A deep learning approach for traffic incident detection in urban networks L Zhu, F Guo, R Krishnan, JW Polak 2018 21st international conference on intelligent transportation systems …, 2018 | 48 | 2018 |
Urban link travel time estimation using traffic states‐based data fusion L Zhu, F Guo, JW Polak, R Krishnan IET Intelligent Transport Systems 12 (7), 651-663, 2018 | 31 | 2018 |
Traffic monitoring and anomaly detection based on simulation of luxembourg road network L Zhu, R Krishnan, A Sivakumar, F Guo, JW Polak 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 382-387, 2019 | 19 | 2019 |
The use of convolutional neural networks for traffic incident detection at a network level L Zhu, F Guo, R Krishnan, JW Polak Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018 | 19 | 2018 |
Early identification of recurrent congestion in heterogeneous urban traffic L Zhu, R Krishnan, F Guo, JW Polak, A Sivakumar 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 4392-4397, 2019 | 12 | 2019 |
Multi-Sensor Fusion Based on the Data from Bus GPS, Mobile Phone and Loop Detectors in Travel Time Estimation L Zhu, F Guo, JW Polak, R Krishnan Transportation Research Board 96th Annual MeetingTransportation Research Board, 2017 | 2 | 2017 |
Spatio-temporal traffic anomaly detection for urban networks L Zhu Imperial College London, 2019 | | 2019 |
Spatial-Temporal Hybrid Deep Neural Networks for Early Congestion Detection L Zhu, F Guo, R Krishnan, JW Polak 7th Symposium of the European Association for Research in Transportation (hEART), 2018 | | 2018 |