Abstract: According to one embodiment, in response to a request for a three-point turn, a set of forward turning paths is generated based on a maximum forward turning angle associated with an ADV. A set of backward tuning paths is generated based on a maximum backward turning angle associated with the ADV. A set of three-point turn path candidates is generated based on the forward turning paths and the backward turning paths. For each of the three-point turn path candidates, a path cost is calculated using a predetermined cost function. One of the three-point turn path candidates with the lowest path cost is selected as the final three-point turn path to drive the ADV to make a three-point turn.

Abstract: In one embodiment, in response to a request to make a three-point turn for an autonomous driving vehicle (ADV), a forward turning path is generated using a first spiral function based on a maximum forward curvature change rate. A backward turning path is generated using a second spiral function based on a maximum backward curvature change rate. The forward and backward curvature change rates may be determined based on the maximum forward and backward turning angles associated with the ADV, which may be specified as a part of vehicle specification or vehicle design of the ADV. The backward turning path is initiated from an end point of the forward turning path. A three-point turn path is then generated based on the forward turning path and the backward turning path. The ADV is then driven according to the three-point turn path by issuing one or more proper control commands.

Abstract: This application discloses a video sequence selection method, applicable to a computer device, the method including: receiving a to-be-matched video and a to-be-matched text, the to-be-matched text having a to-be-matched text feature sequence; invoking a spatiotemporal candidate region generator to extract a spatiotemporal candidate region set from the to-be-matched video, the spatiotemporal candidate region set including N spatiotemporal candidate regions; performing feature extraction on each spatiotemporal candidate region by using a convolutional neural network, to obtain N to-be-matched video feature sequences; invoking an attention-based interactor to obtain a matching score corresponding to each spatiotemporal candidate region, the matching score being used for representing a matching relationship between the spatiotemporal candidate region and the to-be-matched text; and selecting a target spatiotemporal candidate region from the spatiotemporal candidate region set according to the matching score corr

Abstract: According to some embodiments, a system receives a captured image perceiving an environment of an ADV from an image capturing device of the ADV. The system identifies an obstacle in motion near the ADV based on the captured image. The system predicts a location for the moving obstacle at each of a number of time points. The system generates a probability ellipse based on the predicted location at the each time point, where the probability ellipse includes a probability indicator indicating different probabilities of the moving obstacle for different locations within the probability ellipse at the each time point.

Abstract: The application relates to the field of lithium ion battery technology and, more particularly, relates to a lithium-supplement layer and its negative electrode sheet, a lithium ion battery and a device. The lithium-supplement layer is formed by connecting a transition layer, an oxide layer and a surface layer in sequence, the surface layer contains an appropriate amount of an organic material and a filling substance, which can reduce a winding temperature of the negative electrode sheet, the oxide layer substance in the lithium-supplement layer is used to provide an additional lithium source, after injection, the lithium source can be continuously supplemented during the cycle process to improve the activity of a lithium layer, at the same time, the filling substance contained in the surface layer can effectively play a role of restraining the expansion of an active substance, and improve the battery cycle performance.

Abstract: A method and an apparatus for environmentally-friendly batch hot-dip coating of high-performance alloy are provided. The method is that workpiece is heated to the process temperature in the heating box with inner gas before galvanizing. The heating box body consist of two or three zones, which are waiting zone, heating zone and post-plating turnover zone (the post-plating turnover zone can be omitted). A zinc pot is arranged in the heating zone, and the zinc pot is configured for hot-dip coating. Workpieces can be processed with zinc or zinc-based alloys. A transporting device is configured to successively transport in a sealed state the workpiece to be processed to the waiting zone, the heating zone, the zinc pot, and the post-plating turnover zone (the post-plating turnover zone can be omitted). The new method realizes hot-dip coating with zinc and other zinc-based alloys without the use of the flux.

Abstract: A method and apparatus for outputting three-dimensional (3D) lines. The apparatus acquires a first image and a second image including lines on a road, generates, based on a first feature map acquired from the first image, a line probability map representing a probability that a pixel point of the first feature map belongs to the lines, calculates matching information of the first image and the second image based on the first feature map and a second feature map acquired from the second image, predicts depth values of the lines using the line probability map and the matching information, detects the lines based on the line probability map, generates 3D lines based on the detected lines and the depth values of the lines, and outputs the 3D lines.

Abstract: In one embodiment, described herein is a system and method for filtering obstacles to reduce the number of obstacles for an autonomous driving vehicle (ADV) to process in a given planning phase. The ADV can identify a first set of obstacles based on a set of criteria in a first lane where the ADV is travelling, filter out the remaining obstacles in the first lane, and expand each identified obstacle to a width of the first lane from the view of the ADV so that the ADV cannot nudge any of the first set of identified obstacles. When switching from the first lane to a second lane, the ADV can identify a second set of obstacles in the second lane using the same set of criteria, and expand each obstacle in the second set of obstacles to a width of the second lane while keep tracking the first set of identified obstacles. When the lane switching is completed, the ADV can stop tracking the first set of identified obstacles.

Abstract: An ADV perceives a driving environment surrounding the ADV based on sensor data obtained from a variety of sensors mounted on the ADV including, for example, perceiving and recognizing a corner the ADV may be about to turn. Based on the perception data of the driving environment, a set of features representing the characteristics of an entrance point of a corner that the ADV is about to turn. Based on the characteristics of the corner, an entrance point of the corner is determined. Based on the entrance point, a lookup operation is performed in a corner mapping table to locate a mapping entry matching the entrance point. A turning radius is then obtained from the mapping entry of the corner mapping table. The turning radius obtained from the corner mapping table is then utilized to plan a trajectory (e.g., steering angle) to drive the ADV to turn the corner.

Abstract: The disclosure describes various embodiments for monitoring safety of an autonomous driving vehicle (ADV. In one embodiment, a method includes the operations of receiving, by a vehicle controller, one or more error message from a patrol module, the one or more error messages generated by an autonomous driving system of the ADV operating in an autonomous mode, the patrol module monitoring the autonomous driving system; evaluating a status of the autonomous driving system based on the one or more error messages; and keeping the ADV in the autonomous mode or switching it to a manual mode based on the status of the autonomous driving system.

Abstract: A computer-implemented method, apparatus, and system for receiving and calibrating lateral deviation values and for controlling an autonomous vehicle to correct the lateral deviation is described. In every perception and planning cycle, a single lateral deviation value representative of an estimated autonomous vehicle lateral deviation from a reference line (e.g., corresponding to a center of the lane) is generated based on camera detection. The deviation value for a present cycle is received. A calibrated deviation value can be updated for the present cycle based on the received deviation value and a Gaussian distribution model. Control signals for the present cycle are generated to drive the autonomous vehicle to at least partially correct the autonomous vehicle lateral deviation based on the updated calibrated deviation value.

Abstract: In one embodiment, a path for parking is planned in operating an autonomous driving vehicle (ADV). The operations comprises: determining a plurality of sample points; determining a plurality of candidate paths connecting a start point and an end point for parking, each of the candidate paths passing through one of the sample points; determining a cost associated with each of the plurality of candidate paths; determining one or more candidate paths from the plurality of candidate paths that meet a boundary check requirement; selecting as the planned path a candidate path associated with a lowest cost that meets the boundary check requirement; determining a speed profile based on the planned path and an environment of the ADV; and generating driving signals based at least in part on the speed profile to control operations of the ADV to perform parking along the planned path.

Abstract: In one embodiment, an autonomous driving system perceives a driving environment surrounding an ADV based on sensor data obtained from various sensors, including identifying one or more objects. For each of the objects, an arc curve is generated connecting the object and a current location of the ADV using a predetermined algorithm. A curvature of the arc curve is calculated. One of the arc curves is selected in which the curvature of the selected arc curve satisfies a predetermined condition, such as the lowest curvature amongst all objects. A reference line is then generated by connecting the selected object and the current location of the ADV. The connected line between the selected object and the ADV is utilized as a part of a reference line. The reference line is utilized to generate a trajectory to drive the ADV.

Abstract: Various embodiments of the invention enable an ADV to dynamically adjust its behaviors to emulate behaviors of a vehicle operated by a human driver when the ADV encounters an obstacle. A dynamic cost function can be used to collect real-time values of a set of parameters, and use the real-time values to constantly adjust a preferred safety distance where the ADV can be stopped ahead of the obstacle. An method includes determining a first distance to the obstacle in response to detecting an obstacle ahead of the ADV; and for each of a number of iterations, collecting a real-time value for each of a set of parameters, determining an offset to the first distance using the real-time value for each of the set of parameters, calculating a second distance based on the first distance and the offset, and controlling the ADV in view of the second distance using an expected value of each of the set of parameters, such that the ADV can stop at a point having the second distance to the obstacle.

Abstract: A computer-implemented method, apparatus, and system for discretizing lane markings and for generating a lane reference line is disclosed. A polynomial defined over an (x,y) coordinate system is received, the polynomial being representative of at least a portion of a lane boundary line. A length of the polynomial is determined. The polynomial is discretized, comprising determining a plurality of discretization points on the polynomial to represent the polynomial, wherein a first discretization point is a first end of the polynomial, wherein subsequent discretization points are determined successively until the polynomial is completely discretized, and wherein each discretization point other than the first discretization point is determined based at least in part on a slope of the polynomial at a previous discretization point. Thereafter, a lane reference line comprising a plurality of points is generated based on the discretized polynomial.

Abstract: In one embodiment, an exemplary method includes the operations of receiving a raw reference line representing a route from a first location to a second location associated with an autonomous driving vehicle (ADV); and smoothing the raw reference line using a Quadratic programming (QP) spline smoother to generate a smoothed reference line. The method further includes the operations of identifying one or more segments on the smoothed reference line, each of the identified reference line segments including a curvature that exceeds a predetermined size; and smoothing each of the one or more identified reference line segments using a spiral smoother, including optimizing each identified curvature in view of a set of constraints, such that an output of the objective function reaches a minimum value while the set of constraints are satisfied; and controlling the ADV using the smoothed reference line.

Abstract: A calibration table usable in operating an autonomous driving vehicle (ADV) is updated. The operations comprise: determining a first torque value at a first time instant prior to executing a control command; determining a control command based on a speed of the ADV, a desired acceleration, and an associated entry in the calibration table; executing the control command; determining a second torque value at a second time instant subsequent to executing the control command; determining a torque error value as a difference between the first and second torque values; updating the associated entry in the calibration table based at least in part on the torque error value; and generating driving signals based at least in part on the updated calibration table to control operations of the ADV.

Abstract: Based on sensor data obtained from a variety of sensors, a driving environment surrounding an autonomous driving vehicle (ADV) is perceived, including perceiving and identifying one or more obstacles. A trajectory is planned based on the perception data according to a set of rules to drive the ADV navigating through the driving environment. Trajectory data representing the trajectory is generated, where the trajectory data includes information indicating target or expected vehicle states at different points in time along the trajectory. The trajectory data is then transmitted in a sequence or a stream of one or more controller area network (CAN) messages to an electronic control unit (ECU) of the ADV over a CAN bus. The ECU is configured to generate and issue one or more control commands (e.g., throttle, brake, steering commands) based on the trajectory data to drive the ADV according to the trajectory.

Abstract: A three-point-turn is planned and executed in the operation of an autonomous driving vehicle (ADV). A candidate route from a start point and going through an end point is determined, the start point and the end point being in lanes associated with opposite travel directions. The candidate route is categorized into partially overlapping first, second, and third segments. A total cost associated with the candidate route is determined based at least in part on the first and second segments. Whether the total cost is below a threshold cost is determined. In response to a determination that the total cost is below the threshold cost, the three-point-turn is planned based on the candidate route. Further, driving signals are generated based at least in part on the planned three-point-turn to control operations of the ADV.

Abstract: In one embodiment, a method for generating a reference line for operating an autonomous driving vehicle includes determining a first ending reference point having a smallest curvature among a plurality of points within a first defined distance along a path, generating a first reference line based on a first initial reference point and the first ending reference point, determining a second ending reference point having a smallest curvature among a plurality of points within a second defined distance along the path, generating a second reference line based on the first and second ending reference points and an end section of the first reference line, connecting the first and second reference lines, and controlling the autonomous driving vehicle along the connected first reference line and the second reference line.