| Multivariate random parameters zero-inflated negative binomial regression for analyzing urban midblock crashes C Liu, M Zhao, W Li, A Sharma Analytic Methods in Accident Research 17, 32-46, 2018 | 59 | 2018 |
| Multivariate Poisson-lognormal model for analysis of crashes on urban signalized intersections approach M Zhao, C Liu, W Li, A Sharma Journal of Transportation Safety & Security 10 (3), 251-265, 2018 | 35 | 2018 |
| Traffic dynamics exploration and incident detection using spatiotemporal graphical modeling C Liu, M Zhao, A Sharma, S Sarkar Journal of Big Data Analytics in Transportation 1, 37-55, 2019 | 19 | 2019 |
| Data driven exploration of traffic network system dynamics using high resolution probe data C Liu, B Huang, M Zhao, S Sarkar, U Vaidya, A Sharma 2016 IEEE 55th Conference on Decision and Control (CDC), 7629-7634, 2016 | 15 | 2016 |
| Traffic information forecast algorithm based on the one-dimension cloud model SW Yu, K Cao, M Zhao Journal of Shandong University (Engineering Science) 37 (2), 121-126, 2007 | 9 | 2007 |
| Improving interstate freeway travel time reliability analysis by clustering travel time distributions X Zhang, M Zhao, J Appiah, MD Fontaine Transportation research record 2675 (10), 566-577, 2021 | 8 | 2021 |
| Examination of Features Correlated With Roadway Departure Crashes on Rural Roads J Appiah, M Zhao Virginia. Dept. of Transportation, 2020 | 8 | 2020 |
| Safety and Operational Analysis of Lane Widths in Mid-Block Segments and Intersection Approaches in the Urban Environment in Nebraska A Sharma, W Li, M Zhao, L Rilett | 7 | 2015 |
| Economic analysis of using a renewable wind power system at a signalized intersection M Zhao, A Sharma, DG Bernt, JA Meyer, B Dickey, S Rosenbaugh, ... Journal of Intelligent Transportation Systems 17 (3), 210-220, 2013 | 7 | 2013 |
| Methods to Analyze and Predict Interstate Travel Time Reliability X Zhang, M Zhao, J Appiah, MD Fontaine Virginia Transportation Research Council (VTRC), 2021 | 6 | 2021 |
| Traffic Speed Prediction for Urban Arterial Roads Using Deep Neural Networks Y Adu-Gyamfi, M Zhao International Conference on Transportation and Development, 85, 2018 | 5 | 2018 |
| Real-time traffic prediction using AOSVR and cloud model M Zhao, K Cao, S Ho 2007 IEEE Intelligent Transportation Systems Conference, 485-489, 2007 | 5 | 2007 |
| Design of real-time traffic information prediction and simulation system based on aosvr and on-line learning C Kai, Z Mo 2006 IEEE International Conference on Vehicular Electronics and Safety, 189-193, 2006 | 5 | 2006 |
| Effect of narrower lane width on traffic operations for urban midblock segments M Zhao, C Liu, W Li, A Sharma | 4 | 2017 |
| Powering Traffic Intersections with Wind and Solar Energy M Zhao, A Sharma Climate Change, Energy, Sustainability and Pavements, 455-480, 2014 | 4 | 2014 |
| Prediction of travel time reliability on interstates using linear quantile mixed models X Zhang, M Zhao, J Appiah, MD Fontaine Transportation research record 2677 (2), 774-791, 2023 | 3 | 2023 |
| Cost of Congestion Due to Incidents on Freeways CL Lan, M Zhao, N Goodall, J Gillespie Virginia Transportation Research Council (VTRC), 2021 | 3 | 2021 |
| Implementation of Arterial Bottleneck Characterization Methods in Virginia M Zhao, R Venkatanarayana Virginia Transportation Research Council (VTRC), 2020 | 3 | 2020 |
| Improving the Identification and Characterization of Arterial Congestion Bottlenecks M Zhao, R Venkatanarayana Virginia Transportation Research Council, 2019 | 3 | 2019 |
| Case Studies of Successful “Big Data” Programs at State Departments of Transportation M Zhao, MD Fontaine, R Venkatanarayana Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018 | 3 | 2018 |
