Xuegang Ban

· William M. and Marilyn M. Conner Endowed Professor

University of Washington · Civil & Environmental Engineering

Active 2002–2025

h-index43

Citations5.8k

Papers20053 last 5y

Funding$1.7M1 active

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Xuegang Ban is the William M. and Marilyn M. Conner Endowed Professor in Civil & Environmental Engineering at the University of Washington. His research areas include infrastructure and smart cities, transportation engineering, transportation network system modeling and simulation, urban traffic system modeling and operations, and intelligent transportation systems. His work focuses on developing innovative solutions for urban transportation challenges, leveraging advanced modeling techniques to improve traffic flow, safety, and sustainability in urban environments.

Research topics

Computer Science
Engineering
Artificial Intelligence
Automotive engineering
Transport engineering
Computer network
Mathematics
Structural engineering
Simulation
Mathematical optimization

Selected publications

Hybrid deep reinforcement learning based eco-driving for low-level connected and automated vehicles along signalized corridors
Transportation Research Part C Emerging Technologies · 2021 · 144 citations
Senior authorCorresponding
DOI
Mixed traffic flow of human driven vehicles and automated vehicles on dynamic transportation networks
Transportation Research Part C Emerging Technologies · 2021 · 76 citations
DOI
Macroscopic fundamental diagram based perimeter control considering dynamic user equilibrium
Transportation Research Part B Methodological · 2020 · 60 citations
Senior authorCorresponding
DOI
Data poisoning attacks in intelligent transportation systems: A survey
Transportation Research Part C Emerging Technologies · 2024-07-10 · 36 citations
articleSenior authorCorresponding
Publisher DOI
Connected Vehicle Data-Driven Fixed-Time Traffic Signal Control Considering Cyclic Time-Dependent Vehicle Arrivals Based on Cumulative Flow Diagram
IEEE Transactions on Intelligent Transportation Systems · 2024-02-14 · 32 citations
article
Fixed-time control is a widely adopted and cost-effective method for signalized intersections. However, existing studies utilizing connected vehicle (CV) data have not effectively addressed fixed-time control due to their reliance on specific vehicle arrival assumptions. To overcome this limitation, this study presents a novel traffic control approach for fixed-time signalized intersections based on a cumulative flow diagram (CFD) framework. The proposed method comprises a CFD model and a multi-…
Publisher DOI

Recent grants

Collaborative Research: Transportation Network Identification: Information Fusion via Stochastic Optimization
NSF · $148k · 2016–2018
Collaborative Research: Data Poisoning Attacks and Infrastructure-Enabled Solutions for Traffic State Estimation and Prediction
NSF · $346k · 2023–2027
CAREER: Using Mobile Sensors for Traffic Knowledge Extraction and Dynamic Network Management
NSF · $412k · 2011–2017

Frequent coauthors

Henry Liu
27 shared
Li Wan
22 shared
Feilong Wang
19 shared
Qiangqiang Guo
First Affiliated Hospital of Soochow University
16 shared
Zhanbo Sun
16 shared
Bin Ran
University of Wisconsin–Madison
15 shared
Jingxing Wang
15 shared
Xiaoyuan Wang
Lanzhou University Second Hospital
14 shared

Awards & honors

NSF CAREER Award (2011)
New Faculty Award, Council of Transportation Research Center…
School of Engineering Research Excellence Award (Junior Facu…
UTRC’s 2008 Best Paper Award, University of Transportation R…

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