Abstract: A system may determine an initial safety prediction for a driver or rider associated with a shared mobility service. Then the system may receive, from various sensors, sensor data collected during operation of a vehicle. The system may determine a subset of the sensor data related to one or more shared mobility statuses, then determine, based on the subset of the sensor data, a safety score for the driver and/or rider. The system may further perform operations based on the safety score and/or the initial safety prediction.

Abstract: Systems and method are described for receiving, by a computing platform, information about a first user of a shared mobility service, generating, based on the information about the first user, a first user profile comprising one or more first user attributes, comparing the one or more first user attributes to one or more second user attributes of a second user profile associated with a second user of the shared mobility service, and based on the comparison, causing a vehicle carrying the second user to pick up the first user.

Abstract: Systems and apparatuses for using machine learning to generate a safety output are provided. In some examples, data may be received from a plurality of sources, may be analyzed and one or more machine learning datasets may be generated based on the analyzed data. In some arrangements, data may be received from one or more vehicles. The vehicles may be autonomous, semi-autonomous, or non-autonomous, and/or configured to operate in one or more of those modes. The data may be evaluated based on the one or more machine learning datasets to determine a safety output associated with the data. The safety output may then be used to classify the data and/or to generate one or more instructions for operation of an autonomous vehicle. The instruction(s) may be transmitted to the autonomous vehicle and may modify operation of the vehicle (e.g., to improve safety associated with the vehicle).