The demand for transport between terminals within port areas, known as inter terminal transport (ITT), is increasing. This paper proposes a dynamic rolling horizon scheduling strategy for ITT using waterborne Autonomous Guided Vessels (waterborne AGVs). The strategy is dynamic in that it can handle the dynamically arriving ITT requests and adapt transport schedules accordingly in real time. Specifically, every certain period of time, we formulate and solve a pick-up and delivery problem considering the dynamic vessel states, waterway network topology, and ITT requests over a future time horizon. In the dynamic setting, waterborne AGVs are allowed to divert from the previously scheduled destination. Moreover, the distances between terminals are not calculated simply as the Euclidean metric but based on the complex port waterway network, which complicates the dynamic problem even more. Time windows of ITT requests, capacity constraints of waterborne AGVs and load/unload service times at terminals are also taken into account. A waterborne ITT transport network in the Port of Rotterdam is constructed. Simulation results demonstrate the effectiveness of the proposed dynamic scheduling strategy.

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 and vessel controllers are responsible for the VTF in waterway segments and the timely arrival at the intersections. An alternating direction method of multipliers (ADMM)-based negotiation framework is proposed for the cooperation among the controllers. The 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. The CMVSs show better path following performance, while the GVO method needs fewer velocity changes. From the perspective of efficiency, the CMVSs help to reduce the total time to pass through the intersection.

The rapidly developing computing and communication technologies improve the autonomy of individual vehicles on the one hand and facilitate the coordination among vehicles on the other. In the context of dynamic speed management, this study considers a platoon of intelligent vehicles that are required to maintain desired inter-vehicle spaces and to respond to speed changes in a collision-free, stable and cooperative way. The platoon is modelled as a cascaded network with linear longitudinal vehicle dynamics, independent physical constraints, and coupling safety constraints. In the case of global information sharing, the authors first propose a centralised collision-free solution on the basis of model predictive control that guarantees asymptotic platoon tracking of speed changes and satisfaction of system constraints during the transient process. A cooperative distributed approach is then further proposed on the basis of the alternating direction method of multipliers resulting in a scheme involving communication only with the roadside infrastructure, e.g. the speed manager. Vehicles in a platoon conduct parallel computation while still achieving global optimal performance and coordination with respect to the collision avoidance constraints. Convergence properties of the distributed solutions are established for the concerned vehicle platoon problem. Simulation results show satisfactory platoon performance and demonstrate the effectiveness of the proposed algorithms.

Since vessel dynamics could vary during maneuvering because of load changes, speed changing, environmental disturbances, aging of mechanism, etc., the performance of model-based path following control may be degraded if the controller uses the same motion model all the time. This article proposes an adaptive path following control method based on least squares support vector machines (LS-SVM) to deal with parameter changes of the motion model. The path following controller consists of two components: the online identification of varying parameters and model predictive control (MPC) using the adaptively identified models. For the online parameter identification, an improved online LS-SVM identification method is proposed based on weighted LS-SVM. Specifically, the objective function of LS-SVM is modified to decrease the errors of parameter estimation, an index is proposed to detect the possible model changes, which speeds up the rate of parameter convergence, and the sliding data window strategy is used to realize the online identification. MPC is combined with the line-of-sight guidance to track straight line reference paths. Finally, case studies are conducted to verify the effectiveness of the proposed path following adaptive controller. Typical parameter varying scenarios, such as rudder aging, current variations and changes of the maneuverability are considered. Simulation results show that the proposed method can handle the above situations effectively.