognized, the traveling trajectory generation unit  34  generates a trajectory T 2  that brings the target vehicle  2 X closer to the target parking space  61 A on the runway RW 1  so that the lane marking L 2  for recognizing the entrance of the target parking space  61 A is included in the object recognition range SR (see  FIG. 5 ). The trajectory T 2  is a traveling trajectory having a path that brings the target vehicle  2 X closer to the target parking space  61 A on the runway RW 1  as compared with the trajectory T 1 . 
       FIG. 5  is a plan view illustrating an example of a trajectory that brings the autonomous driving vehicle closer to the target parking space on a runway.  FIG. 5  is different from the situation of  FIG. 4  in that a trajectory T 2  that brings the target vehicle  2 X closer to the target parking space  61 A is generated in a section from the coordinate  66 A to a coordinate  69 A. That is, the traveling trajectory generation unit  34  generates a trajectory T 2  to bring the autonomous driving vehicle  2  closer to the target parking space  61 A in a section ahead of the coordinates  66 A (second coordinate). 
     The coordinate  69 A of the trajectory T 2  is moved to the left in the advancing direction of the target vehicle  2 X by a distance D 3  as compared with the coordinate  65 A of the trajectory T 1 . The distance D 3  corresponds to a distance obtained by subtracting the distance D 2  from the distance D 1  in the example of  FIG. 4 . In the example of  FIG. 4 , since the lane marking L 2  is not included in the range of the distance D 2 , the distance D 3  is a positive value. By moving the trajectory T 2  to the left by the distance D 3 , the lane marking L 2  can be included in the range of the distance D 2  as illustrated in  FIG. 5 . The coordinate  69 A of the trajectory T 2  may be newly set as a coordinate different from the coordinate  65 A of the trajectory T 1 , or may be handled to move the coordinate  65 A of the trajectory T 1  instead of being newly set. 
     In the examples of  FIGS. 4 and 5 , although the target parking space  61 A extends at a right angle to the advancing direction of the target vehicle  2 X, the parking space  61  may extend in a direction diagonally intersecting the advancing direction of the target vehicle  2 X. The generation of the trajectory T 2  as described above is also effective for such a parking spaces. 
     Another specific example will be described.  FIG. 6  is a plan view illustrating another example of a case where the entrance of the target parking space is determined to be unrecognizable.  FIG. 6  is a plan view on the assumption that the target vehicle  2 X autonomously travels along a trajectory T 3  to a coordinate (first coordinate)  65 B located on a runway RW 3  facing a target parking space  61 B in order to automatically park the target vehicle  2 X in the target parking space  61 B located in front of the advancing direction of the target vehicle  2 X. The trajectory T 3  is a trajectory generated as a path extending along coordinates  65 B,  66 B,  67 B, and  68 B. The coordinates  65 B,  66 B,  67 B, and  68 B are arranged along the runway RW 2 . That is, the runways RW 2  and RW 3  in  FIG. 6  intersect each other as a T-junction. It is assumed that the coordinate  66 B is the second coordinate. 
     In the example of  FIG. 6 , the position of the vehicle center of the target vehicle  2 X coincides with the position of the coordinate  65 B. In order to recognize an entrance of the target parking space  61 B located in front of the target vehicle  2 X, a lane marking L 3  extending in front of the target vehicle  2 X is set as the object to be recognized by the external sensor  22 . The runway RW 3  extends along the lane marking L 3 . 
     In the example of  FIG. 6 , the traveling trajectory generation unit  34  determines whether or not the lane marking L 3  is included in a range of a distance D 5  in the direction toward the position of the lane marking L 3  (in front of the advancing direction) for recognizing the entrance of the target parking space  61 B when viewed from the vehicle center (coordinate  65 B) of the target vehicle  2 X. The distance D 5  is a distance from the vehicle center of the target vehicle  2 X in which the object is recognized with at least a certain accuracy using the external sensor  22  in front of the advancing direction. A distance D 4  is a distance from the vehicle center of the target vehicle  2 X to the lane marking L 3 . The distance D 4  can be calculated based on vehicle position information on the target vehicle  2 X and parking lot map information (position information on the lane marking L 3 ) in front of the advancing direction. 
     In  FIG. 6 , since the lane marking L 3  is not included in the range of the distance D 5 , the traveling trajectory generation unit  34  determines that the entrance of the target parking space  61 B cannot be recognized. When it is determined that the entrance of the target parking space  61 B cannot be recognized, the traveling trajectory generation unit  34  generates a trajectory T 4  that brings the target vehicle  2 X closer to the target parking space  61 B on the runway RW 3  so that the lane marking L 3  for recognizing the entrance of the target parking space  61 B is included in the object recognition range SR (see  FIG. 7 ). The trajectory T 4  is a traveling trajectory having a path that brings the target vehicle  2 X closer to the target parking space  61 B on the runway RW 3  as compared with the trajectory T 3 . 
       FIG. 7  is a plan view illustrating another example of a trajectory that brings the autonomous driving vehicle closer to the target parking space on a runway.  FIG. 7  is different from the situation of  FIG. 6  in that a trajectory T 4  that brings the target vehicle  2 X closer to the target parking space  61 B is generated in a section from the coordinate  66 B to a coordinate  69 B. That is, the traveling trajectory generation unit  34  generates a trajectory T 4  to bring the autonomous driving vehicle  2  closer to the target parking space  61 B in a section ahead of the coordinates  66 B (second coordinate). 
     The coordinate  69 B of the trajectory T 4  is moved forward in the advancing direction of the target vehicle  2 X by a distance D 6  as compared with the coordinate  65 B of the trajectory T 3 . The distance D 6  corresponds to a distance obtained by subtracting the distance D 5  from the distance D 4  in the example of  FIG. 6 . In the example of  FIG. 6 , since the lane marking L 3  is not included in the range of the distance D 5 , the distance D 6  is a positive value. By moving (extending) the trajectory T 4  forward by the distance D 6 , the lane marking L 3  can be included in the range of the distance D 5 . The coordinate  69 B of the trajectory T 4  may be newly set as a coordinate different from the coordinate  65 B of the trajectory T 3 , or may be handled to move the coordinate  65 B of the trajectory T 3  instead of being newly set. 
     In the examples of  FIGS. 6 and 7 , the target parking space  61 B may be located in a dead end ahead of the runway RW 2 . That is, the generation of the trajectory T 4  as described above is effective even in the situation of the dead end where the runway RW 3  does not extend to the right and left acrossing the advancing direction. In this case, the lane marking L 3  may be provided at the entrance of the target parking space  61 B. 
     The parking trajectory generation unit  35  generates a parking trajectory of the target vehicle  2 X based on, for example, the position of the target parking space  61 T, the position of the target vehicle  2 X, the external environment of the target vehicle  2 X, and the traveling state of the target vehicle  2 X. A known method can be used to generate the parking trajectory of the target vehicle  2 X. 
     The vehicle controller  36  executes autonomous traveling control and automated parking control of the target vehicle  2 X. In the autonomous traveling control until the target vehicle  2 X reaches the front of the target parking space  61 T, the autonomous driving vehicle  2  autonomously travels by a known method along the traveling trajectory of the autonomous traveling control generated by the traveling trajectory generation unit  34 . In the automated parking control after the target vehicle  2 X reaches the front of the target parking space  61 T, the autonomous driving vehicle  2  is automatically parked in the target parking space  61 T by a known method along the parking trajectory of the automated parking control generated by the parking trajectory generation unit  35 . 
     The user frontend  3  is a portable information terminal of the user associated with the autonomous driving vehicle  2 . The user frontend  3  is registered in the autonomous driving vehicle  2  as the terminal of the owner of the autonomous driving vehicle  2 , for example. The user frontend  3  may be a terminal of a user who is registered as an authority holder in the autonomous driving vehicle  2  by a temporary owner by rental or transfer of the instruction authority from the owner. The user frontend  3  is configured by a computer including a processor such as a CPU, a memory such as a ROM or a RAM, and a user interface including a display and a touch panel, for example. 
     The user frontend  3  has a function of making a vehicle entrance request and a pick-up request to the parking lot management server  1 . By operating the user frontend  3 , the user can make a vehicle entrance request and a pick-up request for the automated valet parking. For example, the user stops the autonomous driving vehicle  2  in the drop-off space  62  of the drop-off area  52  of the parking lot  50  and gets out of the vehicle, and then gives the parking lot management server  1  the instruction authority for the autonomous driving vehicle  2  by operating the user frontend  3  to complete the vehicle entrance request. 
     The user causes the autonomous driving vehicle  2  parked in the parking space  61  to travel to the pick-up space  63  of the pick-up area  53  through the parking lot management server  1  by making a pick-up request. The autonomous driving vehicle  2  waits for the user in the pick-up space  63 . For example, when the autonomous driving vehicle  2  arrives at the pick-up space  63  and stops, the parking lot management server  1  terminates the instruction authority for the autonomous driving vehicle  2 . The instruction authority may be terminated when the user gives an instruction to open the door or start the vehicle to the autonomous driving vehicle  2 . The autonomous driving vehicle  2  may terminate the instruction authority. In addition, the operation of the autonomous driving vehicle  2  associated with the vehicle entrance request and the pick-up request is not limited to the above-described aspect. The same applies to the parking lot management server  1 . 
     [Processing of Automated Valet Parking System] Next, the processing of the automated valet parking system  100  will be described with reference to the drawings.  FIG. 8  is a flowchart illustrating instruction processing of the parking lot management server. The instruction processing of the parking lot management server is executed by the parking lot management server  1  before the automated valet parking is started, such as when the autonomous driving vehicle  2  capable of communicating with the parking lot management server  1  enters the parking lot, for example. 
     As illustrated in  FIG. 8 , in S 11 , the parking lot management server  1  of the automated valet parking system  100  causes the vehicle information acquisition unit  11  to acquire information regarding the vehicle position of the target vehicle  2 X and the position of the target parking space. In S 12 , the parking lot management server  1  causes the traveling map information acquisition unit  12  to acquire traveling map information including information on the traveling coordinates. In S 13 , the parking lot management server  1  causes the vehicle instruction unit  13  to distribute traveling map information. Subsequently, the parking lot management server  1  ends the processing of  FIG. 8 . 
       FIG. 9  is a flowchart illustrating traveling trajectory generation processing of the autonomous driving ECU. The traveling trajectory generation processing of the autonomous driving ECU  20  is executed by the autonomous driving ECU  20  when the traveling map information is distributed to the target vehicle  2 X by the vehicle instruction unit  13  of the parking lot management server  1 , for example. The traveling trajectory generation processing of the autonomous driving ECU  20  is processing for generating a traveling trajectory of autonomous traveling control until the target vehicle  2 X reaches the entrance of the target parking space. 
     As illustrated in  FIG. 9 , in S 21 , the autonomous driving ECU  20  of the target vehicle  2 X causes the traveling trajectory generation unit  34  to determine whether or not the autonomous driving vehicle  2  (target vehicle  2 X) has reached the first coordinate. When it is determined that the target vehicle  2 X has not reached the first coordinate (S 21 : NO), the autonomous driving ECU  20  proceeds to processing of S 22 . In S 22 , the autonomous driving ECU  20  causes the traveling trajectory generation unit  34  to generate a traveling trajectory based on the distributed traveling map information. Subsequently, the autonomous driving ECU  20  ends the processing of  FIG. 9 . 
     On the other hand, when the autonomous driving ECU  20  determines that the target vehicle  2 X has reached the first coordinate (S 21 : YES), the autonomous driving ECU  20  ends the processing of  FIG. 9 . 
       FIG. 10  is a flowchart illustrating a specific example of the traveling trajectory generation processing of  FIG. 9 . The autonomous driving ECU  20  performs processing of  FIG. 10  as an example of the processing of S 22  of the traveling trajectory generation processing of  FIG. 9 . 
     In the processing of  FIG. 10 , the traveling trajectory generation unit  34  generates a traveling trajectory for a predetermined section from a traveling coordinate on the vehicle position side of the target vehicle  2 X toward a traveling coordinate on the entrance side of the target parking space among a plurality of traveling coordinates located between the vehicle position of the target vehicle  2 X and the entrance of the target parking space. The traveling trajectory generation unit  34  repeats the processing of  FIG. 10  to generate a traveling trajectory for all sections from the vehicle position of the target vehicle  2 X to the entrance of the target parking space, for example. 
     As illustrated in  FIG. 10 , in S 31 , the autonomous driving ECU  20  of the target vehicle  2 X causes the traveling trajectory generation unit  34  to determine whether or not the generation of the traveling trajectory in the section corresponds to the generation of the trajectory ahead of the second coordinate. The traveling trajectory generation unit  34  determines whether or not the generation of the traveling trajectory in the section corresponds to the generation of the trajectory ahead of the second coordinate based on, for example, a vehicle position of the target vehicle  2 X, a position of the target parking space, traveling map information, and a position of traveling coordinates forming the section. The “ahead of the second coordinate” means a position closer to the first coordinate than the second coordinate. 
     When it is determined that the generation of the traveling trajectory in the section corresponds to the generation of the trajectory ahead of the second coordinate (S 31 : YES), the autonomous driving ECU  20  proceeds to processing of S 32 . When it is determined that the generation of the traveling trajectory in the section does not correspond to the generation of the trajectory ahead of the second coordinate (S 31 : NO), the autonomous driving ECU  20  proceeds to processing of S 34 . 
     In S 32 , the autonomous driving ECU  20  causes the traveling trajectory generation unit  34  to determine whether or not the entrance of the target parking space is unrecognizable by using the external sensor  22  of the target vehicle  2 X. The traveling trajectory generation unit  34  determines whether or not the entrance of the target parking space is unrecognizable based on, for example, the object recognition range of the external sensor  22 , the information on the traveling coordinate, and the position of the target parking space. 
     When it is determined that the entrance of the target parking space is unrecognizable by using the external sensor  22  (S 32 : YES), the autonomous driving ECU  20  proceeds to processing of S 33 . When it is determined that the entrance of the target parking space is not unrecognizable (is recognizable) by using the external sensor  22  (S 32 : NO), the autonomous driving ECU  20  proceeds to processing of S 34 . 
     In S 33 , the autonomous driving ECU  20  causes the traveling trajectory generation unit  34  to generate a second trajectory that brings the target vehicle  2 X closer to the target parking space than the first trajectory. The traveling trajectory generation unit  34  generates the second trajectory so that the object for recognizing the entrance of the target parking space is included in the object recognition range based on, for example, the distributed traveling map information, the object recognition range of the external sensor  22 , and the position of the object for recognizing the entrance of the target parking space. Subsequently, the autonomous driving ECU  20  ends the processing of  FIG. 10 , returns to the processing of  FIG. 9 , and ends the processing of  FIG. 9 . 
     On the other hand, when it is determined that the generation of the traveling trajectory in the section is not the generation of the trajectory ahead of the second coordinate (S 31 : NO), or when it is determined that the entrance of the target parking space is not unrecognizable (is recognizable) by using the external sensor  22  (S 32 : NO), in S 34 , the autonomous driving ECU  20  generates the first trajectory along the traveling coordinates. 
     Subsequently, the autonomous driving ECU  20  ends the processing of  FIG. 10  and repeats the processing of  FIG. 10  for the next section to generate a traveling trajectory for all sections from the vehicle position of the target vehicle  2 X to the entrance of the target parking space. 
     With the automated valet parking system  100  described above, whether or not the entrance of the target parking space can be recognized is determined based on the object recognition range of the external sensor  22 , the information on the traveling coordinate, and the position of the target parking space. For example, when there is a possibility that the object to be recognized (lane markings L 2 , L 3 , or the like) is located outside the object recognition range, it is determined that the entrance of the target parking space  61 T is unrecognizable. Therefore, the trajectories T 2  and T 4  that bring the target vehicle  2 X closer to the target parking space  61 T on the runways RW 1  and RW 3  are respectively generated so that the object for recognizing the entrance of the target parking space  61 T is included in the object recognition range. Thereby, it is possible to prevent the object to be recognized from being located outside the object recognition range. Therefore, it is possible to ensure the recognition of the object for recognizing the entrance of the target parking space  61 T. 
     In the automated valet parking system  100 , the traveling coordinates include the coordinates  65 A and  65 B which are the coordinates constituting the trajectories T 1  and T 3  and are located on the runways RW 1  and RW 3  facing the target parking space  61 T, respectively. The traveling trajectory generation unit  34  generates in advance a trajectory for bringing the target vehicle  2 X closer to the target parking space  61 T on the runways RW 1  and RW 3  before the target vehicle  2 X reaches the coordinates  65 A and  65 B. Thereby, by generating in advance the trajectories T 2  and T 4  that bring the target vehicle  2 X closer to the target parking space  61 T side on the runways RW 1  and RW 3  respectively, the target vehicle  2 X can be caused to travel along the trajectories T 2  and T 4  before the target vehicle  2 X reaches the coordinates  65 A and  65 B respectively. 
     In the automated valet parking system  100 , the traveling coordinates include the coordinates  65 A and  65 B that are coordinates constituting the trajectories T 1  and T 3  and are located on the runways RW 1  and RW 3  facing the target parking space  61 T respectively, and the coordinates  66 A and  66 B that are coordinates that constitute the trajectories and are located behind the coordinates  65 A and  65 B by a predetermined number (here, one) in the advancing direction of the target vehicle  2 X respectively. The traveling trajectory generation unit  34  generates the trajectories T 2  and T 4  to bring the target vehicle  2 X closer to the target parking space  61 T in the section ahead of the coordinates  66 A and  66 B respectively. Thereby, behind the coordinates  66 A and  66 B (that is, in the section of the coordinates  66 A to  68 A and the section of the coordinates  66 B to  68 B), the target vehicle  2 X travels along the trajectories T 1  and T 3  away from the target parking space  61 T on the runways RW 1  and RW 3  as compared with the sections ahead of the coordinates  66 A and  66 B respectively. Therefore, for example, when an obstacle such as another vehicle or a pillar is located on the target parking space  61 T side, the spatial margin of the target vehicle  2 X with respect to the obstacle can be maintained. 
     In addition, there may be errors due to surveying errors associated with map creation or construction errors when installing objects, between the position of the object stored in the parking lot map information and the position of the object detected by the external sensor  22 . When such an error becomes a certain level or more, it may become difficult to recognize the entrance of the target parking space as a result. Even in such a case, according to the automated valet parking system  100 , the second trajectory that brings the autonomous driving vehicle closer to the target parking space on the runway is generated, so that the object for recognizing the entrance of the target parking space can be included in the object recognition range. 
     Although the embodiment of the present disclosure has been described above, the present disclosure is not limited to the above-described embodiment. The present disclosure can be implemented in various for us including various modifications and improvements based on the knowledge of those skilled in the art, including the above-described embodiment. 
     In the above embodiment, the object recognition range is defined as a rectangular range surrounded by four sides extending in the front-rear direction and the right-left direction of the autonomous driving vehicle  2 , but the object recognition range is not limited to this example. The object recognition range may be a range in which an object is recognized with at least a certain accuracy using the external sensor  22  and is a range based on a predetermined position of the autonomous driving vehicle  2 , and may be a region having various shapes such as a perfect circle, an ellipse, or another polygon. 
     In the above embodiment, in the examples of  FIGS. 4 to 7 , it is assumed that the first coordinate and the predetermined position of the target vehicle  2 X coincide with each other, but the present disclosure is not limited to these example. Even if the first coordinate and the predetermined position of the target vehicle  2 X are deviated from each other, it may be determined whether or not the entrance of the target parking space can be recognized. 
     In the above embodiment, the traveling trajectory generation unit  34  generates the trajectories T 2  and T 4  in advance before the target vehicle  2 X reaches the coordinates (first coordinates)  65 A and  65 B respectively, but the trajectories T 2  and T 4  may be generated after the target vehicle  2 X reaches the coordinates  65 A and  65 B. In this case, in order to cause the target vehicle  2 X to autonomously travel along the generated trajectories T 2  and T 4 , after the target vehicle  2 X reaches the coordinates  65 A and  65 B, the target vehicle  2 X may be once retracted to the coordinates  66 A and  66 B, and the target vehicle  2 X may be caused to autonomously travel again along the trajectories T 2  and T 4  respectively. 
     In the above embodiment, the coordinates (second coordinates)  66 A and  66 B are respectively located behind the coordinates (first coordinates)  65 A and  65 B by one, and the numbers are invariable. But the predetermined number may be variable. For example, the predetermined number may be increased as the instructed speed is faster, depending on the instructed speed when the target vehicle  2 X is caused to autonomously travel. 
     In the above embodiment, the autonomous driving vehicle  2  has the function of the traveling trajectory generation unit  34 , but the parking lot management server  1  may have the function of the traveling trajectory generation unit  34 . In this case, information such as the object recognition range and the specifications of the autonomous driving vehicle  2  may be transmitted from the autonomous driving vehicle  2  to the parking lot management server  1  by communication. 
     In the above embodiment, the target parking spaces  61 A and  61 B are divided by the lane markings L 2  and L 3  respectively, but the present disclosure is not limited thereto. For example, by using at least one of a lane marking that divides the parking space  61 , a pole that divides the parking space  61 , a road stud that divides the parking space  61 , a pillar of the parking lot  50 , a wall of the parking lot  50 , a safety cone that divides the parking space  61 , and the like, the position of the corner of the parking space  61  may be specified. 
     In the above embodiment, the trajectory includes information on the deflection angle of the target vehicle  2 X when passing through each traveling coordinate included in the traveling map, and information such as the order in which the target vehicle  2 X passes through each traveling coordinate included in the traveling map and the time when the target vehicle  2 X can pass, but the present disclosure is not limited thereto. For example, the trajectory may be data of a change in the steering angle (steering angle plan) of the autonomous driving vehicle  2  based on the position on the target route, for example. In this case, the position on the target route may be, for example, a set vertical position set at predetermined intervals (for example, 1 m) in the advancing direction on the target route. The steering angle plan may be data in which a target steering angle is associated with each set vertical position. 
     The parking lot management server  1  does not need to be able to directly communicate with the autonomous driving vehicle  2 , and may be configured to communicate through another server or the like. The parking lot management server  1  may communicate with the autonomous driving vehicle  2  through a management server on the manufacturer side of the autonomous driving vehicle  2  or an operation server of Mobility-as-a-Service (Maas), for example.