REMOTE ASSISTANCE SYSTEM AND REMOTE ASSISTANCE METHOD

A remote assistance system according to the present disclosure comprises a memory storing a database and one or more processors. The database manages, for each of a plurality of operators, feature values of a plurality of feature items regarding a last assistance scene. The one or more processors are configured to execute the following first to third processes. The first process is, when a new assistance request is received from s vehicle, specifying one or more index items from the plurality of feature items. The second process is specifying, from the plurality of operators, one or more candidate operators whose the last assistance scene is similar to a current assistance scene based on the feature values of the one or more index items. The third process is selecting an operator to process the new assistance request from the one or more candidate operators.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority under 35 U.S.C. § 119 to Japanese Patent Application No. 2022-149059, filed Sep. 20, 2022, the contents of which application are incorporated herein by reference in their entirety.

TECHNICAL FIELD

Background

The present disclosure relates to a technique for remote assistance of a vehicle.

Background Art

In recent years, a remote assistance system has been considered in which an operator that processes a remote assistance request is selected from a plurality of operators and assigned to an autonomous driving vehicle which issues the remote assistance request.

For example, Patent Literature 1 discloses a remote instruction system comprising a remote instruction point situation recognition unit configured to recognize a remote instruction point situation on a target route, a time prediction unit configured to predict a monitoring start time and a monitoring end time of a remote commander (operator) for the remote instruction point situation on the target route, and a monitoring time allocation unit configured to allocate a monitoring time, which is a time between the monitoring start time and the monitoring end time, to a plurality of remote commanders (operators) based on the monitoring start time and the monitoring end time of the remote instruction point situation in a plurality of autonomous driving vehicles.

LIST OF RELATED ART

Patent Literature 1: JP 2021/026696 A

SUMMARY

It is assumed that remote assistance requests are issued from various autonomous driving vehicles in various scenes. For this reason, if an operator to be assigned is randomly selected each time in response to a remote assistance request, the operator is required to recognize various traffic environments and respond to various tasks one after another. As a result, the operator may feel a much greater burden as compared with a case where the operator continuously supports one autonomous driving vehicle.

In view of the above problems, an object of the present disclosure is to provide a technique capable of reducing a burden on the assigned operator in a case where an operator that processes a remote assistance request is selected from a plurality of operators and assigned to an autonomous driving vehicle which issues the remote assistance request.

A first aspect of the present disclosure is directed to a remote assistance system for providing a remote assistance function of a vehicle by a plurality of operators.

The remote assistance system according to the first aspect comprises:a memory storing a database that manages, for each of the plurality of operators, feature values of a plurality of feature items regarding a last assistance scene that is a target scene in a last processed remote assistance request; and one or more processors.

The one or more processors are configured to execute:when a new assistance request is received from the vehicle, specifying one or more index items from the plurality of feature items as indicators for similarity determination between the last assistance scene and a current assistance scene that is a target scene in the new assistance request;specifying, from the plurality of operators, one or more candidate operators whose the last assistance scene is similar to the current assistance scene based on the feature values of the one or more index items; andselecting an operator to process the new assistance request from the one or more candidate operators.

A second aspect of the present disclosure is directed to a remote assistance method for providing, by a computer, a remote assistance function of a vehicle by a plurality of operators.

The remote assistance method according to the second aspect includes:managing, for each of the plurality of operators, feature values of a plurality of feature items regarding a last assistance scene that is a target scene in a last processed remote assistance request;when a new assistance request is received from the vehicle, specifying one or more index items from the plurality of feature items as indicators for similarity determination between the last assistance scene and a current assistance scene that is a target scene in the new assistance request;specifying, from the plurality of operators, one or more candidate operators whose the last assistance scene is similar to the current assistance scene based on the feature values of the one or more index items; andselecting an operator to process the new assistance request from the one or more candidate operators.

According to the present disclosure, one or more candidate operators whose the last assistance scene is similar to the current assistance scene are specified from the plurality of operators based on the feature values of the specified one or more index items. The one or more candidate operators specified in this way are expected to have a smaller burden than the other operators when processing the new remote assistance request. Then, an operator to process the new remote assistance request is selected from the one or more candidate operators. It is thus possible to reduce a burden on each of the plurality of operators.

DETAILED DESCRIPTION

FIG.1is a block diagram illustrating a configuration of a remote assistance system10according to the present embodiment. The remote assistance system10according to the present embodiment provides a remote assistance function of the vehicle100by the plurality of operators320. To be more specific, the remote assistance system10according to the present embodiment selects and assigns the operator320that processes the remote assistance request from the plurality of operators320to the vehicle100that issues the remote assistance request. The operator320to be assigned (hereinafter also referred to as an “assigned operator”) operates the remote support terminal310to perform remote support of the vehicle100that issues the remote support request.

In this embodiment, the vehicle100is an autonomous driving vehicle. That is, the vehicle100performs recognition of the surrounding environment, driving determination according to the recognition result, and autonomous traveling according to the driving determination by the automatic driving function. Then, the vehicle100issues a remote assistance request in a case where it is impossible or difficult to perform driving determination in the autonomous driving function. Hereinafter, the vehicle100is referred to as an autonomous driving vehicle100.

FIG.2Ashows an example of the type and content of a remote assistance request issued by an autonomous driving vehicle100. For example, in a case where the autonomous driving vehicle100recognizes a pedestrian near a crosswalk in the vicinity of the crosswalk, when a sufficient degree of certainty is not given as to whether or not the pedestrian will cross the crosswalk, the autonomous driving vehicle100issues a remote support request of “Passing Permission for Crosswalk”. For example, in a case where the autonomous driving vehicle100tries to open a door for getting off a passenger, when the timing at which the opening of the door does not interfere with the surroundings cannot be determined with sufficient accuracy, the autonomous driving vehicle100issues a remote support request of “Door Open/Close Permission”. Note that the autonomous driving vehicle100may simultaneously issue a plurality of types of remote assistance requests. For example, the autonomous driving vehicle100may simultaneously issue remote support requests of “Door Open/Close Permission” and “Door Open/Close Alert”.

Refer toFIG.1again. The autonomous driving vehicle100includes a sensor101, a storage device102, a control device103, and a communication device104. The control device103is connected to the sensor101, the storage device102, and the communication device104so that information can be transmitted therebetween (thick lines inFIG.1). For example, the controller103is connected to these devices via an in-vehicle network including a control area network (CAN) or the like.

The sensor101is a sensor for recognizing a surrounding environment and a road structure. Examples of the sensor101include a light detection and ranging (LiDAR), a radar, a camera, and the like. The recognition information of the sensor101is transmitted to the controller103.

The memory102stores information related to an autonomous driving function. The memory102is constituted by recording media such as an HDD and an SSD. In particular, the storage device102stores map information105. The map information105is typically information indicating a position of a road, a structure, or the like on a map. The control device103can acquire the map information105by accessing the storage device102.

The communication device104communicates with a device outside the autonomous driving vehicle100to transmit and receive information. In particular, the communication device104includes a device that communicates with the remote assistance server200and the remote support terminal310. For example, the communication device104communicates with the remote assistance server200and the remote support terminal310via a mobile communication network and the Internet. The communication device104may be configured to start communication with the remote support terminal310corresponding to the allocation operator in response to the determination of the allocation operator. Information received by the communication device104is transmitted to the controller103.

The control device103executes processing related to the autonomous driving function based on the recognition information of the sensor101and the map information105. That is, autonomous driving of the autonomous controller103is realized by the autonomous driving vehicle100executing the processing. The controller103includes, for example, one or a plurality of in-vehicle electronic control units (ECUs). In particular, the control device103executes a process of generating a remote assistance request in a case where it is impossible or difficult to perform driving determination in the autonomous driving function. Then, the control device103transmits the generated remote support request to the remote assistance server200via the communication device104. Thereafter, the control device103receives the determination of the assignment operator with respect to the remote support request via the communication device104, and causes the autonomous driving vehicle100to autonomously travel in accordance with the determination of the assignment operator.

Here, when transmitting the remote assistance request to the remote assistance server200, the control device103is configured to further transmit, to the remote assistance server200, information (scene information) the remote support request to the remote assistance server. Examples of the scene information include point group data detected by the LiDAR, image data captured by the camera, a position of the autonomous driving vehicle100on a map, map information105around the autonomous driving vehicle100, attributes (vehicle specifications, body type, and the like) of the autonomous driving vehicle100, information on passengers (number of passengers, attributes, position, state, and the like), and the like. The scene information can be obtained as a processing result of the controller103or recognition information of the sensor101.

In the remote assistance system10according to the present embodiment, the remote assistance function is realized by the remote assistance server200executing processing. The remote assistance server200is typically a computer accessible via the Internet. In this case, the remote assistance server200may be a cloud server or a dedicated server. In particular, the remote assistance server200may be configured to communicate with the autonomous driving vehicle100and the remote assistance device310. The configuration of the remote assistance server200will be described later.

The processing executed by the remote assistance server200includes an assignable operator specification processing P202, a scene feature calculation processing P203, an index item specification processing P204, a similarity determination processing P205, an assigned operator determination processing P206, and a remote assistance processing P207.

The assignable operator specification processing P202receives a new remote support request from the autonomous driving vehicles100and identifies an allocable operator320among the plurality of operators320. For example, the assignable operator specification processing P202specifies one or more operators320who are not currently performing remote support or operators320who are currently performing remote support but are permitted to interrupt other remote support based on the remote support statuses of the plurality of operators320. When there is no operator320to which assignment is possible, the assignable operator specification processing P202may be configured to wait until there is one or more operators to which assignment is possible. Alternatively, the assignable operator specification processing P202may be configured to reject the remote assistance request from the autonomous driving vehicles100.

The scene feature calculation processing P203calculates a feature (scene feature) of a scene that is a target of the currently received remote assistance request based on the scene information received from the autonomous driving vehicles100. Here, the scene feature is represented by a combination of feature values of a plurality of feature items.FIG.2billustrates an example of a feature item and a possible feature value for each feature item. For example, the scene feature calculation processing P203calculates the feature value of the “Service Area” as the area A from the map information105and the position of the autonomous driving vehicles100acquired as the scene information.

Table 1 shows an example of the scene feature calculated by the scene feature calculation processing P203. The scene feature shown in Table 1 is, for example, a case where the autonomous driving vehicle100, which is a medium-sized bus, issues a remote support request of “Departure Permission at Bus Stop” near the bus stop B in the area A.

Note that the remote assistance server200may be configured to acquire the scene feature as the scene information. In this case, the scene feature calculation processing P203is realized in the autonomous driving vehicle100. For example, it is realized by the control device103of the autonomous driving vehicle100. The one or more characteristic elements may be determined in advance in accordance with an environment to which the remote assistance system10according to the present embodiment is applied, or may be determined in accordance with the type of the remote support request received this time.

The mode of the possible feature values shown inFIG.2Bis merely an example, and other modes may be employed. For example, the feature values of the respective feature items shown inFIG.2Bmay be modified as follows.

The feature value of the “Check Target (Attention Direction)” can also be represented by a binary number representing a combination of cameras that present video to the operator320. The feature value of the “Service Area” can be expressed by the maximum value and the minimum value of the latitude and longitude. The feature value of “Location” can also be expressed by latitude and longitude (GPS position) or a relative position on a map (localized position). The feature value of the “Road Shape” can be expressed by a numerical value representing a curvature, a road width, the number of lanes, the number of branches, or the like. The feature value of the “Vehicle Shape” can also be expressed by a numerical value representing a total length, a total width, a vehicle type, or the like. The feature value of the “Surrounding Object” may be represented by a list of vector information representing the type, relative position, relative speed, and the like of the target for each target. The feature value of “Passenger” can also be represented by a list of vector information representing each piece of information for each passenger who recognizes the inside of the vehicle cabin.

Refer toFIG.1again. The index item specification processing P204specifies one or a plurality of indicator elements as indicators for similarity determination with respect to a scene that is a target of the currently received remote support request among the plurality of feature items. For example, the index item specification processing P204specifies one or more indicator elements in accordance with the type of the currently received remote support request. In this case, the index item specification processing P204can specify one or more indicator elements by referring to a list in which indicator elements are defined for each type of remote assistance request.

FIG.3Aillustrates an example of a list in which index items are defined for each type of remote assistance request. In the list illustrated inFIG.3A, a characteristic element in which a check mark is written is defined as an index element for the type of the remote assistance request. For example, when the type of the remote support request received this time is “Departure Permission at Intersection”, the index item specification processing P204specifies “Check Target”, “Service Area”, “Location”, “Road Shape”, and “Surrounding Object” as indicator factors.

The index item specification processing P204may be further configured to set priorities for the specified one or more indicator elements. For example, the index item specification processing P204can specify one or more indicator components and set priorities by referring to a list in which indicator components and priorities are defined for each type of remote assistance request.

FIG.3Billustrates an example of a list in which index items and priorities are defined for each type of remote assistance request. In the list shown inFIG.3B, a characteristic element in which a numerical value is described is defined as an index element with respect to the type of the remote support request, and the priority order of the index element is defined by the numerical value. For example, when the type of the remote support request received this time is “Passenger Alert”, the index item specification processing P204specifies “Check Target”, “Vehicle Shape”, and “Passenger” as indicator elements, and sets priorities1,2, and3in this order.

The lists shown inFIGS.3A and3Bmay be given in advance in accordance with the environment to which the remote assistance system10is applied. Here, the index element defined for the type of the remote support request may be a feature item related to a burden when the operator320processes the type of the remote support request among the plurality of feature items. In addition, the priority order may be an order of magnitude of influence on a burden when the operator320processes the type of remote assistance request.

Refer toFIG.1again. The similarity determination processing P205determines similarity between a scene (hereinafter referred to as a “last assistance scene”) which is a target of a remote support request previously processed by the operator320and a scene (hereinafter referred to as a ““current assistance scene”) which is a target of the remote support request received this time for each of the operators320to which assignment is possible. Then, the similarity determination processing P205outputs, as a processing result, an operator320whose last assistance scene is similar to the current assistance scene (hereinafter referred to as a “candidate operator”) among the operators320that can be assigned.

The similarity determination processing P205performs similarity determination by comparing the scene feature of the last assistance scene with the scene feature of the current assistance scene. Here, the scene feature of the last assistance scene of each of the plurality of operators320is managed as the scene feature database215. That is, the similarity determination processing P205can acquire the scene feature of the last assistance scene for each of the operators320to which assignment is possible by referring to the scene feature database215.

In particular, the similarity determination processing P205performs the similarity determination based on the feature value of the specified one or more indicator elements. An example of processing performed by the similarity determination processing P205will be described below with reference toFIGS.4A and4B.FIGS.4A and4Billustrate examples of the scene feature of the last assistance scene of the operator320that can be assigned to the scene feature of the current assistance scene. InFIGS.4A and4B, the operators320that can be assigned are three operators,320a,320b, and320c. In addition, inFIGS.4A and4B, a priority order is set to the one or more specified index items.

First, reference is made toFIG.4A. The similarity determination processing P205performs similarity determination of the feature value with respect to the current assistance scene in the order of the indicator elements according to the priorities. Therefore, the similarity determination processing P205first performs the similarity determination of the feature value of the “Check Target” having the precedence order of 1. Here, the similarity determination processing P205can determine whether or not they are similar from the fact that the feature values match each other. Therefore, the similarity determination processing P205can determine that the operator320bdoes not have the similarity between the last assistance scene and the current assistance scene by the similarity determination of the feature value of the “Check Target”. Next, the similarity determination processing P205performs the similarity determination of the feature value of the “Service Area” having the precedence2. At this time, the similarity determination processing P205may exclude the operator320bfrom the target of the similarity determination. The similarity determination processing P205can determine that the last assistance scene of the operator320cis not similar to the current assistance scene based on the similarity determination of the feature value of the “Service Area”. At this point in time, among the operators320that can be assigned, the operator320(hereinafter referred to as a “target operator”) for which the last assistance scene is not determined to be dissimilar to the current assistance scene is only the operator320a. Therefore, the similarity determination processing P205sets the operator320aas a candidate operator.

Reference is now made toFIG.4b. When similarity determination is performed similarly to the case described inFIG.4A, in the example illustrated inFIG.4b, it is understood that the similarity determination processing P205sets the operator320cas a candidate operator.

When a plurality of target operators remain at the time when the similarity determination of the feature value is performed for all of the one or plurality of specified indicator elements, the similarity determination processing P205may set the plurality of remaining target operators as candidate operators. In addition, when there is no more target operator due to the similarity determination of a certain feature value, the similarity determination processing P205may be configured to skip the similarity determination of the feature value. Thus, it is possible to avoid a situation in which no candidate operator exists.

In this way, the similarity determination processing P205performs the similarity determination based on the feature value of the specified one or more indicator elements. On the other hand, the similarity determination processing P205does not perform similarity determination for feature items that are not indicator elements. As a result, it can be expected that the candidate operator specified by the similarity determination processing P205is less burdened than the other operators320when processing the currently received remote support request.

For example, the example illustrated inFIG.4Acan be considered as a case where the autonomous driving vehicle100issues a remote assistance request of “Departure Permission at Intersection”. In this case, it is considered that the “Check Target” or the “Service Area” serving as the index element has a large influence on the load when the operator320processes the remote support request. On the other hand, it is considered that the “Vehicle Shape” and the “Passenger” have little influence on the burden when the operator320processes the remote support request. In the example illustrated inFIG.4A, the operator320awho has confirmed and determined the out-of-vehicle traffic in the same area as the current assistance scene is the candidate operator. When the operator320aprocesses the remote assistance request of “Departure Permission at Intersection”, the operator SL can start remote assistance in a state familiar with the region-specific traffic environment. As a result, the operator320ais expected to be less burdened when processing the remote assistance request received this time.

In addition, for example, the example illustrated inFIG.4Bcan be considered as a case where the autonomous driving vehicle100issues a remote support request of “Passenger Alert”. In this case, it is considered that the “Check Target” or the “Vehicle Shape” serving as the index element has a large influence on the load when the operator320processes the remote support request. On the other hand, the “Service Area” and the “Location” are considered to have little influence on the load when the operator320processes the remote assistance request. In the example illustrated inFIG.4B, the operator320cwho has checked and determined the interior of the vehicle having the same shape as that in the current assistance scene is a candidate operator. The operator320ccan initiate remote assistance in a manner familiar to the structure of the car in processing the request for remote assistance of “Passenger Alert”. As a result, the operator320cis expected to be less burdened when processing the remote assistance request received this time.

Furthermore, in the examples illustrated inFIGS.4A and4B, the similarity determination of the feature value with respect to the current assistance scene is performed in the order of the index items according to the priority order. By performing the similarity determination in this manner, it is possible to preferentially specify, as the candidate operator, the operator320who is particularly similar to the index element having a large influence on the load when the last assistance scene and the current assistance scene are processed in the remote support request. As a result, it is possible to preferentially specify, as the candidate operator, the operator320who is less burdened when processing the remote assistance request received this time.

For example, in the example illustrated inFIG.4A, the operator320bhas a larger number of similar index items than the operator320a. However, the operator320bis not similar to the current assistance scene with respect to the “Check Target” which is the highest-priority indicator and has a large influence on the load when the remote support request is processed. Therefore, it is assumed that the operator320bhas a larger burden when processing the remote assistance request than the operator320a. As described above, in the example illustrated inFIG.4A, it is understood that the operator320awho is assumed to have a smaller burden when processing the currently received remote support request can be appropriately specified as the candidate operator.

The similarity determination processing P205can also adopt processing from another viewpoint for the similarity determination based on the feature values of the one or more specified indicator elements.

Another aspect is to calculate the degree of similarity between the last assistance scene and the current assistance scene on the basis of the feature value of the specified one or more index items for each of the operators320to which assignment is possible.

For example, the similarity determination processing P205can calculate, for each of one or more indicator elements, a similarity point indicating a degree of similarity between the feature value of the last assistance scene and the feature value of the current assistance scene according to a predetermined criterion, and calculate the sum of the similarity points for each of one or more indicator elements as the degree of similarity. In this case, the predetermined criterion is that, for example, for the index element of “Check Target”, the similarity point between “traffic outside vehicle” and “inside vehicle” is given 1 point, and the similarity point when there is a match in “traffic outside vehicle” is given 3 points. In addition, for example, when the feature value is represented by a numerical value, the similarity determination processing P205can calculate a difference or a distance in a predetermined space between the feature value of the last assistance scene and the feature value of the current assistance scene for each of one or more indicator elements, and calculate a reciprocal of a sum of the difference or the distance for each of one or more indicator elements as the degree of similarity. Furthermore, the similarity determination processing P205may be configured to calculate the sum by weighting the similarity point, the difference, or the distance of each of the one or more indicator elements. In this case, the index item specification processing P204may be configured to weight the specified one or more indicator elements. For example, the index item specification processing P204can specify and weight one or a plurality of indicator elements by referring to a list in which numerical values indicating weights are given to the types of remote assistance requests as inFIG.3B. By thus weighting and calculating the sum, it is possible to further increase the contribution of the index element having a large influence on the load in processing the remote support request to the similarity.

Then, the similarity determination processing P205determines the operator320whose similarity is equal to or greater than a predetermined value as a candidate operator. Here, the predetermined thresholds may be suitably determined in accordance with the environment to which the remote assistance system10is applied. At this time, the similarity determination processing P205may be configured to output the similarity of each of the specified one or more candidate operators as a processing result. By performing the similarity determination in this manner, it is possible to prevent the operator320to which a certain load or more is applied when processing the currently received remote support request from being specified as a candidate operator.

From this viewpoint, the similarity determination processing P205may be configured to set the operator320having the maximum similarity as a candidate operator.

These aspects can be employed in combination. For example, the similarity determination processing P205may be configured to perform the similarity determination of the feature value with respect to the current assistance scene in the order of the indicator elements according to the priorities for the operators320whose similarities are equal to or greater than a predetermined value among the operators320to which the assignment is possible.

Further, the similarity determination processing P205may be configured to set the operator320whose last assistance scene is not managed by the scene feature database215as one of the candidate operators. With such a configuration, it is possible to avoid a situation in which the operator320who performs remote support for the first time is not identified as a candidate operator at all.

In such a configuration, the similarity determination processing P205may be configured to calculate the highest similarity of the operator320whose last assistance scene is not managed by the scene feature database215among the one or more specified candidate operators. This is because such an operator320can start remote assistance in a state without prejudice, and can be expected to have a small burden for any remote assistance request.

Alternatively, the similarity determination processing P205may be configured to calculate such a degree of similarity of the operator320as a constant height value. This is because it is considered that a candidate operator having an extremely high similarity value is expected to have a further smaller burden than such an operator320.

As described above, the similarity determination processing P205outputs one or more candidate operators specified as the processing result.

Refer toFIG.1again. The assigned operator determination processing P206determines an operator320to be selected from one or more candidate operators as an assignment operator. When the specified candidate operator is one, the assigned operator determination processing P206may be configured to select the one candidate operator. When a plurality of candidate operators is specified, the assigned operator determination processing P206selects, for example, the operator320randomly from the plurality of candidate operators. Alternatively, when the similarity determination processing P205outputs the similarity of each of a plurality of candidate operators as the processing result, the assigned operator determination processing P206may be configured to select the candidate operator having the highest similarity. Alternatively, the assigned operator determination processing P206may be configured to select the operator320based on another indicator such as the number of times of assignment of the remote support performed so far. For example, the assigned operator determination processing P206selects the operator320so as to reduce the bias of the number of assignments of the remote support.

The remote assistance processing P207notifies the remote assistance terminals310corresponding to the determined assignment operators that the remote assistance of the autonomous driving vehicles100that issue the remote assistance request received this time has been assigned. Upon receiving the notification, the remote support device310starts communication with the autonomous driving vehicle100. Thus, remote support between the remote support device310and the autonomous driving vehicle100is performed. The remote support terminal310presents information necessary for remote support to the operator320, and receives an operation related to remote support by the operator320(for example, input of determination with respect to a remote assistance request). The operation related to the remote support accepted by the remote support device310is transmitted to the autonomous driving vehicle100. As a result, the assigned operator remotely supports the autonomous driving vehicle100.

Further, the remote assistance processing P207updates the scene feature database215with the scene feature of the current assistance scene as the scene feature of the last assistance scene for the assigned operator. Thus, the scene feature database215can be constructed.

As described above, the remote assistance system10according to the present embodiment is configured. In addition, in the remote assistance system10according to the present embodiment, generally, there may be a plurality of autonomous driving vehicle100as a target of remote assistance.

Next, the configuration of the remote assistance server200will be described with reference toFIG.5.FIG.5is a block diagram showing a preferred example of the configuration of the remote assistance server200. The remote assistance server200includes a processing unit210and a communication unit220.

The communication unit220communicates with an external device of the remote assistance server200to transmit and receive information. In particular, the communication unit220communicates with the autonomous driving vehicle100and the remote support terminal310. Typically, the communication unit220communicates with the autonomous driving vehicle100and the remote support terminal310via the Internet. The communication unit220realizes reception of a remote support request and scene information, and transmission of a notification of assignment of remote support to the remote support terminal310.

The processing unit210executes processing related to the remote support function. The processing unit210is a computer including a storage device211and a processor216.

The memory211is coupled to the processor216and stores a plurality of instructions213executable by the processor216and various kinds of information214required for execution of processing. The memory211can be constituted by recording media such as a ROM, a RAM, an HDD, and an SSD.

The instructions213are provided by the computer program212. The plurality of instructions213are also configured to cause the processor216to perform operations associated with the remote assistance function. That is, when the processor216operates in accordance with the plurality of instructions213, the processor216functions as the assignable operator specification processing P202, the scene feature calculation processing P203, the index item specification processing P204, the similarity determination processing P205, the assigned operator determination processing P206, and the remote assistance processing P207. The processor216can be constituted by a CPU or the like including an arithmetic unit, a register, or the like.

The date214includes information acquired by the remote assistance server200, parameter information of the computer program212, and the like. In particular, datum214includes a scene feature database215. The scene feature database215is updated by a process executed by the processor216.

Here, the scene feature database215may be configured to continuously hold the scene feature of the last assistance scene for each of the plurality of operators320, or may be configured to delete the scene feature of the last assistance scene for some of the operators320by processing executed by the processor216. For example, the processor216may be configured to execute a process of deleting the scene feature managed by the scene feature database215as follows.

One example is to delete a scene feature for an operator320for which a certain amount of time has elapsed since the last update.

Another example is to delete the scene feature for the operator320who has left his/her seat or made a break. In this case, the absence or break can be determined by detecting that the remote support terminal310has not been operated for a certain period of time or that the operator320has performed an explicit operation (for example, the absence button is pressed).

Another example is to delete a scene feature for an operator320who has finished a day's work or an operator320who will start a day's work.

By configuring the processor216to execute the process of deleting the scene feature in this manner, it is possible to express the operator320who is assumed to have no feeling of the last assistance scene support scene. Since it can be expected that the burden on the operator320is small in response to any remote assistance request, the processor216may be configured to execute a process of updating the feature value of each of the plurality of feature items to a special value similar to any feature value instead of deleting the scene feature in the same case as described above.

The remote assistance server200is configured as described above.

Hereinafter, processing executed by the remote assistance server200will be described.

FIG.6is a flowchart illustrating processing executed by the remote assistance server200, more specifically, processing executed by the processor216. The flowchart illustrated inFIG.6typically starts when a new remote assistance request is received from the autonomous driving vehicle100.

In Step S100, the remote assistance server200uses the assignable operator specification processing P202to specify an allocable operator320among the plurality of operators320. In step S200, the remote assistance server200calculates the scene feature of the current assistance scene by the scene feature calculation processing P203. In step S300, the remote assistance server200specifies one or a plurality of index items as indicators of similarity determination for the current assistance scene by the indicator element-specifying index item specification processing P204. Here, the processes related to steps S100, S200, and S300may be executed in random order. Alternatively, the processes related to steps S100, S200, and S300may be executed in parallel.

Next, in step S400, the remote assistance server200causes the similarity determination processing P205to perform similarity determination based on the feature values of the one or more specified index items, and specifies one or more candidate operators from the operators320to which assignment is possible.

Next, in step S500, the remote assistance server200selects the operator320to process the remote assistance request received this time from the specified one or more candidate operators by the assignment assigned operator determination processing P206.

Next, in step S600, the remote assistance server200causes the remote assistance processing P207to allocate the remote support of the autonomous driving vehicles100to the determined assigned operator.

Next, in step S700, the remote assistance server200causes the remote assistance processing P207to update the scene feature database215with the feature of the current assistance scene as the scene feature of the last assistance scene for the assigned operator. After step S700, the current process is terminated.

As described above, the processing is executed by the remote assistance server200(processor216). When the remote assistance server200executes processing in this manner, a remote support method for providing the remote support function according to the present embodiment by a computer is realized.