Systems and methods for improving driver attention awareness are disclosed herein. One embodiment monitors the attention status of the driver of a vehicle; detects, based on the monitoring, the commencement of a distracted-driving incident; records, during the distracted-driving incident, information pertaining to the distracted-driving incident; detects, based on the monitoring, the end of the distracted-driving incident; and reports, at the earliest opportunity after the end of the distracted-driving incident and prior to the conclusion of the current trip, the information to the driver.

A collision avoidance system may validate, reject, or replace a trajectory generated to control a vehicle. The collision avoidance system may comprise a secondary perception component that may receive sensor data, receive and/or determine a corridor associated with operation of a vehicle, classify a portion of the sensor data associated with the corridor as either ground or an object, determine a position and/or velocity of at least the nearest object, determine a threshold distance associated with the vehicle, and control the vehicle based at least in part on the position and/or velocity of the nearest object and the threshold distance.

A method of thickening cosmetics containing a crosslinked water-swellable polymer, or a microgel obtained by pulverizing a hydrophilic compound having gelation ability. The method comprises adding a linear polyacrylic acid or a salt thereof, or a linear poly(2-acrylamido-2-methylpropanesulfonic acid) or a salt thereof, having a weight-average molecular weight of 500,000 to 8,000,000, which has a thread length of 10 mm or less at room temperature when formed into a 1% by mass solution. The method provides cosmetics having an improved viscoelastic ratio, with a rich and full-bodied feeling upon application.

A travel route generation device (4) includes a travel route acquisition unit (4) configured to acquire position information (Pc) about a travel route (H) for a moving object (M) to perform autonomous travel or remotely controlled travel, a surrounding environment information acquisition unit (22) configured to acquire surrounding environment information, a dangerous location detection unit (23) configured to detect dangerous locations (Pd1 to Pd3) where there is a risk of an accident from the surrounding environment information, and an information processing unit (24) configured to add dangerous location information including first information indicating the dangerous locations (Pd1 to Pd3) to the position information (Pc) corresponding to the dangerous locations (Pd1 to Pd3).

A tire-side device is attached to a tire included in a vehicle and applied to a tire apparatus for estimating a condition of a road surface on which the vehicle travels. The tire-side device includes: a vibration detector outputting a detection signal according to a level of vibration of the tire; a controller having a feature quantity extraction device extracting a feature quantity of the detection signal in one rotation of the tire; and a transmitter transmitting road surface data including the feature quantity extracted by the feature quantity extraction device.

This application relates to a lane edge extraction method and apparatus, an autonomous driving system, a vehicle, and a storage medium. The lane edge extraction method includes the steps of: receiving tracking edge points, about lane edges, of an immediately preceding frame of an edge image sequence; determining observation edge points, about the lane edges, of a current frame of the edge image sequence; continuing and correcting the tracking edge points of the immediately preceding frame based on the observation edge points of the current frame, to obtain temporary tracking edge points of the current frame; fitting a lane edge curve based on the temporary tracking edge points; and excluding outliers from the temporary tracking edge points based on the lane edge curve, to form tracking edge points of the current frame. The method can improve the stability and accuracy of lane edge extraction.

A method for a scene interpretation of an environment of a vehicle. The method includes: receiving environment sensor data from at least one environment sensor of a vehicle; carrying out an object detection based on the environment sensor data and detecting first objects in the environment of the vehicle; carrying out a scene analysis of the environment by taking into consideration the detected first objects and second objects stored in a map display of the environment, the scene analysis including: comparing the first objects detected in the object detection based on the environment sensor data to the second objects of the map display; and supplying a scene interpretation based on the scene analysis to a vehicle control of the vehicle, and at least the first objects detected in the object detection that agree with corresponding second objects of the map display are considered in the scene interpretation.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for planning the future trajectory of an autonomous vehicle in an environment. In one aspect, a method comprises obtaining multiple types of scene data characterizing a scene in an environment that includes an autonomous vehicle and multiple agents; receiving route data specifying an intended route for the autonomous vehicle; for each data type, processing at least the data type using a respective encoder network to generate a respective encoding of the data type; processing a sequence of the encodings using an encoder network to generate a respective alternative representation for each data type; and processing the alternative representations using a decoder network to generate a trajectory planning output that comprises respective scores for candidate trajectories that represent predicted likelihoods that the candidate trajectory is closest to resulting in the autonomous vehicle successfully navigating the intended route.

Techniques are provided for autonomous vehicle operation using linear temporal logic. The techniques include using one or more processors of a vehicle to store a linear temporal logic expression defining an operating constraint for operating the vehicle. The vehicle is located at a first spatiotemporal location. The one or more processors are used to receive a second spatiotemporal location for the vehicle. The one or more processors are used to identify a motion segment for operating the vehicle from the first spatiotemporal location to the second spatiotemporal location. The one or more processors are used to determine a value of the linear temporal logic expression based on the motion segment. The one or more processors are used to generate an operational metric for operating the vehicle in accordance with the motion segment based on the determined value of the linear temporal logic expression.

An apparatus and a method for controlling a velocity of an autonomous driving vehicle is provided. The method includes steps of: obtaining information of an environment surrounding the vehicle when an obstacle is detected to be on a planning path of the vehicle; obtaining an initial reference velocity profile of the vehicle; determining a safety factor based on the initial reference velocity profile, the information of the environment and information of the vehicle, wherein the safety factor at least comprises a safety distance between the vehicle and the obstacle for the vehicle to follow the obstacle; determining an optimized reference velocity profile based on the information of the environment, the information of the vehicle and the safety factor; and performing the step of determining the safety factor by using the optimized reference velocity profile as the initial reference velocity profile and the step of determining the optimized reference velocity iteratively.