A system for controlling a motion of a vehicle, comprising: an input interface configured to accept a current state of the vehicle, an image of an environment, formed by a map of the environmental and traffic data, in proximity to the vehicle, and a next driving decision of the vehicle; characterized by further comprising: a memory configured to store a set of control functions, wherein each control function is configured to transition the current state of the vehicle into a target state based on its corresponding control objective, wherein at least some of the control functions are probabilistic and include a deterministic component for transitioning the current state into the target state and a probabilistic component for determining a probabilistic distribution of values around the target state determined by the deterministic component, such that an output of the probabilistic control function is a parametric probability distribution over the target state defined by a first moment and at least one higher order moment; a processor configured to execute a motion planner and a controller, wherein upon the execution, the motion planner submits the current state into at least a subset of control functions, based on the current state, the image of the environment, and the next driving decision of the vehicle, consistent with the next driving decision to produce a subset of parametric probability distributions over the target state; and combines the subset of parametric probability distributions to produce a joint parametric probability distribution of the target state, wherein upon the execution, the controller determines a control command based on the first moment and at least one higher order moment of the joint parametric probability distribution of the target state; and an output interface configured to output the control command to an actuator of the vehicle. a memory configured to store a set of control functions, wherein each control function is configured to transition the current state of the vehicle into a target state based on its corresponding control objective, wherein at least some of the control functions are probabilistic and include a deterministic component for transitioning the current state into the target state and a probabilistic component for determining a probabilistic distribution of values around the target state determined by the deterministic component, such that an output of the probabilistic control function is a parametric probability distribution over the target state defined by a first moment and at least one higher order moment; a processor configured to execute a motion planner and a controller, wherein upon the execution, the motion planner submits the current state into at least a subset of control functions, based on the current state, the image of the environment, and the next driving decision of the vehicle, consistent with the next driving decision to produce a subset of parametric probability distributions over the target state; and combines the subset of parametric probability distributions to produce a joint parametric probability distribution of the target state, wherein upon the execution, the controller determines a control command based on the first moment and at least one higher order moment of the joint parametric probability distribution of the target state; and an output interface configured to output the control command to an actuator of the vehicle.