A system includes a controller comprising at least one processor coupled to a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving information indicative of operation of the vehicle and of a driving condition for the vehicle; determining that a speed of the vehicle is less than a target speed for the vehicle based on the received information; determining, in response to the determination that the speed is less than the target speed, that the lane change and takeover event is at least one of feasible or efficient based on the received information; and providing, in response to the determination regarding the lane change and takeover event, a notification.

A system includes a controller comprising at least one processor coupled to a memory storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising: receiving information indicative of operation of the vehicle and of a driving condition for the vehicle; determining that a speed of the vehicle is less than a target speed for the vehicle based on the received information; determining, in response to the determination that the speed is less than the target speed, that the lane change and takeover event is at least one of feasible or efficient based on the received information; and providing, in response to the determination regarding the lane change and takeover event, a notification.

A vehicle information service implemented on one or more computers of a service provider network implements a first application programmatic interface (API) that allows a client to define inclusion parameters and a sample size for a fleet of vehicles from which vehicle data is to be collected. The vehicle information service also implements a second API that notifies the client when the requested vehicle data has been collected from the vehicle fleet. Additionally, the vehicle information service provides the client access to the collected vehicle data. The vehicle information service manages the collection of the vehicle data from the client defined vehicle fleet without requiring further client involvement and notifies the client when the collection of the vehicle data is complete.

A vehicle information service implemented on one or more computers of a service provider network implements a first application programmatic interface (API) that allows a client to define inclusion parameters and a sample size for a fleet of vehicles from which vehicle data is to be collected. The vehicle information service also implements a second API that notifies the client when the requested vehicle data has been collected from the vehicle fleet. Additionally, the vehicle information service provides the client access to the collected vehicle data. The vehicle information service manages the collection of the vehicle data from the client defined vehicle fleet without requiring further client involvement and notifies the client when the collection of the vehicle data is complete.

Systems and apparatuses include one or more processing circuits comprising one or more memory devices coupled to one or more processors, the one or more memory devices configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to: receive vehicle information including operating conditions and historical vehicle information, develop a vehicle model using a machine learning engine that receives the vehicle information, determine a fleet failure probability based on the vehicle model and fleet information including fleet usage and fleet vehicle types, and determine a predictive maintenance schedule based on the fleet failure probability.

Systems and apparatuses include one or more processing circuits comprising one or more memory devices coupled to one or more processors, the one or more memory devices configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to: receive vehicle information including operating conditions and historical vehicle information, develop a vehicle model using a machine learning engine that receives the vehicle information, determine a fleet failure probability based on the vehicle model and fleet information including fleet usage and fleet vehicle types, and determine a predictive maintenance schedule based on the fleet failure probability.

Systems and methods for live utilization and tracking of vehicular movement producing a fluid representation of the movement of vehicles and means to evaluate vehicle movement/activities relative to response requirements may be provided. Accordingly, real-time evaluations and/or corrections may be made based on this improved tracking of movement/activities. Replay analysis of movement/activities that have already occurred may be provided to evaluate and make adjustments for future responses and activities. Colors and other unique display items may be used to highlight different activities, movements and/or timing for completion within an online mapping application. Layering of different mapping displays also may be provided.

Systems and methods for live utilization and tracking of vehicular movement producing a fluid representation of the movement of vehicles and means to evaluate vehicle movement/activities relative to response requirements may be provided. Accordingly, real-time evaluations and/or corrections may be made based on this improved tracking of movement/activities. Replay analysis of movement/activities that have already occurred may be provided to evaluate and make adjustments for future responses and activities. Colors and other unique display items may be used to highlight different activities, movements and/or timing for completion within an online mapping application. Layering of different mapping displays also may be provided.

A machine is disclosed. The machine may include at least one of a propulsion system or a steering system configured to operate under automatic control in an autonomous mode of the machine; and a controller configured to obtain one or more parameters associated with a task that is to be performed in the autonomous mode, determine an estimated completion time for the task based on the one or more parameters associated with the task, and perform one or more actions based on the estimated completion time for the task.

A machine is disclosed. The machine may include at least one of a propulsion system or a steering system configured to operate under automatic control in an autonomous mode of the machine; and a controller configured to obtain one or more parameters associated with a task that is to be performed in the autonomous mode, determine an estimated completion time for the task based on the one or more parameters associated with the task, and perform one or more actions based on the estimated completion time for the task.