Aspects of the disclosure relate to controlling a transition between a manual driving mode and an autonomous driving mode of a vehicle. For instance, one or more processors of one or more control computing devices may control the vehicle in the autonomous driving mode. While controlling the vehicle in the autonomous driving mode and decelerating at a given rate, the processors may receive at a user input of the vehicle input requesting a transition from the autonomous driving mode to the manual driving mode. In response to the input, the processors may transition the vehicle to the manual driving mode. After transitioning the vehicle to the manual driving mode, the processors may send deceleration signals to a deceleration actuator thereby causing the vehicle to continue to decelerate at the given rate.

A navigation system for a host vehicle may include a processor programmed to: receive from a center camera onboard the host vehicle a captured center image including a representation of at least a portion of an environment of the host vehicle, receive from a left surround camera onboard the host vehicle a captured left surround image including a representation of at least a portion of the environment of the host vehicle, and receive from a right surround camera onboard the host vehicle a captured right surround image including a representation of at least a portion of the environment of the host vehicle; provide the center image, the left surround image, and the right surround image to an analysis module configured to generate an output relative to the at least one captured center image; and cause a navigational action by the host vehicle based on the generated output.

A method for modifying a trailer detection routine for a vehicle trailer detection system includes identifying a trailer in image data via a trailer detection model and activating a detection training routine for the trailer. The method further includes capturing the image data of the trailer from a plurality of perspectives relative to a trailer heading of the trailer and controlling an update procedure configured to generate a modified trailer detection model operable to detect the trailer.

Methods and systems are disclosed for determining sensor degradation by actively controlling an autonomous vehicle. Determining sensor degradation may include obtaining sensor readings from a sensor of an autonomous vehicle, and determining baseline state information from the obtained sensor readings. A movement characteristic of the autonomous vehicle, such as speed or position, may then be changed. The sensor may then obtain additional sensor readings, and second state information may be determined from these additional sensor readings. Expected state information may be determined from the baseline state information and the change in the movement characteristic of the autonomous vehicle. A comparison of the expected state information and the second state information may then be performed. Based on this comparison, a determination may be made as to whether the sensor has degraded.

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.

There is disclosed a control system and a method for a host vehicle operable in an autonomous mode. The control system comprises one or more controllers. The speed and/or path of the vehicle in the autonomous mode is appropriate to a driving context.

A parking assist system includes an environment information obtainer and a parking assist controller. The parking assist controller includes an available parking space detector, a target guiding route setter, a target stop position setter, and a steering controller. The steering controller turns a steered wheel of a vehicle and fixes the steered wheel to a steering angle at which the vehicle starts to be reversed at a target stop position for turning the vehicle along a target guiding route. The steering controller also turns the steered wheel to a steering angle at which the vehicle starts to be reversed to an available parking space at a target stop position for parking the vehicle in a state in which the vehicle is in line with the available parking space.

A method for modifying a trailer detection routine for a vehicle trailer detection system includes identifying a trailer in image data via a trailer detection model and activating a detection training routine for the trailer. The method further includes capturing the image data of the trailer from a plurality of perspectives relative to a trailer heading of the trailer and controlling an update procedure configured to generate a modified trailer detection model operable to detect the trailer.

An apparatus for controlling parking of a vehicle, a system having the same, and a method for the same are provided. The apparatus for controlling parking of a vehicle includes a processor to stop the vehicle when the vehicle arrives at a target parking space while performing an automatic parking of the vehicle to the target parking space, to adjust a steering angle, and to terminate the automatic parking after moving the vehicle for a predetermined distance when the steering angle is adjusted and the steering angle is greater than a preset threshold angle and a storage to store a parking path and the threshold angle.

Provided are methods, systems and computer program products for predicting vehicle crossing and yielding, which can include receiving sensor information indicating an object surrounding a vehicle. Some methods also include determining a future position of the vehicle based on a first trajectory of the vehicle, determining a future position of the object based on a second trajectory of the object, and determining a vehicle control based on the future position of the vehicle and the future position of the object. The methods also include training a model using the vehicle control, the first trajectory of the vehicle, and the second trajectory of the object.