Abstract: In one embodiment, a real time map can be generated by an autonomous driving vehicle (ADV) based on a navigation guideline for a lane and associated lane boundaries for the lane on a particular segment of a road. When travelling in the lane on the road segment, the ADV can use the navigation guideline as a reference line and use the lane boundaries as boundaries. The navigation guideline can be derived from manual driving path data collected by a manned vehicle that has travelled multiple times on the particular segment of the road.

Abstract: According to some embodiments, a system selects a number of polynomials representing a number of time segments of a time duration to complete the path trajectory. The system selects an objective function based on a number of cost functions to smooth speeds between the time segments. The system defines a set of constraints to the polynomials to at least ensure the polynomials are smoothly joined together. The system performs a quadratic programming (QP) optimization on the objective function in view of the set of constraints, such that a cost associated with the objective function reaches a minimum while the set of constraints are satisfied. The system generates a smooth speed for the time duration based on the optimized objective function to control the ADV autonomously.

Abstract: Embodiments of the present disclosure provide a communication method, a network side device, and a user terminal. The method includes: establishing, by a user terminal, a connection to a first base station by using a first component carrier; sending, by the first base station, a preprocessing indication message to the user terminal, to indicate that the user terminal is to perform uplink synchronization with a second base station on a second component carrier; and obtaining, by the first base station, a target second base station, and sending a first indication message to the target second base station, to indicate that the user terminal is to perform data transmission with the target second base station.

Abstract: According to some embodiments, a system determines a number of boundary areas having predetermined dimensions centered around each of a number of control points of a first reference line. The system selects a number of two-dimensional polynomials each representing a segment of an optimal reference line between adjacent control points. The system defines a set of constraints to the two-dimensional polynomials to at least ensure the two-dimensional polynomials passes through each of the boundary areas. The system performs a quadratic programming (QP) optimization on a target function such that a total cost of the target function reaches minimum while the set of constraints are satisfied. The system generates a second reference line representing the optimal reference line based on the QP optimization to control the ADV autonomously according to the second reference line.

Abstract: When generating a control command of an autonomous driving vehicle (ADV), a pitch status and/or a roll status of the road is determined. The control command is adjusted based on the pitch status and the roll status. For example, when an ADV is driving on an uphill or downhill road, a pitch status of the road is determined and a speed control command will be generated based on the pitch status of the road, such that the ADV have a similar acceleration rate as of driving on a flat road. Similarly, when the ADV is driving on a road that is tilted or rolled left or right, a roll status of the road is determined and a steering control command will be generated in view of the roll status of the road, such that the ADV have a similar heading direction as of driving on a flat road.

Abstract: According to some embodiments, a system segments a first path trajectory selected from an initial location of the ADV into a number of path segments, where each path segment is represented by a polynomial function. The system selects an objective function in view of the polynomial functions of the path segments for smoothing connections between the path segments. The system defines a set of constraints to the polynomial functions based on adjacent path segments in view of at least a road boundary and an obstacle perceived by the ADV. The system performs a quadratic programming (QP) optimization on the objective function in view of the added constraints, such that an output of the objective function reaches a minimum. The system generates a second path trajectory representing a path trajectory with an optimized objective function based on the QP optimization to control the ADV autonomously.

Abstract: In one embodiment, one or more first data items associated with a planned trip of a user riding in an autonomous driving vehicle (ADV) are displayed on a display device within the ADV. Each of the first data items is associated with a user selectable option to indicate whether the user wishes or allows the ADV to store each of the first data items in a persistent storage device. User inputs are received via a user interface such as touch screen of the display device, including a first selection indicating that the user wishes to store a first subset of the first data items. In response to the first selection, the first subset of the data items is stored in the persistent storage device of the ADV.

Abstract: In one embodiment, a method, apparatus, and system for automatically detecting and notifying a user of a traffic rule violation using sensors and a perception module of an autonomous driving vehicle is disclosed. The operations performed comprise: capturing surrounding road traffic information at an autonomous driving vehicle (ADV) based on sensor data obtained from a plurality of sensors of the ADV; automatically detecting at the ADV a traffic rule violation of a first vehicle within a perception range of the ADV based on the surrounding road traffic information and a set of pre-configured traffic rules maintained by the ADV, including analyzing the surrounding road traffic information in view of the pre-configured traffic rules; and generating an alert in response to the detected traffic rule violation.

Abstract: User equipment, a base station, a base station access method, and a radio link monitoring method are provided, where the user equipment includes: a first receiving module, configured to receive first indication information sent by a first base station,where the first indication information includes a time period required by the user equipment to initially request to access a second base station; a first sending module, configured to send the random access scrambling code to the second base station; and a first notification module, configured to: if the user equipment fails to access the second base station within the time period, notify the first base station that a secondary cell group failure occurs. In this application, efficiency of accessing the second base station by the user equipment is improved by limiting a time in which the user equipment requests to access the second base station.

Abstract: In one embodiment, a method, apparatus, and system for trajectory planning for autonomous driving in an autonomous driving vehicle equipped with a low accuracy localization and perception module is disclosed.

Abstract: In some implementations, a method is provided. The method includes determining a path for an autonomous driving vehicle. The path is located within a first lane of an environment in which the autonomous driving vehicle is currently located. The method also includes obtaining sensor data. The sensor data indicates a set of speeds for a set of moving obstacles located in a second lane of the environment and wherein the second lane is adjacent to the first lane. The method further includes determining whether the set of speeds is lower than a threshold speed. The method further includes determining a new speed for the autonomous driving vehicle in response to determining that the set of speeds is lower than the threshold speed. The method further includes controlling the autonomous driving vehicle based on the path and the new speed.

Abstract: Methods and systems for multimodal motion planning framework for autonomous driving vehicles are disclosed. In one embodiment, driving environment data of an autonomous vehicle is received, where the environment data includes a route segment. The route segment is segmented into a number of route sub-segments. A specific driving scenario is assigned to each of the route sub-segments, where each specific driving scenario is included in a set of driving scenarios. A first motion planning algorithm is assigned according to a first assigned driving scenario included in the set of driving scenarios. The first motion planning algorithm is invoked to generate a first set of trajectories. The autonomous vehicle is controlled based on the first set of trajectories.

Abstract: An uplink synchronization processing method, a User Equipment (UE), and a base station are provided. The method includes: receiving a component carrier (CC) uplink synchronization indication message sent by a base station, where the uplink synchronization indication message carries identification information of one or multiple newly configured CCs; sending synchronization signaling to the base station when determining that the uplink synchronization needs to be executed on all or a part of the one or multiple newly configured CCs corresponding to the identification information; and receiving a time advanced (TA) adjusting message that is sent by the base station according to the synchronization signaling, and applying a TA value carried in the TA adjusting message to the CC on which the uplink synchronization needs to be executed.

Abstract: A parking system for autonomous driving vehicles optimizes a solution to a parking problem. The ADV detects a parking lot and selects a parking space. The ADV defines constraints for the parking lot, parking space, and kinematic constraints of the ADV, and generates a plurality of potential parking paths to the parking space, taking into account the constraints of the parking lot, parking space, and kinematics of the ADV, but without taking into any obstacles that may be surrounding the ADV. The ADV determines a cost for traversing each of the parking paths. One or more least cost candidate paths are selected from the parking paths, then one or more candidate paths are eliminated based on obstacles surrounding the ADV. Remaining candidates can be analyzed using a quadratic optimization system. A best parking path can be selected from the remaining candidates to navigate the ADV to the parking space.

Abstract: A parking system for autonomous driving vehicles (ADV) is disclosed that utilizes the perception, planning, and prediction modules of ADV driving logic to more safely and accurately park an ADV. An ADV scans a parking lot for an available space, then determines a sequence of portions or segments of a parking path from the ADV's location to a selected parking space. The sequence of segments involves one or more forward driving segments and one or more reverse driving segments. During the forward driving segments, the ADV logic uses the perception, planning, and prediction modules to identify one or more obstacles to the ADV parking path, and speed and direction of those obstacles. During a reverse driving segment, the ADV logically inverts the orientation of the perception, planning, and prediction modules to continue to track the one or more obstacles and their direction and speed while the ADV is driving in a reverse direction.

Abstract: An autonomous driving vehicle (ADV) may determine a predicted path for a moving obstacle and speeds for different portions of the path. The ADV use multiple threads in parallel to determine the path and speeds for the different portions of the path.

Abstract: According to some embodiments, described herein is a system and method for handling sensor failures in autonomous driving vehicles (ADV) that is navigating in a world coordination as an absolute coordination system. When the ADV encounters a sensor failure, but still has at least one camera working properly, the sensor failure handling system can switch the ADV from navigating in the world coordination to a local coordination, in which the ADV relies camera-based obstacle detection and lane mark detection to drive safely until human dis-engagement or until the ADV is parked along a road side.

Abstract: User equipment includes a receiving module configured to receive first indication information sent by a first base station. The first indication information includes a time period required by the user equipment to request to access a second base station. The user equipment includes a sending module to send the random access scrambling code to the second base station. The user equipment further includes a notification module to notify the first base station that a secondary cell group failure occurs if the user equipment fails to access the second base station within the time period.

Abstract: According to one embodiment, a system receives sensor data from a number of sensors of the ADV. The system extracts a predetermined number of features from the sensor data using a machine learning model. The system determining whether to alert a user to intervene the ADS based on the extracted features using the machine learning model. The system then generating a safety alarm based on the determining whether to alert the user to intervene the ADS and alerts the user to intervene the ADS of the ADV based on the generated safety alarm.

Abstract: An ADV may determine whether there is preexisting map data for an environment or geographical area/location where the ADV is located/travelling. If there is no preexisting data, the ADV may generate map data based on sensor data obtained from one or more sensors of the ADV. The ADV may determine a path for the ADV based on the generated map data. If there is preexisting map data, the ADV may determine a path for the ADV based on the preexisting map data.