64 citations · 165 across the 19 of their papers we have counts for
9 papers · 1 filter
Editing Driver Character: Socially-Controllable Behavior Generation for Interactive Traffic Simulation
Wei-Jer Chang, Chen Tang, Chenran Li +3
Traffic simulation plays a crucial role in evaluating and improving autonomous driving planning systems. After being deployed on public roads, autonomous vehicles need to interact…
Analyzing and Enhancing Closed-loop Stability in Reactive Simulation
Wei-Jer Chang, Yeping Hu, Chenran Li +2
Simulation has played an important role in efficiently evaluating self-driving vehicles in terms of scalability. Existing methods mostly rely on heuristic-based simulation, where t…
Transferable and Adaptable Driving Behavior Prediction
Letian Wang, Yeping Hu, Liting Sun +3
While autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient, transferable, and…
Hierarchical Adaptable and Transferable Networks (HATN) for Driving Behavior Prediction
Letian Wang, Yeping Hu, Liting Sun +3
When autonomous vehicles still struggle to solve challenging situations during on-road driving, humans have long mastered the essence of driving with efficient transferable and ada…
Scenario-Transferable Semantic Graph Reasoning for Interaction-Aware Probabilistic Prediction
Yeping Hu, Wei Zhan, Masayoshi Tomizuka
Accurately predicting the possible behaviors of traffic participants is an essential capability for autonomous vehicles. Since autonomous vehicles need to navigate in dynamically c…
Multi-agent Interactive Prediction under Challenging Driving Scenarios
Weihao Xuan, Ruijie Ren
In order to drive safely on the road, autonomous vehicle is expected to predict future outcomes of its surrounding environment and react properly. In fact, many researchers have be…
Generic Tracking and Probabilistic Prediction Framework and Its Application in Autonomous Driving
Jiachen Li, Wei Zhan, Yeping Hu +1
Accurately tracking and predicting behaviors of surrounding objects are key prerequisites for intelligent systems such as autonomous vehicles to achieve safe and high-quality decis…
Generic Prediction Architecture Considering both Rational and Irrational Driving Behaviors
Yeping Hu, Liting Sun, Masayoshi Tomizuka
Accurately predicting future behaviors of surrounding vehicles is an essential capability for autonomous vehicles in order to plan safe and feasible trajectories. The behaviors of…
Towards a Fatality-Aware Benchmark of Probabilistic Reaction Prediction in Highly Interactive Driving Scenarios
Wei Zhan, Liting Sun, Yeping Hu +2
Autonomous vehicles should be able to generate accurate probabilistic predictions for uncertain behavior of other road users. Moreover, reactive predictions are necessary in highly…