2020
DOI: 10.1109/access.2020.2968618
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A Dual Learning Model for Vehicle Trajectory Prediction

Abstract: Automated vehicles and advanced driver-assistance systems require an accurate prediction of future traffic scene states. The tendency in recent years has been to use deep learning approaches for accurate trajectory prediction but these approaches suffer from computational complexity, dependency on a specific environment/dataset, and lack of insight into vehicle interactions. In this paper, we aim to address these limitations by proposing a Dual Learning Model (DLM) using lane occupancy and risk maps for vehicl… Show more

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Cited by 47 publications
(15 citation statements)
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“…e comparison results show that the proposed knowledge-driven LSTM network has better performance in RMSE for NGSIM. Note that as compared to the baseline [24], the prediction accuracy gets a slight improvement, but the proposed method enhances the real-time performance and much reduces the computational complexity due to the reduction of the feature space dimension.…”
Section: Comparative Studymentioning
confidence: 94%
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“…e comparison results show that the proposed knowledge-driven LSTM network has better performance in RMSE for NGSIM. Note that as compared to the baseline [24], the prediction accuracy gets a slight improvement, but the proposed method enhances the real-time performance and much reduces the computational complexity due to the reduction of the feature space dimension.…”
Section: Comparative Studymentioning
confidence: 94%
“…e results show that the proposed method outperforms the state-of-the-art model and decreases the overall RMSE value of the system by 10 percent on average. Table 2 summarizes the RMSE values comparing the proposed methods with the baseline trajectory prediction models in the literature [20,[22][23][24]35].…”
Section: Comparative Studymentioning
confidence: 99%
See 1 more Smart Citation
“…Vehicles do not drive exactly along the track line. Additionally, the distribution of the wheel track line along the transverse direction varies significantly among different countries; thus, it cannot be simply applied [52]. e Dazhenggang Bridge is a one-way four-lane bridge.…”
Section: Selection Of Most Unfavorable Position Of Lateral Force and Effect Of Wheel Transverse Positionmentioning
confidence: 99%
“…By contrast, maneuver-based approaches (e. g. [1], [17]- [22]) try to infer the maneuver a driver intends to perform. Finally, interaction-aware approaches [23]- [26] provide the most advanced motion models by predicting the motions of all vehicles in a given situation simultaneously. In particular, these models consider that all vehicles mutually influence each other.…”
Section: B Behavior Prediction Approachesmentioning
confidence: 99%