Interpretable Motion Planner for Urban Driving via Hierarchical Imitation Learning

no code implementations • 24 Mar 2023 • Bikun Wang, Zhipeng Wang, Chenhao Zhu, Zhiqiang Zhang, Zhichen Wang, Penghong Lin, Jingchu Liu, Qian Zhang

We evaluate our method both in closed-loop simulation and real world driving, and demonstrate the neural network planner has outstanding performance in complex urban autonomous driving scenarios.

Autonomous Driving Imitation Learning +1

Elements of Effective Deep Reinforcement Learning towards Tactical Driving Decision Making

no code implementations • 1 Feb 2018 • Jingchu Liu, Pengfei Hou, Lisen Mu, Yinan Yu, Chang Huang

Tactical driving decision making is crucial for autonomous driving systems and has attracted considerable interest in recent years.

Autonomous Driving Decision Making +2

A Block Regression Model for Short-Term Mobile Traffic Forecasting

no code implementations • 17 Nov 2015 • Huimin Pan, Jingchu Liu, Sheng Zhou, Zhisheng Niu

Based on these characteristics, we propose a \emph{Block Regression} ({BR}) model for mobile traffic forecasting.

regression