Abstract: The present disclosure provides a method for multimodal emotion classification based on modal space assimilation and contrastive learning. The present disclosure introduces the concept of assimilation. A guidance vector composed of complementary information between modalities is utilized to guide each modality to simultaneously approach a solution space. This operation not only further improves the efficiency of searching for the solution space but also renders heterogeneous spaces of three modalities isomorphic. In a process of making spaces isomorphic, contributions of a plurality of modalities to a final solution space can be effectively balanced to a certain extent. When guiding each modality, this strategy enables a model to be more concerned about emotion features, thereby reducing intra-modal redundancy. Thus, the difficulty of establishing a multimodal representation is reduced.

Abstract: According to one embodiment, a system receives a captured image perceiving an environment of an autonomous driving vehicle (ADV) from an image capturing device of the ADV capturing a plurality of obstacles near the ADV. The system generates a first tunnel based on a width of a road lane for the ADV, where the first tunnel represents a passable lane for the ADV to travel through. The system generates one or more additional tunnels based on locations of the obstacles, where the one or more additional tunnels modify a width of the passable lane according to a level of invasiveness of the obstacles. The system generates a trajectory of the ADV based on the first and the additional tunnels to control the ADV according to the trajectory to navigate around the obstacles without collision.

Abstract: The present disclosure provides a method, an apparatus, a device and a readable storage medium for planning a pass path. The method includes: acquiring current road environment information in front of a vehicle; setting pass candidate points according to the current road environment information and a driving strategy; and determining a current optimal passable path according to the pass candidate points. Since the pass candidate points are set according to the current road environment information and the driving strategy, and the current optimal passable path is determined according to the pass candidate points, thereby effectively decreasing the calculation amount of the impassable path calculation in prior art due to direct setting of pass candidate points in all areas in front of an unmanned vehicle.

Abstract: Provided are a pass route planning method and apparatus, a device and a readable storage medium. The method includes: obtaining current road environment information in front of a vehicle; determining a current passable area according to the current road environment information; setting pass candidate points in the current passable area; and determining a current optimal passable route according to the pass candidate points. Firstly, the passable area is determined, and then the pass candidate points are set in the passable area, and thus the current optimal passable route is calculated according to the pass candidate points in the passable area, which can effectively reduce a calculation amount of unreachable pass routes in the prior art in which candidate points are set in all areas directly in front of an unmanned vehicle, thereby reducing a calculation amount for planning a pass route and improving a planning speed of the pass route.

Abstract: In one embodiment, instead of using map data, a relative coordinate system is utilized to assist perception of the driving environment surrounding an ADV for some driving situations. One of such driving situations is driving on a highway. Typically, a highway has fewer intersections and exits. The relative coordinate system is utilized based on the relative lane configuration and relative obstacle information to control the ADV to simply follow the lane and avoid potential collision with any obstacles discovered within the road, without having to use map data. Once the relative lane configuration and obstacle information have been determined, regular path and speed planning and optimization can be performed to generate a trajectory to drive the ADV. Such a perception system is referred to as a relative perception system based on a relative coordinate system.

Abstract: The present disclosure provides a method, an apparatus, a device and a readable storage medium for preventing a vehicle collision. The method includes determining a current conservative anti-collision region of a vehicle acquiring the omnidirectional environmental information in the current region in the current conservative anti-collision region; predicting a behavior of an obstacle according to the omnidirectional environmental information in the current region, and controlling the vehicle to conduct an anti-collision behavior according a prediction result, a reasonable prediction may be made to the behavior of the obstacle based on the conservative anti-collision region and the omnidirectional environmental information, thus controlling the vehicle to conduct an accurate anti-collision behavior, thereby preventing collisions effectively, and avoiding an occurrence of traffic accidents.

Abstract: According to one embodiment, a system receives a captured image perceiving an environment of an ADV from an image capturing device of the ADV capturing a plurality of obstacles near the ADV. The system generates a first tunnel based on a width of a road lane for the ADV, where the first tunnel represents a passable lane for the ADV to travel through. The system generates one or more additional tunnels based on locations of the obstacles, where the one or more additional tunnels modify a width of the passable lane according to a level of invasiveness of the obstacles. The system generates a trajectory of the ADV based on the first and the additional tunnels to control the ADV according to the trajectory to navigate around the obstacles without collision.

Abstract: In one embodiment, instead of using map data, a relative coordinate system is utilized to assist perception of the driving environment surrounding an ADV for some driving situations. One of such driving situations is driving on a highway. Typically, a highway has fewer intersections and exits. The relative coordinate system is utilized based on the relative lane configuration and relative obstacle information to control the ADV to simply follow the lane and avoid potential collision with any obstacles discovered within the road, without having to use map data. Once the relative lane configuration and obstacle information have been determined, regular path and speed planning and optimization can be performed to generate a trajectory to drive the ADV. Such a perception system is referred to as a relative perception system based on a relative coordinate system.

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: In one embodiment, in response to a route from a source location to a target location, the route is analyzed to identify a list of one or more driving scenarios along the route that match one or more predetermined driving scenarios. The route is segmented into a list of route segments based on the driving scenarios. At least one of the route segments corresponds to one of the identified driving scenarios. A path is generated based on the route segments for driving an autonomous driving vehicle from the source location to the target location. The path includes a number of path segments corresponding to the route segments. At least one of the path segments of the path is determined based on a preconfigured path segment of a predetermined driving scenario associated with the path segment, without having to calculating the same at real time.

Abstract: According to some embodiments, a system calculates a first trajectory based on a map and a route information. The system generates a path profile based on the first trajectory, traffic rules, and an obstacle information describing one or more obstacles perceived by the ADV. The system generates a speed profile based on the path profile, where the speed profile includes, for each of the obstacles, a decision to yield or overtake the obstacle. The system performs a quadratic programming optimization on the path profile and the speed profile to identify an optimal path with optimal speeds. The system generates a second trajectory based on the optimal path and optimal speeds to control the ADV autonomously according to the second trajectory.

Abstract: The present disclosure provides a method, an apparatus, a device and a readable storage medium for preventing a vehicle collision. The method includes determining a current conservative anti-collision region of a vehicle acquiring the omnidirectional environmental information in the current region in the current conservative anti-collision region; predicting a behavior of an obstacle according to the omnidirectional environmental information in the current region, and controlling the vehicle to conduct an anti-collision behavior according a prediction result, a reasonable prediction may be made to the behavior of the obstacle based on the conservative anti-collision region and the omnidirectional environmental information, thus controlling the vehicle to conduct an accurate anti-collision behavior, thereby preventing collisions effectively, and avoiding an occurrence of traffic accidents.

Abstract: Provided are a pass route planning method and apparatus, a device and a readable storage medium. The method includes: obtaining current road environment information in front of a vehicle; determining a current passable area according to the current road environment information; setting pass candidate points in the current passable area; and determining a current optimal passable route according to the pass candidate points. Firstly, the passable area is determined, and then the pass candidate points are set in the passable area, and thus the current optimal passable route is calculated according to the pass candidate points in the passable area, which can effectively reduce a calculation amount of unreachable pass routes in the prior art in which candidate points are set in all areas directly in front of an unmanned vehicle, thereby reducing a calculation amount for planning a pass route and improving a planning speed of the pass route.

Abstract: The present disclosure provides a method, an apparatus, a device and a readable storage medium for planning a pass path. The method includes: acquiring current road environment information in front of a vehicle; setting pass candidate points according to the current road environment information and a driving strategy; and determining a current optimal passable path according to the pass candidate points. Since the pass candidate points are set according to the current road environment information and the driving strategy, and the current optimal passable path is determined according to the pass candidate points, thereby effectively decreasing the calculation amount of the impassable path calculation in prior art due to direct setting of pass candidate points in all areas in front of an unmanned vehicle.

Abstract: Systems and methods are disclosed for question generation to infer the most probable cause from the observable outcome and known Noisy-OR causal relations. In embodiments, the outcomes are sorted by indices according to an order including but not limited to the outcomes' natural frequency order, expert-labeled order, machine-learning derived order, etc. According to their assigned indices, in embodiments, observed outcomes with lower indices are assigned for exact inference while observed outcomes with higher indices are assigned for variational inference. In embodiments, results of exact inference and variational inference are combined to predict the most probable cause. The unique combination of exact inference and variational inference according to outcome indices makes the probable cause inferring process faster.

Abstract: Driving parameters (e.g., speed, heading direction) that an autonomous driving vehicle (ADV) likely utilize as target driving parameters are grouped into a number of ranges and one of the driving parameters in each range is selected as a driving parameter representative or a target driving parameter representing the respective range or segment. For each of the target driving parameters representing the ranges, a particle swarm optimization method is utilized to derive a set of most optimized coefficients for a controller (e.g., speed controller, steering controller) for controlling an ADV. A driving parameter to coefficient (parameter/coefficient) mapping table is generated to map a particular driving parameter representing a range of driving parameter to a set of one or more coefficients of a particular controller. The parameter/coefficient mapping table is utilized at real-time to configure a controller in response to a particular target driving parameter using the corresponding coefficients.

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: 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: In one embodiment, a computer system generates a first vehicular path based on map information. The system collects data points representing geographical coordinates of vehicles that drove on a vehicular path lane at different points in time. The system segments the first vehicular path into path segments based on the collected data points. For each of the path segments, the system applies a smoothing function to select a subset of the data points that are within a predetermined proximity of the corresponding path segment and calculates a segment reference point to represent the path segment by combining the selected data points. The segment reference points of the path segments of the first vehicular path are interpolated to generate a second vehicular path such that the second vehicular path is used as a reference line to control ADVs driving on the first vehicular path.

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.