A method and an apparatus for monitoring a motorcycle. Based on the acceleration-relevant data, a vehicle motion and a vehicle position in three-dimensional space are estimated. The vehicle position in space is analyzed and is evaluated as a normal or a critical riding state. A detection direction of a sensor unit is predefined in such a way that in an upright normal resting position of the motorcycle the detection direction lies in a horizontal plane, and the detected acceleration-relevant data encompass a first acceleration component in a longitudinal vehicle direction and a second acceleration component in a transverse vehicle direction. A riding state evaluated as critical is plausibilized with the estimated vehicle motion in order to recognize a critical resting position after an accident. An emergency call is generated when a critical resting position after an accident is recognized.

A method and an apparatus for monitoring a motorcycle. Based on the acceleration-relevant data, a vehicle motion and a vehicle position in three-dimensional space are estimated. The vehicle position in space is analyzed and is evaluated as a normal or a critical riding state. A detection direction of a sensor unit is predefined in such a way that in an upright normal resting position of the motorcycle the detection direction lies in a horizontal plane, and the detected acceleration-relevant data encompass a first acceleration component in a longitudinal vehicle direction and a second acceleration component in a transverse vehicle direction. A riding state evaluated as critical is plausibilized with the estimated vehicle motion in order to recognize a critical resting position after an accident. An emergency call is generated when a critical resting position after an accident is recognized.

Disclosed is a vehicle fuel economy evaluation method based on data analysis. The method combines data processing and a fuel model with an enhanced learning mechanism to predict fuel consumption, analyze driving behavior and output an improvement suggestion. With continuous enhanced learning and long-term dynamic improvement, the model will be able to predict economic fuel consumption in an increasingly accurate way, along with specific and intuitive driving behavior suggestions to help drivers to drive economically.

Disclosed is a vehicle fuel economy evaluation method based on data analysis. The method combines data processing and a fuel model with an enhanced learning mechanism to predict fuel consumption, analyze driving behavior and output an improvement suggestion. With continuous enhanced learning and long-term dynamic improvement, the model will be able to predict economic fuel consumption in an increasingly accurate way, along with specific and intuitive driving behavior suggestions to help drivers to drive economically.

Vehicle controller circuitry for a subject vehicle to determine vehicle constraints including predicted values for vehicle speed of at least one other vehicle and predicted values of for vehicle position of the at least one other vehicle relative to the subject vehicle, wherein the vehicle constraints are determined at predetermined time steps (k) over a time horizon (Th).

Vehicle controller circuitry for a subject vehicle to determine vehicle constraints including predicted values for vehicle speed of at least one other vehicle and predicted values of for vehicle position of the at least one other vehicle relative to the subject vehicle, wherein the vehicle constraints are determined at predetermined time steps (k) over a time horizon (Th).

A driving force control device changes, when shifted to the manual driving mode, the driving force from a driving force generated in an automated driving mode to a driving force generated in a manual driving mode. Further, when the manual driving mode is shifted to the automated driving mode, the driving force is controlled based on an override driving force characteristic specifying the target acceleration according to the vehicle speed, the accelerator pedal position, and a traveling resistance to the vehicle, and when a driving mode is switched to the manual driving mode during the automated driving mode in which the driving force is controlled based on the override driving force characteristic, the control of the driving force based on the override driving force characteristic is continued for a predetermined period after the switching to the manual driving mode.

A driving force control device changes, when shifted to the manual driving mode, the driving force from a driving force generated in an automated driving mode to a driving force generated in a manual driving mode. Further, when the manual driving mode is shifted to the automated driving mode, the driving force is controlled based on an override driving force characteristic specifying the target acceleration according to the vehicle speed, the accelerator pedal position, and a traveling resistance to the vehicle, and when a driving mode is switched to the manual driving mode during the automated driving mode in which the driving force is controlled based on the override driving force characteristic, the control of the driving force based on the override driving force characteristic is continued for a predetermined period after the switching to the manual driving mode.

A method for measuring a slope angle of a vehicle includes, by a controller: determining whether or not a speed of the vehicle is 0 based on a speed signal received from a vehicle speed sensor of the vehicle; measuring an extremal value measured first, an extremal value measured second, and an extremal value measured third among extremal values of an output signal of an acceleration sensor detecting a signal corresponding to the slope angle of the vehicle when the speed of the vehicle is 0; verifying whether or not the measured three extremal values satisfy conditions of the extremal values based on reference conditions of each of the extremal values; estimating a steady state value of the output signal of the acceleration sensor, based on the extremal values measured first and second among the verified three extremal values and a dynamic characteristic parameter of the vehicle or based on the verified three extremal values; and converting the steady state value into the slope angle of the vehicle. The output signal of the acceleration sensor has a damped free vibration waveform.

A method for measuring a slope angle of a vehicle includes, by a controller: determining whether or not a speed of the vehicle is 0 based on a speed signal received from a vehicle speed sensor of the vehicle; measuring an extremal value measured first, an extremal value measured second, and an extremal value measured third among extremal values of an output signal of an acceleration sensor detecting a signal corresponding to the slope angle of the vehicle when the speed of the vehicle is 0; verifying whether or not the measured three extremal values satisfy conditions of the extremal values based on reference conditions of each of the extremal values; estimating a steady state value of the output signal of the acceleration sensor, based on the extremal values measured first and second among the verified three extremal values and a dynamic characteristic parameter of the vehicle or based on the verified three extremal values; and converting the steady state value into the slope angle of the vehicle. The output signal of the acceleration sensor has a damped free vibration waveform.