Abstract: A method for parking brake adaptable assistance on a vehicle, the vehicle comprising a parking brake and a set of sensors, and at least one electronic control unit controlling the parking brake and the set of sensors, each sensor being monitored by the at least one control unit to measure a specific parameter, and a set of actuators, each actuator being activated by the at least one electronic control unit to engage a specific action or reminder, characterized in that the method comprises a first list (102) of situations defined by a set of valued parameters measured by the sensors, and a second list (101) of parking brake actions or reminders, and a list of relations (103) establishing a relation between each situation of the first list and an action or reminder from the second list and further comprising the following steps: i. determine the values of the parameters measured by the sensors; ii. determine the situation defined by the set of values determined at step i. iii.

Abstract: A method, system and non-transitory computer readable medium which monitor a road user in order to move the external position of the vehicle intent notification (eHMI) to another external position that can be seen by the road user based on the gaze direction of the road user. In some aspects, the eHMI notification displays the vehicle intent for a single autonomous vehicle. In another aspect, a group eHMI notification displays the trajectories for a plurality of autonomous and non-autonomous vehicles. Based on the gaze direction of the road user, the eHMI notification can be displayed on a single external position or on multiple external positions. Different eHMI notifications can be displayed at different external positions on the autonomous vehicle to provide information to more than one road user.

Abstract: An algorithm formulating system for use with a sensing ecosystem for identifying enterprise space states, the sensing ecosystem including a plurality of sensor devices mounted within an enterprise space wherein each sensor device is capable of sensing a plurality of parameters within the enterprise space, the system comprising a processor programmed to perform the steps of accessing a rule set that specifies a first parameter value set that corresponding to a perceived state within a first enterprise space, receiving sensor data from sensor devices within the first enterprise space, comparing the sensor data to the rule set to identify instances of the perceived state, examining sensor data to identify a second parameter value set that occurs at least a threshold percentage of time for the identified instances of the perceived state and using the second parameter value set as the basis for a new rule set to be associated with the perceived state.

Abstract: Systems and methods are described herein for managing communications for a connected vehicle, such as between the connected vehicle and other connected vehicle and/or between the connected vehicle and infrastructure entities, such as providers of services to the connected vehicle. For example, a communication network, such as a network provided by a network carrier, may include various cloud engines or other network-based servers that manage, coordinate, and/or provision communications between the connected vehicle and other parties, such as vehicles, road devices, buildings, and other infrastructure entities.

Abstract: A method for estimating a future fall of a cargo, the method may include receiving by a computerized system, sensed information related to driving sessions of multiple vehicles; applying a machine learning process on the sensed information to detect actual or estimated cargo falling events and generate one or more future falling cargo predictors for multiple types of cargo; estimating, from the sensed information, an impact of cargo falling events related to at least some of the types of cargo; and responding to the estimating, wherein the responding comprises at least one out of (a) storing the one or more future falling cargo predictors for the multiple types of cargo, (b) transmitting the one or more future falling cargo predictors for the multiple types of cargo; (c) storing the estimated impact of cargo falling events related to the at least some of the types of cargo, and (d) transmitting the impact of cargo falling events related to the at least some of the types of cargo.

Abstract: A vehicle control apparatus comprising, a center of gravity six-component calculation unit for calculating a center of gravity six-component as vehicle motion targets based on a driver input, a tire three-component calculation unit for calculating a tire three-component of four wheels of a vehicle based on the center of gravity six-component, a vehicle control unit for performing vehicle control by the vehicle control, actuator group based on the tire three-component of the four wheels, and wherein the tire three-component calculation unit calculates the tire three-component of the four wheels from the center of gravity six-component by a coordinate transformation without repetition, which is normalization with the driving stiffness of each wheel and the cornering stiffness of each wheel, when the number of control requests in the vehicle control is less than degrees of freedom of the vehicle control actuator group.

Abstract: A travel route determination system including: a route generating unit generating planned travel routes including work routes along which a work vehicle performs autonomous travel; a control unit capable of causing the work vehicle to perform autonomous travel along the planned travel routes; an information obtaining unit obtaining position information and orientation information on the work vehicle; and a determination unit determining an autonomous travel candidate route at which the work vehicle can start autonomous travel, before the work vehicle starts autonomous travel. The determination unit sets a candidate determination region based on the position information and orientation information on the work vehicle, and the determination unit determines, among the work routes, a work route in the candidate determination region as the autonomous travel candidate route.

Abstract: Systems, methods, and computer-readable media are provided for receiving first data from a first sensor utilizing a first communication protocol, wherein the first sensor is positioned in an aggregation zone, receiving second data from a second sensor utilizing a second communication protocol, wherein the second sensor is positioned in the aggregation zone, processing the first data received from the first sensor and the second data received from the second sensor to conform the first communication protocol and the second communication protocol, and providing instructions based on the processed first data and the processed second data in a third communication protocol, wherein the instructions adjust auxiliary functions of an autonomous vehicle.

Abstract: The present teaching relates to different configurations for facilitating calibration of multiple sensors of different types. A plurality of fiducial markers are arranged in space for simultaneously calibrating multiple sensors of different types. Each of the plurality of fiducial markers has a feature point thereon and is provided to enable the multiple sensors to calibrate by detecting the features points and estimating their corresponding 3D coordinates with respect to respective coordinate systems of the multiple sensors.

Abstract: In one embodiment, an ADV is routed by executing a first driving scenario that is active. The first driving scenario is one of a plurality of driving scenario types, each driving scenario type being associated with one or more stages to be executed while a corresponding driving scenario type is active. Based on an environmental condition around the ADV, a second driving scenario is set as active. The ADV is routed by executing the second driving scenario. When the second driving scenario exits, execution of the first driving scenario resumes at the one or more stages of the first driving scenario that remains to be executed.

Abstract: Using a read sensor to sense wrong-way driving. A method may include sensing, by a rear sensor of a vehicle, an environment of the vehicle to provide rear sensed information; processing the rear sensed information to provide at least one rear-sensed vehicle progress direction indications; generating or receiving at least one front-sensed vehicle progress direction indications; wherein the at least one front-sensed vehicle progress direction indications is generated by processing front-sensed information acquired during right-way progress; comparing at least one rear-sensed vehicle progress direction indications to the at least one front-sensed vehicle progress direction indications to determine whether the vehicle is wrong-way driving; and responding to the finding of the wrong-way driving.

Abstract: In one embodiment, a method for synchronizing sensor data of an autonomous driving vehicle includes determining, by a processing device of an inertial navigation system (INS), that global navigation satellite system (GNSS) data is unavailable and identifying an alternative source of time information. The method further includes retrieving time information from the alternative source and synchronizing sensor data with the time information from the alternative source of time information.

Abstract: In some examples, a moisture-proof mat is provided for an intelligent cleaning apparatus or an intelligent cleaning system. The intelligent cleaning apparatus is provided with a wet cleaning pad. The intelligent cleaning apparatus can be charged by a charging station. The moisture-proof mat may include an installation unit, configured to install the moisture-proof mat to the charging station. At least a portion of the moisture-proof mat is configured to be located under the wet cleaning pad (4) when the intelligent cleaning apparatus is charged by the charging station. When the intelligent cleaning apparatus is charged by the charging station, at least a portion of the moisture-proof mat is positioned under the intelligent cleaning apparatus.

Abstract: A method for controlling a vehicle platoon includes determining whether a vehicle platoon is capable of safely passing through a weight-limited road section, generating segment information of the vehicle platoon when the vehicle platoon is incapable of safely passing through the weight-limited road section, and sending this information to a lead vehicle in the vehicle platoon. The lead vehicle can then segment the vehicle platoon based on the segment information.

Abstract: Location data is obtained in which an arrival link from which a vehicle can enter a location serving as a destination and an arrival link direction are associated with the location, the arrival link direction indicating a direction in which the vehicle can enter upon entering the location from the arrival link. A cost related to the arrival link is corrected based on the obtained location data. A route to the destination is searched for, using the corrected cost related to the arrival link.

Abstract: An advance driver brake customizing method applied to a brake customizing system is provided to identically implement a braking feeling set according to a driver's vehicle regardless of a vehicle type by transplanting driver braking feeling information of a driver's vehicle into a braking feeling matching vehicle. A braking characteristic of a brake of a brake system, which is applied to the braking feeling matching vehicle, is directed to follow the braking characteristic of a brake of the brake system, which is applied to the braking feeling matching vehicle, through driver matching control in conjunction with a wireless network. In particular, even when the same driver changes a vehicle or a driver for the same vehicle is changed, the same braking feeling is maintained.

Abstract: A robot climbing control method is disclosed. A gravity direction vector in a gravity direction in a camera coordinate system of a robot is obtained. A stair edge of stairs in a scene image is obtained and an edge direction vector of the stair edge in the camera coordinate system is determined. A position parameter of the robot relative to the stairs is determined according to the gravity direction vector and the edge direction vector. Poses of the robot are adjusted according to the position parameter to control the robot to climb the stairs.

Abstract: Provided are methods for augmenting data related to generation of vehicle trajectories, which include predicting, using a machine learning model, a first trajectory of a vehicle at a first time in an environment surrounding the vehicle and including at least one object, detecting a deviation of the predicted first trajectory at the first time from a first ground truth trajectory of the vehicle and determining that, at the first time, the deviation satisfies a threshold, predicting, using the machine learning model, a second trajectory of the vehicle based on the predicted first trajectory of the vehicle and a second ground truth trajectory of at least one object at a second time being subsequent to the first time, and generating a training dataset for training the machine learning model using the predicted first and second trajectories of the vehicle. Systems and computer program products are also provided.

Abstract: A computer implemented method for generating traffic pathways that includes recording images from a transportation site with a fixed position camera. The method further includes extracting vehicle point data from the images, and calculating projected vehicle characteristics from the extracted point data to provide an extracted vehicle continuous data set. The method may further include generating a simulated traffic flow and simulated vehicle motion from the extracted vehicle continuous data set. A traffic pathway can be calculated using simulated vehicle motion and simulated traffic flow. The traffic pathway can be used for directing a guided vehicle on the transportation site.

Abstract: An autonomous vehicle is described, wherein the autonomous vehicle is configured to estimate a change in direction of a vehicle that is on a roadway and is proximate to the autonomous vehicle. The autonomous vehicle has a mechanical system, one or more sensors that generate one or more sensor signals, and a computing system in communication with the mechanical system and the one or more sensors. The autonomous vehicle is configured to detect an imminent lane change by another vehicle based on at least one of a computed angle between a wheel of the other vehicle and a longitudinal direction of travel of the other vehicle, a degree of misalignment between the wheel of the other vehicle and a body of the other vehicle, and/or an eccentricity of the wheel of the other vehicle. The mechanical system of the autonomous vehicle is controlled by the computing system based upon the detected imminent lane change.