Abstract: A steering for a marine propulsion unit adjusts at least one of a required steering speed and a required steering torque such that the required steering speed and the required steering torque fall within an output region when the required steering speed and the required steering torque are outside the output region, sets a target steering angle according to the adjusted required steering speed and required steering torque, and sets the target steering angle according to a rotation angle of a steering wheel when the required steering speed and the required steering torque are within the output region.

Abstract: A rearwardly directed movement of a first vehicle that has a driving assistance system that can be controlled, the driving assistance system having at least one sensor and a control device, in which threshold values for triggering a warning intervention and/or braking intervention in respect of the interval in relation to at least one further road user are set, and additionally being connected to or having a camera, by which activated travel-direction indicators of a further road user are recognized, which travel-direction indicators are included in the calculation of a probable trajectory of the further road user, and a probability of a collision is calculated, according to which the threshold values are lowered or raised.

Abstract: Aspects of the disclosure provide for controlling an autonomous vehicle having an autonomous driving mode. For instance, sensor data generated by a perception system of a vehicle may be received. The sensor data identifying objects in an environment of the vehicle. A trajectory corresponding to a future path of the vehicle may be received. That the vehicle is approaching an unmarked crosswalk situation may be determined based on the trajectory and the sensor data. In response to the determination, an area for an unmarked crosswalk is identified. The vehicle may be controlled in the autonomous driving mode based on the determination and the area.

Abstract: A method and system provide for temporal fusion of depth maps in an image space representation. A series of depth maps are obtained/acquired from one or more depth sensors at a first time. A first Gaussian mixture model (GMM) is initialized using one of the series of depth maps. A second depth map is obtained from the depth sensors at a second time. An estimate of the motion of the depth sensors, from the first time to the second time, is received. A predictive GMM at the second time is created based on a transform of the first GMM and the estimate of the motion. The predictive GMM is updated based on the second depth map.

Abstract: A system or method implemented by an autonomous vehicle involves determining a path plan to reach a destination from an origin. The path plan includes two or more path steps indicating tasks to be completed to reach the destination. The method includes, during traversal of the path plan by the autonomous vehicle, evaluating one or more of the two or more path steps of a planning horizon to determine a behavior plan for the planning horizon. The planning horizon is based on a current position of the autonomous vehicle, the behavior plan includes a speed and a trajectory, and the evaluating includes performing a cost analysis using a parallelized tree-based decision scheme at each of two or more simulation intervals within the planning horizon. The evaluating and the determining the behavior plan is repeated at two or more positions of the autonomous vehicle from the origin to the destination.

Abstract: In one example, a method for resolving sensor conflicts in autonomous vehicles includes monitoring conditions around the autonomous vehicle by analyzing data received from a plurality of sensors, detecting a conflict in the data received from two sensors of the plurality of sensors, sending a first instruction to an auxiliary sensor of the autonomous vehicle that is not one of the plurality of sensors, wherein the first instruction instructs the auxiliary sensor to gather additional data about the conditions around the autonomous vehicle, receiving the additional data from the auxiliary sensor, and making a decision regarding operation of the autonomous vehicle, wherein the decision is based at least in part on the additional data.

Abstract: The invention relates to a method for updating a digital map of a mobile navigation system, in particular a navigation system of a motor vehicle, wherein the updating of map data is improved with respect to the availability of current map data and the minimization of the data volume to be transferred (and thus also the avoidance of the updating of map data that are not required at all). For this purpose, a geographic region comprised by the digital map is divided into a plurality of regions, wherein map data of the digital map represent respective regions, wherein at least one of the regions has a first boundary line directly surrounding the region, wherein the region has an additional boundary line, which surrounds the region with greater distance than the first boundary line at least in some sections.

Abstract: Systems and methods are described for determining an actual pose of an articulating boom arm using an artificial intelligence mechanism (e.g., a neural network) trained to determine the actual pose of the articulating boom arm based on captured image data. In some implementations, an electronic processor is configured to control movement of the articulating boom arm based at least in part on pose information determined by applying the image-based neural network. In some implementations, an electronic processor is configured to train the neural network by using, as training data, captured image data and output signals from sensors indicative of measured positions of the components of the articulating boom arm.

Abstract: A watercraft includes an information acquirer and a controller. The controller starts data transmission when a communication start condition based on at least one of a reception strength of a radio wave received by a communication terminal from a base station, a rotation speed of an engine, a traveling speed of a hull, and a state of a shift device is satisfied, and does not start the data transmission when the communication start condition is not satisfied.

Abstract: A system is provided for performing an automated range estimation process for an electric vehicle using a processor. Included in the system is a range estimator configured to estimate an initial value of an energy required to travel a unit distance for the electric vehicle. The range estimator generates a first estimation model based on a correlation between a maximum all-electric-range and the energy required to travel a unit distance. Then, the first estimation model is adjusted based on one or more predetermined driving conditions. The maximum all-electric-range of the electric vehicle is updated based on the adjusted first estimation model. An estimated range of the electric vehicle is calculated based on the updated maximum all-electric-range of the electric vehicle and a fraction of total energy capability remaining in the electric vehicle. The estimated range of the electric vehicle is outputted and is used to control the electric vehicle.

Abstract: The present technology pertains to visualization of maps used for autonomous vehicle applications. These maps include many layers of dense information. Each layer can be stored in a vector format and small portions, called tiles, of a map can be requested by a users web browser. The web browser can filter for desired layers and render all desired map layers at once to provide visualization of map and layers of interest.

Abstract: Provided is an electric suspension device including an electromagnetic actuator that is provided between a body and wheel of a vehicle and generates damping force for damping vibration of the body. It includes: an information acquisition unit that acquires information on a sprung speed and sprung acceleration of the vehicle; a bounce target value computation unit that computes a bounce target value for controlling the vehicle's bounce orientation based on the sprung speed; and a driving control unit that controls driving of the actuator with a control target load which is based on the bounce target value. The bounce target value computation unit has a bounce target load map in which the bounce target value is associated with the sprung speed. The bounce target value computation unit adjusts a width of a dead zone set in the map based on the information on the sprung speed and sprung acceleration.

Abstract: The invention provides systems and methods for an Intelligent Road Infrastructure System (IRIS), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. IRIS systems and methods provide vehicles with individually customized information and real-time control instructions for vehicle driving tasks such as car following, lane changing, and route guidance. IRIS systems and methods also manage transportation operations and management services for both freeways and urban arterials. The IRIS manages one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control. IRIS is supported by real-time wired and/or wireless communication, power supply networks, and cyber safety and security services.

Abstract: A locomotive inspection system includes sensors that are selectively coupled to a locomotive during an inspection or maintenance event for the locomotive and a controller that is operable to cause a control system of the locomotive that controls plural operations of the locomotive to initiate a first operation and a different, second operation. The controller determines whether the control system has first sensor information indicative of a state of the locomotive during the first operation. The controller sends a command signal to the control system to direct the control system to change locomotive operations from the first operation to the second operation responsive to determining that the control system lacks the first sensor information. The controller obtains second sensor information from the one or more sensors based on the second operation and determines a condition of components of the locomotive based on the first and second sensor information.

Abstract: A system accesses a three-dimensional map of a geographic region and generates a two-dimensional projection of the road based on the three-dimensional map. The two-dimensional projection comprises a plurality of points along the road and each point is assigned a score measuring a navigability of the point. Based on the navigability score of each point and history of vehicle positions on the road, the system identifies a plurality of navigable points on the two-dimensional projection of the road. Based on the plurality of navigable points, the system determines a navigable surface corresponding to a physical area over which a vehicle may safely navigate and navigable surface boundaries surrounding that area. The navigable surface area and boundaries on the two-dimensional projection are converted into a three-dimensional representation, which the system uses to generate an updated three-dimensional map of the geographic region.

Abstract: Methods and systems are provided for coordinating engine and motor torque in a hybrid vehicle system. The systems and methods use an engine torque command to obtain a motor torque command, and adjust the engine torque command based on an estimate of a time delay between commanded and actual motor torque prior to the engine command being sent to an engine controller. In this way, crankshaft torque accuracy may be improved.

Abstract: Systems and methods for data acquisition utilizing spare or unused databus capacity are provided. In one example aspect, the system includes a vehicle that includes an engine and a controller. The controller generates a data file indicative of Continuous Engine Operation Data (CEOD). The data file is transmitted over a serial databus to a bus recorder. Particularly, the data file is continuously generated by the controller and stored in a buffer. The available bandwidth of a transmission frame for the serial databus is determined. A portion of the data file is retrieved from the buffer based at least in part on the determined bandwidth. The portion of the data file is divided into relatively small transmission payloads and packed into the available bandwidth of the transmission frame. This process is repeated on a continuous basis and the bus recorder records the data. The data file is then reconstituted and decoded.

Abstract: An example operation includes one or more of determining automatically, by a processor based on data received from at least one sensor on a transport, a driving behavior associated with an operator of the transport over at least one first period of time as the operator's normal driving behavior, determining automatically by the processor a difference between the operator's normal driving behavior and a second driving behavior currently occurring over a second period of time as the operator's current driving behavior, and in the case the difference between the operator's normal driving behavior and the operator's current driving behavior indicates the operator's current driving behavior is unsafe, automatically guiding at least one of the operator and the transport to operate the transport in a safe driving behavior.

Abstract: In one embodiment, an open space model is generated for a system to plan trajectories for an ADV in an open space. The system perceives an environment surrounding an ADV including one or more obstacles. The system determines a target function for the open space model based on constraints for the one or more obstacles and map information. The system iteratively, performs a first quadratic programming (QP) optimization on the target function based on a first trajectory while fixing a first set of variables, and performs a second QP optimization on the target function based on a result of the first QP optimization while fixing a second set of variables. The system generates a second trajectory based on results of the first and the second QP optimizations to control the ADV autonomously according to the second trajectory.

Abstract: An information processing apparatus manages a ride-sharing system in which a plurality of users travels together on the same moving vehicle. The apparatus includes a control unit configured to calculate a second evaluation value for a user group traveling on the same moving vehicle, based on a first evaluation value based on a user's attribute and a time during which the user group is maintained, and in a case where there is a candidate user who is a candidate of a user newly riding in a predetermined moving vehicle, calculate the second evaluation value when a predetermined user group is formed for the predetermined moving vehicle, and determine a response policy for the candidate user based on whether or not the second evaluation value satisfies a predetermined policy.