Otomatikleştirilmiş rehberli araç sistemlerinin transport tekniğinde modellemesi

The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature.Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir

Limited Visibility and Uncertainty Aware Motion Planning for Automated Driving

Adverse weather conditions and occlusions in urban environments result in impaired perception. The uncertainties are handled in different modules of an automated vehicle, ranging from sensor level over situation prediction until motion planning. This paper focuses on motion planning given an uncertain environment model with occlusions. We present a method to remain collision free for the worst-case evolution of the given scene. We define criteria that measure the available margins to a collision while considering visibility and interactions, and consequently integrate conditions that apply these criteria into an optimization-based motion planner. We show the generality of our method by validating it in several distinct urban scenarios

Modeling Automated Guided Vehicle Systems in Material Handling

Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

Modeling Automated Guided Vehicle Systems in Material Handling

Çalışmanın amaçları; 1) Otomatikleştirilmiş Rehberli Araç (ORA, ingilizcesi, Automated Guided Vehicle, AGV) sistemlerinin kullanımı ve faydaları hakkında bilgiler vermek ve 2) ORA sistemlerinin tasarım, modellenme ve simulasyonu (benzetimi) ile ilgili kapsamlı bir literatür incelemesinin sonuçlarını sunmaktır. Öncelikle ORA sistemlerinin tasarım problemlerinde kullanılan yöntemleri analitik ve simülasyon yöntemler olarak ikiye ayrılıp, daha sonra, ilgili literatürden her iki gruba ait örnekler verilmektedir.The study objectives are to 1) provide information regarding the use and benefits of Automated Guided Vehicle (AGV) systems in manufacturing environments, and 2) review the literature related to design, modeling and simulation of AGV systems. We classify the tools utilized in design problems of AGV systems as analytical and simulation-based tools. Then, give examples of both categories from related literature

Intelligent Simulation Modeling of a Flexible Manufacturing System with Automated Guided Vehicles

Although simulation is a very flexible and cost effective problem solving technique, it has been traditionally limited to building models which are merely descriptive of the system under study. Relatively new approaches combine improvement heuristics and artificial intelligence with simulation to provide prescriptive power in simulation modeling. This study demonstrates the synergy obtained by bringing together the "learning automata theory" and simulation analysis. Intelligent objects are embedded in the simulation model of a Flexible Manufacturing System (FMS), in which Automated Guided Vehicles (AGVs) serve as the material handling system between four unique workcenters. The objective of the study is to find satisfactory AGV routing patterns along available paths to minimize the mean time spent by different kinds of parts in the system. System parameters such as different part routing and processing time requirements, arrivals distribution, number of palettes, available paths between workcenters, number and speed of AGVs can be defined by the user. The network of learning automata acts as the decision maker driving the simulation, and the FMS model acts as the training environment for the automata network; providing realistic, yet cost-effective and risk-free feedback. Object oriented design and implementation of the simulation model with a process oriented world view, graphical animation and visually interactive simulation (using GUI objects such as windows, menus, dialog boxes; mouse sensitive dynamic automaton trace charts and dynamic graphical statistical monitoring) are other issues dealt with in the study

An agent-based simulation model for autonomous trailer docking

This paper presents a simulation model of a generic automated planning and control system for the pick-up and docking of semi-trailers by means of autonomous Yard Tractors (YTs) in a collision- and conflict free environment. To support the planning and control of the YTs, we propose a Multi-Agent System (MAS). We illustrate our approach using a case study at a Dutch logistics service provider. To evaluate the proposed system, we design an agent-based simulation model, which is set up in a similar way as the MAS. We conclude with the verification and validation of the simulation model

Search-based Test Generation for Automated Driving Systems: From Perception to Control Logic

abstract: Automated driving systems are in an intensive research and development stage, and the companies developing these systems are targeting to deploy them on public roads in a very near future. Guaranteeing safe operation of these systems is crucial as they are planned to carry passengers and share the road with other vehicles and pedestrians. Yet, there is no agreed-upon approach on how and in what detail those systems should be tested. Different organizations have different testing approaches, and one common approach is to combine simulation-based testing with real-world driving. One of the expectations from fully-automated vehicles is never to cause an accident. However, an automated vehicle may not be able to avoid all collisions, e.g., the collisions caused by other road occupants. Hence, it is important for the system designers to understand the boundary case scenarios where an autonomous vehicle can no longer avoid a collision. Besides safety, there are other expectations from automated vehicles such as comfortable driving and minimal fuel consumption. All safety and functional expectations from an automated driving system should be captured with a set of system requirements. It is challenging to create requirements that are unambiguous and usable for the design, testing, and evaluation of automated driving systems. Another challenge is to define useful metrics for assessing the testing quality because in general, it is impossible to test every possible scenario. The goal of this dissertation is to formalize the theory for testing automated vehicles. Various methods for automatic test generation for automated-driving systems in simulation environments are presented and compared. The contributions presented in this dissertation include (i) new metrics that can be used to discover the boundary cases between safe and unsafe driving conditions, (ii) a new approach that combines combinatorial testing and optimization-guided test generation methods, (iii) approaches that utilize global optimization methods and random exploration to generate critical vehicle and pedestrian trajectories for testing purposes, (iv) a publicly-available simulation-based automated vehicle testing framework that enables application of the existing testing approaches in the literature, including the new approaches presented in this dissertation.Dissertation/ThesisDoctoral Dissertation Computer Engineering 201

Stochastic Modeling of Unloading and Loading Operations at a Container Terminal using Automated Lifting Vehicles

With growing worldwide trade, container terminals have grown in number and size. Many new terminals are now automated to increase operational efficiency. The key focus is on improving seaside processes, where a distinction can be made between single quay crane operations (all quay cranes are either loading or unloading containers) and overlapping quay crane operations (some quay cranes are loading while others are unloading containers). From existing studies, it is not clear if the design insights obtained from analyzing single operations, such as optimal stack layout, are consistent with the insights obtained from analyzing overlapping operations. In this paper, we develop new integrated stochastic models for analyzing the performance of overlapping loading and unloading operations that capture the complex stochastic interactions among quayside, vehicle, and stackside processes. Using these integrated models, we are able to show that that there are stack layout configurations that are robust for both single (either loading or unloading) and for overlapping (both loading and unloading) operations