Abstract: A driving support apparatus includes a surrounding information acquisition device which acquires surrounding information, a steering information acquisition device which acquires steering information, a control unit which executes driving support control including at least one of pre-right/left-turn deceleration assist control or pre-right/left-turn warning control when a predetermined first execution condition is satisfied. When a precondition which is satisfied in a case in which an intersection is detected based on the surrounding information and steering operation is being performed by a driver based on the steering information is satisfied, the control unit determines whether or not the first execution condition is satisfied based on the steering operation being performed and traveling lane arrow information which is road arrow information of a traveling lane or adjacent lane arrow information which is road arrow information of an adjacent lane, both of which being stored in a storage device.

Abstract: A vehicle driving control system includes: an input device configured to receive LiDAR data and camera and/or radar data obtained for a region of interest around a host vehicle; a microprocessor configured to obtain information for localization on objects of interest by executing a first process for the LiDAR data and the camera and/or radar data and obtain information for driving path on the objects by executing a second process for the LiDAR data and the camera and/or radar data; and an output device configured to output the information for localization and the information for driving path.

Abstract: An e-bike interface is a hybrid wired/wireless e-bike control system that integrates wireless bicycle components into operation of an e-bike. The e-bike interface provides a frame-mounted control and display that is wired to, for example, an assist motor and a battery, and provides a wireless communication bridge between wireless bicycle components and corresponding wireless controls located on a handlebar.

Abstract: A feedback control processing for computing a feedback control input value for controlling the posture of a construction machine using the control gain, in which a control parameter adjustment processing includes: overshoot computation processing for computing an amount of overshoot of a posture detection value with respect to a target position in a previous control section; addition/subtraction rate computation processing for computing a control gain addition/subtraction rate, which is an addition/subtraction rate of the control gain in the next control section, based on the amount of overshoot; addition/subtraction rate smoothing processing for computing a post-smoothing addition/subtraction rate in which the control gain addition/subtraction rate is smoothed based on a post-smoothing addition-subtraction rate computed in the previous control section and the control gain addition/subtraction rate; and control gain computation processing for computing the control gain in the next control section from the pos

Abstract: An AMU system includes an Autonomous Mobile Unit (“AMU”), base station, lanyard, and Warehouse Management System (“WMS”) configured to communicate with one another over a network. The AMU includes a microphone configured to receive verbal commands from an individual. The individual can further provide verbal commands through the base station and the lanyard when worn by the individual. The lanyard can also provide a geo-fence around the individual where the AMU slows down to enhance safety.

Abstract: There is provided methods, systems, and computer-readable media for determining intention of bicycles and other person-wide vehicles. A method comprises: receiving, from one or more sensors of an autonomous vehicle, sensor data relating to an external environment of the autonomous vehicle; detecting, based at least in part on the sensor data, a person-wide vehicle in the external environment proximate to the autonomous vehicle; determining, based at least in part on the sensor data and the person-wide vehicle, image data including the person-wide vehicle; inputting the image data to a machine-learned model; receiving, from the machine-learned model based on the image data, a future intention of the person-wide vehicle; and controlling the autonomous vehicle based at least in part on the future intention of the person-wide vehicle.

Abstract: Aspects of the disclosure relate to controlling a vehicle having an autonomous driving mode. For instance, that the vehicle is approaching a crosswalk may be determined. A set of segments may be identified for the crosswalk. A set of potential occluded pedestrians may be generated. Each potential occluded pedestrian of the set is assigned a speed characteristic and a segment. The segments of the set of potential occluded pedestrians may be updated over time using the assigned speed characteristics. Sensor data from a perception system of the vehicle is received, and one or more potential occluded pedestrians an having an updated assigned segment corresponding to a segment that is visible to a perception system of the vehicle may be removed from the set of potential occluded pedestrians. After the removing, the set may be used to control the vehicle in the autonomous driving mode.

Abstract: An HCU is to be used in a vehicle including an autonomous driving operation, and includes a function of a presentation control device that controls presentation of information to a driver of the vehicle. The presentation control device determines interruption of a second task other than driving permitted to the driver in an autonomous traveling period where the vehicle travels by the autonomous driving operation. Based on the interruption determination of the second task, the HCU changes a provision method of content provided in association with the second task in the autonomous traveling period.

Abstract: A vehicle includes a battery, an electric machine, an electrical port, sensors, and a controller. The battery is configured to store electrical power. The electric machine is configured to receive electrical power from the battery to propel the vehicle. The electrical port is configured to receive an electrical connector of a charging station to initiate a charging operation of the battery. The sensors are configured to monitor an exterior of the vehicle. The controller is programmed to, in response to the sensors detecting an unidentified individual approaching the vehicle, eject the electrical connector from the electrical port or enable full operation of the vehicle.

Abstract: An example operation includes one or more of: detecting that a plurality of wireless devices are located in a vehicle; pairing a wireless device of the plurality of wireless devices and a head unit of the vehicle, when the wireless device is receiving or transmitting audio; and transmitting the audio through the head unit of the vehicle.

Abstract: A remote controller including an emergency stop button that receives an emergency stop operation, a temporary stop button that receives a temporary stop operation, and a control unit that restarts the running of a tractor when a running restart operation is performed after the tractor has been temporary stopped, the running restart operation including a pressing operation for pressing the temporary stop button continuously for a first predetermined time and a release operation for releasing the pressing operation on the temporary stop button within a second predetermined time following the first predetermined time.

Abstract: A system for routing a vehicle based on roadway characteristics includes a global navigation satellite system (GNSS) for determining a geographical location of the vehicle, a vehicle communication system for communicating with at least one external system, and a vehicle controller in electrical communication with the GNSS and the vehicle communication system. The vehicle controller is programmed to determine a vehicle length and a vehicle width, receive a navigation request from an occupant of the vehicle, and determine a navigation route using at least the GNSS and the vehicle communication system in response to receiving the navigation request, where the navigation route is based at least in part on the vehicle length and the vehicle width.

Abstract: A mobile charging apparatus is provided. The apparatus comprises a battery for charging a work machine; a movement unit that causes the mobile charging apparatus to autonomously move; and a controller that executes a program to perform control such that the movement unit moves the mobile charging apparatus to a predetermined position to wait for the work machine.

Abstract: The present disclosure relates to a method for a torque control of a hybrid vehicle, a storage medium and an electronic device. The method includes: determining a target-total-torque-change-gradient when a limitation requirement for a gradient of torque change of a DCT is received; determining a torque request of an electric motor and an actual-torque-response-change-gradient of an engine; and determining a gradient of torque change of the electric motor according to the target-total-torque-change-gradient and the actual-torque-response-change-gradient of the engine; and filtering the torque request of the electric motor according to the gradient of torque change of the electric motor. The limitation of the gradient of torque change of the DCT is considered, A problem that the actual total torque responses of the electric motor and the engine exceeds the limitation requirement of the gradient of torque change of the DCT is effectively solved, and a drivability of the whole vehicle is improved.

Abstract: Methods and systems are provided for improving a Driver Monitoring System (DMS) of a vehicle. The system includes a controller in operable communication with the DMS of the vehicle. The controller is configured to, by a processor: receive a signal from the DMS that a camera of the DMS is unable to monitor a driver of the vehicle, determine a cause of the camera being unable to monitor the driver, and adjust an escalation algorithm of the DMS based on the determined cause of the camera being unable to monitor the driver. The escalation algorithm is configured to perform actions based on activity of the driver.

Abstract: A method for calibrating extrinsic parameters (182) of a trailer camera (132d, 132e, 132f) supported by a trailer (106) attached to a tow vehicle (102). The method includes determining a three-dimensional feature map (162) from one or more vehicle images (133) received from a camera (132a, 132b, 132c) supported by the tow vehicle and identifying reference points (163) within the three-dimensional feature map. The method includes detecting the reference points within one or more trailer images received from the trailer camera after the vehicle and the trailer moved a predefined distance in the forward direction. The method also includes determining a trailer camera location (172) of the trailer camera (132d, 132e, 132f) relative to the three-dimensional feature map (162) and determining a trailer reference point (184) based on the trailer camera location. The method also includes determining extrinsic parameters (182) of the trailer camera relative to the trailer reference point.

Abstract: The present teaching relates to method, system, medium, and implementations for sensor calibration. An ego vehicle determines whether a sensor deployed on the ego vehicle to facilitate autonomous driving of the ego vehicle needs to be calibrated and sends, if it is determined that the sensor needs to be calibrated, a request for assistance in collaborative calibration of the sensor, with a first position of the ego vehicle or a first configuration of the sensor with respect to the ego vehicle. When a response of the request is received, an assisting vehicle is indicated to travel to be near the ego vehicle to facilitate the calibration of the sensor by collaborating with the moving ego vehicle and the ego vehicle coordinates with the assisting vehicle to enable the sensor to acquire information of a target present on the assisting vehicle for the collaborative calibration of the sensor.

Abstract: Command determination for controlling a vehicle, such as an autonomous vehicle, is described. In an example, individual requests for controlling the vehicle relative to each of multiple objects or conditions in an environment are received (substantially simultaneously) and based on the request type and/or additional information associated with a request, command controllers can determine control commands (e.g., different accelerations, steering angles, steering rates, and the like) associated with each of the one or more requests. The command controllers may have different controller gains (which may be based on functions of distance, distance ratios, time to estimated collisions, etc.) for determining the controls and a control command may be determined based on the all such determined controls.

Abstract: Aspects of the present invention relate to control system (100) for controlling a transition of a vehicle between a first driving mode and a second driving mode. The control system comprises one or more controllers, configured to: receive (302) a first request signal indicative of an occupant-initiated preparatory request; receive (303) a second request signal indicative of an occupant-initiated transition request; determine (304) a first control signal for controlling output of information to an occupant of the vehicle indicative of the driving environment in dependence on receipt of the first request signal; determine (308) a second control signal for causing transition of the vehicle from the first driving mode to the second driving mode in dependence on receipt of both the first request signal and the second request signal; and output (306, 310) the first or second control signal to a vehicle system.

Abstract: Autonomous vehicle navigation is disclosed. A tangible computer readable medium includes instructions which, when executed cause a machine to divide an image of an area being approached by a lawn mower into a grid of separate image sections. Each of the image sections corresponds to a respective portion of the area being approached. For each of the image sections in the grid, the instructions, when executed, cause the machine to calculate, using an image recognition algorithm, a percentage of the image section categorized as corresponding with unmowable material and assign a result value based on a comparison between the calculated percentage and one or more movement thresholds. The instructions, when executed, also cause the machine to instruct a drive system to control movement of the lawn mower based on an arrangement of result values in the grid of the image sections.