Abstract: A driving information generating section 20 successively generates as driving information diverse types of information indicative of a driving state of a vehicle. A dangerous driving determining section 31 determines whether dangerous driving is underway on the basis of the driving information generated by the driving information generating section 20. A supplementary information acquiring section 32 acquires state supplementary information manually or automatically upon determination of dangerous driving by the dangerous driving determining section 31, and associates the acquired state supplementary information with the result of the determination of dangerous driving. An information communication section 34 transmits the result of the determination of dangerous driving and the state supplementary information to an information management apparatus 40.

Abstract: A driving information generating section 20 successively generates as driving information diverse types of information indicative of a driving state of a vehicle. A dangerous driving determining section 31 determines whether dangerous driving is underway on the basis of the driving information generated by the driving information generating section 20. A supplementary information acquiring section 32 acquires state supplementary information manually or automatically upon determination of dangerous driving by the dangerous driving determining section 31, and associates the acquired state supplementary information with the result of the determination of dangerous driving. An information communication section 34 transmits the result of the determination of dangerous driving and the state supplementary information to an information management apparatus 40.

Abstract: A configuration of selecting content corresponding to the driving situation of a driver and presenting the content to the driver, thereby enabling improvement of the safe driving consciousness of the driver, can be implemented. The configuration includes a situation data acquisition unit that acquires automobile driving situation data, an output content determination unit that determines output content on the basis of the situation data, and a content output unit that outputs the output content determined by the output content determination unit. The output content determination unit determines, as the output content, content including the details of a situation that matches or that is similar to the situation data. The output content determination unit determines, as the output content, content including the details of a risk or an accident in a situation that matches or that is similar to the situation data.

Abstract: A configuration calculates an insurance fee of an automobile insurance considering not only driving behavior data associated with a driver but also an awareness level of the driver concerning driving is achieved. An insurance fee calculation device receives an input of a driving behavior score based on the driving behavior data and a test result of the self-awareness test, and executes an insurance fee calculation process that sets the insurance fee such that the insurance fee decreases from a reference insurance fee in accordance with an increase in a correlation between the driving behavior score and the self-awareness test result, and sets the insurance fee such that the insurance fee increases from the reference insurance fee in accordance with a decrease in the correlation between the driving behavior score and the self-awareness test result.

Abstract: A situation determining section 11 determines a situation of a vehicle on the basis of driving information. A support image setting section 13 sets a support image in accordance with a determination result obtained by the situation determining section 11. A display control section 14 executes display control for displaying the support image set by the support image setting section on a window glass of the vehicle in accordance with the determination result obtained by the situation determining section 11. The support image enables a leading operation for a running route, an emphasis operation for a traffic sign or the like, a visibility lowering operation for an outside-vehicle object that may cause lowering of attentiveness of the driven vehicle, and the like, and driving support can be executed with a natural sense.

Abstract: There is provided an information processing apparatus and an information processing method allowing variations of scenes of various events to be realized in a simulator environment simulating the real world. A reward providing unit provides rewards to a first agent and a second agent taking action in the simulator environment and learning an action decision rule according to the reward for the action. The first agent is provided with the reward in accordance with a prescribed reward definition. The second agent is provided with the reward in accordance with an opposing reward definition opposing the prescribed reward definition, the opposing reward definition causing a resultant reward to be increased in a case where the second agent acts to bring about a situation where the reward for the first agent is reduced and causing a resultant reward to be reduced in a case the reward for the first agent is increased.

Abstract: There is provided a learning apparatus and a learning method that allow a reinforcement learning model to be easily corrected on the basis of user input. A display control section causes a display section to display reinforcement learning model information regarding a reinforcement learning model. A correcting section corrects the reinforcement learning model on the basis of user input to the reinforcement learning model information. The present disclosure can be applied to, for example, a personal computer (PC) and the like that correct a reinforcement learning model on the basis of input from a user and perform reinforcement learning of a movement policy of an agent using the corrected reinforcement learning model.