Automated guided vehicle (AGV) systems provide the flexibility and integration required for flexible manufacturing systems. Previous AGV system studies have attempted to reduce the controlling complexities commonly encountered in these systems. However, this has not been accomplished without additional resources (e.g., automated guided vehicles) and lower system flexibility. The primary objective of this study is to compare the performance of AGV system configurations that reduce controlling and modification complexities (i.e., tandem configurations) to traditional AGV system configuration. Three AGV system configurations were tested under 16 experimental conditions. Performance metrics considered were AGV utilization, mean flowtime, mean tardiness, and percent tardy. The results of this study extend the findings of the previous studies in demonstrating the viability of tandem configurations, in that the tandem configurations match the performance of traditional configuration across all performance metrics, without sacrificing ease of control and system flexibility. Finally, the cost tradeoffs inherent in selecting a particular configuration are discussed.
The paper presents the development of a 3D laser scanning system that can produce an indoor navigation map for an automated guided vehicle. The system uses only a 1D Light Detection and Ranging (LiDAR) as a measuring device and two stepper motors for positioning. Several tests are performed to determine the best trade-off between the time needed for the scan and the required resolution to produce an indoor navigation map, and the relationship between these variables is presented.
Describes a company‐based PhD project into the use of automated guided vehicles in a small‐batch manufacturing environment. The project led to a balanced‐cell methodology to facilitate the use of guided vehicles in a difficult environment. The methodology itself was found to provide benefits for material flow. Having formulated the above approach, a theoretical model is presented, analysing the operational effects of improved workflow. The above theoretical analysis showed the potential benefits of balanced cells on the factory floor, and these were confirmed by a simulation study. This being so, a DCF analysis showed that balanced cells enabled the economic use of guided vehicle systems in multi‐product batch manufacture, by transforming an AGV project from a negative to a positive net present value. An analysis of the wider effects of cellular manufacture enabled the value of the investment to be increased.
Fahrerlose Transportsysteme bieten großes Potenzial für die Optimierung intralogistischer Prozesse. Durch vielfältige Prozess- und Umgebungsanforderungen hat sich ein variantenreicher Markt mit vielen Anbietern entwickelt. Eine passende Lösung zu finden und auszuwählen stellt viele Unternehmen vor eine große Herausforderung. Dieser Beitrag zeigt, wie ein Softwaretool umgesetzt werden kann, das den Anwender systematisch durch die Anforderungsaufnahme führt und bei der Lösungsauswahl unterstützt. Automated guided vehicle systems provides great potential for optimizing intralogistical processes. A wide variety of different process and environmental requirements has led to a market with many suppliers and a wide range of different solutions. To find and select a solution for an individual process is a challenging task for many companies. This paper shows how to accomplish a software tool for guiding users through the requirements specification and selection process for a suitable solution.
Intro -- Preface -- Contents -- Acronyms -- Symbols -- 1 Introduction -- 1.1 Overview of Main Research Activities -- 1.1.1 Fault-Tolerant Control -- 1.1.2 Fault-Tolerant Design -- 1.2 Essential Concepts of Fault-Tolerance -- 1.3 Structure of this Book -- References -- Principles of Fault-Tolerant Design and Control -- 2 Fault-Tolerant Control -- 2.1 FTC for Continuous Processes -- 2.2 FTC for Discrete Event Systems -- 2.3 Fault Identification-A Fundamental Tool for Active FTC -- 2.4 Fault-Tolerant Controllers -- 2.5 Prognosis of Faults -- 2.6 Summary -- References -- 3 Fault-Tolerant Design -- 3.1 Requirements Exploration -- 3.2 Functional Architecture -- 3.3 Physical Realization -- 3.4 Geometrical Considerations -- 3.5 Summary -- References -- Fault-Tolerant Design and Control of Automated Vehicles -- 4 Methodical and Model-Based Design of Automated Vehicles -- 4.1 Process Planning -- 4.1.1 Development Methodology for Mechatronic Systems -- 4.1.2 Planning and Control of the Development Process -- 4.2 Customer Needs Exploration -- 4.3 Requirements Management -- 4.3.1 Background -- 4.3.2 Model Based Requirements Management -- 4.3.3 Industrial Situation -- 4.3.4 Application to the Requirements Management of Automated Guided Vehicles -- 4.4 System Design -- 4.5 Domain Specific Design -- 4.6 System Integration -- 4.7 Verification and Validation -- 4.8 Summary -- References -- 5 Design of Virtual Diagnostic Sensors for an Automated Guided Vehicle -- 5.1 State of the Art -- 5.2 Research Question and Structure -- 5.3 Description of Discrete Time Systems -- 5.4 Design and Realisation of an Automated Guided Vehicle -- 5.5 Mathematical Model of the Automated Guided Vehicle -- 5.6 Virtual Sensor Design -- 5.6.1 Uncertainty Intervals -- 5.6.2 Diagnostic Principles -- 5.7 Experimental Verification -- 5.8 Experimental Results and Discussion.
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The deployment of Automated Vehicles (AV) is starting to become widespread throughout transportation, resulting in the recognition and awareness by legislative leaders of the potential impact on transportation operations. To assist transportation operators in making the needed preparations for these vehicles, an in-depth study regarding the impact of AV and Connected Automated Vehicles (CAV) is needed. In this research, the impact of AV and CAV on the highway setting is studied. This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, such as the Intelligent Driver Model (IDM), the IDM with traffic adaptive driving Strategy (SIDM), the Improved IDM (IIDM), the IIDM with Constant-Acceleration Heuristic (CAH), and the MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) were examined with the state-of-the-art vehicle trajectory data. The Highway Drone dataset (HighD) were analyzed through the implementation of genetic algorithm to gain more insight about the trajectories of these vehicles. In 2020, there is no commercially available gully automated vehicle available to the public, although many companies are conducting in field testing. This research generated AV trajectories based on the actual vehicle trajectories from the High-D dataset and adjusts those trajectories to account for ideal AV operations. The analysis from the fitted trajectory data shows that the calibrated IIDM with CAH provides a best fit on AV behavior. Next, the AV and CAV were modeled in microscopic perspective to show the impact of these vehicles on a corridor. The traffic simulation software, VISSIM, modified by implementing an external driver model to govern the interactions between Legacy Vehicles (LV), AV, and CAV on a basic and merging highway segment as well as a model of the Interstate 95 corridor south of Richmond, Virginia. From the analysis, this research revealed that the AV and CAV could increase highway capacity significantly. Even with a small portion of AV or CAV, the roadway capacity increased. On I-95, CAV performed better than AV because of Cooperative Adaptive Cruise Control (CACC) and platooning due to CAV's ability to coordinate movement through communication; however, in weaving segments, CAV underperformed AV. This result indicates that the CAV algorithms would need to be flexible in order to maintain flow in areas with weaving sections. Lastly, diverse operational conditions, such as different heavy vehicle market penetration and different aggressiveness were examined to support traffic operators transition to the introduction of AV and CAV. Based on the analysis, the study concludes that the different aggressiveness could mitigate congestion in all cases if the proper aggressiveness level is selected considering the current traffic condition. Overall, the dissertation provides guidance to researchers, traffic operators, and lawmakers to model, simulate, and evaluate AV and CAV on highways. ; Doctor of Philosophy ; The deployment of Automated Vehicles (AV) is starting to become widespread throughout transportation, resulting in the recognition and awareness by legislative leaders of the potential impact on transportation operations. To assist transportation operators in making the needed preparations for these vehicles, an in-depth study regarding the impact of AV and Connected Automated Vehicles (CAV) is needed. In this research, the impact of AV and CAV on the highway setting is studied. This study addresses car-following models that are currently used for simulating AV and CAV. Diverse car-following models, such as the Intelligent Driver Model (IDM), the IDM with traffic adaptive driving Strategy (SIDM), the Improved IDM (IIDM), the IIDM with Constant-Acceleration Heuristic (CAH), and the MIcroscopic model for Simulation of Intelligent Cruise control (MIXIC) were examined with the state-of-the-art vehicle trajectory data. The Highway Drone dataset (HighD) were analyzed through the implementation of genetic algorithm to gain more insight about the trajectories of these vehicles. In 2020, there is no commercially available gully automated vehicle available to the public, although many companies are conducting in field testing. This research generated AV trajectories based on the actual vehicle trajectories from the High-D dataset and adjusts those trajectories to account for ideal AV operations. The analysis from the fitted trajectory data shows that the calibrated IIDM with CAH provides a best fit on AV behavior. Next, the AV and CAV were modeled in microscopic perspective to show the impact of these vehicles on a corridor. The traffic simulation software, VISSIM, modified by implementing an external driver model to govern the interactions between Legacy Vehicles (LV), AV, and CAV on a basic and merging highway segment as well as a model of the Interstate 95 corridor south of Richmond, Virginia. From the analysis, this research revealed that the AV and CAV could increase highway capacity significantly. Even with a small portion of AV or CAV, the roadway capacity increased. On I-95, CAV performed better than AV because of Cooperative Adaptive Cruise Control (CACC) and platooning due to CAV's ability to coordinate movement through communication; however, in weaving segments, CAV underperformed AV. This result indicates that the CAV algorithms would need to be flexible in order to maintain flow in areas with weaving sections. Lastly, diverse operational conditions, such as different heavy vehicle market penetration and different aggressiveness were examined to support traffic operators transition to the introduction of AV and CAV. Based on the analysis, the study concludes that the different aggressiveness could mitigate congestion in all cases if the proper aggressiveness level is selected considering the current traffic condition. Overall, the dissertation provides guidance to researchers, traffic operators, and lawmakers to model, simulate, and evaluate AV and CAV on highways.
A new class of Intelligent and Autonomous Vehicles (IAVs) has been designed in the framework of Intelligent Transportation for Dynamic Environment (InTraDE) project funded by European Union. This type of vehicles is technologically superior to the existing Automated Guided Vehicles (AGVs), in many respects. They offer more flexibility and intelligence in maneuvering within confined spaces where the logistic operations take place. This includes the ability of pairing/unpairing enabling a pair of 1-TEU (20-foot Equivalent Unit) IAVs dynamically to join, transport containers of any size between 1-TEU and 1-FFE (40-foot Equivalent) and disjoin again. Deploying IAVs helps port operators to remain efficient in coping with the ever increasing volume of container traffic at ports and eliminate the need for deploying more 40-ft transporters in the very confined area of ports. In order to accommodate this new feature of IAVs, we review and extend one of the existing mixed integer programming models of AGV scheduling in order to minimize the makespan of operations for transporting a set of containers of different sizes between quay cranes and yard cranes. In particular, we study the case of Dublin Ferryport Terminal. In order to deal with the complexity of the scheduling model, we develop a Lagrangian relaxation-based decomposition approach equipped with a variable fixing procedure and a primal heuristics to obtain high-quality solution of instances of the problem.
Global warming is endangering the earth as we know it, and CO2 levels are rising to amounts the world has never seen before and cannot handle. Additionally fossil fuels and natural resources are depleting very rapidly. For that reason the 1997 Kyoto protocol up to the 2018 Paris Agreement were signed, aiming towards a more sustainable and environmentally friendly re-source extraction and reduction of the CO2 footprint. Introducing Smart, emission free cities, is one of the solutions to this challenge. To develop such a city, all day to day activities must be considered. This includes but is not limited to: communication, electricity and mobility. These factors are in the bigger picture connected and will be introduced through analyzing future mobility in this thesis. Mobility plays a big role in maintaining the stability of the grid, expected to be supporting the unpredictable renewable energy sources through charging and discharging when needed. This will play a big factor for Demand Side Management and enable a better, higher quality of life. Future vehicles are expected to be electrical and autonomous, requiring no human interaction during the driving. They should be a part of a bigger system, allowing all the city's residents to be able to get from A to B safely and efficiently. Allowing on the city to become more self sufficient and sustainable and on the other hand easier connection to neighbouring cities. The future resident will not have to worry about getting from a place to the other, even if its in a rural area. The beauty of having such a system enables worry free mobility for the citizen and a structured design for the governments. The potential of these autonomous vehicles is analysed on a techno-economical base and their implementation is simulated on a virtual residential quarter in Berlin, Germany. The technical simulation works intelligently, creating iterations to provide the best possible way and the amount of vehicles needed. Whereas the economical analysis shows the potential of the autonomous ve-hicle with regards to value and money. The potential of autonomous vehicles as means of mobility in Smart Cities will be conveyed in this master thesis, clearly showing the benefits if such a system were adapted.
Global warming is endangering the earth as we know it, and CO2 levels are rising to amounts the world has never seen before and cannot handle. Additionally fossil fuels and natural resources are depleting very rapidly. For that reason the 1997 Kyoto protocol up to the 2018 Paris Agreement were signed, aiming towards a more sustainable and environmentally friendly re-source extraction and reduction of the CO2 footprint. Introducing Smart, emission free cities, is one of the solutions to this challenge. To develop such a city, all day to day activities must be considered. This includes but is not limited to: communication, electricity and mobility. These factors are in the bigger picture connected and will be introduced through analyzing future mobility in this thesis. Mobility plays a big role in maintaining the stability of the grid, expected to be supporting the unpredictable renewable energy sources through charging and discharging when needed. This will play a big factor for Demand Side Management and enable a better, higher quality of life. Future vehicles are expected to be electrical and autonomous, requiring no human interaction during the driving. They should be a part of a bigger system, allowing all the city's residents to be able to get from A to B safely and efficiently. Allowing on the city to become more self sufficient and sustainable and on the other hand easier connection to neighbouring cities. The future resident will not have to worry about getting from a place to the other, even if its in a rural area. The beauty of having such a system enables worry free mobility for the citizen and a structured design for the governments. The potential of these autonomous vehicles is analysed on a techno-economical base and their implementation is simulated on a virtual residential quarter in Berlin, Germany. The technical simulation works intelligently, creating iterations to provide the best possible way and the amount of vehicles needed. Whereas the economical analysis shows the potential of the autonomous ve-hicle with regards to value and money. The potential of autonomous vehicles as means of mobility in Smart Cities will be conveyed in this master thesis, clearly showing the benefits if such a system were adapted.
