Systems and methods are provided for determining an optimal point during operation of a hybrid electric vehicle towing a trailer at which the energy that can be recouped through regenerative braking is maximized. Operating conditions or characteristics of the hybrid electric vehicle and the brake characteristics of the trailer are considered in determining the optimal point at which the energy that can be recouped is maximized. At the optimal point at which the energy that can be recouped is maximized, the engine of the hybrid electric vehicle is turned off. Otherwise, the engine of the hybrid electric vehicle is left on.

It is an object of the present invention to provide a technique that makes it possible to estimate a rolling friction coefficient. A friction coefficient estimation apparatus includes an acquisition unit, a determination unit, and an estimation unit. The acquisition unit acquires the number of tire rotations, a rotation vehicle speed, and slip information. The determination unit determines whether a tire slips or not on the basis of the slip information acquired by the acquisition unit. When the determination unit determines that the tire does not slip, the estimation unit estimates the rolling friction coefficient on the basis of the number of tire rotations and the rotation vehicle speed which are acquired by the acquisition unit.

A vehicle, and a method of controlling a vehicle, is capable of selecting a wheel speed that is most appropriate to obtain a speed of the vehicle from among wheel speeds of the vehicle to obtain an accurate speed of the vehicle. The vehicle includes a sensor configured to obtain wheel speed information of at least one wheel. The vehicle also includes a controller configured to select wheel speed information from among the wheel speed information of the at least one wheel based on a driving state of the vehicle and configured to determine a speed of the vehicle based on the selected wheel speed information.

A backend for a hazard detection system comprising: a processor; and a memory in communication with the processor, the memory storing a set of instructions. The set of instructions, when accessed and executed by the processor, cause the processor to: receive vehicle and/or driver data from a vehicle, evaluate the received vehicle and/or driver data, use the evaluation as a basis for detecting a hazard in road traffic, and send the information about the detected hazard to at least one vehicle to warn said vehicle about the hazard.

A method for terminating driving on the road shoulder by a transportation vehicle includes detection by a detection unit that the transportation vehicle is situated at least partially on a road shoulder, determination of a steering intensity of a manual steering maneuver, and assignment of one of at least two predetermined steering codes to the steering maneuver by a computing unit as a function of the steering intensity. An automatic intervention into a transportation vehicle control is carried out as a function of the assigned steering code.

A vehicle control system configured to control a braking operation of a hitch ball to a coupler on a trailer. The system may comprise a vehicle brake control system, a maneuvering system, an image sensor configured to capture an image data, and a velocity sensor. The system may also comprise a vehicle mass sensor configured to detect a vehicle mass and a controller. The controller may be configured to control the maneuvering system of the vehicle along a vehicle path. The controller may also identify a coupler distance based on the image data depicting a coupler of the trailer. The controller may also calculate a stopping distance for the braking operation based on a plurality of braking parameters, wherein the braking parameters comprise the velocity, the break pressure, and the vehicle mass.

The present invention is intended to make it possible to automatically drive a test object without performing pre-learning for a running performance map for each vehicle. There is provided an automatic test object driving device that automatically drives a test vehicle based on a command vehicle speed, and that includes a driving actuator for performing driving operation of the test vehicle, and a driving control unit for controlling the driving actuator. The driving control unit includes a first accelerator map and a second accelerator map each of which indicates a relationship among a vehicle-speed-related value, an acceleration-related value, and an accelerator-depression-amount-related value. The driving control unit uses the first accelerator map to determine an accelerator depression amount corresponding to the command vehicle speed, and uses the second accelerator map to correct the accelerator depression amount by feeding back a vehicle speed and an acceleration of the test vehicle.

A method for predicting, for a motor vehicle traveling on a first road segment, a future coefficient of friction of the vehicle on a second road segment. The method includes steps of obtaining operating parameters of the vehicle and at least one characteristic of the first road segment, of computing an indicator on the basis of the obtained operating parameters of the vehicle, of determining a frictional category of the vehicle according to the value of the computed indicator and of the at least one obtained characteristic of the road segment, of selecting a friction profile of the vehicle on the basis of the determined frictional category, and of determining a coefficient of friction of the vehicle by applying the selected profile to at least one characteristic of the second road segment. A device for implementing the prediction method is also disclosed.

A method includes collecting sensor data from a sensor associated with a vehicle, storing the sensor data in a buffer associated with the sensor, wherein the buffer stores an amount of buffer data, analyzing the sensor data for a proximate event trigger. When the proximate event trigger is not detected, the method includes purging a portion of the sensor data exceeding the amount of buffer data. When the proximate event trigger is detected, the method includes stopping the purging of any of the sensor data and storing the sensor data of the buffer and the sensor data associated with the proximate event trigger and sending the sensor data of the buffer and the sensor data associated with the proximate event trigger to a server.

The present disclosure extends to methods, systems, and computer program products for predicting the movement intent of objects. In one aspect, a mobile robot predicts the movement intent of pedestrians from past pedestrian trajectory data and landmark proximity. In another aspect, a host mobile robot predicts the movement intent of other robots/vehicles using motion analysis models for different driving behaviors, including curve negotiation, zigzagging, rapid acceleration/deceleration, and tailgating. In a further aspect, a mobile robot can self-predict movement intent and share movement intent information with surrounding robots/vehicles (e.g., through vehicle-to-vehicle (V2V) communication). The mobile robot can self-predict future movement by comparing the operating values calculated from the monitored components to the operating limits of the mobile robot (e.g., an adhesion limit between the tires and ground). Exceeding operating limits can be an indication of skidding, oversteering, understeering, or fishtailing.