References:

[1] Abdelmagid, A. M., Gheith, M., & Eltawil, A. (2022). Scheduling external trucks appointments in container terminals to minimize cost and truck turnaround times. Logistics, 6(3), 45.
[2] Abu Aisha, T., Ouhimmou, M., & Paquet, M. (2020). Optimization of Container Terminal Layouts in the Seaport—Case of Port of Montreal. Sustainability, 12(3), Article 3. https://doi.org/10.3390/su12031165
[3] Alagesan, V. (2017). Investigating congestion mitigation scenarios to reduce truck turn time at Port of Montreal using Discrete Event Simulation [Masters, Concordia University]. https://spectrum.library.concordia.ca/id/eprint/983258/
[4] Arango-Pastrana, C. A. (2019). A simulation model for the management for containers internal transport in a seaport. Cuadernos de Administración (Universidad Del Valle), 35(64), 96–109.
[5] Augustine, E. O. (2021). Application of Mixed Simulation Method to Modelling Port Traffic.
[6] Azab, A. E., & Eltawil, A. B. (2016). A Simulation Based Study Of The Effect Of Truck Arrival Patterns On Truck Turn Time In Container Terminals. ECMS 2016 Proceedings Edited by Thorsten Claus, Frank Herrmann, Michael Manitz, Oliver Rose, 80–86. https://doi.org/10.7148/2016-0080
[7] Bateman, K. (2021, November 23). Could autonomous trucks be the answer to the global supply chain crisis? World Economic Forum. https://www.weforum.org/stories/2021/11/can-autonomous-trucks-fix-supply-chain/
[8] Bergvall, J., & Gustavsson, C. (2017). The Economic Impact of Autonomous Vehicles in the Logistics Industry.
[9] Bett, D. K., Ali, I., Gheith, M., & Eltawil, A. (2024). Simulation-Based Optimization of Truck Appointment Systems in Container Terminals: A Dual Transactions Approach with Improved Congestion Factor Representation. Logistics, 8(3), Article 3. https://doi.org/10.3390/logistics8030080
[10] Bottani, E., & and Casella, G. (2024). Discrete-event simulation in logistics and supply chain management: A scientometric perspective. Production & Manufacturing Research, 12(1), 2415038. https://doi.org/10.1080/21693277.2024.2415038
[11] Brunetti, M., Mes, M., & Van Heuveln, J. (2020). A General Simulation Framework for Smart Yards. 2020 Winter Simulation Conference (WSC), 2743–2754. https://doi.org/10.1109/WSC48552.2020.9383928
[12] Button, K. J., & Hensher, D. A. (Eds.). (2005). Handbook of transport strategy, policy and institutions. Emerald Group Publishing Limited.
[13] Buzinkay, M. (2023, August 1). Identec Solutions: Spearheading the Future of Container Terminal Automation. https://www.identecsolutions.com/news/identec-solutions-spearheading-the-future-of-container-terminal-automation
[14] Carboni, A., Deflorio, F., Caballini, C., & Cangelosi, S. (2024). Advances in terminal management: Simulation of vehicle traffic in container terminals. Maritime Economics & Logistics. https://doi.org/10.1057/s41278-024-00300-5
[15] Chen, H. (2025). Prediction of truck turnaround time based on machine learning approach. https://repository.tudelft.nl/record/uuid:92c1fbd8-30e8-46fa-bd99-a296966c0119
[16] Cheng, S., Liu, Q., Jin, H., Zhang, R., Ma, L., & Kwong, C. F. (2025). Collaborative optimization of truck scheduling in container terminals using graph theory and DDQN. Scientific Reports, 15, 6950. https://doi.org/10.1038/s41598-025-91140-7
[17] dos Santos Silva, R. C., Brito, T. B., Botter, R. C., & Pereira, N. N. (2011). Modeling of a closed-loop maritime transportation system with discrete event simulation and multi-criteria decision analysis. In Proceedings of the World Congress on Engineering and Computer Science (Vol. 2).
[18] Du, L., Zhang, T., & Zhang, J. (2023). Simulation of road traffic flow in the port. Fourth International Conference on Signal Processing and Computer Science (SPCS 2023), 12970, 62–68. https://doi.org/10.1117/12.3012459
[19] Durlik, I., Miller, T., Kostecka, E., Zwierzewicz, Z., & Łobodzińska, A. (2024). Cybersecurity in Autonomous Vehicles—Are We Ready for the Challenge? Electronics, 13(13), Article 13. https://doi.org/10.3390/electronics13132654
[20] Ebrahim, R. A., Singh, S., Li, Y., & Ji, W. (2022). Discrete Event Simulation for Port Berth Maintenance Planning. 2022 Winter Simulation Conference (WSC), 2386–2396. https://doi.org/10.1109/WSC57314.2022.10015296
[21] Engesser, V., Rombaut, E., Vanhaverbeke, L., & Lebeau, P. (2023). Autonomous Delivery Solutions for Last-Mile Logistics Operations: A Literature Review and Research Agenda. Sustainability, 15(3), Article 3. https://doi.org/10.3390/su15032774
[22] Faisal, A., Kamruzzaman, M., Yigitcanlar, T., & Currie, G. (2019). Understanding autonomous vehicles: A systematic literature review on capability, impact, planning and policy. Journal of Transport and Land Use, 12(1), 45–72.
[23] Fleming, M., Huynh, N., & Xie, Y. (2013). Agent-based simulation tool for evaluating pooled queue performance at marine container terminals. Transportation research record, 2330(1), 103-112.
[24] Garikapati, D., & Shetiya, S. S. (2024). Autonomous Vehicles: Evolution of Artificial Intelligence and the Current Industry Landscape. Big Data and Cognitive Computing, 8(4), Article 4. https://doi.org/10.3390/bdcc8040042
[25] Fiedler, R., Bosse, C., Gehlken, D., Brümmerstedt, K., & Burmeister, H. S. (2019). Autonomous vehicles’ impact on port infrastructure requirements. Fraunhofer Center for Maritime Logistics and Services CML, Hamburg.
[26] Gracia, M. D., Mar-Ortiz, J., & Vargas, M. (2025). Truck Appointment Scheduling: A Review of Models and Algorithms. Mathematics, 13(3), Article 3. https://doi.org/10.3390/math13030503
[27] Gomes, C. E. V., Martinez, V. J. B., de Carvalho, J. A. F., Clımaco, F. G. N., Júnior, G. B., Borchatt, T. B., & de Almeida, J. D. S. Optimizing Truck Flow in Ship Unloading: A Real-Time Simulation Approach for the Port of Itaqui.
[28] Graf, L., & Anner, F. (2021). Autonomous Vehicles as the Ultimate Efficiency Driver in Logistics. In C. Wurst & L. Graf (Eds.), Disrupting Logistics: Startups, Technologies, and Investors Building Future Supply Chains (pp. 191–206). Springer International Publishing. https://doi.org/10.1007/978-3-030-61093-7_15
[29] Hasiri, A., & Kermanshah, A. (2024). Exploring the Role of Autonomous Trucks in Addressing Challenges within the Trucking Industry: A Comprehensive Review. Systems, 12(9), Article 9. https://doi.org/10.3390/systems12090320
[30] Huang, P., Wang, H., Tan, F., Jiang, Y., & Cai, J. (2025). Optimization of external container delivery and pickup scheduling based on appointment mechanism. PloS One, 20(2), e0318606.
[31] Huynh, N. (2009). Reducing truck turn times at marine terminals with appointment scheduling. Transportation research record, 2100(1), 47-57. https://doi.org/10.3141/2100-06
[32] Huynh, N., Walton, C. M., & Davis, J. (2004). Finding the number of yard cranes needed to achieve desired truck turn time at marine container terminals. Transportation Research Record, 1873(1), 99-108.
[33] Huynh, N. N. (2005). Methodologies for reducing truck turn time at marine container terminals. http://hdl.handle.net/2152/1579
[34] Huynh, N., & Walton, C. M. (2008). Robust Scheduling of Truck Arrivals at Marine Container Terminals. Journal of Transportation Engineering, 134(8), 347–353. https://doi.org/10.1061/(ASCE)0733-947X(2008)134:8(347)
[35] Ilati, G., Sheikholeslami, A., & Hassannayebi, E. (2014). A Simulation-Based Optimization Approach for Integrated Port Resource Allocation Problem. Promet - Traffic&Transportation, 26(3), 243–255.
[36] Im, H., Yu, J., & Lee, C. (2021). Truck Appointment System for Cooperation between the Transport Companies and the Terminal Operator at Container Terminals. Applied Sciences, 11(1), Article 1. https://doi.org/10.3390/app11010168
[37] Javaudin, L. (2024). Development of a Dynamic Transport Simulator for Policy Evaluation: Applications to Ride-Sharing and Low Emission Zone in Paris (Doctoral dissertation, University Paris 1 Panthéon-Sorbonne).
[38] Kiani, M., Sayareh, J., & Nooramin, S. (2010). A Simulation Framework for Optimising Truck Congestions in Marine Terminals. ResearchGate, Journal of Maritime Research 7.1 (2010): 55-70. https://www.researchgate.net/publication/237075970_A_Simulation_Framework_for_Optimising_Truck_Congestions_in_Marine_Terminals
[39] Kotachi, M., Rabadi, G., Msakni, M. K., Al-Salem, M., & Diabat, A. (2016). A discrete event simulation for the logistics of Hamad’s container terminal of Qatar. 2016 Winter Simulation Conference (WSC), 2262–2271. https://doi.org/10.1109/WSC.2016.7822267
[40] Kotachi, M., Rabadi, G., & Obeid, M. F. (2013). Simulation Modeling and Analysis of Complex Port Operations with Multimodal Transportation. Procedia Computer Science, 20, 229–234. https://doi.org/10.1016/j.procs.2013.09.266
[41] Kristoffersson, I., & Pernestål Brenden, A. (2018). Scenarios for the development of self-driving vehicles in freight transport. 7th Transport Research Arena TRA 2018, April 16-19, 2018, Vienna, Austria. https://urn.kb.se/resolve?urn=urn:nbn:se:vti:diva-13441
[42] Lakhmas, K., & Sedqui, A. (2018). Port Logistics Optimization Model Study. 2018 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA), 00212667984883, 111–116. https://doi.org/10.1109/LOGISTIQUA.2018.8428265
[43] Lange, A.-K., Schwientek, A., & Jahn, C. (2017). Reducing truck congestion at ports – classification and trends. https://doi.org/10.15480/882.1484
[44] Lee, P. T. W., & Lam, J. S. L. (2015). Container port competition and competitiveness analysis: Asian major ports. Handbook of ocean container transport logistics: Making global supply chains effective, 97-136.
[45] Lei, Q., & Bachmann, C. (2020). Assessing the role of port efficiency as a determinant of maritime transport costs: Evidence from Canada. Maritime Economics & Logistics, 22, 562-584.
[46] Li, B., Tan, K. W., & Tran, K. T. (2016). Traffic simulation model for port planning and congestion prevention. 2016 Winter Simulation Conference (WSC), 2382–2393. https://doi.org/10.1109/WSC.2016.7822278
[47] Liu, W., Zhu, X., Wang, L., Yan, B., & Zhang, X. (2021). Optimization Approach for Yard Crane Scheduling Problem with Uncertain Parameters in Container Terminals. Journal of Advanced Transportation, 2021(1), 5537114. https://doi.org/10.1155/2021/5537114
[48] Mbanefo, H. C. (2020). Development of Nigerian Ports for Organizational Efficiency and Faster Turnaround Times. RSU Journal of Strategic and Internet Business, 5(1),845-859.
[49] Mohammadhashem, M., Ulgen, S., Damoon, R., & Mohammad, T. (2024). An Optimization of Inventory Model at Seaports Using a System Dynamics Approach.
[50] Motunrayo Oluremi Ibiyemi & David Olanrewaju Olutimehin. (2024). Revolutionizing logistics: The impact of autonomous vehicles on supply chain efficiency. International Journal of Scientific Research Updates, 8(1), 009–026. https://doi.org/10.53430/ijsru.2024.8.1.0042
[51] Morais, P., & Lord, E. (2006). Terminal appointment system study (No. TP 14570E).
[52] Mpacd, J. (2021). The study of determining the factors affecting the truck turnaround time in a container terminal. http://dl.lib.uom.lk/handle/123/19430
[53] Natarajan, S. (2019). How Autonomous Vehicles Will Disrupt Logistics and Create New Business Opportunities. 4. 23.
[54] Neagoe, M., Hvolby, H.-H., Taskhiri, M. S., & Turner, P. (2021). Using discrete-event simulation to compare congestion management initiatives at a port terminal. Simulation Modelling Practice and Theory, 112, 102362. https://doi.org/10.1016/j.simpat.2021.102362
[55] Neuweiler, L., & Riedel, P. V. (2017). Autonomous Driving in the Logistics Industry: A multi-perspective view on self-driving trucks, changesin competitive advantages and their implications. https://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-36803
[56] Notteboom, T., Pallis, A., & Rodrigue, J.-P. (2022). Port Economics, Management and Policy. Routledge. https://doi.org/10.4324/9780429318184
[57] Nurcahyo, R., Rifa’i, M., & Habiburrahman, M. (2020). Designing container trucks arrival schedule using truck turnaround time method at terminal Peti Kemas Selatan PT. Pelabuhan Tanjung Priok. 040004. https://doi.org/10.1063/5.0000980
[58] Obasi, C., S., O., & A. M., O. (2024). Port Logistics and Supply Chain Management: An Empirical Review. African Journal of Economics and Sustainable Development, 7(3), 82–91. https://doi.org/10.52589/AJESD-CB4SA99C
[59] Othman, K. (2022). Exploring the implications of autonomous vehicles: A comprehensive review. Innovative Infrastructure Solutions, 7(2), 165. https://doi.org/10.1007/s41062-022-00763-6
[60] Oudani, M., Benghalia, A., Boukachour, J., Boudebous, D., & Alaoui, A. E. H. (2018). Innovative Port Logistics Through Coupled Optimization/Simulation Approaches. In Contemporary Approaches and Strategies for Applied Logistics (pp. 317–336). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-5225-5273-4.ch013
[61] Ozbas, B., Spasovic, L. N., Besenski, D., & Campo, M. (2014). Analyses of interactions between the marine terminal and highway operations (No. CAIT-UTC-020). Rutgers University.
[62] Oztanriseven, F., Pérez-Lespier, L., Long, S., & Nachtmann, H. (2014). A Review of System Dynamics in Maritime Transportation. IIE Annual Conference. Proceedings. Institute of Industrial and Systems Engineers (IISE), 2014.
[63] Palmer, J. G. (1996). SIMULATION MODELING OF TRAFFIC ACCESS FOR PORT PLANNING. Transportation Research Circular 459 (1996): 180-186.
[64] Port Authority. (2022). Port of Montreal Annual Report 2022. https://www.port-montreal.com/en/annual-report-2022
[65] Port Authority Report, M. P. (2024). Annual meeting of the Montreal Port Authority - Results from 2024 operations: At the core of a resilient economy. https://www.newswire.ca/news-releases/annual-meeting-of-the-montreal-port-authority-results-from-2024-operations-at-the-core-of-a-resilient-economy-814617078.html
[66] Preparing for the Future of Transportation Automated Vehicles 3.0. (2018, October 15). SAE International. https://www.sae.org/standards/content/ j3016_201806/.
[67] Qi, S., & Haoyuan, L. (n.d.). Simulation-based optimization on quay crane scheduling of container terminals. ResearchGate. https://doi.org/10.1109/CCDC.2017.7978689
[68] Qi, Y., Tao, T., Zhao, Q., Azimi, M., Qu, W., & University of North Carolina at Charlotte. Center for Advanced Multimodal Mobility Solutions and Education. (2021). A New Method for Estimating Truck Queue Length at Marine Terminal Gates (No. 2020 Project 13). https://rosap.ntl.bts.gov/view/dot/58268
[69] Ramadhan, F. I., & Wasesa, M. (2020). Agent-based Truck Appointment System for Containers Pick-up Time Negotiation. IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 14(1), Article 1. https://doi.org/10.22146/ijccs.51274
[70] Research suggests tsunami of automation set to hit ports. (2023). Riviera. https://www.rivieramm.com/news-content-hub/news-content-hub/abi-research-seaports-to-deploy-370000-autonomous-guided-vehicles-by-end-of-decade-77373
[71] Riaventin, V. N., Cakravastia, A., Cahyono, R. T., & Suprayogi. (2024). Sustainable Synchronization of Truck Arrival and Yard Crane Scheduling in Container Terminals: An Agent-Based Simulation of Centralized and Decentralized Approaches Considering Carbon Emissions. Sustainability, 16(22), Article 22. https://doi.org/10.3390/su16229743
[72] Riches, T. (2023, February 20). Port Simulation: To Manage Port and Terminal Operations. InterDynamics. https://www.interdynamics.com/2023/02/20/port-simulation-an-effective-tool-for-optimizing-port-and-terminal-operations/
[73] Rodrigue, J. P., & Notteboom, T. E. (2013). Containerization, box logistics and global supply chains: The integration of ports and liner shipping networks. Port management, 5-28.
[74] Rodrigue, J. P. (2020). The geography of transport systems. Routledge.
[75] Rusgiyarto, F., Sjafruddin, A., Frazila, R. B., & Suprayogi. (2017). Discrete event simulation model for external yard choice of import container terminal in a port buffer area. AIP Conference Proceedings, 1855(1), 040014. https://doi.org/10.1063/1.4985510
[76] Sadaf, M., Iqbal, Z., Javed, A. R., Saba, I., Krichen, M., Majeed, S., & Raza, A. (2023). Connected and Automated Vehicles: Infrastructure, Applications, Security, Critical Challenges, and Future Aspects. Technologies, 11(5), Article 5. https://doi.org/10.3390/technologies11050117
[77] SAE International Recommended Practice, Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles, SAE Standard J3016_202104, Revised April 2021, Issued January 2014, https://doi.org/10.4271/J3016_202104.
[78] Said, G. A. E.-N. A., Mahmoud, A. M., & El-Horbaty, E.-S. M. (2014). Simulation and optimization of container terminal operations: A case study (No. arXiv:1407.6257). arXiv. https://doi.org/10.48550/arXiv.1407.6257
[79] Sgouridis, S. P., & Angelides, D. C. (2002). Simulation-based analysis of handling inbound containers in a terminal. Proceedings of the Winter Simulation Conference, 2, 1716–1724 vol.2. https://doi.org/10.1109/WSC.2002.1166456
[80] Shahedi, A., Dadashpour, I., & Rezaei, M. (2023). Barriers to the sustainable adoption of autonomous vehicles in developing countries: A multi-criteria decision-making approach. Heliyon, 9(5), e15975. https://doi.org/10.1016/j.heliyon.2023.e15975
[81] Sharma, R. (2023). Port Autonomous Driving Market Report | Global Forecast From 2025 To 2033. https://dataintelo.com/report/port-autonomous-driving-market
[82] Shin, B., Min ,Yusung, Lee ,Gunwoo, Yang ,Hyounseok, & and Cho, B. (2024). Deep learning-based estimation of truck Turn Around Time at container port. Maritime Policy & Management, 0(0), 1–17. https://doi.org/10.1080/03088839.2025.2470437
[83] Sokolowski, J. A., & Banks, C. M. (2010). Modeling and simulation fundamentals: theoretical underpinnings and practical domains. John Wiley & Sons.
[84] Spoel, S. van der, Chintan Amrit, & Jos van Hillegersberg. (2016). A Benchmark for Predicting Turnaround Time for Trucks at a Container Terminal. ResearchGate. https://www.researchgate.net/publication/301216186_A_Benchmark_for_Predicting_Turnaround_Time_for_Trucks_at_a_Container_Terminal
[85] Srisurin, P., Pimpanit, P., & Jarumaneeroj, P. (2022). Evaluating the long-term operational performance of a large-scale inland terminal: A discrete event simulation-based modeling approach. PLOS ONE, 17(12), e0278649. https://doi.org/10.1371/journal.pone.0278649
[86] Stergiopoulos, G., Valvis, E., Mitrodimas, D., Lekkas, D., & Gritzalis, D. (2018). Analyzing Congestion Interdependencies of Ports and Container Ship Routes in the Maritime Network Infrastructure. IEEE Access, 6, 63823–63832. https://doi.org/10.1109/ACCESS.2018.2877659
[87] Team, P. T. (2020). Montreal to accelerate smart port project with AI tool. Port Technology International. https://www.porttechnology.org/news/montreal-to-accelerate-smart-port-project-with-ai-tool/
[88] Thennakoon, K., Bandaranayake, N., Kiridena, S., & Kulatunga, A. K. (2024). Quantification of Landside congestion in ports: an analysis based on GPS Data. Journal of South Asian Logistics and Transport, 4(1).
[89] Thylén, N., Flodén, J., Johansson, M. I., & Hanson, R. (2025). Requirements for the automated loading and unloading of autonomous trucks: An interoperability perspective. International Journal of Physical Distribution & Logistics Management, 55(11), 23–56. https://doi.org/10.1108/IJPDLM-02-2024-0092
[90] Toukan, M., & Chan, H. L. (2018). Beyond the Seaport: Assessing the Inland Container Transport Chain Using System Dynamics. https://dspace.mit.edu/handle/1721.1/117631
[91] Transport Canada. (2021). Backgrounder on the economic impact of a strike at the Port of Montreal. https://tc.canada.ca/en/corporate-services/transparency/briefing-documents-transport-canada/minister-s-appearance-senate-committee-whole-port-montreal-legislation-april-30-2021/backgrounder-economic-impact-strike-port-montreal
[92] U.S.A, T. D. (2024, February 8). New TMS Systems Get Drivers Real-Time Insight. Truck Drivers USA. https://truckdriversus.com/new-tms-systems-get-drivers-real-time-insight/
[93] Van Meldert, B., & De Boeck, L. (2016). Introducing autonomous vehicles in logistics: a review from a broad perspective. Working Papers of Department of Decision Sciences and Information Management, Leuven, (543558).
[94] Wang, R., Li, J., & Bai, R. (2023). Prediction and Analysis of Container Terminal Logistics Arrival Time Based on Simulation Interactive Modeling: A Case Study of Ningbo Port. Mathematics, 11(15), Article 15. https://doi.org/10.3390/math11153271
[95] Willems, L. (2021). Understanding the Impacts of Autonomous Vehicles in Logistics. In The Digital Transformation of Logistics (pp. 113–127). John Wiley & Sons, Ltd. https://doi.org/10.1002/9781119646495.ch8
[96] Yang, K. (2012). The Influence of the Quay Crane Traveling Time for the Quay Crane Scheduling Problem. https://www.semanticscholar.org/paper/The-Influence-of-the-Quay-Crane-Traveling-Time-for-Yang/9c4e581f7b77e31d2ebf418f2c894a2c767c73d3
[97] Yasuda, K., Shibasaki, R., Yasuda, R., & Murata, H. (2024). Terminal congestion analysis of container ports using satellite images and AIS. Remote Sensing, 16(6), 1082.
[98] Yu, B., Zhang, C., Kong, L., Bao, H.-L., Wang, W.-S., Ke, S., & Ning, G. (2014). System dynamics modeling for the land transportation system in a port city. SIMULATION, 90(6), 706–716. https://doi.org/10.1177/0037549714533619
[99] Zehendner, E., & Feillet, D. (2014). Benefits of a truck appointment system on the service quality of inland transport modes at a multimodal container terminal. European Journal of Operational Research, 235(2), 461–469. https://doi.org/10.1016/j.ejor.2013.07.005
[100] Zeng, Q., & Yang, Z. (2009). Integrating simulation and optimization to schedule loading operations in container terminals. Computers & Operations Research, 36(6), 1935–1944. https://doi.org/10.1016/j.cor.2008.06.010
[101] Zou, Y., Wen, J., Tang, S., Zhou, H., Zhang, P., & Ning, W. (2022). Research on the application of autonomous driving technology in port. Highlights in Science, Engineering and Technology, 9, 14–18. https://doi.org/10.54097/hset.v9i.1709