397 citations · 951 across the 17 of their papers we have counts for
18 papers
Smart City Drivers and Challenges in Urban-Mobility, Health-Care, and Interdependent Infrastructure Systems
Amro M. Farid, Muhannad Alshareef, Parupkar Singh Badhesha +11
At the turn of the 21st century, urban development has experienced a paradigm shift so that the quest for smarter cities has become a priority agenda, with the direct participation…
Edge Computing for Real-Time Near-Crash Detection for Smart Transportation Applications
Ruimin Ke, Zhiyong Cui, Yanlong Chen +3
Traffic near-crash events serve as critical data sources for various smart transportation applications, such as being surrogate safety measures for traffic safety research and corn…
Traffic Performance Score for Measuring the Impact of COVID-19 on Urban Mobility
Zhiyong Cui, Meixin Zhu, Shuo Wang +5
Measuring traffic performance is critical for public agencies who manage traffic and individuals who plan trips, especially when special events happen. The COVID-19 pandemic has si…
Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network for Forecasting Network-wide Traffic State with Missing Values
Zhiyong Cui, Ruimin Ke, Ziyuan Pu +1
Short-term traffic forecasting based on deep learning methods, especially recurrent neural networks (RNN), has received much attention in recent years. However, the potential of RN…
A Smart, Efficient, and Reliable Parking Surveillance System with Edge Artificial Intelligence on IoT Devices
Ruimin Ke, Yifan Zhuang, Ziyuan Pu +1
Cloud computing has been a main-stream computing service for years. Recently, with the rapid development in urbanization, massive video surveillance data are produced at an unprece…
Graph Markov Network for Traffic Forecasting with Missing Data
Zhiyong Cui, Longfei Lin, Ziyuan Pu +1
Traffic forecasting is a classical task for traffic management and it plays an important role in intelligent transportation systems. However, since traffic data are mostly collecte…
Road Surface Friction Prediction Using Long Short-Term Memory Neural Network Based on Historical Data
Ziyuan Pu, Shuo Wang, Chenglong Liu +2
Road surface friction significantly impacts traffic safety and mobility. A precise road surface friction prediction model can help to alleviate the influence of inclement road cond…
Mining Public Transit Ridership Flow and Origin-Destination Information from Wi-Fi and Bluetooth Sensing Data
Ziyuan Pu, Meixin Zhu, Zhiyong Cui +1
Transit ridership flow and origin-destination (O-D) information is essential for enhancing transit network design, optimizing transit route and improving service. The effectiveness…
Time-Aware Gated Recurrent Unit Networks for Road Surface Friction Prediction Using Historical Data
Ziyuan Pu, Zhiyong Cui, Shuo Wang +2
An accurate road surface friction prediction algorithm can enable intelligent transportation systems to share timely road surface condition to the public for increasing the safety…
Traffic Sign Detection and Recognition for Autonomous Driving in Virtual Simulation Environment
Meixin Zhu, Jingyun Hu, Ziyuan Pu +3
This study developed a traffic sign detection and recognition algorithm based on the RetinaNet. Two main aspects were revised to improve the detection of traffic signs: image cropp…
Personalized Context-Aware Multi-Modal Transportation Recommendation
Meixin Zhu, Jingyun Hu, Hao +3
This study proposes to find the most appropriate transport modes with awareness of user preferences (e.g., costs, times) and trip characteristics (e.g., purpose, distance). The wor…
Two-Stream Multi-Channel Convolutional Neural Network (TM-CNN) for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact
Ruimin Ke, Wan Li, Zhiyong Cui +1
Traffic speed prediction is a critically important component of intelligent transportation systems (ITS). Recently, with the rapid development of deep learning and transportation d…
Forecasting Transportation Network Speed Using Deep Capsule Networks with Nested LSTM Models
Xiaolei Ma, Yi Li, Zhiyong Cui +1
Accurate and reliable traffic forecasting for complicated transportation networks is of vital importance to modern transportation management. The complicated spatial dependencies o…
Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism
Zhengchao Zhang, Meng Li, Xi Lin +2
Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications. To capture the complex non-stationary temporal dynami…
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
Zhiyong Cui, Kristian Henrickson, Ruimin Ke +2
Traffic forecasting is a particularly challenging application of spatiotemporal forecasting, due to the time-varying traffic patterns and the complicated spatial dependencies on ro…
A Deep Generative Adversarial Architecture for Network-Wide Spatial-Temporal Traffic State Estimation
Yunyi Liang, Zhiyong Cui, Yu Tian +2
This study proposes a deep generative adversarial architecture (GAA) for network-wide spatial-temporal traffic state estimation. The GAA is able to combine traffic flow theory with…
Deep Bidirectional and Unidirectional LSTM Recurrent Neural Network for Network-wide Traffic Speed Prediction
Zhiyong Cui, Ruimin Ke, Ziyuan Pu +1
Short-term traffic forecasting based on deep learning methods, especially long short-term memory (LSTM) neural networks, has received much attention in recent years. However, the p…
Plug-in Electric Vehicle Charging Congestion Analysis Using Taxi Travel Data in the Central Area of Beijing
Huimiao Chen, Hongcai Zhang, Zechun Hu +3
Recharging a plug-in electric vehicle is more time-consuming than refueling an internal combustion engine vehicle. As a result, charging stations may face serious congestion proble…