A vehicle control device, a vehicle control method, a vehicle motion control system, and a lane estimation device according to the present invention obtain first information on lane markings defining a lane in which a vehicle travels based on external information obtained from an external recognition unit, obtain second information on a curvature of the lane based on information on a road shape obtained from a road shape information acquisition unit, obtain third information on a behavior of the vehicle based on a physical quantity that is related to a motion state of the vehicle and obtained from a vehicle motion state detection unit, and estimate lane information including information on curvatures of the lane markings and information on relative positions of the vehicle with respect to the lane markings based on the first information, the second information, and the third information.

Disclosed embodiments provide a technical improvement for providing localization for a transportation vehicle by detecting road wear reference lines in a roadway on which the transportation vehicle is travelling and controlling, guiding or otherwise facilitating alignment of the transportation vehicle wheel centers with the detected centers of the road wear.

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 platooning control system includes a platoon controller that generates environmental maps used for platooning of vehicles, and a travel controller that controls travel of a following vehicle following a leading vehicle. The platoon controller generates the environmental maps each representing the position of an object around the vehicles, and delivers the maps to the following vehicle. The travel controller transmits object information indicating the position of an object detected from environmental data outputted by an environmental sensor mounted on the following vehicle to the platoon controller, executes update so that the position of the object represented in the latest environmental map is changed to the position of the object at the time when the following vehicle reaches the position of the leading vehicle represented in the latest environmental map, and controls travel of the following.

An autonomous vehicle and a system and method of operating the autonomous vehicle. The system includes a sensor and a processor. The processor determines an effective observation area of the sensor, the effective observation area being affected by an extrinsic condition. The processor determines an available time for performing a lane change based on the effective observation area and performs the lane change based on the available time.

The present disclosure relates to an autonomous vehicle, a control system for sharing information therewith, and a method thereof. An exemplary embodiment of the present disclosure provides an autonomous vehicle, including: a communication device configured to transmit abnormal vehicle information to a control system and to receive analysis information of an abnormal vehicle from the control system; and an autonomous driving control apparatus including a processor that executes avoidance control logic based on the analysis information of the abnormal vehicle received from the control system during autonomous driving.

Embodiments provide a vehicle computer coupled to a vehicle. The vehicle computer may be configured to compute (e.g., generate) a first (e.g., regular, main) trajectory and a second (e.g., fail-safe, minimal risk maneuver) trajectory for the vehicle. Embodiments may provide a fault detection interval during which the second trajectory may be activated due to missing updated trajectory input. Embodiments may also provide a recovery detection interval during which an updated regular trajectory may be generated and followed instead of the fail-safe trajectory if a valid trajectory update is received. Accordingly, embodiments allow for an early activation of a fail-safe trajectory compared to conventional systems, while also allowing the system to recover (e.g., revert back to a modified version of the first trajectory) if a valid trajectory update is received during a recovery detection interval.

Techniques for a perception system of a vehicle that can detect and track objects in an environment are described herein. The perception system may include a machine-learned model that includes one or more different portions, such as different components, subprocesses, or the like. In some instances, the techniques may include training the machine-learned model end-to-end such that outputs of a first portion of the machine-learned model are tailored for use as inputs to another portion of the machine-learned model. Additionally, or alternatively, the perception system described herein may utilize temporal data to track objects in the environment of the vehicle and associate tracking data with specific objects in the environment detected by the machine-learned model. That is, the architecture of the machine-learned model may include both a detection portion and a tracking portion in the same loop.

Disclosed are methods, systems, and non-transitory computer readable media that control an autonomous vehicle via at least two sensors. One aspect includes capturing an image of a scene ahead of the vehicle with a first sensor, identifying an object in the scene at a confidence level based on the image, determining the confidence level of the identifying is below a threshold, in response to the confidence level being below the threshold, directing a second sensor having a field of view smaller than the first sensor to generate a second image including a location of the identified object, further identifying the object in the scene based on the second image, controlling the vehicle based on the further identification of the object.

Devices, systems, and methods are provided for enhanced sensor cleaning validation. A device may determine a baseline performance measurement associated with a clean performance baseline of a sensor. The device may actuate a cleaning mechanism to remove at least a portion of an obstruction deposited on the sensor. The device may determine a first post-clean performance measurement associated with the sensor. The device may determine a degradation measurement between the baseline performance measurement and the first post-clean performance measurement, wherein the degradation measurement indicates an effectiveness of the cleaning mechanism.