Various embodiments include a method for determining an effective wind speed to which a vehicle is exposed while driving comprising: determining an effective mechanical drive power for the vehicle by measuring the current and voltage at an electric motor and using an efficiency characteristic diagram of the electric motor and accounting for losses in a drive train of the motor vehicle; and calculating the effective wind speed based on the effective mechanical drive power.

Disclosed is a method for controlling engagement of an engine clutch in a hybrid electric vehicle in which an engagement control method of the engine clutch is accurately determined so as to minimize a determination error and a sense of discontinuity caused by conversion of the engagement control method resulting therefrom.

The present disclosure relates to improvements in the stability of work machines. A method for predicting a risk of instability for one or more work machine(s) moving along a route along terrain of a worksite is provided. Ground condition data indicative of the ground condition of the terrain along the route is obtained. Surface topography data indicative of the surface topography of the terrain along the route is obtained. Route data indicative of the route along the terrain is generated. The ground condition data, the surface topography data and the route data are processed to generate risk data indicative of a risk of instability along the route.

A travel control device that is mounted on a vehicle including an electric motor and an internal combustion engine as a power source includes an electronic control unit configured to create a speed profile in which a speed of the vehicle at each time is predicted, approximate the speed profile with a predetermined approximation model and estimate a predicted amount of regenerative energy based on an approximation result, the regenerative energy being energy that is recoverable by regenerative braking of the electric motor, and determine the power source used for traveling based on the predicted amount of the regenerative energy.

A system for adaptive in-drive updating, for a vehicle travelling on a route, includes a controller having a processor and tangible, non-transitory memory. The vehicle is carrying a load. The controller is adapted to obtain one or more dynamic parameters pertaining to the load. A plurality of adaptive predictors is selectively executable by the controller at a timepoint during the route at which a completed portion of the route has been traversed by the vehicle and a remaining portion remains untraversed. The plurality of adaptive predictors includes a speed predictor configured to generate a global speed profile. The plurality of adaptive predictors includes a driving consumption predictor is configured to predict a driving consumption profile for the remaining portion of the route based in part on the dynamic parameter, the route features, the global speed profile, and a past drive consumption.

Methods, systems, and non-transitory computer-readable media estimate coasting behavior of a vehicle; identify a scenario associated with coasting in an environment of the vehicle; and based in part on the coasting behavior, generate a trajectory associated with coasting for the vehicle to move in the scenario.

A flood sensing device includes: an acquiring section that acquires plural types of traveling state data relating to traveling of a vehicle; and a sensing section that senses flooding of a road on which the vehicle travels by using (a) a physical quantity that is estimated on the basis of (i) a vehicle behavior model, which is configured by driving force of the vehicle and traveling resistance that includes air resistance applied to the vehicle, slope resistance applied to the vehicle and rolling resistance applied to the vehicle, and which determines the physical quantity that varies due to the vehicle traveling, and (ii) the plural types of traveling state data of the present time that are acquired by the acquiring section, and (b) the physical quantity that is obtained from the traveling state data of the present time that is acquired by the acquiring section.

A flooding sensing device, including: an acquisition section configured to acquire vehicle model information and plural items of travel state data related to travel of a vehicle; and a detection section configured to select a vehicle behavior model from plural vehicle behavior models that are derived in advance for each vehicle model, the vehicle behavior model corresponding to the vehicle model information and calculates a physical quantity that changes in accordance with travel by the vehicle, the detection section detects flooding of a road on which the vehicle travels, using the physical quantity, which is predicted based on the selected vehicle behavior model and on the current plurality of items of travel state data acquired by the acquisition section, and using the physical quantity, which is obtained from the current plurality of items of travel state data acquired by the acquisition section.

A variety of methods, controllers and algorithms are described for controlling a vehicle to closely follow one another safely using automatic or partially automatic control. The described control schemes are well suited for use in vehicle platooning and/or vehicle convoying applications, including truck platooning and convoying controllers. In one aspect, a power plant (such as an engine) is controlled using a control scheme arranged to attain and maintain a first target gap between the vehicles. Brakes (such as wheel brakes) are controlled in a manner configured to attain and maintain a second (shorter) target gap. Such control allows a certain degree of encroachment on the targeted gap (sometimes referred to as a gap tolerance) before the brakes are actuated. The described approaches facilitate a safe and comfortable rider experience and reduce the likelihood of the brakes being actuated unnecessarily.

Embodiments of this application disclose a vehicle control method and device, where the method includes: calculating a longitudinal force interference compensation torque and a lateral force interference compensation torque of a vehicle when a flat tire occurs in the vehicle; calculating a feedback control torque of the vehicle; determining an additional yaw moment based on the longitudinal force interference compensation torque, the feedback control torque, and the lateral force interference compensation torque; and controlling, based on the additional yaw moment, a wheel in which the flat tire occurs.