Fangce Guo

发表

Prediction Method for a Congestion State in an Urban Road Network Bottleneck

Heng Ding, Liangyuan Zhu, Chengbin Jiang, 2016 .

Short-term traffic prediction under normal and abnormal conditions

Fangce Guo, 2013 .

A computationally efficient 2-satge method for short-term traffic prediction on urban roads

Fangce Guo, Miss Fangce, Guo, 2011 .

Multi-Sensor Fusion Based on the Data from Bus GPS, Mobile Phone and Loop Detectors in Travel Time Estimation

Rajesh Krishnan, John W. Polak, Lin Zhu, 2017 .

Network-scale traffic prediction via knowledge transfer and regional MFD analysis

X. Chen, Fangce Guo, Kaiwen Zhang, 2022, Transportation Research Part C: Emerging Technologies.

An analysis of the value of optimal routing and signal timing control strategy with connected autonomous vehicles

A. Sivakumar, Fangce Guo, R. Krishnan, 2022, Journal of Intelligent Transportation Systems.

Traffic Monitoring and Anomaly Detection based on Simulation of Luxembourg Road Network

John W. Polak, Lin Zhu, Rajesh Krishnan, 2019, 2019 IEEE Intelligent Transportation Systems Conference (ITSC).

Evaluating grid-interactive electric bus operation and demand response with load management tariff

Goran Strbac, J. Polak, Zhentao Wu, 2019 .

Traffic guidance–perimeter control coupled method for the congestion in a macro network

Fang Guo, Weihua Zhang, Heng Ding, 2017 .

Transferability improvement in short-term traffic prediction using stacked LSTM network

Aruna Sivakumar, Fangce Guo, Rajesh Krishnan, 2021, Transportation Research Part C: Emerging Technologies.

A Deep Learning Approach for Traffic Incident Detection in Urban Networks

Rajesh Krishnan, Lin Zhu, John W. Polak, 2018, 2018 21st International Conference on Intelligent Transportation Systems (ITSC).

A computationally efficient two-stage method for short-term traffic prediction on urban roads

Rajesh Krishnan, John W. Polak, Fangce Guo, 2013 .

The influence of alternative data smoothing prediction techniques on the performance of a two-stage short-term urban travel time prediction framework

Rajesh Krishnan, John W. Polak, Fangce Guo, 2017, J. Intell. Transp. Syst..

Early Identification of Recurrent Congestion in Heterogeneous Urban Traffic

John W. Polak, Lin Zhu, Rajesh Krishnan, 2019, 2019 IEEE Intelligent Transportation Systems Conference (ITSC).

Spatial-Temporal Hybrid Deep Neural Networks for Early Congestion Detection Extended

J. Polak, Fangce Guo, R. Krishnan, 2018 .

Right-of-way reallocation for mixed flow of autonomous vehicles and human driven vehicles

John W. Polak, Fangce Guo, Aruna Sivakumar, 2020, Transportation Research Part C: Emerging Technologies.

A Domain Adaptation Framework for Short-term Traffic Prediction

Panagiotis Angeloudis, Simon Hu, Loutao Shen, 2021, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC).

Novel Three-Stage Framework for Short-Term Travel Time Prediction Under Normal and Abnormal Traffic Conditions

Rajesh Krishnan, John W. Polak, Fangce Guo, 2014 .

Short-Term Traffic Prediction Under Normal and Abnormal Traffic Conditions on Urban Roads

Rajesh Krishnan, John W. Polak, Fangce Guo, 2012 .

Predictor fusion for short-term traffic forecasting

Rajesh Krishnan, John W. Polak, Fangce Guo, 2018, Transportation Research Part C: Emerging Technologies.

Urban link travel time estimation using traffic states based data fusion

Rajesh Krishnan, John W. Polak, Lin Zhu, 2018 .

Few-Shot traffic prediction based on transferring prior knowledge from local network

A. Sivakumar, Sisi Jian, Fangce Guo, 2023, Transportmetrica B: Transport Dynamics.

Short-term Traffic Prediction with Deep Neural Networks and Adaptive Transfer Learning

Yibing Wang, Xiaoxiang Na, Simon Hu, 2020, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC).

Modular Bus Unit Scheduling for an Autonomous Transit System under Range and Charging Constraints

Fangce Guo, Jiangbo Wang, Kai Liu, 2023, Applied Sciences.