Abstract: A vehicle and a braking method and a device therefor are provided. The method includes the following steps: obtaining a first state information of the vehicle, where the first state information includes a vehicle mass and a deceleration required by braking; calculating a braking torque required by the vehicle according to the first state information, and controlling the vehicle to output an electric braking torque according to the braking torque required by the vehicle; obtaining a current vehicle speed of the vehicle and an electric braking exit protection speed; and calculating an electric braking exit speed according to the braking torque required by the vehicle and the deceleration required by braking, and controlling the vehicle to unload the electric braking torque when the current vehicle speed is less than a larger one of the electric braking exit speed and the electric braking exit protection speed.

Abstract: Systems, methods and computer program products that facilitate driver assist interface in a vehicle. A system can include a memory and a processor that executes computer executable components. The computer executable components can include: a monitoring component that monitors driver operation of a vehicle, an analysis component that analyzes the driver operation of the vehicle, a recommendation component that generates real-time recommendations regarding improving at least one of driver turning, accelerating or braking of the vehicle, and an interactive display component that generates a real-time graphical user interface that visually represents the real-time recommendations relative to the driver's current operation of the vehicle.

Abstract: A method for selecting a subset of devices from a plurality of devices in a wireless network to perform: a first function comprising transmitting, receiving and/or processing a first radio frequency signal in a first frequency band for detecting atmospheric conditions; and a second function comprising transmitting, receiving and/or processing a second radio frequency signal in a second frequency band, at least partially overlapping with the first frequency band, for performing network communications; wherein the first and the second function are performed during a time period; and wherein the time period comprises a first subset of timeslots and a second subset of timeslots; wherein the method comprises: selecting the subset of devices based on a physical location of the devices relative to an area in which atmospheric conditions are to be monitored; assigning the first subset of timeslots to each of the selected devices to perform the first function, wherein the first subset of timeslots is assigned based on

Abstract: A vehicle control apparatus includes a plurality of control units communicable with each other. The plurality of control unit includes a host unit and a plurality of lower units managed by the host unit. The vehicle control apparatus configured to perform: specifying a lower unit used for executing a predetermined operation among the plurality of lower units when received a signal for instructing any one of the plurality of lower units to start the predetermined operation of the vehicle control apparatus; outputting an activation request command to the lower unit used for executing the predetermined operation; and outputting, after a predetermined time elapsed since the activation request command is output, an operation start command of the predetermined operation to the lower unit used for executing the predetermined operation.

Abstract: Described herein are examples of a system that processes information describing movement of a vehicle at a time related to a potential collision to reliably determine whether a collision occurred and/or one or more characteristics of the collision. In response to obtaining information regarding a potential collision, data describing movement of the vehicle before and/or after a time associated with the potential collision is analyzed to determine whether the collision occurred and/or to determine one or more collision characteristic(s). The analysis may be carried out at least in part using a trained classifier that classifies the vehicle movement data into one or more classes, where at least some the classes are associated with whether a collision occurred and/or one or more characteristics of a collision. If a collision is determined to be likely, one or more actions may be triggered based on the characteristic(s) of the collision.

Abstract: Text and speech from a computer simulation are processed by a machine learning engine to animate the face of a computer avatar.

Abstract: An actuator module for a vehicle includes an actuator control device configured to output an actuator activation signal and at least one actuator configured to receive the actuator activation signal and perform, based on the actuator activation signal, an actuator operation. The actuator control device includes a driving dynamics sensor device configured to measure at least one driving dynamics measurement variable of the vehicle and to generate a driving dynamics measurement signal. The actuator control device also includes a signal compensation device configured to receive the driving dynamics measurement signal and an actuator information signal indicating the actuator operation of the actuator control device, to filter the driving dynamics measurement signal in a manner dependent on the actuator information signal, and to output a compensated driving dynamics measurement signal.

Abstract: Systems and methods include obtaining observation points of a lane line using a sensor of a vehicle. Each observation point indicates a location of a point on the lane line. A method includes generating or updating a lane model with the observation points. The lane model indicates a path of the lane line and the lane model is expressed in a lane-specific coordinate system that differs from a vehicle coordinate system that is defined by an orientation of the vehicle. The method also includes transforming the lane-specific coordinate system to maintain a correspondence between the lane-specific coordinate system and the vehicle coordinate system based on a change in orientation of the vehicle resulting in a change in the vehicle coordinate system.

Abstract: A method and a processor for controlling in-lane movement of a Self-Driving Vehicle (SDV) are provided. The method comprises: acquiring initial kinematic data associated with an obstacle; determining future kinematic data associated with the obstacle; acquiring initial kinematic data associated with the SDV; determining future kinematic data associated with the SDV which is indicative of at least two candidate future states of the SDV at a future moment in time; determining at least two candidate state-transition datasets for the SDV to transition from the initial state of the SDV to a respective one of the at least two candidate future states of the SDV using only in-lane movement; determining, by the electronic device, an energy efficiency score for a respective one of the at least two candidate state-transition datasets; determining a target state-transition dataset for the SDV based on respective energy efficiency scores.

Abstract: A system and method for distributing data for a group of at least two electronic devices, wherein each of the devices has an electronic communication unit, each of which is designed for exchanging internal data among one another, wherein at least one of the communication units has a receiver unit which is designed for receiving external data from an external computer unit, has an arithmetic unit using an algorithm, wherein the algorithm is designed, based on the external data, to generate configuration data as internal data, and is designed to transmit the configuration data to at least one other communication unit of the system, and has a digital display device for the visual display of information for a user, wherein the display device is designed to display information which is updated based on the configuration data.

Abstract: A controller for a vehicle, a system, a vehicle, a method, a computer program and a non-transitory computer-readable storage medium are disclosed. The controller is configured to receive an indication of a measured speed of the vehicle, and determine whether a gradient on which the vehicle is located is below a threshold gradient. The controller is also configured to provide an output signal to cause a brake of the vehicle to be automatically applied to hold the vehicle stationary, in dependence on: the received indication of the measured speed of the vehicle being below a threshold speed; and the determination that the gradient is below the threshold gradient.

Abstract: A method of a first transportation vehicle for predicting channel load. The first transportation vehicle predicts a critical area with channel congestion of at least one communication channel, determines a propagation trajectory of at least one second transportation vehicle and compares the propagation trajectory of the at least one second transportation vehicle and the critical area. Based on the comparison, the first transportation vehicle then selectively transmits a message having information on the critical area to at least one second transportation vehicle. Also disclosed is a transportation vehicle for performing the method and a computer program having instructions for performing the method.

Abstract: The present embodiments relate to systems and methods for using a blockchain to record information related to processes and services in the vehicle industry. The systems and methods may include (1) receiving an indication of vehicle being involved a vehicle collision and a vehicle VIN; (2) accessing, at a memory, a loss history blockchain associated with the vehicle using the VIN as a key; (3) receiving vehicle sensor data generated or collected prior to, during, and/or after the vehicle collision; (4) creating a block to add to the loss history blockchain that includes the vehicle sensor data, or otherwise updating the loss history blockchain with the vehicle sensor data associated with the vehicle collision; (5) analyzing the vehicle sensor data to reconstruct the vehicle collision; and/or (6) updating the loss history blockchain to include and/or indicate the reconstructed vehicle collision by including the created block.

Abstract: In a parking assistance device, a target parking position calculation unit calculates a target parking position of a subject vehicle based on a position of a corner point of a parking space. A constraint condition setting unit sets a constraint condition regarding a target parking route for guiding the subject vehicle to the target parking position based on a position and a posture angle of the subject vehicle, peripheral information of the subject vehicle, and the position of the corner point of the parking space. The constraint condition includes a condition that a curvature change rate of the target parking route is continuous. A target parking route calculation unit calculates the target parking route based on the position and the posture angle of the subject vehicle, the position of the corner point of the parking space, the target parking position, and the constraint condition.

Abstract: A method for generating vehicle controlling data includes executing an operating process that operates an electronic device, executing an obtaining process that obtains a state of a vehicle, executing a reward calculation process that assigns a reward based on the state of the vehicle, and an updating process that updates relationship specifying data. The reward calculation process includes a changing process that changes a reward assigned when an area variable equals a second value and a property of the vehicle is a predetermined property from a reward assigned when the area variable equals a first value and the property of the vehicle is the predetermined property.

Abstract: A speed planning method and apparatus and a calculating apparatus for automatic driving of a vehicle. The method comprises: using a training sample set to perform machine learning to obtain a machine learning model; partitioning an input space, and obtaining a decision result corresponding to a determined partition based on the obtained machine learning model to form a partition decision table of each partition corresponding to the corresponding decision result; and obtaining each dimensional feature vector of a vehicle while driving in real time as an input feature, determining an input partition to which the input feature belongs, and querying the partition decision table based on the determined partition to obtain the corresponding decision result.

Abstract: In one embodiment, a method comprises: receiving, by a constrained wireless network device comprising a local clock, a plurality of messages from respective neighboring wireless network devices advertising as available parent devices in a directed acyclic graph of a time-synchronized network that is synchronized to a master clock device; determining, by the constrained wireless network device, a corresponding timing error of the local clock relative to each message output by the corresponding available parent device; and executing, by the constrained wireless network device, a distributed time synchronization of the local clock with the master clock device based on correlating the respective timing errors relative to the local clock.

Abstract: A vehicle seat system includes a seat including a seat back and a seat base and a passive restraint system mounted adjacent to the seat. The passive restraint system includes a lap belt. A belt adjuster is mounted at the seat. The belt adjuster includes a member operable to engage and shift the lap belt away from the seat back upon being exposed to a selected deceleration force.

Abstract: A path planning of the ADV is performed. A set of obstacle boundaries are generated for one or more obstacles, where each of the set of obstacle boundaries has a corresponding buffer distance ranging from a predetermined minimum buffer distance to a predetermined maximum buffer distance. A set of paths of the ADV is generated using quadratic programming based on the set of obstacle boundaries in parallel, where each path of the set of paths corresponds to one of the set of obstacle boundaries. A path is selected from successful paths of the set of paths based on a corresponding obstacle boundary having a smallest corresponding buffer distance, where the ADV is at least a predetermined distance away from the one or more obstacles in the successful paths. The ADV is controlled to drive autonomously according the selected path to avoid the one or more obstacles.

Abstract: A system and method for assisting a driver in controlling a vehicle, the vehicle comprising one or more driver controls, the method comprising determining an optimal path for the vehicle; determining, based on the current motion of the vehicle and a current setting of one or more driver controls, a predicted path of the vehicle; determining if there is a difference between the optimal path for the vehicle and the predicted path of the vehicle; and if it is determined that there is a difference between the optimal path and the predicted path, delivering haptic and non-haptic feedback to the driver of the vehicle, the feedback comprising an indication that the driver should alter the current setting of one or more driver controls, wherein alteration of the setting of one or more driver controls modifies the motion of the vehicle to reduce the difference.

Abstract: Systems and methods for improving driver attention awareness are disclosed herein. One embodiment monitors the attention status of the driver of a vehicle; detects, based on the monitoring, the commencement of a distracted-driving incident; records, during the distracted-driving incident, information pertaining to the distracted-driving incident; detects, based on the monitoring, the end of the distracted-driving incident; and reports, at the earliest opportunity after the end of the distracted-driving incident and prior to the conclusion of the current trip, the information to the driver.

Abstract: A method for diagnosing secure communication. Before performing a data transmission, a self-diagnosing mode is entered. Error checkpoints are checked to generate a diagnostic status. The diagnostic status is collected. An error handling mode is entered to determine whether an error exists in the diagnostic status. When there is an error, the error is shielded. The method for diagnosing secure communication solves the problem of image burn-in, and further reduces the use of non-volatile memory. Therefore, the size and function utility of the integrated circuit can be further reduced.

Abstract: A filter monitor system (“FMS”) module is installed on the engine/vehicle and is connected to the filter systems, sensors and devices to monitor various performance parameters. The module also connects to the engine control module (“ECM”) and draws parameters from the ECM. The FMS module is capable of interfacing with various output devices such as a smartphone application, a display monitor, an OEM telematics system or a service technician's tool on a computer. The FMS module consists of hardware and software algorithms which constantly monitor filter systems and provide information to the end-user. FMS module provides necessary inputs and outputs for electronic sensors and devices.

Abstract: In various embodiments, methods, systems, and vehicle apparatuses are provided. A method for implementing a lane-keeping assist unit of a vehicle by receiving information of a plurality of road geometries, and driving scenarios wherein at least one driving scenario is combined with a target path that is parallel and biased from a lane center by a desired path offset, and a reference path for guiding the vehicle to merge with the target path; adapting the reference path with control based on a selected road geometry and driving scenario; adjusting the desired path offset by considering lane markings during an intervention for an inner curve, an outer curve and a straight road; controlling the vehicle trajectory for enabling the vehicle to track the reference path; exiting the intervention once a trajectory tracking performance by the vehicle is confirmed; and aborting once an instability of the trajectory tracking performance is confirmed.

Abstract: A vehicle control apparatus including: a storage portion configured to store therein a vehicle control software for controlling a vehicle; an updating portion configured to update the vehicle control software stored in the storage portion, to an update software, and an operation check portion configured, when the update software is stored in the storage portion, to make an operation check as to whether the vehicle operates normally or not, by executing processing of the update software on condition that the vehicle is in a vehicle stopped state in which the vehicle is suppressed from being moved in forward and reverse directions. When it is checked by the operation check portion that the vehicle operates normally with the processing of the update software, the updating portion is configured to update the vehicle control software to the update software.

Abstract: Techniques for detecting the presence of interference in a channel of a VHF data radio are provided. Upon detecting a sufficient level interference, the mode of the VHF data radio is changed from VHF data link (VDL) mode 2 to VDL mode A. Optionally, the VHF data radio mode may be changed back to VDL 2 from VDL mode A departing or preparing to depart.

Abstract: A method of operating a communication adapter of a gas turbine engine of an aircraft includes receiving a plurality of time series data at the communication adapter from an engine control of the gas turbine engine. The method also includes recording a plurality of internal sensor data of an internal sensor system of the communication adapter. The method further includes correlating the time series data with the internal sensor data based on an alignment in time to form an enhanced data set and transmitting the enhanced data set from the communication adapter to an offboard system.

Abstract: An example system includes an in-vehicle content-delivery system (CDS) on a vehicle storing a library of content, and a content server including a content portal. The content portal may receive a request for a customized content manifest from the CDS, identify the vehicle, identify a customized content manifest, and provide the customized content manifest to the CDS. The customized content manifest may include a list of content customized for an itinerary and/or the vehicle, and wherein the customized content manifest differs from another content manifest customized for a different itinerary and/or a different vehicle. The CDS may remove first content from the library of content when the first content is not included in the list of content, and load second content to the library of content when the second content is included in the list of content and not already present in the library of content.

Abstract: A system for controlling an autonomous vehicle is capable of predicting and eliminating a possibility of motion sickness before and during travelling of the autonomous vehicle. The system includes: a first control unit which compares a first vehicle motion sickness index that is determined by a travelling simulation with a first threshold set including passenger information before travelling and controls a boarding location of a passenger before travelling; and a second control unit which computes a passenger motion sickness index from passenger state information and vehicle state information detected during travelling, compares a second threshold indicating the degree of sensitivity to motion sickness according to passenger information during travelling with the passenger motion sickness index, and controls the autonomous vehicle so as to reduce or eliminate a generation of a motion sickness causing frequency.

Abstract: A road shape recognizer includes a peripheral information recognizer that recognizes at least two items of peripheral information based on an output of a periphery detector. A reliability assigner assigns a reliability level to each of the peripheral information. A point sequence generator generates and places a point sequence representing a shape of a road on which the own vehicle travels, based on at least two items of peripheral information and the reliability level. The point sequence generator generates and places a point sequence by generating and placing points one by one toward a distant place from a point located at a prescribed relative position to the own vehicle. The point sequence generator generates and places the next point corresponding to an amount of change in shape and a position of a point generated and placed at the end of the point sequence. The amount of change in shape is represented by the peripheral information and determined per section having a prescribed distance.

Abstract: An upgrade system upgrades a motorized mobile chair to a smart motorized mobile chair. The motorized mobile chair has a processing system comprising at least two processors. The upgrade system comprises a plurality of object detection sensors and at least one processing unit connected between at least a first one of the at least two processors of the processing system and at least a second one of the at least two processors of the processing system. The processing unit receives sensor data from at least one of the plurality of object detection sensors, receives at least one control signal transmitted from the first processor, the control signal comprising data, modifies or does not modify the data of the control signal based on at least the sensor data, and transmits the modified or not modified control signal, the transmitted control signal to be received by the second processor.

Abstract: A method of operating a vehicle, comprising: receiving ambient air information; receiving size, distance and relative velocity information about a vehicle in proximity to the vehicle; receiving road surface properties information; receiving wind velocity and direction information; computing an air density ratio factor using the ambient air information; computing an aerodynamic drag ratio factor using the size, distance and relative velocity information; computing a rolling resistance ratio factor using the information road surface properties information; computing effective velocity of the vehicle using the wind velocity and direction information; combining at least one of the air density ratio factor, the aerodynamic drag ratio factor and the rolling resistance ratio factor with vehicle loss coefficients to determining new vehicle loss coefficients; computing an energy loss or power loss of the vehicle using the new vehicle loss coefficients and the effective velocity of the vehicle; and controlling the vehi

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for implementing an accident reporter are disclosed. In one aspect, a method includes the actions of receiving data that reflects characteristics of a vehicle. The actions further include, based on the data, determining that the vehicle has been in an accident. The actions further include, based on determining that the vehicle has been in an accident and based on the data that reflects the characteristics of the vehicle, determining a classification of the accident. The actions further include determining additional data to collect and a recipient of a description of the accident. The actions further include receiving the additional data. The actions further include generating the description of the accident based on the data that reflects the characteristics of a vehicle and the additional data. The actions further include providing, for output, the description of the accident.

Abstract: A health condition of a person may be assessed from a thermal sensor signal. By increasing performance indices of a thermal camera (for example, resolution, frame rate, sensitivity), operation may be extended to identification verification, biometric data extraction and health condition analysis, and so forth. Prediction may be carried out by monitoring a time sequence of thermal images, and consequently early warning of the health condition may be provided. The apparatus may be used for, but not limited to, personalization of smart home devices through supervised and reinforcement learnings. The application of the apparatus may be, but not limited to, smart homes, smart buildings and smart vehicles, and so forth.

Abstract: A framework for safely operating autonomous machinery, such as vehicles and other heavy equipment, in an in-field or off-road environment, includes detecting, identifying, classifying and tracking objects and/or terrain characteristics from on-board sensors that capture images in front and around the autonomous machinery as it performs agricultural or other activities. The framework generates commands for navigational control of the autonomous machinery in response to perceived objects and terrain impacting safe operation. The framework processes image data and range data in multiple fields of view around the autonomous equipment to discern objects and terrain, and applies artificial intelligence techniques in one or more neural networks to accurately interpret this data for enabling such safe operation.

Abstract: There is disclosed system to warn a driver about driving laws and/or conditions. Optionally, the system includes a database of traffic laws, for example indexed according to location and/or time and/or conditions. For example, the device may display a speed limit reflecting local conditions such as weather, construction, school hours. In some embodiments, warnings may be customized to a particular vehicle and/or driver. In some embodiments, the system may warn a third party about driving behavior and/or legal infringements.

Abstract: Provided is an in-vehicle system in which an own vehicle does not decelerate according to a preceding vehicle even if the preceding vehicle changes lanes to the right turn lane or the left turn lane and decelerates after own vehicle entering an intersection area. A CPU 107 (first control unit) controls the own vehicle to follow the preceding vehicle. An image processing circuit 106 (detection unit) detects a lane marking of the traveling lane. The CPU 107 (determination unit) determines whether an own vehicle 201 has entered the intersection area. When the detection of one of the right and left lane markings of the traveling lane is interrupted (S20: YES) after the own vehicle 201 has entered the intersection area (S15: YES), the CPU 107 (second control unit) releases ACC that causes the own vehicle 201 to follow the preceding vehicle 202.

Abstract: A computer includes a processor and a memory storing instructions executable by the processor to detect an object in data received from a rear-facing radar on a vehicle and activate an alarm in response to the object moving through a predesignated region behind the vehicle at a speed below a threshold speed or for a duration above a threshold time.

Abstract: A motorcycle including a motorcycle body having a front part, a tail part and a central part between the front part and the tail part front and rear wheels constrained to the motorcycle body (2,3,4), a traction engine constrained to the motorcycle body (2,3,4) and operatively connected to at least one of the wheels, at least one optical signalling device fixed to the motorcycle body arranged and oriented so as to be visible by a vehicle that is following the motorcycle, an electronic control unit of the optical signalling device operatively connected to the optical signalling device, an obstacle sensor fixed to the motorcycle body (2,3,4) and operatively connected to the electronic control unit, where the electronic control unit is adapted and configured to receive at least one output signal supplied by the obstacle sensor, verifying whether said output signal meets at least one logical activation condition and, in such case, turning on the optical signalling device to signal a risk of collision with the moto

Abstract: One or more devices in a data analysis computing system may be configured to receive and analyze acceleration data corresponding to driving data, analyze the acceleration data, and determine driving patterns and associated drivers based on the data. Acceleration data may be collected by one or more mobile devices, such as smartphones, tablet computers, and/or on-board vehicle systems. Drivers associated with driving trips may be identified based on the acceleration data collected by the mobile devices. In some cases, driving patterns may be determined based on the acceleration data before and after stopping points during driving trips, and the driving patterns may be compared to a set of previously stored driving patterns associated with various different drivers.

Abstract: An intelligent driving method comprising: obtaining feature parameters of a vehicle at a current moment and a road attribute of a driving scenario of the vehicle in a preset future time period; comparing the feature parameters at the current moment with feature parameters of a standard scenario in a scenario feature library; comparing the road attribute of the driving scenario of the vehicle in the preset future time period with a road attribute of the standard scenario in the scenario feature library; determining a total similarity of each scenario class to a driving scenario of the vehicle at the current moment based on comparing results; determining, as the driving scenario at the current moment, a first scenario class with a highest total similarity in N scenario classes; and controlling, based on the determining result, the vehicle to perform intelligent driving.

Abstract: A vehicle data analysis device and a vehicle data analysis method thereof are provided. The vehicle data analysis device receives a sensing data and a controller area network (CAN) message, and performs a similarity comparison on the sensing data and a plurality of bytes of a data field of the CAN message to determine whether the CAN message is a target CAN message corresponding to the sensing data.

Abstract: A computer-implemented method for determining whether an electric vehicle (EV) requires a current charge. The method analyzes a set of EV data, wherein the set of EV data comprises a battery level, a destination, a current position, and a predicted arrival time to the destination. The method further constructs a charging regulation model for the EV, based on the analyzed set of EV data. The method further computes a risk score pertaining to charging the EV, based on the constructed charging regulation model for the EV, and determines whether the EV requires a current charge based on the computed risk score. The method further engages one or more wireless charging points on a roadway, if the computed risk score is below a threshold value.

Abstract: In order to display driving assistance images to a driver in a vehicle, visible light images are captured using a visible light camera mounted for viewing a roadway on which the vehicle travels and infrared images overlapping with the visible light images are captured using an infrared camera mounted for viewing the roadway. The visible light images are normally displayed on a display screen when a visible light brightness around the vehicle is greater than a brightness threshold. Trigger conditions are monitored which are indicative of limitations of a driver visibility when directly viewing the roadway. The trigger conditions include a driver reaction. The monitored trigger condition is classified according to a plurality of predetermined classifications which indicate an occurrence of an impairment event. The infrared images are selected for display on the display screen upon occurrence of the impairment event.

Abstract: According to an embodiment disclosed in this specification, an electronic device may be configured to control a size of an exposed region of a first display based on driving information of a vehicle and to set a user interface for receiving a user input associated with content displayed on the first display to at least one of the first display or an auxiliary input interface based on a size of an exposed region. Other various embodiments as understood from the specification are also possible.

Abstract: A vehicle movement identification method and device, and a vehicle alert system. The method comprises: after a vehicle shuts off, collecting real-time state data of the vehicle by means of a sensor (74) provided for the vehicle (S202); comparing the real-time state data with the pre-stored post-shutdown stationary state data of the vehicle (S204); and determining, according to the comparison result, whether the vehicle is moved by a tow truck (S206).

Abstract: A vehicle control system and method includes identifying a segment of a route where one or more first vehicle systems were operated manually instead of operated by one or more processors according to one or more trip plans during prior traversals of the segment by the one or more first vehicle systems. A segment plan is generated for traversing the segment under control of the one or more processors. The segment plan is generated based on how the one or more first vehicle systems were manually operated during the prior traversals of the segment. One or more second vehicle systems are controlled with the one or more processors to traverse the segment according to the segment plan.

Abstract: A method includes obtaining a time-series of training samples that include one or more states, a ground truth value, an output value produced in the presence of the one or more states, and an actual error value that is defined as a difference between the ground truth value and the output value. The method also includes training a machine learning model using the time-series of training samples such that the machine learning model is configured to determine a condition-dependent error distribution for a current time step based on simulated states for the current time step.

Abstract: A program update system includes a vehicle including a first and second electronic devices, and a program transmission device. The program transmission device is configured to communicate with the vehicle and transmit a program for the first electronic device and a program for the second electronic device to the vehicle. The program transmission device transmits an update program for a first electronic device to a second electronic device. The program transmission device transmits a program in a state before the update for backup. The second electronic device updates the program for the first electronic device based on the update program. The second electronic device stores the program in the state before the update.

Abstract: A method for controlling rights of an autonomous vehicle includes acquiring, via a network, identification information for identifying a user or a terminal of the user, and dispatching request information that indicates a dispatch request for the autonomous vehicle issued by the user. The method further includes selecting the autonomous vehicle to be dispatched to the user from among multiple autonomous vehicles based on the dispatch request information, and assigning a control right for the selected autonomous vehicle, to the user or the terminal, based on the identification information.