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Specialization: Transport Engineering and Logistics Report number: 2013.TL.7799
Title: A comparison of the performance of automated vehicles in
container terminals
Author: R.J.W. van Gils
Title (in Dutch) Een vergelijking van de prestatie van geautomatiseerde voertuigen op container terminals
Assignment: Master thesis Confidential: yes
Initiator (university): Dr. R.R. Negenborn
Initiator (company): A. de Waal, MSc (TBA, Delft) Professor: Prof. Dr. Ir. G. Lodewijks Supervisor: Dr. R.R. Negenborn
Summary
Since the beginning of the container era in the middle of the last century, the containerization is growing. Nowadays more than 90 percent of the world’s non-bulk cargo is being transported in a container. With many shipping liners deploying container vessels on the world seas, the competition is strong. Therefore the need to lower the price per container has resulted in the development of vessels with increasing sizes. Continuing on cost reduction, shipping lines tend to make fewer port calls with their vessels. Consequently the call sizes, i.e. the number of containers that have to be unloaded and loaded per vessel in a port, will increase. Because of the competition between harbours and container terminals, terminal operators are forced to handle container vessels as fast as possible while reducing the operational costs. Especially in high labour regions, the labour costs are a large part of the operational costs of container terminals. Accordingly, in 1993, automation in container terminals has been introduced at ECT’s Delta terminal in Rotterdam in order to reduce the operational costs. Nowadays there are several (semi-) automated container terminals worldwide and currently there are four in the planning stage. In the first automated container terminals automated guided vehicles (AGVs) were used for the supply and discharge of containers at the quay cranes. Because the realized quay crane productivities were lower than the theoretical ones, and this is partly caused by the transportation vehicles, other vehicles such as the Lift-AGV (L-AGV) and the automated shuttle carrier (AShC), were developed. In this research a comparison is made between several state-of-the-art automated vehicles to find out which is the best performing vehicle type.
The characteristics of the investigated automated vehicles are elaborated to gain insight in the possibilities of the vehicles. These characteristics are influencing the behaviour of the automated vehicles in container terminals. Whether or not the interchange between the stack or quay cranes is linked and what the vehicles manoeuvrability is. Due to the complexity of the system a simulation model should assist in answering the research questions. Taking into account the requirements, a simulation model has been set up using the simulation library of TBA.
A benchmark model has been defined using the dimensions of automated container terminals which are currently being build of already exist. For each type of vehicle, terminal layouts are designed within the benchmark model. The design of these layouts largely depend on the size of the vehicle and the manoeuvrability, which manoeuvres can it perform and how much space is needed. An implementation for each type of vehicle and each terminal layout has been made in the model. Several peak scenarios with a varying number of vehicles has been performed in order to obtain results which assist in answering the research questions. The output of the model is also used to gain more insight in the behaviour of the different vehicle types. The results must also contribute to the validation of the model.
Considering the quay crane productivities, it can be concluded that according to the results of the performed experiments the L-AGV is the best performing vehicle, however the differences with the other vehicles are not very large. This result deviates from the expectation, which can be explained using the generated output of the simulation. However the use of another type of quay crane could be beneficial for other vehicle types.
Summary in Dutch
Sinds het begin van het container tijdperk, halverwege vorige eeuw, is de toename van de het gebruik van containers gegeroeid. Tegenwoordig wordt meer dan 90 procent van de niet-bulk goederen vervoerd in een container. De competitie is groot tussen de vele rederijen met containerschepen. De vraag naar lagere prijzen per container heeft geleidt tot grotere schepen. Ook het aantal havens dat door een schip wordt bezocht per reis is minder geworden om de prijzen te drukken. Dit heeft als geveolg dat het aantal containers dat in een haven gelost en geladen moet worden steeds groter wordt. Door de competitie tussen havens en container terminals, zijn terminal operators gedwongen om schepen zo snel mogelijk af te handelen tegen een zo laag mogelijke prijs. De personeelskosten vormt een groot deel van de operationele kosten van een container terminal, vooral in landen waar de personeelskosten hoog zijn. Dit heeft geresulteerd in 1993 in de ontwikkeling van de eerste geautomatiseerde container terminal, ECT’s Delta terminal in Rotterdam. Vandaag de dag zijn er verschillende (half-) geautomatiseerde container terminals, en zijn er vier in aanbouw. In de eerste geautomatiseerde container terminal worden AGV’s (Automated Guided Vehicle) gebruikt voor het vervoer van containers tussen de stack en de container kranen. De behaalde productiviteit van container kranen liggen lager dan de theoretische waarden, wat deels wordt veroorzaakt door de geautomatiseerde voertuigen. Dit het geresulteerd in de ontwikkeling van andere voertuigen zoals de L-AGV (Lift AGV) en de AShC (Automated Shuttle Carrier). In dit onderzoek worden de prestaties van verschillende state-of-the-art geautomatiseerde voertuigen met elkaar vergeleken om te kunnen vast stellen welke het beste presteert.
De eigenschappen van de onderzochte voertuigen zijn uitgewerkt om inzicht te krijgen in de mogelijkheden van de voertuigen. De eigenschappen hebben invloed op het gedrag van de voertuigen, zoals de al dan niet gekoppelde overdracht van een container tussen het voertuig en een opslag of kade kraan en de manoeuvreerbaarheid. De onderzoeksvragen worden beantwoord met behulp van een simulatie model, dit vanwege de complexiteit van het systeem. Met gebruik van de simulatie software van TBA is een simulatie model gemaakt, hierbij is rekening gehouden met de gestelde eisen.
Gebruik makende van de afmetingen van bestaande en in aanbouw zijnde geautomatiseerde container terminals is een referentie terminal gedefinieerd. Binnen deze referentie terminal zijn er voor elke type voertuig lay-outs gemaakt. Het ontwerp van deze lay-outs hangen in grote mate af van de afmetingen van het voertuig, de manoeuvreerbaarheid en de ruimte welke het nodig heeft tijdens deze manoeuvres. Voor alle voertuigen zijn deze lay-outs ge¨ımplementeerd in het simulatie model. Verschillende piek scenario experimenten met een vari¨erend aantal voertuigen zijn uitgevoerd om resultaten te verkrijgen welke moeten bijdragen aan het beantwoorden van de onderzoeksvragen. De verkregen resultaten worden ook gebruikt voor het verkrijgen van inzicht in het systeem gedrag. Tevens dragen de resultaten bij aan de validatie van het model.
Op basis van de verkregen resultaten voor de kade kraan productiviteit, kan er gesteld worden dat binnen de uitgevoerde experimenten, de L-AGV het beste presteert. Hoewel de verschillen met de andere voertuigen niet groot zijn. Dit resultaat wijkt af van de verwachting, dit kan
worden verklaard aan de hand van de andere verkregen resultaten. Toch zou het kunnen zijn dat het gebruik van een ander type kade kraan resulteer in betere resultaten voor de andere voertuigen.
List of Abbreviations
AGV Automated guided vehicle ALV Automated lifting vehicle Lift-AGV Lift automated guided vehicle P-AGV Portal automated guided vehicle QC Quay crane
RMG Rail mounted gantry crane RTG Rubber tired gantry crane TEU Twenty-foot equivalent unit TOS Terminal operating system TP Transfer point
List of Figures
1.1 Evolution of container ships . . . 1
1.2 Automated vehicles . . . 3
1.3 Structure of the research . . . 4
2.1 HHLA Container Terminal Altenwerder in Hamburg . . . 8
2.2 Parallel and perpendicular stacking . . . 8
2.3 Terminal overview and container movements . . . 9
2.4 Container quay crane . . . 10
2.5 The most common used spreaders . . . 10
2.6 Automated stacking cranes . . . 11
2.7 Battery AGV . . . 12
2.8 Lift AGV . . . 13
2.9 Automated shuttle carrier . . . 14
2.10 The automated straddle carrier . . . 15
2.11 An impression of the P-AGV . . . 15
2.12 Designs of 1-over-0 ALVs . . . 16
2.13 Examples of landside vehicles . . . 16
2.14 General apron layout . . . 17
2.15 IT infrastructure of automated container terminals . . . 18
3.1 Simulation model architecture . . . 22
3.2 Process of the terminal operating syste . . . 23
3.3 Quay crane in the simulation . . . 24
3.4 Code fragment of moving obstacle in backreach quay crane . . . 25
3.5 Job assignment for vehicles . . . 25
3.6 90 degree curve claims . . . 26
3.7 Original and improved s-curve claim for an AGV. . . 27
3.8 Method for driving s-curve . . . 28
3.9 Improved crab claims . . . 29
3.10 Code fragment for construction crab claim . . . 29
3.11 Assignment procedure stack . . . 29
4.1 Placement of the quay cranes . . . 36
4.2 AGV layout I . . . 38
4.3 ALV layout Ia . . . 39
4.4 ALV layout Ib . . . 40
4.5 P-AGV layout I . . . 41
4.6 Cross sections of terminal layouts . . . 42
4.7 Stack density . . . 44
LIST OF FIGURES
5.1 Vehicle status - AGV model I and II . . . 48
5.2 Quay crane status - AGV model I and II . . . 48
5.3 Quay crane productivity - AGV model I and II . . . 49
5.4 Vehicle status - L-AGV model I and II . . . 50
5.5 Quay crane status - L-AGV model I and II . . . 50
5.6 Quay crane productivity - L-AGV model I and II . . . 51
5.7 Vehicle status - AShC model Ia and Ib . . . 52
5.8 Quay crane status - AShC model Ia and Ib . . . 52
5.9 Quay crane productivity - AShC model Ia and Ib . . . 53
5.10 Quay crane productivity - AShC model Ia and IIa . . . 53
5.11 Vehicle status - P-AGV model I and II . . . 54
5.12 Quay crane status - P-AGV model I and II . . . 55
5.13 Quay crane productivity - P-AGV model I and II . . . 55
5.14 Quay crane productivity - All vehicle types . . . 56
5.15 Vehicle status - 3 and 4 vehicles . . . 57
5.16 Vehicle cycle time per box - 3 and 4 vehicles . . . 57
5.17 Vehicle driving time per box - 3 and 4 vehicles . . . 58
5.18 Vehicle distance per box - 3 and 4 vehicles . . . 58
5.19 Average velocity vehicles - 3 and 4 vehicles . . . 59
5.20 Quay crane status - 3 and 4 vehicles . . . 59
5.21 Quay crane productivity per move type - 3 and 4 vehicles . . . 60
5.22 Waterside RMG status - 3 and 4 vehicles . . . 60
5.23 RMG productivity - 3 and 4 vehicles . . . 61
5.24 Vehicle cycle time per box - 5 and 6 vehicles . . . 62
5.25 Vehicle driving time per box - 5 and 6 vehicles . . . 62
5.26 Vehicle distance per box - 5 and 6 vehicles . . . 63
5.27 Average velocity vehicles - 5 and 6 vehicles . . . 63
5.28 Quay crane status - 5 and 6 vehicles . . . 64
5.29 Traffic density count - 60 vehicles . . . 64
5.30 Traffic density occupation - 60 vehicles . . . 65
B.1 Ackerman condition for a front-wheel-steering vehicle . . . 86
B.2 Symmetric (left) and asymmetric (right) curves of an AGV . . . 86
B.3 Ackerman condition for an AShC . . . 87
B.4 Navigation principle of AGVs . . . 87
B.5 A clothoid with A = 10 . . . 88 B.6 AGV curve . . . 89 B.7 AShC curve . . . 91 B.8 P-AGV curve . . . 92 B.9 Construction of a s-curve . . . 93 B.10 S-curve AShC . . . 94 B.11 Extended s-curve . . . 95
B.12 Crab move AGV & L-AGV . . . 96
LIST OF TABLES
List of Tables
2.1 Main characteristics of automated vehicles . . . 12
4.1 Specifications of automated container terminals . . . 35
4.2 Benchmark terminal main particulars . . . 36
4.3 Measurements apron layouts . . . 42
4.4 Quay crane settings . . . 43
4.5 Stack crane settings . . . 43
5.1 Total number of vehicles for a quay crane productivity of 35 boxes per hour . . . 65
5.2 Total number of vehicles for a quay crane productivity of 35 boxes per hour . . . 65
B.1 AGV curve data . . . 90
B.2 AShC curve data . . . 90
CONTENTS
Contents
Assignment ii
Summary iii
Summary (in Dutch) iii
List of abbreviations vii
List of Figures x List of Tables xi 1 Introduction 1 1.1 Background . . . 1 1.2 Research question . . . 3 1.3 Research approach . . . 3
2 Automated Container Terminals 7 2.1 Yard areas . . . 7 2.2 Equipment . . . 9 2.2.1 Quay cranes . . . 9 2.2.2 Stacking Cranes . . . 11 2.2.3 Waterside vehicles . . . 11 2.2.4 Landside vehicles . . . 16 2.3 Apron layout . . . 16 2.4 IT infrastructure . . . 17 2.5 Processes . . . 17 2.5.1 Job dispatching . . . 18 2.5.2 Routing . . . 19 2.5.3 Claiming . . . 19 3 Implementation 21 3.1 Requirements . . . 21
3.2 Simulation model architecture . . . 21
3.3 Terminal operating system . . . 23
3.4 Quay cranes . . . 23
3.5 Vehicles . . . 24
3.5.1 Job dispatching . . . 24
3.5.2 Routing . . . 24
CONTENTS
3.6 Stack cranes . . . 27
3.7 Trucks . . . 27
3.8 Key performance indicators . . . 30
3.9 Verification and Validation . . . 33
4 Simulation Experiments 35 4.1 Layouts . . . 35
4.1.1 Benchmark terminal . . . 35
4.1.2 AGV and L-AGV . . . 36
4.1.3 ALV . . . 37 4.1.4 P-AGV . . . 37 4.2 Settings . . . 43 4.3 Scenarios . . . 44 5 Results 47 5.1 AGV . . . 47 5.2 L-AGV . . . 49 5.3 AShC . . . 49 5.3.1 Layouts Ia and Ib . . . 49
5.3.2 Layouts Ia and IIa . . . 51
5.4 P-AGV . . . 51 5.5 Vehicle comparison . . . 54 5.5.1 3 and 4 vehicles . . . 54 5.5.2 5 and 6 vehicles . . . 56 5.5.3 Traffic density . . . 61 5.6 Discussion . . . 65
6 Conclusions and Recommendations 67 6.1 Conclusions . . . 67 6.2 Recommendations . . . 68 Bibliography 74 A Paper 75 B Manoeuvrability of vehicles 85 B.1 Vehicle steering . . . 85 B.2 Curve control . . . 87 B.3 90 degree curve . . . 88 B.4 S-curve . . . 93 B.5 Crabbing . . . 95
CHAPTER 1. INTRODUCTION
Chapter 1
Introduction
The subject of this chapter is the problem description of this research. At first the motivation for this research together with some background information will be given in Section 1.1. In Section 1.2 the main research question and the related sub questions will be outlined. Finally, in Section 1.3 the approach of this research is discussed. Some concepts regarding container terminals will be briefly discussed in this chapter, these are explained in more detail in subsequent chapters.
1.1
Background
Since the beginning of the container era in the middle of the last century (Jansen, 2006), the containerization is growing. Nowadays more than 90 percent of the world’s non-bulk cargo is being transported in a container (Ebeling, 2009). With many shipping liners deploying container vessels on the world seas, the competition is strong. Therefore the need to lower the price per TEU (Twenty-foot Equivalent Unit, standard container size) has resulted in the development of vessels with increasing sizes, which is depicted in Figure 1.1. Continuing on cost reduction,
1.1. BACKGROUND
shipping lines tend to make fewer port calls with their vessels, as discussed by Kemme (2011), Pawellek and Sch¨onknecht (2011), and Schinas and Dionelis (2011). Consequently the call sizes, i.e. the number of containers that have to be unloaded and loaded per vessel in a port, will increase. Because of the competition between harbours and container terminals, terminal operators are forced to handle container vessels as fast as possible while reducing the operational costs. Rademaker (2007) states that, especially in high labour regions, the labour costs are a large part of the operational costs of container terminals. Accordingly, in 1993, automation in container terminals has been introduced at ECT’s Delta terminal in Rotterdam (ECT, 2013). Automation results in a reduction of the operational costs, however the investment cost are higher, as discussed by Saanen et al. (2006). Nowadays there are several (semi-) automated container terminals worldwide and currently there are four in the planning stage (Fossey, 2012). This research will focus on automated container terminals (ACTs). Optimizing the processes at ACTs have been the subject of discussion of many investigations, were consideration was given to the type of automated equipment as well as the implementation strategies. The most, for this study, relevant studies will be discussed in this report.
The global layout of container terminals is almost always the same (Meisel, 2009) and discussed in more detail in Chapter 2. Vessels are berthed at the quay, quay cranes (QCs) handle containers between the quay and the vessels. The container transport between the QCs and the stack, which is called the horizontal transport, can be done by several types of vehicles. Incoming and outgoing containers are temporary stored in the stack, each stack block is served by one or more stacking cranes. On the other side of the stack containers can enter or leave the terminal by either truck or train. In automated container terminals the stacking cranes and the vehicles used for the horizontal transport between the quay crane and the stack, are automated. These equipment pieces are not manned any more and are controlled by a computer system. In semi-automated container terminals only the stacking cranes are automated, the vehicles are still manned.
The number of QCs that can handle a vessel simultaneously is limited by the size of the cranes and vessel (Park and Kim, 2003), so the handling time of a ship depends on the productivity of the QCs (expressed in boxes per hour [bx/h]). The achieved productivity of QCs deviates from their theoretical maximum, as discussed by Steenken et al. (2004). One of the reasons for this is the interaction with the horizontal transport. For example, when a vessel is being loaded and a container carrying vehicle is (for some reason) delayed, the QC has to wait before it can continue working. A delay of the vehicle may occur by congestion with other vehicles and has an influence on their productivity. So improving the productivity of the vehicles will result in a decrease in the amount of vehicles needed, which in turn reduces the chance on congestion, which in turn reduces the chance on delays. The most recent development concerning optimizing the horizontal transport in ACTs has led to the development of the Lift-AGV (Automated Guided Vehicle) and the Automated Shuttle Carrier (AShC).
The Lift-AGV and the AShC, depicted in Figure 1.2a and 1.2b respectively, are both automated vehicles designed for the horizontal container transport. These together with the AGV are explained in detail in Chapter 2. AGVs are being used on terminals in Rotterdam and Hamburg. The Lift-AGV will operate for the first time on the two new container terminals which are currently being build at the Maasvlakte 2 in Rotterdam. The AShC has not been implemented yet. In an attempt to improve the performance of these automated vehicles Gottwald is currently developing a new type of automated vehicle, called the P-AGV (Portal - Automated Guided Vehicle). In short, its design combines the Lift-AGVs manoeuvrability and the AShCs possibility of picking up and putting down containers. Because of the manoeuvrability and the decoupling of the process at the yard and the quay cranes, the designers expect the Portal-AGV to be more efficient compared to its opponents. All the advantages and disadvantages of the
CHAPTER 1. INTRODUCTION
(a) Lift-AGV (Gottwald Port Technology, 2008) (b) AShC (Kalmar, 2013)
Figure 1.2: Automated vehicles
P-AGV regarding its opponents, the AGV, Lift-AGV and the AShC, are further explained in Chapter 2. An investigation should find out whether or not the development of the P-AGV should be continued.
1.2
Research question
In order to be able to judge the efficiency of the designed P-AGV, it has to be compared with all, comparable vehicles. These are the AGV, Lift-AGV and the AShC. Therefore the difference between these vehicles needs to be investigated, and the advantages and disadvantages should be elaborated. The resulting main research question reads:
Will the deployment of the Portal-AGV, for the horizontal container transport at au-tomated container terminals, be more efficient, compared to other, existing, auau-tomated vehicles?
The related sub questions give an insight in the potential of the P-AGV design and the areas which should be investigated:
• What are the characteristics of the considered vehicles?
• What kind of simulation model should be used for the comparison of the vehicles, in order to gain results which are as realistic as possible?
• Considering the space for the horizontal transport between the quay cranes and the stack (and vice versa), which layouts should be used for the deployment of these vehicles? • How should the performance of the automated vehicles be evaluated?
This report contains information and results of the research which are used for answering the questions listed above. The structure of the report corresponds to the used approach, which is discussed in the next section.
1.3
Research approach
The used approach in order to formulate answers to the discussed research questions will be outlined in this section. To get familiar with the global structure of automated container terminals, the general concepts will be studied at first. These include the yard areas, equipment types and
1.3. RESEARCH APPROACH
Figure 1.3: Structure of the research
ongoing processes. The considered automated vehicles will be studied more in depth to gain insight in the characteristics of each vehicle. Hereafter a simulation model of an automated container terminal will be set up in which a benchmark terminal will be implemented. After determining the key performance indicators, simulation experiments will be performed for all vehicles. Finally all results will be evaluated in order to formulate conclusions and make recommendations for future research. An overview of the discussed approach is listed below.
• Study the general concepts of automated container terminals. • Study the characteristics of the considered automated vehicles. • Set up a simulation model.
• Implement the considered vehicles in the simulation model using a benchmark terminal. • Determine the key performance indicators which will be measured during simulation runs. • Define and execute experiments.
• Interpret the results and conduct conclusions. • Make recommendations for future research.
The structure of the report is depicted in Figure 1.3. In Chapter 2 the general yard layout of automated container terminals together with the ongoing processes will be discussed. The present equipment will be explained, with special attention to automated vehicles. In Chapter 3 the used simulation model together with the determined key performance indicators are discussed.
CHAPTER 1. INTRODUCTION
Subsequently the benchmark terminal and the implementation of the vehicles into this terminal are illustrated in Chapter 4. All results are presented in Chapter 5. Finally in Chapter 6 the conclusions and recommendations are formulated.
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
Chapter 2
Automated Container Terminals
In order to get familiar with automated container terminals (ACTs) and the used concepts in this report, the structure, operations and equipment types on container terminals will be discussed in this chapter. Section 2.1 starts with the global yard layout and the on going processes. In Section 2.2 various types of terminal equipment are discussed. Some general consideration regarding apron layouts are discussed in Section 2.3. Besides hardware, software is needed for the control of ACTs which is discussed in Section 2.4. In Section 2.5 the main processes on automated container terminals are elaborated.
2.1
Yard areas
The three main areas on container terminals which can be distinguished are the waterside, stack and landside. In Figure 2.1 an overview of a automated container terminal in Hamburg is given, the three areas are indicated by respectively blue, red and green. These areas will be explained below, there will be referenced to the letters in this figure.
Waterside
The waterside of a container can be divided into the berth, quay and apron (indicated by A,B and C respectively). The sea-going vessels are at the berth. At the quay the container cranes takes care of the container interchange between ship and transporting vehicle. The apron is the driving space for the transporting vehicles, to transport containers from the quay crane to the stack and vice versa. The layout of the apron is discussed in section
Stack
Temporary storage of containers takes place in the stack (E). The interchange between the stack and the waterside transporting vehicles takes place in the area indicated by D and the interchange with the landside vehicles in F. The stack can be placed parallel or perpendicular to the quay wall. The choice of stacking direction depends, among others, on the type of equipment used for the waterside transport and the stack. As is discussed in Wiese et al. (2011), the stacks in automated container terminals are always placed perpendicular on the quay wall because of safety and operational reasons (as in Figure 2.1). Automation requires a strict separation of manned and automated equipment from the viewpoint of safety. In perpendicular stacking the interchange between automated vehicles and the stack takes place on one side of the stack and the interchange with trucks on the other side. The travel distance between the quay crane and stack is also minimized using perpendicular stacks, the two stacking variants can be seen in Figure 2.2. Accordingly in this research only perpendicular stack will be considered. The
2.1. YARD AREAS
(a) Top view
(b) Top view with indicated areas
Figure 2.1: HHLA Container Terminal Altenwerder in Hamburg (Google Earth, 2013)
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
capacity of the stack influences the maximum achievable throughput of a container terminal as is discussed in Watanabe (2001).
Land-side
The landside of the terminal makes the connection with the hinterland. There are three hinterland transport types, trucks, trains and barges. Although barges often are in the same berth as the sea-going vessels and sometimes even are handled by the same cranes, still they are considered being part of the hinterland transport. Therefore J (in Figure 2.1b) indicates the part of the quay where barges are handled. The truckgate is indicated by I after which truck pick or drop their container in G. The rail terminal is indicated by H. Using these main areas on container terminals, 3 types of containers (flows) can be distinguished. Import containers, arrive at the quay (by deep sea-going vessels) and leave, possibly via the stack, the terminal at the land-side. Export containers enter the yard at the land-side an leave the container terminal, possibly via the stack, at the waterside. The last type are transshipment containers, these enter and leave the container terminal on the waterside, and may have a stay at the stack. Figure 2.3 depicts the terminal areas and the possible container movements.
Figure 2.3: Terminal overview and container movements
The next section will provide concise information about the equipment types which can be found on automated container terminals.
2.2
Equipment
2.2.1 Quay cranes
Lifting a container from and to a vessel is done by quay cranes. If such a vessel is a sea-going one, the cranes are referred to as ship-to-shore cranes (Achterberg, 2012), which is abbreviated as STS
2.2. EQUIPMENT
Figure 2.4: Container quay crane (Liebherr, 2012)
cranes. In the remaining part of this report the term quay crane (QC) will be used for this type of crane. Figure 2.4 gives an example of a quay crane. The distance indicated by A is the distance between the legs of the quay crane, measured from waterside rail to landside rail. B indicated the cranes maximum outreach measured from the waterside rail to the maximum position of a container towards the waterside. The measurement indicated by C is the back-reach of the crane. The back-reach is measured between the quay cranes landside rail and the maximum position of the container towards the landside. An extensive overview of this type of cranes is given by Achterberg (2012). The number of containers a quay crane can lift at once depends on the used spreader. With a simple spreader only one container can be lifted, this can be either a 20 ft or a 40 ft container. A twin-lift spreader is capable of lifting two 20 ft containers or one 40 ft. The newest type of spreader is a tandem-lift one, which can lift four 20 ft or 2 40 ft containers. In Figure 2.5 these 3 types of spreaders can be seen. As discussed in Achterberg (2012) the
(a) Single-lift spreader (b) Twin-lift spreader (c) Tandem-lift spreader
Figure 2.5: The most common used spreaders (Bromma, 2013)
single-lift spreader is rarely mounted in STS cranes. In order to be able to use a tandem-lift spreader, all containers must be on the same level, which is not always the case because not all containers have the same height. In such cases a change of spreader is needed which takes time. Therefore a twin-lift spreader is the most used spreader type and it will be used in this
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
(a) RTG (b) RMG (c) OBC
Figure 2.6: Automated stacking cranes
simulation.
2.2.2 Stacking Cranes
In (semi-) automated terminals the stacking cranes are always automated. The first phase of automation on container terminals were automated stacking cranes (ASC). Three types of ASC can be distinguished, Rail Mounted Gantry Cranes (RMG), Rubber Tired Gantry Cranes (RTG) and Overhead Bridge Cranes (OBC). The second one has been automated recently and therefore it has not yet been deployed on container terminals. The benefit of this type of crane is that is does not need additional infrastructure (rails or elevated rails) and therefore can shift between stacks. As the name indicates the RMGs are fixed to rails and therefore are dedicated to one stack. Just as with OBCs, only in that case the rails is elevated. The size of RTGs and RMGs can go over more than 10 containers wide and 5 high. The stacking width and height of OBCs can be even larger, resulting in a increase in stacking capacity. However more stacking more containers on top of each other also results in additional crane moves to reach the bottom one when needed. More information about stacking cranes can be found in Hekman (2001), examples of the three discussed stacking cranes are given in Figure 2.6.
2.2.3 Waterside vehicles
At the waterside of automated container terminals, automated vehicles are being used for the horizontal transport of containers. Currently the AGV, Lift-AGV, AShC and the AutoStrad (Automated Straddle carrier) are on the market available. These vehicles will be discussed in
this section, including the recently designed P-AGV. AGV
An AGV consists of a body-frame with 4 wheels. All wheels can be steered, resulting in a highly manoeuvrable vehicle. This is explained in Appendix B. Depending on the type of AGV a diesel engine or batteries are located in the body. Containers are loaded on top of the body and it can carry either one 40 [ft] or two 20 [ft] containers. In Figure 2.7 the newest battery driven AGV designed and produced by Gottwald Port Technology can be seen. The main characteristics this AGV are given in Table 2.1. The AGV is only capable of transporting containers, for the loading or discharging of the vehicle another equipment type is necessary. When an AGV delivers a container to the stack, it has to wait until the stack crane is available. Only once the stack crane has grabbed the container the AGV is allowed to leave. This is called a linked interchange. The interchange at the QC is also linked, the vehicle has to wait for handling by the QC. The first implementation of AGVs at a container terminal was in 1993 at ECTs Delta terminal in Rotterdam (ECT, 2013).
2.2. EQUIPMENT
Figure 2.7: Battery AGV (Gottwald Port Technology, 2009)
Vehicle AGV L-AGV AShC P-AGV
Length [m] 14.84 14.84 9.2 / 13.72 9.2
Width [m] 2.98 2.98 5.1 5.0
Height [m] 1.7 2.2 10.13 7.23 Dead weight [ton] 25 34 47 39 Maximum load [ton] 60 60 50 60 Maximum speed [m/s] 6 6 8.3 / 6.9 6 Maximum speed curves [m/s] 3 3 3 3 Maximum crab speed [m/s] 1 1 N/A 1 Minimum curve radius [m] 10 10 7 7
Table 2.1: Main characteristics of automated vehicles
(Gottwald Port Technology, 2008, 2009; Kalmar, 2013) (Kalmar, 2013).
Lift-AGV
The main characteristics of the L-AGV are almost the same as for the AGV, except for the height and the dead weight, as can be seen in Table 2.1. Just as the AGV the L-AGV is able to carry on 40 [ft] or two 20 [ft] containers. In addition, the L-AGV is capable of lifting its load. Using a rack, this vehicle can load or unload its own containers. In Figure 2.8 a L-AGV is depicted, in this figure the rack positioned on the right of the vehicle. When it approaches a rack loaded, the vehicle will stop in front of the rack and lifts its load. Then the vehicle drives into the rack. After lowering its platform the containers will linger in the rack and the vehicle can drive away. Loading a container involves the same actions, only in reversed order. Until now these racks are only available fixed to the ground, no solutions for usage at the quay crane have been found yet. Consequently the racks are only placed at the transfer points (TPs) of the stack, the quay crane loads and unloads the vehicle at the quay. Therefore the interchange at the stack is unlinked, at the quay crane its linked. On the terminals of AMPT and RWG on
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
Figure 2.8: Lift AGV (Gottwald Port Technology, 2008)
the Maasvlakte 2 in Rotterdam, the first implementation of the L-AGV will take place. While writing this thesis the test phases of both terminals have been started (APM Terminals, 2013; Rotterdam World Gateway, 2013).
AShC
An automated shuttle carrier (AShC) is 1-over-1 (automated) straddle carrier, which means that it the maximum lifting height is two container. Where a straddle carrier is used for the transportation and stacking of containers, an AShC is only used for the transport of containers (due to its limited stacking height). This vehicle is able to pick-up and drop a container on its own, without the use of a stacking or quay crane. In order to do this well, the vehicle has to scan the position and orientation of the container before driving over it. This time consuming operation is because of the unknown position of the container and its deviating orientation with respect to that of the vehicle. An advantage of this vehicle is that it can pass grounded containers while its loaded by just driving over it. The AShC is given in Figure 1.2b. The maximum length of the vehicle depends on the load, with a maximum of the length of a 45[f t] container, which is equal to 13.72[m]. The minimum length of the vehicle is 9.2[m], which is the maximum length of the body of the vehicle. This vehicle has 6 wheels of which the first two and the last two can turn, the middle pair of wheels is fixed. This results in a limited manoeuvrability with respect to the AGV (and L-AGV), which is explained in Appendix B. The main characteristics given in Table 2.1 are acquired from the manned version of this shuttle carrier, the differences in dimensions with the automated version is assumed to be negligible. The speeds of the automated vehicle may be lower due to take into account for the communication delay. In researches which involve the simulation of ALVs the assumed velocity of a loaded vehicle is not higher than 6[m/s] as in Meer (2000) and Vis and Harika (2004). Meer (2000) uses for ALVs a maximum speed in curves, loaded and unloaded, of 3[m/s].
2.2. EQUIPMENT
Figure 2.9: Automated shuttle carrier (Kalmar, 2013)
AutoStrad
The automated straddle carrier (AutoStrad, Kalmar (2013)) is a 3-over-1 straddle carrier which is used for the transport and stacking of containers, as can be seen in Figure 2.10. Due to its stacking capability, there is no need for stacking cranes. However, the vehicle has to drive through the stack, which requires space between each row of containers. Also the stacking height is limited to 2 containers because the autostrad is a 3-over-1 straddle carrier which implies that the maximum lifting height is 3 containers. Consequently, as discussed in Hekman (2001) and Watanabe (2001), the stack capacity is much lower compared to stacks with stacking cranes when regarding the same amount of available land. Therefore this type of vehicle is excluded from this research.
Portal-AGV
In essence the Portal-AGV (P-AGV) will be a 1-over-0 straddle carrier, so its capable of lifting a container somewhat of the ground. It cannot stack containers on top of each other or pass a grounded container. An impression of the P-AGV is given in Figure 2.11. The design parameters are given in Table 2.1, the dimensions are comparable with those of the AShC except for the height. Speeds correspond to those of the (L-)AGV. This vehicle has 4 wheels which all can steer, the advantages of this is explained in the previous section. Just as with the ALV, the P-AGV has to scan the position and orientation container before driving over it. The idea of a 1-over-0 lifting vehicle is not a new concept. In Meeusen and Evers (1994) the design of an automated (1-over-0) lifting vehicle is proposed for the inter-terminal transport of containers, which can be seen in Figure 2.12a. To investigate their dispatching methods for ALVs, Nguyen and Kim (2009) using an ALV which is developed by the Korea Maritime Institute in co-operation with
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
Figure 2.10: The automated straddle carrier
2.3. APRON LAYOUT
Seoho Electric Co. This design can be seen in Figure 2.12b.
(a) Meeusen and Evers (1994) (b) Nguyen and Kim (2009)
Figure 2.12: Designs of 1-over-0 ALVs
2.2.4 Landside vehicles
In the current automated terminals all landside vehicles are manned. The used vehicles are vehicles which also can be found at the waterside of manned terminals. Examples of these vehicles are shown in Figure 2.13. Can be automated or manned (often manned), can be any type of equipment which also can be found on (manned or semi-automated) container terminals. A detailed description of these type of vehicles is made by Onneweer (1992).
2.3
Apron layout
The design of the apron depends on the main characteristics of the used transporting vehicles as discussed in Ranau (2011). Lane widths for example depend on the width of the vehicle and the required transversal space during turning. The apron consist of 3 main zones. In the first zone the quay lanes are located. All vehicles are driving in the same direction on these lanes. In the newest automated terminals, these are located in the backreach of the quay crane. This is done for safety reasons, to get a strict separation between manned equipment and automated equipment. The space in the gauge of the crane (between the rails) is used for hatch covers, service lanes and for the supply and discharge of special cargo. The transfer points of the quay cranes are located on these lanes. The second zone is the buffer zone, all vehicles pass a buffer on their route to or from the quay crane. In the last zone the highway lanes are located. The driving direction of these lanes is alternating. In the case of 4 highways the two located the closest to the buffer are being used to drive to the buffer, the two lanes located on the stack side
(a) Terminal truck (b) Multi-trailer truck (c) Reach stacker (d) Empty handler
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
Figure 2.14: General apron layout
are being used to drive to the stack. The zones and routes are depicted in Figure 2.14. The arrows at the left side of the figure indicates the driving direction of the lanes. The circles around the transfer points of the quay cranes indicate the alternating positions of the transfer points. In this case quay crane transfer points are located alternating on lanes 2-3 and 5-6 (lane numbers can be found at the right side of the figure). Lanes 1 and 4 are used as passing lanes. Using alternating transfer point location results in more space for the vehicles to enter or leave the quay lanes because it is not allowed to cross the transfer points.
2.4
IT infrastructure
In automated container terminals the information technology (IT) infrastructure has a very important role. It is responsible for the planning, allocation and execution of jobs. The IT infrastructure exists of several software packages which communicate which each other. The central controller of a container terminal is the Terminal Operating System (TOS). In this system jobs are planned and scheduled. Jobs results in equipment orders, which are dispatched by the TOS to the equipment managers. Also all information regarding containers, such as size, weight, positions, origin and destination, is stored in the TOS. Each equipment type has a manager which dispatches the received orders to individual equipment pieces. Equipment managers are also responsible for managing the interchange between equipment types. In the case of automated vehicles the equipment manager determines the collision and deadlock free routes. Each equipment piece has again its own manager, this one is responsible for the executing of the assigned order by controlling the vehicle. In the case of manned equipment, the latter manager can be regarded as the driver. The IT infrastructure is depicted in Figure 2.15, in which the landside managers are not elaborated as is the case with the waterside ones.
2.5
Processes
On manned container terminals the job dispatching is the most important process which is performed by the terminal operating systems. This system dispatches the order to a manned vehicle. An driver knows the origin and destination and is able to determine the best or shortest
2.5. PROCESSES
Figure 2.15: IT infrastructure of automated container terminals
route based on experience. While driving drivers react on other vehicles based on what they see and some simple priority rules. In automated container terminals the job dispatching is comparable, but some system has to determine te route and be able to drive collision free. Regarding the automated vehicles, these three processes are the most important ones and will be discussed in the next subsections.
2.5.1 Job dispatching
The process of assigning jobs to equipment is called job dispatching. The objective in this process can be minimizing costs, driving times, driving distances waiting times or a combination of these. The dispatching of vehicle jobs in container terminals has been discussed in the literature extensively. Before an algorithm can be made some choices have to be made, these have an influence on the complexity of the algorithm. Vehicles can either serve one specific quay crane (dedicated), or they may serve any crane (pooling) (Rashidi and Tsang, 2011). The vehicles discussed in the preceding are all capable of transporting one or two containers (depending on the size). A quay crane can lift two 20 [ft] containers in one move, if these containers are located in different stack, a vehicle has to visit two stacks. This is called multi-load as discussed by Grunow et al. (2004). The complexity is reduced if only one load is assigned to one vehicle (single-load), but this increases the total driven distance. Another choice is to dispatch the jobs online or offline (Grunow et al., 2004; Steenken et al., 2004). If all necessary information is available in advance all decisions can be made before the process starts. However if this is not the case, real-time dispatching is required.
In container terminals, job dispatching is a complex task. In order to use the vehicles as efficient as possible, the vehicles are pooled and can carry multi-loads. Also the environment is very dynamic and contains many uncertainties. Container destinations sometimes change and
CHAPTER 2. AUTOMATED CONTAINER TERMINALS
due to the interaction between vehicles, driving times vary. Therefore online job dispatching is needed, requiring short calculation times (Steenken et al., 2004). In all references discussed in this section, sophisticated algorithms are presented to minimize some objective. However they have one common problem, when the number of vehicles and jobs becomes too large, the calculation time also becomes too large. Therefore heuristic algorithms are used for the job dispatching, these do not guarantee fully optimized solutions but can be calculated in a short time period. In Chapter 3 the implementation of the job dispatching in the simulation model is discussed, these algorithms is similar to the ones that are used in terminal operating systems. 2.5.2 Routing
Vehicle routing is interrelated with job dispatching. During the process of assigning jobs to vehicles the corresponding routes are considered. The length of the route or the expected driving time is used in the decision of which vehicle is the most suitable for a certain job. Vis and Harika (2004) makes a distinction between static and dynamic routing. When a vehicle always drives exactly the same route between A and B, its is called static routing, otherwise its dynamic. In Duinkerken et al. (2006) a distinction is made between routing AGVs along a predefined mesh or let them drive in a straight line from origin to destination. In both cases the number of possible routes is limited (assuming a limited number of origins and destinations), however the latter option tends to free routing (unlimited number of possible routes). An overview of routing algorithms for AGVs is given by Dahari and Liu (2012). However, many of these are only suitable for relatively small AGV systems (approximately less than 10 AGVs), so not for container terminals. This is due to the complexity of the calculation which requires to much time for large systems.
In container terminals, vehicles are routed along a predefined infrastructure as discussed in Section 2.3. This reduces the complexity of the routing problem. Routes are determined in real time with an heuristic algorithm which makes decisions based on free transfer point and buffer positions.
2.5.3 Claiming
In order to prevent automated vehicles for colliding, claiming is used. Claiming is the process of area reservation for a vehicle. As discussed in Bae et al. (2007), a vehicle reserves an amount of space, during the time period that an area is claimed by a vehicle, other vehicles are not allowed to enter that area. For a driving vehicle the claimed space is large enough to come to a full stop, so the claimed space depends on the velocity and the deceleration. With claiming there is a risk for deadlocks, in Lehmann et al. (2006) deadlocks are described as “a situation where one or more concurrent processes in a system are blocked forever because the requests for resources by the processes can never be satisfied ”. The design of the apron can contribute to the prevention of deadlocks. Defining lanes with a fixed driving direction prevent deadlocks of oncoming vehicles. The width of adjacent lanes depends on the space vehicles need to make a turn. Other deadlocks can be prevented by a central controller. Prospected deadlocks are prevented by intervention of such a controller.
CHAPTER 3. IMPLEMENTATION
Chapter 3
Implementation
In this chapter the implementation of the simulation model is discussed. The model is created using TBAs TIMESQUARE (TBA, 2013). This is an extensive container terminals simulation library created in eM-Plant (Tecnomatix, 2013). Section 3.2 starts with the overall structure of the model. Then the implementation of the equipment types will be discussed in Sections 3.4 to 3.7. In these sections special attention is given to the adoptions that have been made to the simulation library for this research. Finally the key performance indicators and the produced output is discussed in Section 3.8.
3.1
Requirements
The used model is a simulation model. As discussed by Law and Kelton (1991), from a simple mathematical model it is possible to get an exact, analytical solution. For highly complex system, analytical solutions can often not be found and the model must be numerically investigated by means of simulation. The simulation model must be able to assist in answering the main research question and the related sub-questions. The main goal of the model is to investigate the performance of automated vehicles. Therefore a container terminal should be modelled in which the vehicles are implemented. Components that affect the behaviour, and hence the performance, should be taken into account in the model. The components include quay cranes, waterside stack cranes and the terminal operating system. To include the interaction between the waterside and landside stack crane, the latter one will be modelled too. Generated trucks on the landside will provide jobs for the landside stack crane. To be able to compare the automated vehicles, the behaviour of the system must be monitored. Measurements including driving times, distances and productivities must be logged. These measurements are also needed for the validation of the model. The above discussed requirements are listed below:
• The model should assist in answering the research questions. • The model must represent a real container terminal.
• All components which interact with the automated vehicles should be included in the model.
• The behaviour of the system must be monitored.
3.2
Simulation model architecture
The architecture of the simulation model is close to the IT infrastructure as discussed in Chapter 2 and is depicted in Figure 3.1. The input of the simulation model consist of information and
3.2. SIMULATION MODEL ARCHITECTURE
Figure 3.1: Simulation model architecture
settings in the model. This includes the ratio between 20 and 40 [ft] containers (TEU factor), the number of automated vehicles and arrival patterns of trucks. The used settings are discussed in Chapter 4.
During the initialization phase of the simulation all equipment pieces are created and started. For each quay crane loading and unloading plans of ships are made, the ships themselves are not simulated. These plans results in orders for the quay cranes, automated vehicles and stack cranes. Stack cranes also receive orders from the visiting trucks. Trucks are simulated, because they pick-up or drop-off containers at the landside of the stack. When the simulation starts the orders will be scheduled by the planning (which is comparable with the Terminal Operating System as discussed in Section 2.4). From the planning the orders will be send to the equipment dispatchers, which dispatches the orders to quay cranes, stack cranes or vehicles. When equipment receives a order, it will start to perform it. During the initialization phase only a limited amount of order is created, the majority is created during runtime. The planning also contains the container database, which includes information about the container size, weight, origin, destination and current location.
The grounding module determines for each container the location where it need to be placed in the stack. This decision is based among others on the origin and destination of the container.
The interchange between vehicles and cranes (quay cranes or stack cranes) takes place at transfer points (TPs) and is being handled by the interchange control. If the interchange is linked, as discussed in Chapter 2, the vehicle must enter first the TP after which it can be handled by the crane. In the case of an unlinked interchange the TP must be free of equipment before a vehicle or crane can use the TP. The transfer point manager, keeps track of all TPs and gives permission if equipment is allowed to enter the TP.
For each vehicle or crane statistics can be written to a database. From the database this information can be loaded into excel to make the data visual. In Section 3.8 the used Key Performance Indicators (KPIs) are discussed, also the graphs which are used to visualize the results are explained in that section.
CHAPTER 3. IMPLEMENTATION
Figure 3.2: Process of the terminal operating system (TBA, 2010)
3.3
Terminal operating system
The scheduling and dispatching of all orders takes place in the terminal. All orders are collected in the terminal operating system (TOS). In here the required steps are determined. For example, a new order is a container which is located in the stack and must be loaded on a ship. This requires orders for one or two stack cranes (depends on whether or not shuffles are necessary), an AGV order and a stack crane order. The steps taken in the process are depicted in the flow diagram in Figure 3.2. On the place of AGV in the diagram, any other vehicle (L-AGV, AShC or P-AGV) can be placed, so the process is equal for all vehicles.
3.4
Quay cranes
Container are being loaded or discharged by quay cranes (QCs). The QCs are equipped with twin-lift spreaders as is discussed in Section 3.4, so they are able to lift one 20 or 40 [ft], or two 20 [ft] containers in one move. The cycle time of the QC (the time it takes to perform one move) depends on its characteristics and the size of the vessel. Figure 3.3 gives an impression of the quay crane. In the figure 3.3 an impression of the quay cranes is given, including some namings (the proportions may vary). As discussed in Chapter 2 the interchange takes place at the transfer points in the backreach of the crane. Containers which are placed on the deck of the vessel, are fixed to each other by twist-locks. Loading containers are grabbed by the QC at the TP, if it needs to be placed on deck the QC will move to the twist-lock platform where it holds the time it takes to install the twist-locks. Then it moves towards the vessel and drops the container at the right spot. Discharging containers which are placed on the deck of the ships also hold some time at the twist-lock platform. A vessel has several bays in which the containers are placed. When a QC finishes a bay, it need to move to another bay. The time for moving to another bay is taken into account in the simualtion. However, in the simulation the QC remains on the same place. The interchange between QC and vehicles is linked when AGVs or L-AGVs are being used. During loading, the QC has to wait until a vehicle is present at the TP with the right loading container. For discharging an empty vehicle must be present at the TP. In the case of an unlinked interchange (which is the case with the AShC and P-AGV) the QC is not allowed to enter the TP when a vehicle is present at that TP. During loading the vehicle drops
3.5. VEHICLES
Figure 3.3: Quay crane in the simulation
its container at the TP, when it has left the TP the QC is allowed to grab the container. For discharging the TP has to be empty (no vehicle, and no container) before the QC can drop its container on the TP. Vehicles are also not allowed to enter the TP when the QC is busy on it.
In the original QCs in the simulation library, the QC was not allowed to move over (manned) shuttle carriers. Therefore when a vehicle was present on a TP located in front (measured from the quay) of a TP which the QC want to enter, the QC had to wait until the vehicle was gone, and vice versa. Resulting in extra waiting times for both equipment types. With the use of manned vehicles this is done because of safety reasons, using automated equipment this restriction could be eliminated. Therefore the QC has been adapted in such a way that the first (or last) part of a lift from (or to) a TP is straight up, at least the height of the used vehicle (including some safety distance). The added code to one of the QC methods can be seen in Figure 3.4.
3.5
Vehicles
3.5.1 Job dispatching
The automated vehicles are managed by a central vehicles manager, as depicted in Figure 2.15. The vehicles manager receives orders from the TOS and is responsible for the dispatching of these orders to individual vehicles. An order for a vehicle is a transportation job of a container. This container has an origin and destination. The time at which te container is expected to be on its destination is also included in the order. All vehicles are capable of transporting two TEU, so an order can contain two containers with different origin or destination. When a vehicle has finished an order a new one will be selected. The process of determining the best order for each vehicle is shown in the flow diagram in Figure 3.5, this process is equal for each vehicle type.
3.5.2 Routing
When an order is assigned to a vehicle, the central vehicles manager will determine the route. The route selection is based on finding the shortest path. In the case of driving from the stack to the QC, the closest possible buffer is selected first. Then the required highway is selected. Finally the quay lane is determined. Choices made in this process depend on the type of vehicle and the apron layout. More details concerning this process already have been given in Chapter 2.
CHAPTER 3. IMPLEMENTATION
Figure 3.4: Code fragment of moving obstacle in backreach quay crane
3.5. VEHICLES
(a) (L-)AGV (b) AShC (c) P-AGV
Figure 3.6: 90 degree curve claims
3.5.3 Claiming
During driving a vehicle claims the space it requires. The length of the claim in front of the vehicle depends on the velocity. The minimum claiming distance should be long enough in order ro come to a complete stop. The claim width is 1 [m] wider than the vehicle (0.5 [m] on both sides). When a vehicle is driving a curve, it crosses (and so it blocks) other driving lanes. When it comes to a stop in a curve it will block the other lanes for a longer time. This results in delays and could lead to deadlocks. Therefore curves are no-stop zones, vehicles are not allowed to stop. When a vehicle leaves a stack TP, it will drive first a straight part and then will turn onto one of the highways. To prevent deadlocks, the straight part before the turn is also a no-stop zone. The several manoeuvres of the vehicles are explained in Appendix B. How these are implemented in the simulation model is discussed in the next sections.
90 degree curves
In the simulation model, all vehicles drive perfect curves, independently on the type of curve (symmetric or asymmetric, see Appendix B). The radius of these curves is equal to the established effective radius. All vehicles are symmetric, so they are able to drive the same curves in each direction. The curves presented in Appendix B are used for the construction of the curve claims. So the curve claims in the simulation model are closer to the reality than the curve trajectory. In Figure 3.6 the claims for 90 degree curves of all vehicles are given. These claims are an improvement in the simulation library regarding the original claims. These where much smaller and did not claim all the used space of an vehicle.
S-curves
If a vehicle drives between the stack and the buffer (or vice versa) and the transversal distance is smaller than twice the (effective) curve radius, then the vehicle will drive a s-curve. The construction of a s-curve is discussed in Appendix B. The claim of a s-curve is constructed from two symmetric 90 degree curve claims. Depending on the width of the s-curve, these are partly cut off. Figure 3.7b gives an example of an AGV which drives a s-curve from the buffer to the stack. In this figure the overlapping claims are clearly visible. In Figure 3.7a the original s-curve claim can be seen. The path and claim are both improved in the simulation library. The method in which the position and orientation of a vehicle driving a s-curve is determined, is depicted in Figure 3.8.
CHAPTER 3. IMPLEMENTATION
(a) Original (b) Improved
Figure 3.7: Original and improved s-curve claim for an AGV.
In Appendix B the idea of extended s-curves is illustrated. This has been implemented in the P-AGV model. All vehicles which drive between the stack and the buffer are routed using an extended s-curve, so that the highways are not used any more. In terms of path length, this is shorter than following a highway. However the vehicles are crossing each other more, which will result in more congestion. The claiming part did not work out, resulting in vehicles which are driving through each other. Therefore no experiments have been performed with this kind of s-curves.
Crabbing
Vehicles with four wheels (the AGV, L-AGV and P-AGV) are capable crabbing, during this move the vehicle will move, with a (small) forward speed, in transversal direction without changing its orientation. This is explained in Appendix B. The crab claim in the original simulation library was equal to the s-curve claim as can be seen in Figure 3.7a. The improved crab claims for the (L-)AGV and P-AGV are depicted in Figure 3.9a and 3.9b respectively. A code fragment of the
creation of the crabbing claim rectangles is given in F
3.6
Stack cranes
Each stack is equipped with two cranes. One crane works on the waterside and one on the landside of the stack. These cranes share the same rails and therefore cannot pass each other. Three types of moves can be disregarded. The first one is a stack in move, a vehicle (on the water or landside) delivers a container at the stack TP which need to be stored in the stack. The second one is a stack out move and is opposite of the stack in move. The last one is a housekeeping move, also called a shuffle. Shuffles are needed when a container which is located in the stack is requested and other containers are on top of it.
When a container must be placed into the stack, the best location in the stack is determined. This process is depicted in Figure 3.11.
3.7
Trucks
The implementation of the trucks is less advanced than the automated vehicles. Truck are generated and enter the system at the truck-gate. All created trucks have a maximum capacity
3.7. TRUCKS
CHAPTER 3. IMPLEMENTATION
(a) AGV (one lane) (b) P-AGV (two lanes)
Figure 3.9: Improved crab claims
Figure 3.10: Code fragment for construction crab claim
3.8. KEY PERFORMANCE INDICATORS
of 2 TEU, which implies that a truck can carry one or two 20 [ft] containers or one 40 [ft]. The order of the truck can be the delivery of a container, the pick-up or a combination of these two. Truck do not claim which allow them for driving to each other.
3.8
Key performance indicators
The purpose of the research is to compare the performance of automated vehicles. Pirhonen (2011) states that the most important key performance indicator for a performance comparison of vehicles is the quay crane productivity. For terminal operators this is also an important measurement, together with the number of vehicles which are required to achieve a certain productivity, because this influences the costs. Therefore the quay crane productivity (expressed in boxes per hour) will be used in this research as a measurement to answer the research question. In graphs with the quay crane productivities (presented in Chapter 5 the 95% confidence intervals will be drawn in order to determine whether or not the results of two simulation experiments differ significantly. For the construction of the confidence intervals the t-test is used as described by Dekking et al. (2005).
To be able to evaluate the results, insight in the system is required. Insight in the behaviour of the system is obtained by the determination of detailed equipment information. This insight information can provide details about the behaviour of the vehicles, which is helpful in making recommendations for future research. Insight in the system behaviour is also useful for the validation of the model, does the model act as it is expected? Are the results in agreement and explainable? The logged measurements for vehicles, quay cranes and stack cranes are illustrated in graphs. The indices presented in these graphs will be explained in the next subsections. Vehicle status
This index represents the average status of the vehicles and is expressed in a percentage of the total time. The status is divided in the following components:
• Idle time - The time that a vehicle is not performing any order.
• Time waiting for route - The time a vehicle is waiting for a route to its destination. • Time waiting for sequence - The time a vehicle is waiting in the buffer until it is allowed to
continue.
• Time at quay crane to deliver load - The time a vehicle is standing still at the QC TP to deliver a container.
• Time at quay crane to collect load - The time a vehicle is standing still at the QC TP to collect a container.
• Time at stack to deliver load - The time a vehicle is standing still at the stack TP to deliver a container.
• Time at stack to collect load - The time a vehicle is standing still at the stack TP to collect a container.
• Driving time loaded - The time a vehicle is driving with a load. • Driving time empty - The time a vehicle is driving without any load.
CHAPTER 3. IMPLEMENTATION
Vehicle drive status
This index represents the average drive status of the vehicles and is expressed in a percentage of the total time. The drive status is divided in the following components:
• Idle time - The time that a vehicle is standing still.
• Time waiting for claim - The time a vehicle is standing still because its route is blocked by another equipment piece.
• Time driving at constant maximum speed - The time a vehicle drives at its maximum speed.
• Time driving at constant maximum curve speed - The time a vehicle drives at its maximum curve speed.
• Time driving at a constant speed - The time a vehicle is driving at a constant velocity. • Time braking - The time a vehicle decelerates.
• Time accelerating - The time a vehicle is accelerating. Vehicle driving time per box
In this index the average drive status of the vehicles is expressed as a percentage of the total average time per box. The time per box is the total driving time of all vehicles divided by the number of handled boxes. The components are the same as in the previous index (Vehicle drive status) except for the idle time.
Vehicle cycle time per box
This index is comparable with the vehicle status index. The difference is that it is expressed as a part of the total average time per box. Therefore the components are the same except for the idle time.
Vehicle distance per box
In this index the average distance driven per box is depicted. It is calculated by counting the driving distances of all vehicles and divided by the total number of handled boxes. The components driving distance loaded and empty are distinguished.
Quay crane status
In this index the average status of the quay cranes is expressed in a percentage of the total time. The status is divide in the following components:
• Time for bay change - The time a quay crane is not performing any move because it drives to another bay.
• Time waiting for loading containers - The time a QC is not performing any move because there is no container available
• Time waiting to unload containers - The time a QC is not performing any move because there is either no free TP or no empty vehicle available (depending on the type of vehicles).
3.8. KEY PERFORMANCE INDICATORS
• Time waiting for transfer point access during loading - The time a QC has to wait because it is blocked by a vehicle during loading.
• Time waiting for transfer point acces during unloading - The time a QC has to wait because it is blocked by a vehicle during discharging.
• Time needed for the handling of twist-locks - The required time for installing or removing twist-locks.
• Time the quay crane is productive - The time a QC is performing loading of discharge moves.
Quay crane productivity per move type
During a move a quay crane can either lift a single container or two, in both cases this can be a load or discharge move. This results in 4 move types of which the productivities are expressed in this index.
Waterside stack crane status
In this index the average status of the waterside stack cranes is expressed as a percentage of the total time. The status is divide in the following components:
• Idle time - The time a stack crane is waiting for a next order
• Idle time due to the transfer points being full - The time a stack crane has to wait because the stack TPs are all occupied.
• Time waiting for other stack crane or its being send away by the other stack crane - The time a stack crane is blocked by another stack crane, or it is send away because the other stack crane needs to be in that area.
• Time waiting to access the transfer points zone - The time a stack crane has to wait before accessing the TP because it is blocked by a vehicle.
• Time performing housekeeping move - The time a stack crane is performing housekeeping moves.
• Time performing shuffle moves for trucks - The time a stack crane is performing shuffles for a truck container.
• Time performing shuffle moves for vessels - The time a stack crane is performing shuffles for a container with for a vessel.
• Time performing a stack in move - The time a stack crane is performing a move for a container which enters the stack.
• Time performing a stack out move - The time a stack crane is performing a move for a container which leaves the stack.
