Abstract: A vehicle program update system and a vehicle program update method are provided which update a vehicle program that is used to control a vehicle by an on-board control device mounted on the vehicle to an update program received by the vehicle from an external device separate from the vehicle via wireless communication. When the update of the vehicle program is completed, determination is made whether the updated vehicle program is normal. When determination is made that the updated vehicle program is not normal, control of the vehicle is switched from control that is performed by the on-board control device using the vehicle program to limp home control for performing a limp home operation in which the vehicle travels using a driving force from a vehicle driving force source without being controlled by the on-board control device.

Abstract: A travel control device is mounted on a vehicle including an electric motor and an internal combustion engine that are power sources and a storage battery that stores energy for driving the electric motor and regenerative energy recovered by regenerative braking of the electric motor. The travel control device includes an electronic control device configured to create a speed profile in which a speed of the vehicle is predicted, estimate a predicted amount of the regenerative energy to be recovered, based on the speed profile, and decide the power source to be used for traveling, based on the predicted amount of the regenerative energy and thermal information indicating a demand related to heat of the vehicle.

Abstract: A work vehicle includes a vehicle body, a work implement including an attachment, an operating device and a controller. The operating device can be operated to a dump side and a tilt side to cause the attachment to dump and tilt. The controller executes an automatic drive control in which the attachment is caused to dump as far as a predetermined dumping position when the operating device is operated by a first dump operation amount or greater to the dump side, or to tilt as far as a predetermined tilt position when the operating device is operated by a first tilt operation amount or greater to the tilt side. The controller disables the automatic drive control when a switching time period required for the operating device to be switched between the tilt and dump sides is at least a predetermined disabling time period.

Abstract: Systems and methods for personalizing adaptive cruise control in a vehicle are disclosed herein. One embodiment collects vehicle-following-behavior data associated with a particular driver; trains a Gaussian Process (GP) Regression model using the collected vehicle-following-behavior data to produce a set of adaptive-cruise-control (ACC) parameters pertaining to the particular driver, the set of ACC parameters modeling learned vehicle-following behavior of the particular driver; generates an acceleration command for the vehicle based, at least in part, on the set of ACC parameters; applies a predictive safety filter to the acceleration command to produce a certified acceleration command that has been vetted for safety; and controls acceleration of the vehicle automatically in accordance with the certified acceleration command to regulate a following distance between a lead vehicle and the vehicle in accordance with the learned vehicle-following behavior of the particular driver.

Abstract: A method for improving the adhesion of a rail vehicle by conditioning selected axle(s), detects whether a higher total brake force can be achieved by changing the manipulated variable of the wheel slip at at least one unit from a current starting wheel slip to a forced wheel slip, and, if so, changes the wheel slip at at least one unit from the current starting wheel slip to the forced wheel slip by regulating the manipulated variable of the brake application force at the unit, whereby the friction ratios between the wheel and the rail changes at the subsequent units, and regulates the manipulated variable of the brake application force at the subsequent units to regulate the wheel slip, which is likewise changed by the changed friction ratios, at the units back to the unchanged manipulated variable of the starting wheel slip, optimized brake forces being produced at the units.

Abstract: A computing system can input first relative location embedding data into an interaction transformer model and receive, as an output of the interaction transformer model, motion forecast data for actors relative to a vehicle. The computing system can input the motion forecast data into a prediction model to receive respective trajectories for the actors for a current time step and respective projected trajectories for the actors for a subsequent time step. The computing system can generate second relative location embedding data based on the respective projected trajectories from the second time step. The computing system can produce second motion forecast data using the interaction transformer model based on the second relative location embedding. The computing system can determine second respective trajectories for the actors using the prediction model based on the second forecast data.

Abstract: An autonomous cleaning robot includes a drive system to maneuver the autonomous cleaning robot across a floor surface; a cleaning assembly for cleaning the floor surface; and a sensor system disposed at a forward portion of the autonomous cleaning robot. The sensor system includes a movable element having (i) a first configuration in which the movable element extends beyond a bottom surface of the autonomous cleaning robot by a first amount, and (ii) a second configuration in which the movable element extends beyond the bottom surface of the autonomous cleaning robot by a second amount less than the first amount; a spring mechanically coupled to the movable element, the spring being biased to hold the movable element in the first configuration; and a sensor assembly configured to generate a signal based on the configuration of the movable element.

Abstract: A system for handling a driving while disconnected event. One example includes an electronic logging device configured to be connected to a vehicle and a mobile device. The mobile device includes an electronic processor configured to determine a connection status between the mobile device and the electronic logging device; determine movement of the mobile device; and determine whether the mobile device is connected to the electronic logging device based on the connection status. In response to determining the mobile device is not connected to the electronic logging device, the electronic processor generates driving information associated with a user of the mobile device and movement of the mobile device; transmits the driving information to an external device; and generates a user-perceivable notification to connect the mobile device to the electronic logging device.

Abstract: An electric powered vehicle may include a maximum speed limiting device. In the first mode, in a case where the distance is shorter than a first reference value, the maximum speed is limited to a value lower than the maximum speed applied when the distance is longer than the first reference value. In the second mode, in a case where the distance is shorter than a second reference value, the maximum speed is limited to a value lower than the maximum speed applied when the distance is longer than the second reference value. In a case where the distance changes from a value shorter than the first and second reference values to a value longer the first and second reference values, the maximum speed limiting device increases the maximum speed at an earlier timing in the second mode than in the first mode.

Abstract: A method and a device for locating a vehicle, able to estimate a first position of a vehicle from data that are generated by sensors of the vehicle and that are applied to a first particle filter, to store in memory, in a history, for a plurality of times, sensor data that led to the best estimations of a current position ti, to receive at the time tn a corrected GNSS position of the vehicle at a time t0, and to estimate using a second particle filter FP2 a corrected position of the vehicle at a time ti by applying the second particle filter FP2 to the received corrected GNSS position, to the data stored in memory in association with the time ti and to the dynamic characteristics of the vehicle that are associated with the time ti?1.

Abstract: When there are a plurality of routes to one parking space, automatic parking cannot be performed on a route with short parking time. A route candidate generation unit 301 changes a reference vehicle speed and a route shape, and searches for a route from a parking start position to a parking target position. The route passage time calculation unit 302 calculates, for each route candidate, the time required to pass through the route based on the reference vehicle speed and the length of the route. A state switching time calculation unit 303 calculates, for each route candidate, the time required for switching between forward and backward movements of a vehicle, and the time required to change steering to a predetermined steering angle in a state where the vehicle is stopped. A route selection processing unit 305 selects a specific route, for example, a route with short parking time, from a generated routes based on route passage time.

Abstract: A vehicle locator includes an on-board computer and a ground penetrating radar mounted on the vehicle that is communicably connected to the on-board computer. A reflective landmark is located at a known location along the path of the vehicle. The reflective landmark includes reflective elements arranged to encode data. The ground penetrating radar transmits signal energy and detects reflected signal energy reflected by the reflective landmark and communicates encoded data representative of the reflected signal energy to the on-board computer. The on-board computer decodes the encoded data and thereby determines the location of the vehicle.

Abstract: A computer having a processor and memory storing instructions executable by the processor. The computer is programmed to: determine a total trip parameter associated with a destination of an occupant of a vehicle; determine a progress parameter since an outset of an occupant trip; and control a light output of a status assembly, wherein the output represents the parameters.

Abstract: GPS-based position reporting suffers from probabilistic error. The system and methods discussed herein reduce uncertainty by mapping a geometric figure that encompasses a GPS-based reported location and that bounds corresponding predetermined-as-more-probable true locations (MPTL's) among possible locations for the source of the reported location. The mapped figure is overlaid on a relatively accurate mapping of substantially adjacent polygonal areas. Areas of overlap are used for picking among the areas, the polygonal area most likely to be occupied by the source. In one embodiment, the polygonal areas are closely packed parking spots in a parking lot, garage or other like structure, the source is a customer's mobile phone and an attendant is tasked with quickly delivering ordered goods to the customer's parking spot.

Abstract: Systems and methods for smoothing automated lane change (ALC) operations. A mission planner, upon receipt of an ALC request, sends a ALC heads up signal to a lateral control. The mission planner then begins confidence building operations, for a preprogrammed duration of time, and awaits an ALC ready signal from the lateral control. The lateral control, upon receipt of the ALC heads up, calculates an index of readiness, RALC, as a function of the requested ALC, a current trajectory, and a lane centering control path. When RALC is less than or equal to a readiness threshold, Rt, the lateral control sends the ALC ready signal. When RALC is greater than Rt, the lateral control generates a steering correction and applies the steering correction to reduce the RALC and thereby stabilize the vehicle and send the ALC ready signal. Upon receiving the ALC ready signal, the ALC operation is executed.

Abstract: A vehicle control system comprising: a driving control device that includes a first processor and controls a driving section at a vehicle; a control instructing device includes a second processor and controls the driving control device by giving instructions by communication to the driving control device; and a communication path connects a plurality of control devices, including the control instructing and the driving control devices, the plurality of control devices communicate with one another, wherein the vehicle control system is structured wherein the first and second processors respectively compare a communication period of communication with another control device via the communication path, and a reference period that is stored in advance, based on results of comparisons on the communication period and the reference period that have been carried out by the first processor and the second processor, the second processor judges that there is an attack on the communication path.

Abstract: A method and system are disclosed and include assigning a vehicle to a user. The method also includes obtaining contextual information associated with the vehicle-sharing request, and the contextual information includes at least one of location information associated with the vehicle-sharing request, route information associated with the vehicle-sharing request, and user information associated with a vehicle-sharing account corresponding to the user. The method also includes determining a cleanliness score based on the contextual information and determining whether the cleanliness score is less than a first threshold value. The method also includes transmitting, in response to (i) the cleanliness score being less than the first threshold value and (ii) a vehicle-sharing session corresponding to the vehicle-sharing request being complete, an alert that is configured to indicate that the vehicle needs to be cleaned.

Abstract: An unmanned aerial signal relay includes an unmanned aerial vehicle, including a communication relay unit and at least one antenna, communicatively connected to the communication relay unit; a tether comprising at least two wires and at least one fiber optic cable, the wires and cable communicatively connected to the unmanned aerial vehicle; and a surface support system comprising a spool physically connected to the tether and a ground-based receiver communicatively connected to the at least one fiber optic cable, wherein the unmanned aerial vehicle is powered by electrical energy provided by the at least two wires, and wherein the communication relay unit is configured to relay signals received from the at least one antenna via the fiber optic cable to the ground-based receiver. Various systems and methods related to an unmanned aerial signal relay are also described.

Abstract: A plug-in hybrid electric vehicle capable of achieving a charging target in response to environmental change via a charging control method. The charging control method includes: setting reserved charging using external power based on a departure time and a target state of charge (SOC) of a battery; monitoring whether change in charging environment has occurred, determining whether the target SOC of the battery is capable of being achieved at a currently set departure time, when the charging environment has been changed; and performing series charging using an engine and a motor upon determining that the target SOC of the battery is incapable of being achieved.

Abstract: Systems, methods, tangible non-transitory computer-readable media, and devices associated with the motion prediction and operation of a device including a vehicle are provided. For example, a vehicle computing system can access state data including information associated with locations and characteristics of objects over a plurality of time intervals. Trajectories of the objects at subsequent time intervals following the plurality of time intervals can be determined based on the state data and a machine-learned tracking and kinematics model. The trajectories of the objects can include predicted locations of the objects at subsequent time intervals that follow the plurality of time intervals. Further, the predicted locations of the objects can be based on physical constraints of the objects. Furthermore, indications, which can include visual indications, can be generated based on the predicted locations of the objects at the subsequent time intervals.