Short-term traffic forecasting: Where we are and where we’re going EI Vlahogianni, MG Karlaftis, JC Golias Transportation Research Part C: Emerging Technologies 43, 3-19, 2014 | 1282 | 2014 |
Statistical methods versus neural networks in transportation research: Differences, similarities and some insights MG Karlaftis, EI Vlahogianni Transportation Research Part C: Emerging Technologies 19 (3), 387–399, 2011 | 1061 | 2011 |
Optimized and meta-optimized neural networks for short-term traffic flow prediction: A genetic approach EI Vlahogianni, MG Karlaftis, JC Golias Transportation Research Part C: Emerging Technologies 13 (3), 211-234, 2005 | 801 | 2005 |
Short‐term traffic forecasting: Overview of objectives and methods EI Vlahogianni, JC Golias, MG Karlaftis Transport reviews 24 (5), 533-557, 2004 | 730 | 2004 |
Road traffic forecasting: Recent advances and new challenges I Lana, J Del Ser, M Velez, EI Vlahogianni IEEE Intelligent Transportation Systems Magazine 10 (2), 93-109, 2018 | 367 | 2018 |
Unmanned Aerial Aircraft Systems for transportation engineering: Current practice and future challenges EN Barmpounakis, EI Vlahogianni, JC Golias International Journal of Transportation Science and Technology 5 (3), 111-122, 2016 | 284 | 2016 |
A real-time parking prediction system for smart cities EI Vlahogianni, K Kepaptsoglou, V Tsetsos, MG Karlaftis Journal of Intelligent Transportation Systems 20 (2), 192-204, 2016 | 267 | 2016 |
Overview of critical risk factors in Power-Two-Wheeler safety EI Vlahogianni, G Yannis, JC Golias Accident Analysis & Prevention 49, 12-22, 2012 | 194 | 2012 |
Innovative motor insurance schemes: A review of current practices and emerging challenges DI Tselentis, G Yannis, EI Vlahogianni Accident Analysis & Prevention 98, 139-148, 2017 | 171 | 2017 |
Spatio‐temporal short‐term urban traffic volume forecasting using genetically optimized modular networks EI Vlahogianni, MG Karlaftis, JC Golias Computer‐Aided Civil and Infrastructure Engineering 22 (5), 317-325, 2007 | 166 | 2007 |
Statistical methods for detecting nonlinearity and non-stationarity in univariate short-term time-series of traffic volume EI Vlahogianni, MG Karlaftis, JC Golias Transportation Research Part C: Emerging Technologies 14 (5), 351-367, 2006 | 153 | 2006 |
Driving analytics using smartphones: Algorithms, comparisons and challenges EI Vlahogianni, EN Barmpounakis Transportation Research Part C: Emerging Technologies 79, 196-206, 2017 | 148 | 2017 |
Innovative insurance schemes: pay as/how you drive DI Tselentis, G Yannis, EI Vlahogianni Transportation Research Procedia 14, 362-371, 2016 | 118 | 2016 |
Memory properties and fractional integration in transportation time-series MG Karlaftis, EI Vlahogianni Transportation Research Part C: Emerging Technologies 17 (4), 444-453, 2009 | 118 | 2009 |
Temporal evolution of short‐term urban traffic flow: a nonlinear dynamics approach EI Vlahogianni, MG Karlaftis, JC Golias Computer‐Aided Civil and Infrastructure Engineering 23 (7), 536-548, 2008 | 113 | 2008 |
Metaheuristics for the transit route network design problem: a review and comparative analysis C Iliopoulou, K Kepaptsoglou, E Vlahogianni Public Transport 11, 487-521, 2019 | 104 | 2019 |
Modeling duration of overtaking in two lane highways EI Vlahogianni Transportation research part F: traffic psychology and behaviour 20, 135-146, 2013 | 99 | 2013 |
Modeling the effects of weather and traffic on the risk of secondary incidents EI Vlahogianni, MG Karlaftis, FP Orfanou Journal of Intelligent Transportation Systems 16 (3), 109-117, 2012 | 97 | 2012 |
Fuzzy‐entropy neural network freeway incident duration modeling with single and competing uncertainties EI Vlahogianni, MG Karlaftis Computer‐Aided Civil and Infrastructure Engineering 28 (6), 420-433, 2013 | 91 | 2013 |
Freeway operations, spatiotemporal-incident characteristics, and secondary-crash occurrence EI Vlahogianni, MG Karlaftis, JC Golias, BM Halkias Transportation research record 2178 (1), 1-9, 2010 | 84 | 2010 |