A vehicle running control method includes: when a junction section lane is present adjacent to a traveling lane of a host vehicle, collecting, by a processor, vehicle information of at least one vehicle traveling in the junction section lane; determining, by the processor, the possibility of cut-in of junction section lane vehicles based on the collected vehicle information and whether the traveling lane is congested; and controlling, by the processor, at least one of the traveling path or the traveling velocity of the host vehicle based on the result of determination in order to display an intention to yield.

A sensing system provided in a vehicle capable of running in an autonomous driving mode, includes: a LiDAR unit configured to acquire point group data indicating surrounding environment of the vehicle; and a LiDAR control module configured to identify information associated with a target object existing around the vehicle, based on the point group data acquired from the LiDAR unit. The LiDAR control module is configured to control the LiDAR unit so as to increase a scanning resolution of the LiDAR unit in a first angular area in a detection area of the LiDAR unit, wherein the first angular area is an area where the target object exists.

The technology relates to detecting and responding to processions. For instance, sensor data identifying two or more objects in an environment of a vehicle may be received. The two or more objects may be determined to be disobeying a predetermined rule in a same way. Based on the determination that the two or more objects are disobeying a predetermined rule, that the two or more objects are involved in a procession may be determined. The vehicle may then be controlled autonomously in order to respond to the procession based on the determination that the two or more objects are involved in a procession.

In a target identification device, an acquisition unit is configured to acquire trajectory information including information on a movement trajectory of a moving object in the surroundings of a vehicle. A calculation unit is configured to calculate a likelihood for each type of moving object from the trajectory information by using a plurality of models predefined for each type of moving object. A target identification unit is configured to identify the type of the moving object according to the likelihood calculated by the calculation unit.

A vehicle for collecting image data of a target object for generating a classifier. The vehicle includes an image sensor and an electronic processor. The electronic processor is configured to determine a plurality of potential trajectories of the vehicle, determine, for each of the plurality of potential trajectories of the vehicle, a total number of views including the target object that would be captured by the image sensor as the vehicle moved along the respective trajectory, and determine a key trajectory of the vehicle from the plurality of potential trajectories based on the total number of views including the target of the key trajectory.

A pedestrian protection system includes a plurality of autonomous driving vehicles and a server configured to be able to communicate with each of the autonomous driving vehicles. The server is configured to select at least one vehicle to be moved to the location of a pedestrian from among the autonomous driving vehicles as a pedestrian protection vehicle when a particular situation occurrence notification is received and is configured to send an instruction notification to the pedestrian protection vehicle. The particular situation occurrence notification indicates that the pedestrian is placed in a particular situation. The instruction notification instructs the pedestrian protection vehicle to move to the location of the pedestrian for protecting the pedestrian. Each of the autonomous driving vehicles is configured to move to the location of the pedestrian for protecting the pedestrian when the instruction notification is received.

Techniques for determining a response of a simulated vehicle to a simulated object in a simulation are discussed herein. Log data captured by a physical vehicle in an environment can be received. Object data representing an object in the log data can be used to instantiate a simulated object in a simulation to determine a response of a simulated vehicle to the simulated object. Additionally, one or more trajectory segments in a trajectory library representing the log data can be determined and instantiated as a trajectory of the simulated object in order to increase the accuracy and realism of the simulation.

An apparatus for controlling autonomous driving of a vehicle includes a processor to control autonomous driving, and a storage to store data and an algorithm to control the autonomous driving. The processor determines whether a target vehicle in front of a host vehicle in a travelling lane of the host vehicle is stopped, and performs a passing control when the target vehicle is stopped.

A method, system and non-transitory computer readable medium which monitor a road user in order to move the external position of the vehicle intent notification (eHMI) to another external position that can be seen by the road user based on the gaze direction of the road user. In some aspects, the eHMI notification displays the vehicle intent for a single autonomous vehicle. In another aspect, a group eHMI notification displays the trajectories for a plurality of autonomous and non-autonomous vehicles. Based on the gaze direction of the road user, the eHMI notification can be displayed on a single external position or on multiple external positions. Different eHMI notifications can be displayed at different external positions on the autonomous vehicle to provide information to more than one road user.

Environmental tracking systems and methods are disclosed. An environmental tracking system receives sensor data from the one or more sensors, such as camera(s) and Light Detection and Ranging (LIDAR) sensors. The system uses trained machine learning (ML) model(s) to detect, within the sensor data, representation(s) of at least a portion of a vehicle with a door that is at least partially open. Based on these representation(s), the system generates a boundary for the vehicle that includes the door and is sized based on the door being at least partially open. The system determines a route that avoids the boundary, for example by planning the route around the boundary or by planning to stop before intersecting with the boundary. In some examples, the sensors are sensors coupled to a second vehicle, and the second vehicle traverses the route.