Green vehicle technology to enhance the performance of a European port: A simulation model with a cost-benefit approach |
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| Institution: | 1. Liverpool Logistics, Offshore and Marine Research Institute, School of Engineering, Technology and Maritime Operations, Liverpool John Moores University, Liverpool L3 3AF, UK;2. Department of Transport Engineering, Dublin Institute of Technology, Bolton St., Dublin 1, Ireland;1. Copenhagen Business School, Kilevej 14A, 3nd Floor, DK-2000 Frederiksberg, Denmark;2. Seafarers International Research Centre, School of Social Sciences, Cardiff University, 52 Park Place, Cardiff CF10 3AT, United Kingdom;1. Faculty of Engineering and Computing, Coventry University, Priory Street, Coventry CV1 5FB, UK;2. Southampton Business School, University of Southampton, Southampton SO17 1BJ, UK;3. Department of Naval Architecture and Ocean Engineering, University of Sao Paulo, Av. Prof. Mello Moraes, 2231, Sao Paulo 05508-030, Brazil;1. Department of Transportation and Communication Management Science and the Research Center for Energy Technology and Strategy, National Cheng Kung University, No. 1, University Road, Tainan 70101, Taiwan;2. Department of Transportation and Communication Management Science, National Cheng Kung University, No. 1, University Road, Tainan 70101, Taiwan;1. Liverpool Logistics Offshore and Marine Research Institute (LOOM), School of Engineering, Technology and Maritime Operations, Liverpool John Moores University, L3 3AF, United Kingdom;2. School of Computer Science, China University of Geosciences, Wuhan, China;3. AECOM, United Kingdom;1. Graduate School of Logistics, Incheon National University, Korea;2. Graduate School of Logistics, Incheon National University, Korea |
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| Abstract: | In this paper, we study the impact of using a new intelligent vehicle technology on the performance and total cost of a European port, in comparison with existing vehicle systems like trucks. Intelligent autonomous vehicles (IAVs) are a new type of automated guided vehicles (AGVs) with better maneuverability and a special ability to pick up/drop off containers by themselves. To identify the most economical fleet size for each type of vehicle to satisfy the port’s performance target, and also to compare their impact on the performance/cost of container terminals, we developed a discrete-event simulation model to simulate all port activities in micro-level (low-level) details. We also developed a cost model to investigate the present values of using two types of vehicle, given the identified fleet size. Results of using the different types of vehicles are then compared based on the given performance measures such as the quay crane net moves per hour and average total discharging/loading time at berth. Besides successfully identifying the optimal fleet size for each type of vehicle, simulation results reveal two findings: first, even when not utilising their ability to pick up/drop off containers, the IAVs still have similar efficacy to regular trucks thanks to their better maneuverability. Second, enabling IAVs’ ability to pick up/drop off containers significantly improves the port performance. Given the best configuration and fleet size as identified by the simulation, we use the developed cost model to estimate the total cost needed for each type of vehicle to meet the performance target. Finally, we study the performance of the case study port with advanced real-time vehicle dispatching/scheduling and container placement strategies. This study reveals that the case study port can greatly benefit from upgrading its current vehicle dispatching/scheduling strategy to a more advanced one. |
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| Keywords: | Discrete-event simulation Fleet sizing Intelligent autonomous vehicles Automated guided vehicles Container terminals Cost-benefit analysis |
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