Abstract: An apparatus includes at least two disk spring washers, at least one ring-shaped outer spacer coupled to the outer edges of one or two of the disk spring washers, and at least one ring-shaped inner spacer coupled to the inner edges of one or two of the disk spring washers. The apparatus also includes a central shaft concentric with the disk spring washers, the outer spacers, and the inner spacers. The apparatus also includes a bottom attachment portion coupled to the bottom of the central shaft to support the at least two disk spring washers, and a top attachment portion configured to slide vertically along the central shaft. The top attachment portion is configured to, with an application of a downward force, compress the at least two disk spring washers.

Abstract: An example operation includes one or more of receiving driving data of a first vehicle, receiving driving data of a second vehicle driving in a different lane than the first vehicle, determining that the first vehicle and the second vehicle will collide via execution of a machine learning model on the driving data of the first and second vehicles, and displaying a warning on a user interface associated with one or more of the first and second vehicles.

Abstract: Certain embodiments of the present disclosure provide techniques for controlling settings (and/or functions) of a vehicle via steering device finger tapping. A method generally includes receiving vibration information from a plurality of vibration sensors associated with a steering device, wherein the plurality of vibration sensors are configured to detect vibration on the steering device caused by a user of the vehicle; in response to receiving the vibration information, determining a user command based on the vibration information, determining a probability that the user intends to employ the user command via the vibration caused by the user, determining whether the probability is equal to or above a threshold, and selectively transmitting or not transmitting, to a controllable device, a control command corresponding to the user command based on whether the probability is determined to be equal to or above the threshold.

Abstract: An example operation includes one or more of receiving, by a processor, first data from a first sensor and second data from a second sensor, on a vehicle, receiving, by the processor, third data from a sensor on a further vehicle, wherein the third data is not observable by the first sensor, interworking, by the processor, the first data, the second data, and the third data, and superimposing, by the processor, the interworked first data, second data, and third data on a display of the vehicle.

Abstract: A bipolar plate-porous transport layer (PTL) assembly for a polymer-electrolyte-membrane water electrolyzer includes a flat metallic bipolar plate and a metal foam PTL adjacent to and in direct contact with the flat metallic bipolar plate. The metal foam PTL includes flow channels defined by flow channels walls with flow channel surfaces. The flow channel walls and flow channel surfaces have an average porosity generally equal to an average porosity of an interior of the metal foam PTL.

Abstract: A hybrid actuation device that includes a first plate coupled to a second plate, a shape memory alloy wire coupled to the first plate, and an artificial muscle stack positioned between the first plate and the second plate. The artificial muscle stack includes a plurality of artificial muscles stacked in a vertical arrangement. Each artificial muscle includes a housing having an electrode region and an expandable fluid region, a first electrode and a second electrode each disposed in the electrode region of the housing and a dielectric fluid disposed within the housing. The expandable fluid region of the housing is positioned apart from a perimeter of the first plate and the second plate.

Abstract: Systems and methods are provided for optimizing predictions regarding traffic conditions based upon learned/measured traffic conditions. Current traffic conditions can be measured and characterized based on speed or other factors as a vehicle traverses the route. These measured traffic conditions can be compared to predicted traffic conditions. A weighting term can be associated with the measured traffic conditions based upon the comparison. During a subsequent time that the vehicle traverses the route, a traffic conditions prediction may be made. The weighting term and measured traffic conditions data can be used to adjust the traffic conditions prediction for better accuracy, and an optimal time(s) during which a battery of a hybrid vehicle can be pre-charged can be requested.

Abstract: A method for measuring a distance is provided. The method includes receiving a fine time measurement (FTM) message, extracting channel state information (CSI) from the FTM message, determining with a channel condition classifier a probability that the FTM message is multi-path based on the corresponding CSI, and discarding the FTM message in response to the probability that the FTM message is multi-path is above a threshold level of probability.

Abstract: Systems, methods, and other embodiments described herein relate to identifying a user of a vehicle. In one embodiment, a method includes determining an activity of the user using one or more mobile devices. The method includes detecting an event in the vehicle using one or more vehicle sensors. The method includes identifying the user based on a relationship between the activity and the event.

Abstract: An example operation includes one or more of identifying, via an ego vehicle, one or more surrounding vehicles of the ego vehicle based on sensor data from the ego vehicle, determining a state of an ego vehicle and a state of the one or more surrounding vehicles of the ego vehicle, dynamically determining parameters for identifying connected vehicles based on the determined states of the ego vehicle and the one or more surrounding vehicles, and detecting a connected vehicle from among the one or more surrounding vehicles via an exchange of messages between the ego vehicle and the one or more surrounding vehicles based on the dynamically determined parameters.

Abstract: An example operation includes one or more of receiving sensor data from one or more hardware sensors of a vehicle, obtaining multi-modal data of an occupant of the vehicle from the sensor data, predicting, via a machine learning model, the occupant of the vehicle suffers from attention deficit hyperactivity disorder (ADHD) based on the multi-modal data, and causing one or more hardware systems within the vehicle to provide an audible alert to the occupant based on the prediction.

Abstract: Systems and methods of leveling a vehicle are disclosed. Exemplary implementations may: provide a plurality of air bag jacks under the vehicle; determine roll and pitch information of the vehicle; determine, using a computing system, an amount of air-adjustment to make for one or more of the plurality of air bag jacks, based on the roll and pitch information, to level the vehicle; and activate, via the computing system, an air compressor to make the determined air-adjustment.

Abstract: An example operation includes one or more of receiving a request from a software application installed on a vehicle, detecting an identifier of the software application from identification information included in the received request, dynamically determining parameters to identify connected vehicles based on the identifier of the software application, and detecting a connected vehicle from among one or more surrounding vehicles via an exchange of messages between the vehicle and the one or more surrounding vehicles based on the dynamically determined parameters.

Abstract: Systems and methods are provided for providing context-based knowledge forwarding which ties a contextual meaning to knowledge, ensuring that knowledge is received within the proper context. A vehicle can query knowledge within a context (e.g., rainy weather conditions), and in response will be forwarded knowledge that was created in similar context (e.g., rainy weather). Contextual features are assigned to knowledge during a knowledge cycle, and contextual features are leveraged when the knowledge is forwarded to be utilized by entities in the vehicular knowledge network. A computer system can construct a knowledge context that corresponds to knowledge. The computer system can also perform context-based knowledge forwarding for a knowledge query by determining that the knowledge context corresponds to a query context of a knowledge query.

Abstract: An electric vehicle (EV) charging and cooling system is described that supplies electric power to charge an EV while simultaneously providing coolant to cool the charging components of the EV during the charging process. For example, the system includes a charging device that provides electrical power for charging a battery of the EV. The system also includes a coolant device that transfers coolant to the EV during charging for cooling the battery of the EV. The system also withdraws the coolant from the EV that has been used, and heated to a temperature that may not be suitable for cooling as a result of absorbing heat from the charging components. The system can cool the used coolant back to the cooled temperature to recirculate to the EV throughout a direct current (DC) fast charging process, which provides thermal stability and mitigates damage to the EV from overheating.

Abstract: An example operation includes one or more of obtaining image data of an occupant of a vehicle from one or more hardware sensors associated with the vehicle, extracting occupant data of the occupant from the obtained image data, predicting that the occupant is impaired from cannabis based on execution of a machine learning model on the extracted occupant data, and transmitting an alert to the vehicle based on the prediction.

Abstract: A discrete metallic particle having a metallic material, and a coating covering at least a portion of the metallic component. The discrete metallic particle has a thickness from 50 nm to 1000 nm, and the discrete metallic particle has a skin depth ? of greater than or equal to 1.0 ?m in a frequency range from 20-40 GHz. The skin depth ? is calculated by: ? = 2 ? ? ( 2 ? ? ? f ) ? ( ? 0 ? ? r ) ? 503 ? ? ? r ? f Where ? is skin depth in meters (m); ? is resistivity in ohm meter (?·m); f is frequency of an electromagnetic radiation in hertz (Hz); ?0 is permeability; and ?r is relative permeability of the metallic material.

Abstract: A fluid transport system that includes a magnetic shape memory pipe having an input end opposite an output end and an outer surface opposite an inner surface. The inner surface defines an inner diameter of the magnetic shape memory pipe and the magnetic shape memory pipe includes a magnetic shape memory alloy. The fluid transport system further includes one or more magnetic field generating devices surrounding the outer surface of the magnetic shape memory pipe and configured to generate a control magnetic field that, when applied to a region of the magnetic shape memory pipe, alters the inner diameter of the region of the magnetic shape memory pipe.

Abstract: Systems and methods of cooperative autonomous driving which maximize objectives of a global traffic environment are provided. In particular, a cooperative controller may control multiple connected vehicles within a traffic environment. In certain embodiments, the cooperative controller may assign each connected vehicle a traffic role, based in part on their situation within the traffic environment. In some embodiments, this traffic role may also be based on a “priority level” for the connected vehicle which corresponds to a desired travel time. Once traffic roles have been assigned, the cooperative controller may control each connected vehicle according to a driving policy associated with its assigned traffic role.

Abstract: A method of determining one or more actions of a vehicle approaching an intersection having traffic lights is provided. Traffic information can be received from the traffic lights. A speed of the vehicle can be detected by a sensor. A distance between the vehicle and an intersection can be determined by processing circuitry. An amount of time for the vehicle to reach the intersection can be calculated. The traffic information with the amount of time can be compared. The one or more actions of the vehicle based on the comparison can be determined.