Dynamic Coordination of Multiple Movable Bridges and Vessels for Time-Efficient Inland Waterway Navigation
This paper considers the presence of movable bridges in inland waterway transport, and presents a control framework for the joint dynamic coordination of bridge operations and autonomous vessel navigation to minimize waiting times of vessels at bridges. Simultaneous evolution of bridge occupancy and...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2025 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/395754 |
| Acesso em linha: | http://hdl.handle.net/10261/395754 https://api.elsevier.com/content/abstract/scopus_id/105001817437 |
| Access Level: | acceso abierto |
| Palavra-chave: | Inland waterway transport Model predictive control Movable bridges Multi-objective optimization Propositional logic |
| Resumo: | This paper considers the presence of movable bridges in inland waterway transport, and presents a control framework for the joint dynamic coordination of bridge operations and autonomous vessel navigation to minimize waiting times of vessels at bridges. Simultaneous evolution of bridge occupancy and vessel position is captured by a control-oriented model that incorporates qualitative behavior in the form of propositional logic expressions. A model predictive control (MPC) strategy is designed considering adaptable bridge opening regimes to exploit vessel passage demand, and operational preferences of both vessel skippers and bridge operators are taken into account to reach fair trade-off decisions. A realistic case study pertaining to the Rhine-Alpine corridor is used to demonstrate the effectiveness of the approach. Appropriate key performance indicators (KPIs) are defined and employed for a quantitative comparison with a mixed-integer programming (MIP) strategy with fixed opening regimes. Furthermore, sensitivity to the main MPC parameters is examined by carrying out extensive testing to assess the effect of each design parameter on the solution. |
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