Abstract:
Methods and systems for construction zone object detection are described. A computing device may be configured to receive, from a LIDAR, a 3D point cloud of a road on which a vehicle is travelling. The 3D point cloud may comprise points corresponding to light reflected from objects on the road. Also, the computing device may be configured to determine sets of points in the 3D point cloud representing an area within a threshold distance from a surface of the road. Further, the computing device may be configured to identify construction zone objects in the sets of points. Further, the computing device may be configured to determine a likelihood of existence of a construction zone, based on the identification. Based on the likelihood, the computing device may be configured to modify a control strategy of the vehicle; and control the vehicle based on the modified control strategy.
Abstract:
Methods and systems for detection of a construction zone using information from a plurality of sources are described. In an example, a computing device, configured to control the vehicle, may be configured to receive information, from a plurality of sources, relating to detection of a construction zone on the road on which the vehicle is travelling. Also, the computing device may be configured to determine a likelihood of existence of the construction zone on the road, based on the information. Further the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle, based on the likelihood; and control the vehicle based on the modified control strategy.
Abstract:
Various embodiments of the invention may use a radio frequency identification (RFID) tag with a writable non-volatile storage element to receive and store configuration parameters for a device connected to the RFID tag, even if the device itself is powered off. Upon power-up and startup of the device, the device may read the configuration parameters from the RFID tag and install them for its subsequent operation. Some embodiments may work in the opposite direction, by allowing the powered device to write its configuration data into the RFID tag's storage element, whose contents may subsequently be transmitted by the RFID tag to an RFID reader, even if the device is unpowered at the time of transmission.
Abstract:
Methods and systems for construction zone sign detection are described. A computing device may be configured to receive a 3D point cloud of a vicinity of a road on which a vehicle is travelling. The 3D point cloud may include points corresponding to light reflected from objects in the vicinity of the road. The computing device may be configured to determine a set of points representing an area at a given height from a surface of the road, and estimate a shape associated with the set of points. Further, the computing device may be configured to determine a likelihood that the set of points represents a construction zone sign, based on the estimated shape. Based on the likelihood, the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle; and control the vehicle based on the modified control strategy.
Abstract:
Aspects of the disclosure relate generally to maneuvering autonomous vehicles. Specifically, the vehicle may use a laser to collect scan data for a section of roadway. The vehicle may access a detailed map including the section of the roadway. A disturbance indicative of an object and including a set of data points data may be identified from the scan data based on the detailed map. The detailed map may also be used to estimate a heading of the disturbance. A bounding box for the disturbance may be estimated using the set of data points as well as the estimated heading. The parameters of the bounding box may then be adjusted in order to increase or maximize the average density of data points of the disturbance along the edges of the bounding box visible to the laser. This adjusted bounding box may then used to maneuver the vehicle.
Abstract:
Various embodiments of the invention may use a radio frequency identification (RFID) tag with a writable non-volatile storage element to receive and store configuration parameters for a device connected to the RFID tag, even if the device itself is powered off. Upon power-up and startup of the device, the device may read the configuration parameters from the RFID tag and install them for its subsequent operation. Some embodiments may work in the opposite direction, by allowing the powered device to write its configuration data into the RFID tag's storage element, whose contents may subsequently be transmitted by the RFID tag to an RFID reader, even if the device is unpowered at the time of transmission.
Abstract:
Methods and systems for detection of a construction zone using information from a plurality of sources are described. In an example, a computing device, configured to control the vehicle, may be configured to receive information, from a plurality of sources, relating to detection of a construction zone on the road on which the vehicle is travelling. Also, the computing device may be configured to determine a likelihood of existence of the construction zone on the road, based on the information. Further the computing device may be configured to modify a control strategy associated with a driving behavior of the vehicle, based on the likelihood; and control the vehicle based on the modified control strategy.
Abstract:
A method and apparatus are provided for optimizing one or more object detection parameters used by an autonomous vehicle to detect objects in images. The autonomous vehicle may capture the images using one or more sensors. The autonomous vehicle may then determine object labels and their corresponding object label parameters for the detected objects. The captured images and the object label parameters may be communicated to an object identification server. The object identification server may request that one or more reviewers identify objects in the captured images. The object identification server may then compare the identification of objects by reviewers with the identification of objects by the autonomous vehicle. Depending on the results of the comparison, the object identification server may recommend or perform the optimization of one or more of the object detection parameters.