A driver assistance device is configured to determine whether a type of a deceleration target is included in a category of a position-fixed object or a moving object, and determine whether the deceleration target is lost, and to continue the deceleration assistance on assumption that the lost deceleration target exists when the deceleration target is determined to be lost. The driver assistance device is configured to notify a driver of a host vehicle that the deceleration target is lost when the deceleration target is determined to be lost and the type of the deceleration target is included in the category of the moving object, and not to notify the driver that the deceleration target is lost when the deceleration target is determined to be lost and the type of the deceleration target is included in the category of the position-fixed object.

The described techniques relate to modifying a trajectory of a vehicle, such as an autonomous vehicle, based on an overlap area associated with an object in the environment. In examples, map data may be used, in part, to generate an initial trajectory for an autonomous vehicle to follow through an environment. In some cases, a yield trajectory may be generated based on detection of the object, and the autonomous vehicle may evaluate a cost function to determine whether to execute the yield or follow the initial trajectory. In a similar manner, the autonomous vehicle may determine a merge location of two lanes of a junction, and use the merge location to update extents of an overlap area to prevent the autonomous vehicle from blocking the junction and/or provide sufficient space to yield to the oncoming vehicle while merging.

Techniques and methods for performing collision monitoring using system data. For instance, a vehicle may generate sensor data using one or more sensors. The vehicle may then analyze the sensor data using systems in order to determine parameters associated with the vehicle and parameters associated with another object. Additionally, the vehicle may determine uncertainties associated with the parameters and then process the parameters using the uncertainties. Based at least in part on the processing, the vehicle may determine a distribution of estimated locations associated with the vehicle and a distribution of estimated locations associated with the object. Using the distributions of estimated locations, the vehicle may determine the probability of collision between the vehicle and the object.

A method of operating an autonomous vehicle includes detecting, based on an input received from a sensor of an autonomous vehicle that is being navigated by an on-board computer system, an occurrence of a driving event, making a determination by the on-board computer system, upon the detecting the occurrence of the driving event, whether or how to alter the path planned by the on-board computer system according to a set of rules, and performing further navigation of the autonomous vehicle based on the determination until the driving event is resolved. The driving event may include a presence of an object in a shoulder area of the road. The driving event may include accumulation of more than a certain number of vehicles behind the autonomous vehicle. The driving event may include a slow vehicle ahead of the autonomous vehicle. The driving event may include a do-not-change-lane zone is within a threshold.

The present disclosure relates to an apparatus and method for determining transfer of control authority of a vehicle for determining whether transfer of control right of a vehicle is required according to whether a reverse-driving vehicle exists in a driving lane. According to the present disclosure, an apparatus for determining transfer of control authority of a vehicle may obtain information on the vehicle's surroundings, and determine whether a reverse-driving vehicle exists in front of the host vehicle on the driving lane during autonomous driving of the vehicle, based on the information on the surroundings of the vehicle and high definition map information and determine a situation in which the transfer of control authority to the user is required based on whether or not a reverse-driving vehicle exists in front of the host vehicle on the driving lane.

Determining classification(s) for object(s) in an environment of autonomous vehicle, and controlling the vehicle based on the determined classification(s). For example, autonomous steering, acceleration, and/or deceleration of the vehicle can be controlled based on determined pose(s) and/or classification(s) for objects in the environment. The control can be based on the pose(s) and/or classification(s) directly, and/or based on movement parameter(s), for the object(s), determined based on the pose(s) and/or classification(s). In many implementations, pose(s) and/or classification(s) of environmental object(s) are determined based on data from a phase coherent Light Detection and Ranging (LIDAR) component of the vehicle, such as a phase coherent LIDAR monopulse component and/or a frequency-modulated continuous wave (FMCW) LIDAR component.

A method of controlling the vehicle may include predicting, by a controller, a braking situation of the vehicle; performing, by the controller, brake distribution control of front and rear wheels of the vehicle in a response to a predicted sudden braking of the vehicle at a predetermined level; and performing, by the controller, independent braking control of the rear wheels of the vehicle in a response to a predicted general braking of the vehicle at the predetermined level.

Apparatus and methods relate to a controller configured to monitor incident risk levels of multiple independently governed autonomous vehicles remote from the controller simultaneously; and, in response to an unsafe incident risk level for one or more vehicles, take control of vehicles having an unsafe incident risk level, to restore a safe incident risk level; and, in response to determining incident risk has been restored to a safe level, returning control to the autonomous vehicles. Incident risk may be determined for multiple vehicles individually, and as a group, based on data from sensors distributed across multiple vehicles. Sensor data from multiple vehicles may be fused, permitting accurate incident risk determination for a vehicle group. Safety measures may be targeted by artificial intelligence to an individual vehicle or a vehicle group, to reduce incident risk by increasing separation between vehicles, or reducing vehicle speed.

The present invention extends to methods, systems, and computer program products for detecting hazards in anticipation of opening vehicle doors. Vehicle sensors (e.g., rear viewing cameras) can be used to detect and classify traffic, for example, as pedestrians, bicyclists, skateboarders, roller skaters, wheel chair, etc., approaching on the side of a vehicle. When there is a possibility of a vehicle occupant opening a door into approaching traffic, a warning can be issued in the vehicle cabin to alert vehicle occupants of the approaching traffic. In one aspect, a vehicle prevents a door from opening if opening the door would likely cause an accident.

An obstacle is detected based on sensor data obtained from a plurality of sensors of the ADV. A distribution of a plurality of positions of the obstacle at a point of time may be predicted. A range of positions of the plurality of positions of the obstacle may be determined based on a confidence level of the range. A modified shape with a modified length of the obstacle may be determined based on the range of positions of the obstacle. A trajectory of the ADV based on the modified shape with the modified length of the obstacle may be planned. The ADV may be controlled to drive according to the planned trajectory to drive safely to avoid a collision with the obstacle.