An apparatus includes at least one camera configured to capture an image of a traffic lane in front of a vehicle. The apparatus also includes a vehicle behavior prediction controller configured to determine lane boundaries and road curvature for a segment of a traffic lane occupied by the vehicle from the captured image and prior captured images; determine lateral distances of the vehicle from the lane boundaries and a rate of departure of the vehicle from the occupied traffic lane that is accurate for the determined road curvature; determine a time to line crossing for the vehicle from the lateral distances and the rate of departure; and activate a lane departure warning indicator based on the determined time to line crossing.

Systems and methods use cameras to provide autonomous navigation features. In one implementation, a method for navigating a user vehicle may include acquiring, using at least one image capture device, a plurality of images of an area in a vicinity of the user vehicle; determining from the plurality of images a first lane constraint on a first side of the user vehicle and a second lane constraint on a second side of the user vehicle opposite to the first side of the user vehicle; enabling the user vehicle to pass a target vehicle if the target vehicle is determined to be in a lane different from the lane in which the user vehicle is traveling; and causing the user vehicle to abort the pass before completion of the pass, if the target vehicle is determined to be entering the lane in which the user vehicle is traveling.

Systems and methods are provided for vehicle navigation. In one implementation, at least one processor may be programmed to receive, from a camera, a captured image representative of features in an environment of the vehicle. The processor may generate a warped image based on the received captured image, which may simulate a view of the features in the environment of the vehicle from a simulated viewpoint elevated relative to an actual position of the camera. The processor may further identify a road feature represented in the warped image, which may be transformed in one or more respects relative to a representation of the road feature in the captured image. The processor may then determine a navigational action for the vehicle based on the identified feature represented in the warped image and cause at least one actuator system of the vehicle to implement the determined navigational action.

An autonomous driving apparatus for generating an intersection path reflecting a driving record may include: a path generating device that generates information on a first path for driving of an autonomous vehicle at an intersection; a path comparison operating device that generates offset information between the generated information on the first path and information on a second path along which the autonomous vehicle is driving; a comparison operation evaluating device that determines whether to store the information on the second path based on the generated offset information; and a comparison operation storage that stores the information on the second path and the offset information based on the determination of whether to store the information on the second path.

A motor-vehicle path-controlling module is arranged to model the path of the vehicle during a change in traffic lane by a Bezier curve relating a value of a parameter to a value of a lateral deviation of the vehicle from the center of a traffic lane and to a value of a time-dependent variable representative of the variation in the change of path; determine a setpoint state vector of a closed feedback loop of a path-controlling device, the loop being designed to control the motor vehicle so that it follows the path modelled by the Bezier curve, the vector being determined on the basis of the lateral deviation, of the time-dependent variable and of the parameter, and transmit the setpoint state vector to the input of the loop.

The present disclosure relates generally to identification of drivable surfaces in connection with autonomously performing various tasks at industrial work sites and, more particularly, to techniques for distinguishing drivable surfaces from non-drivable surfaces based on sensor data. A framework for the identification of drivable surfaces is provided for an autonomous machine to facilitate it to autonomously detect the presence of a drivable surface and to estimate, based on sensor data, attributes of the drivable surface such as road condition, road curvature, degree of inclination or declination, and the like. In certain embodiments, at least one camera image is processed to extract a set features from which surfaces and objects in a physical environment are identified, and to generate additional images for further processing. The additional images are combined with a 3D representation, derived from LIDAR or radar data, to generate an output representation indicating a drivable surface.

A vehicle travel control apparatus includes an information acquiring section; a determining section that determines whether a special road terrain exists; and a speed control section that controls a speed of the subject vehicle. The speed control section is further configured to: when the special road terrain exists but a preceding vehicle does not exist, increase or decrease the speed of the subject vehicle with respect to a pre-set vehicle speed in the energy efficiency zone such that the energy efficiency is improved; and when the special road terrain and a preceding vehicle exists and the speed of the subject vehicle is planned to increase in the energy efficiency zone, control the speed of the subject vehicle in an inter-vehicle distance maintenance zone such that the subject vehicle has an inter-vehicle distance to the preceding vehicle longer than a pre-set inter-vehicle distance.

A method includes identifying mass distribution data of an autonomous vehicle (AV). The mass distribution data is associated with a first load proximate a first distal end of a first axle of the AV and a second load proximate a second distal end of the first axle of the AV. The method further includes determining, based on the mass distribution data, one or more handling maneuver limits for the AV. The method further includes causing the AV to travel a route based on the one or more handling maneuver limits.

A system and method of path planning utilizing a clothoid curve to connect a start point and an end point is provided. The method includes receiving at a path planning system inputs including the start point and the end point of a desired path. The method further includes calculating clothoid parameters for a clothoid curve connecting the start point and the end point based the received start point, the received end point, and a closed-form expression, wherein the closed-form expression is generated based on a relationship between a plurality of unique center point values associated with a plurality of unique clothoid curves and the clothoid parameters associated with each of the plurality of unique clothoid curves. A clothoid curve is generated based on the determined clothoid parameters, wherein the generated clothoid curve represents a planned path from the start point to the end point.

A processor unit (3) is configured for accessing speed data of a second vehicle (18), the speed data generated by a sensor of a first vehicle (1). The processor unit is also configured for creating a driving behavior profile of the second vehicle (18) based on the speed data and making a prediction about the future driving behavior of the second vehicle (18) based on the driving behavior profile of the second vehicle (18). Moreover, the processor unit is configured for determining a trajectory for the first vehicle (1) by executing an MPC algorithm, which includes a longitudinal dynamic model of the first vehicle and a cost function, such that the cost function is minimized. The prediction about the future driving behavior of the second vehicle (18) is taken into account in the determination of the trajectory.