Publications       Rudy Negenborn
Full Professor, Head of Section
Team & Themes

Title:Cooperative multi-vessel systems in urban waterway networks
Authors:L. Chen, Y. Huang, H. Zheng, J.J. Hopman, R.R. Negenborn

Journal:IEEE Transactions on Intelligent Transportation Systems

Abstract:Urban waterways have great potential in cargo transport to relieve the congestion in the overloaded road networks. This paper explores the potential of applying Cooperative Multi-Vessel Systems (CMVSs) to improve the safety and efficiency of transport in urban waterway networks. A framework consisting of Vessel Train Formation (VTF) and Cooperative Waterway Intersection Scheduling (CWIS) is proposed. Two types of controllers are introduced: intersection controllers solve the CWIS problems and assign each vessel a desired time of arrival; vessel controllers are responsible for the VTF in waterway segments and the timely arrival at the intersections. An ADMM-based negotiation framework is proposed for the cooperation among the controllers. Simulation experiments involving the scenarios in which up to 50 vessels sailing in the canal network in Amsterdam are carried out to illustrate the effectiveness of the proposed approach. In the simulation of an isolated intersection, rescheduling is triggered when some vessels cannot arrive on time. Although some ASVs arrive later, the time that is needed for all the ASVs to pass through is the same after rescheduling. Moreover, we compare the cooperative situation with the proposed CMVSs with a baseline situation. In the baseline situation, vessels avoid collisions using the Generalized Velocity Obstacle (GVO) method and cross the intersection with a First In First Out rule. CMVSs show better path following performance, while GVO method needs fewer velocity changes. From the perspective of efficiency, CMVSs help to reduce the total time to pass through the intersection.

Reference:Cooperative multi-vessel systems in urban waterway networks. L. Chen, Y. Huang, H. Zheng, J.J. Hopman, R.R. Negenborn. IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 8, pp. 3294-3307, 2019.
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