Abstract: A data transmitter to be mounted on a vehicle detects the driver's state from output data of a camera mounted on the vehicle. The data transmitter determines whether the driver's state is suitable for continuing the control by the level of autonomous driving; transmits, when it is determined that the state is suitable for continuing the control, the face image to a terminal communicably connected via a communication network, together with a first setting for displaying the face image on the terminal in first mode; and transmits, when it is determined that the state is unsuitable for continuing the control, the face image to the terminal, together with a second setting for displaying the face image on the terminal in second mode that draws more attention of a user of the terminal than the first mode.

Abstract: The present invention relates to a method for guiding a vehicle at least in part automatically. The method includes generating gaze tracking data by tracking a gaze direction of a user of the vehicle for a predefined time interval and analyzing the gaze tracking date by a computer unit with respect to a lane change intention of the user. Depending on a result of the analysis, an at least partially automatic lane change maneuver is proposed to the user or the at least partially automatic lane changer maneuver is initiated by the computing unit.

Abstract: A notification apparatus includes: an acquisition section that acquires first information on a first amount of power used for travel of a vehicle that operates with power, and second information on a second amount of power used for equipment in the vehicle for a purpose other than the travel; and a control section that notifies a user of the first amount of power and the second amount of power in accordance with the first information and the second information so that the first amount of power and the second amount of power can be compared.

Abstract: An in-vehicle equipment setup device includes a storage configured to store at least in-vehicle equipment information indicating mounting presence or absence of a plurality of pieces of in-vehicle equipment mounted in a vehicle and user setup information in which a setup of the in-vehicle equipment desired by a user of the vehicle is shown for each user, an equipment determiner configured to determine whether the in-vehicle equipment included in the in-vehicle equipment information is mounted equipment mounted in the vehicle or unmounted equipment not mounted in the vehicle, and a setter configured to perform the setup of the in-vehicle equipment shown in the user setup information based on the in-vehicle equipment information. The equipment determiner updates the in-vehicle equipment information based on a result of determining the mounted equipment and the unmounted equipment.

Abstract: A signal processing module is provided. The signal processing module includes a function weight table that stores weights for each first sensor for an autonomous driving mode and an ADAS driving mode and selects and outputs only the weight for each first sensor, a first weight applying device that generates a function weight application signal by applying the weight for each first sensor to sensing information of sensors for sensing an object, a road environment determining device that determines a road environment based on the sensing information of the sensors for sensing the object, a road environment weight table that stores weights for each second sensor for a road environment and selects and outputs an weight for each second sensor, and a second weight applying device that outputs a dataset by applying the weight for each second sensor to the function weight application signal.

Abstract: A signal processing module is provided. The signal processing module includes a function weight table that stores weights for each first sensor for an autonomous driving mode and an ADAS driving mode and selects and outputs only the weight for each first sensor, a first weight applying device that generates a function weight application signal by applying the weight for each first sensor to sensing information of sensors for sensing an object, a road environment determining device that determines a road environment based on the sensing information of the sensors for sensing the object, a road environment weight table that stores weights for each second sensor for a road environment and selects and outputs an weight for each second sensor, and a second weight applying device that outputs a dataset by applying the weight for each second sensor to the function weight application signal.

Abstract: A vehicle controller includes a memory configured to store map information including information on a predetermined area used in autonomous driving control of a vehicle; and a processor configured to: refer to the map information to identify an autonomous-driving practicable point at which a planned travel route from the current position of the vehicle outside the predetermined area to a destination of the vehicle enters the predetermined area, calculate a manual-driving section length from the current position of the vehicle to the autonomous-driving practicable point along the planned travel route, and notify the calculated manual-driving section length to a driver of the vehicle via a notification device provided in the interior of the vehicle.

Abstract: Systems and methods for detecting and labeling a collidability of obstacles within a vehicle environment are provided. The method may comprise generating one or more data points from one or more sensors coupled to a vehicle. The method may comprise, using a processor, detecting one or more obstacles within a LiDAR point cloud, generating a patch for each of the one or more detected obstacles, projecting the LiDAR point cloud into the image, performing a factor query on an image for each of the one or more detected obstacles, for each of the one or more detected obstacles, based on the factor query, determining a label for the obstacle, and, for each of the one or more detected obstacles, labeling the obstacle with the label. The label may indicate whether each of the one or more detected obstacles is collidable and not non-collidable.

Abstract: Systems and methods for planning a trajectory of a vehicle based on one or more obstacles is provided. The method may comprise generating one or more data points from one or more sensors coupled to a vehicle, and, using a processor, detecting one or more obstacles within a LiDAR point cloud, generating a patch for each of the one or more obstacles, projecting the LiDAR point cloud into the image, wherein each patch represents a region of an image for each of the one or more obstacles, performing a factor query on the image for each of the one or more obstacles, for each of the one or more obstacles, based on the factor query, determining a label for the obstacle and labeling the obstacle with the label, and planning a trajectory of the vehicle. The label may indicate a collidability of the obstacle.

Abstract: A system for a host vehicle operating on a road surface includes a polarimetric camera, a global positioning system (“GPS”) receiver, a compass, and an electronic control unit (“ECU”). The camera collects polarimetric image data of a drive scene, including a potential driving path on the road surface. The ECU receives the polarimetric image data, estimates the Sun location using the GPS receiver and compass, and computes an ideal representation of the road surface using the Sun location. The ECU normalizes the polarimetric image data such that the road surface has a normalized representation in the drive scene, i.e., an angle of linear polarization (“AoLP”) and degree of linear polarization (“DoLP”) equal predetermined fixed values. The ECU executes a control action using the normalized representation.

Abstract: A detection system for a host vehicle includes a camera, global positioning system (“GPS”) receiver, compass, and electronic control unit (“ECU”). The camera collects polarimetric image data forming an imaged drive scene inclusive of a road surface illuminated by the Sun. The GPS receiver outputs a present location of the vehicle as a date-and-time-stamped coordinate set. The compass provides a directional heading of the vehicle. The ECU determines the Sun's location relative to the vehicle and camera using an input data set, including the present location and directional heading. The ECU also detects a specular reflecting area or areas on the road surface using the polarimetric image data and Sun's location, with the specular reflecting area(s) forming an output data set. The ECU then executes a control action aboard the host vehicle in response to the output data set.

Abstract: A control device for a vehicle including a first sensor and a second sensor. The control device includes a processor configured to function as: a data receiving part, receiving sensor data from the first sensor; an occlusion detection part, detecting a presence of an occlusion around the vehicle based on the sensor data received; a target trajectory generating part, generating the predetermined target trajectory of the vehicle for automated driving of the vehicle, the predetermined target trajectory is set such that the vehicle is configured to enter a roadway from an outside of the roadway via a rear direction of the vehicle; wherein in a case when the occlusion detection part detects the presence of the occlusion, the predetermined target trajectory is generated such that, when the vehicle enters the roadway, the rear direction of the vehicle relative to the roadway is set such that the occlusion is reduced.

Abstract: In an approach to autonomous vehicle traffic management, one or more computer processors retrieve an identification associated with a first autonomous vehicle. One or more computer processors retrieve a distance rule corresponding to the first autonomous vehicle from a smart contract, wherein the distance rule is a rule for a minimum distance that other autonomous vehicles must maintain with respect to the first autonomous vehicle. One or more computer processors determine a context of the first autonomous vehicle. Based on the context of the first autonomous vehicle, one or more computer processors determine whether a first exception to the distance rule is required. One or more computer processors generate the first exception to the distance rule. One or more computer processors communicate the distance rule and the first exception to the distance rule to one or more additional autonomous vehicles traveling in proximity to the first autonomous vehicle.

Abstract: A system and method for vehicle control adaptation to external environmental conditions includes receiving, by a controller, weather and roadway condition data, from an external source. The weather and roadway condition data includes a sustained wind velocity, a sustained wind direction, and a wind gust level for a location of the vehicle. The controller receives vehicle measurement data from one or more sensors situated within the vehicle and determines a criticality of a wind impact on the vehicle based on the weather and roadway data and the vehicle measurement data. The controller than generates feedback and/or a control based on the criticality of the wind impact.

Abstract: A vehicle positioning device, comprises a wireless communicator, at least one ultra-wideband transceiver and a signal processor. The ultra-wideband transceiver is disposed in a vehicle and configured to receive a pulse signal with source information from another ultra-wideband transceiver. The signal processor is connected to the at least one ultra-wideband transceiver and a speed measuring device of the vehicle, and configured to generate a position information according to the signal value of the pulse signal and the source information and transmit the position information and a vehicle speed information obtained from the speed measuring device through the wireless communicator to a server, and receive a driving information associated with the position information and the vehicle speed information from the server through the wireless communicator.

Abstract: A driving support system includes a storage unit that stores a plurality of pieces of invasion event information including information on an invasion position where a moving object invades a traveling region, the invasion event information being information on an invasion event in which the moving object invades the traveling region, an invasion frequent occurrence region calculation unit that specifies an invasion frequent occurrence region which is a region where the invasion event easily occurs based on the plurality of pieces of invasion event information, a position specification unit that specifies a position of the vehicle, and a driving support unit that supports driving of the vehicle by notifying an occupant of the vehicle and controlling traveling of the vehicle based on a relationship between the invasion frequent occurrence region and the position of the vehicle.

Abstract: A vehicle control device includes a recognizer configured to recognize a surrounding situation of a vehicle, a driving controller configured to control steering, acceleration, and deceleration of the vehicle independently of an operation of a driver of the vehicle, and a mode decider configured to decide on a driving mode of the vehicle as one of a plurality of driving modes including a first driving mode and a second driving mode. The recognizer recognizes an available travel lane in the same direction as the vehicle located inside of a reference range. The mode decider changes the driving mode of the vehicle from the second driving mode to the first driving mode on the basis of the number of lanes recognized by the recognizer when the driving mode of the vehicle is the second driving mode.

Abstract: Systems and methods related to controlling an autonomous vehicle (“AV”) are described herein. Implementations can process actor(s) from a past episode of locomotion of a vehicle, and stream(s) in an environment of the vehicle during the past episode to generate predicted output(s). The actor(s) may each be associated with a corresponding object in the environment of the vehicle, and the stream(s) may each represent candidate navigation paths in the environment of the vehicle. Further, implementations can process the predicted output(s) to generate further predicted output(s), and can compare the predicted output(s) to associated reference label(s). The processing can be performed utilizing layer(s) or distinct, additional layer(s) of machine learning (“ML”) model(s). Implementations can update the layer(s) or the additional layer(s) based on the comparing, and subsequently use the ML model(s) in controlling the AV.

Abstract: Motion planning with implicit occupancy for autonomous systems includes obtaining a set of trajectories through a geographic region for an autonomous system, and generating, for each trajectory in the set of trajectories, a set of points of interest in the geographic region to obtains sets of points of interest. Motion planning further includes quantizing the sets of points of interest to obtain a set of query points in the geographic region and querying the implicit decoder model with the set of query points to obtain point attributes for the set of query points. Motion planning further includes processing, for each trajectory of a least a subset of trajectories, the point attributes corresponding to the set of points of interest to obtain a trajectory cost for the trajectory. From the set of trajectories, a selected trajectory is selected according to trajectory cost.

Abstract: Diffusion for realistic scene generation includes obtaining a current set of agent state vectors and a map data of a geographic region, and iteratively, through multiple diffusion timesteps, updating the current set of agent state vectors. Iteratively updating includes processing, by a noise prediction model, the current set of agent state vectors, a current diffusion timestep of the plurality of diffusion timesteps, and the map data to obtain a noise prediction value, generating a mean using the noise prediction value, generating a distribution function according to the mean, sampling a revised set of agent state vectors from the distribution function, and replacing the current set of agent state vectors with the revised set of agent state vectors. The current set of agent state vectors are outputted.

Abstract: Various methods and systems for determining one or more states of an autonomous vehicle for positioning when transitioning between two or more different environments are disclosed herein. The systems and methods disclosed herein can include a positioning system that includes two or more different positioning subsystems operable to generate positional data representing a current position of the autonomous vehicle.

Abstract: An information processing method includes obtaining, by a first apparatus, first information that includes environment information of a terminal in which the first apparatus is located; receiving second information from a second apparatus, where the second information indicates region information and/or time information of the terminal; and then outputting first sensed information for the terminal based on the first information and the second information.

Abstract: A computer-implemented method and a corresponding system for planning the behavior of a vehicle using a predefined set of rules with prioritized rules for assessing possible behaviors of the vehicle in a given situation. For this purpose, situation-specific information is aggregated, and an environmental model of the given situation is generated based on the aggregated situation-specific information. The set of rules includes a decision-making process structure, which represents the prioritization of the individual rules of the set of rules. On the basis of the environmental mode, boundary conditions for the possible behaviors of the vehicle are determined. The latter are then prioritized by applying the decision-making process structure to the respective boundary conditions.

Abstract: A system for data-driven, modular decision making and trajectory generation includes a computing system. A method for data-driven, modular decision making and trajectory generation includes: receiving a set of inputs; selecting a learning module such as a deep decision network and/or a deep trajectory network from a set of learning modules; producing an output based on the learning module; repeating any or all of the above processes; and/or any other suitable processes. Additionally or alternatively, the method can include training any or all of the learning modules; validating one or more outputs; and/or any other suitable processes and/or combination of processes.

Abstract: The driving support device includes an acquisition unit that acquires the driver's input results, and an output control unit that outputs a confirmation voice requesting the driver's consent in response to the driver's input for executing the driving support function. A determination unit that determines execution of the driving support function in response to the driver's input to the confirmation voice. The output control unit outputs the text in which the keyword is set as a confirmation voice. The determination unit does not accept the driver's approval for the confirmation voice before outputting the keyword.

Abstract: Exemplary embodiments include systems and methods to maintain tracking of an object that passes into an occluded area, including defining a map of a driving area; defining one or more occlusion areas within the map; detecting an object using sensor data from one or more sensors; creating an object track for the object detected using sensor data; determining that the object track entered one of the one or more occlusion areas; and maintaining the object track while the object track remains in the one or more occlusion areas.

Abstract: A vehicle controller is configured to: recognize a surrounding situation of a vehicle; execute first control of giving a first alarm to an occupant of the vehicle in response to a first condition being satisfied; execute second control of controlling braking or steering of the vehicle and giving a second alarm to the occupant in response to a second condition being satisfied; detect an abnormality of the occupant; execute third control of decelerating or stopping the vehicle and giving a third alarm in response to the abnormality of the occupant; and arrange execution of the first, second and third control. The vehicle controller executes the third control with priority over the first control when conditions of the first control and the third control are satisfied; and executes the second control with priority over the third control when conditions of the second control and the third control are satisfied.

Abstract: An autonomous commercial vehicle transporting oversized loads is controlled based on sensor data determined by environment sensors of the commercial vehicle and/or data of a digital map. Navigable areas including lanes in the direction of and against the direction of travel and hard shoulders are determined in the form of respective polygons, in which the autonomous commercial vehicle may be present. The behavior of the autonomous commercial vehicle is determined depending on the navigable areas, objects identified on the basis of the sensor data, and an intrinsic movement estimation. At least one corridor command is transmitted to a movement planning module, which plans a trajectory and/or a path of the commercial vehicle with avoidance of a collision with identified objects. The planned trajectory and/or the planned path are/is fed to a movement control module, which controls the autonomous commercial vehicle such that it follows the planned trajectory and/or the planned path.

Abstract: A computer-implemented method of determining control signals for controlling an autonomous vehicle to implement a slowdown manoeuvre, comprising: detecting an obstacle at a distance ahead of the autonomous vehicle; comparing the distance with a threshold value and implementing a slowdown manoeuvre in dependence on the comparison, the slowdown manoeuvre selected from: a first slowdown manoeuvre carried out by a kinematic function, which is a time derivative of acceleration, in which a constraint optimisation has been applied to optimise a cost function of the slowdown manoeuvre subject to a set of hard constraints that require a final acceleration, speed and position to satisfy respective acceleration, speed and position targets, given an initial speed and acceleration of the vehicle, and impose a jerk magnitude upper limit; and a second slowdown manoeuvre implemented in an adaptive cruise control mode which aims to reach a target headway between the autonomous vehicle and the obstacle.

Abstract: In various examples, an integrated circuit includes first and second portions. The first portion includes a timer that starts when the first portion transmits at least one error signal to the second portion. The timer may reset when data corresponding to at least one fault has been cleared from the first portion. The first portion transmits a timeout error signal when the timer indicates at least a predetermined amount of time has elapsed. The second portion receives the at least one error signal and the timeout error signal when the timeout error signal has been sent. The second portion may notify an external system after the timeout error signal is received.

Abstract: A vehicle control device includes one or more processors configured to: on a travel route of an autonomous driving taxi configured to travel toward a desired drop-off position of a user of the autonomous driving taxi, set a predetermined travel route range from a point behind the desired drop-off position to the desired drop-off position, as a permissible midway drop-off range in which midway drop-off from the autonomous driving taxi is permitted; receive a setting about a midway drop-off position in the permissible midway drop-off range, the setting being made by the user in the autonomous driving taxi configured to travel toward the desired drop-off position; and stop the autonomous driving taxi at the midway drop-off position set by the user such that the user drops off the autonomous driving taxi midway.

Abstract: Systems and techniques are provided for fusing sensor data from multiple sensors. An example method can include obtaining a first set of sensor data from a first sensor and a second set of sensor data from a second sensor; detecting an object in the first set of sensor data and the object in the second set of sensor data; aligning the object in the first set of sensor data and the object in the second set of sensor data to a common time; based on at least one of the aligned object from the first set of sensor data and the aligned object from the second set of sensor data, aligning the first set of sensor data and the second set of sensor data to the common time; and fusing the aligned first set of sensor data and the aligned second set of sensor data.

Abstract: Systems and techniques are provided for fusing sensor data from multiple sensors. An example method can include obtaining a first set of sensor data from a first sensor and a second set of sensor data from a second sensor; detecting an object in the first set of sensor data and the object in the second set of sensor data; aligning the object in the first set of sensor data and the object in the second set of sensor data to a common time; and based on the aligned object from the first set of sensor data and the aligned object from the second set of sensor data, fusing the aligned object from the first set of sensor data and the aligned object from the second set of sensor data.

Abstract: The present invention is directed to computer-implemented method for controlling an autonomous or semi-autonomous vehicle. A vehicle model is provided and information describing a roadway (301) is obtained. This information is transformed in a Frenet-Serret frame, which defines a curvilinear coordinate space. Then, in the curvilinear coordinate space, a plurality of line segments (306, 307) are defined (3) along the roadway (301), at locations spaced longitudinally along a reference line defining the Frenet-Serret frame. The line segments have respective lengths that extends, each, perpendicularly to the reference line. Next, based on the defined line segments, a space-time corridor (327, 327?, 326?) is determined (5) to obtain a time-dependent space available for the vehicle. Bounds for the vehicle within said time-dependent space are subsequently obtained (6). The bounds define a set of constraints that delimit a plurality of convex space-time objects along the reference line.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating trajectory predictions for one or more agents in an environment. In one aspect, a method comprises: obtaining scene context data characterizing a scene in an environment at a current time point and generating a respective predicted future trajectory for each of a plurality of agents in the scene at the current time point by sampling a sequence of discrete motion tokens that defines a joint future trajectory for the plurality of agents using a trajectory prediction neural network that is conditioned on the scene context data.

Abstract: Systems and methods for latency-tolerant assistance of autonomous vehicles (AVs) are described herein. In one aspect, a computer-implemented method for receiving latency-tolerant assistance of an AV can include receiving sensory data from the AV; detecting from the sensory data a trigger for assistance; generating a request for assistance including at least a portion of the sensory data of the AV; receiving, in response to the request for assistance, an operator command for responding to the trigger for assistance; and initiating one or more actuation commands via an actuation subsystem of the AV in response to the received operator command.

Abstract: The driver monitoring device includes a judgment part configured to judge whether a driver of a vehicle is in a drive ready state in which the driver can perform driving operations; and a notification part configured to issue a warning to the driver when it is judged that the driver is not in the drive ready state. The judgment part is configured to acquire an image generated by an imaging device provided at the vehicle so as to capture the driver and driver information acquired by a terminal able to be operated by the driver, and judge whether the driver is in the drive ready state based on the image and the driver information.

Abstract: A method for operating a vehicle in the automated driving operation involves continuously monitoring a rear space of the vehicle. If a following vehicle is recorded coming critically close to the vehicle, a warning is output to the following vehicle. If, after a period of time which can be pre-determined, the following vehicle continues to come critically close to the vehicle, a takeover request relating to a driving task is transmitted to a vehicle user of the vehicle.

Abstract: Provided is a rail vehicle that can promote a weight reduction of the rail vehicle by providing a film body in a side film or a ceiling film, can ensure a large vehicle inner space, can prevent the occurrence of stains, scratches, and the like. The rail vehicle includes an underframe including a floor portion, side structures that each have a window and are erected along a longitudinal direction of the side structures at both end portions in a width direction of the underframe, and side films provided along surfaces of the side structures on a vehicle inner side. Each of the side films has a window opening portion at a portion corresponding to the window, and a window frame portion that presses a peripheral edge portion of the window opening portion toward the side structure is provided.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for receiving a first medium; a second inlet for receiving a second medium, a first thermodynamic device and a second thermodynamic device. The first thermodynamic device is fluidly coupled to both the first inlet and the second inlet and the second thermodynamic device is fluidly coupled to the second inlet. The second medium is provided to the first thermodynamic device and the second thermodynamic device in parallel.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for receiving a first medium, at least one inlet for receiving a second medium, and a thermodynamic device including a compressor and a plurality of turbines operably coupled by a shaft. The plurality of turbines includes a first turbine and a second turbine arranged in series relative to a flow of the first medium. Energy extracted from the second medium at one of the plurality of turbines is used to drive the compressor. The flow of the first medium and a first flow of the second medium are mixed to form a third medium at a first mixing point located downstream from the thermodynamic device relative to the flow of the first medium.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for receiving a first medium, a second inlet for receiving a second medium, and a thermodynamic device including an electric generator and at least one turbine operably coupled by a shaft. A first mixing point is fluidly coupled to the second inlet and an outlet of the at least one turbine.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for a first medium, a second inlet for a second medium, and a thermodynamic device including a compressor and at least one turbine. The at least one turbine is fluidly coupled to and arranged downstream from the first and second inlet. A flow of the first medium and a first flow of the second medium are mixed to form a third medium at a first mixing point arranged downstream from the thermodynamic device relative to the flow of the first medium. A dehumidification system is fluidly coupled to the thermodynamic device and is arranged upstream from the at least one turbine. A regeneration heat exchanger is fluidly coupled to and is downstream from the compressor. Heat is removed from the first medium at the regeneration heat exchanger.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for receiving a first medium and at least one inlet for receiving a second medium. The second medium includes a first flow of the second medium and a second flow of the second medium. A thermodynamic device is fluidly coupled to the first inlet and includes a compressor and at least one turbine operably coupled by a shaft. The first medium is provided to the compressor and the at least one turbine in series. A first mixing point is fluidly coupled to the second inlet and an outlet of the at least one turbine. A regeneration heat exchanger is fluidly coupled to another outlet of the thermodynamic device and to the at least one inlet.

Abstract: An environmental control system for conditioning a cabin of a vehicle positioned in an enclosed air-evacuated environment includes a first inlet for receiving a flow of a first medium, a second inlet for receiving a flow of a second medium, and a thermodynamic device fluidly coupled to both the first inlet and the second inlet. The thermodynamic device includes a compressor and at least one turbine operably coupled by a shaft. At least one conduit is fluidly coupled to the second inlet and bypasses the thermodynamic device. A mixing point is fluidly coupled to an outlet of the at least one turbine to the at least one conduit. A recirculation heat exchanger is fluidly coupled to an outlet of the thermodynamic device and to the at least one conduit at a location upstream from the mixing point.

Abstract: Provided is a rail vehicle including a projector-type in-vehicle display device that is provided with a projector and a projection surface, the rail vehicle including the in-vehicle display device that can prevent a crew or the like who walks on a passage between seats from blocking a projection image, that provides good visibility for a passenger or the like, and that has a light weight. A rail vehicle includes a roof structure serving as a roof of the rail vehicle, a side structure serving as a side surface of the rail vehicle, a luggage rack portion provided along a longitudinal direction of the rail vehicle on a vehicle inner side of the rail vehicle at an upper end portion of the side structure, a projector provided in the luggage rack portion, and a ceiling film provided on a vehicle inner side of the roof structure and serves as a projection surface onto which an image is projected from the projector.

Abstract: Provided is a rail vehicle including a film that can be maintained in a construction state without being affected by expansion and contraction or the like of the film due to aging, and can be easily constructed and replaced, in addition to being able to promote a weight reduction by reducing the number of components. In a rail vehicle including a structure, the structure includes a film provided along the structure on a vehicle inner side of the rail vehicle, the film has a film central portion, a film end portion connected to the structure via an elastic body, and a first fastener portion that separably connects the film central portion and the film end portion, and tension of the elastic body is applied to the film in a state in which the first fastener portion is closed.

Abstract: A method for 3D positioning in a subway construction site. The method includes: establishing a 3D coordinate system corresponding to a shaft area, and determining a coordinate of each UWB base station set in different layers of the shaft area; ranging a positioning label through each UWB base station; filtering and discarding error data from the ranging data; dividing the 3D coordinate system into a plurality of equal cube grids, selecting a preset number of UWB base stations from the set UWB base stations based on the filtered result, and determining a position record of the positioning label in each cube grid in turn based on coordinates of the selected UWB base stations and corresponding ranging data, and the center point coordinate of each cube grid; and determining a conclusion coordinate of the positioning label by voting based on the position record of each cube grid.

Abstract: The system 100 can include: a railroad integration system, a motion planner, a vehicle controller, an optional user interface (UI), an optional fleet management system, and an optional track data system. However, the system 100 can additionally or alternatively include any other suitable set of components. The system functions to facilitate vehicle control and/or manage authority within a rail network.

Abstract: A railcar fouling detection system is disclosed herein that is configured to monitor a railway foul zone between a switch and a foul line by detecting railway vehicles moving within or through the foul zone and determining whether railway vehicles are positioned within the foul zone based on information obtained by the one or more sensors. In some embodiments, the railcar fouling detection system may be configured to determine whether a railway vehicle is positioned within the foul zone by counting the number of wheels (or railway vehicles) entering and exiting the foul zone. The railcar fouling detection system may be configured to provide a visual indication of whether or not a railway vehicle is presently within the foul zone and/or provide a notification to locomotives in response to detecting a railway vehicle positioned within the foul zone.