Abstract: In one embodiment, in response to detecting an obstacle based on a driving environment surrounding an autonomous driving vehicle (ADV), a system projects the obstacle onto a station-time (ST) graph, where the ST graph indicates a location of the obstacle relative to a current location of the ADV at different points in time. The system determines a first set of end points that are not overlapped with the obstacle within the ST graph, wherein each of the end points in the first set represents a possible end condition. The system generates a first set of trajectory candidates between a starting point representing the current location of the ADV and the end points of the first set based on the ST graph. The system selects one of the trajectory candidates in the first set using a predetermined trajectory selection algorithm to control the ADV in view of the obstacle.

Abstract: According to one embodiment, an obstacle is predicted to move from a starting point to an end point based on perception data perceiving a driving environment surrounding an ADV that is driving within a lane. A longitudinal movement trajectory from the starting point to the end point is generated in view of a shape of the lane. A lateral movement trajectory from the starting point to the end point is generated, including optimizing a shape of the lateral movement trajectory using a first polynomial function. The longitudinal movement trajectory and the lateral movement trajectory are then combined to form a final predicted trajectory that predicts how the obstacle is to move. A path is generated to control the ADV to move in view of the predicted trajectory of the obstacle, for example, to avoid the collision with the obstacle.

Abstract: In one embodiment, a system generates a plurality of trajectory candidates for an autonomous driving vehicle (ADV) from a starting point to an end point of a particular driving scenario. The system generates a reference trajectory corresponding to the driving scenario based on a current state of the ADV associated with the starting point and an end state of the ADV associated with the end point, where the reference trajectory is associated with an objective. For each of the trajectory candidates, the system compares the trajectory candidate with the reference trajectory to generate an objective cost representing a similarity between the trajectory candidate and the reference trajectory. The system selects one of the trajectory candidates as a target trajectory for driving the ADV based on objective costs of the trajectory candidates.

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Abstract: A first reference line representing a trajectory from a first location to a second location associated with an autonomous driving vehicle (ADV) is received. The first reference line is segmented into a number of reference line segments. For each of the reference line segments, a quintic polynomial function is defined to represent the reference line segment. An objective function is determined based on the quintic polynomial functions of the reference line segments. An optimization is performed on coefficients of the quintic polynomial functions in view of a set of constraints associated with the reference line segments, such that an output of the objective function reaches minimum while the constraints are satisfied. A second reference line is then generated based on the optimized parameters or coefficients of the quintic polynomial functions of the objective function. The second reference line is then utilized to plan and control the ADV.

Abstract: In one embodiment, when an ADV is driving on a trajectory generated based on a reference line, a separate processing thread is executed to precalculate a new reference line as a future reference line for a future planning cycle in parallel. The future reference line is being created while the ADV is moving along a trajectory generated based on the original reference line and before reaching a location corresponding to the starting point of the future reference line. The future reference line is overlapped with an end section of the original reference line, such that the future reference line can be connected to the end section of the original reference line. The future reference line serves an extension of the original reference line before the ADV reaches the end section of the original reference line.

Abstract: Via a first processing thread, an ADV is controlled according to a first trajectory that was generated based on a first reference line starting at a first location. Concurrently via a second processing thread, a second reference line is generated based on a second location of the first trajectory that the ADV will likely reach within a predetermined period of time in future. The predetermined period of time is greater than or equals to an amount of time to generate a reference line for the ADV. The second reference line is generated while the ADV is moving according to the first trajectory and before reaching the second location. Subsequently, in response to determining that the ADV is within a predetermined proximity of the second location, a second trajectory is generated based on the second reference line without having to calculate the second reference line at the second location.

Abstract: According to one embodiment, an ADV is controlled according to a first trajectory planned during a first planning cycle. A control error is determined which represents a drifting error at a first location of the ADV at a first point in time at the end of the first planning cycle. A second point in time is selected on the first trajectory. A second trajectory is generated from a second location on the first trajectory corresponding o the second point in time as a starting location of the second trajectory for a second planning cycle as a next planning cycle. A segment of the first trajectory between the first point in time and the second point in time is combined with the second trajectory to generate a third trajectory for the second planning cycle. The ADV is driven and controlled according to the third trajectory corresponding to the second planning cycle.

Abstract: A first reference line representing a trajectory from a first location to a second location associated with an autonomous driving vehicle (ADV) is received. The first reference line is segmented into a number of reference line segments. For each of the reference line segments, a quintic polynomial function is defined to represent the reference line segment. An objective function is determined based on the quintic polynomial functions of the reference line segments. An optimization is performed on coefficients of the quintic polynomial functions in view of a set of constraints associated with the reference line segments, such that an output of the objective function reaches minimum while the constraints are satisfied. A second reference line is then generated based on the optimized parameters or coefficients of the quintic polynomial functions of the objective function. The second reference line is then utilized to plan and control the ADV.

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: 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: 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: 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.