Abstract: Conventionally, a method in which pieces of point group information for use in position matching between a white line position detected by an object detection sensor and a white line position on a map are extracted from the white line positions according to a travel environment, has not been taken into account. In the present disclosure, a point group extraction condition is changed according to change in the travel environment so that: a process of position matching that exhibits robustness with respect to change in the travel environment can be realized; and an own position and a white line position existing at a long distance from an own vehicle can be detected with high accuracy.

Abstract: To provide a traveling support system and a traveling support method which can switch a rough traveling support adapted to a rough merging behavior of the merging vehicle, and a traveling support of avoiding a collision between the object vehicle and the merging vehicle, according to conditions. A traveling support system comprising: a merging supporter that supports a traveling of the object vehicle so that a traveling at a time of merging becomes smooth; a collision avoidance supporter that calculates a collision risk and supports a traveling of the object vehicle so that the collision risk decreases; and a traveling support selector that determines whether the traveling support of the merging supporter or the traveling support of the collision avoidance supporter is performed.

Abstract: An acquisition unit acquires pieces of information including information related to a vehicle, information related to the environment inside and outside the vehicle, and information related to a driver on board the vehicle. A determination unit determines priorities of the pieces of information acquired by the acquisition unit on the basis of a service or the like used by the driver among services or the likes provided using information accumulated in a server device. A selection unit selects a piece of information to be transmitted to the server device from among the pieces of information acquired by the acquisition unit on the basis of the priorities determined by the determination unit. A communication unit transmits the piece of information selected by the selection unit to the server device.

Abstract: To provide a lane change prediction system and a lane change prediction method which can predict whether the merging vehicle interrupts on the front side or the back side of the object vehicle. A lane change prediction system, when the peripheral vehicle which exists around the object vehicle is a merging vehicle, predicts whether the merging vehicle interrupts on a front side or a back side of the object vehicle, based on a detection value of the relative position with respect to the object vehicle, a detection value of the relative speed, and a positive or negative of the detection value of the relative speed.

Abstract: Included are: a surrounding situation acquiring unit that acquires surrounding situation information regarding a situation around a control target apparatus; a control amount inferring unit that infers a control amount of the control target apparatus on the basis of the surrounding situation information and acquires attention-paid region information regarding an attention-paid region in the surrounding situation information used when the control amount is inferred; a target detecting unit that detects a position of a target present around the control target apparatus on the basis of the surrounding situation information acquired by the surrounding situation acquiring unit; and a reliability determining unit that determines reliability of the control amount inferred by the control amount inferring unit on the basis of the attention-paid region information acquired by the control amount inferring unit and target position information regarding the position of the target detected by the target detecting unit.

Abstract: A driving assistance device includes processing circuitry configured to acquire environmental information on an environment around a mobile object, acquire action information on an action of a driver of the mobile object, obtain control information for performing automated driving control of the mobile object on a basis of the acquired environmental information and a machine learning model, determine contribution information having a high degree of contribution to the control information, calculate cognitive information indicating a cognitive region of the driver in the environment around the mobile object, specify unrecognized contribution information estimated not to be recognized by the driver, and output driving assistance information necessary for driving assistance on a basis of the unrecognized contribution information.

Abstract: An acquisition unit to acquire input data; an abstraction unit to generate abstraction data representing the input data in an abstract expression form on a basis of the input data acquired by the acquisition unit; a feature amount extracting unit to output a feature amount of the abstraction data by using the abstraction data generated by the abstraction unit as an input; a restoration unit to output restored abstraction data obtained by restoring the abstraction data by using the feature amount output by the feature amount extracting unit as an input; and a reliability determination unit to determine reliability of the feature amount output by the feature amount extracting unit on a basis of the abstraction data generated by the abstraction unit and the restored abstraction data output by the restoration unit are provided.

Abstract: A lane-change prediction device includes: a first index calculating unit to calculate a first index that corresponds to a conditional probability of keeping the travel lane of a second vehicle and a conditional probability of changing the travel lane of the second vehicle, on the basis of time-series information related to the travel lane of the second vehicle; a second index calculating unit to calculate a second index related to a travel lane change or deceleration of the second vehicle, on the basis of surrounding vehicle information; and a lane-change prediction unit to calculate a lane change probability that the second vehicle changes the travel lane, on the basis of the first index and the second index.

Abstract: This route prediction device includes: an information acquisition circuitry to acquire a position and a speed of an own vehicle, positions and speeds of surrounding vehicles traveling around the own vehicle, and map information around the own vehicle; a cut-in determinator to determine whether or not the surrounding vehicle will cut in onto a traveling lane of the own vehicle, on the basis of an inducing factor of inducing cut-in of another vehicle; an assumptive vehicle setting circuitry to determine a traveling position, on a road, of an assumptive vehicle assumed to influence traveling of a cut-in vehicle determined to cut in, among the surrounding vehicles, using road information obtained from the map information; and a route prediction circuitry to predict a traveling route of one of the surrounding vehicles, on the basis of the traveling position of the assumptive vehicle, and so forth.

Abstract: There is provided a course prediction device which includes: a vehicle information detection unit for detecting positions and velocities of multiple vehicles; a road information acquisition unit for acquiring road information indicative of positions of lanes in a road on which the vehicles are traveling; a predicted course calculation unit for calculating a predicted course of each vehicle that is a future traveling course thereof; a collision-expected vehicle extraction unit for extracting the front vehicle and the rear vehicle on the same lane that may possibly collide with each other, on the basis of the road information and the predicted courses; an avoidance-action vehicle prediction unit for predicting which one of the front and rear vehicles is an avoidance action vehicle that will take a collision avoidance action; and an avoidance course calculation unit for calculating a collision avoidance course of the avoidance action vehicle.

Abstract: Conventionally, a method in which pieces of point group information for use in position matching between a white line position detected by an object detection sensor and a white line position on a map are extracted from the white line positions according to a travel environment, has not been taken into account. In the present disclosure, a point group extraction condition is changed according to change in the travel environment so that: a process of position matching that exhibits robustness with respect to change in the travel environment can be realized; and an own position and a white line position existing at a long distance from an own vehicle can be detected with high accuracy.

Abstract: To provide an own position estimation apparatus and an own position estimation method which can correct the position coordinate of own vehicle, even if a periphery monitoring apparatus in which detection points detected with good accuracy at the same timing is few is used. An own position estimation apparatus detects relative positions of a road side wall based on detection information of a periphery monitoring apparatus; converts the past relative positions, into relative positions on a basis of the current position of the own vehicle, and superimposes the current relative positions and the past relative positions after conversion; searches for a relative position relation that a coincidence degree between the relative positions of the road side wall after superposition and the positions of the road side wall of the map data becomes high; and corrects the position coordinate of the own vehicle based on the relative position relation.

Abstract: An environmental information acquiring unit (11) to acquire environmental information on an environment around a mobile object, an action information acquiring unit (12) to acquire action information on an action of a driver of the mobile object, a calculation unit (13) to obtain control information for performing automated driving control of the mobile object on the basis of the environmental information acquired by the environmental information acquiring unit (11) and a machine learning model (18) that uses the environmental information as an input and outputs the control information, a contribution information determining unit (14) to determine contribution information having a high degree of contribution to the control information on the basis of the environmental information and the control information, a cognitive information calculating unit (15) to calculate cognitive information indicating a cognitive region of the driver in the environment around the mobile object on the basis of the action informat

Abstract: An information collection unit collects information indicating a driving operation of a vehicle by a driver and a state of the vehicle changed by the driving operation, and outputs, among the collected information, information in a period from a start point at which a driving operation contributing to stop of the vehicle is performed to a stop start point in a stop state where a stop time of the vehicle continues for a predetermined time or more, as driving operation information. A state estimation unit acquires driver state information indicating a state of the driver from a learned learner on which machine learning has been performed so as to output the driver state information when the driving operation information is input, by inputting the driving operation information output from the information collection unit to the learner and performing arithmetic processing of the learner.

Abstract: A control device: includes a data acquiring unit to acquire inference data including moving speed information indicating a moving speed of an autonomous mobile object, relative position information indicating a relative position of a dynamic obstacle with respect to the autonomous mobile object, and relative speed information indicating a relative speed of the dynamic obstacle with respect to the autonomous mobile object; a control amount calculating unit to calculate a control amount for controlling movement of the autonomous mobile object depending on movement of the dynamic obstacle using the inference data or preprocessed inference data corresponding to the inference data, and a control unit to control the movement of the autonomous mobile object using the control amount. The control amount calculating unit uses a learned model by machine learning, and the learned model receives an input of the inference data or the preprocessed inference data and outputs the control amount.

Abstract: A notifying device predicts the position of a vehicle, on a road through which the vehicle is predicted to pass, after a lapse of the time taken for the driver to fall into an abnormal state. When the predicted position of the vehicle is included in a communication impossible area, the notifying device notifies, at the position of a point where an indication that the driver is going to fall into the abnormal state is detected, a call center terminal that the indication that the driver is going to fall into the abnormal state is detected from the driver.

Abstract: An environmental information acquiring unit for acquiring one or more pieces of environmental information, an important information specifying unit for specifying important environmental information among the pieces of environmental information acquired by the environmental information acquiring unit, a calculation unit for performing a calculation related to control of a vehicle on the basis of the pieces of environmental information acquired by the environmental information acquiring unit, and a trained model in machine learning, a contribution information specifying unit for specifying contribution environmental information among the pieces of environmental information used for the calculation by the calculation unit, and a reliability determination unit for determining a degree of reliability of a result of the calculation performed by the calculation unit by comparing the important environmental information specified by the important information specifying unit with the contribution environmental informa

Abstract: A notifying device predicts the position of a vehicle, on a road through which the vehicle is predicted to pass, after a lapse of the time taken for the driver to fall into an abnormal state. When the predicted position of the vehicle is included in a communication impossible area, the notifying device notifies, at the position of a point where an indication that the driver is going to fall into the abnormal state is detected, a call center terminal that the indication that the driver is going to fall into the abnormal state is detected from the driver.

Abstract: Provided are a first route condition acquirer to acquire a route condition of a planned travel route of a moving body, the route including a plurality of sections; a recommended operation definer to define a content of recommended operation information related to a device included in the moving body and an output point in the planned travel route at which the recommended operation information is output; a complexity level determiner to determine a complexity level of a route in one of the sections including the defined output point by using a static route condition out of the route condition of the planned travel route and, when the complexity level of the section is greater than or equal to a threshold value, determining a complexity level of each of the other sections in the planned travel route; and a recommended operation determiner to determine the output point using the determination result.

Abstract: An acquisition unit acquires pieces of information including information related to a vehicle, information related to the environment inside and outside the vehicle, and information related to a driver on board the vehicle. A determination unit determines priorities of the pieces of information acquired by the acquisition unit on the basis of a service or the like used by the driver among services or the likes provided using information accumulated in a server device. A selection unit selects a piece of information to be transmitted to the server device from among the pieces of information acquired by the acquisition unit on the basis of the priorities determined by the determination unit. A communication unit transmits the piece of information selected by the selection unit to the server device.