Abstract: A vehicle includes an engine, a motor generator, a battery, and an ECU, and is configured to selectively perform EV running and engine running. When requested power is smaller than reference power, ECU calculates an engine fuel consumption ratio h1 when the engine outputs power resulting from addition of optimal charging power for the battery to the requested power, and determines whether the engine fuel consumption ratio h1 is larger than an EV criterion line resulting from addition of a margin K to a battery equivalent fuel consumption ratio F. When the engine fuel consumption ratio h1 is larger than the EV criterion line, ECU selects EV running, and otherwise selects engine running. The ECU calculates the margin K by referring to an F?K map which defines correspondence between the battery equivalent fuel consumption ratio F and the margin K with which an SOC is converged to a target range.

Abstract: According to some embodiments, a system calculates a first trajectory based on a map and a route information. The system performs a path optimization based on the first trajectory, traffic rules, and an obstacle information describing obstacles perceived by the ADV. The path optimization is performed by performing a spline curve based path optimization on the first trajectory, determining whether a result of the spline curve based path optimization satisfies a first predetermined condition, performing a finite element based path optimization on the first trajectory in response to determining that the result of the spline curve based path optimization does not satisfy the first predetermined condition, performing a speed optimization based on a result of the path optimization, and generating a second trajectory based on the path optimization and the speed optimization to control the ADV.

Abstract: A system and method for feeding back and incorporating the uncertainty distribution of the state estimate output by the INS in the image geo-registration process to handle larger navigation errors, provide a full six degree of freedom position and attitude absolute navigation update for the navigation system and provide a more accurate update for autonomous aerial, underwater or ground vehicles. Generating the update simultaneously for multiple images may provide a more robust solution to address any observability issues that may be present, the ability to fuse different sensor modalities and in general more accurate updates. Key frames may be used to improve the computational efficiency of the method.

Abstract: A method for providing circling approach data onboard an aircraft is disclosed. For a current, circling approach of the aircraft to a destination airport, the method identifies a circling approach procedure applicable to an optimal runway, by a processor communicatively coupled to a system memory element configured to store a database of circling approach procedures and a source for temporary restrictions; determines a circling boundary to the optimal runway, based on the circling approach procedure; determines temporary circling restrictions for the aircraft, based on conflicting traffic from at least a second airport; constructs a lateral path and a vertical path to guide the aircraft to the optimal runway of the destination airport, based on the circling approach procedure, the circling boundary, and the temporary circling restrictions; and presents graphical elements and text associated with the circling approach procedure, the circling boundary, and the temporary restrictions, by a display device.

Abstract: A travel route selection system is provided and includes historical latency data and travel route modules. The historical latency data module includes data and characterization modules. The data module collects historical latency data. The historical latency data are associated with transmission of signals in a network for one or more vehicle applications of a vehicle. The characterization module: obtains characteristic distributions of the historical latency data at selected locations along travel routes; based on the characteristic distributions, (i) calculates metrics along the travel routes for the vehicle, or (ii) combines the characteristic distributions to obtain an overall distribution for each of the travel routes; and based on the metrics or the overall distribution, performs a statistical process to predict latencies of the signals along each of the travel routes. The travel route module selects one of the travel routes based on the predicted latencies of the signals.

Abstract: A collision avoidance device includes an electronic control unit configured to: determine whether or not a driver of a host vehicle performs turn-back steering based on a detection value of a steering angle or steering torque detected by a steering sensor of the host vehicle; and execute the collision avoidance control for avoiding a collision between the host vehicle and an obstacle in a case where the electronic control unit determines that there is a collision possibility between the host vehicle and the obstacle based on a path of the host vehicle and a position of the obstacle, wherein the electronic control unit is configured not to execute the collision avoidance control while the electronic control unit determines that the driver of the host vehicle performs turn-back steering.

Abstract: Embodiments relate to producing a plan of a route in a transportation system. The method receives route requirements, including a starting location and an ending location. The method builds a model of the transportation system from data about vehicles. The model abstracts a “prospect travel” between two locations using any of a range of choices of vehicles and walks that can transport between the two locations. Given anticipated wait durations for the vehicles and their ride durations, the method determines an expected minimum travel duration using any of these choices. The method combines the expectations for various locations in a scalable manner. As a result, a route plan that achieves a shortest expected travel duration, and meets other requirements, is computed for one of the largest metropolitan areas in existence today. Other embodiments include a computer system and a product service that implement the method.

Abstract: A self-traveling vehicle of the present disclosure includes a controller. Every time a marker sensor detects a command marker during travel of the self-traveling vehicle, the controller reads from storage a command of a command group among a plurality of command groups, and executes content of the read command. Commands of the command group are read and executed sequentially upon detection of respective command markers. When another marker sensor detects a reset marker, the controller selects another command group next to a currently executed command group in execution order, and every time the marker sensor detects a command marker, reads from the storage a command of the selected command group and executes content of the read command. Commands of the selected command group are read and executed sequentially upon detection of respective command markers.

Abstract: A cartoning machine for packaging one or more products in a respective carton includes a product conveyor for conveying the products along an advancement direction, a transport device for transporting the carton along a transport path, an insertion zone wherein the products face an aperture of the carton and are inserted into the carton. The product conveyor includes a first belt on which first edges are mounted and a second belt on which second edges are mounted, each first edge defining with a respective second edge a pair of containment edges of the products. A mutual position of the first belt and of the second belt is adjustable so as to adjust accordingly a distance between the first edges and the second edges to adapt the pair of containment edges to a dimension of the products.

Abstract: The self-propelled vehicle system includes a drive line, a start marker, and a self-propelled vehicle. The self-propelled vehicle includes a plurality of drive line sensors arranged, in a direction intersecting with the travel direction of the self-propelled vehicle, at a wider range than a width of the drive line, a marker sensor that detects the start marker, and a control unit. After the start marker is detected by the marker sensor, the control unit nullifies the detection output of one group of the drive line sensors out of a plurality of groups that are formed by dividing all the drive line sensors, and in accordance with the detection output of another of the groups, the control unit makes the travel direction of the self-propelled vehicle follow the drive line branched towards a side of the another group, which is one of the two drive lines branched into two directions.

Abstract: A vehicle control apparatus including an assisting device for performing a parking assist operation and a controlling device for performing a first control operation that controls charging an electric power storage by using an output of an engine if an amount of the stored electric power is smaller than a first threshold value. The controlling device performs a second control operation for putting the engine into a stopping state before a moving start time at which the vehicle starts to move after an assist start time and forbidding the engine from being started after the moving start time if the amount of the stored electric power at a timing before the moving start time is larger than a second threshold value.