FIELD

This disclosure relates generally to autonomous vehicles and, more particularly, to action planning systems and methods for autonomous vehicles.

BACKGROUND

Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to the prior art by inclusion in this section.

Conventional action planning device is based on a finite state machine (FSM) approach where the autonomous vehicle decides to make specific actions based on heuristic transition conditions. This FSM approach, however, only allows the autonomous vehicle to passively react to changes in its environment and provides no future look ahead for how the given action might affect how the future traffic situation evolves.FIGS. 1 and 2illustrate various possible actions such as “follow lane” action with a target or “lane change” action between two target vehicles on an adjacent lane that are evaluated by the prior art action planning devices using the FSM approach.

SUMMARY

A summary of certain embodiments disclosed herein is set forth below. It should be understood that these aspects are presented merely to provide the reader with a brief summary of these certain embodiments and that these aspects are not intended to limit the scope of this disclosure. Indeed, this disclosure may encompass a variety of aspects that may not be set forth below.

Embodiments of the disclosure related a non-transitory computer-readable storage medium having stored thereon a computer program for evaluating reactions and interactions with one or more vehicles, the computer program comprising a routine of set instructions for causing the machine to perform searching through a tree of possible action sequence combinations for an ego vehicle and capturing reactions and interactions with one or more vehicles.

Another aspect of the disclosed embodiment is a method by one or more processors includes estimating future environment of an autonomous vehicle, generating a possible trajectory for the autonomous vehicles, predicting motion and reactions of each dynamic obstacle in the future environment of the autonomous vehicle based on current local traffic context, and generating a prediction iteratively over timesteps. The method further decoupling, by the one or more processors, an action decision time resolution from an iterative prediction resolution.

Another aspect of the disclosed embodiment is a system for an autonomous vehicle includes one or more processors and one or more non-transitory computer-readable storage medium having stored thereon a computer program used by the one or more processors, wherein the computer program causes the one or more processors to estimate future environment of an autonomous vehicle, generate a possible trajectory for the autonomous vehicles, predict motion and reactions of each dynamic obstacle in the future environment of the autonomous vehicle based on current local traffic context, and generate a prediction iteratively over timesteps.

