A method for providing a prediction of a radius of a motorcycle turn, the method may include determining that the motorcycle is about to turn; predicting values of multiple radius of turn impacting (RTI) parameters; wherein the multiple RTI parameters are selected out of a group of parameters, wherein the selection was made during a machine learning training process, and the group of parameters comprises motorcycle kinematic parameters; determining, based on the determined values of the multiple RTI parameters, the estimated radius of the motorcycle turn; and performing a driving related operation based on the estimated radius of the motorcycle turn.

An apparatus for determining bicycle pedaling may include a sensor that detects the angular velocity and position of a drivetrain or rear sprocket assembly of the bicycle and a processor that is configured to compare the detected values against values indicative of at least one pedaling state. The apparatus may be configured to be housed within a component of the bicycle, such as within a hollow opening of the spindle or crank axle. The apparatus also may include a wireless transmitter to communicate with another component, such as a suspension controller.

An embodiment of the invention provides a method and system including a sensor on a vehicle and a processor connected to the sensor. The processor determines a probability of falling based on input from the sensor, whether the probability of falling exceeds a threshold, and a state of an operator of the vehicle. An actuator connected to the processor receives a signal from the processor when the probability of falling exceeds the threshold and when the state of the operator includes an impaired state. Stabilizer wheels are connected to the actuator, where the signal includes a command to deploy the stabilizer wheels.

A method for classifying an accident event of a two-wheeled vehicle, in particular a bicycle. The method is able to run as an algorithm on a device having an evaluation unit in order to indicate to the driver of the two-wheeled vehicle or to a third party a collision or fall of the two-wheeled vehicle with the aid of correspondingly generated and/or transmitted information. The device may be used for a two-wheeled vehicle such as a bicycle and in particular for an electric bicycle. The use is naturally also possible for a motorcycle or some other single-track vehicle.

A bicycle component is provided other than a rear derailleur and a drive unit. The bicycle component includes an electrical part, a rechargeable power source and a non-contact charging portion. The rechargeable power source is electrically connected to the electrical part. The non-contact charging portion is configured to wirelessly receive external electric power and to supply the external electric power to the rechargeable power source. A non-contact charging method is also provided for charging the rechargeable power source of the bicycle component.

Position indicating devices, systems and methods useable for signaling the positions of pedestrians or vehicles.

A telescopic apparatus comprises a first tube, a second tube, and a non-contact detector. The second tube is configured to be telescopically received in the first tube. The non-contact detector is provided inside at least one of the first tube and the second tube configured to detect a position of the second tube relative to the first tube.

A telescopic apparatus comprises a first tube, a second tube, and a non-contact detector. The second tube is configured to be telescopically received in the first tube. The non-contact detector is provided inside at least one of the first tube and the second tube configured to detect a position of the second tube relative to the first tube.

An electronic device includes an artificial intelligence processor that is configured to generate second information for controlling an electric component including at least one of a drive unit that applies propulsion force to a human-powered vehicle, an electric adjustable seatpost, and an electric suspension in accordance with first information related to at least one of the human-powered vehicle, a rider of the human-powered vehicle, and an environment of the human-powered vehicle. The artificial intelligence processor changes a process for generating the second information in accordance with the first information and in accordance with an operation of a first operation unit for operating the at least one of the drive unit, the electric adjustable seatpost, and the electric suspension.

A human-powered vehicle control device includes an artificial intelligence processor, an operation device, and a communication device. The artificial intelligence processor is configured to generate second information for controlling an electric component of a human-powered vehicle in accordance with first information related to at least one of the human-powered vehicle, a rider of the human-powered vehicle, and an environment of the human-powered vehicle. The operation device operates the electric component. The communication device is configured to communicate with an external device. The artificial intelligence processor is configured to change a process for generating the second information in accordance with the first information and an operation of the operation device. The communication device is configured to transmit third information related to a process for generating the second information to the external device.