Ewert, R. (2019). Modellierung und Simulation des städtischen Abfallwirtschaftsverkehrs am Beispiel Berlins. TU Berlin, Institute for Land and Sea Transport Systems

Thunig, T., Kühnel, N. and Nagel, K. (2019). Adaptive traffic signal control for real-world scenarios in agent-based transport simulations. Transportation Research Procedia. Elsevier BV, 481–488.

Thunig, T. and Nagel, K. (2019). Effects of user adaption on traffic-responsive signal control in agent-based transport simulations. 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), 1–7.

Thunig, T., Scheffler, R., Strehler, M. and Nagel, K. (2019). Optimization and simulation of fixed-time traffic signal control in real-world applications. Procedia Computer Science. Elsevier BV, 826–833.

Ziemke, D., Agarwal, A. and Kaddoura, I. (2019). Entwicklung eines regionalen, agentenbasierten Verkehrssimulationsmodells zur Analyse von Mobilitätszenarien für die Region Ruhr. 10. Wissenschaftsforum Mobilität : Mobility in Times of Change – Past, Present, Future. Springer Gabler, Wiesbaden, 383–410.

Ziemke, D., Kaddoura, I. and Nagel, K. (2019). The MATSim Open Berlin Scenario: A multimodal agent-based transport simulation scenario based on synthetic demand modeling and open data. Procedia Computer Science, 870–877.

Kaddoura, I. (2019). Simulated Dynamic Pricing for Transport System Optimization. TU Berlin

Kaddoura, I., Laudan, J., Ziemke, D. and Nagel, K. (2019). Verkehrsmodellierung für das Ruhrgebiet: Simulationsbasierte Szenariountersuchung und Wirkungsanalyse einer verbesserten regionalen Fahrradinfrastruktur.

Kaddoura, I. and Nagel, K. (2019). Congestion pricing in a real-world oriented agent-based simulation context. Research in Transportation Economics, 40–51.

Kuehnel, N., Ziemke, D., Moeckel, R. and Nagel, K. (2019). The end of travel time matrices? Or: why we should use individual travel times.

Kühnel, N., Kaddoura, I. and Möckel (2019). Incorporation of noise shielding in an agent-based transport model by using volunteered geographic data. Procedia Computer Science, 808–813.

Leich, G. and Nagel, K. (2019). Improving speed and realism of an evolutionary minibus network design process. Procedia Computer Science. Elsevier BV, 834–839.

Livingston, C., Beyer Bartana, I., Ziemke, D. and Bahamonde-Birke, F. (2019). The Influence of the Route Environment on the Route Choice of Bicyclists – A Preliminary Study.

Singh, D., Padgham, L. and Nagel, K. (2019). Using MATSim as a Component in Dynamic Agent-based Micro-Simulations.

Márquez-Fernández, F. J. A. D.-O. A. B. J. A. A. M. (2019). Using Multi-Agent Transport Simulations to assess the impact of EVcharging infrastructure deployment. IEEE Transportation Electrification Conference and Expo (upcoming)