Leilei Cui Leilei Cui is a Ph.D. student at the New York University Tandon School of Engineering, advised by Professor Zhong-Ping Jiang at the Control and Networks Lab (CANLab). His research interests include reinforcement learning, adaptive dynamic programming, control theory, and applications to robotics and transportation. Prior to joining NYU Tandon, Leilei received his bachelor’s…
Tong Liu Tong Liu received a bachelor’s degree in rail traffic signal and control in 2017 and a master’s degree in traffic information engineering and control in 2020 both from Beijing Jiaotong University. Now he is working towards the Ph.D. degree in electrical engineering at NYU Tandon School of Engineering advised by Professor Zhong-Ping Jiang.…
Understanding, Modeling and Presenting the Impact of Various Endogenous & Exogenous Factors on Mobility in New York City Overview The multi-modal nature of transportation in NYC presents choices to users such as fixed-route public transit systems (e.g., subway and bus), on-demand taxi, and bike-sharing (e.g., Citibike). However, the usage of each of these modes depends…
Integration and Operation of an Advanced Weigh-in-Motion (A-WIM) System for Autonomous Enforcement of Overweight Trucks Overview Roadways in New York City handle substantial daily traffic throughout different boroughs. Trucks have been an integral part of the freight movement network in distributing goods and services to various communities; however, a percentage of these trucks are often…
A Comprehensive Analysis of the Air Quality in the NYC Subway System Overview Exposure to ambient particulate matter (PM) air pollution is one of the leading risk factors for global disease burden, including respiratory, cardiovascular, metabolic, and mental health disorders. These include asthma, heart disease, diabetes, as well as bipolar disorder, and anxiety. The mechanism…
Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed Overview Cities like NYC and Seattle need to deal with significant growth of urban deliveries as a result of increasing e-commerce compounded by increased stay-at-home behavior due to COVID-19. Even with the production of vaccines and a return to “normality” in the next…
Autonomous Vehicle Good Citizenry Standard Overview New York City is moving toward a more efficient, safer, and sustainable future that includes autonomous vehicles for transit, e-commerce, and medical transport. However, autonomy often runs on incomplete or flawed foundations: training data sets might not prepare vehicles to “see” people of color; transit shuttles may operate without…
Evaluating Remote Repositioning for Shared Scooters Overview Utilization of vehicles, commonly measured in trips per vehicle per day, is a key to economic and environmental sustainability of shared micromobility (i.e. bikeshare and scootershare) services. With large capital costs tied up in bikes or scooters, a micromobility operator needs its vehicles to be used frequently to…
Lane Changing of Autonomous Vehicles in Mixed Traffic Environments: A Reinforcement Learning Approach Overview According to an accident report from Volvo, lane changing maneuver is the main cause of various severe highway accidents, due to human drivers’ inaccurate estimation and prediction of the surrounding traffic, illegal maneuver, and inefficient driving skill. Autonomous driving is regarded…
Deployment and Tech Transfer of a Street-level Flooding Platform: Sensing and Data Sharing for Urban Accessibility and Resilience Overview Of the myriad impacts that are predicted to accompany climate change, flooding is expected to have an outsized influence on public health, infrastructure, and mobility in urban areas. In New York City, for example, sea-level rise…