165 citations · 310 across the 14 of their papers we have counts for
14 papers
CSMapping: Scalable Crowdsourced Semantic Mapping and Topology Inference for Autonomous Driving
Zhijian Qiao, Zehuan Yu, Tong Li +3
Crowdsourcing enables scalable autonomous driving map construction, but low-cost sensor noise hinders quality from improving with data volume. We propose CSMapping, a system that p…
MARS: Exploiting Multi-Level Parallelism for DNN Workloads on Adaptive Multi-Accelerator Systems
Guan Shen, Jieru Zhao, Zeke Wang +5
Along with the fast evolution of deep neural networks, the hardware system is also developing rapidly. As a promising solution achieving high scalability and low manufacturing cost…
FlowMap: Path Generation for Automated Vehicles in Open Space Using Traffic Flow
Wenchao Ding, Jieru Zhao, Yubin Chu +5
There is extensive literature on perceiving road structures by fusing various sensor inputs such as lidar point clouds and camera images using deep neural nets. Leveraging the late…
EPSILON: An Efficient Planning System for Automated Vehicles in Highly Interactive Environments
Wenchao Ding, Lu Zhang, Jing Chen +1
In this paper, we present an Efficient Planning System for automated vehicles In highLy interactive envirONments (EPSILON). EPSILON is an efficient interaction-aware planning syste…
Learning to Predict Vehicle Trajectories with Model-based Planning
Haoran Song, Di Luan, Wenchao Ding +2
Predicting the future trajectories of on-road vehicles is critical for autonomous driving. In this paper, we introduce a novel prediction framework called PRIME, which stands for P…
FP-Stereo: Hardware-Efficient Stereo Vision for Embedded Applications
Jieru Zhao, Tingyuan Liang, Liang Feng +4
Fast and accurate depth estimation, or stereo matching, is essential in embedded stereo vision systems, requiring substantial design effort to achieve an appropriate balance among…
Efficient Uncertainty-aware Decision-making for Automated Driving Using Guided Branching
Lu Zhang, Wenchao Ding, Jing Chen +1
Decision-making in dense traffic scenarios is challenging for automated vehicles (AVs) due to potentially stochastic behaviors of other traffic participants and perception uncertai…
PiP: Planning-informed Trajectory Prediction for Autonomous Driving
Haoran Song, Wenchao Ding, Yuxuan Chen +3
It is critical to predict the motion of surrounding vehicles for self-driving planning, especially in a socially compliant and flexible way. However, future prediction is challengi…
Safe Trajectory Generation for Complex Urban Environments Using Spatio-temporal Semantic Corridor
Wenchao Ding, Lu Zhang, Jing Chen +1
Planning safe trajectories for autonomous vehicles in complex urban environments is challenging since there are numerous semantic elements (such as dynamic agents, traffic lights a…
An Efficient B-spline-Based Kinodynamic Replanning Framework for Quadrotors
Wenchao Ding, Wenliang Gao, Kaixuan Wang +1
Trajectory replanning for quadrotors is essential to enable fully autonomous flight in unknown environments. Hierarchical motion planning frameworks, which combine path planning wi…
Trajectory Replanning for Quadrotors Using Kinodynamic Search and Elastic Optimization
Wenchao Ding, Wenliang Gao, Kaixuan Wang +1
We focus on a replanning scenario for quadrotors where considering time efficiency, non-static initial state and dynamical feasibility is of great significance. We propose a real-t…
Online Vehicle Trajectory Prediction using Policy Anticipation Network and Optimization-based Context Reasoning
Wenchao Ding, Shaojie Shen
In this paper, we present an online two-level vehicle trajectory prediction framework for urban autonomous driving where there are complex contextual factors, such as lane geometri…
Predicting Vehicle Behaviors Over An Extended Horizon Using Behavior Interaction Network
Wenchao Ding, Jing Chen, Shaojie Shen
Anticipating possible behaviors of traffic participants is an essential capability of autonomous vehicles. Many behavior detection and maneuver recognition methods only have a very…
Mixed-Timescale Online PHY Caching for Dual-Mode MIMO Cooperative Networks
An Liu, Vincent Lau, Wenchao Ding +1
Recently, physical layer (PHY) caching has been proposed to exploit the dynamic side information induced by caches at base stations (BSs) to support Coordinated Multi-Point (CoMP)…