Abstract
Based on a novel discrete-event zone-control model, in our previous papers [ 1 , 2 ], we presented a time-efficient traffic control for automated guided vehicle (AGV) systems to exclude inter-vehicle collisions and system deadlocks, together with a case study on container terminals. The traffic control allows each vehicle in an AGV system to freely choose its routes for any finite sequence of zone-to-zone transportation tasks and the routes can be constructed in an online fashion. In this paper, we extended our previous results with two practical goals: (1) to increase the utilization of the workspace area by reducing the minimally allowed area of each zone; (2) to avoid vehicle collisions and deadlocks with the occurrence of vehicle breakdowns. To achieve the first goal, we include one extra vehicle event that allows each vehicle to probe further ahead while it is moving on the guide-path. This leads to an extension of our previous discrete-event model and traffic control rules, which are presented in the first part of the paper. The second part of the paper concerns the second goal, for which an emergency traffic control scheme is designed as supplementary to the normal traffic control rules. As in our previous papers, the improved model and traffic control are applied to a simulation of quayside container transshipment at container terminals; our simulation results are compared with those from two interesting works in the literature.
Highlights
Automated guided vehicles (AGVs) are used as a trans‐ portation means in many industrial fields
In the rest of this section, the performance of an AGV system incorporating the traffic control presented in the previous section is evaluated in a simulation case study for automated container terminals; the result is compared with those described in two existing papers in the literature
We focus on the quayside container transshipment, where the quay cranes (QCs) and yard stackers (YSs)6 are, respectively, in charge of the container pick-up and dropoff handling in the quay area (QA) and yard area (YA); and a team of AGVs are used to shuttle between these two areas to serve the cranes with containers
Summary
Automated guided vehicles (AGVs) are used as a trans‐ portation means in many industrial fields. There have been some research activities aiming at maximally permissive deadlock avoidance algorithms with complexity concerns by using the resource allocation system theory [37] and Petri net formalism [38] It seems that there is still quite some distance from the current status of the development to the practical applications of these optimal algorithms for large-scale AGV systems (with tens or even hundreds of vehicles). We have two specific goals in mind: (1) increase the utilization of the workspace area by reducing the minimally allowed area of each zone; and (2) design an emergency traffic control scheme to avoid vehicle collisions and deadlocks with the presence of vehicle breakdowns Both these goals are motivated by practical concerns from general applications. All the technical proofs are included in the appendix of the paper
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