Microsimulation analysis for network traffic assignment (MANTA) at metropolitan-scale for agile transportation planning

References

• AC Transit, Arup, and Cambridge Systematics. 2010. Bay Bridge Corridor Congestion Study, Tech. rep., TJPA.
   Google Scholar
• Auld, J., M. Hope, H. Ley, V. Sokolov, B. Xu, and K. Zhang. March, 2016. “POLARIS: Agent-based Modeling Framework Development and Implementation for Integrated Travel Demand and Network and Operations Simulations.” Transportation Research Part C: Emerging Technologies 64: 101–116.
   Google Scholar
• Axhausen, K. W., and T. Gärling. October, 1992. “Activity-based Approaches to Travel Analysis: Conceptual Frameworks, Models, and Research Problems.” Transport Reviews 12: 323–341.
   Google Scholar
• Barceló, J., and J. Casas. 2005. “Dynamic Network Simulation With AIMSUN.” In Simulation Approaches in Transportation Analysis, Vol. 31, edited by R. Kitamura and M. Kuwahara, 57–98. New York: Springer-Verlag.
   Google Scholar
• Barceló, J., J. L. Ferrer, D. García, M. Florian, and E. L. Saux. 1998. “Parallelization of Microscopic Traffic Simulation for Att Systems Analysis.” In Equilibrium and Advanced Transportation Modelling, edited by P. Marcotte and S. Nguyen, 1–26, Boston, MA: Springer US.
   Google Scholar
• Ben-Akiva, M., M. Bierlaire, H. Koutsopoulos, and R. Mishalani. 1998. “DynaMIT: A simulation-Based System for Traffic Prediction.” In DACCORD Short Term Forecasting Workshop, 12.
   Google Scholar
• Boeing, G. September, 2017. “OSMnx: New Methods for Acquiring, Constructing, Analyzing, and Visualizing Complex Street Networks.” Computers, Environment and Urban Systems 65: 126–139.
   Google Scholar
• Chan, C., B. Wang, J. Bachan, and J. Macfarlane. November, 2018. “Mobiliti: Scalable Transportation Simulation Using High-Performance Parallel Computing.” In 2018 21st International Conference on Intelligent Transportation Systems (ITSC), (Maui, HI), 634–641, IEEE.
   Google Scholar
• Choudhury, C. F., M. E. Ben-Akiva, T. Toledo, G. Lee, and A. Rao. January, 2007. “Modeling Cooperative Lane-Changing and Forced Merging Behavior”.
   Google Scholar
• Csardi, G., and T. Nepusz. 2006. “The Igraph Software Package for Complex Network Research.” InterJournal, Complex Systems 1695 (5): 1–9.
   Google Scholar
• Delling, D., P. Sanders, D. Schultes, and D. Wagner. 2009. “Engineering Route Planning Algorithms.” In Algorithmics of Large and Complex Networks: Design, Analysis, and Simulation, edited by J. Lerner, D. Wagner, and K. A. Zweig, Lecture Notes in Computer Science, 117–139, Berlin, Heidelberg: Springer Berlin Heidelberg.
   Google Scholar
• Dowling, R., A. Skabardonis, and V. Alexiadis. June, 2004. “Traffic Analysis Toolbox, Volume III: Guidelines for Applying Traffic Microsimulation Modeling Software.” Transportation Research Board, FHWA-HRT-04-040.
   Google Scholar
• Garcia-Dorado, I., D. G. Aliaga, and S. V. Ukkusuri. 2014, May. “Designing Large-scale Interactive Traffic Animations for Urban Modeling: Designing Large-scale Interactive Traffic Animations for Urban Modeling.” Computer Graphics Forum 33: 411–420.
   Google Scholar
• Geroliminis, N., and A. Skabardonis. December, 2011. “Identification and Analysis of Queue Spillovers in City Street Networks.” IEEE Transactions on Intelligent Transportation Systems 12: 1107–1115.
   Google Scholar
• Horni, A., K. Nagel, and K. Axhausen, eds. August, 2016. Multi-Agent Transport Simulation MATSim. London: Ubiquity Press.
   Google Scholar
• Iqbal, M. S., C. F. Choudhury, P. Wang, and M. C. González. March, 2014. “Development of Origin–destination Matrices Using Mobile Phone Call Data.” Transportation Research Part C: Emerging Technologies 40: 63–74.
   Google Scholar
• Kim, S. 2012. “Design of the Adaptive Cruise Control Systems: An Optimal Control Approach.” p. 135.
   Google Scholar
• Kokkinogenis, Z., L. S. Passos, R. Rossetti, and J. Gabriel. 2011. “Towards the Next-Generation Traffic Simulation Tools: A First Evaluation.” In Iberian Conference on Information Systems and Technologies, 14.
   Google Scholar
• Kotusevski, G., and K. A. Hawick. 2009. “A Review of Traffic Simulation Software.” Research Letters in the Information and Mathematical Sciences 13: 35–54.
   Google Scholar
• Krajzewicz, D., M. Bonert, and P. Wagner. June, 2006. “The Open Source Traffic Simulation Package SUMO.” In RoboCup 2006, RoboCup 2006.
   Google Scholar
• Loder, A., L. Ambühl, M. Menendez, and K. W. Axhausen. December, 2019. “Understanding Traffic Capacity of Urban Networks.” Scientific Reports 9: 16283.
   Google Scholar
• Maerivoet, S., and B. De Moor. July, 2005. “Transportation Planning and Traffic Flow Models.” arXiv:physics/0507127.
   Google Scholar
• Metropolitan Transportation Commission and Association of Bay Area Governments. 2017. “Plan Bay Area 2040”.
   Google Scholar
• Milam, R. T., M. Birnbaum, C. Ganson, S. Handy, and J. Walters. January, 2017. “Closing the Induced Vehicle Travel Gap Between Research and Practice.” Transportation Research Record: Journal of the Transportation Research Board 2653: 10–16.
   Google Scholar
• Milanés, V., and S. E. Shladover. November, 2014. “Modeling Cooperative and Autonomous Adaptive Cruise Control Dynamic Responses Using Experimental Data.” Transportation Research Part C: Emerging Technologies 48: 285–300.
   Google Scholar
• Nagel, K., and M. Rickert. November, 2001. “Parallel Implementation of the TRANSIMS Micro-simulation.” Parallel Computing 27: 1611–1639.
   Google Scholar
• National Renewable Energy Laboratory. “Transportation Secure Data Center.” https://www.nrel.gov/tsdc.
   Google Scholar
• Park, B. B., and J. D. Schneeberger. January, 2003. “Microscopic Simulation Model Calibration and Validation: Case Study of VISSIM Simulation Model for a Coordinated Actuated Signal System.” Transportation Research Record: Journal of the Transportation Research Board 1856: 185–192.
   Google Scholar
• Saidallah, M., A. El Fergougui, and A. E. Elalaoui. 2016. “A Comparative Study of Urban Road Traffic Simulators.” MATEC Web of Conferences 81: 05002.
   Google Scholar
• Saxena, P., D. Singh, M. Pant, and I. Giannoccaro. 2016, eds. Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications. Advances in Computational Intelligence and Robotics, IGI Global.
   Google Scholar
• Shun, J., and G. E. Blelloch. 2013. “Ligra: A Lightweight Graph Processing Framework for Shared Memory.” In Proceedings of the 18th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming, 135–146.
   Google Scholar
• Technical Activities Division, Transportation Research Board, and National Academies of Sciences, Engineering, and Medicine. July, 2011. Dynamic Traffic Assignment: A Primer. Washington, D.C.: Transportation Research Board.
   Google Scholar
• Toledo, T., H. Koutsopoulos, M. Ben-Akiva, and M. Jha. 2005. “Microscopic Traffic Simulation: Models and Application.” In Simulation Approaches in Transportation Analysis, 99–130. New York: Springer-Verlag.
   Google Scholar
• Treiber, M., and A. Kesting. 2013. Traffic Flow Dynamics: Data, Models and Simulation. Springer Berlin Heidelberg.
   Google Scholar
• Waddell, P. 2002. “UrbanSim Modeling Urban Development for Land Use, Transportation, and Environmental Planning.” Journal of the American Planning Association 68.
   Google Scholar
• Waddell, P., G. Boeing, M. Gardner, and E. Porter. February, 2018. “An Integrated Pipeline Architecture for Modeling Urban Land Use, Travel Demand, and Traffic Assignment.” arXiv:1802.09335 [cs].
   Google Scholar
• Waraich, R. A., D. Charypar, M. Balmer, and K. W. Axhausen. 2015. “Performance Improvements for Large-Scale Traffic Simulation in MATSim.” In Computational Approaches for Urban Environments, edited by M. Helbich, J. Jokar Arsanjani, and M. Leitner, 211–233. Cham: Springer International Publishing.
   Google Scholar
• Yang, Q., and H. N. Koutsopoulos. June, 1996. “A Microscopic Traffic Simulator for Evaluation of Dynamic Traffic Management Systems.” Transportation Research Part C: Emerging Technologies 4: 113–129.
   Google Scholar
• Zhao, B., K. Kumar, G. Casey, and K. Soga. January 2019. “Agent-Based Model (ABM) for City-Scale Traffic Simulation: A Case Study on San Francisco.” In International Conference on Smart Infrastructure and Construction 2019 (ICSIC), 203–212. Cambridge, UK: ICE Publishing.
   Google Scholar