Abstract: A driving mode control method, apparatus, device, program and storage medium, which relates to the technical field of electronic control, and is for a control platform, the method includes: acquiring a location information sent by a target vehicle, wherein the location information comprises a target location; determining a status data of at least one sample vehicle pre-stored by the control platform based on the target location, wherein the sample vehicle is a vehicle which has travelled through the target location; determining a target driving mode based on the status data of the sample vehicle, and sending the target driving mode to the target vehicle, such that the target vehicle travels in the target driving mode. This disclosure enables the target vehicle to travel in the target driving mode. The driver needs not to manually switch the driving mode, and the accuracy and convenience of controlling the drive mode are improved.

Abstract: An automated driving system includes a security companion subsystem to access data generated at a compute subsystem of the automated driving system, which indicates a determination by the compute subsystem associated with an automated driving task. The security companion subsystem determines whether the determination is safe based on the data. The security companion subsystem is configured to realize a higher safety integrity level than the compute subsystem.

Abstract: Scheduling state transitions in an autonomous vehicle, including: detecting a transition signal for transitioning from a first state associated with a first machine learning model to a second state associated with a second machine learning model; determining whether a precondition for generating output by the second machine learning model has been satisfied; and delaying, in response for the precondition not being satisfied, a transition from the first state to the second state.

Abstract: From a set of point data, a set of scattered rays is constructed. From the set of scattered rays, a set of ray slopes is computed. The set of ray slopes is mapped to a corresponding set of trigonometric functions. Using an optimization method, a parameter of the set of trigonometric functions is selected. Using an inverse of the set trigonometric functions, a vehicle mass corresponding to the set of point data is computed. Based on the vehicle mass, a threshold braking distance of a collision avoidance system of the vehicle is adjusted, the threshold braking distance comprising a distance from an object predicted to collide with the vehicle. By braking the vehicle at least the threshold braking distance from the object, a predicted collision between the vehicle and the object is avoided.

Abstract: An unmanned vehicle control method includes acquiring a delivery request for an item, the delivery request comprising delivery information of the item, and determining, according to the delivery information, predicted travelling data associated with delivering the item and at least one of network coverage or network connection quality associated with the predicted travelling data. The method further includes allocating network resources according to the at least one of the network coverage or the network connection quality of the predicted travelling data, and generating a remote driving control instruction according to the predicted travelling data. The method further includes transmitting the remote driving control instruction to an unmanned vehicle using the allocated network resources, so as to cause the unmanned vehicle to drive based on the remote driving control instruction, the unmanned vehicle being configured to transport the item.

Abstract: Systems and methods of manipulating/controlling robots. In many scenarios, data collected by a sensor (connected to a robot) may not have very high precision (e.g., a regular commercial/inexpensive sensor) or may be subjected to dynamic environmental changes. Thus, the data collected by the sensor may not indicate the parameter captured by the sensor with high accuracy. The present robotic control system is directed at such scenarios. In some embodiments, the disclosed embodiments can be used for computing a sliding velocity limit boundary for a spatial controller. In some embodiments, the disclosed embodiments can be used for teleoperation of a vehicle located in the field of view of a camera.

Abstract: A vehicle includes a vehicle body and an optical sensor supported by the vehicle body and defining a field-of-view. The vehicle includes a transparent shield in the field-of-view, the transparent shield having an outer surface. The vehicle includes a camera facing the outer surface of the transparent shield.

Abstract: A method and system controller includes determining a power requirement for a vehicle system to complete a planned trip over a route. The method includes determining whether an amount of available power from the vehicle system is sufficient to propel the vehicle system to complete the planned trip by comparing the available power with the power requirement that is determined. The method includes changing one or more operational aspects of the planned trip based on the comparison between the amount of available power and the power requirement that is determined to generate a newly planned modified trip.

Abstract: System, methods, and other embodiments described herein relate to communicating a recommended speed through feedback on a combined pedal for acceleration or braking. In one embodiment, a control system includes a pedal coupled to a first device having a throttle sensor for a vehicle and a first actuator that generates throttle feedback by applying force to the pedal. The control system also includes the pedal being coupled to a second device having a brake activation sensor for the vehicle and a second actuator that generates braking feedback, the first actuator triggers a rotation of the pedal that initiates a braking command through the brake activation sensor according to a recommended speed computed using vehicle data.

Abstract: The disclosure includes embodiments re-identification and revocation for misbehaving vehicle detection. A misbehaving vehicle is an example of an anomaly. A method includes receiving from a vehicular micro cloud, by a connected vehicle that is a member of the vehicular micro cloud, vehicular micro cloud data describing an anomaly and a first state of the anomaly in a geographic area. The method includes causing a sensor to record sensor data describing the geographic area. The method includes determining, based on the sensor data and the vehicular micro cloud data, whether the anomaly is still present and in the first state. The method includes generating evidence data describing a second state of the anomaly. The method includes transmitting the evidence data to the vehicular micro cloud. The method includes modifying an operation of the connected vehicle based on the evidence data.

Abstract: A system described herein may provide a technique for a determination of a path through a node map using one or more searches. The nodes may be associated with respective priorities. A first search may be performed from a first node in ascending order of priority. A second search may be performed from a second node in ascending order of priority, until a third node, traversed during the first search is reached. A third search may be performed from the third node, in descending order of priority, until the first node is reached. The third search may be restricted only to nodes traversed during the first search. A path that is based on the second and third searches may be provided in response to a navigation request from a starting point associated with the second node to a destination associated with the first node.

Abstract: A navigation ECU executes processing including the following steps. The steps include: a step of acquiring information on travel sections to destination; a step of setting a starting point travel section and an nth travel section; a step of setting an n+1th travel section as an nth travel section when the starting point travel section and the nth travel section are identical in regulation information and road type, and difference in load is equal to or less than a threshold A; and a step of integrating the travel sections from the starting point travel section to an n?1th travel section when the starting point travel section and the nth travel section are not identical in regulation information and road type, and the difference in load is greater than the threshold A.

Abstract: A vehicle control device includes: a recognition part recognizing a first road marking line on a first side of a lane traveled by a vehicle; an obtaining part obtaining information on a second road marking line on the first side of the lane from map information; and a support part that executes a support processing for preventing the vehicle from deviating from a road marking line when a probability that the vehicle deviates from the road marking line is greater than or equal to a predetermined degree. When a degree of matching between a first position of the first road marking line and a second position of the second road marking line is less than or equal to a first threshold value, the support part suppresses execution of the support processing for preventing the vehicle from deviating from a road marking line on the first side.

Abstract: A flight route information acquisition module acquires flight route information indicating a flight route of an unmanned aerial vehicle in a real space. A real space position/direction identifier identifies a visually recognized position and a visually recognized direction in the real space. A flight route image generator generates a flight route image representing the flight route viewed from the visually recognized position in the visually recognized direction based on the flight route information. A display controller displays the flight route image under a state in which a position of the flight route image is matched with a situation viewed from the visually recognized position in the visually recognized direction in the real space on a display.

Abstract: This technology provides designs and methods for the vehicle on-board unit (OBU), which facilitates vehicle operations and control for connected automated vehicle highway (CAVH) systems. OBU systems provide vehicles with individually customized information and real-time control instructions for vehicle to fulfill the driving tasks such as car following, lane changing, route guidance. OBU systems also realize transportation operations and management services for both freeways and urban arterials. The OBU composed of the following devices: 1) a vehicle motion state parameter and environment parameter collection unit; 2) a multi-mode communication unit; 3) a location unit; 4) an intelligent gateway unit, and 5) a vehicle motion control unit. The OBU systems realize one or more of the following function categories: sensing, transportation behavior prediction and management, planning and decision making, and vehicle control.

Abstract: The disclosed systems can regulate access to an online mode for a dynamic transportation matching system. For example, based on a provider efficiency parameter associated with the dynamic transportation matching system, the disclosed systems can prevent a transportation provider device from switching to the online mode within a geographic area. In addition, the disclosed systems can detect a pattern of behavior and, based on a comparison between the pattern of behavior and a behavioral threshold, cause a transportation provider device to switch from the online mode to an offline mode. Further, the disclosed systems can provide a map interface that indicates where a transportation provider device can switch from the offline mode to the online mode. Additionally, the disclosed systems can determine priorities associated with transportation provider devices and, based on the prioritization, selectively allow the transportation provider devices to switch from the offline mode to the online mode.

Abstract: A method in a data processing system including at least one processor and at least one memory including instructions executed by the at least one processor to implement a lane change system is provided by the present disclosure. The method includes receiving, from at least one of a plurality of sensors coupled to a vehicle, information associated with a location of an object longitudinally ahead of the vehicle, determining a sequence of control inputs associated with a time horizon to avoid a collision between the vehicle and the object based on a constraint and the location of the object, and the determining the sequence of control inputs including minimizing a maximum tire slip angle of the vehicle during the time horizon subject to the constraint, and causing a vehicle control system of the vehicle to perform a vehicle maneuver based on the sequence of control inputs.

Abstract: The present invention relates to a method for operating a driver model for controlling a vehicle. The driver model comprises a vehicle module (203) which determines an accelerator pedal position to be set on the vehicle. In addition, the vehicle module (203) determines a required power as a component of a total power, which total power can be generated by a drive system of the vehicle, wherein the required power corresponds to a power that is necessary for moving the vehicle at a required speed and/or a required acceleration (311) along a predefined road course. The method according to the invention further provides for a value (313) of a permissible pedal position to be assigned to the required power and for the value (313) of the permissible pedal position to be transmitted to the driver model in order to control the vehicle.

Abstract: A method and system for determining risk indicators for intersections. A method includes receiving, by a computing node from intersection proximate sensors at each intersection, intersection data. For each intersection, the method includes determining, by the computing node for each connected vehicle proximate to an intersection, a driver risk score based on driver distraction data from the intersection data for the intersection, determining, by the computing node, a near miss score based on the intersection data for the intersection, and assigning, by the computing node for the intersection, an intersection risk indicator level based on an exponential moving average of intersection risk indicator scores determined from driver risk scores and near miss scores. The method includes providing, by the computing node, intersection risk indicator levels to each connected vehicle to facilitate control decisions by each connected vehicle when approaching intersections.

Abstract: An information providing system includes: first servers in which each first server including a first processor with hardware is provided for each of a plurality of bases. The first processor is configured to calculate a traffic frequency of a vehicle on a road link included in a road map based on past travel data of the vehicle, partition the road map into a plurality of areas so that a total of the traffic frequency in a road link straddling each partitioned area becomes minimum, allocate each base to each of the partitioned areas, and output predetermined information to the vehicle traveling in the partitioned area to which the base is allocated.