30 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of MichiganUS12 papers
- Chalmers University of TechnologySE3 papers
- Tsinghua UniversityCN2 papers
- University of Michigan–DearbornUS2 papers
- Virginia TechUS2 papers
- Beijing National Research Center for Information Science and TechnologyCN1 paper
- California University of PennsylvaniaUS1 paper
- Carnegie Mellon UniversityUS1 paper
- DEVCOM Army Research LaboratoryUS1 paper
- Eunice Kennedy Shriver National Institute of Child Health and Human DevelopmentUS1 paper
- Insurance Institute for Highway SafetyUS1 paper
- Massachusetts Institute of TechnologyUS1 paper
16 papers
Advanced Assistance for Traffic Crash Analysis: An AI-Driven Multi-Agent Approach to Pre-Crash Reconstruction
Gerui Xu, Boyou Chen, Huizhong Guo +6
Traffic collision reconstruction traditionally relies on human expertise and can be accurate, but pre-crash reconstruction is more challenging. This study develops a multi-agent AI…
Assessing the Effectiveness of Driver Training Interventions in Improving Safe Engagement with Vehicle Automation Systems
Chengxin Zhang, Huizhong Guo, Zifei Wang +3
This study investigates how targeted training interventions can improve safe driver interaction with vehicle automation (VA) systems, focusing on Adaptive Cruise Control (ACC) and…
Mcity Data Engine: Iterative Model Improvement Through Open-Vocabulary Data Selection
Daniel Bogdoll, Rajanikant Patnaik Ananta, Abeyankar Giridharan +3
With an ever-increasing availability of data, it has become more and more challenging to select and label appropriate samples for the training of machine learning models. It is esp…
RAVE Checklist: Recommendations for Overcoming Challenges in Retrospective Safety Studies of Automated Driving Systems
John M. Scanlon, Eric R. Teoh, David G. Kidd +12
The public, regulators, and domain experts alike seek to understand the effect of deployed SAE level 4 automated driving system (ADS) technologies on safety. The recent expansion o…
Active sampling: A machine-learning-assisted framework for finite population inference with optimal subsamples
Henrik Imberg, Xiaomi Yang, Carol Flannagan +1
Data subsampling has become widely recognized as a tool to overcome computational and economic bottlenecks in analyzing massive datasets. We contribute to the development of adapti…
Adaptive Safety Evaluation for Connected and Automated Vehicles with Sparse Control Variates
Jingxuan Yang, Haowei Sun, Honglin He +3
Safety performance evaluation is critical for developing and deploying connected and automated vehicles (CAVs). One prevailing way is to design testing scenarios using prior knowle…
A Probabilistic Framework for Estimating the Risk of Pedestrian-Vehicle Conflicts at Intersections
Pei Li, Huizhong Guo, Shan Bao +1
Pedestrian safety has become an important research topic among various studies due to the increased number of pedestrian-involved crashes. To evaluate pedestrian safety proactively…
A Continual Learning Framework for Adaptive Defect Classification and Inspection
Wenbo Sun, Raed Al Kontar, Judy Jin +1
Machine-vision-based defect classification techniques have been widely adopted for automatic quality inspection in manufacturing processes. This article describes a general framewo…
Multitasking additional-to-driving: Prevalence, structure, and associated risk in SHRP2 naturalistic driving data
András Bálint, Carol A. C. Flannagan, Andrew Leslie +3
This paper 1) analyzes the extent to which drivers engage in multitasking additional-to-driving (MAD) under various conditions, 2) specifies odds ratios (ORs) of crashing associate…
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…
Evaluation of the Energy Efficiency in a Mixed Traffic with Automated Vehicles and Human Controlled Vehicles
Xun Gong, Yaohui Guo, Yiheng Feng +2
The energy efficiency of Connected and Automated Vehicles (CAVs) is significantly influenced by surrounding road users. This paper presents the evaluation of energy efficiency of C…
Energy Efficiency and Emission Testing for Connected and Automated Vehicles Using Real-World Driving Data
Yan Chang, Weiqing Yang, Ding Zhao
By using the onboard sensing and external connectivity technology, connected and automated vehicles (CAV) could lead to improved energy efficiency, better routing, and lower traffi…
Global Brain Dynamics During Social Exclusion Predict Subsequent Behavioral Conformity
Nick Wasylyshyn, Brett Hemenway, Javier O. Garcia +6
Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt…
Evaluation of Automated Vehicles Encountering Pedestrians at Unsignalized Crossings
Baiming Chen, Ding Zhao, Huei Peng
Interactions between vehicles and pedestrians have always been a major problem in traffic safety. Experienced human drivers are able to analyze the environment and choose driving s…
The Impact of Road Configuration on V2V-based Cooperative Localization
Macheng Shen, Ding Zhao, Jing Sun
Cooperative localization with map matching has been shown to reduce Global Navigation Satellite System (GNSS) localization error from several meters to sub-meter level by fusing th…
Accelerated Evaluation of Automated Vehicles in Car-Following Maneuvers
Ding Zhao, Xianan Huang, Huei Peng +2
The safety of Automated Vehicles (AVs) must be assured before their release and deployment. The current approach to evaluation relies primarily on (i) testing AVs on public roads o…