Abstract: Systems and methods for automatically determining, in near real-time, whether a vehicular incident has occurred and for automatically assessing whether the driver of a specific vehicle contributed to that incident. Data related to a specific vehicle is gathered by at least one sensor. The data is then transmitted to a data processing unit, which uses an incident detection module to determine whether an incident occurred. The system may verify that conclusion by sending a message to the vehicle occupant(s). The system may also take actions in response to the incident. If an incident has occurred, the data processing unit can use the vehicle-related data, as well as external data, to assess the contribution of the vehicle's driver. The system may comprise one or more neural networks. The system may also comprise a database for storing the vehicle-related data.

Abstract: Systems and methods for automatic, near real-time detection of an increased risk that a specific vehicle will be imminently involved in an incident, and for taking automatic, near real-time actions to attempt to reduce that risk. At least one sensor gathers data related to a specific vehicle and/or its occupant(s). The data is then transmitted to a data processing unit, which uses a risk factor identification module to detect an increase in the risk that an incident is imminent. If that risk has increased, the system takes at least one preventive action to attempt to reduce that risk. The preventive action is determined using an incident prevention module, and may comprise communicating with the vehicle's driver, with the specific vehicle itself, and/or with external response teams. External data may also be used to identify risk factors. The risk factor identification module may comprise a neural network and/or a database.

Abstract: Systems and methods for automatically determining, in near real-time, whether a vehicular incident has occurred and for automatically assessing whether the driver of a specific vehicle contributed to that incident. Data related to a specific vehicle is gathered by at least one sensor. The data is then transmitted to a data processing unit, which uses an incident detection module to determine whether an incident occurred. The system may verify that conclusion by sending a message to the vehicle occupant(s). The system may also take actions in response to the incident. If an incident has occurred, the data processing unit can use the vehicle-related data, as well as external data, to assess the contribution of the vehicle's driver. The system may comprise one or more neural networks. The system may also comprise a database for storing the vehicle-related data.

Abstract: Systems and methods relating to vehicle damage detection and assessment. An input dataset of data derived from a vehicle is used to determine if at least one component of a vehicle has been damaged. Suitably trained neural networks are used to determine if a component has been damaged as well as the cost of a repair or replacement of the damaged components. The neural networks may be trained using sensor readings, images of damaged and undamaged vehicles, as well as previous repair or replacement costs.