The present invention obtains a controller and a control method capable of appropriately assisting with driving by a rider.

In the controller and the control method according to the present invention, an acquisition section of a controller (60) acquires yaw rate information of a traveling straddle-type vehicle (100), and in a control mode in which behavior control operation to make the straddle-type vehicle (100) automatically decelerate or automatically accelerate is performed, an execution section of the controller (60) changes the behavior control operation according to the yaw rate information.

An electro-mechanical actuation control system includes: a comparator configured to compare a desired vehicular component data to an actual vehicular component data; a controller that is configured to enable control of vehicular components and includes vehicle component controllers; a transmitter configured to remotely transmit input signals to the vehicle; a receiver configured to receive the transmitted input signals from the controller and mounted on the vehicle; an actuator driver configured to receive inputs from the receiver and mounted on the vehicle; an actuator coupled to the actuator driver and configured to be operable in any one of an enabled state and a disabled state caused by the actuator driver; and one or more vehicle components that comprise a drive unit including one of an engine assembly, an electric motor and a combination of the engine assembly and the electric motor.

An electro-mechanical actuation control system includes: a comparator configured to compare a desired vehicular component data to an actual vehicular component data; a controller that is configured to enable control of vehicular components and includes vehicle component controllers; a transmitter configured to remotely transmit input signals to the vehicle; a receiver configured to receive the transmitted input signals from the controller and mounted on the vehicle; an actuator driver configured to receive inputs from the receiver and mounted on the vehicle; an actuator coupled to the actuator driver and configured to be operable in any one of an enabled state and a disabled state caused by the actuator driver; and one or more vehicle components that comprise a drive unit including one of an engine assembly, an electric motor and a combination of the engine assembly and the electric motor.

A vehicle travel assistance system includes a travel assistance control unit, an operation unit, and a travel assistance setting unit. The travel assistance control unit is configured to perform travel assistance in a braking-and-driving-force distribution control mode and an automatic cruise control mode. The travel assistance setting unit supplies, to the travel assistance control unit, setting information of travel assistance in response to the received operation under a condition that the operation received by the operation unit is for selecting the braking-and-driving-force distribution control mode, the travel assistance setting unit automatically supplies setting information of the braking-and-driving-force distribution control mode to the travel assistance control unit regardless of the operation in a case where a speed of the vehicle becomes an automatic deactivation speed or higher and thereafter becomes an automatic reactivation speed or lower.

A vehicle travel assistance system includes a travel assistance control unit, an operation unit, and a travel assistance setting unit. The travel assistance control unit is configured to perform travel assistance in a braking-and-driving-force distribution control mode and an automatic cruise control mode. The travel assistance setting unit supplies, to the travel assistance control unit, setting information of travel assistance in response to the received operation under a condition that the operation received by the operation unit is for selecting the braking-and-driving-force distribution control mode, the travel assistance setting unit automatically supplies setting information of the braking-and-driving-force distribution control mode to the travel assistance control unit regardless of the operation in a case where a speed of the vehicle becomes an automatic deactivation speed or higher and thereafter becomes an automatic reactivation speed or lower.

Provided are systems and methods for controlling a vehicle based on a map that designed using a factor graph. Because the map is designed using a factor graph, positions of the road can be modified in real-time while operating the vehicle. In one example, the method may include storing a map which is associated with a factor graph of variable nodes representing a plurality of constraints that define positions of lane lines in a road and factor nodes between the variable nodes on the factor graph which define positioning constraints amongst the variable nodes, receiving an indication from the road using a sensor of a vehicle, updating positions of the variable nodes based on the indication and an estimated location of the vehicle within the map, and issue commands capable of controlling a steering operation of the vehicle based on the updated positions of the factor nodes.

Methods and systems for autonomous and semi-autonomous vehicle control, routing, and automatic feature adjustment are disclosed. Sensors associated with autonomous operation features may be utilized to search an area for missing persons, stolen vehicles, or similar persons or items of interest. Sensor data associated with the features may be automatically collected and analyzed to passively search for missing persons or vehicles without vehicle operator involvement. Search criteria may be determined by a remote server and communicated to a plurality of vehicles within a search area. In response to which, sensor data may be collected and analyzed by the vehicles. When sensor data generated by a vehicle matches the search criteria, the vehicle may communicate the information to the remote server.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: estimate a slip condition corresponding to at least one vehicle wheel; and generate, via an explicit Nonlinear Model Predictive Control (NMPC) module, control data for operating the at least one vehicle wheel based on the estimated slip condition. The explicit Nonlinear Model Predictive Control (NMPC) module includes a feedforward control module that is configured to generate adjustment data based on the estimated slip condition, wherein the adjustment data modifies the control data.

A system comprises a computer including a processor and a memory. The memory includes instructions such that the processor is programmed to: estimate a slip condition corresponding to at least one vehicle wheel; and generate, via an explicit Nonlinear Model Predictive Control (NMPC) module, control data for operating the at least one vehicle wheel based on the estimated slip condition. The explicit Nonlinear Model Predictive Control (NMPC) module includes a feedforward control module that is configured to generate adjustment data based on the estimated slip condition, wherein the adjustment data modifies the control data.

An agricultural work machine includes a geographic position sensor that detects a geographic location of the agricultural work machine. An in-situ sensor detects a value of a dynamic response characteristic of the agricultural work machine corresponding to the geographic location. A predictive model generator generates a predictive model that models a relationship between the terrain feature characteristic and the dynamic response characteristic based on a value of the terrain feature characteristic in a prior information map at the geographic location and a value of the dynamic response characteristic sensed by the in-situ sensor at the geographic location. A predictive map generator generates a functional predictive dynamic response map of the field, that maps predictive values of the dynamic response characteristic to the different geographic locations in the field, based on the values of the terrain feature characteristic in the prior information map and based on the predictive model.