Abstract: An autonomous vehicle may be configured to use environmental information for image processing. The vehicle may be configured to operate in an autonomous mode in an environment and may be operating substantially in a lane of travel of the environment. The vehicle may include a sensor configured to receive image data indicative of the environment. The vehicle may also include a computer system configured to compare environmental information indicative of the lane of travel to the image data so as to determine a portion of the image data that corresponds to the lane of travel of the environment. Based on the portion of the image data that corresponds to the lane of travel of the environment and by disregarding a remaining portion of the image data, the vehicle may determine whether an object is present in the lane, and based on the determination, provide instructions to control the vehicle in the autonomous mode in the environment.

Abstract: A vehicle can be controlled in a first autonomous mode of operation by at least navigating the vehicle based on map data. Sensor data can be obtained using one or more sensors of the vehicle. The sensor data can be indicative of an environment of the vehicle. An inadequacy in the map data can be detected by at least comparing the map data to the sensor data. In response to detecting the inadequacy in the map data, the vehicle can be controlled in a second autonomous mode of operation and a user can be prompted to switch to a manual mode of operation. The vehicle can be controlled in the second autonomous mode of operation by at least obtaining additional sensor data using the one or more sensors of the vehicle and navigating the vehicle based on the additional sensor data.

Abstract: A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a representative trajectory. Afterwards, the autonomous vehicle may change at least one of its speed or direction based on the representative trajectory.

Abstract: An autonomous vehicle may be configured to detect objects based on known structures of an environment. The vehicle may be configured to obtain image data from a sensor and be configured to operate in an autonomous mode. The image data may include data indicative of a known structure in the environment. The vehicle may include a computer system. The computer system may determine, based on a first portion of the image data, information indicative of an appearance of the known structure. The computer system may determine, based on a second portion of the image data, information indicative of an appearance of an unknown object in the environment. The computer system may also compare the information indicative of the appearance of the known structure with the information indicative of the appearance of the unknown object and provide instructions to control the vehicle in the autonomous mode based on the comparison.

Abstract: Methods and devices for using uncertainty regarding observations of traffic intersections to modify behavior of a vehicle are disclosed. In one embodiment, an example method includes determining a state of a traffic intersection using information from one or more sensors of a vehicle. The vehicle may be configured to operate in an autonomous mode. The method may also include determining an uncertainty associated with the determined state of the traffic intersection. The method may further include controlling the vehicle in the autonomous mode based on the determined state of the traffic intersection and the determined uncertainty.

Abstract: A method is provided that includes receiving user input identifying a travel destination for a first vehicle, determining, by a processor, a first route for the first vehicle to follow, and configuring the first vehicle to follow the first route. The method further includes obtaining a model for a second vehicle that shares a road with the first vehicle and comparing model to a pre-determined template for a vehicle that is known to be a special purpose vehicle in order to determine whether the first template and the second template match. The method further includes determining, by the processor, a second route that leads to the travel destination, when a match is found to exist, and switching the first vehicle from following the first route to following the second route.

Abstract: A vehicle may operate in an autonomous mode in an environment during a test period. The vehicle may include at least one sensor coupled to the vehicle, configured to acquire sensor data during the test period. The sensor data may include data representative of a target object in the environment. The vehicle may operate the sensor to obtain the sensor data. The vehicle may define a movement of the vehicle, determine a predicted movement of the target object in the sensor data based on the defined movement, initiate the defined movement of the vehicle at an initiation time during the test period, complete the defined movement of the vehicle at a completion time during the test period, analyze the sensor data obtained during the test period, and determine a latency of the at least one sensor based on the analyzed data.

Abstract: Aspects of the disclosure relate generally to speed control in an autonomous vehicle. For example, an autonomous vehicle may include a user interface which allows the driver to input speed preferences. These preferences may include the maximum speed above the speed limit the user would like the autonomous vehicle to drive when other vehicles are present and driving above or below certain speeds. The other vehicles may be in adjacent or the same lane the vehicle, and need not be in front of the vehicle.

Abstract: A method and apparatus is provided for controlling the operation of an autonomous vehicle. According to one aspect, the autonomous vehicle may track the trajectories of other vehicles on a road. Based on the other vehicle's trajectories, the autonomous vehicle may generate a pool of combined trajectories. Subsequently, the autonomous vehicle may select one of the combined trajectories as a representative trajectory. The representative trajectory may be used to change at least one of the speed or direction of the autonomous vehicle.

Abstract: In an example implementation, an autonomous vehicle is configured to detect closures and lane shifts in a lane of travel. The vehicle is configured to operate in an autonomous mode and determine a presence of an obstacle substantially positioned in a lane of travel of the vehicle using a sensor. The lane of travel has a first side, a second side, and a center, and the obstacle is substantially positioned on the first side. The autonomous vehicle includes a computer system. The computer system determines a lateral distance between the obstacle and the center, compares the lateral distance to a pre-determined threshold, and provides instructions to control the autonomous vehicle based on the comparison.

Abstract: Methods and devices for using uncertainty regarding observations of traffic intersections to modify behavior of a vehicle are disclosed. In one embodiment, an example method includes determining a state of a traffic intersection using information from one or more sensors of a vehicle. The vehicle may be configured to operate in an autonomous mode. The method may also include determining an uncertainty associated with the determined state of the traffic intersection. The method may further include controlling the vehicle in the autonomous mode based on the determined state of the traffic intersection and the determined uncertainty.

Abstract: Aspects of the disclosure relate generally to detecting the edges of lane lines. Specifically, a vehicle driving on a roadway may use a laser to collect data for the roadway. A computer may process the data received from the laser in order to extract the points which potentially reside on two lane lines defining a lane. The extracted points are used by the computer to determine a model of a left lane edge and a right lane edge for the lane. The model may be used to estimate a centerline between the two lane lines. All or some of the model and centerline estimates, may be used to maneuver a vehicle in real time and also to update or generate map information used to maneuver vehicles.

Abstract: Methods and devices for controlling a vehicle in an autonomous mode are disclosed. In one aspect, an example method is disclosed that includes obtaining lane information that provides an estimated location of a lane of a road on which a vehicle is traveling. The example method further includes determining that the lane information has become unavailable or unreliable and, in response, using a sensor to monitor a first distance and a second distance between the vehicle and a neighboring vehicle, determining first and second relative positions of the neighboring vehicle based on the first and second distances, respectively, and, based on the first and second relative positions, determining an estimated path of the neighboring vehicle. The example method further includes, based on the estimated path, determining an updated estimated location of the lane, and controlling the vehicle based on the updated estimated location of the lane.

Abstract: Methods and devices for controlling a vehicle in an autonomous mode are disclosed. In one aspect, an example method is disclosed that includes obtaining, by a computer system, lane information that provides an estimated location of a lane of a road on which a vehicle is travelling, where the computer system is configured to control the vehicle in an autonomous mode. The example method further includes determining, by the computer system, that the lane information has become unavailable or unreliable and, in response to determining that the lane information has become unavailable or unreliable, the computer system analyzing trajectories of other vehicles to locate a potential merge point on the road and creating a new trajectory that follows the lane at the potential merge point.

Abstract: Aspects of the disclosure relate generally to detecting discrete actions by traveling vehicles. The features described improve the safety, use, driver experience, and performance of autonomously controlled vehicles by performing a behavior analysis on mobile objects in the vicinity of an autonomous vehicle. Specifically, an autonomous vehicle is capable of detecting and tracking nearby vehicles and is able to determine when these nearby vehicles have performed actions of interest by comparing their tracked movements with map data.

Abstract: A method includes receiving, at a computing system, audio data from one or more microphones associated with a vehicle. In one example, the audio data originates from a source external to the vehicle and the vehicle is configured to operate in an autonomous mode. The method also includes processing the audio data to generate directional data related to a direction of the source of the audio data relative to the vehicle and processing the audio data to generate identification data related to an identity of the source of the audio data. Further, the method includes controlling the vehicle in the autonomous mode in response to the directional data and the identification data, using the computing system.

Abstract: A vehicle can be controlled in a first autonomous mode of operation by at least navigating the vehicle based on map data. Sensor data can be obtained using one or more sensors of the vehicle. The sensor data can be indicative of an environment of the vehicle. An inadequacy in the map data can be detected by at least comparing the map data to the sensor data. In response to detecting the inadequacy in the map data, the vehicle can be controlled in a second autonomous mode of operation and a user can be prompted to switch to a manual mode of operation. The vehicle can be controlled in the second autonomous mode of operation by at least obtaining additional sensor data using the one or more sensors of the vehicle and navigating the vehicle based on the additional sensor data.

Abstract: Aspects of the invention relate generally to autonomous vehicles. Specifically, the features described may be used alone or in combination in order to improve the safety, use, driver experience, and performance of these vehicles.

Abstract: Methods and devices for controlling a vehicle in an autonomous mode are disclosed. In one aspect, an example method is disclosed that includes obtaining lane information that provides an estimated location of a lane of a road on which a vehicle is traveling. The example method further includes determining that the lane information has become unavailable or unreliable and, in response, using a sensor to monitor a first distance and a second distance between the vehicle and a neighboring vehicle, determining first and second relative positions of the neighboring vehicle based on the first and second distances, respectively, and, based on the first and second relative positions, determining an estimated path of the neighboring vehicle. The example method further includes, based on the estimated path, determining an updated estimated location of the lane, and controlling the vehicle based on the updated estimated location of the lane.

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.