A method is disclosed. A data set including: (a) identifiers of a set of incidents occurring within a defined geographic region to which at least one service provider responded during a first time period and (b) address data identifying a location within the geographic region of each said incident of the set is retrieved over a network. An instruction to generate a heat map of the incidents occurring within the geographic region during the first time period is received from a user via a user interface generated to a display device. In response to the instruction to generate the heat map, the address data is converted to GPS data. A heat map of an aerial view of the geographic region based on the GPS data is generated. The heat map is displayed to the display device in a user interface.

A computer-implemented method of managing a fleet of autonomous vehicles is provided. The method comprises receiving at least one request for a passenger journey from a client device associated with a passenger and allocating an autonomous vehicle to the passenger from the fleet. Confirmation that the autonomous vehicle has reached the passenger is then received and one or more vehicle status signals are received from the autonomous vehicle. Subsequently, the autonomous vehicle is authorised to proceed with the passenger journey in dependence on the vehicle status signals.

There is provided an information processing system capable of performing driving assistance according to different automated driving levels.

An information processing system according to an embodiment of the present disclosure includes one or more mobile devices capable of setting an automated driving level, and an external network device capable of communicating with the mobile devices. The external network device includes a communication device that communicates with the mobile device, an arithmetic model determination device that determines an arithmetic model corresponding to the automated driving level and provides the arithmetic model to the mobile device via the communication device, and a registration determination device that determines whether or not registration of the automated driving level is possible on the basis of information regarding possession of the arithmetic model, and gives a notification of registration permission to the mobile device via the communication device. The mobile device includes an arithmetic model request unit that requests the arithmetic model from the arithmetic model determination device, and causes the information to be transmitted to the registration determination device when the requested arithmetic model is provided, and a movement control unit that starts movement control based on the automated driving level permitted to be registered when the notification is received from the registration determination device.

An ego vehicle determines an intended maneuver and identifies a first set of agents for coordinating the intended maneuver. The ego vehicle also determines a spatial distance for obtaining a level of communication reliability with the set of agents that is greater than a communication reliability threshold. The ego vehicle further applies the determined spatial distance to a sensor-sharing message. The ego vehicle also transmits the sensor-sharing message to a second set of agents within the determined range. The ego vehicle performs the intended maneuver.

A computer-implemented method for altering an appearance of an electrochromic coating of a vehicle is provided. The method includes determining that a vehicle is a boundary area of a testing zone based on a determined location of the vehicle. The method also includes changing a base appearance of the electrochromic coating of the vehicle to an altered appearance based on the determination that the vehicle is in the boundary area.

A security system includes: an autonomous vehicle; a camera installed in the autonomous vehicle; and a crime determination unit that makes a determination regarding a crime on the basis of an image captured by the camera. The autonomous vehicle is a shared car shared by residents within a region; in response to a request, the autonomous vehicle automatically picks up at the departure point of the residents and automatically moves to the destination of the residents; and the camera take pictures of the moving section to the starting point and the moving section from the starting point to the destination; and the crime determination unit determines a crime based on the images taken in the moving section to the departure point and the moving section from the starting point to the destination.

To enhance identification accuracy for the external environment of a movable object.

Acquired is image data having an image feature (such as area, date and time, and weather) corresponding to a movement scene of the movable object. Learning with the image data is performed to acquire an inference DNN coefficient for identification of the external environment of the movable object from the image data of the movement scene. For example, the external environment is identified on the basis of, for example, semantic segmentation or depth. The inference DNN to which the inference DNN coefficient is set enables accurate identification of the external environment of the movable object from the image data of the movement scene.

A human machine interface control unit as an information presentation control device is used in a vehicle having an autonomous driving function to perform a driving action on behalf of a driver, and controls an information presentation device configured to present information to the driver. The human machine interface control unit includes a permissible action determination unit configured to determine a permissible action that a driver is permitted to take among actions, other than a driving action, to be possibly taken by the driver when the autonomous driving function is implemented, and an information presentation content control unit configured to cause an information presentation device to present information related to a determination result of the permissible action.

At least a method for determining risk behavior of a driver is described. While a vehicle is being driven, data is obtained related to the position and movement of a wireless communications device. The data may indicate the type of behavior exhibited by the driver while the vehicle is being driven.

Methods and devices for using a relationship between activities of different traffic signals in a network to improve traffic signal state estimation are disclosed. An example method includes determining that a vehicle is approaching an upcoming traffic signal. The method may further include determining a state of one or more traffic signals other than the upcoming traffic signal. Additionally, the method may also include determining an estimate of a state of the upcoming traffic signal based on a relationship between the state of the one or more traffic signals other than the upcoming traffic signal and the state of the upcoming traffic signal.