Provided is a weight estimation system (S) including: a change amount calculation device (2) which acquires a height of a loading platform (N) before loading a vehicle and a height of the loading platform (N) after loading the vehicle and calculates an amount of change between the heights of the loading platform (N) between before and after the loading; and a loaded weight estimation device (4) which estimates a loaded weight on the basis of a correlation between the amount of change and a loaded weight stored in advance.

The invention relates to a method of controlling a working machine. The method includes monitoring a detection region behind the working machine by means of a rear detection device; and determining whether the working machine is traveling forward or in reverse. The method further includes disregarding an object in the detection region detected by the rear detection device when the working machine is traveling forward. The invention also relates to a control system for controlling a working machine having a rear detection device arranged to monitor a detection region behind the working machine. The invention also relates to a working machine.

Aspects and implementations of the present disclosure relate to performance and safety improvements for autonomous trucking systems, including techniques of obtaining an identification of an unfavorable condition on a route of an autonomous vehicle (AV), causing the AV to exit the route, and performing one or more waiting loops until the unfavorable condition is resolved, the AV is rerouted, assistance arrives, and the like.

Systems and methods are disclosed for managing task assignments for a fleet of haul trucks at a mine site. An assignment engine may: receive state data for a haul truck including haul weight data and second state data for the mine site that is indicative of a plurality of available tasks and associated task material weight data; assign a task to the haul truck by inputting the state data into a trained reinforcement-learning model, wherein: the model has been trained to learn an assignment policy that optimizes a reward function, such that the learned policy accounts for vehicle performance variance due to changing vehicle haul weight and/or road conditions; and cause the at least one haul truck to be operated according to the at least one task assignment.

An apparatus for providing a route of an electric vehicle and a method thereof are provided. The apparatus includes a processor that estimates a weight of a vehicle when guiding a user along a route to a destination, calculates a driving load for each route section using the estimated weight of the vehicle, calculates a driving force using motor torque, and determines a probability of hill climbing for each route section using the driving force and the driving load and a display that is controlled by the processor to display at least one of a driving load for each route section or a probability of hill climbing according to a driving force for each route section.

An autonomous vehicle can comprise winter servicing equipment, such as a snowplow, salt spreader, etc. A controller can be supported by the vehicle and can be operatively coupled thereto. The controller can be configured to control the vehicle to autonomously move through an area along a planned route to effect servicing (e.g., snow removal or remediation) of the area. For example, the controller can be configured to discretize the area into a plurality of cells and to determine a quantity of snow in each cell. The route through the area can be planned by the controller based at least in part on simulated movements of the snow quantities in the cells.

A method for avoiding a collision of a vehicle with a potential collision object includes defining a safety zone around the potential collision object. The safety zone is located outside a danger zone around the vehicle. The method further includes predicting a trajectory corridor which is covered by the vehicle along a future trajectory and during a certain time period and performing a safety measure on the vehicle in order to avoid a collision of the vehicle with the potential collision object. The safety measure is performed as a function of a geometric comparison of the predicted trajectory corridor with the defined safety zone.

A scalable tractive power system for vehicles (car, truck, bus, semi-trailer), integrated with all-wheel steering system which leverage synergies between plurality of differently designed electric traction-motors and all-wheel electric steering-motors is configured with plurality of sensors to virtually eliminate wheel-dragging and EPS, as part of virtually 100% dynamic efficiency. A fully automated electronic clutch-system attached to selected electric traction motors is configured to carry out above 90% traction efficiency by coupling to wheels selected electric traction-motors in their high efficiency range of operation, and de-coupling and replacing electric traction-motors with another electric traction-motors while the vehicle is changing speed or when the vehicle requires higher or lower tractive-power, from forward-motion start to top-rated speed of the vehicle. A holistic controller is configured with multi-objective optimization design (MOOD) procedures computing complex variable values and parameters, finding the required trade-off among design objectives, and improving the pertinence of solutions, while complying with NHTSA's ‘fail operational systems’ for steer-by-wire.

The present disclosure relates to a vehicle motion management system as well as a motion support system for a vehicle. The vehicle motion management system and the motion support system are arranged to control operation of at least one actuator configured to apply a torque to at least one wheel of the vehicle. The vehicle motion management system is configured to transmit a control signal indicative of a desired torque and a wheel speed limit to the motion support system, whereby the motion support system is, based on the received signal, configured to transmit an actuator signal to the actuator for the actuator to generate an operating torque on the at least one wheel without exceeding an actuator rotational speed limit.

A fire fighting vehicle includes a chassis, a front axle, a rear axle, an engine, a battery system, an electromagnetic device, an accessory drive, and a controller. The accessory drive is positioned to receive a mechanical input from the engine and the electromagnetic device. The controller is configured to selectively engage a plurality of operational modes including a standby mode and a hybrid mode. According to the standby mode, the controller is configured to operate the electromagnetic device using stored energy stored in the battery system to drive the accessory drive with the engine off. According to the hybrid mode, the controller is configured to operate both the engine and the electromagnetic device.