In some embodiments, a range sensor is configured to detect a distance between a portion of a vehicle and an object above the portion of the vehicle. In some embodiments, the detected distance may be presented to an operator to allow the operator to control a height of an adjustable suspension in order to manually control the distance. In some embodiments, the detected distance may be used to automatically control the distance. In some embodiments, the distance may be controlled in order to allow the vehicle to couple to the object, such as a fifth wheel of the vehicle coupling to a kingpin of a trailer.

The invention relates to a method for controlling a vehicle (1), the method comprising—establishing (S1) a plurality of example situations, wherein each example situation is characterized by a plurality of example situation features, including at least a velocity of the vehicle (VS), a velocity change of the vehicle (VCS), and a road inclination (αS), —determining (S2), for each of plurality of the example situations, a example situation cost (CS) dependent on a cost for operating the vehicle in the respective example situation, —subsequently obtaining (S3) topology data, indicative of a topology of a route (RT) to be travelled by the vehicle, —determining (S4-S8, S41), based at least partly on the route topology, and at least a plurality of the example situation costs (CS), a velocity profile (VP) for the vehicle along the route (RT).

Various applications for use of mass estimations of a vehicle, including to control operation of the vehicle, sharing the mass estimation with other vehicles and/or a Network Operations Center (NOC), organizing vehicles operating in a platoon and/or partially controlling the operation of one or more vehicles operating in a platoon based on the relative mass estimations between the platooning vehicles. When vehicles are operating in a platoon, the relative mass between a lead and a following vehicle may be used to scale torque and/or brake commands generated by the lead vehicle and sent to the following vehicle.

A method, a device, and a system for parking a truck accurately in a shore crane area are provided. A vehicle controller transmits a parking request for a truck to be parked. A main controller receives the parking request and acquires real-time point cloud data by scanning one or more lanes crossed by a shore crane using one or more LiDARs. The main controller clusters the real-time point cloud data to obtain a set of point clouds for the truck and applies an Iterative Closest Point algorithm to the set of point clouds and a vehicle point cloud model to obtain a real-time distance from the truck to a target parking space. The vehicle controller controls the truck to stop at the target parking space based on the real-time distance.

A system for avoiding blind spot using accident history information, includes an image sensor configured to provide image information by acquiring a surrounding image of a host vehicle, and a vehicle controller. The vehicle controller is configured to detect, through the image sensor, an adjacent vehicle traveling adjacent to the host vehicle and a license plate of the adjacent vehicle; determine a dangerous level of the blind spot of the adjacent vehicle, based on accident history information of the adjacent vehicle and driver tendency information of a driver of the adjacent vehicle obtained by inquiring about the license plate of the adjacent vehicle, after determining a blind spot range of the adjacent vehicle; and generate a path in which the host vehicle deviates from the blind spot or avoids the blind spot to reduce the dangerous level of the blind spot, based on a traveling situation of the host vehicle.

Image processing techniques are described to receive bounding box information that describes a bounding box located around a detected obj ect in an image, determine one or more positions of one or more reference points on the bounding box, determine, for each reference point, 3D world coordinates of a point of intersection of the reference point and the road surface, and assign the 3D world coordinates of the one or more reference points to a location of the detected object.

A motor vehicle controller performs one or more control and/or monitoring functions. The controller includes a processor which determines a first utilization level of the controller during the motor vehicle's travel mode, and a communication interface which receives program code. The program code defines a new control and/or monitoring function of the controller and/or modifies a control and/or monitoring function of the controller. The processor further determines a second utilization level of the controller in the motor vehicle's standstill mode. The program code is the basis for performing the controller's new control and/or monitoring function and/or the modified control and/or monitoring function of the controller, and take the first and second utilization levels as basis for deciding to perform the controller's new control and/or monitoring function and/or the controller's modified control and/or monitoring function in the vehicle's travel mode. A corresponding method for operating such a controller is also disclosed.

The present invention relates to a method for having a vehicle (100) follow a desired curvature path (C1), said vehicle (100) comprising at least one differential (10, 20, 30) with a differential lock connected to at least one driven wheel axle (40, 50) of said vehicle (100), said method comprising at least the following steps: —providing (S1) information regarding state of said differential lock, said state being either that said differential lock is activated or unlocked, and when said differential lock is activated: —calculating (S2) a yaw moment, M.sub.diff, of said vehicle (100), caused by said differential lock; and —compensating (S3) for a deviation from said desired curvature path (C1) caused by said yaw moment, M.sub.diff, such that a resulting steering angle is equal to or less than a maximum allowed steering angle of said vehicle (100), whereby said compensation is a feed forward compensation. The invention also relates to a control unit, a vehicle, a computer program and a computer readable medium.

The technology relates to autonomous vehicles having articulating sections such as the trailer of a tractor-trailer. Aspects include approaches for tracking the pose of the trailer, including its orientation relative to the tractor unit. Sensor data is analyzed from one or more onboard sensors to identify and track the pose. The pose information is usable by on-board perception and/or planning systems when driving the vehicle in an autonomous mode. By way of example, on-board sensors such as Lidar sensors are used to detect the real-time pose of the trailer based on Lidar point cloud data. The orientation of the trailer is estimated based on the point cloud data, and the pose is determined according to the orientation and other information about the trailer. Aspects also include determining which side of the trailer the sensor data is coming from. A camera may also detect trailer marking information to supplement the analysis.

An embodiment vehicle includes a sensor configured to measure a current acceleration of the vehicle and a controller configured to derive a target acceleration value based on a surrounding environment of the vehicle, derive a first acceleration value based on an acceleration performance of the vehicle, determine a second acceleration value based on a predetermined limit value and the first acceleration value, determine a final target acceleration value based on the target acceleration value and the second acceleration value, and cause the current acceleration of the vehicle to be changed based on the final target acceleration value.