457 citations · 845 across the 36 of their papers we have counts for
36 papers
CVAE-H: Conditionalizing Variational Autoencoders via Hypernetworks and Trajectory Forecasting for Autonomous Driving
Geunseob Oh, Huei Peng
The task of predicting stochastic behaviors of road agents in diverse environments is a challenging problem for autonomous driving. To best understand scene contexts and produce di…
Improved Robustness and Safety for Pre-Adaptation of Meta Reinforcement Learning with Prior Regularization
Lu Wen, Songan Zhang, H. Eric Tseng +3
Meta Reinforcement Learning (Meta-RL) has seen substantial advancements recently. In particular, off-policy methods were developed to improve the data efficiency of Meta-RL techniq…
Real-time Semantic 3D Dense Occupancy Mapping with Efficient Free Space Representations
Yuanxin Zhong, Huei Peng
A real-time semantic 3D occupancy mapping framework is proposed in this paper. The mapping framework is based on the Bayesian kernel inference strategy from the literature. Two nov…
Correspondence-Free Point Cloud Registration with SO(3)-Equivariant Implicit Shape Representations
Minghan Zhu, Maani Ghaffari, Huei Peng
This paper proposes a correspondence-free method for point cloud rotational registration. We learn an embedding for each point cloud in a feature space that preserves the SO(3)-equ…
VIN: Voxel-based Implicit Network for Joint 3D Object Detection and Segmentation for Lidars
Yuanxin Zhong, Minghan Zhu, Huei Peng
A unified neural network structure is presented for joint 3D object detection and point cloud segmentation in this paper. We leverage rich supervision from both detection and segme…
Quick Learner Automated Vehicle Adapting its Roadmanship to Varying Traffic Cultures with Meta Reinforcement Learning
Songan Zhang, Lu Wen, Huei Peng +1
It is essential for an automated vehicle in the field to perform discretionary lane changes with appropriate roadmanship - driving safely and efficiently without annoying or endang…
Monocular 3D Vehicle Detection Using Uncalibrated Traffic Cameras through Homography
Minghan Zhu, Songan Zhang, Yuanxin Zhong +3
This paper proposes a method to extract the position and pose of vehicles in the 3D world from a single traffic camera. Most previous monocular 3D vehicle detection algorithms focu…
An Interaction-aware Evaluation Method for Highly Automated Vehicles
Xinpeng Wang, Songan Zhang, Kuan-Hui Lee +1
It is important to build a rigorous verification and validation (V&V) process to evaluate the safety of highly automated vehicles (HAVs) before their wide deployment on public road…
Driving-Policy Adaptive Safeguard for Autonomous Vehicles Using Reinforcement Learning
Zhong Cao, Shaobing Xu, Songan Zhang +2
Safeguard functions such as those provided by advanced emergency braking (AEB) can provide another layer of safety for autonomous vehicles (AV). A smart safeguard function should a…
Uncertainty-Aware Voxel based 3D Object Detection and Tracking with von-Mises Loss
Yuanxin Zhong, Minghan Zhu, Huei Peng
Object detection and tracking is a key task in autonomy. Specifically, 3D object detection and tracking have been an emerging hot topic recently. Although various methods have been…
SUPER: A Novel Lane Detection System
Pingping Lu, Chen Cui, Shaobing Xu +2
AI-based lane detection algorithms were actively studied over the last few years. Many have demonstrated superior performance compared with traditional feature-based methods. The a…
Combined Eco-Routing and Power-Train Control of Plug-In Hybrid Electric Vehicles in Transportation Networks
Arian Houshmand, Christos G. Cassandras, Nan Zhou +3
We study the problem of eco-routing for Plug-In Hybrid Electric Vehicles (PHEVs) to minimize the overall energy consumption cost. We propose an algorithm which can simultaneously c…
Generating Socially Acceptable Perturbations for Efficient Evaluation of Autonomous Vehicles
Songan Zhang, Huei Peng, Subramanya Nageshrao +1
Deep reinforcement learning methods have been widely used in recent years for autonomous vehicle's decision-making. A key issue is that deep neural networks can be fragile to adver…
Safe Reinforcement Learning for Autonomous Vehicles through Parallel Constrained Policy Optimization
Lu Wen, Jingliang Duan, Shengbo Eben Li +2
Reinforcement learning (RL) is attracting increasing interests in autonomous driving due to its potential to solve complex classification and control problems. However, existing RL…
Monocular Depth Prediction through Continuous 3D Loss
Minghan Zhu, Maani Ghaffari, Yuanxin Zhong +4
This paper reports a new continuous 3D loss function for learning depth from monocular images. The dense depth prediction from a monocular image is supervised using sparse LIDAR po…
Mcity Data Collection for Automated Vehicles Study
Yiqun Dong, Yuanxin Zhong, Wenbo Yu +5
The main goal of this paper is to introduce the data collection effort at Mcity targeting automated vehicle development. We captured a comprehensive set of data from a set of perce…
Eco-Mobility-on-Demand Fleet Control with Ride-Sharing
Xianan Huang, Boqi Li, Huei Peng +2
Shared Mobility-on-Demand using automated vehicles can reduce energy consumption and cost for future mobility. However, its full potential in energy saving has not been fully explo…
Modeling Multi-Vehicle Interaction Scenarios Using Gaussian Random Field
Yaohui Guo, Vinay Varma Kalidindi, Mansur Arief +4
Autonomous vehicles are expected to navigate in complex traffic scenarios with multiple surrounding vehicles. The correlations between road users vary over time, the degree of whic…
Impact of Traffic Lights on Trajectory Forecasting of Human-driven Vehicles Near Signalized Intersections
Geunseob Oh, Huei Peng
Forecasting trajectories of human-driven vehicles is a crucial problem in autonomous driving. Trajectory forecasting in the urban area is particularly hard due to complex interacti…
Vehicle Energy Dataset (VED), A Large-scale Dataset for Vehicle Energy Consumption Research
G. S. Oh, David J. Leblanc, Huei Peng
We present Vehicle Energy Dataset (VED), a novel large-scale dataset of fuel and energy data collected from 383 personal cars in Ann Arbor, Michigan, USA. This open dataset capture…
Developing Robot Driver Etiquette Based on Naturalistic Human Driving Behavior
Xianan Huang, Songan Zhang, Huei Peng
Automated vehicles can change the society by improved safety, mobility and fuel efficiency. However, due to the higher cost and change in business model, over the coming decades, t…
Efficient Mobility-on-Demand System with Ride-Sharing
Xianan Huang, Huei Peng
An algorithm to cluster mobility-on-demand trips considering road network structure is developed in this paper. The benefits of our network partition algorithm are demonstrated in…
Eco-Routing based on a Data Driven Fuel Consumption Model
Xianan Huang, Huei Peng
A nonparametric fuel consumption model is developed and used for eco-routing algorithm development in this paper. Six months of driving information from the city of Ann Arbor is co…
Enhancing the performance of a safe controller via supervised learning for truck lateral control
Yuxiao Chen, Ayonga Hereid, Huei Peng +1
Correct-by-construction techniques, such as control barrier functions (CBFs), can be used to guarantee closed-loop safety by acting as a supervisor of an existing or legacy control…