Techniques for estimating a height range of an object in an environment are discussed herein. For example, a sensor, such as a lidar sensor, can capture three-dimensional data of an environment. The sensor data can be associated with a two-dimensional representation. A ground surface can be removed from the sensor data, and clustering techniques can be used to cluster remaining sensor data provided in a two-dimensional representation to determine object(s) represented therein. A height of a sensor object can be represented as a first height based on an extent of the sensor data associated with the object and can be represented as a second height based on beam spreading aspects of the sensor data and/or sensor data associated with additional objects. Thus, a minimum and/or maximum height of an object can be determined in a robust manner. Such height ranges can be used to control an autonomous vehicle.

An alert control apparatus that notifies a driver in advance of a transfer of control relating to a driving operation from an automatic driving function to the driver by controlling an alert device mounted on a vehicle, which is equipped with the automatic driving function, includes: an estimator that estimates an occurrence of a change execution situation that requires a lane change under a condition in which the driving operation of the vehicle is controlled by the automatic driving function; a determiner that determines a level of difficulty of lane change control based on a plurality of travel environment factors in the change execution situation; and a notification device that notifies the driver of a possibility of the transfer of the control together with a reason of the transfer of the control with a notification mode corresponding to the level using the alert device.

A computing device including interface for receiving from a sensor device sensor data representative of an environment surrounding a host vehicle, and a processor configured to obtain a planned driving action for accomplishing a navigational goal of a host vehicle operating in a first lane of a roadway, identify, from the sensor data, a moving target vehicle located in a second lane of the roadway, identify, based on the target vehicle speed and direction, the target vehicle predicted trajectory indicating a cut-in movement of the target vehicle from the second lane to the first lane, identify an intersection of a planned trajectory for the host vehicle with the predicted trajectory for the target vehicle, and determine a safety action of the host vehicle to respond to the movement of the target vehicle; and cause the safety action to be performed in the host vehicle.

A driving assistance apparatus operates a collision avoidance apparatus that is mounted in a vehicle based on a distance to an object that is positioned ahead of the vehicle in a travelling direction. The driving assistance apparatus includes: a resistance determining unit that determines whether or not running resistance that suppresses rolling of wheels forward in the travelling direction of the vehicle is present; an operation determining unit that determines whether or not an accelerator operation by a driver of the vehicle is being performed; and a distance setting unit that sets an operation distance that is a distance at which the collision avoidance apparatus is operated. When the resistance determining unit determines that the running resistance is present and when the operation determining unit determines that the accelerator operation is being performed, the distance setting unit sets the operation distance to a value that is less than that when the running resistance is not present.

A computing device configured to: obtain images representative of an environment of a host vehicle, the host vehicle traveling on a roadway; detect, from the images, a mark located on the roadway; identify, from the images, points corresponding to the mark on the roadway; identify the mark as a type of roadway marking, corresponding to the identified points, the type of roadway marking selected from multiple types of roadway markings; determine a position of the mark on the roadway relative to the host vehicle, using the identified points corresponding to the mark; and determine a trajectory to navigate the host vehicle on the roadway, based on the position of the mark within the roadway and the type of roadway marking.

The technology relates to maneuvering a vehicle prior to making a turn from a current lane of the vehicle. As an example, a route that includes making the turn from the lane is identified. An area of the lane prior to the turn having a lane width of at least a predetermined size is also identified. Sensor data identifying an object within the lane is received from a perception system of a vehicle. Characteristics of the object, including a location of the object relative to the vehicle, are identified from the sensor data. The vehicle is then maneuvered through the area prior to making the turn using the identified characteristics.

Systems and methods are provided for navigating a host vehicle. In some embodiments, the system may include at least one processing device programmed to: receive at least one image representative of an environment of the host vehicle; determine a navigational action of the host vehicle; analyze the at least one image to identify a target vehicle in the environment of the host vehicle; determine a next-state distance between the host vehicle and the target vehicle that would result if the navigational action was taken; determine a maximum braking capability of the host vehicle, a maximum acceleration capability of the host vehicle, and a speed of the host vehicle; determine a stopping distance for the host vehicle; determine a speed of the target vehicle; and implement the navigational action if the determined stopping distance for the host vehicle is less than the next-state distance summed with a target vehicle travel distance.

An obstacle avoidance reminding method includes: performing ground detection based on acquired image data to acquire ground information of a road; performing passability detection based on the acquired ground information, and determining a traffic state of the road; if it is determined that the road is impassable, performing road condition detection for the road to acquire a first detection result, and performing obstacle detection for the road to acquire a second detection result; and determining obstacle avoidance reminding information based on the first detection result and the second detection result.

The present application relates to a method for performing off road adaptive cruise control in a host vehicle including controlling a vehicle speed at a first speed according to an adaptive cruise control algorithm, detecting an obstacle, using a sensor, within a host vehicle path, reducing the vehicle speed to a reduced speed in response to the detection of the obstacle, detecting a vehicle contact with the obstacle in response to a first inertial measurement unit measurement, applying a brake friction force and increasing an engine torque in response to detecting the vehicle contact with the obstacle, determining a traverse of the obstacle in response to a second inertial measurement unit measurement, and resuming the control of the vehicle speed at the first speed in response to the traverse of the obstacle.

Disclosed is an autonomous passenger vehicle system including an autonomous vehicle having electronic motor apparatuses, a control network associated with control center driver operating the autonomous passenger vehicle remotely through computer programs involving a network component using a mobile communication system and receiving information related to driving instructions to autonomous work at a traffic situation from the network component.