Maneuver-Aware Pooling for Vehicle Trajectory Prediction
This work addresses the challenge of accurate trajectory prediction for autonomous vehicles sharing roads with human drivers, focusing on specific maneuvers like lane changes and merging, which is an incremental improvement over existing pooling methods.
The paper tackles the problem of predicting vehicle trajectories on highways, particularly during lane changes and merging maneuvers, by proposing a novel pooling strategy that uses polar trajectory representation, orientation, and radial velocity to capture inter-dependencies between vehicles, resulting in improved prediction accuracy compared to state-of-the-art methods on the NGSIM dataset.
Autonomous vehicles should be able to predict the future states of its environment and respond appropriately. Specifically, predicting the behavior of surrounding human drivers is vital for such platforms to share the same road with humans. Behavior of each of the surrounding vehicles is governed by the motion of its neighbor vehicles. This paper focuses on predicting the behavior of the surrounding vehicles of an autonomous vehicle on highways. We are motivated by improving the prediction accuracy when a surrounding vehicle performs lane change and highway merging maneuvers. We propose a novel pooling strategy to capture the inter-dependencies between the neighbor vehicles. Depending solely on Euclidean trajectory representation, the existing pooling strategies do not model the context information of the maneuvers intended by a surrounding vehicle. In contrast, our pooling mechanism employs polar trajectory representation, vehicles orientation and radial velocity. This results in an implicitly maneuver-aware pooling operation. We incorporated the proposed pooling mechanism into a generative encoder-decoder model, and evaluated our method on the public NGSIM dataset. The results of maneuver-based trajectory predictions demonstrate the effectiveness of the proposed method compared with the state-of-the-art approaches. Our "Pooling Toolbox" code is available at https://github.com/m-hasan-n/pooling.