| Estimating historical hourly traffic volumes via machine learning and vehicle probe data: A Maryland case study P Sekuła, N Marković, Z Vander Laan, KF Sadabadi Transportation Research Part C: Emerging Technologies 97, 147-158, 2018 | 70 | 2018 |
| Operational performance of a congested corridor with lanes dedicated to autonomous vehicle traffic Z Vander Laan, KF Sadabadi International Journal of Transportation Science and Technology 6 (1), 42-52, 2017 | 67 | 2017 |
| Applications of trajectory data from the perspective of a road transportation agency: Literature review and maryland case study N Marković, P Sekuła, Z Vander Laan, G Andrienko, N Andrienko IEEE Transactions on Intelligent Transportation Systems 20 (5), 1858-1869, 2018 | 51* | 2018 |
| Estimating hourly traffic volumes using artificial neural network with additional inputs from automatic traffic recorders S Zahedian, P Sekuła, A Nohekhan, Z Vander Laan Transportation Research Record 2674 (3), 272-282, 2020 | 23 | 2020 |
| Scaling GPS trajectories to match point traffic counts: A convex programming approach and Utah case study S Miller, Z Vander Laan, N Marković Transportation Research Part E: Logistics and Transportation Review 143, 102105, 2020 | 15 | 2020 |
| Modeling heterogeneous traffic with cooperative adaptive cruise control vehicles: A first-order macroscopic perspective Z Vander Laan, P Schonfeld Transportation planning and technology 43 (2), 113-140, 2020 | 10 | 2020 |
| Scalable framework for enhancing raw GPS trajectory data: application to trip analytics for transportation planning Z Vander Laan, M Franz, N Marković Journal of big data analytics in transportation 3 (2), 119-139, 2021 | 8 | 2021 |
| Predicting work zone collision probabilities via clustering: application in optimal deployment of highway response teams P Sekuła, Z Vander Laan, K Farokhi Sadabadi, MJ Skibniewski Journal of Advanced Transportation 2018 (1), 3179207, 2018 | 4 | 2018 |
| Evaluating Commercial Probe Data Quality on Arterial Facilities: Insights From Multi-Year Cross-Vendor Validation Z Vander Laan, E Sharifi Transportation Research Record 2675 (11), 193-203, 2021 | 3 | 2021 |
| Video analytics usage in transportation agencies: Nationwide survey and Maryland feasibility study ZV Laan, KF Sadabadi, T Jacobs Transportation Research Record 2672 (19), 34-44, 2018 | 3 | 2018 |
| Transferability of a Machine Learning‐Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study P Sekuła, ZV Laan, KF Sadabadi, K Kania, S Zahedian Journal of Advanced Transportation 2021 (1), 9944918, 2021 | 1 | 2021 |
| Visual exploration of Utah trajectory data and their applications in transportation N Markovic, S Miller, ZV Laan, Y Wang National Institute for Transportation and Communities (NITC), 2020 | 1 | 2020 |
| Visual exploration of Utah trajectory data and their applications in transportation S Miller, Z Vander Laan, Y Wang, N Markovic | 1 | 2020 |
| Application of vehicle probe data in estimating traffic volumes: a Maryland case study P Sekula, N Marković, Z Vander Laan, K Farokhi Sadabadi Transportation Research Board 97th Annual MeetingTransportation Research Board, 2018 | 1 | 2018 |
| I-95 Corridor Coalition Vehicle Probe Project: Update on Validation of Arterial Probe Data Z Vander Laan, E Sharifi I-95 Corridor Coalition Vehicle Probe Project, 2019 | | 2019 |
| Acquiring Quality Traffic Volume Data Anytime & Anywhere: A Big Data Success Story in the Making S Young, S Mahapatra, Z Vander Laan, C Willoughby 2018 ITS America Annual Meeting Detroit, 2018 | | 2018 |
| Modeling heterogeneous traffic with cooperative adaptive cruise control vehicles: A macroscopic equilibrium approach Z Vander Laan University of Maryland, College Park, 2017 | | 2017 |
