Provided is a conveying vehicle that ensures efficiently travelling while suppressing vehicle slip. A dump truck 100 includes a vehicle body 101 provided with wheels 103 and a vehicle control device 300 and travels on a travel route. The vehicle control device 300 calculates and stores slip limit values at a plurality of positions on the travel route, reads out the slip limit values to calculate at least one of a maximum acceleration and a maximum deceleration of the dump truck 100 at which the wheels 103 is capable of maintaining a grip state against a road surface, and sets a target travel speed at a travel position between the dump truck 100 and a target position according to a target speed at the target position and at least one of the maximum acceleration and the maximum deceleration.

An advanced driver assistance system for a heavy-duty vehicle. The ADAS includes a road geometry determining device arranged to determine a geometry of a road section in a forward direction ahead of the vehicle, and a vehicle motion management module configured to predict a swept area by the vehicle when driving in the forward direction, based on a geometric model of the vehicle and on a current vehicle control command, wherein the swept area by the vehicle comprises an area traversed by an overhang of the vehicle. The ADAS further includes a display device configured to illustrate the geometry of the road section and the predicted swept area by the vehicle in dependence of the current vehicle control command.

A method of verifying a position of a vehicle using a vehicle-mounted device, the method including generating first position data for the vehicle-mounted device responsive to receiving data from a transponder-based localization system, generating second position data for the vehicle-mounted device responsive to receiving data from another localization system; and reporting verified vehicle position data for the vehicle, based on a comparison of the data from the other localization system with the data from the transponder-based localization system for the vehicle-mounted device.

An unmanned vehicle management device includes an upper limit speed storage unit that stores an upper limit of a traveling speed of an unmanned vehicle on a downhill set based on an inclination angle of the downhill, an input speed acquisition unit that acquires an input value input by an input device, and an output control unit that causes an output device to output upper limit speed data indicating a relationship between the inclination angle and the upper limit, and input speed data generated based on the input value.

A system for detecting distribution of a weight of a payload in a dump body of a vehicle includes first sensors, second sensors, and a controller. The dump body is pivotable about pins to be selectively seated and titled to a frame of the vehicle. The first sensors are arranged between the dump body and the frame, and detect components of the weight of the payload exerted through the dump body when the dump body is seated relative to the frame. The second sensors are arranged correspondingly within the pins, and detect components of the weight of the payload exerted through the dump body. The controller determines a status of payload distribution in the dump body based on the component of the weight of the payload detected by the first sensors and second sensors, and generate a notification to indicate the status of payload distribution.

The present invention discloses a backward anti-collision driving decision-making method for a heavy commercial vehicle. Firstly, a traffic environment model is established, and movement state information of a heavy commercial vehicle and a vehicle behind the heavy commercial vehicle is collected. Secondly, a backward collision risk assessment model based on backward distance collision time is established, and a backward collision risk is accurately quantified. Finally, a backward anti-collision driving decision-making problem is described as a Markov decision-making process under a certain reward function, a backward anti-collision driving decision-making model based on deep reinforcement learning is established, and an effective, reliable and adaptive backward anti-collision driving decision-making policy is obtained. The method provided by the present invention can overcome the defect of lack for research on the backward anti-collision driving decision-making policy for the heavy commercial vehicle in the existing method, can quantitatively output proper steering wheel angle and throttle opening control quantities, can provide effective and reliable backward anti-collision driving suggestions for a driver, and can reduce backward collision accidents.

The invention pertains to a road condition determining system and a method for determining a condition of a road traversed by at least one vehicle. The road condition determining system comprises a vehicle position determination means for determining a position of the vehicle, a calibration parameter detection unit adapted to determine at least one calibration parameter of a part of the vehicle, a vertical acceleration sensor adapted to continuously sense a vertical acceleration of the vehicle, a calculation unit adapted to calculate a road condition value based on the vertical acceleration and on the calibration parameter, and to continuously monitor whether the road condition value exceeds a predefined schedule, and a data transmission unit adapted to provide maintenance data to at least one receiver, the maintenance data comprising at least an information about the vehicle position.

A control system for controlling one or more torque generating devices on a heavy-duty vehicle comprising a primary sensor system with a primary sensor control unit configured to interpret an output signal of the primary sensor system, wherein the primary sensor control unit is configured to determine a first load value associated with the heavy-duty vehicle, and one or more tire sensor devices mounted on one or more tires of the heavy-duty vehicle, and a tire sensor control unit configured to interpret an output signal of the one or more tire sensor devices, wherein the tire sensor control unit is configured to determine a second load value associated with the heavy-duty vehicle, wherein the control system is arranged to base control of the heavy-duty vehicle on the second load value in case of malfunction in the primary sensor system and/or in the primary sensor control unit.

A vehicle sensing system is for being disposed on a vehicle. The vehicle sensing system includes a calculating unit, which includes a turning calculating module and a vehicle dimension dataset. The vehicle dimension dataset includes at least one of a wheelbase, a vehicle width, a front overhang and a rear overhang of the vehicle. The calculating unit is configured to receive a turning dataset of the vehicle. Based on the turning calculating module, the calculating unit is configured to determine an inner front wheel and an inner rear wheel. The calculating unit is configured to further determine a turning alarm zone in accordance with the vehicle dimension dataset and the turning dataset. The turning alarm zone is dependent on at least one of time and the turning dataset.

The present disclosure relates to system for controlling operation of machine. The system includes fatigue detection unit configured to generate a signal indicative of fatigue parameter of an operator of the machine. The system includes proximity sensing unit to capture image of a surrounding area of the machine. The system further includes a controller, configured to determine fatigue condition of the operator and to detect presence of an obstacle in the surrounding area of the machine. The controller is further configured to generate a warning signal based on the fatigue condition of the operator and the captured image of the surrounding area of the machine. The controller is configured to communicate signal indicative of the action of the operator with a control module of the machine. The control module autonomously control operation of the machine based on a signal indicative of the action of the operator.