Our work is to produce new insights into device-edge-cloud data-driven communicating frameworks and future transportation services, build digital replicas of real-world entities based on AI, big data, cloud/edge computing, and mixed reality. Our goal aims to create an environment with freedom and inclusion to explore newly generating thoughts and make outstanding contributions to our field or even the whole industry.
Our lab is currently seeking candidates for various positions including PhD, MS, and BS students, as well as remote-friendly interns. If you are interested, please send your resume or CV to ziran@purdue.edu with the email title "[Position] Application-[Full Name]". Professor Wang can fund and supervise prospective students in Civil Engineering, Electrical and Computer Engineering, and Mechanical Engineering at Purdue University.
Our three papers "Quantifying Uncertainty in Motion Prediction with Variational Bayesian Mixture", "LaMPilot: An Open Benchmark Dataset for Autonomous Driving with Language Model Programs", and "MAPLM: A Real-World Large-Scale Vision-Language Dataset for Map and Traffic Scene Understanding" were accepted to the 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
Professor Ziran Wang served as the program chair of the 4th IEEE Forum for Innovative Sustainable Transportation Systems, held in Riverside, CA.
We hosted Dr. Yin Zhou from Waymo for a campus visit at Purdue University.
Our three papers "Driver Digital Twin for Online Recognition of Distracted Driving Behaviors", "REDFormer: Radar Enlightens the Darkness of Camera Perception with Transformers", and "Federated learning for connected and automated vehicles: A survey of existing approaches and challenges" were published on IEEE Transactions on Intelligent Vehicles (IF=8.2).
We attended the Transportation Research Board (TRB) 103rd Annual Meeting in Washington D.C. and presented three posters highlighting our work.
We presented three papers and organized the 1st Workshop on Large Language and Vision Models for Autonomous Driving (LLVM-AD) at 2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) in Waikoloa, Hawaii.
Our paper "Eco-approach at an isolated actuated signalized intersection: Aware of the passing time window" was published in the Journal of Cleaner Production (IF = 11.1).
Our chapter "Cloud and Edge Computing for Connected and Automated Vehicles" was published in the Foundations and TrendsĀ® in Electronic Design Automation.
We presented a paper and organized the 1st Workshop on Digital Twins at the 2023 ACM/IEEE Symposium on Edge Computing in Wilmington, Delaware.
We hosted Dr. Ali Borhan from Cummins for a campus visit at Purdue University.
We hosted Dr. Masayoshi Tomizuka from the University of California, Berkeley for a campus visit at Purdue University.
We hosted the second special session on "Cooperative Driving in Mixed Traffic" at the IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain.
Our lab was selected as one of the Autoware Foundation Centers of Excellence. More information can be found here.
Our lab was featured in the Fall 2023 issue of Purdue University Lyles School of Civil Engineering Impact Magazine. You can read the article here.
We hosted Anthony Gregory, Vice President of Cruise, at Purdue University, where meaningful discussions were held.
Our three papers "Radar Enlighten the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion", "CEMFormer: Learning to Predict Driver Intentions from In-Cabin and External Cameras via Spatial-Temporal Transformers", and "A Survey of Federated Learning for Connected and Automated Vehicles" were accepted to IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain.
We serve as organization committee members for the Transportation Research Board Conference on Innovations in Travel Analysis and Planning in Indianapolis, IN.
Our Ph.D. student Yunsheng Ma delivered a presentation at the 3rd Annual Conference on Next-Generation Transport Systems (NGTS-3) and received the Outstanding Speaker Award!
Our two papers "Multi-View Multi-Scale Driver Action Recognition with Vision Transformer" and "Peer-to-Peer Federated Continual Learning for Naturalistic Driving Action Recognition" were accepted to 2023 IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR) Workshops in Vancouver, Canada.
A demo shows the advanced features of our Talk2Drive framework.
Prof. Wang was invited for a talk and panel discussion at the Digital Twins Symposium organized by Purdue Rosen Center for Advanced Computing (RCAC).
A talk at Purdue in Oct. 2022 that summarizes our work during the past five years.