Methods by which an autonomous vehicle may predict actions of other actors are disclosed. A vehicle will assign either a high priority rating or a low priority rating to each actor that it detects. The vehicle will then generate a forecast for each of the detected actors. Some of not all high priority actors will receive a high resolution forecast. Low priority actors, and optionally also some of the high priority actors, will receive a low resolution forecast. The system will the forecasts to predict actions for the actors. The autonomous vehicle will then use the predicted actions to determine its trajectory.

The technology involves to pickups performed by autonomous vehicles. In particular, it includes identifying one or more potential pullover locations adjacent to an area of interest that an autonomous vehicle is approaching. The vehicle detects that a given one of the potential pullover locations is occupied by another vehicle and determines whether the other vehicle will be vacating the given pullover location within a selected amount of time. Upon determining that the other vehicle will be vacating the given potential pullover location within the timeframe, the vehicle determines whether to wait for the other vehicle to vacate the given pullover location. Then a driving system of the vehicle either performs a first action in order to wait for the other vehicle to vacate the given pullover location or performs a second action that is different from the first action when it is determined to not wait.

We disclose adaptive active safety systems which utilize a sensing system to detect road conditions and actuate an active safety routine based thereon. One disclosed method includes transmitting, with a multispectral LIDAR system on a vehicle, a multispectral light beam directed at an anticipated region of travel of the vehicle within a road, and analyzing a response, of a photodetector, to a return of the multispectral light beam. The method also includes determining, based on the analyzing of the response, a hazardous surface condition in the anticipated region of travel of the vehicle, and actuating, based on the determination of the hazardous surface condition, an active safety routine. The method can be executed by an ADAS in which the determinations of the hazardous surface conditions on the road in the anticipated region of travel are executed in real time to thereby produce a road aware ADAS.

The present disclosure provides a method, an apparatus, a device and a readable storage medium for planning a pass path. The method includes: acquiring current road environment information in front of a vehicle; setting pass candidate points according to the current road environment information and a driving strategy; and determining a current optimal passable path according to the pass candidate points. Since the pass candidate points are set according to the current road environment information and the driving strategy, and the current optimal passable path is determined according to the pass candidate points, thereby effectively decreasing the calculation amount of the impassable path calculation in prior art due to direct setting of pass candidate points in all areas in front of an unmanned vehicle.

An in-vehicle data collection and processing device receives real-time data from a plurality of sensors relating to at least one of a current vehicle condition and a current driver condition. The device then predicts, by processing at least a portion of the real-time data through a pre-trained pattern recognition algorithm, a likelihood of occurrence of at least one of a plurality of incidents involving the vehicle. In response, the device outputs one or more types of warnings and/or conducts a vehicle evasive maneuver if the likelihood is predicted to be above one or more thresholds.

Embodiments of the present disclosure relate to generating velocity profiles for an autonomous vehicle (101). An ECU (107) of the autonomous vehicle (101) receives road information from one or more sensors (106) associated with the autonomous vehicle (101). One or more parameters related to smooth movement of the autonomous vehicle on the road is determined from the road information. Further, a first velocity profile is produced using an AI model and a second velocity profile is produced using a hierarchical model, based on the one or more parameters. Furthermore, one of the first and the second velocity profile is selected by comparing the first and the second velocity profiles. The selected velocity profile has a lower value of velocity value compared to the other velocity profile. The selected velocity profile is provided to the autonomous vehicle (101) for navigating on the road (102) smoothly.

A system of a first vehicle includes sensors and a processor that performs generating of an initial trajectory along a travel route of the first vehicle, acquiring trajectories of second vehicles along the route, adjusting the initial trajectory based on the acquired trajectories of the second vehicles, and navigating the first vehicle based on the adjusted initial trajectory.

A system of linearizing a trajectory of an autonomous vehicle about a reference path includes a computing device and a computer-readable storage medium. The computer-readable storage medium includes one or more programming instructions that, when executed, cause the computing device to receive a reference path for an autonomous vehicle, where the reference path defines a proposed trajectory for the autonomous vehicle in a Cartesian reference frame, identify an objective based on the received reference path, where the objective comprises a longitudinal component and a lateral component, project the objective into a curvilinear coordinate frame described by the received reference path, decouple the longitudinal component and the lateral component, linearize the lateral component about the reference path, generate a new reference path for the autonomous vehicle by fusing the linearized longitudinal component and the linearized lateral component, and map the new reference path back to the Cartesian reference frame.

An apparatus for providing a notification of control authority transition in a vehicle is provided. The apparatus includes a speaker configured to output a sound notification, a vibration motor configured to output a vibration notification, and a control circuit configured to be electrically connected with the speaker and the vibration motor. The control circuit is configured to output a first notification using the speaker during a first time interval, when a situation to transfer control authority for the vehicle occurs, output a second notification using the speaker and the vibration motor during a second time interval, after the first time interval elapses, and output a third notification using the speaker and the vibration motor during a third time interval, after the second time interval elapses.

A method of operating a vehicle having a driver assistance system includes detecting driving parameters pertaining to the vehicle while the vehicle is being driven on a roadway using a sensor system of the vehicle. Objects including road signs, lane indicators, and other vehicles are detected using the sensor system. The objects include at least road signs, lane indicators, and other vehicles on the roadway. A traffic rule pertaining to the roadway is identified using a traffic violation warning and prevention system of the driver assistance system. A traffic situation pertaining to the traffic rule is detected based on the detected objects and the driving parameters. An alert is generated that warns the driver of a potential traffic violation when the traffic situation is detected. Alternatively, the driver assistance system may be configured to take control of the vehicle to prevent violation of the traffic rule.