Abstract: Systems and methods for dynamic predictive control of autonomous vehicles are disclosed. In one aspect, an in-vehicle control system for a semi-truck includes one or more control mechanisms configured to control movement of the semi-truck and a processor. The system further includes computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive a desired trajectory and a vehicle status of the semi-truck, determine a dynamic model of the semi-truck based on the desired trajectory and the vehicle status, determine at least one quadratic program (QP) problem based on the dynamic model, generate at least one control command for controlling the semi-truck by solving the at least one QP problem, and provide the at least one control command to the one or more control mechanisms.

Abstract: An autonomous vehicle simulation system for analyzing motion planners is disclosed. A particular embodiment includes: receiving map data corresponding to a real world driving environment; obtaining perception data and configuration data including pre-defined parameters and executables defining a specific driving behavior for each of a plurality of simulated dynamic vehicles; generating simulated perception data for each of the plurality of simulated dynamic vehicles based on the map data, the perception data, and the configuration data; receiving vehicle control messages from an autonomous vehicle control system; and simulating the operation and behavior of a real world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.

Abstract: Techniques are described for managing temperature in an autonomous vehicle. An exemplary method comprises performing autonomous driving operations that operate the autonomous vehicle in an autonomous mode, receiving one or more messages from a temperature sensor associated with an electrical device located on or in the autonomous vehicle while the autonomous vehicle is operated in the autonomous mode, determining a cooling technique to reduce the temperature of electrical device, and performing the cooling technique.

Abstract: Disclosed are devices, systems and methods for securing wireless communications between a remote monitor center and a vehicle by using redundancy measures to increase the robustness of the system. In some embodiments, a system may include redundant communication channels, deploy redundant hardware and software stacks to enable switching to a backup in an emergency situation, and employ hypervisors at both the remote monitor center and the vehicle to monitor hardware and software resources and perform integrity checks. In other embodiments, message digests based on a cryptographic hash function and a plurality of predetermined commands are generated at both the remote monitor center and the vehicle, and compared to ensure the continuing integrity of the wireless communication system.

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: A system comprises an autonomous vehicle (AV) and a control device operably coupled with the AV. The control device receives, from an operation server, a command to navigate the AV to avoid an expected road condition. The control device receives, from sensors of the AV, sensor data comprising location coordinates of a plurality of objects ahead of the AV. The control device determines whether at least one object from the plurality of objects impedes performing the command. In response to determining that at least one object impedes performing the command, the control device updates the command, such that the updated command comprises one or more navigation instructions to avoid the at least one object while performing the command. The control device navigates the AV according to the updated command.

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: Disclosed are devices, systems and methods for an audio assistant in an autonomous or semi-autonomous vehicle. In one aspect the informational audio assistant receives a first set of data from a vehicle sensor and identifies an object or condition using the data from the vehicle sensor. Audio is generated representative of a perceived danger of an object or condition. A second set of data from the vehicle sensor subsystem is received and the informational audio assistant determines whether an increased danger exists based on a comparison of the first set of data to the second set of data. The informational audio assistant will apply a sound profile to the generated audio based on the increased danger.

Abstract: A method for controlling an autonomous vehicle includes collecting data about a surrounding of the autonomous vehicle, the data including global information of where the autonomous vehicle is positioned; deriving, at least in part based on the collected data, a perceived environment based on localizing the global information; determining a driving condition of the autonomous vehicle based on the perceived environment; modifying, according to the determined driving condition, a first configuration parameter of a sensor to adjust an amount of output data from the sensor; and simultaneously adjusting, according to the determined driving condition, a second configuration parameter for processing the output data to allow consistent data capturing and processing of the output data. A control system can employ such a method, and an autonomous vehicle can utilize such a control system.

Abstract: Techniques are described to estimate orientation of one or more cameras located on a vehicle. The orientation estimation technique can include obtaining an image from a camera located on a vehicle while the vehicle is being driven on a road, determining, from a terrain map, a location of a landmark located at a distance from a location of the vehicle on the road, determining, in the image, pixel locations of the landmark, selecting one pixel location from the determined pixel locations; and calculating values that describe an orientation of the camera using at least an intrinsic matrix and a previously known extrinsic matrix of the camera, where the intrinsic matrix is characterized based on at least the one pixel location and the location of the landmark.

Abstract: Described is a two-level optimal path planning process for autonomous tractor-trailer trucks which incorporates offline planning, online planning, and utilizing online estimation and perception results for adapting a planned path to real-world changes in the driving environment. In one aspect, a method of navigating an autonomous vehicle includes determining, by an online server, a current vehicle state of the autonomous vehicle in a mapped driving area. The method includes receiving, by the online server from an offline path library, a path for the autonomous driving vehicle through the mapped driving area from the current vehicle state to a destination vehicle state, and receiving fixed and moving obstacle information. The method includes adjusting the path to generate an optimized path that avoids the fixed and moving obstacles and ends at a targeted final vehicle state, and navigating the autonomous vehicle based on the optimized path.

Abstract: An autonomous vehicle includes a detection system for identifying the presence changes in wind incident on the autonomous vehicle, particularly wind gusts. The detection system may include one or more wind sensors, particularly those configured to detect wind incident on the vehicle from a direction that is transverse or perpendicular to the direction of motion of the autonomous vehicle. Additionally, systems may be present that correlate the detected wind gusts to changes in the behavior of the autonomous vehicle. The autonomous vehicle may react to the detected wind gusts by altering the vehicle's trajectory, by stopping the vehicle, or by communicating with a control center for further instructions.

Abstract: An apparatus is provided to comprise: at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to: receive, from an electronic control unit of a vehicle, a test result comprising a result of a self test performed by the electronic control unit; analyze the received test result to determine a vehicle status, the vehicle status comprising a status indicator and status information to be included in a report; periodically transmit, to a remote system according to a first time period, a report including the vehicle status, a duration of the first time period being dependent on the vehicle status; receive, from the remote system, a control command; and in response to the control command being received, implement the control command.

Abstract: Devices, systems, and methods for hardware-based time synchronization for heterogenous sensors are described. An example method includes generating a plurality of input trigger pulses having a nominal pulse-per-second (PPS) rate, generating, based on timing information derived from the plurality of input trigger pulses, a plurality of output trigger pulses, and transmitting the plurality of output trigger pulses to a sensor of a plurality of sensors, wherein a frequency of the plurality of output trigger pulses corresponds to a target operating frequency of the sensor, wherein, in a case that a navigation system coupled to the synchronization unit is functioning correctly, the plurality of input trigger pulses is generated based on a nominal PPS signal from the navigation unit, and wherein, in a case that the navigation system is not functioning correctly, the plurality of input trigger pulses is generated based on a simulated clock source of the synchronization unit.

Abstract: A method, apparatus and computer program product are configured to generate, based on a user profile, one or more dynamic inspection task checklists for a respective autonomous vehicle (AV) of one or more AVs in an AV fleet based on a first enterprise-defined task protocol. The one or more dynamic inspection task checklists are associated with one or more respective AV subsystems, and the user profile is associated with a respective user role such that the one or more dynamic inspection task checklists differ dependent upon the respective user role. The method, apparatus and computer program product are also configured to cause the one or more dynamic inspection task checklists to be rendered via an interactive inspection interface of a user computing device associated with the user profile such that one or more respective inspection tasks comprised in the one or more dynamic inspection task checklists are interactive.

Abstract: Disclosed are devices, systems and methods for the operational testing on autonomous vehicles. One exemplary method includes configuring a primary vehicular model with an algorithm, calculating one or more trajectories for each of one or more secondary vehicular models that exclude the algorithm, configuring the one or more secondary vehicular models with a corresponding trajectory of the one or more trajectories, generating an updated algorithm based on running a simulation of the primary vehicular model interacting with the one or more secondary vehicular models that conform to the corresponding trajectory in the simulation, and integrating the updated algorithm into an algorithmic unit of the autonomous vehicle.

Abstract: Image processing techniques are described to obtain an image from a camera located on a vehicle while the vehicle is being driven, cropping a portion of the obtained image corresponding to a region of interest, detecting an object in the cropped portion, adding a bounding box around the detected object, determining position(s) of reference point(s) on the bounding box, and determining a location of the detected object in a spatial region where the vehicle is being driven based on the determined one or more positions of the second set of one or more reference points on the bounding box.

Abstract: Techniques are described for measuring angle and/or orientation of a rear drivable section (e.g., a trailer unit of a semi-trailer truck) relative to a front drivable section (e.g., a tractor unit of the semi-trailer truck) using an example rotary encoder assembly. The example rotary encoder assembly comprises a base surface; a housing that includes a second end that is connected to the base surface and a first end that is at least partially open and is coupled to a housing cap; and a rotary encoder that is located in the housing in between the base surface and the housing cap, where the rotary encoder includes a rotatable shaft that protrudes from a first hole located in the housing cap, and where a top of the rotatable shaft located away from the rotary encoder is coupled to magnet(s).

Abstract: A system and method for taillight signal recognition using a convolutional neural network is disclosed. An example embodiment includes: receiving a plurality of image frames from one or more image-generating devices of an autonomous vehicle; using a single-frame taillight illumination status annotation dataset and a single-frame taillight mask dataset to recognize a taillight illumination status of a proximate vehicle identified in an image frame of the plurality of image frames, the single-frame taillight illumination status annotation dataset including one or more taillight illumination status conditions of a right or left vehicle taillight signal, the single-frame taillight mask dataset including annotations to isolate a taillight region of a vehicle; and using a multi-frame taillight illumination status dataset to recognize a taillight illumination status of the proximate vehicle in multiple image frames of the plurality of image frames, the multiple image frames being in temporal succession.

Abstract: Described are devices, systems and methods for real-time remote control of vehicles with high redundancy. In some embodiments, two copies of at least one control command are received using two different wireless communication protocols, and are compared. The at least one control command is executed when the two copies are in agreement, but is rejected when the two copies differ. In other embodiments, additional wireless communication protocols may exist to provide a redundant mode of communication when one of the two different wireless communication protocols are unavailable. In yet other embodiments, redundant GPS units may be used to determine availability of any of the communication protocols, and relevant control commands may be downloaded in advance to circumvent a lack of coverage.