Abstract: A vehicle control system includes: a recognizer that recognizes a distribution state of obstacles in an advancement direction of a vehicle; a trajectory determiner that determines a target trajectory for each vehicle wheel of the vehicle on the basis of the distribution state of the obstacles recognized by the recognizer; and an automated driving controller that executes automated driving of the vehicle along the target trajectory determined by the trajectory determiner.

Abstract: The present invention relates to a method and system for accurately predicting future trajectories of observed objects in dense and ever-changing city environments. More particularly, the present invention relates to substantially continuously tracking and estimating the future movements of an observed object. As an example, an observed object may be a moving vehicle, for example along a path or road. Aspects and/or embodiments seek to provide an end to end method and system for substantially continuously tracking and predicting future movements of a newly observed object, such as a vehicle, using motion prior data extracted from map data.

Abstract: A motion planner performs motion planning with collision assessment, using a motion planning lattice that represents configuration states of a primary agent (e.g., autonomous vehicle) as nodes and transitions between states as edges. The system may assign cost values to edges, the cost values representing probability or likelihood of collision for the corresponding transition. The cost values may additionally or alternatively represent a severity of collision, for example generated via a parametric function with two or more parameters and one or more weights. A primary agent and/or dynamic obstacles may be represented as respective oriented bounding boxes. Some obstacles (e.g., road markings, edge of road) may be represented as curves.

Abstract: Redundant environment perception tracking for automated driving systems. One example embodiment provides an automated driving system for a vehicle, the system including a plurality of sensors, a memory, and an electronic processor. The electronic processor is configured to receive, from the plurality of sensors, environmental information of a common field of view, generate, based on the environmental information, a plurality of hypotheses regarding an object within the common field of view, the plurality of hypotheses including at least one set of hypotheses excluding the environmental information from at least one sensor of a first sensor type, determine, based on a subset of the plurality of hypotheses, an object state of the object, wherein the subset includes the at least one set of hypotheses excluding the environmental information from the at least one sensor, and perform a vehicular maneuver based on the object state that is determined.

Abstract: An autonomous vehicle (AV) is automatically navigated within a a driving lane. Lane line data is received from one or more sensors, such as one or more cameras. A first parametric curve can be matched to a location of a first lane line detected from the lane line data. A second parametric curve can be matched to a location of a second lane line detected from the lane line data. A center parametric curve can be then generated in the center of the first parametric curve and the second parametric curve. The center parametric curve is then sampled to generate a discrete vector of trajectory points along the center parametric curve. The AV is then navigated along the road based on the trajectory points.

Abstract: A vehicle position correction device corrects a position error of an host vehicle provided with a navigation control unit that includes a target route corrector that corrects a target route. The target route corrector detects a lane boundary of a lane in which the host vehicle travels. The target route corrector compares positional relationships between a detect lane boundary and a target route on a map, and calculates a lateral correction amount for the target route in situations where the target route is within a prescribed distance of the lane boundary, or in situations where the target route is on an opposite side of the lane boundary to the host vehicle. Upon calculating the lateral correction amount, the target route corrector moves the target route sideways in a lateral direction by the lateral correction amount to correct the target route.

Abstract: A vehicle position correction device is provided with a controller for correcting a position error of an autonomous host vehicle. The controller detects a lane boundary of a lane in which the host vehicle travels. The controller calculates a target value for a lateral correction amount of the target route by comparing positional relationships between lane boundary detection results and the target route on a map, and changes a lateral movement speed of the target route to calculate the target value for the lateral correction amount according to a bearing of the host vehicle in which the bearing being a vehicle attitude angle. The controller corrects the target route by moving the target route sideways in a lateral direction by an amount equal to the lateral correction amount upon the calculation of the lateral correction amount.

Abstract: Among other things, we describe techniques for estimating a speed profile for a proposed trajectory for a vehicle and operating the vehicle along the proposed trajectory according to the speed profile, including a method for: obtaining, by a planning circuit on a vehicle, a proposed trajectory for the vehicle in response to a driving scenario; obtaining, by the planning circuit, an estimated speed profile, and a confidence score, wherein the confidence score represents a similarity of the estimated speed profile to an actual speed profile that would be generated by a control circuit for the proposed trajectory; determining whether the confidence score meets a confidence threshold; and in accordance with a determination that the confidence score exceeds the confidence threshold, operating, by a control circuit on the vehicle, the vehicle along the proposed trajectory.

Abstract: A vehicle control system includes a travel control section, a first traffic condition quantity acquisition section, a second traffic condition quantity acquisition section, a correction parameter calculator, and a correction section. The first traffic condition quantity acquisition section acquires a current traffic condition quantity on a road on which a preceding vehicle is traveling further ahead of a front vehicle. The second traffic condition quantity acquisition section acquires a reference traffic condition quantity, which is a traffic condition quantity that serves as a reference for the road on which the preceding vehicle is traveling. The correction parameter calculator calculates a difference between the current traffic condition quantity and the reference traffic condition quantity and calculates a correction parameter using the difference.

Abstract: Aspects of the disclosure relate to methods for controlling a vehicle having an autonomous driving mode. For instance, sensor data may be received from one or more sensors of the perception system of the vehicle, the sensor data identifying characteristics of an object perceived by the perception system. That the object mt is no longer being perceived by the perception system may be determined. Based on the determination, predicted characteristics for the object may be generated based on one or more of the characteristics. The predicted characteristics of the object may be used to control the vehicle in the autonomous driving mode such that the vehicle is able to respond to the object when the object is no longer being perceived by the one or more sensors of the perception system.

Abstract: A vehicle system comprises an engine, a motor-generator and a controller. The engine has a combustion mode in which a part of an air-fuel mixture is combusted by spark ignition, and then the remaining air-fuel mixture is combusted by self-ignition. The controller sets a target additional deceleration based on a steering angle, when a steering wheel is turned, and sets an air-fuel ratio of the air-fuel mixture to either one of a first air-fuel ratio and a second air-fuel ratio which is on a lean side, based on an operating state, when the engine performs the combustion mode. The controller controls an ignition timing so as to generate the target additional deceleration in the first air-fuel ratio, and controls a regenerative electric power generation of the motor-generator so as to generate the target additional deceleration in the second air-fuel ratio.

Abstract: A method for controlling a trailer driven by an electric motor comprises defining a distance between the trailer and a towing vehicle as a neutral position and determining an actual distance between the trailer and the towing vehicle. A deviation between the actual distance and the neutral position is determined and output as a distance value. The braking of the trailer is electrically-actuated when the actual distance is decreased relative to the neutral position by at least a first distance value. The braking of the trailer is mechanically-actuated when the actual distance is decreased relative to the neutral position by at least a second distance value, wherein the second distance value is greater than the first distance value. The trailer is accelerated by the electric motor when the actual distance is increased relative to the neutral position by a third distance value.

Abstract: A method for controlling a motor vehicle including the steps of transitioning the vehicle from a brake holding mode to an engine driving mode and then accelerating the vehicle in a forward direction until a set vehicle target speed has been reached. The method including maintaining the vehicle at the set target speed until a driver of the vehicle intervenes.

Abstract: An exemplary system for controlling creep running of a vehicle equipped with an engine and a transmission includes, a driving information detection unit detecting driving information of the vehicle, an engine controller for controlling an output torque of the engine, and a vehicle control unit controlling the engine controller to output a basic creep driving torque, and when the vehicle is on a sloped road of more than a predetermined inclination, to further output a first additional driving torque corresponding to an inclination of the sloped road.

Abstract: A coasting driving control method and system for a vehicle may determine virtual engine RPM for a current driving state using engine RPM, vehicle speed, and gear stage information by a controller when coasting is started with the clutch in the neutral position and outputs a downshifting instruction signal for a gear stage by the controller when the virtual engine RPM is less than a coasting engine RPM which is greater than an idling RPM by a predetermined value.

Abstract: An assistance System for a vehicle for providing an emergency stop assistance function that includes an execution device to execute the emergency stop assistance function using at least one of a plurality of activation stages; a detection device for automatic detection of driver inactivity, in order to activate the emergency stop assistance function using a first stage selection of the activation stages; a triggering device for monitoring an operating element of an electrical parking brake or a parking lock of a transmission of the vehicle, in order to activate the emergency assistance function using a second stage selection of the activation stages, which differs from the first stage selection, in the case of a manual activation of the operating element.

Abstract: A vehicle controller may determine a decelerator input associated with controlling an engine speed of an engine of the vehicle. The vehicle controller may determine, while the vehicle is moving and based on the decelerator input satisfying a braking threshold, that an engine decelerator, associated with the decelerator input, is to be enabled for use in stopping the vehicle. The vehicle controller may determine, based on determining that the engine decelerator is to be used to cause the vehicle to be stopped, an amount of braking to be applied by a braking device of the vehicle to stop the vehicle. The vehicle controller may automatically cause the braking device to apply the amount of braking to stop the vehicle.

Abstract: A travel control method comprises: learning points which a vehicle has traveled over based on images of the surroundings of the vehicle captured with a camera mounted on the vehicle; learning the travel trajectory of the vehicle based on vehicle signals obtained from the vehicle; determining whether the vehicle has passed the points based on the images captured with the camera; and performing travel control of the vehicle by using the travel trajectory learned based on the vehicle signals as a target trajectory between the points.

Abstract: Aspects of the disclosure relate to a method of controlling a vehicle having an autonomous driving mode at a multi-way stop intersection. For instance, that the vehicle has come to a stop at a multi-stop intersection may be determined. At least one road user at the intersection may be identified. Based on the determination that the vehicle has come to the stop, a period of time to wait for the at least one road user to proceed through the intersection may be determined. After waiting the determined period of time, that the at least one road user has not begun to proceed through the intersection may be determined. Based on the determination that the at least one user has not begun to proceed through the intersection, the vehicle may be controlled in the autonomous driving mode in order to proceed through the intersection.

Abstract: An automatic driving assist apparatus includes a map information acquirer; an own vehicle position estimator; a route information input unit; a traveling environment information acquirer, a traveling route setting unit, an other-vehicle traveling route acquirer, and an automatic driving controller. The automatic driving controller further includes a target travel path generator, an other-vehicle detection determiner, and a relative vehicle speed determiner, an other-vehicle traveling route determiner, and an automatic traveling controller. The automatic traveling controller causes the own vehicle to travel following another vehicle along a target travel path generated by the target travel path generator in a case where the other-vehicle traveling route determiner determines that a traveling route of the other vehicle is set in a direction of a branch path.

Abstract: Systems and methods for operating a vehicle that includes an engine and an electric machine are described. In one example, an actual total number of transmission gear downshifts are counted to determine whether or not a transmission clutch characterization is immature. The transmission clutch characterization may be adjusted if it is determined to be immature.

Abstract: A control device for an automatic transmission includes a traveling drive source, an automatic transmission, an AT controller, and a traveling drive source controller. The AT controller is configured to execute shifting by changeover of friction elements upon receiving a shift request. The traveling drive source controller is configured to execute torque limit control of the traveling drive source when a request for limiting a torque by an upper limit torque is input from the AT controller. The AT controller has an upper limit torque change processing unit configured to change the upper limit torque from a low gear upper limit torque to a high gear upper limit torque when auto-upshift is executed. The upper limit torque change processing unit is configured to raise the upper limit torque using a prescribed gradient during an inertia phase when the inertia phase is started with the auto-upshift.

Abstract: A method for determining a set of dynamic objects in sensor data representative of a surrounding area of a vehicle having sensors, the method being executed by a server, the server executing a machine learning algorithm (MLA). Sensor data is received, and the MLA generates, based on the sensor data, a set of feature vectors. Vehicle data indicative of a localization of the vehicle is received. The MLA generates, based on the set of feature vectors and the vehicle data, a tensor, the tensor including a grid representation of the surrounding area. The MLA generates an mobility mask indicative of grid cells occupied by at least one moving potential object in the grid, and a velocity mask indicative of a velocity associated with the at least one potential object in the grid. The MLA determines, based on the mobility mask and the velocity mask, the set of dynamic objects.

Abstract: Force-detecting sensors are installed in a motorcycle's handlebars, footpegs and seat to detect the rider's grip, weight and weight distribution. A control unit interprets the signals from the sensors to determine an attribute of the rider or an intention of the rider to make a manoeuvre. Signals from environmental sensors are used by the control unit to determine whether the intended manoeuvre would endanger the rider, and, if so, the rider is alerted before the manoeuvre is undertaken. The alert is provided before the rider notices the hazard, or before the rider reacts to the hazard. By giving advance warning, of as little as a fraction of a second, a rider is given extra time to avert a potential accident. The control unit also controls settings of the motorcycle during a hazardous state of the motorcycle.

Abstract: A method for controlling vehicle systems includes receiving monitoring information from one or more monitoring systems and determining a plurality of driver states based on the monitoring information from the one or more monitoring systems. The method includes determining a combined driver state based on the plurality of driver states and modifying control of one or more vehicle systems based on the combined driver state.

Abstract: In accordance with an embodiment, a neural network is configured to: process a first grid representing at least a first portion of a field of view of a first sensor; process a second grid representing at least a second portion of a field of view of a second sensor; and fuse the processed first grid with the processed second grid into a fused grid, where the fused grid includes information about the occupancy of the first portion of the field of view of the first sensor and the occupancy of the second portion of the field of view of the second sensor.

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 communications cable includes a bundle of strands. The bundle of strands includes an electrically insulative first strand, an electrically conductive second strand disposed adjacent to the first strand, an electrically conductive third strand disposed adjacent to the first strand and opposite the second strand, and one or more additional electrically insulative strands disposed adjacent to the first strand.

Abstract: A trainer device trains an automated driver system. The trainer device may include a vehicle manager that manages data associated with controlling a vehicle and a simulation manager that manages data associated with simulating the vehicle. The vehicle manager may analyze vehicle data to identify an intervention event, and the simulation manager obtains a portion of the vehicle data corresponding to the intervention event to generate simulation data, obtains user data associated with the simulation data, analyzes the user data to determine whether the user data satisfies a predetermined intervention threshold, and, on condition that the user data satisfies the predetermined intervention threshold, transmits the user data to the vehicle manager for modifying the first control data.

Abstract: The present disclosure relates to a method for controlling an autonomous driving configuration or driving assistance configuration comprising at least two adjustable parameters. The method includes, at an electronic device with a display, displaying on the display a user interface. The user interface includes a graphical representation of a current setting of the at least two adjustable parameters associated with the autonomous driving configuration or driving assistance configuration. The method further includes detecting via one or more input devices, a user input directed towards a first adjustable parameter of the at least two adjustable parameters, and updating the graphical representation on the display based on the detected user input. More specifically, the updating of the graphical representation is done by modifying the current setting of the first parameter of the at least two adjustable parameters and modifying at least one characteristic of a second adjustable parameter.

Abstract: An apparatus for an autonomous vehicle may include a controller. The controller may monitor one or more components or systems of the autonomous vehicle. The controller may determine a fault condition of the autonomous vehicle, such as for a component or a system of the autonomous vehicle. The apparatus may include a human-machine interface for a user, such as an occupant of the autonomous vehicle. The apparatus may communicate, via the human-machine interface, an alert based on the fault condition. This may be in accordance with a profile associated with the user.

Abstract: A driving information generating section 20 successively generates as driving information diverse types of information indicative of a driving state of a vehicle. A dangerous driving determining section 31 determines whether dangerous driving is underway on the basis of the driving information generated by the driving information generating section 20. A supplementary information acquiring section 32 acquires state supplementary information manually or automatically upon determination of dangerous driving by the dangerous driving determining section 31, and associates the acquired state supplementary information with the result of the determination of dangerous driving. An information communication section 34 transmits the result of the determination of dangerous driving and the state supplementary information to an information management apparatus 40.

Abstract: A method for detecting non-visible vehicles in a vehicle's environment, wherein each vehicle is equipped with at least one proximity sensor, the method comprising for a driven vehicle the steps of: screening, by a receiver of the proximity sensor, any incoming proximity signal capable of propagating through the air along a non-linear path; Receiving an incoming proximity signal coming from a non-visible vehicle (B); processing the received proximity signal to detect the non-visible vehicle; and warning a driver and/or an advanced driver-assistance system about the detected non-visible vehicle.

Abstract: A method is intended to assist the driver of a vehicle (VA) capable of being driven in an automated manner and in a manual manner, by means of a steering wheel (VV), in a traffic lane (VC1). This method comprises a step that involves determining an optimum trajectory of the vehicle (VA) in the event of automated driving, an actual current trajectory of the vehicle (VA) in the traffic lane (VC1), and a value of a parameter representative of a manual intervention being carried out by the driver on the steering wheel (VV), and representing these determined optimum and actual current trajectories on a medium (EA) with an aspect that depends on this determined value of the parameter.

Abstract: In lane selection control in which a lane in which a host vehicle travels is selected based on the map information and information acquired by an external sensor that acquires periphery information of the host vehicle, a self-position correction object in an intended travel route is identified based on the map information. When the host vehicle reaches a correction point where the self-position correction object is present, a determination is made as to whether or not the self-position correction object can be recognized by the external sensor from the lane in which the host vehicle travels. Upon determined that the self-position correction object cannot be recognized from the center lane in which the host vehicle travels, a lane change to a leftmost lane where the self-position correction object can be recognized is made before the host vehicle reaches the correction point.

Abstract: A vehicle system includes a first vehicle platform including a first computer configured to operate by means of electric power from a first electric power source and perform traveling control of a vehicle, a second vehicle platform including a second computer configured to operate by means of electric power from a second electric power source different from the first electric power source and perform traveling control of the vehicle, and an autonomous driving platform including a third computer configured to perform autonomous driving control of the vehicle by transmitting a control instruction including data for autonomously driving the vehicle to the first computer when the first vehicle platform is in a normal state and perform autonomous stoppage control of the vehicle by transmitting a control instruction including data for causing the vehicle to autonomously stop to the second computer when the first vehicle platform is in an abnormal state.

Abstract: The present disclosure relates to a method for operating a vehicle guiding system of a motor vehicle, said vehicle guiding system being designed to guide the motor vehicle in a completely automated manner. The presence of a traffic officer and/or instruction data which describes a traffic instruction provided by the traffic officer is ascertained by analyzing sensor data of at least one surroundings sensor of the motor vehicle and taken into consideration during the completely automated guidance of the vehicle. At least one radar sensor with a semiconductor chip which acts as a radar transceiver is used as the surroundings sensor, and upon detecting the presence of a traffic officer, the radar sensor is switched from at least one normal operating mode to an additional operating mode provided for detecting limbs of the traffic officer and/or their movement, wherein the sensor data of the radar sensor is analyzed for instruction data which describes the limbs of the traffic officer and/or their movement.

Abstract: A monitoring system detects and mitigates traffic risks among a group of vehicles. The group of vehicles includes a ground-based vehicle (GBV), e.g. an automotive vehicle, and an air-based vehicle (ABV), e.g. a drone, which is operated to track a ground-based object (GBO), e.g. an unprotected road user or an animal. The monitoring system performs a method comprising: obtaining (301) predicted navigation data for the ground-based vehicle and the air-based vehicle, processing (302) the predicted navigation data to obtain one or more future locations of the ground based-object and to detect an upcoming spatial proximity between the ground-based object and the ground-based vehicle, and causing (305), upon detection of the upcoming spatial proximity, an alert signal to be provided to at least one of the ground-based object and the ground-based vehicle.

Abstract: A system for a reliability of objects for a driver assistance or automated driving of a vehicle includes a plurality of sensors that include one or more sensor modalities for providing sensor data for the objects. An electronic tracking unit is configured to receive the sensor data to determine a detection probability (p_D) for each of the plurality of sensors for each of the objects, to determine an existence probability (p_ex) for each of the plurality of sensors for each of the objects, and to provide vectors for each of the objects based on the existence probability (p_ex) for each contributing one of the plurality of sensors for the specific object. The vectors are provided by the electronic tracking unit for display as an object interface on a display device. The vectors are independent from the sensor data from the plurality of sensors.

Abstract: Methods and systems for controlling an autonomous vehicle. The method includes receiving sensor data from a plurality of sensors, determining, a plurality of probability hypotheses based upon the sensor data, and receiving metadata from at least one sensor of the plurality of sensors. An integrity level of at least one of the plurality of probability hypotheses is determined based upon the received metadata and at least one action is determined based upon the determined integrity level and at least one probability hypothesis of the plurality of probability hypotheses. The at least one action is then initiated by an electronic controller for the vehicle.

Abstract: Systems and methods for generating a virtual environment in a flock of vehicles are provided. In this method a reflector is utilized to define a coverage area. Sensory data from autonomous vehicles within this coverage area is collected, along with non-vehicle data. Then a virtual environment may be replicated using the data at a local computational device on each of the vehicles via the transmission of messages through the reflector. Each vehicle can use this data to make decisions regarding movements, as well as having the traffic patterns optimized based upon an objective. When traffic flow is being optimized it is also possible to assign weights to the vehicles to provide them preferential treatment in the traffic flow model. The traffic flow model that is generated may be a fluid dynamics model, or may be based upon deep learning techniques. The objective for the model is generally to maximize total vehicle throughput in order to reduce overall traffic congestion.

Abstract: Methods and systems for multi-hypothesis object tracking for automated driving systems. One system includes an electronic processor configured to receive environment information and generate pseudo-measurement data associated with an object within an environment of the vehicle. The electronic processor is also configured to determine, based on the environment information and the pseudo-measurement data, a set of association hypotheses regarding the object. The electronic processor is also configured to determine, based on the set of association hypotheses, an object state of the object. The electronic processor is also configured to control the vehicle based on the determined object state.

Abstract: A service providing system, a vehicle and a method for providing a service are provided. The service providing system includes a server device configured to provide a service to a vehicle via a telecommunication line, the server device including processing circuitry configured to: acquire, from the vehicle, information on a communication standard and a service that are being used and position information; and create, at least partly based on the information on the communication standard and the service and the position information, a service map indicating a communication standard and a service that are usable in a communication area; and control content of the service provided to the vehicle using the service map.

Abstract: A plurality of sections in a planned travel route include a first basic section for a first automatic driving level, a second basic section for a second automatic driving level lower than the first automatic driving level, and a change preparation section and a main section in the first basic section. An information output control device controls an information output system so as to perform information output in accordance with an output structure allowed in a current section, among a plurality of types of output structures each determined by a combination of output information, an output format, and an output destination device. Allowed output structures for the change preparation section include part of not-allowed output structures for the main section and also include at least part of allowed output structures for the second basic section.

Abstract: A vehicle control system includes a vehicle platform including a first computer configured to perform traveling control of a vehicle and an autonomous driving platform including a second computer configured to perform autonomous driving control of the vehicle. The second computer generates control instruction information with respect to the vehicle platform and the first computer performs the traveling control of the vehicle based on the control instruction information. The vehicle control system further includes a vehicle control interface configured to relay the control instruction information. The vehicle control interface prohibits the second computer from performing the autonomous driving control of the vehicle in a case where predetermined authentication information indicating that the autonomous driving platform is genuine is not received from the autonomous driving platform.

Abstract: Techniques are provided for autonomous vehicle fleet management for reduced traffic congestion. A request is received for a vehicular ride. The request includes an initial spatiotemporal location and a destination spatiotemporal location. A processor is used to generate a representation of lane segments. Each lane segment is weighted in accordance with a number of other vehicles on the lane segment. A vehicle located within a threshold distance to the initial spatiotemporal location is identified such that the identified vehicle has at least one vacant seat. The processor is used to determine a route for operating the identified vehicle from the initial spatiotemporal location to the destination spatiotemporal location. The route includes one or more lane segments of the lane segments. An aggregate of weights of the one or more lane segments is below a threshold value. The received request and the determined route are transmitted to the identified vehicle.

Abstract: A transport installation includes a traction member extending in a circuit and associated with an external power source so as to be moved along the circuit, a vehicle having a power storage system, a motor system, a generator system and a fixed support adjacent to the circuit. The generator system of the vehicle includes a generator that may be activated to supply power to the storage system when the vehicle is coupled to the traction member and driven along the circuit by the traction member. The motor system of the vehicle includes a motor that may be activated to receive power from the storage system and move the vehicle relative to the fixed support.

Abstract: A gondola car has a door and an associated door frame the end. The door hangs hingedly from the header of the frame. The header runs across the top of the door opening and is connected to the top chords at either side. The door posts are positioned inside the side sheets and tie into the header at each upper corner. The side sheets lap onto the door posts to allow longitudinal adjustment of the side assemblies and the door frame relative to each other, at assembly. The side posts are connected to the header with a tie plate that is bolted to both members. The car may also have a tarp dome at each end. The tarp dome has non-welded connections that have play to permit the tarp dome to accommodate movement of the top chords.

Abstract: Disclosed are an electromagnetic transverse active damping system, and a control method and apparatus therefor. The electromagnetic transverse active damping system comprises an electromagnet controller, wherein the electromagnet controller can determine a value of a damper target gap for an electromagnet active damper according to acquired train transverse acceleration, train position information and train speed, and control the action of the electromagnet active damper according to the determined value of the damper target gap; and electrical control is employed during the control of the electromagnet active damper by the electromagnet controller.

Abstract: A railroad equipment state determination apparatus includes: a storage that stores a plurality of operation data associated with a prescribed operation performed by railroad equipment that is driven by a motor from a stopped state to perform the prescribed operation and then comes into the stopped state again; an evaluation criteria setting section that sets evaluation criteria based on the plurality of operation data stored in the storage; and a determination section that determines whether new operation data resulting from the prescribed operation newly performed by the railroad equipment is abnormal based on the evaluation criteria.