Abstract: The technology relates to autonomous vehicles having hitched or towed trailers for transporting cargo and other items between locations. Aspects of the technology provide a smart hitch connection between the fifth-wheel of a tractor unit and the kingpin of a trailer. This avoids requiring a person to make physical pneumatic and electrical connections between the fifth-wheel and kingpin using external hoses and cables. Instead, the necessary connections are made internally, autonomously. For instance, the fifth-wheel may provide air pressure via one or more slots arranged on a connection surface, and the trailer is configured to receive the air pressure through one or more openings on a contact surface of the kingpin. An electrical connection section of the fifth-wheel may also provide electrical signals and/or power to an electrical contact interface of the kingpin. Rotational information about relative alignment of the trailer to the tractor unit may also be provided.

Abstract: Methods and system are provided for training and using a model to determine states of lanes of interest. For instance, image data including an image and an associated label identifying at least one traffic light, a state of the at least one traffic light, and a lane controlled by the at least one traffic light are received and used to train the model such that the model is configured to, in response to receiving an image and a lane of interest included in the image, output a lane state for the lane of interest. This model is then used by a vehicle in order to determine a state of a lane of interest. This state is then used to control the vehicle in an autonomous driving mode based on the state of the lane of interest.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating a simulation of an environment that is being interacted with by a plurality of agents over a plurality of time steps, wherein the simulation comprises a respective simulation state for each time step that specifies a respective state of each agent at the time step. In one aspect, a method comprises, for each time step: obtaining a current simulation state for the current time step; generating a plurality of candidate next simulation states for a next time step; determining, for each candidate next simulation state, a discriminative score characterizing a likelihood that the candidate next simulation state is a realistic simulation state; and selecting a candidate next simulation state as the simulation state for the next time step based on the discriminative scores for the candidate next simulation states.

Abstract: The disclosure provides for a system that includes a seat mounted in a vehicle. The seat includes a base, a back support, a hinge, and a seat belt integrated into the seat. The back support is capable of rotating relative to the base and thereby reclining. The hinge is between the base and the back support and is configured to lock the back support in positions in relation to the base. The seat belt has a shoulder portion and a lap portion and is attached to the seat at a shoulder anchor in the back support and a base anchor in the base. When a generated torque, created from a forward force applied by the shoulder portion of the seat belt, exceeds a threshold amount of torque, the hinge is configured to unlock and back support is configured to rotate forward from a reclined position towards an upright position.

Abstract: Aspects of the disclosure relate to controlling a first vehicle in an autonomous driving mode. While doing so, a second vehicle may be identified. This vehicle may be determined to be a tailgating vehicle. An initial allowable discomfort value representing expected discomfort of an occupant of the first vehicle and expected discomfort of an occupant of the second vehicle may be identified. Determining a speed profile for a future trajectory of the first vehicle that meets the value may be attempted based on a set of factors corresponding to a reaction of the tailgating vehicle. When a speed profile that meets the value cannot be determined, the value may be adjusted until a speed profile that meets the value is determined. The speed profile that meets an adjusted value is used to control the first vehicle in the autonomous driving mode.

Abstract: Methods, systems, and apparatus, for a stray-light testing station. In one aspect, the stray-light testing station includes an illumination assembly including a spatially extended light source and one or more optical elements arranged to direct a beam of light from the spatially extended light source along an optical path to an optical receiver assembly including a lens receptacle configured to receive a lens module and position the lens module in the optical path downstream from the parabolic mirror so that the lens module focuses the beam of light from the spatially extended light source to an image plane, and a moveable frame supporting the optical receiver assembly including one or more adjustable alignment stages to position the optical receiver assembly relative to the illumination assembly such that the optical path of the illumination assembly is within a field of view of the optical receiver assembly.

Abstract: Aspects of the disclosure relate to a vehicle having an autonomous driving mode and a manual driving mode. The vehicle may include a steering system having one or more processors configured to control the orientation of the one or more wheels based on control commands. The vehicle may also include an autonomous driving control system configured to control the vehicle in an autonomous driving mode by generating the control commands and to send the control commands to the steering system. In addition, the steering system may thermally derate the steering system based on first temperature information for the steering system when the vehicle is operating in a manual drive mode, and the autonomous driving control system may thermally derate the steering system based on second temperature information for the steering system when the vehicle is operating in the autonomous driving mode.

Abstract: The technology relates to detecting and responding to emergency vehicles. This may include using a plurality of microphones to detect a siren noise corresponding to an emergency vehicle and to estimate a bearing of the emergency vehicle. This estimated bearing is compared to map information to identify a portion of roadway on which the emergency vehicle is traveling. In addition, information identifying a set of objects in the vehicle's environment as well as characteristics of those objects is received from a perception system is used to determine whether one of the set of objects corresponds to the emergency vehicle. How to respond to the emergency vehicle is determined based on the estimated bearing and identified road segments and the determination of whether one of the set of objects corresponds to the emergency vehicle. This determined response is then used to control the vehicle in an autonomous driving mode.

Abstract: A method and apparatus are provided for determining whether a driving environment has changed relative to previously stored information about the driving environment. The apparatus may include an autonomous driving computer system configured to detect one or more vehicles in the driving environment, and determine corresponding trajectories for those detected vehicles. The autonomous driving computer system may then compare the determined trajectories to an expected trajectory of a hypothetical vehicle in the driving environment. Based on the comparison, the autonomous driving computer system may determine whether the driving environment has changed and/or a probability that the driving environment has changed, relative to the previously stored information about the driving environment.

Abstract: The technology relates to predicting that an object is going to enter into a trajectory of a vehicle. This may include receiving sensor data identifying a first location of the object in an environment of the vehicle at a first point in time and receiving sensor data identifying a second location of the object in the environment at a second point in time. In addition, a boundary of the trajectory is determined by defining at least a two-dimensional area through which the vehicle is expected to travel in the future. A first distance between the boundary and the first location and a second distance between the trajectory and the second location are determined. The first distance and the second distance are used to determine that the object is going to enter into the trajectory at a future point in time.

Abstract: Example embodiments described herein involve reducing the formation of ice on external modules by incorporating a heater within the module. The system may include a microphone module for an autonomous vehicle. The microphone module may include a housing and a microphone inside an opening of the housing. The system may further include a cover abutting the opening of the housing. The cover may enclose the microphone within the housing and seal the opening of the housing. The system may also include a heater adjacent to the opening of the housing and configured to prevent ice from forming over the opening. The heater may at least partially surround the opening.

Abstract: Example embodiments relate to identification of proxy calibration targets for a fleet of sensors. An example method includes collecting, using a sensor coupled to a vehicle, data about one or more objects within an environment of the vehicle. The sensor has been calibrated using a ground-truth calibration target. The method also includes identifying, based on the collected data, at least one candidate object, from among the one or more objects, to be used as a proxy calibration target for other sensors coupled to vehicles within a fleet of vehicles. Further, the method includes providing, by the vehicle, data about the candidate object for use by one or more vehicles within the fleet of vehicles.

Abstract: This technology relates to dynamically detecting, managing and mitigating driver fatigue in autonomous systems. For instance, interactions of a driver in a vehicle may be monitored to determine a distance or time when primary tasks associated with operation of the vehicle or secondary tasks issued by the vehicle computing were last performed. If primary tasks or secondary tasks are not performed within given distance thresholds or time limits, then one or more secondary tasks are initiated by the computing device of the vehicle. In another instance, potential driver fatigue, driver distraction or overreliance on an automated driving system is detected based on gaze direction or pattern of a driver. For example, a detected gaze direction or pattern may be compared to an expected gaze direction or pattern given the surrounding environment in a vicinity of the vehicle.

Abstract: Systems and methods for estimating sensor timestamps by oversampling are provided. One example method involves observing, at a sampling frequency, sensor data from a register of a sensor. The sensor updates the register with sensor data at as sensor update frequency. The sampling frequency is different from the sensor update frequency. The method also involves generating, based on the sensor update frequency and the sampling frequency, an observed sequence representing the sensor data. The observed sequence indicates whether the register is observed to be updated or not updated. The method also involves estimating, from the observed sequence, the sensor update frequency and a sensor update phase. The method also involves determining, based on the sensor update frequency as estimated and the sensor update phase as estimated, a timestamp corresponding to an update of the register.

Abstract: A system includes a light detection and ranging device configured to generate, for each respective point of a plurality of points in an environment, a corresponding waveform that represents physical characteristics of the respective point. The system also includes a signal processor configured to determine, based on the corresponding waveform of each respective point, a map of the environment that includes a representation of a corresponding position of the respective point. The system additionally includes an embedding model configured to determine, for each respective point and based on the corresponding waveform, a corresponding vector comprising a plurality of values representative of the physical characteristics of the respective point. The system further includes a feature detector configured to detect or classify a physical feature based on (i) the corresponding positions of one or more points of the plurality of points and (ii) the corresponding vectors of the one or more points.

Abstract: The technology relates to articulated autonomous vehicles that can potentially jackknife. To avoid or mitigate such hazardous conditions, the current state of the vehicle is evaluated against the vehicle's planned trajectory, for instance as it drives along a freeway or surface streets. When the evaluation indicates a likelihood of jackknifing, an automated braking approach is implemented using elective braking to stabilize the vehicle. The braking approach can depend on whether the situation involves tractor jackknifing or trailer jackknifing, and one or more different braking mechanisms can be employed for a selective modulation of the braking profile to address actual jackknifing or to prevent the vehicle from entering a jackknifing situation.