Abstract: Devices, systems and methods for controlling an exterior and dashboard lights of an autonomous vehicle are described. One example of a method for controlling one or more exterior lights includes receiving, from an autonomous driving system (ADS) of the vehicle, an input to control one or more exterior lights that are part of a lighting system of the vehicle, and transmitting, based on the input, a message to a controller area network (CAN) bus of the lighting system, the message being further based on a driver command upon a determination that a driver-initiated message is received. In an example, the lighting system of the vehicle further comprises a plurality of dashboard lights.

Abstract: A workflow management system is described to manage tasks to be performed with vehicles. The workflow management system includes a workflow management server and a computer located in a vehicle. The workflow management server generates and sends to the computer a record that describes a task to be performed with a vehicle. The task may include collecting sensor data from one or more sensors on the vehicle, or performing a vehicle driving test using an updated operating system to be used by the vehicle. The record can include a starting location and a destination of a route on which the vehicle is to perform the task. The computer receives the record, executes an operating system of the vehicle to perform the task, determines that the task is completed, and sends to a database a record status information that indicates that the task is completed.

Abstract: A system and method for lateral vehicle detection is disclosed. A particular embodiment can be configured to: receive lateral image data from at least one laterally-facing camera associated with an autonomous vehicle; warp the lateral image data based on a line parallel to a side of the autonomous vehicle; perform object extraction on the warped lateral image data to identify extracted objects in the warped lateral image data; and apply bounding boxes around the extracted objects.

Abstract: Techniques are described for transitioning control of a steering system from an autonomous mode in a vehicle to a driver-controlled mode where the driver can control the steering wheel of the steering system. A method includes receiving values that describe an amount of torque and a direction of torque in response to a torque applied to a steering wheel of a steering system operated in an autonomous mode, determining that the values are either greater than or equal to a threshold value or are less than or equal to a negative of the threshold value, determining that the values are measured over a period of time greater than or equal to a pre-determined amount of time, and transitioning the steering system from being operated in the autonomous mode to being operated in a driver-controlled mode in which the steering system is under manual control.

Abstract: Techniques are described for an autonomous vehicle to provide the autonomous vehicle's health-related information, identification information, and/or inspection information to a device that may be used by law enforcement or a government agency or a third-party so that the autonomous vehicle can comply with government regulations and can continue to operate on the road.

Abstract: A power management system is disclosed for managing power in a vehicle. The system may include a power distribution unit (PDU) communicably coupled to a power controller unit located in the vehicle. The power controller unit comprises a microcontroller configured to: receive, from the PDU, a temperature value that indicates a temperature of the PDU, one or more voltage values from the one or more voltage sensors, or one or more current values from the one or more current sensors, perform a determination that the temperature value, the one or more voltage values, or the one or more current values are below one or more of their respective pre-determined threshold values, and send, after the determination, a health status message to a computer located in the vehicle, where the health status message indicates that the PDU is operating in a safe operating condition.

Abstract: A system and method for occluding contour detection using a fully convolutional neural network is disclosed. A particular embodiment includes: receiving an input image; producing a feature map from the input image by semantic segmentation; learning an array of upscaling filters to upscale the feature map into a final dense feature map of a desired size; applying the array of upscaling filters to the feature map to produce contour information of objects and object instances detected in the input image; and applying the contour information onto the input image.

Abstract: Techniques are described for managing redundant steering system for a vehicle. A method includes sending a first control command that instructs a first motor coupled to a steering wheel in a steering system to steer a vehicle, receiving, after sending the first control command, a speed of the vehicle, a yaw rate of the vehicle, and a steering position of the steering wheel, determining, based at least on the speed and the yaw rate, an expected range of steering angles that describes values within which the first motor is expected to steer the vehicle based on the first control command, and upon determining that the steering position of a steering wheel is outside the expected range of steering angles, sending a second control command that instructs a second motor coupled to the steering wheel in the steering system to steer the vehicle.

Abstract: A system and method for large-scale lane marking detection using multimodal sensor data are disclosed. A particular embodiment includes: receiving image data from an image generating device mounted on a vehicle; receiving point cloud data from a distance and intensity measuring device mounted on the vehicle; fusing the image data and the point cloud data to produce a set of lane marking points in three-dimensional (3D) space that correlate to the image data and the point cloud data; and generating a lane marking map from the set of lane marking points.

Abstract: Systems and methods for updating navigational maps based using at least one sensor are provided. In one aspect, a control system for an autonomous vehicle, includes a processor and a computer-readable memory configured to cause the processor to: receive output from at least one sensor located on the autonomous vehicle indicative of a driving environment of the autonomous vehicle, retrieve a navigational map used for driving the autonomous vehicle, and detect one or more inconsistencies between the output of the at least one sensor and the navigational map. The computer-readable memory is further configured to cause the processor to: in response to detecting the one or more inconsistencies, trigger mapping of the driving environment based on the output of the at least one sensor, update the navigational map based on the mapped driving environment, and drive the autonomous vehicle using the updated navigational map.

Abstract: A method of lane detection for a non-transitory computer readable storage medium storing one or more programs is disclosed. The one or more programs include instructions, which when executed by a computing device, cause the computing device to perform the following steps comprising: generating a ground truth associated with lane markings expressed in god's view; receiving features from at least one of a hit-map image and a fitted lane marking, wherein the hit-map image includes a classification of pixels that hit a lane marking, and the fitted lane marking includes pixels optimized based on the hit-map image; and training a confidence module based on the features and the ground truth, the confidence module configured to determine on-line whether a fitted lane marking is reasonable, using parameters that express a lane marking in an arc.

Abstract: A telescopic sensor system for an autonomous vehicle enables sensors located on movable telescopic apparatuses to obtain sensor data when an object obstructs an area scanned by fixed sensors. An example method of controlling a movable telescopic apparatus on an autonomous vehicle includes obtaining, from a first sensor located on the autonomous vehicle, a first sensor data of a first area relative to a location of the autonomous vehicle, performing, from the first sensor data, a first determination that a view of the first area is obstructed, causing, in response to the first determination, a second sensor coupled to the movable telescopic apparatus to extend to a pre-determined position, and obtaining, from the second sensor, a second sensor data of a second area relative to the location of the autonomous vehicle, where the second area includes at least some of the first area.

Abstract: A vehicle position and velocity estimation based on camera and LIDAR data are disclosed.

Abstract: Devices, systems, and methods for a vehicular safety system in autonomous vehicles are described. An example method for safely controlling a vehicle includes selecting, based on a first control command from a first vehicle control unit, an operating mode of the vehicle, and transmitting, based on the selecting, the operating mode to an autonomous driving system, wherein the first control command is generated based on input from a first plurality of sensors, and wherein the operating mode corresponds to one of (a) a default operating mode, (b) a minimal risk condition mode of a first type that configures the vehicle to pull over to a nearest pre-designated safety location, (c) a minimal risk condition mode of a second type that configures the vehicle to immediately stop in a current lane, or (d) a minimal risk condition mode of a third type that configures the vehicle to come to a gentle stop.

Abstract: A system and method for implementing a neural network based vehicle dynamics model are disclosed. A particular embodiment includes: training a machine learning system with a training dataset corresponding to a desired autonomous vehicle simulation environment; receiving vehicle control command data and vehicle status data, the vehicle control command data not including vehicle component types or characteristics of a specific vehicle; by use of the trained machine learning system, the vehicle control command data, and vehicle status data, generating simulated vehicle dynamics data including predicted vehicle acceleration data; providing the simulated vehicle dynamics data to an autonomous vehicle simulation system implementing the autonomous vehicle simulation environment; and using data produced by the autonomous vehicle simulation system to modify the vehicle status data for a subsequent iteration.

Abstract: Disclosed are devices, systems and methods for capturing an image. In one aspect an electronic camera apparatus includes an image sensor with a plurality of pixel regions. The apparatus further includes an exposure controller. The exposure controller determines, for each of the plurality of pixel regions, a corresponding exposure duration and a corresponding exposure start time. Each pixel region begins to integrate incident light starting at the corresponding exposure start time and continues to integrate light for the corresponding exposure duration. In some example embodiments, at least two of the corresponding exposure durations or at least two of the corresponding exposure start times are different in the image.

Abstract: Disclosed are devices, systems and methods for using a rotating camera for vehicular operation. One example of a method for improving driving includes determining, by a processor in the vehicle, that a trigger has activated, orienting, based on the determining, a single rotating camera towards a direction of interest, and activating a recording functionality of the single rotating camera, where the vehicle comprises the single rotating camera and one or more fixed cameras, and where the single rotating camera provides a redundant functionality for, and consumes less power than, the one or more fixed cameras.

Abstract: Techniques are described for determining visibility conditions of an environment in which an autonomous vehicle is operated and performing driving related operations based on the visibility conditions. An example method of adjusting driving related operations of a vehicle includes determining, by a computer located in an autonomous vehicle, a visibility related condition of an environment in which the autonomous vehicle is operating, adjusting, based at least on the visibility related condition, a set of one or more values of one or more variables associated with a driving related operation of the autonomous vehicle, and causing the autonomous vehicle to be driven to a destination by causing the driving related operation of one or more devices located in the autonomous vehicle based on at least the set of one or more values.

Abstract: A system and method for vehicle wheel detection is disclosed. A particular embodiment can be configured to: receive training image data from a training image data collection system; obtain ground truth data corresponding to the training image data; perform a training phase to train one or more classifiers for processing images of the training image data to detect vehicle wheel objects in the images of the training image data; receive operational image data from an image data collection system associated with an autonomous vehicle; and perform an operational phase including applying the trained one or more classifiers to extract vehicle wheel objects from the operational image data and produce vehicle wheel object data.