A vehicle control device includes a detecting unit that detects a towing state of a subject vehicle, a recognizing unit that recognizes surrounding situations of the subject vehicle, a control unit that performs automatic control in which at least one of acceleration-and-deceleration and steering of the subject vehicle is automatically controlled on the basis of the surrounding situations of the subject vehicle recognized by the recognizing unit, and a changing unit that changes, if the detecting unit has detected that the subject vehicle is in a state of towing an object, details of control performed by the control unit in such a manner that it is less likely to perform the automatic control than in the case where the detecting unit has not detected that the subject vehicle is in a state of towing an object.

A vehicle operable to pull a trailer comprising a payload is provided, that includes a plurality of sensors configured to capture sensor data related to the vehicle, the trailer, or both, and a controller configured to (i) receive the sensor data from the plurality of sensors, (ii) determine, based on the sensor data, one or more parameters associated with the trailer, the payload, or both, (iii) update, based on an analysis of the one or more parameters, a confidence level associated with an operation of the vehicle with the trailer and the payload, and (iv) based on the confidence level, responsively execute an autonomous control strategy comprising one or more adjustments to the operation of the vehicle.

A dimension calculation system in a host vehicle for dynamically calculating a vehicle dimension using solar shadow information is disclosed. The system is configured to: calculate solar position and an expected vehicle shadow based on geocode location, time and vehicle dynamics; detect an actual vehicle shadow in an image from a vehicle camera; compare the actual vehicle shadow to an expected vehicle shadow; determine a dimension profile and max height point for a vehicle plus vehicle cargo based on a comparison of the actual vehicle shadow to the expected vehicle shadow; calculate a confidence level for the dimension profile and max height point for the vehicle plus cargo; and use the dimension profile and max height point to provide one or more dimension notifications when the confidence level for the dimension profile and max height point for the vehicle plus cargo are above a first threshold level.

The vehicle 1 includes a tow vehicle 2 and a loading platform 3. The loading platform 3 includes a ROM 23 storing loading platform information including a loading platform type and a plurality of first external sensors 8 that detect an object around the loading platform 3. The tow vehicle 2 acquires the loading platform type from the loading platform 3 and includes an ADAS ECU 10 that performs a driving assist of the vehicle 1 based on the acquired loading platform type and a plurality of second external sensors 9 that detect an object around the tow vehicle 2. The ADAS ECU 10 converts the acquired detection data of each of the first external sensors 8 from a sensor coordinate system of each first external sensor to a loading platform coordinate system, further converts from the loading platform coordinate system to the tow vehicle coordinate system, integrates detection data of the first external sensor 8 and detection data of the second external sensor 9 into the tow vehicle coordinate system, and calculates the relative position and the relative speed of the detected object based on the integrated detection data.

An autonomous vehicle is provided that includes one or more sensors coupled to the autonomous vehicle, and a computing device configured to: (i) receive, from the one or more sensors, operational data related to an operation of the autonomous vehicle, (ii) receive geographical data related to an anticipated route of the autonomous vehicle, (iii) generate, for the anticipated route and based on the operational data and the geographical data, an operational response model representing respective operational constraints for one or more operational parameters of the autonomous vehicle, wherein values for the one or more operational parameters are represented along coordinate axes of a geometrical shape, and wherein the one or more operational parameters are mutually coupled to each other, and (iv) responsively execute, based on the operational response model, an autonomous control strategy comprising one or more adjustments to the operation of the vehicle within the respective operational constraints.

Example embodiments relate to lane adjustment techniques for slow lead agents. A vehicle computing system may use sensor data depicting the surrounding environment to detect when another vehicle is traveling in front of the vehicle at a speed that is less than a threshold minimum speed. If the other vehicle fails to increase speed above the minimum speed, the computing system may determine whether to change lanes to avoid the other vehicle based on speed data for other lanes. In some implementations, the computing system assigns penalties to lane segments surrounding the vehicle based on speed data for the different lane segments. For instance, the path finding system for the vehicle can use penalties and speed data to determine efficient routes that safely circumvent slow agents.

Example embodiments relate to lane adjustment techniques for slow lead agents. A vehicle computing system may use sensor data depicting the surrounding environment to detect when another vehicle is traveling in front of the vehicle at a speed that is less than a threshold minimum speed. If the other vehicle fails to increase speed above the minimum speed, the computing system may determine whether to change lanes to avoid the other vehicle based on speed data for other lanes. In some implementations, the computing system assigns penalties to lane segments surrounding the vehicle based on speed data for the different lane segments. For instance, the path finding system for the vehicle can use penalties and speed data to determine efficient routes that safely circumvent slow agents.

According to a method for assisting reverse driving of a combination (1), an actual value for a hitch angle of the combination (1) is determined by a computing unit (6) depending on sensor data generated by a hitch angle sensor. A hitch length of a trailer (3), given by a distance between a trailer body (11) and a hitch (7) of a vehicle (2), is determined depending on environmental sensor data of the combination (1). A collision value for the hitch angle is determined by the computing unit (6) depending on the hitch length, and the safety measure is triggered by the computing unit (6) depending on the actual value and the collision value for the hitch angle.

Embodiments are presented herein for a panable camera with trailer length and object detection for vehicles equipped with cameras to supplement or replace mirrors commonly used today. In one embodiment, a vehicle controller is provided comprising: one or more processors; a non-transitory computer-readable medium; and program instructions stored on the non-transitory computer-readable medium. The program instructions, when executed by the one or more processors, cause the one or more processors to: cause a side-view camera on a tractor to capture image(s) of leading, lower, upper and/or trailing edges of a trailer coupled with the tractor; and estimate a length of the trailer based on the image(s) captured by the side-view camera. Other embodiments are provided.

An assistance system for an at least partially autonomously operated motor vehicle includes a detection device configured to record a trajectory of the motor vehicle during forward movement from a starting point to an endpoint within the vehicle's environment. An electronic computing device within the system determines a further trajectory based on the recorded trajectory for a future reverse movement of the motor vehicle from the starting point to the endpoint. The assistance system utilizes the further trajectory for future autonomous driving. Additionally, the system includes a computer program product associated with the assistance system.