Abstract: A method for inspecting a road surface condition includes the steps of obtaining detailed information on a road surface condition set for each inspection point based on a traveling record of a vehicle, and information on an own position of the vehicle, generating an inspection execution plan of the vehicle in the inspection point when the inspection point is included in a predetermined range in an advancing direction of the vehicle with the own position as a reference, performing evaluation of a road surface condition in the inspection point based on a traveling condition of the vehicle that is obtained during the inspection execution plan, and updating the detailed information on a road surface condition set for the inspection point based on latest information on the road surface condition the evaluation of which is performed.

Abstract: An autonomous driving system that performs a traveling of an autonomous driving vehicle based on a remote instruction by a remote commander includes: a vehicle position acquisition unit configured to acquire a position of the autonomous driving vehicle on the map; an external environment recognition unit configured to recognize an external environment of the autonomous driving vehicle; a remote instruction location situation recognition unit configured to recognize a remote instruction location situation on a target route of the autonomous driving vehicle set in advance based on the target route, the position of the autonomous driving vehicle on the map, and map information; and a remote instruction request determination unit configured to determine whether or not to request the remote commander for the remote instruction with regard to the remote instruction location situation, based on the external environment of the autonomous driving vehicle.

Abstract: The vehicle control system comprises a vehicle speed acquisition device, a rotary-typed LIDAR and a controller. The vehicle speed acquisition device is configured to acquire traveling speed of a vehicle. The LIDAR is configured to acquire surrounding information of the vehicle using a laser beam. The controller is configured to control a rotational movement of the LIDAR. The controller is configured to execute processing to set a cycle of the rotational movement based on the traveling speed. In the setting processing, the controller is configured to set the cycle during the traveling speed is relatively fast to a longer cycle than that during the traveling speed is relatively slow.

Abstract: A map management system stores map information used by an automated driving vehicle. The automated driving vehicle detects an obstacle based on the map information, or acquires a margin distance when stopping in front of an obstacle based on the map information. When requiring a remote operator's decision about an action with respect to the obstacle, the automated driving vehicle issues a support request that requests the remote operator to give support. The map management system acquires an operator instruction to the automated driving vehicle issued by the remote operator in response to the support request. The map management system estimates a type of the obstacle based on a state of acquisition of the operator instruction or a content of the operator instruction. Then, the map management system updates the map information according to the type of the obstacle.

Abstract: A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

Abstract: A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

Abstract: A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

Abstract: A management device manages remote support for a vehicle. The management device executes assigns a remote operator to a target vehicle in response to a support request from the target vehicle. Vehicle information includes a position and a travel plan of the target vehicle. When receiving a plurality of support requests in a same period respectively from a plurality of target vehicles scheduled to pass through a predetermined area, the management device recognizes, based on the vehicle information, an entry direction into the predetermined area and an exit direction from the predetermined area for each target vehicle. Based on a combination of the entry direction and the exit direction, the management device determines whether to assign a same remote operator to the plurality of target vehicles or assign different remote operators to the plurality of target vehicles.

Abstract: In deceleration set processing, first-class and second-class deceleration are specified. The first-class deceleration is deceleration of the vehicle corresponding to a first-class state. The first-class state is a state of a slowdown target of the vehicle. The second-class deceleration is deceleration of a following moving body corresponding to a second-class state. The second-class state is a state of the vehicle as viewed from the following moving body. If a minimum value of the first-class deceleration (a first-class minimum value) is equal to or greater than a minimum value of the second-class deceleration (a second-class minimum value), target deceleration is set to the first-class minimum value. Otherwise, based on a second-class minimum value phase, the target deceleration is set to deceleration equal to or greater than the second-class minimum value. The second-class minimum value phase is a phase to which the second-class minimum value belongs in a second deceleration feature.

Abstract: A remote support system requests a remote operator to perform remote support for passing through a predetermined area, when a vehicle is determined to be in a remote support request situation that a continuation of autonomous driving is difficult due to the vehicle during autonomous driving and one or more avoidance target vehicles approaching each other in the predetermined area. Then, the system displays information of the one or more avoidance target vehicles on a display of the remote operator, receives information of a starting reference vehicle serving as a reference for start permission designated by the remote operator from the displayed information, determines whether the starting reference vehicle has passed through the predetermined area, and causes the vehicle to pass through the predetermined area by autonomous driving in case where the starting reference vehicle has passed through the predetermined area.

Abstract: A map information system includes a map database including map information; and a driving assist level determination device. The map information is associated with an evaluation value indicating a certainty of the map information for each location in an absolute coordinate system. Information indicating that the intervention operation is performed is included in driving environment information indicating a driving environment of a vehicle. The driving assist level determination device is configured to acquire, based on the driving environment information, intervention operation information indicating an intervention operation location where the intervention operation is performed, acquire, based on the map information, the evaluation value for each point or section in a target range, and determine, based on the evaluation value and the intervention operation location, an allowable level for each point or section within the target range.

Abstract: A vehicle includes a LIDAR. An object recognition device: sets a space having a height from an absolute position of a road surface as a noise space; classifies a LIDAR point cloud into a first point cloud included in the noise space and a second point cloud outside the noise space; extracts a fallen object candidate being a candidate for a fallen object on the road surface based on the first point cloud; extracts a tracking target candidate being a candidate for a tracking target based on the second point cloud; determines whether horizontal positions of the fallen object candidate and the tracking target candidate are consistent with each other; integrates the fallen object candidate and the tracking target candidate whose horizontal positions are consistent with each other, to be the tracking target; and recognizes the fallen object candidate not integrated into the tracking target as the fallen object.

Abstract: A traffic signal information management system executes a region-of-interest calculation processing to calculate, based on a position information of a vehicle and a traffic signal information indicating the position of a traffic signal, a region of interest in which a traffic signal is presumed to be present in an image imaged by the camera, and also execute a traffic signal image detection processing to detect a traffic signal image included in the region of interest. The traffic signal information management system then execute an evaluation processing to perform a comparison between the position of the region of interest calculated by the region-of-interest calculation processing and the position of the traffic signal image detected by the traffic signal image detection processing and evaluate the certainty of the traffic signal information based on the comparison.

Abstract: A processor of a vehicle determines whether remote assistance from a remote facility is necessary during autonomous driving control. When determination is made that the remote assistance is necessary, the processor generates a target trajectory of the vehicle that includes an expected waiting position. The expected waiting position is a position where the vehicle is expected to wait for reception of an assistance signal from the remote facility. The processor calculates a traveling efficiency level indicating a level of traveling efficiency required in the vehicle, and calculates, based on the traveling efficiency level, a request timing to transmit a request signal for the remote assistance to the remote facility. When the traveling efficiency level is low in calculation of the request timing, the processor outputs a late timing.

Abstract: Setting processing of a target acceleration is executed based on a deceleration feature. In the deceleration feature, a relationship between deceleration and a state of a slowdown target of a vehicle is defined. In the deceleration feature, the state is divided into multiple phases by a predetermined boundary deceleration. In the setting processing, at least one deceleration corresponding to the state is specified. Also, a plausibility indicating an accuracy of information on the state or the accuracy of information associated with the state is calculated for each of the at least one deceleration. Further, a minimum value of the at least one deceleration is specified. Based on a phase to which the minimum value belongs in the deceleration feature and a minimum value plausibility indicating a plausibility corresponding to the minimum value, the minimum value is reflected to a target acceleration in a reflection degree of 0 to 100%.

Abstract: A remote support system is configured to determine whether a vehicle collides with an object to be avoided when the vehicle gets into a remote control request situation, stop to send a remote control request when the remote support system determines that the vehicle does not collide with the object, generate a first speed plan for the vehicle to continue autonomous driving at a predicted collision position and a second speed plan for the vehicle to stop before reaching the predicted collision position when the remote support system determines that the vehicle collides with the object, and determine to send a remote control request based on the degree of deviation between these speed plans.

Abstract: A remote control method includes: sending a remote control request to a remote operator when a vehicle configured to drive autonomously is predicted to have difficulty continuing autonomous driving, the remote control request being a request requesting remote control of the vehicle; performing a determination process of determining whether the vehicle has difficulty continuing the autonomous driving, based on a future travel trajectory of the vehicle generated based on driving environment information; determining necessity of sending the remote control request, based on a determination result of the determination process performed based on a first evaluation criterion; and determining necessity of correcting the travel trajectory, based on a determination result of the determination process performed based on a second evaluation criterion.

Abstract: At least one processor of a vehicle is configured to execute at least one program to: generate a speed plan for a first travel route from a blind spot elimination position to a position specified by a control standby condition, the speed plan specifying a speed of the vehicle for a position on the first travel route so as to meet a requirement that the vehicle be decelerated at a predetermined allowable deceleration or less for a predetermined time from the blind spot elimination position to satisfy the control standby condition; and instruct, for a second travel route from a current position of the vehicle to the blind spot elimination position, the vehicle to travel along the second travel route by autonomous driving so as to cause the vehicle to reach a speed specified by the speed plan at the blind spot elimination position.

Abstract: A map information system includes: an in-vehicle device that executes driving support control based on map information; an external device having external map information used for the driving support control; and an update determination device. The in-vehicle device further executes external update processing that updates first map information being the map information of a first area by using first external map information being the external map information of the first area. The update determination device calculates a change degree being a difference between the first map information and the first external map information, for each point or each area in the first area. The external update processing is prohibited with respect to a section in which the change degree is equal to or less than a threshold. The external update processing is permitted with respect to a section in which the change degree exceeds the threshold.

Abstract: A self-position estimation accuracy verification method includes a step of moving a mobile object to a first check point, a step of acquiring first check information, a step of starting a self-position estimation using the first check information as an initial value, a step of moving the mobile object to a second check point while continuing the self-position estimation, a step of acquiring second check information, and a step of calculating a deviation between a position and a posture of the mobile object on the map estimated by the self-position estimation at the second check point and a position and a posture of the mobile object on the map indicated in the second check information, and verifying the accuracy of the self-position estimation based on the deviation.