Scientific paper ID 2211 : 2022/2
VEHICLE TO VEHICLE COMMUNICATION AT AUTOMATED CONTAINER TERMINAL
Khaldon Al Karmadi
The aim of any Container Terminal is to increase efficiency to be able to handle the increase in demand and the increase in container vessel size. Considering the limited space and resources of any container terminal and the high cost of increasing the capacity, automation can be an efficient solution. Automated Container Terminal became a worldwide trend to be applied to many big container terminals. In addition, many researches are focusing on this topic to use automation and other technologies to increase efficiency in container terminals. This research paper will use Internet of Things (IoT) technology to increase transportation efficiency at an Automated Container Terminal. In addition, the research paper proposes an algorithm to increase efficiency in the automated container terminal and achieve the research objective. Finally, a simulation results will be shown to prove the effects of using the proposed algorithm in decreasing total discharging time and reducing terminal handling charges.
Автоматизиран контейнерен терминал Интернет на нещата Комуникации „превозно средство – превозно средство“ и „превозно средство – инфраструктура“ Симулации Ефективност.Automated Container Terminal Internet of Things Vehicle-to-Vehicle and Vehicle-toKhaldon Al Karmadi
 Angeloudis, P., & Bell, M. G. H. (2010). An uncertainty-aware AGV assignment algorithm for automated container terminals. Transportation Research Part E, 46, 354–366.
 Ashokkumar, K., Sam, B., & Arshadprabhu, R. (2015). Cloud Based Intelligent Transport System. Procedia Computer Science, 58-63.
 Bish, E. K., Chen, F. Y., Leong, Y. T., Nelson, B. L., Ng, J. W. C., & Simchi-Levi, D. (2005). Dispatching vehicles in a mega container terminals. OR Spectrum, 27, 491–506.
 Briskorn, D., Drexl, A., & Hartmann, S. (2006). Inventory-based dispatching of automated guided vehicles on container terminals. OR Spectrum, 28, 611–630.
 Carlo, H., Vis, I., & Roodbergen, K. (2014). Transport operations in container terminals: Literature overview, trends, research directions and classification scheme. European Journal of Operational Research, 1-13.
 Gawrilow, E., Klimm, M., Möhring, R. H., & Stenzel, B. (2012). Conflict-free vehicle routing: Load balancing and deadlock prevention. European Journal of Transport Logistics, 1, 87–111.
 Gawrilow, E., Köhler, E., Möhring, R. H., & Stenzel, B. (2008). Dynamic routing of automated guided vehicles in real-time. In Krebs, & Jäger, (Eds.), Mathematics – Key technology for the future (pp. 165–177).
 Gnimpieba, Z., Nait-Sidi-Moh, A., Durand, D., & Fortin, J. (2015). Using Internet of Things Technologies for a Collaborative Supply Chain: Application to Tracking of Pallets and Containers. Procedia Computer Science, 550-557.
 Guler, S., Menendez, M., & Meier, L. (2014). Using connected vehicle technology to improve the efficiency of intersections. Transportation Research Part C: Emerging Technologies, 121-131.
 Haass, R., Dittmer, P., Veigt, M., & Lutjen, M. (2015). Reducing food losses and carbon emission by using autonomous control – A simulation study of the intelligent container. International Journal of Production Economics, 400-408.
 He, J., Huang, Y., Yan, W., & Wang, S. (2015). Integrated internal truck, yard crane and quay crane scheduling in a container terminal considering energy consumption. Expert Systems with Applications, 2464-2487.
 Homchaudhuri, B., Pisu, P., & Ozguner, U. (2015). Secure Vehicle Localization and Cruise Control for Connected Vehicles. IFAC-PapersOnLine, 1192-1197.
 Kezic , D., Vujovic , I., & Gudelj, A. (2007). Petri net approach of collision prevention supervision design in port transport system. Promet – Traffic & Transportation, 19(5), 269–275.
 Kim, K. H., & Bae, J. W. (2004). A look-ahead dispatching method for automated guided vehicles in automated port container terminals. Transportation Science, 38(2), 224–234.
 Kim, K. H., Jeon, S. M., & Ryu, K. R. (2006). Deadlock prevention for automated guided vehicles in automated container terminals. OR Spectrum, 28, 659–679.
 Koo, P. H., Lee, W. S., & Jang, D. W. (2004). Fleet sizing and vehicle routing for container transportation in a static environment. OR Spectrum, 26, 193–209.
 Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for enterprises. Business Horizons, 431-440.
 Lehmann, M., Grunow, M., & Günther, H. O. (2006). Deadlock handling for real-time control of AGVs at automated container terminals. OR Spectrum, 28, 631–657.
 Li, C. L., & Vairaktarakis, G. L. (2004). Loading and unloading operations in container terminals. IIE Transactions, 36(4), 287–297.
 Luo, J., & Wu, Y. (2015). Modelling of dual-cycle strategy for container storage and vehicle scheduling problems at automated container terminals. Transportation Research Part E: Logistics and Transportation Review, 49-64.
 Ng, W. C., Mak, K. L., & Zhang, Y. X. (2007). Scheduling trucks in container terminal using a genetic algorithm. Engineering Optimization, 39(1), 33–47.
 Nishimura, E., Imai, A., & Papadimitriou, S. (2005). Yard trailer routing at a maritime container terminal. Transportation Research Part E, 41, 53–76.
 Osman, O., & Ishak, S. (2015). A network level connectivity robustness measure for connected vehicle environments. Transportation Research Part C: Emerging Technologies, 48-58.
 Park, Y. H., Kim, H. J., & Lee, C. (2009). Ubiquitous software controller to prevent deadlocks for automated guided vehicle systems in a container port terminal environment. Journal of Intelligent Manufacturing, 20, 321–325.
 Rashidi, H., & Tsang, E. P. K. (2011). A complete and an incomplete algorithm for automated guided vehicle scheduling in container terminals. Computers and Mathematics with Applications, 61, 630–641.
 Siror, J., Huanye, S., & Dong, W. (2011). RFID based model for an intelligent port. Computers in Industry, 795-810.
 Sun, C. (2012). Application of RFID Technology for Logistics on Internet of Things. AASRI Procedia, 106-111.
 Talebpour, A., Mahmassani, H., & Hamdar, S. (2015). Modeling lane-changing behavior in a connected environment: A game theory approach. Transportation Research Part C: Emerging Technologies, 216-232.
 Tsai, F., & Huang, C. (2012). Cost-Benefit Analysis of Implementing RFID System in Port of Kaohsiung. Procedia - Social and Behavioral Sciences, 40-46.
 UNCTAD, (2011). (United Nations Conference on Trade and Development) secretariat. Review of Maritime Transport 2011, United Nations publication.
 Wu, Y., Luo, J., Zhang, D., & Dong, M. (2013). An integrated programming model for storage management and vehicle scheduling at container terminals. Research in Transportation Economics, 13-27.
 Xin, J., Negenborn, R., Corman, F., & Lodewijks, G. (2015). Control of interacting machines in automated container terminals using a sequential planning approach for collision avoidance. Transportation Research Part C: Emerging Technologies, 377-396.
 Xing, Y., Yin, K., Quadrifoglio, L., & Wang, B. L. (2012). Dispatch problem of automated guided vehicles for serving tandem lift quay crane. Transportation Research Record, 79–86.
 Zeng, J., & Hsu, W. J. (2008). Conflict-free container routing in mesh yard layouts. Robotics and Autonomous Systems, 56, 451–460.
 Zeng, Q., Yang, Z., & Lai, L. (2009). Models and algorithms for multi-crane oriented scheduling method in container terminals. Transport Policy, 16, 271–278.
 Zhang, L. W., Ye, R., Huang, S. Y., & Hsu, W. J. (2005). Mixed integer programming models for dispatching vehicles at a container terminal. Journal of Applied Mathematics & Computing, 17(1–2), 145–170.