Patent Publication Number: US-2023147357-A1

Title: Vehicle control system, apparatus, and method

Description:
TECHNICAL FIELD 
     The present disclosure relates to a vehicle control system, an apparatus, a method, and a computer-readable medium. 
     BACKGROUND ART 
     As a related art, Patent Literature 1 discloses a vehicle driving assistance system that assists in driving a vehicle. In the vehicle driving assistance system described in Patent Literature 1, a vehicle obtains driving information or traffic information from another vehicle or an on-road facility by using inter-vehicle communication or road-vehicle communication. A driving control unit of the vehicle controls automated driving of the vehicle on the basis of information obtained from the other vehicle or the on-road facility and information relating to a driving situation of the vehicle that has been obtained from a sensor of the local vehicle. 
     As another related art, Patent Literature 2 discloses an automated traveling assistance system. In the automated traveling assistance system described in Patent Literature 1, a vehicle detects an obstacle on the road by using an obstacle sensor. The vehicle reports the detection of the obstacle to a roadside control apparatus (a centralized base station) by using road-vehicle communication. The roadside control apparatus analyzes a situation of the obstacle by using a roadside sensor. The roadside control apparatus generates avoidance action instruction information on the basis of a result of analysis, and transmits the avoidance action instruction information to the vehicle serving as an obstacle report source and a vehicle around the vehicle. The vehicle that has received the avoidance action instruction information performs an operation to avoid the obstacle in accordance with the content of the avoidance action instruction information. 
     CITATION LIST 
     Patent Literature 
     
         
         Patent Literature 1: Japanese Unexamined Patent Application Publication No. 2018-077652 
         Patent Literature 2: Japanese Unexamined Patent Application Publication No. 2000-306194 
       
    
     SUMMARY OF INVENTION 
     Technical Problem 
     In Patent Literature 1, for example, in a case where a vehicle passes another vehicle, the vehicle starts inter-vehicle communication with the other vehicle. The vehicle obtains, from the other vehicle, information indicating an avoidance direction, and determines an avoidance direction of the local vehicle in accordance with the obtained information. However, in Patent Literature 1, automated driving of the vehicle is performed on the basis of sensor information of the local vehicle. Therefore, the vehicle fails to handle a potential risk that fails to be recognized by only using a sensor of the local vehicle. 
     In Patent Literature 2, in a case where the detection of an obstacle has been reported from a vehicle, the roadside control apparatus analyzes a situation of the obstacle by using the roadside sensor, and generates avoidance action instruction information on the basis of a result of analysis. Each vehicle avoids the obstacle in accordance with the avoidance action instruction information, and therefore a safer obstacle avoidance operation can be performed with time to spare in comparison with a case where each of the vehicles performs autonomous traveling by only relying on a sensor mounted on the local vehicle. However, the roadside control apparatus analyzes an obstacle on the basis of only an image captured by the roadside sensor. Therefore, the roadside control apparatus does not always perform an analysis suitable for control performed on each of the vehicles. 
     In view of the circumstances described above, it is an object of the present disclosure to provide a vehicle control system, an apparatus, a method, and a computer-readable medium that are capable of more precisely determining a situation of a vehicle and controlling automated driving of the vehicle on the basis of the situation of the vehicle. 
     Solution to Problem 
     In order to achieve the object described above, the present disclosure provides a vehicle control system including: vehicle control means for controlling a target vehicle on the basis of first information obtained by a sensor that is provided in the target vehicle; analysis means for analyzing state information of the target vehicle on the basis of the first information received via a network, and second information obtained from a sensor that is provided outside the target vehicle; and specification means for specifying a control policy of the target vehicle on the basis of the state information analyzed by the analysis means. 
     The present disclosure provides a vehicle control apparatus including: analysis means for analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being driven in an automated manner on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and specification means for specifying a control policy of the target vehicle on the basis of the state information analyzed by the analysis means. 
     The present disclosure provides a vehicle control method including: analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being controlled on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and specifying a control policy of the target vehicle on the basis of the state information that has been analyzed. 
     The present disclosure provides a non-transitory computer-readable medium configured to store a program that causes a computer to perform a process including: analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being controlled on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and specifying a control policy of the target vehicle on the basis of the state information that has been analyzed. 
     Advantageous Effects of Invention 
     A vehicle control system, an apparatus, a method, and a computer-readable medium according to the present disclosure are capable of more precisely determining a situation of a vehicle and assisting in driving the vehicle on the basis of the situation of the vehicle. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a block diagram schematically illustrating a vehicle control system according to the present disclosure. 
         FIG.  2    is a flowchart schematically illustrating an operation procedure in the vehicle control system according to the present disclosure. 
         FIG.  3    is a block diagram illustrating a vehicle control system according to a first example embodiment of the present disclosure. 
         FIG.  4    is a block diagram illustrating an example of a configuration of a vehicle to be controlled. 
         FIG.  5    is a flowchart illustrating an operation procedure in the vehicle control system. 
         FIG.  6    is a block diagram illustrating a vehicle control system according to a second example embodiment of the present disclosure. 
         FIG.  7    is a block diagram illustrating a vehicle that is used in a vehicle control system according to a third example embodiment of the present disclosure. 
         FIG.  8    is a block diagram illustrating a control center that is used in the vehicle control system according to the third example embodiment of the present disclosure. 
         FIG.  9    is a block diagram illustrating an example of a configuration of a computer apparatus. 
     
    
    
     EXAMPLE EMBODIMENT 
     Prior to the description of an example embodiment of the present disclosure, an outline of the present disclosure is described.  FIG.  1    schematically illustrates a vehicle control system according to the present disclosure. A vehicle control system  10  includes vehicle control means  12 , analysis means  14 , and specification means  15 . A sensor  11  is disposed in a vehicle  20  serving as a target vehicle. The vehicle control means  12  controls the vehicle  20  on the basis of first information obtained by the sensor  11 . The first information obtained by the sensor  11  is transmitted to the analysis means  14  via a network. 
     A sensor  13  is a sensor that is disposed outside the target vehicle. The analysis means  14  analyzes state information of the vehicle  20  on the basis of the first information obtained by the sensor  11  and second information obtained by the sensor  13 . The specification means  15  specifies a control policy of the vehicle  20  on the basis of the state information analyzed by the analysis means  14 . 
       FIG.  2    schematically illustrates an operation procedure in the vehicle control system  10 . The analysis means  14  analyzes the state information of the vehicle  20  on the basis of the first information that has been obtained by the sensor  11  provided in the vehicle  20  and has been received via the network, and the second information that has been obtained from the sensor  13  provided outside the target vehicle (step A 1 ). The specification means  15  specifies a control policy of the vehicle  20  on the basis of the analyzed state information (step A 2 ). 
     In the present disclosure, the analysis means  14  analyzes the state information of the vehicle  20  on the basis of the sensor  11  of the vehicle  20  and the sensor  13  outside the target vehicle. The specification means  15  specifies a control policy of automated driving of the vehicle  20  on the basis of the analyzed state information. The vehicle control means  12  controls the vehicle  20  on the basis of the specified control policy. In the present disclosure, the control policy is specified by using the sensor  13  outside the target vehicle in addition to the sensor  11  of the vehicle  20 . By doing this, a situation of the vehicle  20  can be determined more precisely, and driving of the target vehicle can be assisted in on the basis of the situation of the vehicle. 
     An example embodiment of the present disclosure is described in detail below with reference to the drawings.  FIG.  3    illustrates a vehicle control system according to a first example embodiment of the present disclosure. A vehicle control system  100  includes a control center (a vehicle control apparatus)  101 , a vehicle  150 , a vehicle  200 , and an on-road facility  250 . In the vehicle control system  100 , the control center  101  is connected to the vehicle  150 , the vehicle  200 , and the on-road facility  250  via a network  102 . The network  102  may be, for example, a network in conformity with communication line standards such as long term evolution (LTE), or may include a wireless communication network such as Wi-Fi (registered trademark) or a fifth generation mobile communication system. 
     Note that  FIG.  3    illustrates a single vehicle  200  and a single on-road facility  250 , but the present example embodiment is not limited to this. In the present example embodiment, the vehicle control system  100  can include a plurality of vehicles  200 . In addition, the vehicle control system  100  can include a plurality of on-road facilities  250 . The vehicle control system  100  does not necessarily include both the vehicle  200  and the on-road facility  250 , and it is sufficient if at least one of the vehicle  200  or the on-road facility  250  is included. 
     The vehicle  150  is a vehicle serving as a target to be controlled by the control center  101 . The vehicle  150  is, for example, a vehicle that travels on the road, such as a private car, a taxi, or a bus. The vehicle  150  includes a sensor  151 . The vehicle  150  is configured to be able to perform automated driving (autonomous driving) by using sensor information obtained by the sensor  151 . The vehicle  150  transmits the sensor information obtained by the sensor  151 , to the control center  101  via the network  102 . The sensor  151  corresponds to the sensor  11  illustrated in  FIG.  1   . 
       FIG.  4    illustrates an example of a configuration of the vehicle  150 . The vehicle  150  includes a periphery monitoring sensor  152 , a vehicle sensor  153 , a vehicle control electric control unit (ECU)  154 , an automated driving ECU  155 , and a communication device  156 . In the vehicle  150 , these components are configured to be mutually communicable via an in-vehicle local area network (LAN). 
     The periphery monitoring sensor  152  is a sensor that monitors a peripheral situation of the vehicle  150 . The periphery monitoring sensor  152  includes, for example, a camera, a radar, light detection and ranging (LiDAR), and the like. The periphery monitoring sensor  152  may include a plurality of cameras that images, for example, a front side, a rear side, a right-hand side, and a left-hand side of the vehicle. 
     The vehicle sensor  153  is a sensor for detecting various states of the vehicle  150 . The vehicle sensor  153  includes sensors, for example, a vehicle speed sensor that detects vehicle speed, a steering sensor that detects a steering angle, an accelerator opening sensor that detects the opening of an accelerator pedal, a brake depression sensor that detects an amount of depression of a brake pedal, and the like. The periphery monitoring sensor  152  and the vehicle sensor  153  correspond to the sensor  151  illustrated in  FIG.  3   . 
     The vehicle control ECU  154  is an electronic control unit that performs traveling control or the like on the vehicle  150 . In general, the electronic control unit includes a processor, a memory, an input/output (I/O), and a bus that connects them. The vehicle control ECU  154  performs various types of control, such as control performed on a fuel injection amount, control performed on an engine injection timing, or control performed on a power steering assistance amount, on the basis of sensor information that has been output by the vehicle sensor  153 . 
     The automated driving ECU  155  is an electronic control unit that controls automated driving of the vehicle  150 . The automated driving ECU  155  obtains sensor information from the periphery monitoring sensor  152  and the vehicle sensor  153 , and controls autonomous traveling of the vehicle  150  on the basis of the obtained sensor information. Automated driving performed by the automated driving ECU  155  can be controlled by the control center  101  by using the control policy described later. The automated driving ECU  155  corresponds to the vehicle control means  12  illustrated in  FIG.  1   . 
     The communication device  156  is configured as a device that performs wireless communication between the vehicle  150  and the network  102  (see  FIG.  3   ). The communication device  156  includes an antenna for wireless communication, a transmitter, and a receiver. In addition, the communication device  156  includes a processor, a memory, an I/O, and a bus that connects them. The communication device  156  includes, as a logical component, a sensor information transmission unit  157  and a control policy reception unit  158 . Functions of the sensor information transmission unit  157  and the control policy reception unit  158  are implemented, for example, by executing a control program stored in the memory by using a microcomputer. 
     The sensor information transmission unit  157  obtains, via the in-vehicle LAN, sensor information that has been obtained by the periphery monitoring sensor  152  and the vehicle sensor  153 . The sensor information transmission unit  157  does not necessarily need to obtain all pieces of sensor information of the periphery monitoring sensor  152  and the vehicle sensor  153  that will be used by the automated driving ECU  155 . The sensor information transmission unit  157  may obtain some pieces of sensor information that have been obtained by the periphery monitoring sensor  152  and the vehicle sensor  153 . The sensor information obtained by the sensor information transmission unit  157  can include image data that has been obtained by imaging a front side, a rear side, a left-hand side, and a right-hand side of the vehicle by using cameras. The sensor information transmission unit  157  transmits the obtained sensor information to the control center  101  via the network  102 . 
     The control policy reception unit  158  receives a control policy from the control center  101 . In a case where the control policy has been received, the control policy reception unit  158  transmits the received control policy to the automated driving ECU  155  via the in-vehicle LAN. In a case where the control policy has been received, the automated driving ECU  155  controls (modifies), on the basis of the received control policy, automated driving of the vehicle  150  that is performed on the basis of the sensor information of the periphery monitoring sensor  152  and the vehicle sensor  153 . 
     Referring back to  FIG.  3   , the vehicle  200  is a vehicle that is different from the vehicle  150  to be controlled. The vehicle  200  includes a sensor  201 . The vehicle  200  is, for example, a vehicle that travels on the road, such as a private car, a taxi, or a bus. The vehicle  200  transmits sensor information obtained by the sensor  201 , to the control center  101  via the network  102 . A configuration of the vehicle  200  may be a configuration obtained by omitting the automated driving ECU  155  and the control policy reception unit  158  from the configuration illustrated in  FIG.  4    of the vehicle  150 . The sensor  201  is configured as a sensor that is equivalent to the periphery monitoring sensor  152  illustrated in  FIG.  4   . 
     The on-road facility  250  is a facility that has been installed on the road, such as a traffic light, a traffic sign, or a street light. The on-road facility  250  includes a sensor  251 . The on-road facility  250  transmits sensor information obtained by the sensor  251 , to the control center  101  via the network  102 . A configuration of the on-road facility  250  may be a configuration obtained by omitting the vehicle sensor  153 , the vehicle control ECU  154 , the automated driving ECU  155 , and the control policy reception unit  158  from the configuration illustrated in  FIG.  4    of the vehicle  150 . The sensor  251  is configured as a sensor that is equivalent to the periphery monitoring sensor  152  illustrated in  FIG.  4   . The sensors  201  and  251  correspond to the sensor  13  illustrated in  FIG.  1   . 
     The control center  101  includes a sensor information reception unit  111 , an analysis unit  112 , a specification unit  113 , and a remote control unit  114 . The sensor information reception unit  111  receives sensor information (first information) that has been obtained by the sensor  151 , from the vehicle  150  to be controlled. In addition, the sensor information reception unit  111  receives pieces of sensor information (second information) that have been obtained by the sensors  201  and  251 , from the vehicle  200  that is not a target to be controlled, and the on-road facility  250 . Note that the sensor information reception unit  111  does not necessarily need to receive sensor information from both the vehicle  200  and the on-road facility  250 . It is sufficient if the sensor information reception unit  111  receives sensor information from at least one of the vehicle  200  or the on-road facility  250 . 
     The analysis unit  112  analyzes state information of the vehicle  150  to be controlled, on the basis of the sensor information of the sensor  151  and the pieces of sensor information of the sensors  201  and  251  that have been received by the sensor information reception unit  111 . The state information of the vehicle  150  includes, for example, an operation state of the vehicle  150  and peripheral information of the vehicle  150 . The operation state of the vehicle includes information relating to a traveling state of the vehicle  150  itself. The operation state can include, for example, information relating to the availability of automated driving, a place where the vehicle travels, and the like. The peripheral information includes information relating to a phenomenon that can affect the traveling of the vehicle  150  in the circumference of the vehicle  150 . Here, the “circumference of a vehicle” can include, for example, a range of several meters with the vehicle  150  as a center, a line-of-sight distance in which the camera of the vehicle  150  can capture an image, an intersection that is one ahead of a traveling location of the vehicle, a place on a route of the vehicle  150 , and the like. The peripheral information can include, for example, information relating to the presence/absence of a pedestrian, the presence/absence of another risky vehicle, the absence/presence of traffic obstruction on the road, and the like. The analysis unit  112  analyzes each of the sensor information of the sensor  151  and the pieces of sensor information of the sensors  201  and  251 . The analysis unit  112  may analyze a plurality of states relating to each of the operation state of the vehicle and the peripheral information. The analysis unit  112  analyzes the state information of the vehicle  150  on the basis of a result of analysis. The analysis unit  112  may include, for example, plural pieces of artificial intelligence (AI) that correspond to plural states to be analyzed, may input sensor information to each of the plural pieces of AI, and may obtain a result of analysis. 
     For example, the analysis unit  112  analyzes information relating to a pedestrian around the vehicle  150 , as the peripheral information. The analysis unit  112  detects, for example, a person from the sensor information, and analyzes whether a person is present or whether a person is crossing the crosswalk, is walking on the sidewalk, or is crossing a place other than the crosswalk. In addition, the analysis unit  112  detects a vehicle from the sensor information, and analyzes whether an emergency vehicle is present, whether a truck is present, whether a vehicle that is speeding up or speeding down is present, or whether a vehicle is traveling in a meandering manner. The analysis unit  112  may analyze whether a bicycle, a motorcycle, or a construction site is present on the basis of the sensor information, or may analyze, for example, whether it is crowded. The analysis unit  112  may analyze whether the vehicle  150  is in a risky state on the basis of, for example, a combination of results of analyzing a plurality of items (states). The analysis unit  112  corresponds to the analysis means  14  illustrated in  FIG.  1   . 
     The sensor information reception unit  111  may receive the sensor information from all of the sensors  201  of the vehicles  200  that are not a target to be controlled, and the sensors  251  of the on-road facilities  250 . The analysis unit  112  may analyze all pieces of sensor information that have been received by the sensor information reception unit  111 , and may analyze pieces of state information relating to places where the vehicles  200  and the on-road facilities  250  are present. The analysis unit  112  may analyze the state information of the vehicle  150  on the basis of a result of analyzing the state information relating to each of the places, and a current location, a destination, a route, or the like of the vehicle  150  to be controlled. For example, in a case where a spot that the vehicle  150  is traveling toward is crowded, the analysis unit  112  may conduct an analysis to determine that the vehicle  150  will enter into a risky state. 
     In analyzing the state information of the vehicle  150  to be controlled, the analysis unit  112  may analyze sensor information that satisfies a specified condition from among collected pieces of sensor information instead of analyzing all of the collected pieces of sensor information. For example, the analysis unit  112  obtains location information of the vehicle  150  from the vehicle  150 , or specifies a route of the vehicle  150  from information relating to a destination, or the like. The analysis unit  112  may analyze pieces of sensor information of a vehicle  200  and an on-road facility  250  that are located around the vehicle  150  to be controlled, or pieces of sensor information of a vehicle  200  and an on-road facility  250  that relate to a traveling direction, from among other vehicles  200  and the on-road facilities  250 . 
     The analysis unit  112  may perform object detection on pieces of sensor information of other vehicles  200  and the on-road facilities  250 . The analysis unit  112  may analyze pieces of sensor information of a vehicle  200  and an on-road facility  250  in which an object that attention is to be paid to, such as a vehicle, a child, or a fallen object, has been detected from the sensor information, from among other vehicles  200  and the on-road facilities  250 , and may analyze the state information of the vehicle  150 . Alternatively, the analysis unit  112  may track pieces of sensor information of other vehicles  200  and the on-road facilities  250 , and may determine a portion having a large movement. The analysis unit  112  may analyze sensor information having a large movement from among pieces of sensor information of other vehicles  200  and the on-road facilities  250 , and may analyze the state information of the vehicle  150 . 
     The sensor information reception unit  111  does not need to receive sensor information from all of the vehicles  200  and the on-road facilities  250  in the same period, and may change a period of obtaining the sensor information depending on the vehicle  200  and the on-road facility  250 . For example, in a case where sensor information satisfies a specified condition, the sensor information reception unit  111  may receive the sensor information from the vehicle  200  and the on-road facility  250  in a relatively short period, for example, a period of 100 milliseconds. In a case where sensor information does not satisfy a specified condition, the sensor information reception unit  111  may receive the sensor information from the vehicle  200  and the on-road facility  250  in a relatively long period, for example, a period of 1 second. In a case where a result of analyzing sensor information indicates a particularly risky state, the sensor information reception unit  111  may receive the sensor information from the vehicle  200  and the on-road facility  250  in a shorter period, for example, a period of 10 milliseconds. 
     The specification unit  113  specifies a control policy of the vehicle  150  to be controlled on the basis of the state information analyzed by the analysis unit  112 . The specification unit  113  may specify a control policy that corresponds to the state information analyzed by the analysis unit  112 , by using, for example, a table in association with the state information and a control policy to be applied. Alternatively, the specification unit  113  may specify a control policy from the state information by using a neural network. The specification unit  113  corresponds to the specification means  15  illustrated in  FIG.  1   . 
     The remote control unit (control policy transmission means)  114  transmits the control policy specified by the specification unit  113  to the vehicle  150  to be controlled via the network  102 . The transmitted control policy is received by the control policy reception unit  158  (see  FIG.  4   ) of the vehicle  150 , and is transmitted to the automated driving ECU  155 . The automated driving ECU  155  controls automated driving in accordance with the control policy. The remote control unit  114  transmits the control policy to the vehicle  150 , and therefore the remote control unit  114  causes the vehicle  150  to perform automated driving based on the transmitted control policy. 
     The control policy is information indicating a policy of control to be applied to automated driving of a vehicle. The control policy has, for example, a hierarchical structure including a plurality of layers, and a highest layer provides an abstract instruction to a vehicle. In the control policy, a lower layer provides a more specific instruction to a vehicle. 
     For example, in automated driving of the vehicle  150 , the vehicle travels at a highest speed and a highest acceleration that correspond to a safety level that has been determined on a vehicle side. In a case where the safety level is low, a highest speed in automated driving is set to a relatively low speed, for example, 20 km/h. In addition, a maximum acceleration is set to a relatively low value. The control center  101  obtains at least one of the sensor information of the vehicle  200  or the sensor information of the on-road facility  250  in addition to the sensor information of the vehicle  150 , and analyzes state information of the vehicle  150 . In a case where there are no pedestrians or the like in the circumference of the vehicle  150  and in a case where congestion has not been recognized in a traveling direction, the control center  101  transmits, to the vehicle  150 , a control policy for setting, for example, a safety level that is higher by one stage. In this case, in the vehicle  150 , the safety level can be increased by one stage, and automated driving can be performed in a state where a highest speed has been set to, for example, 30 km/h. The control policy may include a specific instruction to be provided to a vehicle, such as whether the vehicle  150  to be controlled may start or not. The control policy may include an instruction to change a priority order of a policy to be applied in automated driving on a side of the vehicle  150 . 
     The automated driving ECU  155  of the vehicle  150  determines whether automated driving is available, by using sensor information of the periphery monitoring sensor  152 , or the like. The control center  101  can determine whether automated driving of the vehicle  150  is available, by using sensor information of the vehicle  150  and sensor information of another vehicle  200  or the on-road facility  250 , separately from determination performed in the vehicle  150  as to whether automated driving is available. Even in a case where the automated driving ECU  155  has determined that automated driving will be able to be continued, when state information analyzed by the analysis unit  112  indicates that automated driving will fail to be continued, the control center  101  transmits, to the vehicle  150 , a control policy indicating switching from automated driving to remote control. The vehicle  150  requests the control center  101  to remotely drive the vehicle, in accordance with the control policy. The control center  101  that has received a request transmits, for example, a control command to the vehicle  150 , and causes the vehicle  150  to perform an operation to avoid an obstacle. Alternatively, in the control center  101 , a remote driver may operate a steering wheel, an accelerator pedal, or the like, and the control center  101  may transmit, to the vehicle  150 , an amount of an operation performed on the steering wheel, the accelerator pedal, or the like, and therefore the vehicle  150  may be remotely maneuvered. By doing this, for example, before the vehicle  150  reaches a place where it has been determined that automated driving is not available, the control center  101  can switch the vehicle  150  to remote control in advance. 
     Next, an operation procedure (a vehicle control method) in the vehicle control system  100  is described.  FIG.  5    illustrates the operation procedure in the vehicle control system  100 . The vehicle  150  to be controlled performs automated driving on the basis of sensor information obtained by the sensor  151  (the periphery monitoring sensor  152  and the vehicle sensor  153  (see  FIG.  4   )). The vehicle  150  transmits the sensor information obtained by the sensor  151 , to the control center  101  via the network  102 . Another vehicle  200  that is not a target to be controlled and the on-road facility  250  respectively transmit pieces of sensor information obtained by the sensors  201  and  251 , to the control center  101  via the network  102 . 
     The sensor information reception unit  111  of the control center  101  collects sensor information from the vehicle  150 , the vehicle  200 , and the on-road facility  250  (step B 1 ). The analysis unit  112  analyzes state information of the vehicle  150  on the basis of the collected pieces of sensor information (step S 2 ). The specification unit  113  determines a control policy on the basis of the state information of the vehicle  150  (step S 3 ). The remote control unit  114  transmits the determined control policy to the vehicle  150  via the network  102  (step S 4 ). 
     The control policy reception unit  158  of the vehicle  150  receives the control policy transmitted from the control center  101 . The automated driving ECU  155  obtains the control policy from the control policy reception unit  158 . The automated driving ECU  155  applies the obtained control policy to automated driving (step S 5 ). The automated driving ECU  155  controls automated driving of the vehicle on the basis of the control policy. The remote control unit  114  may transmit, to the vehicle, information in which the control policy can be selected on a vehicle side instead of the control policy itself. The vehicle  150  may receive the information, and may select the control policy. 
     In the present example embodiment, the control center  101  analyzes state information of a vehicle on the basis of sensor information of the vehicle  150  to be controlled and pieces of sensor information of the vehicle  200  that is not a target to be controlled and the on-road facility  250 , and specifies a control policy on the basis of the state information. The control center  101  transmits the specified control policy to the vehicle  150 , and therefore automated driving of the vehicle  150  is controlled. In the present example embodiment, pieces of sensor information of the vehicle  200  that is not a target to be controlled and the on-road facility  250  are used to control automated driving of the vehicle  150 . The control center  101  can more precisely analyze state information of the vehicle  150  to be controlled in comparison with a case where the state information is analyzed on the basis of only the sensor information of the vehicle  150  to be controlled. Therefore, the control center  101  can appropriately control automated driving of the vehicle  150  in accordance with a situation of the vehicle. 
     Next, a second example embodiment of the present disclosure is described.  FIG.  6    illustrates a vehicle control system according to the second example embodiment of the present disclosure. A vehicle control system  100   a  according to the present example embodiment includes an external server  300  in addition to the configuration illustrated in  FIG.  3    of the vehicle control system  100  according to the first example embodiment. The control center  101  can perform communication with the external server  300  via the network  102 . In the present example embodiment, the analysis unit  112  uses information obtained from the external server  300  to analyze state information of the vehicle  150 . Other points may be similar to points in the first example embodiment. 
     The external server  300  transmits, to the control center  101 , information (third information) relating to an area where the vehicle  150  to be controlled is present. The information transmitted by the external server  300  includes, for example, information that can affect traffic in the area where the vehicle  150  to be controlled is present. The external server  300  transmits information, such as traffic congestion information, weather information, or an event situation, to the control center  101 . The analysis unit  112  analyzes the state information of the vehicle  150  on the basis of the information obtained from the external server  300  in addition to sensor information of the sensor  151  of the vehicle  150  to be controlled and pieces of sensor information of the sensors  201  and  251  of the vehicle  200  that is not a target to be controlled and the on-road facility  250 . 
     The analysis unit  112  analyzes whether an event is being held in a traveling direction of the vehicle  150 , for example, on the basis of the event situation obtained from the external server  300 . For example, in a case where an event is being held in a spot that the vehicle  150  will travel toward, it is predicted that a large number of persons will gather. Therefore, the analysis unit  112  may conduct an analysis to determine that the vehicle  150  will enter into a risky state. Alternatively, in a case where the weather information obtained from the external server  300  indicates rain, snow, or the like, the analysis unit  112  may conduct an analysis to determine that the vehicle  150  will enter into a risky state. The specification unit  113  specifies a control policy on the basis of the state information of the vehicle  150 . The remote control unit  114  transmits the specified control policy to the vehicle  150 , and controls automated driving in the vehicle  150 . 
     In the present example embodiment, the analysis unit  112  analyzes the state information of the vehicle  150  to be controlled, by using the information obtained from the external server  300  in addition to pieces of sensor information of another vehicle  200  and the on-road facility  250 . By doing this, a variety of pieces of state information of a vehicle can be analyzed in comparison with a case where only sensor information is used. Other effects are similar to effects exhibited in the first example embodiment. 
     Next, a third example embodiment of the present disclosure is described.  FIG.  7    illustrates a vehicle that is used in a vehicle control system according to the third example embodiment of the present disclosure. In the present example embodiment, a vehicle  150   a  includes a learning device  159  in addition to the components illustrated in  FIG.  4    of the vehicle  150 . The learning device (a first learning device)  159  leans a rule (a first rule) relating to automated driving controlled by the automated driving ECU  155 . 
     It is assumed, for example, that in a video obtained by the periphery monitoring sensor  152 , a person has been present in a specified area, and then the person has crossed the road. In this case, the learning device  159  learns a rule in which speed will be reduced in a case where a person is present in a specified region. Alternatively, the learning device learns a rule in which speed will be reduced in a case where the traffic light has started blinking. The automated driving ECU  155  controls automated driving on the basis of pieces of sensor information obtained from the periphery monitoring sensor  152  and the vehicle sensor  153 , and the learned rule. 
       FIG.  8    illustrates a control center that is used in the present example embodiment. A control center  101   a  includes a learning device  115  in addition to the components illustrated in  FIG.  3    of the control center  101 . The learning device (a second learning device)  115  leans a rule (a second rule) relating to state information analyzed by the analysis unit  112 . The learning device  115  learns, for example, a rule in which in a case where a large number of persons are present in a specified place, the persons in the specified place will move, and another place will be crowded. Alternatively, the learning device  115  learns a rule in which in a case where it is raining in a certain place, it will rain in another place. In the present example embodiment, the specification unit  113  may specify a control policy on the basis of the first rule and the second rule. 
     In the present example embodiment, the vehicle  150  includes the learning device  159  that learns a rule of automated driving. In addition, the control center  101  includes the learning device  115  that leans a rule relating to state information analyzed by the analysis unit  112 . In the present example embodiment, the learning devices  115  and  159  are used, and therefore automated driving and the analysis of state information according to actual circumstances can be achieved. Other effects are similar to effects of the first example embodiment and the second example embodiment. 
     Note that in each of the example embodiments described above, the vehicle  200  may be a vehicle that is configured to be able to perform automated driving, similarly to the vehicle  150 . In a case where the vehicle  200  is a vehicle that is configured to be able to perform automated driving, the control center  101  may determine that both the vehicle  150  and the vehicle  200  are vehicles to be controlled. In this case, the analysis unit  112  analyzes state information of the vehicle  150  and state information of the vehicle  200 . The specification unit  113  specifies a control policy of the vehicle  150  on the basis of the state information of the vehicle  150 , and specifies a control policy of the vehicle  200  on the basis of the state information of the vehicle  200 . In analyzing the state information of the vehicle  200 , information obtained by the sensor  201  is used as first information, and information obtained by the sensor  151  is used as second information. 
     In the present disclosure, the control center  101  can be configured as a computer apparatus (a server apparatus).  FIG.  9    illustrates an example of a configuration of a computer apparatus that can be used as the control center  101 . A computer apparatus  500  includes a control unit (a central processing unit (CPU))  510 , a storage unit  520 , a read only memory (ROM)  530 , a random access memory (RAM)  540 , a communication interface (IF)  550 , and a user interface  560 . 
     The communication interface  550  is an interface for connecting the computer apparatus  500  to a communication network by using wired communication means, wireless communication means, or the like. The user interface  560  includes, for example, a display unit such as a display. In addition, the user interface  560  includes an input unit such as a keyboard, a mouse, or a touch panel. 
     The storage unit  520  is an auxiliary storage device that can hold various types of data. The storage unit  520  does not necessarily need to be part of the computer apparatus  500 , and may be an external storage device or a cloud storage connected to the computer apparatus  500  via a network. 
     The ROM  530  is a non-volatile storage device. As the ROM  530 , for example, a semiconductor storage device, such as a flash memory, that has a relatively small capacity is used. A program executed by the CPU  510  can be stored in the storage unit  520  or the ROM  530 . The storage unit  520  or the ROM  530  stores, for example, various programs for implementing a function of each unit in the control center  101 . 
     The program described above can be stored by using various non-transitory computer-readable media, and can be supplied to the computer apparatus  500 . The non-transitory computer-readable media include various tangible storage media. Examples of the non-transitory computer-readable medium include a magnetic recording medium such as a flexible disk, a magnetic tape, or a hard disk, a magneto-optical recording medium such as a magneto-optical disk, an optical disk medium such as a compact disc (CD) or a digital versatile disk (DVD), and a semiconductor memory such as a mask ROM, a programmable ROM (PROM), an erasable PROM (EPROM), a flash ROM, or a RAM. In addition, the program may be supplied to a computer by using various transitory computer-readable media. Examples of the transitory computer-readable medium include an electrical signal, an optical signal, and electromagnetic waves. The transitory computer-readable medium can supply the program to a computer via a wired communication line such as an electric wire or an optical fiber, or a wireless communication line. 
     The RAM  540  is a volatile storage device. As the RAM  540 , various semiconductor memory devices, such as a dynamic random access memory (DRAM) or a static random access memory (SRAM), are used. The RAM  540  can be used as an internal buffer that transitorily stores data or the like. The CPU  510  deploys a program stored in the storage unit  520  or the ROM  530  in the RAM  540 , and executes the deployed program. The CPU  510  executes the program, and therefore a function of each of the units in the control center  101  can be implemented. The CPU  510  may include an internal buffer in which data or the like can be transitorily stored. 
     Although example embodiments of the present disclosure has been described in detail above, the present disclosure is not limited to the example embodiment described above, and the present disclosure also includes those that are obtained by making changes or modifications to the example embodiment described above without departing from the spirit of the present disclosure. 
     For example, part or the entirety of the example embodiment disclosed above can be described as described in the following supplementary notes, but is not limited to the following. 
     [Supplementary Note 1] 
     A vehicle control system including: 
     vehicle control means for controlling a target vehicle on the basis of first information obtained by a sensor that is provided in the target vehicle; 
     analysis means for analyzing state information of the target vehicle on the basis of the first information received via a network, and second information obtained from a sensor that is provided outside the target vehicle; and 
     specification means for specifying a control policy of the target vehicle on the basis of the state information analyzed by the analysis means. 
     [Supplementary Note 2] 
     The vehicle control system according to Supplementary Note 1, in which the analysis means further analyzes the state information of the target vehicle on the basis of third information indicating information relating to an area where the target vehicle is present. 
     [Supplementary Note 3] 
     The vehicle control system according to Supplementary Note 2, in which the third information includes information that affects traffic in the area where the target vehicle is present. 
     [Supplementary Note 4] 
     The vehicle control system according to any one of Supplementary Notes 1 to 3, in which the state information includes an operation state of the target vehicle, and peripheral information of the target vehicle. 
     [Supplementary Note 5] 
     The vehicle control system according to any one of Supplementary Notes 1 to 4, in which the control policy indicates a policy of automated driving. 
     [Supplementary Note 6] 
     The vehicle control system according to any one of Supplementary Notes 1 to 5, further including a first learning device configured to learn a first rule relating to automated driving that is controlled by the vehicle control means, and a second learning device configured to learn a second rule relating to the state information analyzed by the analysis means, in which the specification means specifies the control policy on the basis of the first rule and the second rule. 
     [Supplementary Note 7] 
     The vehicle control system according to any one of Supplementary Notes 1 to 6, further including control policy transmission means for transmitting the control policy that has been specified to the target vehicle, 
     in which the vehicle control means controls automated driving of the target vehicle on the basis of the control policy that has been transmitted. 
     [Supplementary Note 8] 
     A vehicle control apparatus including: 
     analysis means for analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being controlled on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and 
     specification means for specifying a control policy of the target vehicle on the basis of the state information analyzed by the analysis means. 
     [Supplementary Note 9] 
     The vehicle control apparatus according to Supplementary Note 8, in which the analysis means further analyzes the state information of the target vehicle on the basis of third information indicating information relating to an area where the target vehicle is present. 
     [Supplementary Note 10] 
     The vehicle control apparatus according to Supplementary Note 9, in which the third information includes information that affects traffic in the area where the target vehicle is present. 
     [Supplementary Note 11] 
     The vehicle control apparatus according to any one of Supplementary Notes 8 to 10, in which the state information includes an operation state of the target vehicle, and peripheral information of the target vehicle. 
     [Supplementary Note 12] 
     The vehicle control apparatus according to any one of Supplementary Notes 8 to 11, in which the control policy indicates a policy of automated driving. 
     [Supplementary Note 13] 
     The vehicle control apparatus according to any one of Supplementary Notes 8 to 12, in which 
     the target vehicle includes a first learning device configured to learn a first rule relating to automated driving, 
     the vehicle control apparatus further includes a second learning device configured to learn a second rule relating to the state information analyzed by the analysis means, and 
     the specification means specifies the control policy on the basis of the first rule and the second rule. 
     [Supplementary Note 14] 
     A vehicle control method including: 
     analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being controlled on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and 
     specifying a control policy of the target vehicle on the basis of the state information that has been analyzed. 
     [Supplementary Note 15] 
     The vehicle control method according to Supplementary Note 14, in which in the analyzing of the state information, the state information of the target vehicle is further analyzed on the basis of third information indicating information relating to an area where the target vehicle is present. 
     [Supplementary Note 16] 
     The vehicle control method according to Supplementary Note 15, in which the third information includes information that affects traffic in the area where the target vehicle is present. 
     [Supplementary Note 17] 
     The vehicle control method according to any one of Supplementary Notes 14 to 16, in which the state information includes an operation state of the target vehicle, and peripheral information of the target vehicle. 
     [Supplementary Note 18] 
     The vehicle control method according to any one of Supplementary Notes 14 to 17, in which the control policy indicates a policy of automated driving. 
     [Supplementary Note 19] 
     The vehicle control method according to any one of Supplementary Notes 14 to 18, in which 
     the target vehicle learns a first rule relating to automated driving, 
     the vehicle control method further includes learning a second rule relating to the state information analyzed in the analyzing of the state information, and 
     the specifying of the control policy includes specifying the control policy on the basis of the first rule and the second rule. 
     [Supplementary Note 20] 
     A non-transitory computer-readable medium configured to store a program that causes a computer to perform a process including: 
     analyzing state information of a target vehicle on the basis of first information and second information, the target vehicle being controlled on the basis of the first information that has been obtained by a sensor that is provided in the target vehicle, the first information having been received via a network from the target vehicle, the second information having been obtained from a sensor that is provided outside the target vehicle; and 
     specifying a control policy of the target vehicle on the basis of the state information that has been analyzed. 
     REFERENCE SIGNS LIST 
     
         
           10  VEHICLE CONTROL SYSTEM 
           11 ,  13  SENSOR 
           12  VEHICLE CONTROL MEANS 
           14  ANALYSIS MEANS 
           15  SPECIFICATION MEANS 
           16  CONTROL POLICY TRANSMISSION MEANS 
           100  VEHICLE CONTROL SYSTEM 
           101  CONTROL CENTER 
           102  NETWORK 
           111  SENSOR INFORMATION RECEPTION UNIT 
           112  ANALYSIS UNIT 
           113  SPECIFICATION UNIT 
           114  REMOTE CONTROL UNIT 
           115  LEARNING DEVICE 
           150  VEHICLE 
           151  SENSOR 
           152  PERIPHERY MONITORING SENSOR 
           153  VEHICLE SENSOR 
           154  VEHICLE CONTROL ECU 
           155  AUTOMATED DRIVING ECU 
           156  COMMUNICATION DEVICE 
           157  SENSOR INFORMATION TRANSMISSION UNIT 
           158  CONTROL POLICY RECEPTION UNIT 
           159  LEARNING DEVICE 
           200  VEHICLE 
           201  SENSOR 
           250  ON-ROAD FACILITY 
           251  SENSOR 
           300  EXTERNAL SERVER