A vehicle includes a chassis, a driveline coupled to the chassis, and a control system. The control system is configured to monitor a condition of at least one of the vehicle, an area around the vehicle, or an operator of the vehicle; and control operation of the driveline based on the condition. Controlling the operation of the driveline includes at least one of limiting a speed at which the driveline drives the vehicle or shutting down the driveline and isolating a component of the driveline.

In one example, a method performed by a processing system including at least one processor includes receiving a plurality of data from an autonomous driving vehicle, presenting the plurality of data in a contextually aware dynamic visual indicator, generating an output that the autonomous driving vehicle is operating improperly based on an analysis of the plurality of data, and transmitting a control signal to the autonomous driving vehicle in response to the output that the autonomous driving vehicle is operating improperly to modify an operation of the autonomous driving vehicle.

The disclosure relates to the process of ascertaining an input variable of a vehicle actuator using a model-based predictive control. According to one exemplary arrangement, a processor unit is designed to access trajectory information and a state data set, which represents a state of surroundings of a vehicle and/or the state of the vehicle and/or a driving state of the vehicle, by an interface. The processor unit carries out a secondary condition algorithm in order to calculate a secondary condition and an MPC algorithm for a model-based predictive control. By carrying out the secondary condition algorithm, a secondary condition is ascertained for the MPC algorithm on the basis of the trajectory information and on the basis of the state data set. By carrying out the MPC algorithm, an input variable is ascertained for an actuator of the vehicle on the basis of the secondary condition. This is carried out in particular such that in a future predicted trajectory, the vehicle follows the specified trajectory with a specified degree of reliability.

A mileage prediction and optimization system (FIG. 1) is disclosed for optimizing the mileage of a vehicle. The mileage prediction and optimization system comprises a prediction and optimization module (300) adapted to determine variation in mileage of the vehicle at least based on the current fuel volume, current speed, current fuel density, the current tire air pressure, the current tire air temperature, current fetched values from an ECU module (700) and the pre-defined mileage data of the vehicle. Further, the prediction and optimization module (300) is adapted to optimize the mileage of the vehicle by reducing variation of fuel density, reducing variation of tire air pressure and informing optimal gear-speed combinations to a user regardless of whether the vehicle is stationary or in motion.

An arithmetic model generation system includes a sensor information acquisition unit, a tire force calculator, and an arithmetic model update unit. The sensor information acquisition unit acquires acceleration of a tire. The tire force calculator includes an arithmetic model for calculating tire force F based on the acceleration, and calculates the tire force F by inputting the acceleration acquired by the sensor information acquisition unit. The arithmetic model update unit compares tire axial force measured by the tire and the tire force F calculated by the tire force calculator, and updates the arithmetic model.

A vehicular collision avoidance system includes a sensor disposed at a vehicle for sensing exterior and forwardly of the vehicle. A processor processes sensor data captured by the sensor to determine the presence of a pedestrian ahead of the vehicle and outside a path of travel of the vehicle. The processor determines a projected path of travel of the pedestrian based on movement of the pedestrian. The processor determines where the forward path of travel of the vehicle intersects the projected path of travel of the pedestrian. The system, responsive at least in part to prediction that the pedestrian will be in the forward path of travel of the vehicle when the vehicle time to intersection elapses, adjusts the speed of the vehicle based at least in part on a driver attentiveness parameter pertaining to a determined attentiveness of a driver of the vehicle.

Operating an autonomous machine using analysis of machine vibration while it is operational. Accelerometers are used to measure the machines vibrations while it is being operated. If the vibrations exceed a predetermined acceleration a controller adjust the velocity of the machine to prevent/reduce further vibrations.

A system for estimating tire parameters for an off-road vehicle in real time, the system including a processing circuit including a processor and memory, the memory having instructions stored thereon that, when executed by the processor, cause the processing circuit to measure a position of the vehicle at a first time, determine, based on the position, motion characteristics of the vehicle, predict, based on the motion characteristics, a position of the vehicle at a second time, measure a position of the vehicle at the second time, and generate a tire parameter associated with the vehicle based on the predicted position and the measured position of the vehicle at the second time.

A road surface determination apparatus includes an acceleration detector and a road surface determination unit. The acceleration detector is configured to detect an acceleration of a vehicle body or a vibration transmission member configured to transmit vibration from a tire to the vehicle body. The road surface determination unit is configured to determine a condition of a surface of a road, using a determination value obtained by extracting a component of a predetermined frequency band from the acceleration detected by the acceleration detector and integrating the component.

A backup control unit for controlling motion of a heavy-duty vehicle during a minimum risk maneuver, where the backup control unit is arranged to receive data indicative of a planned sequence of vehicle control commands from a main vehicle control unit. The backup control unit comprises a first vehicle model configured to map the planned sequence of vehicle control commands into a desired vehicle behavior and is arranged to obtain a measured vehicle behavior from one or more vehicle sensors. Also, the back-up control unit is arranged to determine an adjusted sequence of vehicle control commands based on the planned sequence of vehicle control commands and on a deviation between the desired vehicle behavior and the measured vehicle behavior, and to transmit the adjusted sequence of vehicle control commands to a motion support device, MSD, control unit of the vehicle.