activity
20172023
most citedINTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

354 citations · 937 across the 110 of their papers we have counts for

collaborators
Showing 2019 · cs.ROShow all

14 papers · 2 filters

cs.RO2019

UrbanLoco: A Full Sensor Suite Dataset for Mapping and Localization in Urban Scenes

Weisong Wen, Yiyang Zhou, Guohao Zhang +5

Mapping and localization is a critical module of autonomous driving, and significant achievements have been reached in this field. Beyond Global Navigation Satellite System (GNSS),…

cs.RO2019★ 2 cited

Multiple criteria decision-making for lane-change model

Ao Li, Liting Sun, Wei Zhan +1

Simulation has long been an essential part of testing autonomous driving systems, but only recently has simulation been useful for building and training self-driving vehicles. Vehi…

cs.RO2019★ 2 cited

Online Learning in Planar Pushing with Combined Prediction Model

Huidong Gao, Yi Ouyang, Masayoshi Tomizuka

Pushing is a useful robotic capability for positioning and reorienting objects. The ability to accurately predict the effect of pushes can enable efficient trajectory planning and…

cs.RO2019★ 354 cited

INTERACTION Dataset: An INTERnational, Adversarial and Cooperative moTION Dataset in Interactive Driving Scenarios with Semantic Maps

Wei Zhan, Liting Sun, Di Wang +8

Behavior-related research areas such as motion prediction/planning, representation/imitation learning, behavior modeling/generation, and algorithm testing, require support from hig…

cs.RO2019

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…

cs.RO2019★ 2 cited

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…