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.

A method for controlling a vehicle active chassis power system includes determining, via a processor, a minimum output voltage/current threshold for an aggregated power supply associated with an active chassis operation, and generating an aggregate State of Function (SoF) indicative of a maximum voltage/current budget for an output of the vehicle active chassis power system. The aggregate SoF is based on a primary power source voltage/current output and a power storage voltage/current output. The method further includes causing to control an active chassis power system actuator based on a minimum voltage/current value associated with the aggregate SoF. Causing to control the active chassis power system actuator can include publishing the aggregate SoF to a braking actuator, a steering actuator, or to a domain controller that actively distributes an aggregated power supply capability SoF to a braking actuator and a steering actuator based on one or more present vehicle states.

Techniques for determining a vehicle action and controlling a vehicle to perform the vehicle action for navigating the vehicle in an environment can include determining a vehicle action, such as a lane change action, for a vehicle to perform in an environment. The vehicle can detect, based at least in part on sensor data, an object associated with a target lane associated with the lane change action sensor data. In some instances, the vehicle may determine attribute data associated with the object and input the attribute data to a machine-learned model that can output a yield score. Based on such a yield score, the vehicle may determine whether it is safe to perform the lane change action.

A vehicle traveling control apparatus includes a detector that detects an accelerator operation amount by a driver, a determiner that determines, based on a driving condition, whether a driving mode is currently a first mode in which a vehicle is caused to travel autonomously along a target travel path or a second mode in which the driver performs driving operation, a calculator that calculates a continuation time of the first mode when the driving mode is the first mode, a first setting unit that variably sets a characteristic of a target acceleration for the detected accelerator operation amount based on the calculated continuation time, and a second setting unit that, when the driving mode has transitioned from the first mode to the second mode, sets the target acceleration for the detected accelerator operation amount by referring to the set characteristic of the target acceleration for the accelerator operation amount.

A vehicle travel control device executes vehicle travel control such that a vehicle follows a target trajectory. An automated driving control device generates a first target trajectory that is the target trajectory for automated driving of the vehicle. The vehicle travel control device further determines whether or not an activation condition of travel assist control is satisfied. When the activation condition is satisfied, the vehicle travel control device generates a second target trajectory that is the target trajectory for the travel assist control. When the second target trajectory is generated during the automated driving, the vehicle travel control device determines whether or not a cancellation condition is satisfied. When the cancellation condition is satisfied, the vehicle travel control device cancels both the first target trajectory and the second target trajectory, and decelerates the vehicle.

A vehicle travel control device executes vehicle travel control such that a vehicle follows a target trajectory. An automated driving control device generates a first target trajectory that is the target trajectory for automated driving of the vehicle. The vehicle travel control device further determines whether or not an activation condition of travel assist control is satisfied. When the activation condition is satisfied, the vehicle travel control device generates a second target trajectory that is the target trajectory for the travel assist control. When the second target trajectory is generated during the automated driving, or when the second target trajectory is generated during the automated driving and a priority condition for giving priority to the second target trajectory is satisfied, the vehicle travel control device executes the vehicle travel control by giving more weight to the second target trajectory than to the first target trajectory.

A parking assist system includes: a control device configured to execute a driving process for autonomously moving a vehicle to a target position; a steering operation member configured to receive a steering operation performed by an occupant; a vehicle state detecting device; and a notification device configured to make a notification to the occupant. In the driving process, the control device executes vehicle speed control and steering control. When, during execution of the driving process, the control device determines that the vehicle is a suspension state in which the driving process should be temporarily suspended, the control device causes the notification device to output a prescribed notification and executes a suspension process. In the suspension process, the control device executes the vehicle speed control to stop the vehicle and stops the steering control.

Techniques to generate driving scenarios for autonomous vehicles characterize a path in a driving scenario according to metrics such as narrowness and effort. Nodes of the path are assigned a time for action to avoid collision from the node. The generated scenarios may be simulated in a computer.

A vehicle having a control element for the speed, acceleration or direction of the vehicle, multiple identical or redundant computing devices (e.g., each implemented as a system on chip (SoC)) to separately generate driving commands in parallel during autonomous driving of the vehicle, and a command controller coupled between the control element and the computing devices. The commands may have one or more matching groups, where commands within each respective group agree with each other and thus vote for a candidate command representing the group. The computing device outputs a candidate command that represents the largest group for execution by the control element.

An automatic parking system is provided. The automatic parking system includes a camera processor that acquires images around a subject vehicle, converts the acquired images into external images and synthesizes the external images. A sensor processor measured spaced distances between the subject vehicle and surrounding vehicles. A parking space recognizing unit periodically receives the spaced distances and the external images and comparing the consecutive external images with the spaced distances using an image recognition technology to recognize parking areas. A controller calculates a moving path between a current position of the subject vehicle and an optimal parking area and operates the subject vehicle based on the moving path.