Abstract: An information processing system receives first travel histories from vehicles that belong to vehicle type A, learns based on the first travel histories to build a first driver model that represents relation between travel situations and behaviors of the vehicles that belong to a first vehicle type, receives second travel histories from vehicles that belong to vehicle type X that is different from vehicle type A, and performs transfer learning in which the second travel histories are used for the first driver model to build a second driver model that represents relation between travel situations and behaviors of the vehicles that belong to vehicle type X.

Abstract: An image display system includes a first processor, a second processor, and a comparator. The first processor acquires a behavior estimation result of a vehicle, and generates future position information after a predetermined time passes of the vehicle based on the behavior estimation result. The second processor acquires present information about the vehicle, and generates present position information on the vehicle and a peripheral object based on the acquired information. The comparator compares the future position information on the vehicle and the present position information on the vehicle and the peripheral object, and generates present image data indicating present positions of the vehicle and the peripheral object and future image data indicating future positions of the vehicle and the peripheral object. Further, the comparator allows a notification device to display a present image based on the present image data and a future image based on the future image data together.

Abstract: An information processing system that appropriately estimates a driving conduct includes: a detector that detects a vehicle environment state, which is at least one of surroundings of a vehicle and a driving state of the vehicle; a behavior learning unit configured to cause a neural network to learn a relationship between the vehicle environment state detected by the detector and a behavior of the vehicle implemented after the vehicle environment state; and a behavior estimation unit configured to estimate a behavior of the vehicle by inputting, into the neural network that learned, the vehicle environment state detected at a current point in time by the detector.

Abstract: An information processing system receives first travel histories from vehicles that belong to vehicle type A, learns based on the first travel histories to build a first driver model that represents relation between travel situations and behaviors of the vehicles that belong to a first vehicle type, receives second travel histories from vehicles that belong to vehicle type X that is different from vehicle type A, and performs transfer learning in which the second travel histories are used for the first driver model to build a second driver model that represents relation between travel situations and behaviors of the vehicles that belong to vehicle type X.

Abstract: A driving support device as an example of a data processor executes processing for estimating a driving behavior of a vehicle by using a driving behavior model trained based on detection results by a sensor. A detected-information input unit acquires detected information including the detection results. From the detection results included in the detected information input to the detected-information input unit, a selection unit selects a detection result that falls within predetermined selection range narrower than a range detectable by the sensor. A processing unit executes the processing, based on the detection result selected by the selection unit.

Abstract: An image display system includes a first processor, a second processor, and a comparator. The first processor acquires a behavior estimation result of a vehicle, and generates future position information after a predetermined time passes of the vehicle based on the behavior estimation result. The second processor acquires present information about the vehicle, and generates present position information on the vehicle and a peripheral object based on the acquired information. The comparator compares the future position information on the vehicle and the present position information on the vehicle and the peripheral object, and generates present image data indicating present positions of the vehicle and the peripheral object and future image data indicating future positions of the vehicle and the peripheral object. Further, the comparator allows a notification device to display a present image based on the present image data and a future image based on the future image data together.

Abstract: An information processing system includes an incorrectness risk determiner, a safe behavior determiner, and a safety determiner. The incorrectness risk determiner makes a determination on whether or not a behavior estimation result of a vehicle carries an incorrectness risk. The safe behavior determiner classifies parameter values each indicating a travel state of the vehicle into multiple ranges based on travel safety. The safe behavior determiner also determines a safe behavior for the vehicle. By the safe behavior, the travel state of the vehicle is adjusted such that the above parameter values fall under a range with high travel safety. The safety determiner determines a behavior control of the vehicle. When the safety determiner acquires a determination including the incorrectness risk from the incorrectness risk determiner, the safety determiner selects the safe behavior.

Abstract: An information processing system includes a safe behavior determiner, clustering range controller, and safety determiner. The safe behavior determiner classifies parameter values indicating a travel state of a vehicle into multiple ranges based on travel safety. The safe behavior determiner also determines a safe behavior for the vehicle by which the travel state of the vehicle is adjusted such that the parameter values fall under a safety range with high travel safety. The clustering range controller changes a position of a boundary between the ranges according to an external environment of the vehicle. The safety determiner acquires a behavior estimation result of the vehicle and the safe behavior determined by the safe behavior determiner, and determines behavior control of the vehicle on the basis of at least the acquired behavior estimation result or safe behavior.

Abstract: A vehicle-mounted interface device includes a receiver and a determiner. The receiver receives an input from a driver who drives a vehicle. On the basis of the input received by the receiver, the determiner determines whether or not the driver is familiar with a route along which the driver is to drive or is driving the vehicle.

Abstract: An automation level determination section selects one of automation levels defined at a plurality of stages based on a deviation degree of reliability, the deviation degree corresponding to each of a plurality of kinds of driving behaviors that are estimation results obtained using a driving behavior model. A generator generates presentation information by applying the plurality of kinds of driving behaviors to an output template corresponding to one selected automation level in output templates corresponding to the automation levels defined at the plurality of stages respectively. An output unit outputs the presentation information that is generated.

Abstract: A driving support device as an example of a data processor executes processing for estimating a driving behavior of a vehicle by using a driving behavior model trained based on detection results by a sensor. A detected-information input unit acquires detected information including the detection results. From the detection results included in the detected information input to the detected-information input unit, a selection unit selects a detection result that falls within predetermined selection range narrower than a range detectable by the sensor. A processing unit executes the processing, based on the detection result selected by the selection unit.

Abstract: An information processing system that appropriately estimates a driving conduct includes: a detector that detects a vehicle environment state, which is at least one of surroundings of a vehicle and a driving state of the vehicle; a behavior learning unit configured to cause a neural network to learn a relationship between the vehicle environment state detected by the detector and a behavior of the vehicle implemented after the vehicle environment state; and a behavior estimation unit configured to estimate a behavior of the vehicle by inputting, into the neural network that learned, the vehicle environment state detected at a current point in time by the detector.