Abstract: A data-driven prediction-based system and method for trajectory planning of autonomous vehicles are disclosed. A particular embodiment includes: generating a first suggested trajectory for an autonomous vehicle; generating predicted resulting trajectories of proximate agents using a prediction module; scoring the first suggested trajectory based on the predicted resulting trajectories of the proximate agents; generating a second suggested trajectory for the autonomous vehicle and generating corresponding predicted resulting trajectories of proximate agents, if the score of the first suggested trajectory is below a minimum acceptable threshold; and outputting a suggested trajectory for the autonomous vehicle wherein the score corresponding to the suggested trajectory is at or above the minimum acceptable threshold.

Abstract: A system and method for real world autonomous vehicle trajectory simulation may include: receiving training data from a data collection system; obtaining ground truth data corresponding to the training data; performing a training phase to train a plurality of trajectory prediction models; and performing a simulation or operational phase to generate a vicinal scenario for each simulated vehicle in an iteration of a simulation. Vicinal scenarios may correspond to different locations, traffic patterns, or environmental conditions being simulated. Vehicle intention data corresponding to a data representation of various types of simulated vehicle or driver intentions.

Abstract: Various embodiments of the present disclosure provide a system and method for lane marking localization that may be utilized by autonomous or semi-autonomous vehicles traveling within the lane. In the embodiment, the system comprises a locating device adapted to determine the vehicle's geographic location; a database; a region map; a response map; a camera; and a computer connected to the locating device, database, and camera, wherein the computer is adapted to: receive the region map, wherein the region map corresponds to a specified geographic location; generate the response map by receiving information form the camera, the information relating to the environment in which the vehicle is located; identifying lane markers observed by the camera; and plotting identified lane markers on the response map; compare the response map to the region map; and generate a predicted vehicle location based on the comparison of the response map and region map.

Abstract: A system and method for instance-level lane detection for autonomous vehicle control are disclosed.

Abstract: A system is disclosed including at least one memory including computer program instructions, which when executed by at least one processor, cause the system to at least generate, based on a plurality of images from a camera, a first map including a first plurality of features; generate, based on data from a light ranging sensor, a second map including a second plurality of features; and determine, based on a comparison of the first plurality of features and the second plurality of features, a position of the first map relative to the second map. A corresponding method and non-transitory computer-readable medium are also provided.

Abstract: Techniques are disclosed for performing hybrid simulation operations with an autonomous vehicle. A method of testing autonomous vehicle operations includes receiving, by a computer, a pre-configured scenario that includes one or more simulation parameters and one or more initial condition parameters, sending, to the autonomous vehicle and based on the one or more initial condition parameters, control signals that instruct the autonomous vehicle to operate at an operative condition, and in response to determining that the autonomous vehicle is operating at the operative condition, performing a simulation with the one or more simulated objects and the autonomous vehicle to test a response of the autonomous vehicle.

Abstract: A system and method for online real-time multi-object tracking is disclosed. A particular embodiment can be configured to: receive image frame data from at least one camera associated with an autonomous vehicle; generate similarity data corresponding to a similarity between object data in a previous image frame compared with object detection results from a current image frame; use the similarity data to generate data association results corresponding to a best matching between the object data in the previous image frame and the object detection results from the current image frame; cause state transitions in finite state machines for each object according to the data association results; and provide as an output object tracking output data corresponding to the states of the finite state machines for each object.

Abstract: Devices, systems and methods for fusing scenes from real-time image feeds from on-vehicle cameras in autonomous vehicles to reduce redundancy of the information processed to enable real-time autonomous operation are described. One example of a method for improving perception in an autonomous vehicle includes receiving a plurality of cropped images, wherein each of the plurality of cropped images comprises one or more bounding boxes that correspond to one or more objects in a corresponding cropped image; identifying, based on the metadata in the plurality of cropped images, a first bounding box in a first cropped image and a second bounding box in a second cropped image, wherein the first and second bounding boxes correspond to a common object; and fusing the metadata corresponding to the common object from the first cropped image and the second cropped image to generate an output result for the common object.

Abstract: Techniques for analysis of autonomous vehicle operations are described. As an example, a method of autonomous vehicle operation includes storing sensor data from one or more sensors located on the autonomous vehicle into a storage medium, performing, based on at least some of the sensor data, a simulated execution of one or more programs associated with the operations of the autonomous vehicle, generating, based on the simulated execution of the one or more programs and as part of a simulation, one or more control signal values that control a simulated driving behavior of a simulated vehicle, and providing a visual feedback of the simulated driving behavior of the simulated vehicle on a simulated road.

Abstract: A control subsystem, method and computer program product are provided to detect the failure of a tire of an autonomous vehicle (AV) and to direct a response to the tire failure that has been detected that is appropriate under the circumstances. In this regard, the control subsystem includes processing circuitry configured to receive signals from microphone(s) carried by the AV. The processing circuitry is configured to evaluate signal characteristics of the signals to identify signals indicative of a tire failure. In an instance in which a tire failure is identified, the processing circuitry is configured to determine a type of the tire failure based upon the signal characteristics. The processing circuitry is further configured to determine remedial action to be taken based at least in part upon the type of tire failure. Different remedial actions are determined to be taken for different types of tire failures.

Abstract: Techniques are described for estimating pose of a camera located on a vehicle. An exemplary method of estimating camera pose includes obtaining, from a camera located on a vehicle, an image including a lane marker on a road on which the vehicle is driven, and estimating a pose of the camera such that the pose of the camera provides a best match according to a criterion between a first position of the lane marker determined from the image and a second position of the lane marker determined from a stored map of the road.

Abstract: Techniques are described to determine parameters and/or values for a control model that can be used to operate an autonomous vehicle, such as an autonomous semi-trailer truck. For example, a method of obtaining a data-driven model for autonomous driving may include obtaining data associated with a first set of variables that characterize movements of an autonomous vehicle over time and commands provided to the autonomous vehicle over time, determining, using at least the first set of data, non-zero values and an associated second set of variables that describe a control model used to perform an autonomous driving operation of the autonomous vehicle, and calculating values for a feedback controller that describes a transfer function used to perform the autonomous driving operation of the autonomous vehicle driven on a road.

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: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for predictive abnormal state detection for autonomous vehicles. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that which evaluate signal characteristics of one or more signals associated with an autonomous vehicle to identify signal characteristics of an abnormal operational state. In an instance one or more abnormal operational states are identified, the autonomous vehicle may perform a safety maneuver within a time window with respect to a safety location.

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 areal world autonomous vehicle based on the vehicle control messages received from the autonomous vehicle control system.

Abstract: Systems and methods for detecting trailer angle are provided. In one aspect, an in-vehicle control system includes an optical sensor configured to be mounted on a tractor so as to face a trailer coupled to the tractor, the optical sensor further configured to generate optical data indicative of an angle formed between the trailer and the tractor. The system further includes a processor and a computer-readable memory in communication with the processor and having stored thereon computer-executable instructions to cause the processor to receive the optical data from the optical sensor, determine at least one candidate plane representative of a surface of the trailer visible in the optical data based on the optical data, and determine an angle between the trailer and the tractor based on the at least one candidate plane.

Abstract: Systems and techniques disclosed in this patent document provide novel and efficient ground transportation of goods by self-driving trucks based on a system of infrastructures with shipping hub facilities serving as warehouses and services centers in accordance with unique characteristics of operating autonomous self-driving trucks without entirely relying on human drivers, including features to cover technological issues, fleet management issues, and customer service issues. In addition, the disclosed systems and techniques may be implemented to integrate other fleet services and modes of transportation of goods with transportation services by self-driving trucks.

Abstract: A system comprises an autonomous vehicle (AV) and an operation server operably coupled with the AV. The operation server accesses environmental data associated with a road traveled by the AV. The environmental data is associated with a time window during which the AV is traveling along the road. The operation server compares the environmental data with map data that comprises expected road conditions ahead of the AV. The operation server determines whether the environmental data comprises an unexpected road condition that is not included in the map data. In response to determining that the environmental data comprises the unexpected road condition that is not included in the map data, the operation server determines a location coordinate of the unexpected road condition, and communicates a command to the AV to maneuver to avoid the unexpected road condition.

Abstract: A system comprises a lead autonomous vehicle (AV), a control device associated with the lead AV, and a following AV. The control device receives a command to navigate the lead AV to avoid an unexpected road condition. The control device receives sensor data from a sensor of the lead AV, comprising location coordinates of objects ahead of the lead AV. The control device accesses environmental data associated with a portion of a road between the lead AV and following AV. The environmental data comprises location coordinates of objects between the lead AV and following AV. The control device determines whether an object in the sensor data or environmental data impedes performing the command by the following AV. The control device updates the command, if the control device determines that an object impedes performing the command by the following AV, and communicates the updated command to the following AV.

Abstract: Various embodiments of the present invention provide methods, apparatus, systems, computing devices, computing entities, and/or the like for dynamic allocation of communication network resources by an autonomous vehicle. For example, certain embodiments of the present invention utilize systems, methods, and computer program products that determine a data transmission prioritization policy and cause an auxiliary data object to be provided based at least in part on the data transmission prioritization policy.