A method for adapting a driving behavior of a semi, highly or fully automated vehicle and includes the following steps: receiving passenger compartment data; ascertaining a safety state of at least one vehicle occupant which in particular represents an injury probability of the vehicle occupant in the event of an accident, based on the passenger compartment data; and adapting the driving behavior of the vehicle based on the safety state of the at least one vehicle occupant.

Techniques are discussed for generating and optimizing a trajectory using closed-form numerical integration in route-relative coordinates. A decision planner component of an autonomous vehicle, for example, can receive or generate a reference trajectory, which may correspond to an ideal route for an autonomous vehicle to traverse through an environment, such as a center of a road segment. Lateral dynamics (e.g., steering angles, curvature values of trajectory segments) and longitudinal dynamics (e.g., velocity and acceleration) can be represented in a single algorithm such that optimizing the reference trajectory (e.g., based on loss functions or costs) can substantially simultaneously optimize the lateral dynamics and longitudinal dynamics in a single convergence operation. In some cases, the trajectory can be used to control the autonomous vehicle to traverse an environment.

In response to perceiving a moving object, one or more possible object paths of the moving object are determined based on the prior movement predictions of the moving object, for example, using a machine-learning model, which may be created based on a large amount of driving statistics of different vehicles. For each of the possible object paths, a set of trajectory candidates is generated based on a set of predetermined accelerations. Each of the trajectory candidates corresponds to one of the predetermined accelerations. A trajectory cost is calculated for each of the trajectory candidates using a predetermined cost function. One of the trajectory candidates having the lowest trajectory cost amongst the trajectory candidates is selected. An ADV path is planned to navigate the ADV to avoid collision with the moving object based on the lowest costs of the possible object paths of the moving object.

An autonomous vehicle automatically implements a lane change in dense traffic condition. A minimum distance gap between the vehicle and a vehicle in front of the present vehicle is calculated for an autonomous vehicle, along with a best trajectory for changing lanes into a left adjacent lane or changing lanes into a right adjacent lane. The left or right lane change is triggered by the driver or the global planner that navigates the vehicle. During the next cycle, pre-calculated information is utilized by a planning module to determine the final speed of the trajectory to complete the final planning trajectory for the lane change.

A vehicle control system includes: a driving operation device provided in a vehicle and configured to accept a driving operation by a user; an operation terminal configured to be carried by the user and including an input/output unit configured to accept an input by the user and to output a signal; and a control device configured to control traveling of the vehicle based on a signal from the driving operation device and to execute remote parking processing to move the vehicle to a parking position based on a signal from the operation terminal. When the control device detects the driving operation based on a signal from the driving operation device during the remote parking processing, the control device executes suspension processing to stop the vehicle and to make the input/output unit notify that the driving operation device has been operated.

A system and method for controlling a balance of a moving motor vehicle whose pitching motion when overcoming an unevenness of the road is corrected by means of an acceleration and/or a deceleration of the vehicle by a value correlated to a level of unevenness of the road. The level of unevenness is detected by monitoring the road ahead of the moving vehicle and the pitching motion is predictively corrected based on such monitoring.

A method for processing point clouds having variable spatial distributions of scan lines includes receiving a point cloud frame generated by a sensor configured to sense an environment through which a vehicle is moving. The point cloud frame includes scan lines arranged according to a particular spatial distribution. The method also includes either generating an enhanced point cloud frame with a larger number of points than the received point cloud frame, or constructing, by one or more processors and based on points of the received point cloud frame, a three-dimensional mesh. The method also includes generating, by performing an interpolation function on the enhanced point cloud frame or a virtual surface provided by the three-dimensional mesh, a normalized point cloud frame, and generating, using the normalized point cloud frame, signals descriptive of a current state of the environment through which the vehicle is moving.

A method for automatically activating a brake application in a vehicle includes using at least one detection device, detecting at least one object in the environment of the vehicle and, using at least one processor, determining that a vehicle is on a collision course with the at least one object, determining an S-shaped avoidance trajectory of the vehicle and at least one avoidance criterion based at least in part on the S-shaped avoidance trajectory, determining two extreme values of a transverse acceleration of the vehicle from the S-shaped avoidance trajectory, determining whether the at least one avoidance criteria is fulfilled by comparing the two extreme values with a threshold value, wherein the avoidance criteria is fulfilled when the two extreme values fall below the threshold value, and activating an automatic brake application in the vehicle when an activation criterion for the automatic brake application is fulfilled.

A method for processing point clouds having variable spatial distributions of scan lines includes receiving a point cloud portion corresponding to an object in a vehicle environment, the point cloud portion including scan lines arranged according to a particular spatial distribution. The method also includes constructing a voxel grid corresponding to the received point cloud portion. The voxel grid includes a plurality of volumes in a stacked, three-dimensional arrangement, and constructing the voxel grid includes (i) determining an initial classification of the object, (ii) setting one or more parameters of the voxel grid based on the initial classification, and (iii) associating each volume of the plurality of volumes with an attribute specifying how many points, from the point cloud portion, fall within that volume. The method also includes generating, using the constructed voxel grid, signals descriptive of a current state of the environment through which the vehicle is moving.

It is an object of the present invention to switch driving modes smoothly and ensure that a passenger understands driving operations controlled in the relevant driving mode and necessary driving operations. An autonomous driving control apparatus capable of switching between a manual driving mode which requires driving operation by a passenger of a vehicle, and an autonomous control mode which does not require the driving operation by the passenger of the vehicle is provided, wherein the autonomous driving control apparatus includes: an autonomous driving control unit that controls the vehicle in the autonomous control mode; and an information notification unit that gives notice to the passenger of the vehicle, wherein when the driving operation by the passenger is required after switching from the autonomous control mode to the manual driving mode, the autonomous driving control unit performs first notice control to cause the information notification unit to give notice that the driving operation by the passenger is required.