Abstract: Aspects of the disclosure provide systems and methods for providing suggested locations for pick up and destination locations. Pick up locations may include locations where an autonomous vehicle can pick up a passenger, while destination locations may include locations where the vehicle can wait for an additional passenger, stop and wait for a passenger to perform some task and return to the vehicle, or for the vehicle to drop off a passenger. As such, a request for a vehicle may be received from a client computing device. The request may identify a first location. A set of one or more suggested locations may be selected by comparing the predetermined locations to the first location. The set may be provided to the client computing device.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering an occupant of the vehicle to a destination autonomously as well as providing information about the vehicle and the vehicle's environment for display to the occupant.

Abstract: Aspects of the disclosure relate to deploying safety mechanisms in an autonomous vehicle. As an example, the situational information identifying a potential impact target corresponding to an object with which the autonomous vehicle is predicted to have a collision within a predetermined period of time may be received. This situational information may also include an estimated time when the second computing device will receive an update for the potential impact target from the first computing device. The estimated time may be used to determine when to deploy a set of active safety mechanisms for the potential impact target. Each active safety mechanism may be configured to reduce a likelihood of damage to an object external to the autonomous vehicle caused by a collision. A signal is then sent to activate the set of active safety mechanisms prior to an impact with the object corresponding to the identified potential impact target.

Abstract: The present disclosure provides methods and apparatuses that enable an apparatus to identify sounds from short samples of audio. The apparatus may capture an audio sample and create several audio signals of different lengths, each containing audio from the captured audio sample. The apparatus my process the several audio signals in an attempt to identify features of the audio signal that indicate an identification of the captured sound. Because shorter audio samples can be analyzed more quickly, the system may first process the shortest audio samples in order to quickly identify features of the audio signal. Because longer audio samples contain more information, the system may be able to more accurately identify features in the audio signal in longer audio samples. However, analyzing longer audio signals takes more buffered audio than identifying features in shorter signals. Therefore, the present system attempts to identify features in the shortest audio signals first.

Abstract: Disclosed herein are embodiments that relate to phase coded linear frequency modulation for a radar system. Embodiments include transmitting at least two signal pulses. The transmitting includes transmitting a first pulse with a first phase modulation and a first chip rate, and transmitting a second pulse with a second phase modulation and a second chip rate. The second chip rate may be different than the first chip rate. Embodiments also include receiving a signal that includes at least two reflection signals associated with reflection of the at least two transmitted signal pulses. Embodiments further include processing the received signal to determine target information. The processing includes filtering the received signal to time-align the at least two reflection signals. The filtering includes applying a frequency-dependent time delay to one or more of the at least two reflection signals. Additionally, embodiments include removing phase code modulations from the time-aligned reflection signals.

Abstract: Aspects of the disclosure relate to arranging a pickup between a driverless vehicle and a passenger. For instance, dispatch instructions dispatching the vehicle to a predetermined pickup area in order to pick up the passenger are received by the vehicle which begins maneuvering to the predetermined pickup area. While doing so, the vehicle receives from the passenger's client computing device the device's location. An indication that the passenger is interested in a fly-by pickup is identified. The fly-by pickup allows the passenger to safely enter the vehicle at a location outside of the predetermined pickup area and prior to the one or more processors have maneuvered the vehicle to the predetermined pickup area. The vehicle determines that the fly-by pickup is appropriate based on at least the location of the client computing device and the indication, and based on the determination, maneuvers itself in order to attempt the fly-by pickup.

Abstract: Aspects of the disclosure relate to determining whether a feature of map information. For example, data identifying an object detected in a vehicle's environment and including location coordinates is received. This information is used to identify a corresponding feature from pre-stored map information based on a map location of the corresponding feature. The corresponding feature is defined as a curve and associated with a tag identifying a type of the corresponding feature. A tolerance constraint is identified based on the tag. The curve is divided into two or more line segments. Each line segment has a first position. The first position of a line segment is changed in order to determine a second position based on the location coordinates and the tolerance constraint. A value is determined based on a comparison of the first position to the second position. This value indicates a likelihood that the corresponding feature has changed.

Abstract: An autonomous vehicle is tested using virtual objects. The autonomous vehicle is maneuvered, by one or more computing devices, the autonomous vehicle in an autonomous driving mode. Sensor data is received corresponding to objects in the autonomous vehicle's environment, and virtual object data is received corresponding to a virtual object in the autonomous vehicle's environment. The virtual object represents a real object that is not in the vehicle's environment. The autonomous vehicle is maneuvered based on both the sensor data and the virtual object data. Information about the maneuvering of the vehicle based on both the sensor data and the virtual object data may be logged and analyzed.

Abstract: Methods and systems for determining instructions for pulling over an autonomous vehicle are described. An example method may involve identifying a region of a road ahead of the autonomous vehicle based on lane boundaries of the road, one or more road boundaries indicating an edge of the road, and a size of the autonomous vehicle. The method may also involve determining a braking profile for reducing the speed of the autonomous vehicle based on the region and a speed of the autonomous vehicle. The method may also involve determining, based on the braking profile, a trajectory such that the autonomous vehicle will travel within the region while reducing the speed of the autonomous vehicle. The method may further involve determining instructions for pulling over and stopping the autonomous vehicle in the region in accordance with the determined trajectory and storing the instructions in a memory accessible by a computing device.

Abstract: Aspects of the present disclosure relate switching between autonomous and manual driving modes. In order to do so, the vehicle's computer may conduct a series of environmental, system, and driver checks to identify certain conditions. The computer may correct some of these conditions and also provide a driver with a checklist of tasks for completion. Once the tasks have been completed and the conditions are changed, the computer may allow the driver to switch from the manual to the autonomous driving mode. The computer may also make a determination, under certain conditions, that it would be detrimental to the driver's safety or comfort to make a switch from the autonomous driving mode to the manual driving mode.

Abstract: Aspects of the disclosure relate to deploying safety mechanisms in an autonomous vehicle. A projected future location of an object may be identified. The projected future location of the object will intersect with a projected future location of the vehicle at a time T. An impact point P corresponding to a three dimensional location in space where the vehicle and object will collide at the time T may be identified. One of a plurality of safety mechanisms of the vehicle that can be moved closest to point P before or at the time T may be selected. The selected safety mechanism may be moved from a first point on the vehicle to a second point on the vehicle such that the safety mechanism moves towards the point P. After moving the selected safety mechanism, the safety mechanism is then deployed based on the time T.

Abstract: Aspects of the present disclosure relate generally to systems and methods for assessing validity of a map using image data collected by a laser sensor along a vehicle path. The method may compile image data received from the laser sensor. The map subject to assessment may define an area prohibiting entry by a vehicle.

Abstract: Models can be generated of a vehicle's view of its environment and used to maneuver the vehicle. This view need not include what objects or features the vehicle is actually seeing, but rather those areas that the vehicle is able to observe using its sensors if the sensors were completely un-occluded. For example, for each of a plurality of sensors of the object detection component, a computer may generate an individual 3D model of that sensor's field of view. Weather information is received and used to adjust one or more of the models. After this adjusting, the models may be aggregated into a comprehensive 3D model. The comprehensive model may be combined with detailed map information indicating the probability of detecting objects at different locations. The model of the vehicle's environment may be computed based on the combined comprehensive 3D model and detailed map information.

Abstract: Example methods and systems for implementing slotted waveguide array antenna using printed waveguide transmission lines technology are described herein. One example method may include developing a slotted waveguide array antenna may be developed using a plurality of slotted waveguides aligned in an antenna array, in which each slotted waveguide may be developed using printed waveguide transmission lines technology. Components of the slotted waveguide array antenna may be developed using printed circuit board materials, such as Kapton-type laminate and FR4. In addition, through using printed waveguide transmission line technology, a slotted waveguide array antenna may be configured to radiate millimeter electromagnetic waves and may be configured to operate in radar, navigation, or other high frequency systems.

Abstract: Aspects of the disclosure relate to airbag systems for vehicles having interlocking airbags. An example airbag system may include a first airbag having a first shape and a second airbag having a second shape. The first shape and the second shape are configured to interlock with one another in order to reduce the likelihood of an object passing between the first airbag and the second airbag when the first and second airbags are inflated. In addition, the first airbag and second airbag are arranged to deploy on an exterior of the vehicle. An airbag system can also include one or more processors configured to determine that an impact with an object is likely to occur within a predetermined period of time. These processors can also use the determination to send a first signal to deploy the first airbag and a second signal to deploy the second airbag.

Abstract: Methods and systems for the use of detected objects for image processing are described. A computing device autonomously controlling a vehicle may receive images of the environment surrounding the vehicle from an image-capture device coupled to the vehicle. In order to process the images, the computing device may receive information indicating characteristics of objects in the images from one or more sources coupled to the vehicle. Examples of sources may include RADAR, LIDAR, a map, sensors, a global positioning system (GPS), or other cameras. The computing device may use the information indicating characteristics of the objects to process received images, including determining the approximate locations of objects within the images. Further, while processing the image, the computing device may use information from sources to determine portions of the image to focus upon that may allow the computing device to determine a control strategy based on portions of the image.

Abstract: Aspects of the present disclosure relate to a vehicle for maneuvering a passenger to a destination autonomously. The vehicle includes a computing system and a set of user input buttons for communicating requests to stop the vehicle and to initiate a trip to the destination with the computing system The vehicle has no steering wheel and no user inputs for the steering, acceleration, and deceleration of the vehicle other than the set of user input buttons. In order to safely test the vehicle, a removable manual control system may be used. The system may include a housing having an electronic connection to a computing system of the vehicle. The housing includes a steering input configured to allow a passenger to control the direction of the vehicle. The system also includes one or more computing devices configured to receive input from the steering input and send instructions the computing system.

Abstract: A vehicle configured to operate in an autonomous mode can obtain sensor data from one or more sensors observing one or more aspects of an environment of the vehicle. At least one aspect of the environment of the vehicle that is not observed by the one or more sensors could be inferred based on the sensor data. The vehicle could be controlled in the autonomous mode based on the at least one inferred aspect of the environment of the vehicle.

Abstract: Methods and devices for detecting traffic signals and their associated states are disclosed. In one embodiment, an example method includes a scanning a target area using one or more sensors of a vehicle to obtain target area information. The vehicle may be configured to operate in an autonomous mode, and the target area may be a type of area where traffic signals are typically located. The method may also include detecting a traffic signal in the target area information, determining a location of the traffic signal, and determining a state of the traffic signal. Also, a confidence in the traffic signal may be determined. For example, the location of the traffic signal may be compared to known locations of traffic signals. Based on the state of the traffic signal and the confidence in the traffic signal, the vehicle may be controlled in the autonomous mode.

Abstract: The present disclosure relates to a fiber encapsulation mechanism for energy dissipation in a fiber amplifying system. One example embodiment includes an optical fiber amplifier. The optical fiber amplifier includes an optical fiber that includes a gain medium, as well as a polymer layer that at least partially surrounds the optical fiber. The polymer layer is optically transparent. In addition, the optical fiber amplifier includes a pump source. Optical pumping by the pump source amplifies optical signals in the optical fiber and generates excess heat and excess photons. The optical fiber amplifier additionally includes a heatsink layer disposed adjacent to the polymer layer. The heatsink layer conducts the excess heat away from the optical fiber. Further, the optical fiber amplifier includes an optically transparent layer disposed adjacent to the polymer layer. The optically transparent layer transmits the excess photons away from the optical fiber.