Abstract: A vehicle routing system includes a vehicle routing and analytics (VRA) computing device, one or more databases, and one or more vehicles communicatively coupled to the VRA computing device. The VRA computing device is configured to generate an optimal route for a vehicle to travel that maximizes potential revenue for operation of the vehicle, the optimal route including a schedule of a plurality of tasks, and generate analytics associated with operation of the vehicle. The VRA computing device is further configured to provide a management hub software application accessible by vehicle users associated with vehicles, tasks sources, and other users.

Abstract: A vehicle has an electric traction chain to supply a drive torque to the wheels, and an energy management system comprising: a generator set configured to generate a first supply voltage and mechanically disconnected from the wheels in every operating condition; a battery storage assembly configured to generate a second supply voltage; a control unit that implements operative conditions of the vehicle, including: (i) powering the electrical traction chain with the first supply voltage; (ii) powering the electrical traction chain with the second supply voltage; (iii) recharging the storage assembly with a network voltage external to the vehicle and coming from a catenary; (iv) recharging the storage assembly with the first supply voltage; and (v) recharging the storage assembly with a recovered voltage generated by the traction chain operating as an electrical generator.

Abstract: A method of providing automated application of turn radius reduction in a driver assist mode may include receiving steering wheel angle and wheel speed information to determine a target wheel slip during a turn. The method may further include comparing the target wheel slip to a current wheel slip to determine a slip error, and applying braking torque to an inside wheel based on the slip error to reduce the turn radius.

Abstract: A driving assistance device for a vehicle includes a traveling environment recognizer, a braking force learner, and a braking force complementer. The traveling environment recognizer is configured to recognize traveling environment information related to an outside of the vehicle. The braking force learner is configured to, in a case where a driver who drives the vehicle has started a brake operation against a braking target recognized ahead based on the traveling environment information before a timing set based on a correlation between the vehicle and the braking target, acquire a braking force characteristic learning value based on a braking force generated from start to end of braking performed by the brake operation. The braking force complementer is configured to, in a case where the driver has started the brake operation after the set timing, complement the braking force based on the braking force characteristic learning value.

Abstract: A method for estimating material compaction can include creating compaction lookup tables based on total drive motor current and slope angle for each of a plurality of machine types. The method can include receiving telematics data related to total drive motor current for an individual machine and receiving telematics data related to a slope angle for the individual machine. The method can further include receiving a machine type of the individual machine and selecting a compaction lookup table corresponding to the individual machine type. A compaction value is determined from the selected lookup table based on the total drive motor current and the slope angle.

Abstract: Aircraft and methods of operating the aircraft to provide for increased descent angles. The aircraft includes a fuselage having fixed wings, a horizontal thrust source coupled to the fuselage and configured to selectively generate and supply horizontal thrust to the aircraft, a vertical thrust source coupled to the fuselage and configured to selectively generate and supply vertical thrust to the aircraft, the vertical thrust source including a vertical thrust rotor that is configured to selectively operate in a locked mode, in which the vertical thrust rotor cannot rotate freely in response to contact of airflow therewith, and an unlocked mode, in which the vertical thrust rotor can rotate freely in response to contact of airflow therewith, and a controller configured to selectively supply a command to the vertical thrust source that causes the vertical thrust rotor to operate in the unlocked mode.

Abstract: Systems and Methods for controlling an autonomous vehicle, may include: receiving sensor data, the sensor data comprising vehicle parameter information for the autonomous vehicle; using the sensor data to determine a vehicle state for the autonomous vehicle, wherein the vehicle state comprises information regarding a magnitude of an actual or predicted effective understeer gradient for the vehicle; computing a yaw moment required to correct the effective understeer gradient based on the magnitude of the effective understeer gradient; and determining a combination of one or more vehicle control inputs, including applying a brake torque, to correct the effective understeer gradient; applying the brake torque to a single wheel of the vehicle, wherein an amount of brake torque applied is sufficient to lock up the single wheel to create a yaw moment on the vehicle to achieve the computed yaw moment required to correct the effective understeer gradient.

Abstract: A control system acquires predicted tsunami information, and generates a flight plan for unmanned aerial vehicles. The flight plan includes flight paths along safety boundaries between an expected damage area and a safe area. The expected damage is an area expected to be damaged by the tsunami indicated by the predicted tsunami information. The safe area is an area to be safe from damage caused by the tsunami. The control system transmits the flight plan to the unmanned aerial vehicles.

Abstract: Vehicles, systems, and methods for navigating or tracking the navigation of a materials handling vehicle along a surface that may include a camera and vehicle functions to match two-dimensional image information from camera data associated with the input image of overhead features with a plurality of global target locations of a warehouse map to generate a plurality of candidate optical targets, an optical target associated with each global target location and a code; filter the targets to determine a candidate optical target; decode the target to identify the associated code; identify an optical target associated with the identified code; determine a camera metric relative to the identified optical target and the position and orientation of the identified optical target in the warehouse map; calculate a vehicle pose based on the camera metric; and navigate the materials handling vehicle utilizing the vehicle pose.

Abstract: The present invention relates to a full-day in each train operation diagram generation method based on a time division scheme and an activity-event relationship, the method including: S1: configuring operation scheme basic parameters; S2: constructing a quantitative relationship between a travel time and a driving interval for different routing ratios and calculating, within a given turn-back time range, an actual turn-back time of each turn-back station that can achieve a routing ratio requirement; S3: generating an arrival event time and a departure event time of a train in each time period at a station platform in accordance with routing division, direction division, and proportion division, correcting a start time and a stop time of each routing in accordance with time period division, and performing transition between the time periods; and S4: connecting a train section operation activity and a stop activity according to the full-time train arrival and departure event times obtained by executing step S3

Abstract: A system and method for detecting a perceived level of driver discomfort in an automated vehicle that include receiving image data associated with a driving scene of an ego vehicle, dynamic data associated with an operation of the ego vehicle, and driver data associated with a driver of the ego vehicle during autonomous operation of the ego vehicle. The system and method also include analyzing the image data, the dynamic data, and the driver data and extracting features associated with a plurality of modalities. The system and method additionally include analyzing the extracted features and detecting the perceived level of driver discomfort. The system and method further include analyzing the perceived level of driver discomfort and detecting a probable driver takeover intent of the driver of the ego vehicle to takeover manual operation of the ego vehicle.

Abstract: A driving assistance device includes a storage medium that stores computer-readable instructions, and a processor connected to the storage medium. The processor executes the computer-readable instructions to recognize an object around a moving body, perform first control for avoiding contact between the moving body and the recognized object by steering, perform second control for avoiding contact between the moving body and the recognized object by braking, derive an estimated value of a yaw rate generated in the moving body on the basis of reference information including at least a plurality of types of information different from a measured value of a yaw rate output by a yaw rate sensor mounted on the moving body, and suppress the first control if a deviation between the measured value and the estimated value is greater than a reference.

Abstract: Provided are methods for detecting when a vehicle is encountering an out of operational design domain (ODD) scenario, which can include training a generative adversarial network (GAN) including a generator network and a discriminator network. The generator network may be trained to generate synthesized scenarios. The discriminator network may be trained to distinguish between true scenarios and the synthesized scenarios generated by the generator network. The trained discriminator network may be applied to detect when a vehicle encounters an out of operational design domain (ODD) scenario. Some methods described also include controlling the motion of the vehicle in response to an output of the trained discriminator network indicating that the vehicle is encountering the out of operational design domain (ODD) scenario. Systems and computer program products are also provided.

Abstract: Lane-level matching is provided. For a time index of a time slot of a period of receiving consecutive position information, a lateral distance of the vehicle to each of a plurality of lanes of a roadway is calculated using data from sensors of a vehicle. For each lane of the plurality of lanes, a positional uncertainty of the vehicle in an orthogonal direction to a lane bearing of the lane is calculated, a lane confidence based on an average of confidence values of the lane over the period of receiving consecutive position information is calculated, and a lane probability based on the lane confidence is calculated. For the time index, it is identified which of the lanes has a highest probability as being the lane to which the vehicle is matched.

Abstract: A method for generating navigation routes for a vehicle includes: receiving an origin position, in a road network, of the vehicle; receiving a destination position, in the road network; receiving a user preference from a user interface device, the user preference indicating a tradeoff value having one of a plurality of values between travel time and energy efficiency; computing a time value for each of a plurality of road segments of the road network using a time consumption model; computing an energy consumption for each of the plurality of road segments of the road network using an energy consumption model; identifying a weighted route from the origin position to the destination position based on the time value and the energy consumption for the road segments and based on the user preference; and supplying the identified weighted route to a navigation system of the vehicle.

Abstract: In some implementations, the EMV uses a calibration to inform autonomous control over the EMV. To calibrate an EMV, the system first selects a calibration action comprising a control signal for actuating a control surface of the EMV. Then, using a calibration model comprising a machine learning model trained based on one or more previous calibration actions taken by the EMV, the system predicts a response of the control surface to the control signal of the calibration action. After the EMV executes the control signal to perform the calibration action, the EMV system monitors the actual response of the control signal and uses that to update the calibration model based on a comparison between the predicted and monitored states of the control surface.

Abstract: Systems and methods are provided for coordinating and controlling power flow during in-flight bidirectional energy transfer events between an electrified vehicle, one or more charging trailers, and optionally, one or more electrified recreational vehicles. The systems and methods may prioritize energy transfers between each connected energy unit based on various parameters, including but not limited to in-transit travel logistics, environmental information, time of day, etc. Charge energy may be transferred to the appropriate power source to meet customer needs with varying levels of priority according to an energy transfer prioritization control strategy that is derived from the various inputs that are considered.

Abstract: A computer-implemented method for identifying corner cases of operating scenarios of vehicles. The method includes receiving one or multiple feature(s) for characterizing an operating state of a vehicle, extracting at least one trace graph relating to the one or to the multiple feature(s) from a graph database, modifying the at least one trace graph, a modified trace graph being generated, reconstructing a first operating scenario from the trace graph, reconstructing a second operating scenario from the modified trace graph, and identifying the second operating scenario as a corner case if the second operating scenario is assessed as new and/or as unknown as compared to the first operating scenario on the basis of a predetermined criterion.

Abstract: A moving path planning apparatus and method for a robot according to the exemplary embodiment of the present disclosure determine an actual moving path using a robot parameter set in advance on the basis of a moving path pattern acquired for every sub region of the map to determine an actual moving path of the robot in consideration of the turning radius of the robot.

Abstract: Techniques associated with generating and maintaining sparse geographic and map data. In some cases, the system may maintain a factor graph comprising a plurality of nodes. In some cases, the nodes may comprise pose data and sensor data associated with an autonomous vehicle at the geographic position represented by the node. The nodes may be linked based on shared trajectories and shared sensor data.