7 papers
EP-Diffuser: An Efficient Diffusion Model for Traffic Scene Generation and Prediction via Polynomial Representations
Yue Yao, Mohamed-Khalil Bouzidi, Daniel Goehring +1
As the prediction horizon increases, predicting the future evolution of traffic scenes becomes increasingly difficult due to the multi-modal nature of agent motion. Most state-of-t…
Reachability-Based Contingency Planning against Multi-Modal Predictions with Branch MPC
Mohamed-Khalil Bouzidi, Bojan Derajic, Daniel Goehring +1
This paper presents a novel contingency planning framework that integrates learning-based multi-modal predictions of traffic participants into Branch Model Predictive Control (MPC)…
Beyond In-Distribution Performance: A Cross-Dataset Study of Trajectory Prediction Robustness
Yue Yao, Daniel Goehring, Joerg Reichardt
We study the Out-of-Distribution (OoD) generalization ability of three SotA trajectory prediction models with comparable In-Distribution (ID) performance but different model design…
Improving Out-of-Distribution Generalization of Trajectory Prediction for Autonomous Driving via Polynomial Representations
Yue Yao, Shengchao Yan, Daniel Goehring +2
Robustness against Out-of-Distribution (OoD) samples is a key performance indicator of a trajectory prediction model. However, the development and ranking of state-of-the-art (SotA…
Motion Planning under Uncertainty: Integrating Learning-Based Multi-Modal Predictors into Branch Model Predictive Control
Mohamed-Khalil Bouzidi, Bojan Derajic, Daniel Goehring +1
In complex traffic environments, autonomous vehicles face multi-modal uncertainty about other agents' future behavior. To address this, recent advancements in learningbased motion…
Learning-Aided Warmstart of Model Predictive Control in Uncertain Fast-Changing Traffic
Mohamed-Khalil Bouzidi, Yue Yao, Daniel Goehring +1
Model Predictive Control lacks the ability to escape local minima in nonconvex problems. Furthermore, in fast-changing, uncertain environments, the conventional warmstart, using th…
An Empirical Bayes Analysis of Object Trajectory Representation Models
Yue Yao, Daniel Goehring, Joerg Reichardt
Linear trajectory models provide mathematical advantages to autonomous driving applications such as motion prediction. However, linear models' expressive power and bias for real-wo…