collaborators

13 papers

cs.LG2026

Deep learning-based pavement performance modeling using multiple distress indicators and road work history

Lu Gao, Zhe Han, Yunshen Chen

The deterioration of pavement is a complex and dynamic process determined by different factors including material, environment, design, and some other unobserved variables. Accurat…

cs.CV2026

Estimating the Impact of COVID-19 on Travel Demand in Houston Area Using Deep Learning and Satellite Imagery

Alekhya Pachika, Lu Gao, Lingguang Song +2

Considering recent advances in remote sensing satellite systems and computer vision algorithms, many satellite sensing platforms and sensors have been used to monitor the condition…

cs.LG2026

Pavement Missing Condition Data Imputation through Collective Learning-Based Graph Neural Networks

Ke Yu, Lu Gao

Pavement condition data is important in providing information regarding the current state of the road network and in determining the needs of maintenance and rehabilitation treatme…

stat.AP2026

Network-Level Travel Time Prediction Considering The Effects of Weather and Seasonality

Yufei Ai, Yao Yu, Wenjing Pu +2

Accurately predicting travel time information can be helpful for travelers. This study proposes a framework for predicting network-level travel time index (TTI) using machine learn…

stat.AP2026

Evaluating the Impact of COVID-19 on Transportation Infrastructure Funding

Lu Gao, Pan Lu, Fengxiang Qiao +3

The coronavirus disease 2019 (COVID-19) pandemic has caused a reduction in business and routine activity and resulted in less motor fuel consumption. Thus, the gas tax revenue is r…

cs.CR2026

Assessing Cybersecurity Risks and Traffic Impact in Connected Autonomous Vehicles

Saurav Silwal, Lu Gao, Ph. D. Yunpeng Zhang +4

Given the promising future of autonomous vehicles, it is foreseeable that self-driving cars will soon emerge as the predominant mode of transportation. While autonomous vehicles of…