Abstract: A system and method for monitoring vehicle performance and updating engine control parameters, which provides a solution to the problem of tuning engine control parameters for a vehicle. The core components of the invention are an engine controller coupled to an interface device which communicates with a remote device. Generally speaking, the components are configured as follows: the engine controller receives signals from various sensors in a vehicle and the engine controller controls the engine based on engine control parameters and the signals from the sensors. The interface device monitors the engine control and sensor signals and transmits information to the remote device. The remote device receives the information and sends back updated engine control parameters. The interface device receives the updated engine control parameters and communicates with the engine controller to update the engine control parameters using the updated engine control parameters.

Abstract: In one embodiment, a lidar system includes a light source configured to emit pulses of light and a scanner configured to scan the emitted pulses of light along a high-resolution scan pattern located within a field of regard of the lidar system. The scanner includes one or more scan mirrors configured to (i) scan the emitted pulses of light along a first scan axis to produce multiple scan lines of the high-resolution scan pattern, where each scan line is associated with multiple pixels, each pixel corresponding to one of the emitted pulses of light and (ii) distribute the scan lines of the high-resolution scan pattern along a second scan axis. The high-resolution scan pattern includes one or more of: interlaced scan lines and interlaced pixels.

Abstract: Methods, systems and apparatus, for an unmanned aerial vehicle electromagnetic avoidance and utilization system. One of the methods includes obtaining a flight package indicating a flight pattern associated with inspecting a structure, the flight pattern causing the UAV to remain at a standoff distance from the structure, wherein the standoff distance is based on an electromagnetic field associated with the structure, and wherein the flight pattern is laterally constrained according to a property geofence associated with a right of way of the structure. The UAV is navigated according to the flight pattern, and the UAV captures images of the structure. For an initial portion of the flight pattern, the UAV navigates at an altitude based on the standoff distance and the property geofence towards the structure. The UAV determines a location at which to capture images of the structure, and the UAV provides the captured images to a user device.

Abstract: A calibration and repair system for advanced driver assistance systems (“ADAS”) and features is configured to provide secure, automated workflow management related to the calibration of ADAS. Automated workflows include steps and interfaces to aid in preparation of a vehicle for calibration, local-remote collaboration during calibration, customer interactions, workflow and event notification, user authentication, remote system management, and other tasks. The system is also capable of automatically and dynamically adding new and updated calibration specifications that are usable during local-remote collaboration.

Abstract: A driving support ECU initializes a target trajectory calculation parameter at a start of LCA; calculates, based on the target trajectory calculation parameter, a target trajectory function representing a target lateral position which is a target position of an own vehicle in a lane width direction in accordance with an elapsed time from the start of LCA; calculates a target control amount based on the target trajectory function; when a steering operation by a driver has been detected, again initializes the target trajectory calculation parameter; and recalculates the target trajectory function based on the target trajectory calculation parameter.

Abstract: A carrier aerial vehicle system includes a propulsion component configured to enable the carrier aerial vehicle system to be in flight. The carrier aerial vehicle system further includes a retention mechanism configured to allow a plurality of deployable parasite aerial vehicles to be coupled to the retention mechanism and released from the retention mechanism while the carrier aerial vehicle system is in flight. The carrier aerial vehicle system further includes a communication component configured to enable the carrier aerial vehicle system to wireless communicate with the plurality of parasite deployable aerial vehicles. The carrier aerial vehicle system further includes a processor configured to determine a position on the retention mechanism for each deployable parasite aerial vehicle of the plurality of deployable parasite aerial vehicles.

Abstract: Technologies are generally described for preparation and drone based delivery of food items. In some examples, a delivery vehicle may be arranged for autonomous or semi-autonomous preparation of food items while the vehicle is en route to a delivery destination or parked at the delivery destination. Aerial and/or ground based drones, which may be stored in the vehicle, may be loaded with prepared food items and deliver their payloads to delivery locations. Preparation timing and other parameters for the food items, travel parameters for the delivery vehicle, and/or the delivery destination may be selected based on suitability of the delivery destination for launching/recovering the drones or delivery of the food items to the delivery locations. The drones may carry multiple payloads to multiple locations and may have environmentally controlled storage.

Abstract: The present technology utilizes vehicles in a fleet of vehicles to record weather data samples at many locations in a service area. Each vehicle in the fleet becomes a weather station that can record weather data at many locations and frequently. The weather data can be used to make intelligent decisions regarding fleet management.

Abstract: One variation of a method for influencing entities proximal a road surface includes, at an autonomous vehicle: over a first period of time, detecting a pedestrian proximal a road surface; predicting an initial path of the pedestrian an initial confidence score for the initial path of the pedestrian based on and motion of the pedestrian during the first period of time; in response to the initial confidence score falling below a threshold confidence, replaying an audio track audible to the pedestrian and calculating a revised path of the pedestrian and a revised confidence score for the revised path based on motion of the pedestrian following replay of the audio track; and autonomously navigating across the road surface according to a planned route in response to the revised path of the pedestrian falling outside of the planned route and the revised confidence score exceeding the threshold confidence.

Abstract: An example method includes receiving, at a computing system, parameters from a vehicle, wherein the parameters correspond to a set of associated parameter identifiers (PIDs), and determining, by the computing system, one or more thresholds for one or more PIDs of the set of associated PIDs. The example method additionally includes determining, by the computing system, one or more indicators displayable on a first graph of parameters corresponding to a first PID of the set of associated PIDs. For instance, at least one indicator of the one or more indicators represents a parameter corresponding to a second PID of the set of associated PIDs breaching a threshold associated with the second PID. The example method further includes displaying, by the computing system on a graphical user interface, the first graph of parameters corresponding to the first PID and the one or more indicators on the first graph.

Abstract: A method of assembling a recreational vehicle includes providing a structural panel for installation in the recreational vehicle, which has a surface and a readable image in or internal to the structural panel, with the readable image being located at or near a location on the surface of the structural panel for installing a component at the location. The readable image has to-be-installed component information about the component to be installed at the location and is readable at the surface of the structural panel. The method further includes reading the readable image to determine the to-be-installed component information about the component that is to be installed at the location on the surface of the structural panel.

Abstract: A driving support ECU initializes a target trajectory calculation parameter at a start of LCA; calculates, based on the target trajectory calculation parameter, a target trajectory function representing a target lateral position which is a target position of an own vehicle in a lane width direction in accordance with an elapsed time from the start of LCA; calculates a target control amount based on the target trajectory function; when a steering operation by a driver has been detected, again initializes the target trajectory calculation parameter; and recalculates the target trajectory function based on the target trajectory calculation parameter.

Abstract: Provided are a method and a system for integratedly managing a vehicle operation state. A vehicle integration management method performed by a server implemented by using a computer may include: receiving vehicle operation data related to an operation state of the vehicle from a vehicle terminal mounted or embedded in the vehicle; and providing a service related to the vehicle operation data through a dedicated application on a user terminal used by a user of the vehicle, wherein the providing may provide at least one of an operation report, a parking impact notification, and an accident situation notification based on the vehicle operation data in association with the application.

Abstract: A system and method for generating a 3D model and/or map of a geographic region is disclosed. A computer designates a geographic region and a number of aircraft, and partitions the designated geographic region into sub-regions, creates waypoints within each sub-region, and plans missions for each aircraft to fly to each waypoint and take pictures. The aircraft are configured to accept and perform missions from the computer, and the computer receives images from the aircraft, assigns each image to a sub-region, and transmits each sub-region and images, as well as instructions, to the computing resource. The computing resource executes the instructions, which perform 3D reconstruction and generate orthophotos and 3D models. The 3D reconstruction comprises trimming distorted portions of the orthophotos and 3D models, and merging the orthophotos and 3D models from each sub-region into a 3D model and/or map of the geographic region.

Abstract: The technology involves operation of a self-driving truck or other cargo vehicle when it is being inspected at a weigh station. This may include determining whether a weigh station is open for inspection. Once at the weigh station, the vehicle may follow instructions of an inspection officer or autonomous inspection system. The vehicle may perform predefined actions or operations so that various vehicle systems and safety issues can be evaluated, such as the brakes, lights, tires, connections between the tractor and trailer, exposed fuel tanks, leaks, etc. A visual inspection may be performed to ensure the load is secured, vehicle and cargo documents meet certain criteria, and the carrier's safety record meets any requirements. In addition, the weigh station itself may be operated in a partly or fully autonomous mode when dealing with autonomous and manually driven vehicles.

Abstract: A drive for a machine includes a computer configured to control a first electric motor for driving vehicle wheels and a second electric motor for driving a work attachment. The second electric motor is configured to drive at least one hydraulic pump with an adjustable stroke volume. A sensor is configured to detect the stroke volume of the pump. The computer processes the stroke volume to control the second electric motor.

Abstract: A method and system of determining whether a stationary vehicle is a blocking vehicle to improve control of an autonomous vehicle. A perception engine may detect a stationary vehicle in an environment of the autonomous vehicle from sensor data received by the autonomous vehicle. Responsive to this detection, the perception engine may determine feature values of the environment of the vehicle from sensor data (e.g., features of the stationary vehicle, other object(s), the environment itself). The autonomous vehicle may input these feature values into a machine-learning model to determine a probability that the stationary vehicle is a blocking vehicle and use the probability to generate a trajectory to control motion of the autonomous vehicle.

Abstract: A multi-stop route selection system may include a telematics device associated with a vehicle having one or more sensors arranged therein, a mobile device, and a server computer. The server computer may receive driving data of a driver of the vehicle and a vehicle location from the telematics device, determine one or more driving behaviors of the driver based on the driving data, receive data regarding a calendar of the driver from the mobile device, identify a plurality of appointments in the calendar, determine a route comprising multiple destinations for the driver based on the vehicle location, the one or more driving behaviors, and the plurality of appointments, transmit the route to the mobile device, receive a request to add a new destination to the route from the mobile device, generate a modified route comprising the new destination, and transmit the modified route for the driver to the mobile device.

Abstract: Embodiments of the present invention provide systems and methods for combining sensor data to measure vehicle movement. Embodiments may collect vehicle and driving data using sensors of a mobile device of a user, such as a location determination sensor and a movement determination sensor. In some embodiments, the data from the sensors may be combined to more accurately estimate vehicle movement, such as vehicle acceleration.

Abstract: This document describes methods and systems for enabling an autonomous vehicle (AV) to determine a path to a stopping location. The AV will determine a desired stop location (DSL) that is associated with a service request. The AV's motion control system will move the AV along a path to the DSL. While moving along the path, the AV's perception system will detect ambient conditions near the DSL. The ambient conditions will be parameters associated with a stopping rule. The AV will apply the stopping rule to the ambient conditions to determine whether the stopping rule permits the AV to stop at the DSL. If the stopping rule permits the AV to stop at the DSL, the motion control system will move the AV to, and stop at, the DSL. Otherwise, the motion control system will not stop the AV at the DSL.