Vehicle motion intention reasoning using cooperative perception on urban road

As autonomous vehicles are venturing on the urban road, reasoning other vehicles' motion intention is always essential for anticipatory decision-making. This paper considers a new class of motion intention reasoning problem using cooperative perception. Specifically, thanks to the extended perception range contributed by cooperative perception, we can explicitly consider the behavior correlations among multiple vehicles, where each vehicle's motion intention can be inferred using both the temporal observations and the other vehicles' motion intention expectation. As such, a Simplified variant of Coupled Hidden Markov Model (S-CHMM) is proposed for motion intention inference. The experiment on an autonomous vehicle shows that the proposed algorithm can improve the motion intention accuracy and provide efficient overtaking triggering for autonomous driving on urban road.