Abstract: A method for determining a minimum state of charge for an energy storage means of a vehicle can include: determining a routine of use of charge of the energy storage means; determining a user requirement for future driving of the vehicle; predicting a reduction in the state of charge of the energy storage means associated with the user requirement in dependence on the determined routine; determining a minimum state of charge for the energy storage means for enabling the user requirement to be satisfied in dependence on the predicted reduction; and providing an output to the user indicative of a time requirement for increasing the state of charge of the energy storage means to a value at or above the minimum state of charge.

Abstract: A non-transitory computer readable medium having instructions stored thereon that, when executed by at least one processor, cause the at least one processor to receive road quality data from at least one vehicle in a fleet of vehicles and determine a route for the at least one vehicle in the fleet of vehicles. The road quality data may be gathered by at least one sensor configured to detect autonomous vehicle movements and orientation. The route may avoid a segment of road that is associated with poor road quality data.

Abstract: A system includes a processor configured to determine a driver identity. The processor is also configured to receive a request for a change to a driving mode and responsive to the request, enable or deny the driving mode based on mode-correlation to one of a predefined set of permissible driving modes pre-associated with the driver identity.

Abstract: The disclosure describes various embodiments for online system-level validation of sensor synchronization. According to an embodiment, an exemplary method of analyzing sensor synchronization in an autonomous driving vehicle (ADV) include the operations of acquiring raw sensor data from a first sensor and a second sensor mounted on the ADV, the raw sensor data describing a target object in a surrounding environment of the ADV; and generating an accuracy map based on the raw sensor data in view of timestamps extracted from the raw sensor data. The method further includes the operations of generating a first bounding box and a second bounding box around the target object using the raw sensor data; and performing an analysis of the first and second bounding boxes and the accuracy map using a predetermined algorithm in view of one or more pre-configured sensor settings to determine whether the first sensor and the second sensor are synchronized with each other.

Abstract: An aircraft position measurement system is provided for an aircraft configured to use an artificial satellite configured to fly in a known orbit. The aircraft position measurement system includes a reflector, a distance-angle measuring member, a satellite position obtainer, and an aircraft position calculator. The reflector configured to be mounted on the artificial satellite and reflect an electromagnetic wave in a direction in which the electromagnetic wave arrives. The distance-angle measuring member is configured to be mounted on the aircraft and emit an electromagnetic wave and measure a bearing and a distance to the artificial satellite when seen from the aircraft. The satellite position obtainer is configured to obtain an absolute position of the artificial satellite. The aircraft position calculator is configured to calculate a position of the aircraft based on the absolute position of the artificial satellite and the bearing and the distance to the artificial satellite.

Abstract: A pickup system for picking up a product using a vehicle having an autonomous travelling function includes a communication unit configured to accept a pickup request from a user, a travel control unit configured to cause the vehicle to autonomously travel to a user position specified in the pickup request accepted through the communication unit, and an informing unit configured to inform the user that, when the vehicle arrives at the user position, the arrived vehicle is a vehicle that is to pick up a product in response to the pickup request.

Abstract: A secondary system operates on a vehicle to avoid a collision when a problem occurs with a primary system. For example, the secondary system may operate independently from the primary system to take over control of the vehicle from the primary system when the secondary system detects a potential collision, when an error occurs with the primary system, and so on. In examples, the primary system may implement first techniques, such as Artificial Intelligence (AI) techniques, to understand an environment around the vehicle and/or instruct the vehicle to move within the environment. In examples, the secondary system may implement second techniques that are based on positioning, velocity, acceleration, etc. of the vehicle and/or objects around the vehicle.

Abstract: A control method of an automatic working system, which comprises the following steps: a signal generating device generates a boundary signal; the boundary signal flows through the boundary wire to generate an electromagnetic field; a detecting device on an automatic moving device detects the electromagnetic field to generate a detection signal, amplify the detection signal to form a gain signal, compare an feature point of the gain signal with a preset condition, the preset condition comprising: the feature point is lower than an upper threshold value and higher than a lower threshold value, then automatically adjust the gain signal according to a comparing result, such that the feather point of the gain signal formed after adjusting accords with the preset condition, further to process the gain signal, An automatic working system and an automatic moving device also be disclosed.

Abstract: A computing system includes: a control unit, coupled to the communication unit, configured to: monitor a current vehicle operation measure for an essential vehicle control function of a user vehicle in an autonomous vehicle operation state; calculate an operation measure modification factor based on a vehicle operation profile of the user vehicle; calculate a modified model input from the current vehicle operation measure based on the operation measure modification factor; generate a vehicle operation instruction, with the modified model input, for the essential vehicle control function according to a vehicle operation model to operate the essential vehicle control function of the user vehicle in the autonomous vehicle operation state; and a communication unit configured to provide the vehicle operation instruction to an autonomous vehicle operation system.

Abstract: A vehicle includes electronic control units (ECUs) to control devices and functions of the vehicle, domain control units (DCUs) to group the ECUs by domain and manage the groups of the ECUs by domain, and a connectivity control unit (CCU) to communicate with the DCUs and an external device. Each of the ECUs includes a memory to store data and software and a processor to generate a control signal to control a device or a function based on the data and software. The DCU determines whether an ECU is available to store new data based on at least one of a remaining capacity and an available level of a memory of the ECU, and when the ECU is unavailable to store the new data, the DCU selects other memory of the ECUs managed by other DCU as an alternative memory, and store the new data in the alternative memory.

Abstract: A pickup system for picking up a product using a vehicle having an autonomous travelling function includes a communication unit configured to accept a pickup request from a user, a travel control unit configured to cause the vehicle to autonomously travel to a user position specified in the pickup request accepted through the communication unit, and an informing unit configured to inform the user that, when the vehicle arrives at the user position, the arrived vehicle is a vehicle that is to pick up a product in response to the pickup request.

Abstract: A method of collecting data regarding the operation of a vehicle that includes receiving sensor data regarding one or more objects or events in a surrounding environment using one or more vehicle sensors, classifying, by one or more processors, the one or more detected objects or events, generating one or more vehicle inquiries based on the classification of the one or more detected objects or events, presenting one or more vehicle inquiries, and receiving user feedback to the one or more vehicle inquiries.

Abstract: A method for a pilot vehicle for influencing a passing maneuver of at least one second vehicle approaching the pilot vehicle, including the steps: detecting surroundings of the pilot vehicle; identifying a passing intention of the at least one second vehicle; detecting at least one third vehicle on a passing trajectory of the at least one second vehicle; ascertaining and selecting at least one passing maneuver of the at least one second vehicle as a function of the at least one detected third vehicle. The method provides for the emission of at least one signal for controlling the at least one selected passing maneuver. Alternatively provided is a method for a second vehicle for influencing a planned passing maneuver of the second vehicle or a method for a third vehicle for influencing a planned passing maneuver of a second vehicle.

Abstract: The disclosure relates to a method for updating an electronic map. The method includes detecting at least one first object by means of a sensor device of a motor vehicle and assigning a position of the motor vehicle, detected by means of a position detecting device of the motor vehicle, to the detected first object. The method also includes generating a first object data set representing the detected first object and the position assigned to the first object, by means of an evaluation device of the motor vehicle. The method further includes deriving a second object data set, representing a second object external to the vehicle, which is different from the first object detected, from the first object data set. The method also includes updating the electronic map by adding map data corresponding to the second object data set to the map or by removing map data contradicting the second object data set from the map by means of a computing device to improve updating of the electronic map.

Abstract: The present disclosure provides systems and methods that apply neural networks such as, for example, convolutional neural networks, to sparse imagery in an improved manner. For example, the systems and methods of the present disclosure can be included in or otherwise leveraged by an autonomous vehicle. In one example, a computing system can extract one or more relevant portions from imagery, where the relevant portions are less than an entirety of the imagery. The computing system can provide the relevant portions of the imagery to a machine-learned convolutional neural network and receive at least one prediction from the machine-learned convolutional neural network based at least in part on the one or more relevant portions of the imagery. Thus, the computing system can skip performing convolutions over regions of the imagery where the imagery is sparse and/or regions of the imagery that are not relevant to the prediction being sought.

Abstract: In a satellite navigation system a navigation terminal continuously receives navigation signals from navigation satellites and continuously implements navigation calculations, thereby obtaining navigation calculation results, and executes in parallel: using clock offset values determined through the navigation calculations, calculates, in real time, changes in difference between time differences with regard to difference between time differences, which are differences between a clock offset value and a standard deviation value, which is the value of the standard deviation of fluctuation amounts of the clock offset values; determines, in real time, two navigation precision indices of the calculated navigation calculation results on the basis of each change in the calculated difference between time differences and standard deviation value; associates, in real time, the determined two navigation precision indices with the calculated navigation calculation results; and outputs, in real time, the navigation calcul

Abstract: A seat assembly includes a seat having a seat base and a seat back, an electronic control unit (ECU), a sensor assembly, and/or a response assembly. The ECU may be configured to determine via the sensor assembly whether an occupant disposed in the seat is in a first state, a second state, or a third state. The ECU may be configured to control the response assembly to change the state of said occupant from the first state to the second state and from the third state to the second state. The ECU may be configured to determine at least one of a breathing rate, a heart rate, and a heart rate variability of said occupant via the sensor assembly.

Abstract: In one embodiment, an intelligent and prompt alarm system is designed on autonomous driving vehicles to help autonomous driving vehicles to communicate to human drivers more vigilantly and promptly, and to improve human driver's performance to take over when an autonomous driving failure occurs. In one embodiment, an alarm system can be developed several levels: 1) basic warning, 2) risk warning, and 3) emergency/take-over alarming.

Abstract: A method includes: determining, by a computer device, conditions along a predefined driving route of a vehicle; determining, by the computer device and based on the conditions, risk factors of segments of the driving route; determining, by the computer device, an optimal one of the segments for switching the vehicle from autonomous driving mode to manual driving mode; and outputting, by the computer device, data defining the determined optimal one of the segments.

Abstract: A computer-readable medium storing instructions that, when executed by a computer in a vehicle, cause the computer to carry out a method for determining an energy-optimal path for the vehicle from an initial location to a final location, the vehicle corresponding to a vehicle energy model. Based at least on the initial location, an initial time, the final location, the vehicle energy model, and an environmental forecast a global path is generated. The global path includes a final maximum net energy path and a plurality of waypoints. Based on the global path a local path from the present location to a next waypoint of the plurality of waypoints is generated. Whether a net energy gain is generated by a deviation from the global path to the next waypoint of the plurality of waypoints is determined. Generating a local path is repeated until the vehicle reaches the final location.