According to one embodiment, a method, computer system, and computer program product for cloud integration for autonomous vehicles is provided. An embodiment may include receiving a location for the autonomous vehicle from a global positioning system, may also include determining a rule area in which the autonomous vehicle is located based on the received location, may include identifying a traffic rule set associated with the determined rule area, may also include, in response to determining that the identified traffic rule set is not available for the determined rule area, transmitting a manual mode alert to a user, and may include enabling a manual mode in the autonomous vehicle.

A method for controlling revolutions per minute (RPM) flare, in which an RPM of a transmission increases due to clutch slip, for a hybrid vehicle can include: determining whether gear-shifting is performed in a transmission of the hybrid vehicle; detecting whether RPM flare of the transmission occurs when it is determined that the gear-shifting is performed; and controlling a torque of a motor of the hybrid vehicle so as to reduce the RPM flare of the transmission by reducing the torque of the motor when the RPM flare of the transmission is detected.

A vehicle control method and system includes: acquiring a face image of a user currently requesting to use a vehicle; acquiring a feature matching result between the face image and at least one pre-stored face image in a data set of the vehicle, where the data set stores pre-stored face images of at least one pre-recorded user allowed to use the vehicle; and if the feature matching result indicates that the feature matching is successful, controlling actions of the vehicle to allow the user to use the vehicle. The rights of pre-recorded personnel can be guaranteed based on feature matching, and feature matching can be achieved without a network, thereby overcoming the dependency on the network and further improving the safety guarantee of the vehicle.

An exemplary method for detecting a lateral oscillation of a vehicle includes monitoring yaw rate data and lateral acceleration data of the vehicle, analyzing the yaw rate and lateral acceleration data to generate a yaw rate signal energy distribution and a lateral acceleration signal energy distribution, determining whether a series of conditions are satisfied; and if the conditions are satisfied, automatically controlling the actuator to reduce the lateral oscillation of the vehicle. In some examples, the series of conditions includes the detection of spikes in the yaw rate and lateral acceleration data at approximately the same frequency, a magnitude of the spikes exceeding a first threshold, and a phase shift between the yaw rate and lateral acceleration data exceeding a second threshold.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, the operating status of the features, the identity of a vehicle operator, risk levels for operation of the vehicle by the vehicle operator, or damage to the vehicle may be determined based upon sensor or other data. According to further aspects, decisions regarding transferring control between the features and the vehicle operator may be made based upon sensor data and information regarding the vehicle operator. Additional aspects may recommend or install updates to the autonomous operation features based upon determined risk levels. Some aspects may include monitoring transportation infrastructure and communicating information about the infrastructure to vehicles.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, vehicle operation safety may be enhanced. An environmental or weather condition (e.g., hail, storm, wind) may be identified that presents a hazard to an autonomous or semi-autonomous vehicle. With the customer's permission, when it is determined that the vehicle is parked in an unprotected location, a protected or covered location to park the vehicle may be identified, a route to that location may be determined, and the vehicle may be directed to travel automatically to the protected location under the operation of autonomous operation features. Insurance discounts or cost savings may be provided to risk averse insurance customers based upon the self-parking functionality that will reduce or mitigate damage to insured vehicles caused by adverse conditions, falling trees or power lines, hail, etc.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for generating or updating usage-based insurance policies for autonomous or semi-autonomous vehicles may be provided. A request to generate an insurance quote may be received via wireless communication, and with the customer's permission, risk levels associated with intended usage by the customer of an autonomous or semi-autonomous vehicle may be determined. An insurance policy may be adjusted based upon the risk levels and the intended vehicle usage. The insurance policy may then be presented on the customer's mobile device for review and approval. In some aspects, the vehicle may be rented, and the intended vehicle usage is measured in distance or duration of vehicle operation. Insurance discounts may be provided to risk averse vehicle owners based upon low risk levels.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having one or more autonomous or semi-autonomous operation features are provided. According to certain aspects, a computer-implemented method for real-time determination of the status of autonomous operation features of an autonomous or semi-autonomous vehicle may be provided. With the customer's permission, the operation of the autonomous or semi-autonomous vehicle may be monitored to obtain operating data from one or more autonomous operation features. An operating status of the autonomous features may be determined based upon the operating data. After which, a change in the operating status of the autonomous features may be identified, and a report containing information regarding the change in the operating status of the autonomous features may be generated. Insurance discounts may be provided to risk averse customers that maintain their autonomous vehicles, and associated accident avoidance functionality, in good working condition.

Methods and systems for monitoring use, determining risk, and pricing insurance policies for a vehicle having autonomous or semi-autonomous operation features are provided. According to certain aspects, with the insurance customer's permission, operation of an autonomous (or semi-autonomous vehicle) by a vehicle operator may be monitored. Based upon vehicle and/or other data analysis, an identity of the operator may be determined, and operating data regarding the autonomous or semi-autonomous vehicle while the operator at least partially controls the autonomous vehicle may be monitored. A vehicle operator profile that includes information regarding an operating style of the vehicle operator based upon the operating data may be determined. Risk levels associated with operation of the autonomous vehicle based upon the information regarding the vehicle operator's operating style may be determined. Insurance discounts may be provided to risk averse vehicle owners and/or operators, or those that utilize vehicle risk mitigation or prevention technology.

An agricultural prime mover, such as a tractor, may be used to execute an agricultural work process. The agricultural prime mover includes work assemblies that can be adjusted with machine parameters, and can be coupled to an attachment for processing a field. The agricultural prime mover includes a control and regulation module that optimizes the work assemblies by ascertaining machine parameters for the work assemblies using optimization data with respect to at least one objective. The control and regulation module executes a multi-step optimization strategy, including a first step at the farm directed to optimizing a basic configuration of the agricultural prime mover, a second step at the field directed to optimizing an attachment-specific configuration of the agricultural prime mover, and a third step in the field directed to optimizing the adaptation of the basic configuration and the attachment-specific configuration while processing the field.