MASTER OF SCIENCE THESIS STOCKHOLM, SWEDEN 2016

Operation of the Expanded Blue Metro Line in Stockholm

SOUMELA PEFTITSI

KTH ROYAL INSTITUTE OF TECHNOLOGY SCHOOL OF ARCHITECTURE AND THE BUILT ENVIRONMENT

TSC-MT 16-009

Operation of the Expanded Blue Metro Line in Stockholm

Soumela Peftitsi

Master thesis June 2016

Department of Transport Science KTH Railway Group KTH Royal Institute of Technology

Abstract

Since the population growth of Stockholm Region is rapid, leading to larger demand on Public Transport and especially metro, four Municipalities of the Region have agreed on the expansion of the metro network. Blue metro line will be extended to Nacka and Hags¨atrain the south and Barkarby in the north of the Swedish capital. The new railway line connections have been already planned, while the operation of the expanded line is analyzed in the current thesis.

Taking the expected increase of passenger volumes and the operation of the current Blue line into account and following the safety restrictions, two alternative regu- lar timetables of the expanded Blue line, limited to the morning rush service on a working weekday, have been constructed. The operation at stations of low expected passenger volume on the train is evaluated concerning the satisfaction of the oper- ator. The first alternative metro operation with traffic every 4 minutes during the rush hour is concluded to be less efficient than the second alternative with 5 minutes headway, as 21 % larger amount of rolling stock is needed and more seats are not occupied.

Finally, in order to achieve higher operational efficiency at the low-demanded sta- tions, a third Blue line operation, that is based on the second alternative and it includes short services, operating on a part of the line and not on the full-length of it, has been proposed. Although the number of trains needed for the morning peak hour operation remains constant between the second and third alternative op- erations, the proportion of empty seats at the analyzed stations is expected to be lower during the last alternative operation, resulting in a metro line scheduling that satisfies the operator most.

Key words: Train scheduling, Metro operation, Operational efficiency, Urban rail, Train timetable, Stockholm metro, Blue metro line

i ii Sammanfattning

Den snabba befolkningstillv¨axteni Stockholmsregionen leder till ¨okad efterfr˚agan i kollektivtrafiken och s¨arskilttunnelbana. D¨arf¨orhar fyra kommuner i regionen enats om utbyggnaden av stadsn¨atet. Bl˚aatunnelbanelinjen kommer att utvidgas till Nacka och Hags¨atrai s¨oderoch Barkarby i norra delen av den svenska huvud- staden. Den nya tunnelbaneslinjen anslutningar har redan planerats. I den aktuella avhandlingen analyseras driften av den ut¨okade linjen .

Med h¨ansyntill den f¨orv¨antade ¨okningenav efterfr˚aganhar tv˚aalternativa tidta- beller tagits fram f¨orden ut¨okade Bl˚aalinjen. Tidtabellerna baseras p˚adagens tidtabell med h¨ansyntill s¨akerhetsaspekter och begr¨ansastill morgonrusningen p˚a en vanlig vardag. F¨orstationer med l˚agf¨orv¨antad resandevolym har operat¨orens nytta utv¨arderats.F¨orstaalternativet som avser 4-minuters trafik under rusningen har visats vara mindre effektiv ¨andet andra d¨art˚ageng˚armed 5 minuters headway eftersom 21 % mer fordonskapacitet beh¨ovs medans fler stolar f¨orbliroanv¨anda.

Slutligen har ett tredje alternativ f¨orslagitsf¨oratt uppn˚ah¨ogreoperativ effektivitet p˚astationer med l˚agefterfr˚aga.Alternativet bygger p˚aalternativ tv˚amen omfattar korta avg˚angarsom endast g˚arp˚aen del av linjen. Aven¨ om antalet t˚agsom beh¨ovs f¨ormorgonrusningen inte kan reduceras med denna ˚atg¨ardf¨orv¨antas antalet tomma platser p˚ade analyserade stationerna minskas, vilket g¨ortredje alternativet mest effektiv f¨oroperat¨oren.

Nyckelord: T˚agschemal¨aggning,Metro drift, Operativ effektivitet, T¨atortstrafik , T˚agtidtabell, Stockholms tunnelbana, Bl˚atunnelbanelinjen

iii iv Acknowledgements

First of all, I would like to thank my supervisors, Anders Lindahl and Jennifer Warg, as well as my examiner Albania Nissan, for their constant guidance, valuable comments and suggestions about this Master thesis.

I wish to acknowledge Hans Sipil¨a,from SWECO, for his availability and useful feed- back concerning data and information about the operation of the metro in Stock- holm and for giving me the opportunity to experience the metro operation from the driver’s point of view. Josef Andersson contributed to this project by analyzing the expected passenger volumes on the SL network using VISUM software, which I really appreciate.

Many thanks to my classmates for the nice moments that we spent at KTH during the last 4 months, sharing the same office and elaborating on our Master projects.

Last but not least, I would like to thank my parents, Dimitris and Zoe, and my brother, Dimos, for supporting and encouraging me throughout my studies despite the distance.

v vi Abbreviations

• PT: Public Transport

• SL: Responsible company for the Public Transport system in Stockholm

• MTR: Stockholm metro operator

• Hju: Hjulsta

• Ten: Tensta

• Rib: Rinkeby

• Ris: Rissne

• Duv: Duvdo

• Sbg: Sundbybergs centrum

• Ssd: Solna station

• Huv: Huvudsta

• Bsn: Barkarby station

• Bas: Barkarbystaden

• Aka: Akalla

• Hub: Husby

• Kis: Kista

• Hab: Hallonbergen

• N¨ar:N¨ackrosen

• Soc: Solna centrum

• V¨as:V¨astraskogen

• Sha: Stadshagen

• Fhp: Fridhemsplan

• R˚ah:R˚adhuset

vii • Tce: T-Centralen

• Ktg: Kungstr¨adg˚arden

• Sfa: Sofia

• Gup: Gullmarsplan

• Slh: Slakthusomr˚adet

• Sop: Sockenplan

• Svm: Svedmyra

• Stb: Stureby

• Bah: Bandhagen

• H¨od:H¨ogdalen

• R˚ag:R˚agsved

• Hag: Hags¨atra

• Hbk: Hammarby kanal

• Sik: Sickla

• J¨al:J¨arla

• Nac: Nacka

viii Contents

Abstract ...... i

Sammanfattning ...... iii

Acknowledgements ...... v

Abbreviations ...... vii

1 Introduction 1

1.1 Background ...... 1

1.2 Objectives ...... 3

1.3 Limitations ...... 4

1.4 Approach ...... 5

2 Literature Review 7

3 Methodology 11

3.1 Railway planning ...... 11

3.2 Timetable planning ...... 12

3.3 Timetable efficiency indicators ...... 13

4 Existing Metro Network in Stockholm 15

4.1 Description of the existing Blue line ...... 15

4.1.1 Blue metro line parts ...... 16

4.1.2 Major metro nodes ...... 18

4.1.3 Rolling stock ...... 19

ix Contents

4.2 Operation of the existing Blue line ...... 20

4.2.1 Travel demand analysis ...... 20

4.2.2 Timetable description ...... 25

4.2.3 Operation at major stations ...... 25

5 Expanded Blue Metro Line 31

5.1 Description of the expanded line ...... 31

5.2 Planning of the expanded line ...... 32

5.2.1 Expected travel demand analysis ...... 32

5.2.2 Line planning ...... 35

5.2.3 Time constraints assumptions ...... 35

5.2.4 Rolling stock circulation ...... 37

6 Analysis of Alternative Timetable Proposals 39

6.1 Alternatives A & B ...... 39

6.1.1 Alternative A ...... 39

6.1.2 Alternative B ...... 43

6.1.3 Alternatives A & B: Comparison ...... 46

6.2 Alternative C ...... 48

6.2.1 Alternatives B & C: Comparison ...... 50

7 Conclusion 53

7.1 Summary ...... 53

7.2 Further analysis ...... 54

References ...... 57

A 59

B 69

x Chapter 1

Introduction

1.1 Background

Swedish capital, Stockholm, is one of the fastest growing cities in Europe, with the population of its region expected to increase by more than 17% by 2023, leading to larger demand on public transport (PT ). Specifically, the population of Stockholm County was about 2.2 million inhabitants in 2013, while it is expected to rise to 2.5 million in 2023. The population density in the County is currently about 332 people per km2 and it is expected to rise to almost 400 people per km2 in about 10 years [1].

Figure 1.1: The south Blue line extension [2].

According to the County Council of Stockholm, City of Stockholm, Municipality of Nacka, J¨arf¨allaMunicipality and City of Solna agreed to extend the metro network, which is the most used PT mode in Stockholm, and construct more residential areas in order to serve the expected population increase. The extension of the Blue metro line in Stockholm is part of the agreement. The Blue line will split into two parts in the South part of the network. One branch of the line will connect Kungstr¨adg˚arden

1 Chapter 1. Introduction to Nacka centrum, passing through S¨odermalm(Figure 1.1). 5 new stations (Sofia, Hammarby kanal, Sickla, J¨arlaand Nacka centrum) are going to be constructed on the new Nacka line, which is estimated to be about 7.7 km long[2].

The other branch in the south part of the network will connect Kungstr¨adg˚arden to Gullmarsplan, through Sofia station, and it will finally reach Hags¨atra,replacing one branch of the green line (Figure 1.2). The length of the line between Sofia to Gullmarsplan is estimated to be 3.3 km, while a new station construction is investigated in Slakthusomr˚adet[2].

Figure 1.2: The south Blue line extension [2].

The extended Blue line in the north part of the region will connect Akalla to Barkarby station, through a 3.4 km-long-line. Barkarbystaden and Barkarby sta- tion areas will be investigated on the new part of the line (Figure 1.3). The metro construction in the south part is expected to be completed by 2025, while the inau- guration of the expanded line in the North part is planned to be in 2021 [2].

2 Chapter 1. Introduction

Figure 1.3: The north Blue line extension [2].

The municipalities that signed the agreement about the metro extension, and specif- ically the Municipalities of Nacka and J¨arf¨allaand the City of Solna, are expected to have a large population growth of 23.5%, 21% and 30% by 2023, respectively [1]. For that reason, regarding the residential areas, developing projects are also planned. More than 13 thousands of new houses are planned to be built on Western Sickla¨on in the Municipality of Nacka, while 14 thousands of new residences are agreed to be built in Barkarbystaden, which is a growing part of Barkarby region [2].

Due to increasing population and the construction of new housing areas, travel demand at stations on the current Blue line as well as on the stations on the extended line is expected to increase, too. Since today’s Blue line is the shortest and less crowded line of the metro network in Stockholm, trains operate every 6 minutes during the peak hour. Consequently, the timetable of the future line needs to be planned considering a more frequent operation.

1.2 Objectives

This project studies the operation of the future Blue metro line in Stockholm, based on the growing forecasted passenger volumes at the stations on the expanded line. Travel demand variation is an important constraint and it should be taken into account in constructing and evaluating a rail timetable. Considering the hour-to- hour and day-to-day travel demand variation, the amount of train departures needed to be chosen.

Since timetable construction is an important part of the railway planning and it follows the line planning, considering the available rolling stock fleet and safety restrictions, alternative timetables are proposed. Finally, regarding the relationship between the available capacity and the travel demand, the timetables are assessed.

Rail timetable efficiency, that satisfies the operator, depends on the number of empty

3 Chapter 1. Introduction seats and the number of trains needed to operate during a day. Aiming the satis- faction of the operating company, which increases with decreasing amount of empty seats and rolling stock needed, short services, operating only on the most demanded part of the metro line and not on the total length of it, need to be considered. On the other hand, passengers’ satisfaction increases by shortening the number of standing or rejected passengers.

A frequent timetable, based on the travel needs of each area, leads to the attractive- ness of the metro and consequently, more activities (businesses, residential areas, etc) are available in areas where the new parts of the metro line will pass through.

The aim of the current thesis is to present a suitable rail timetable planning method- ology, describe and analyze the operation of the existing Blue metro line in Stock- holm, analyze the future expanded Blue line, create and evaluate alternative schedul- ing proposals and finally choose the one that leads to the more efficient operation of the metro from the operator’s point of view. The most efficient operation is the one that occupies the largest number of seats and needs the smallest amount of rolling stock fleet. For this thesis, the developing areas of Stockholm County and the increasing travel demand there, are taken into account.

1.3 Limitations

The timetable and rolling stock planning are studied in the current project. However, crew scheduling, which is the final step of the railway planning, is not taken into account.

In order to assess how well the train capacity meets the travel demand, passenger volume is an important factor. The number of seats that remain empty, as well as the number of people that are left behind if the train, coming, is overcrowded can be also estimated. Data about the variation of the on-board passenger volume after each station on the existing Blue line during the morning and afternoon peak hours are available by MTR. In the current project, volumes during the off peak hours, that are not available, are interpolated in order to describe the current Blue line operation in detail.

On the other hand, the expected average number of boarding, alighting and on- board passengers at each station on the future expanded metro network in 2030 are available by SL for the morning peak hour. In this case, demand data about the afternoon peak hour and the off-peak, that are missing, will not be interpolated in order to avoid non realistic results and consequently, the thesis will focus on planning a metro timetable during the morning rush hour on an average winter weekday. Moreover, since the hour-to-hour future demand variation is not provided, the analysis of the operational efficiency of the expanded metro line will not be perfectly realistic.

Additionally, the amount of rolling stock used and the proportion of seats that remain empty are the efficiency criteria which the study and the timetable selection

4 Chapter 1. Introduction are based on. Detailed financial criteria and a cost-benefit analysis (CBA), that will not be examined in the project, would give a more reliable evaluation.

Finally, attractive timetable patterns should be decided so as to achieve connectivity between the metro and other public transport modes, such as bus lines and commuter railways of high demand. However, the metro line timetables that will be proposed in this project, will be independently constructed and they will not be based on the operation of other public transport systems.

1.4 Approach

The current thesis consists of two main parts, the future Blue metro line timetable planning, where the frequency is decided and graphical timetables are created, and the evaluation of its operational efficiency, that depends on the proportion of seats that are occupied.

First of all, necessary data and information are collected:

• Characteristics of the existing line (current travel demand variation, frequency)

• Expected travel demand

• Metro network track layout

• Distance and trip times between consecutive stations

Then, the operation of the existing Blue line is roughly described and the relationship between the travel demand and the available capacity at major stations is presented using Matlab software.

After that, the project focuses on manually planning three alternative scheduling proposals of the future line through Microsoft Excel, based on the operation of the current line and on the future passenger volumes. Matlab software is used in order to construct graphical timetables for each branch of the line.

The proposed timetables are evaluated (through Matlab) and finally, the one that meets the satisfaction of the operator is chosen to be the most operationally efficient.

5 Chapter 1. Introduction

6 Chapter 2

Literature Review

Timetable planning, which is considered to be one of the most important and com- plicated parts of public transport and specifically, railway operation, is determined by the times that a train is scheduled to arrive at each station and depart from the same station. Constructing a rail timetable, travel demand variation, available rolling stock fleet and safety restrictions are taken into account.

Manual rail scheduling requires a graphical train timetable, which is a time-distance diagram, giving information about the identity number, the direction and the speed of the train, while conflicts between trains are also shown. Timetable is rescheduled to avoid conflicts between trains operating on single tracks, in case the trains meet point is located between the stations. Stockholm metro, which operates on double tracks, allows conflicts not only at the stations, but also between them.

The operation of urban public transportation modes and specifically, metro, is mainly based on periodic timetables of regular intervals between the train depar- tures. Many recent studies about the periodic rail timetabling use approaches of the periodic event scheduling problem (PESP), which was first proposed by Serani and Ukovich in 1989.

Liebchen and M¨ohring(2002) used the periodic event scheduling problem (PESP), a mathematical optimization approach of scheduling periodic events that are repeated every period time T and applied it on the Berlin underground, taking periodic con- straints proposed by the operating company into account. Period T varies between different demand-oriented services of the Berlin metro (”weak”, ”normal”, ”rush” and ”night” services). Liebchen and M¨ohring concluded that optimized timetables are more efficient compared to manually planned ones, in terms of rolling stock needed and the average passengers waiting time [3].

In 2012, Kroon et al focused on constructing a differentiated PESP model, using dy- namic rolling stock and passengers connections as opposed to the initial formulation of it, that leads to optimal and flexible solutions. The model was applied on three intercity lines, connected to each other, on the Netherlands rail network. For both flexible passengers connection and rolling stock, the PESP model was proven to be feasible more times, while rolling stock fleet, running and dwell times are minimized

7 Chapter 2. Literature Review

[4].

Tzieropoulos and Emery (2009), mentioning that a timetable could not have per- fect regular intervals, recently described the methodology of designing a cyclic rail timetable on a line and on the whole network and assessing the regularity of it by defining a regularity indicator [5].

A common scheduling approach is a timetable based on peak and off peak hours. Urban railway seems to be congested during peak hours, when passenger demand is possible to exceed the capacity of the train, while an amount of boarded passengers are left behind, waiting for the following train. Niu and Zhou (2013) built a mathe- matically optimization model, based on an origin-destination matrix among the day, collected by Automated Fare Collection (AFC) system and the passengers waiting times, to construct dynamical timetables that are sensitive to congested conditions. The proposed model was implemented on a subway line in Guangzhou in China and it was concluded that the passengers waiting times and the amount of rolling stock decrease, compared to the regular timetable [6].

Additionally, Sun et al (2014) also considered dynamic passenger demand as an important factor in designing efficient timetables that lead to shorter waiting times. Three optimized models, with and without capacity constraints, were developed in order to construct dynamical demand-based rail timetables. The models, for- mulated, were applied on a metro line in Singapore. Demand variation data were collected using AFC system that gives information about the origin and destination of passengers trips. Sun et al concluded that the dynamic timetable that allows ca- pacity constraints has better performance, but it is more difficult for passengers to understand, as the timetable does not consist of regular intervals between the trains [7]. Another optimization model for scheduling passenger trains was presented in the study of Ghoseiri et al in 2004, where lower fuel consumption and shorter travel times are considered as indicators of satisfaction of the operator and passengers, respectively [8].

Finally, evaluating the stability and efficiency of a rail timetable seems to be an important part of railway planning. A delayed train might affect the whole rail network and cause secondary delays on more trains of a dense network. For that reason, Goverde (2007) formulated a max-plus algebra model that examines if a timetable is able to compensate primary and secondary delays and how easily it can return to stable conditions after disruptions. The model is finally, applied to the Dutch railway timetable, estimating also the propagation of the primary delay to the network [9].

Delorme et al in 2007 introduced a new optimization approach to evaluate the stability of a rail timetable, which is based on secondary delays caused by primary delays. The shortest path, which is the marginal time between two trains before the conflict happens, is also estimated. The Pierrefitte-Gonesse railway intersection in France is finally chosen to apply the optimization model [10].

A study of Lai et al in 2015, presented an evaluation model for a metro system based on capacity characteristics(normal, downgraded and used capacity) and on historical

8 Chapter 2. Literature Review data about disturbances. Two performance indicators, operational stability and efficiency, are developed in order to estimate the mean and variance of the recovery time and the percentage of the capacity used, respectively [11].

In this thesis, considering different periods T for various traffic demand-oriented services among the day as Liebchen and M¨ohring(2002) proposed in their study, alternative periodic timetables of the expanded Blue metro line are manually con- structed. The proposed metro operation is evaluated regarding the satisfaction of the operator, as Gosheiri et al did. Specifically, operational efficiency of the proposed timetables is evaluated through occupied capacity, inspired by Lai et al. However, passengers’ waiting times as well as delays are not taken into account in the timetables’ assessment.

9 Chapter 2. Literature Review

10 Chapter 3

Methodology

3.1 Railway planning

According to Peeters (2003), railway planning, which is mentioned to be one of the most complicated parts of the railway operation, consists of some steps that directly affects the construction of a timetable (Figure 3.1).

Figure 3.1: Railway planning process [12].

Travel demand, which is the number of passengers traveling from a place to another, is initially estimated and finally an OD matrix, containing the number of trips from each origin station to a destination station, is created. During the second step, line planning, the way that the lines are connected to each other and the stations that are included in the route are decided. The rail timetable for the Blue metro line network, that is already specified by Stockholm County Council (SLL), is then planned. The amount of the rolling stock fleet and the size of the train (full and short-length trains) are decided so that the train capacity meets the estimated passengers demand. Additional short services that operate only on a part of the line are also decided in the current step. Finally, the crew should be planned, deciding when and where drivers and conductors start and finish their working shifts [12]. However, crew scheduling is not included in the scope of the current thesis.

11 Chapter 3. Methodology

3.2 Timetable planning

A time-distance diagram is the main requirement for the construction of a rail timetable. For this thesis, graphical timetables are constructed for both branches of the Blue line. Time is represented on the horizontal axis, while the stations on each branch of the line are shown on the vertical axis of the diagram. Each train, operating between two stations of the metro line, is represented with a line on the diagram, steeper slope of which, indicates higher speed. The dwell time, that a train stops at each station, is presented with an horizontal flat line. A metro timetable is homogeneous, as the the tracks are only used by metro trains that operate at the same average speed and have the same dwell time at the stations.

Trains, operating on both directions, are shown on the same diagram and hence, conflicts between the paths are visible. A rail timetable is rescheduled so that conflicts between train paths are avoided. Stockholm metro, which is a double-track network, allows conflicts both at stations and between them. However, conflicts between trains using the same track should also be taken into account by choosing the minimum headway time, which is the safety time between two consecutive trains.

An example of a time-distance diagram for a rail timetable is shown on Figure 3.2.

Figure 3.2: Example of a time-distance diagram [13].

The minimum running time between the stations is considered to be the main time parameter needed for a timetable construction. The running times depend on the morphology of the network, acceleration, deceleration and average speed of the rolling stock and it might vary among the two directions. Apart from the travel times, other time constraints are also considered in rail timetable planning.

Turnaround time which is the time between the arrival of the train at the terminal station and its departure to the opposite direction, affects the amount of rolling stock fleet that is needed for the rail operation. Moreover, dwell times at stops, which are selected according to the travel demand at each station, are added to the

12 Chapter 3. Methodology total travel time on the metro line.

3.3 Timetable efficiency indicators

A rail timetable is assessed, considering both operator’s and passengers’ satisfaction. In this thesis, the operational efficiency indicator (3.1) is used [11]. It estimates the percentage of the occupied train unit seats. The more seats are occupied, the higher the level of operating company’s satisfaction.

Occupied capacity (seats) Operational efficiency (%) = × 100 (3.1) Total train unit capacity (seats)

Similarly, the number of seats that remain empty is given by the positive difference between the seated capacity and the travel demand. The empty seats indicator is given by the equation 3.2.

# of seats – Total passengers Empty seats (%) = × 100 (3.2) # of seats

On the other hand, the larger the number of standing and rejected passengers, the less satisfied the passengers are. The standing passengers are estimated by the difference between the total number of boarded passengers in a train unit and the number of seated passengers (3.3). The rejected passengers, that do not manage to board on a train, are estimated by the difference between the total number of passengers who want to enter the train and the total capacity of the train unit, including both seated and standing passengers (3.4).

Total passengers – # of seats Standing passengers (%) = × 100 (3.3) Total passengers

Passengers demand – Train capacity Rejected passengers (%) = × 100 (3.4) Passengers demand

13 Chapter 3. Methodology

14 Chapter 4

Existing Metro Network in Stockholm

4.1 Description of the existing Blue line

AB Storstockholms Lokaltrafik (SL), which is owned by the Stockholm County Council, is responsible for the public transport services in Stockholm (Metro, Bus, Commuter and Local trains) and it is the owner of the PT network infrastructure and maintenance depot. Stockholm metro, which is called tunnelbana (T-bana) and its total length is 105.7 km, is operated by a private company, named MTR[14].

The metro network in Stockholm consists of 3 lines (Green, Red and Blue), which are divided into 7 branches (Table 4.1), and 100 stations[14].

Table 4.1: Stockholm Metro Lines[15].

Stockholm Metro Line Branch Expanse Stations T10 Hjulsta-Kungstr¨adg˚arden 14 Blue Line T11 Akalla-Kungstr¨adg˚arden 12 T13 Ropsten-Norsborg 25 Red Line T14 M¨orby centrum-Fru¨angen 19 T17 Akeshov-Skarpn¨ack˚ 24 Green Line T18 Alvik-Farsta strand 23 T19 H¨assalby strand-Hags¨atra 35

The map of the existing Stockholm metro network is represented in Figure 4.1. The Blue, which is the newest line of the network, was inaugurated in 1975 and it consists of 20 stations, 19 of which are underground. The line connects the city center to the Northern part of the municipality of Stockholm, passing through the central station and the municipalities of Solna and Sundbybergs. The length of the line is 24.5 km of double tracks[14] and it extends from Kungstr¨adg˚ardento V¨astraskogen, where it splits into two branches that lead to Hjulsta (T10) and Akalla (T11).

15 Chapter 4. Existing Metro Network in Stockholm

Figure 4.1: The map of Stockholm metro [16].

4.1.1 Blue metro line parts

Considering the point of the existing metro network, where the two branches of the Blue line are merged (V¨astraskogen station), the line can be divided in three parts, two of which are operated by only one branch and one is served by both T10 and T11.

Central Part The central part of the line, which is common for T10 and T11 branches of the Blue line, is 6.2km and connects Kungstr¨adg˚ardento V¨astraskogen through an underground tunnel (Figure 4.2). Two of the stations, included in the central part, T-Centralen and Fridhemsplan, are connected to other metro lines. According to the data, provided by the operating company MTR, these stations seem to have the largest passenger demand[17]. T-Centralen is the central station that offers transfer between the three metro lines (Green, Red, Blue), while Green and Blue lines are also connected at Fridhemsplan station.

16 Chapter 4. Existing Metro Network in Stockholm

Figure 4.2: The central part of Stockholm metro.

Hjulsta Part The first branch of the Blue line connects V¨astraskogen to Hjulsta (Figure 4.3), which is located in the North part of Stockholm municipality. The Hjulsta segment consists of 8.9 km of underground tracks and it passes through the municipalities of Solna, Sundbybergs and Stockholm. The maintenance depot, serving the metro cars operating on the Blue line is located at Rissne station. Blue metro line (T10) is connected to the commuter railway at Sundbybergs centrum, a station of large passenger load.

Figure 4.3: The Hjulsta part of Stockholm metro.

Akalla Part The second branch of the Blue line connects V¨astraskogen to Akalla station (Figure 4.4), in the North part of Stockholm municipality. The length of the segment is approximately 9.4 km, including stations, located under and above ground, in the municipalities of Solna, Sundbybergs and Stockholm. Transfer between the Blue metro line and the tram line is possible at the Solna centrum station.

17 Chapter 4. Existing Metro Network in Stockholm

Figure 4.4: The Akalla part of Stockholm metro.

4.1.2 Major metro nodes

T-Centralen The central station, located in the center of Stockholm, is a node that offers con- nectivity between the three lines of the metro, as well as between different transport modes (subway, commuter and intercity railways and buses). There are more than 174 thousands of boarding passengers on a winter weekday on the three lines crossing the station[18]. The travel demand is large at the central metro station due to the number of shopping centers and working places nearby the station. T-Centralen is a station that consists of three levels of platforms, while the trains leading to both di- rections of the Blue line are operating on the deepest level. Around 45 thousands of passengers boarding at the central station use the Blue line, while 14 thousands pas- sengers depart from T-centralen in the afternoon rush hour (15:00-18:00), traveling on the Blue line [17].

Fridhemsplan Another important metro station is Fridhemsplan station, which is located on Kung- sholmen island, part of the Stockholm center. It is a connection node between the Blue and Green line, serving more than 57 thousands of boarding passengers on an average weekday [18]. The average number of boarding passengers traveling on the Blue line on a winter weekday is approximately 24 thousands [17].

V¨astraskogen The two branches (T10, T11) of the Blue metro line meet each other at the V¨astra skogen station, located in the district of Huvudsta. For that reason, there are two platforms and three tracks, two towards Kungstr¨adg˚ardenand one for trains to Akalla and Hjulsta. More than 8 thousands of boarding passengers are observed on a weekday at the node [18].

Sundbybergs centrum Sundbybergs centrum is a metro station of large daily passenger flow, as more than 11 thousands of passengers travel by metro on a winter weekday. The is located in

18 Chapter 4. Existing Metro Network in Stockholm the center of the municipality of Sundbyberg, the population of which is more than 12 thousands of people [19]. The connection between the metro and the commuter railway makes Sundbybergs centrum a station of great importance.

Kista Kista is the only one station on the Blue line that is not located underground. The district of Kista is part of Stockholm municipality and it is primarily occupied by industries. As Kista is an industrial area, offering place for a large number of employees, the passengers flow is also high at the metro station. Specifically, the number of boarding passengers at Kista station on an average weekday is almost 20 thousands.

4.1.3 Rolling stock

The main type of a metro car that is used in the Stockholm metro network and specifically, on the Blue line is the C20 metro unit. It is the newest unit that has replaced the older stocks. The main metro unit (C20) is a double-articulated car that allows the free movement of the passengers throughout the car. A C20 unit is 46.5 m long and 2.9 m wide and it has a driver’s cabin at each end (Figure 4.5). The material that the car body is made of, is stainless steel and the maximum speed that it can reach is 90km/hr. Regarding the capacity of the C20 metro unit, there are seats for 126 passengers and space for 288 standing passengers [20].

Figure 4.5: Technical drawing of C20 metro unit[20].

Different metro car sizes, full and short-length, are combined together to meet pas- sengers demand, that varies among hours and days, so as to achieve a metro op- eration of cost and demand efficiency. Full-length C20 metro cars of about 140m length, consisting of 3 metro units, operate during weekdays and rush hours and offer place for 378 seated passengers and 864 standing passengers. According to the annual report of the Stockholm County Council, full-length evening services operate until 9:30 pm instead of 7:00pm as it was before 2014 [22]. Short-length C20 metro cars, which are often operating during night hours and on weekend days, consist of two metro units. The capacity of a short train is 252 seated and 576 standing passengers.

19 Chapter 4. Existing Metro Network in Stockholm

Figure 4.6: Technical drawing of C6 metro unit [21].

The main train type often operates in combination with an older train type during the peak hours, when the passenger demand is larger and more frequent timetable is needed. A C6 metro unit (Figure 4.6) is an older train type of 14.6 m length, offering capacity of 48 seated and 108 standing passengers [23]. A full-length C6 metro car consists of 8 units, reaching capacity of 384 seated and 864 standing passengers. Both train types are able to operate on the tracks of Stockholm subway which are of standard gauge (1435 mm), while the metro follows the left-side traffic.

4.2 Operation of the existing Blue line

4.2.1 Travel demand analysis

The existing Blue line is the shortest and less crowded line of the Stockholm metro network, while the average number of trips on a winter weekday is around 200 thousands [18]. The boarding and alighting passenger load, that varies among the stations on the T10 and T11 branches of the line, is represented on Figures 4.7 and 4.8, respectively. The largest number of boarding passengers is observed at T-Centralen, Fridhemsplan, Sundbybergs centrum and Kista stations, which makes these stations of major importance in the timetable planning.

20 Chapter 4. Existing Metro Network in Stockholm

Figure 4.7: Average travel demand variation along the T10 metro line on a winter weekday in 2014 (Data source: [18]).

Figure 4.8: Average travel demand variation along the T11 metro line on a winter weekday in 2014 (Data source: [18]).

21 Chapter 4. Existing Metro Network in Stockholm

Peak hours The Blue line is operated between 5:00 am and 1:00 am on weekdays, while the timetable is more extensive during weekend, when there are also night services. However, the number of the metro trips, and specifically the Blue metro line trips, varies among the day, leading to the creation of peak and off-peak periods. It is observed that there are more trips during the morning and afternoon period, when people travel to and from their working places. According to SL, the morning and afternoon rush periods are considered to be between 06:30 am and 9:30 am, and 15:00 and 18:00, respectively and hence, a more frequent service is needed. However, the passenger flow is observed to reach its peak from 07:30 am to 8:30 am and 16:30 to 17:30 [18].

Demand variation at major interchanges The passenger volume in the train after each stop, which vary among an average winter day, is provided by MTR for each station and direction. However, data are only available for morning and afternoon peak hours and for that reason, Matlab software is used in order to interpolate the missing numeric data during the non- peak hour (09:30-14:30). Cubic interpolation, that uses a third degree polynomial and its derivative, is used to obtain a smooth curve for the unknown data through Matlab.

Passenger demand variation at 5 major stations is indicated on Figures 4.9, 4.10, 4.11, 4.12 and 4.13.

Figure 4.9: Average passenger volume after stop at T-Centralen (Northbound) among a weekday (Data source:[17]).

22 Chapter 4. Existing Metro Network in Stockholm

Figure 4.10: Average passenger volume after stop at Fridhemsplan (Northbound) among a weekday (Data source:[17]).

Figure 4.11: Average passenger volume after stop at V¨astraskogen (Southbound) among a weekday (Data source:[17]).

23 Chapter 4. Existing Metro Network in Stockholm

Figure 4.12: Average passenger volume after stop at Kista (Southbound) among a weekday (Data source:[17]).

Figure 4.13: Average passenger volume after stop at Sundbybergs centrum (South- bound) among a weekday (Data source:[17]).

The number of on-board passengers after the train stops at T-Centralen and Frid-

24 Chapter 4. Existing Metro Network in Stockholm hemsplan stations towards the north part of the Blue line as well as at V¨astraskogen and Sundbybergs centrum towards south is larger during the morning rush hour. On the other hand, on-board passengers at Kista station heading south are observed to be more during afternoon peak hours.

4.2.2 Timetable description

The timetable of the Blue line in Stockholm is periodic, as the headway between two metro trips is constant for a period of the day. The headway is shorter during the peak-hours and longer during the night, as it varies according to the passenger vol- umes. Table 4.2 summarizes the headway of ”normal”, ”weak” and ”night services” on weekdays and weekend days on the Blue line.

The service gets more frequent during the peak hours on a weekday, when the trains of each line branch operate every 6 min. However, the time headway between two consecutive trains is 3 min for six of the stations on the Blue metro line, which are served by both branches, during the rush hours.

Table 4.2: Headway (min) variation[16].

Service Period Headway 05:00-06:30 Weak 15 21:00-24:00 Monday-Thursday Normal 06:30-21:00 10 Night 00:00-01:00 30 05:00-06:30 Weak 15 21:00-01:00 Friday Normal 06:30-21:00 10 Night 01:00-06:00 30 06:00-09:00 Weak 15 21:00-01:00 Saturday Normal 09:00-21:00 10 Night 01:00-06:00 30 06:00-09:00 Weak 15 21:00-01:00 Sunday Normal 09:00-21:00 10 Night 00:00-01:00 30

4.2.3 Operation at major stations

The number of train departures between 6:30 and 19:00, provided by SL, are used to estimate the available train capacity (seats and standing passengers) at major stations among a weekday. Since, detailed data about how the types of rolling stock are combined together on a winter weekday are not available, the train capacity is estimated, assuming that full-length C20 metro cars are operating on a winter

25 Chapter 4. Existing Metro Network in Stockholm weekday. The offered seated and standing capacity for a full-length C20 metro car for different number of train departures are summarized on Table 4.3.

Table 4.3: Offered capacity (seated and standing passengers) of a C20 metro car.

Full-length C20 train Departures Seated capacity(passengers) Standing capacity(passengers) 3 trains/30 min 1134 3726 4 trains/30 min 1512 3456 5 trains/30 min 1890 6210 6 trains/30 min 2268 7452 7 trains/30 min 2646 8694 8 trains/30 min 3024 9936 9 trains/30 min 3402 11178 10 trains/30 min 3780 12420

Figures 4.14, 4.15, 4.16, 4.17 and 4.18 indicate the relationship between the average travel demand variation of a day, which is also given on figures 4.9 - 4.13, and the train capacity at each station, giving information about the operational efficiency of the metro. The seats that remain empty as well as the standing passengers among the day are shown on the shaded parts of the plots.

Figure 4.14: Operation at T-Centralen station (3-min-headway) (Data source:[16],[17]).

26 Chapter 4. Existing Metro Network in Stockholm

Figure 4.15: Operation at Fridhemsplan station (3-min-headway) (Data source:[16],[17]).

Figure 4.16: Operation at V¨astra skogen station (3-min-headway) (Data source:[16],[17]).

27 Chapter 4. Existing Metro Network in Stockholm

Figure 4.17: Operation at Kista station (6-min-headway) (Data source:[16],[17]).

Figure 4.18: Operation at Sundbybergs centrum (6-min-headway) (Data source:[16],[17]).

It is shown that the metro operation at the major stations on the existing line, satisfies the passenger, as the number of standing passengers is kept at the minimum.

28 Chapter 4. Existing Metro Network in Stockholm

Since travel demand is usually larger in the morning than in the afternoon rush hour at most of the stations, standing passengers are mostly observed during the morning peak periods at the highly demanded stations, T-Centralen, Fridhemsplan and V¨astraskogen. Consequently, the morning ”rush service” at stations of larger demand satisfies the operator, as more seats are occupied. On the other hand, the proportion of empty seats is larger during the non rush hours at the stations of lower demand, Kista and Sundbybergs centrum.

As it is presented on the figures, there are no rejected passengers at these four major station on the existing Blue line and all of them manage to board the train. Using the equations 3.2 and 3.3, the proportion of the available number of seats that are not occupied as well as the proportion of the total amount of passengers that are standing are estimated and summarized in table 4.4. The largest percentage of empty seats is observed at Kista station towards Kungstr¨adg˚arden,where 42.55 % of the total number of seats remain empty. On the other hand, 3.55 % of the total passenger demand at Fridhemsplan station towards North are standing passengers, leading to the decrease of total satisfaction.

Table 4.4: Operational efficiency of the existing Blue line.

Stations Standing passengers (%) Empty seats (%) T-Centralen (Northbound) 1.05 25.57 Fridhemsplan (Northbound) 3.55 20.08 V¨astraskogen (Southbound) 1.41 22.36 Kista (Southbound) – 42.55 Sundbybergs (Southbound) – 37.8

29 Chapter 4. Existing Metro Network in Stockholm

30 Chapter 5

Expanded Blue Metro Line

5.1 Description of the expanded line

The future Blue line will consist of two branches, T10 and T11, extending from Hjulsta to Hags¨atra,replacing one of the three branches of the green line to the south part of the network and from Barkarby station to Nacka centrum, respectively (Table 5.1).

Table 5.1: Expanded Blue metro line.

Line Branch Expanse Stations T10 Hjulsta-Hags¨atra 24 Blue Line T11 Barkarby station-Nacka centrum 19

36 stations, 8 of which will be newly constructed, will be located on the Blue line , while 7 of the stations, from V¨astraskogen to Sofia, will be served by both branches (Figure 5.1).

Apart from the major nodes on the existing line, Sofia and Gullmarsplan stations are considered as important nodes on the future line.

Sofia Sofia metro station, located on the east part of S¨odermalm island, will be also a transfer point between the two branches of the metro line. Sofia district, which is currently served by a bus network, is a large residential area, that has a great demand for a completed and attractive transportation system.

31 Chapter 5. Expanded Blue Metro Line

Gullmarsplan Gullmarsplan, located in a big residential area in the south part of Stockholm mu- nicipality, is a point where the branches of the green line, the tramway and the bus lines meet. Nowadays, almost 38 thousands of passengers are boarding on the metro at Gullmarsplan station [18], while it is expected to be one of the most crowded sta- tions on the extended Northbound line. The trains, that will be operating on the future Blue line, will use one of the two platforms of the station that is currently occupied by the T19 branch.

Figure 5.1: The expanded metro network [24].

5.2 Planning of the expanded line

5.2.1 Expected travel demand analysis

An alternative net of the extended Blue metro line in Stockholm, provided by SL, has been analyzed through VISUM software by Josef Andersson and the average number of boarding, alighting and on-board passengers at each station on the line in the morning peak hour in 2030 is available. However, Barkarby station and Barkarbystaden are not implemented in the alternative.

Figures 5.2, 5.3, 5.4 and 5.5 represent the average passenger flow at each station on each direction of the branches of the future Blue metro line in the morning rush

32 Chapter 5. Expanded Blue Metro Line hour.

Figure 5.2: Expected average travel demand among T10 (Southbound) in 2030.

Figure 5.3: Expected average travel demand among T10 (Northbound) in 2030.

33 Chapter 5. Expanded Blue Metro Line

Figure 5.4: Expected average travel demand among T11 (Southbound) in 2030.

Figure 5.5: Expected average travel demand among T11 (Northbound) in 2030.

The trains towards Nacka centrum and Hags¨atraseems to have smaller passenger volumes on-board than trains heading northbound. Specifically, the trains towards

34 Chapter 5. Expanded Blue Metro Line the north part of the line seems to be the most crowded after the stop at stations around Gullmarsplan and Hammarby kanal during the morning peak hour.

5.2.2 Line planning

The connection of the lines that will form the future Blue line as well as the stations that will be included in the branches of the metro line are decided. The track layout and the stations included in the future Blue line are shown on Figure A.1.

Sofia station, which is up for debate, will start with a 2-track layout (Figure 5.6). However, it may end in a solution where preparations for further future expansion to a 3-track layout are made.

Figure 5.6: The track layout at Sofia station [25].

Existing depots, that are terminal stations where train are maintained and remain over night, are located at H¨ogdalenon the branch of the Green line that will be part of the future Blue line and at Rissne, connected to both Rinkeby and Hallonbergen, on the Blue line and they are shown on Figure A.1. The expansion of the depot at Rissne is possible to get more parking tracks for the metro cars.

5.2.3 Time constraints assumptions

Travel times The travel time between two stations on a metro line depends on the speed of the train and the geometry of the tracks. The railway timetables are usually constructed considering train speed lower than the allowed, in order to compensate possible delays during rush hours. Moreover, the average speed that a train operates is also affected by the type and the maximum acceleration of it. Regarding the tracks geometry, steeper positive gradient might lead to longer travel times, differing from the ones on the opposite direction.

The travel times between most of the stations are estimated for an average speed of 50 km/hr, while for network sections longer than 2 km, the train operation is designed for a speed of 60 km/hr, since the train can reach higher speed before deceleration. On the other hand, the trip times of the trains that run without

35 Chapter 5. Expanded Blue Metro Line passengers, from and to the depot, and do not stop at the stations, are estimated using a lower speed (40 km/hr) so as to avoid conflicts between them and the full ones.

Tables B.1 and B.2 summarize the travel times between consecutive stations on branches T10 and T11 of the expanded Blue metro line for both directions.

Trains coming from Hjulsta (T10 branch) have a speed restriction of 50 km/hr until a couple of hundred meters after V¨astraskogen station in the tunnel, where they merge with the T11 branch. For that reason, the travel time from V¨astraskogen to Stadshagen differ between the two branches.

Dwell times Dwell time is the time that a train is required to remain at a station in order to serve boarding and alighting passengers and it varies between rush and non-rush hours, while longer stop times are needed at stations of larger passenger volumes. The dwell times on the stations of the Blue line are decided according to MTR-policy (Table 5.2) and they are taken into account in analyzing the operation of the expanded line. Stations between V¨astraskogen and Sofia are considered as inner-city stations, while the rest are included in outer-city.

Table 5.2: Dwell times variation [25].

Dwell time (sec) Station Off-peak Peak T-Centralen 45 45 V¨astraskogen 35 35 Gullmarsplan 35 35 Inner-city stations 23 30 Outer-city stations 23 23

Turnaround times The time that a train needs to turn around at a terminal station varies with the track layout at the station, the frequency of the service and between different train types.

Considering the average walking speed (5km/hr) and the length of a full-size metro car (139.5 m), the time that the driver needs to switch to the cabin at the other end of the train can be estimated and hence, turnaround time equal to 3.5 minutes is on the limit to be accepted by MTR. However, for safety reasons, the minimum turning time is assumed to be 4.5 minutes for the current thesis.

Minimum headway Two consecutive trains that operate in the same direction and on the same track should be separated by the minimum headway time so as to avoid conflicts between them. The minimum headway time is chosen to be 2 min and it should be respected on the total length of the route in order to keep the safety distance between any two trains.

36 Chapter 5. Expanded Blue Metro Line

5.2.4 Rolling stock circulation

Taking the origin and destination stations, as well as the time constraints assump- tions, described in 5.2.3, into account, the train paths are planned. When a train reaches the terminal station, it waits for a few minutes and then the rolling stock composition is assigned to operate to the opposite direction of the same line con- nection, as it is presented on Figure 5.7 [12].

Figure 5.7: Rolling stock circulation [12].

In order to achieve optimized rolling stock circulation and follow the safety restric- tions, the turnaround time is kept longer than the minimum allowed turning time, given by MTR, and it is adjusted to the frequency of the service (peak/ off-peak periods). Moreover, the rolling stock is planned so as to avoid conflicts between trains at the terminal stations, as a station consisting of a double track could be occupied by no more than 2 trains at the same time.

Each train is represented with a continuous line, on the graphical timetable, starting from a station, that is connected to the depot, leading to a terminal station and then to another terminal on the opposite direction. The number of round trips a train does is affected by the frequency of the service (”rush service”, ”normal service”). Finally, directly after the peak period, the number of trains on the tracks is larger than what is needed during the ”normal service” and hence, some trains need to return to the depot.

37 Chapter 5. Expanded Blue Metro Line

38 Chapter 6

Analysis of Alternative Timetable Proposals

6.1 Alternatives A & B

6.1.1 Alternative A

Considering the existing Blue line that has been described in Chapter 4, which operates every 6 minutes during the peak hours and 10 minutes during off-peaks as well as the expected increase of travel demand in 2030, it is chosen to construct a timetable with 4-minute-traffic during rush hour (”rush service”) and 8-minute- traffic during non rush hour (”normal service”), using Microsoft Excel. Since future travel demand data are only available for the morning rush hour, the operation of the expanded line is limited to the period between 06:30 am and 09:30 am.

The methodology that is described and the time constraints that are assumed, are taken into account in order to plan the numerical timetable and finally, assign the rolling stock needed.

Figures A.2 and A.3 indicate the graphical timetables, which are created using Matlab software, of both branches of the Blue line. Each line shows the operation of a single train, starting from the depot, with its black part representing the operation without any passengers. Since T10 and T11 branches are merged between V¨astra skogen and Sofia stations, the timetables are constructed simultaneously so as to avoid conflicts and lead to an operation of high regularity (Figure A.4). The amount of rolling stock used for the specific proposed timetable is 24 trains for each branch of the examined line.

Stations of low demand, such as Kista, Sickla and Slakthusomr˚adetas well as sta- tions of higher demand, such as Gullmarsplan and Hammarby kanal, are chosen to evaluate the operational efficiency. The relationship between the expected average travel demand and the seated and standing capacity per hour is represented on Fig- ures 6.2, 6.3, 6.1, 6.5 and 6.4. Assuming capacity characteristics of a C20 full-length

39 Chapter 6. Analysis of Alternative Timetable Proposals metro car, the standing passengers and the empty seats are represented with shaded areas on the plots.

Figure 6.1: Operation at Slakthusomr˚adetsouthbound (4-minute-headway).

Figure 6.2: Operation at Kista northbound (4-minute-headway).

40 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.3: Operation at Sickla southbound (4-minute-headway).

Figure 6.4: Operation at Gullmarsplan northbound (4-minute-headway).

41 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.5: Operation at Hammarby kanal northbound (4-minute-headway).

Although the results are not perfectly realistic due to lack of travel demand variation, the evaluation of the operational efficiency of the expanded Blue line will be based on the average travel demand per hour during the morning rush period on a weekday.

It is observed that the proportion of empty seats is large at the stations of lower demand, which leads to the fact that from the operator’s point of view the operation of the Blue line every 4 minutes is not efficient. Specifically, more than 70% of the total number of seats remain empty after the train, heading to North, stops at Kista. On the other hand, according to the data about the future passenger demand, Gullmarsplan and Hammarby kanal are the stations where the largest number of travelers is expected and consequently, the number of standing passengers will also be higher there.

The proportion of the empty seats as well as the passengers that do not have a seat in the train at the stations, chosen to be analyzed, are summarized in Table 6.1.

Table 6.1: Operational efficiency of the expanded Blue line for 4-minute-headway.

Alternative A Stations Standing passengers (%) Empty seats (%) Slakthusomr˚adet 2.70 37.25 Kista – 72.14 Sickla 4.50 28.94 Gullmarsplan 66.92 – Hammarby kanal 65.00 –

42 Chapter 6. Analysis of Alternative Timetable Proposals

6.1.2 Alternative B

Considering the results of the first alternative timetable-proposal, the 4-minute- headway timetable does not satisfy the operating company of Stockholm metro at stations of low demand. For that reason, the frequency is reduced and consider- ing 5-minute-traffic for the ”rush service” and 10-minute-headway for the ”normal service”, a new numerical timetable is planned. Following the same process as for the first alternative, the graphical timetables for the second alternative proposal are created for T10 and T11 branches and represented on Figures A.5, A.6, while the operation on the merged track section is shown on Figure A.7. 17 % and 25 % less trains are assigned for the alternative B on T10 and T11, respectively, comparing to the first alternative. Specifically, 20 trains are operated on T10 and 18 trains on T11 line and therefore, alternative B can be considered as more efficient.

The percentage of the seats that remain empty after the stop at the analyzed stations is also estimated. The proportion of empty seats and standing passengers are shown on Figures 6.6, 6.7, 6.8, 6.9 and 6.10.

Figure 6.6: Operation at Slakthusomr˚adetsouthbound (5-minute-headway).

43 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.7: Operation at Kista northbound (5-minute-headway).

Figure 6.8: Operation at Sickla southbound (5-minute-headway).

44 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.9: Operation at Gullmarsplan northbound (5-minute-headway).

Figure 6.10: Operation at Hammarby kanal northbound (5-minute-headway).

Table 6.2 summarizes the percentage of standees and empty seats at the stations for 5-minute-operation.

45 Chapter 6. Analysis of Alternative Timetable Proposals

Table 6.2: Operational efficiency of the expanded Blue line for 5-minute-headway.

Alternative B Stations Standing passengers (%) Empty seats (%) Slakthusomr˚adet 8.78 26.24 Kista – 65.18 Sickla 13.50 22.77 Gullmarsplan 73.70 – Hammarby kanal 72.14 –

6.1.3 Alternatives A & B: Comparison

The operation at the stations of lower demand is compared between alternative operations A and B on Figures 6.11, 6.12 and 6.13.

Figure 6.11: Comparison of alternative operations A & B at Slakthusomr˚adet (Southbound).

Figure 6.12: Comparison of alternative operations A & B at Kista (Northbound).

46 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.13: Comparison of alternative operations A & B at Sickla (Southbound).

It is presented that the alternative timetable B is expected to be more efficient during ”rush” and ”normal” services than alternative A. Table 6.3 summarizes the expected percentage change of the standing passengers and empty seats from alternative Blue line operation A to B.

Table 6.3: Percentage change of standing passengers and empty seats for alternative operation B.

Percentage change (Alternative B) Stations Standing passengers (%) Empty seats (%) Slakthusomr˚adet + 6.08 - 11.01 Kista – - 6.96 Sickla + 9.00 - 6.17 Gullmarsplan + 6.78 – Hammarby kanal + 7.14 –

Although Kista towards North is still the least operationally efficient station at the alternative operation B, the proportion of the seats that remain empty has decreased by about 7 % comparing to alternative A. However, Slakthusomr˚adet towards Hags¨atrafaces the largest efficiency improvement, as 11 % less empty seats are expected after the stop.

On the other hand, a less frequent metro service has negative effect on passengers’ comfort, as about 7 % more travelers do not manage to find a seat at the stations of large demand (Gullmarsplan and Hammarby kanal), while 9 % of the passengers are standing after the stop at Sickla towards south. However, passengers satisfaction is not considered as a criterion to choose the most efficient metro operation.

47 Chapter 6. Analysis of Alternative Timetable Proposals

6.2 Alternative C

Concluding that the alternative timetable with ”rush” traffic every 5 minutes and ”normal” traffic every 10 minutes is expected to satisfy the operator most, a third alternative operation, based on alternative B, is planned. Alternative C includes short services, operating on a part of the line and not on the full length of it.

Stations that allow turnaround according to the track layout, shown on Figure A.1, and stations where the expected travel demand is low at both directions so as to avoid rejecting passengers, are taken into account in order to decide the part of the network where the short services will operate. Moreover, 5-minute-traffic is kept for all the stations from 07:30 am to 08:30 am when the maximum travel demand is observed.

As it is presented on Figures 5.4 and 5.5, the expected average travel demand at the stations between Barkarby and Kista as well as those between J¨arlaand Nacka does not significantly vary for the two directions. For that reason, T11 branch is chosen to apply short services.

Figure 6.14: Operation at Kista northbound (5-minute-headway & short services).

48 Chapter 6. Analysis of Alternative Timetable Proposals

Figure 6.15: Operation at Sickla southbound (5-minute-headway & short services).

Sickla, which is a station that allows the turnaround of a train, is set as a terminal point for some train services, while the amount of empty trains operating from and to the depot is reduced by getting the operation of some services started and finished directly from and to Hallonbergen which is connected to Rissne depot. Figure A.8 represents the graphical timetable including short services. It is shown that the peak traffic is every 5 minutes during the morning rush hour (6:30am to 9:30am) for all the stations between Sickla and Hallonbergen. However, trains from Sickla to Nacka and from Hallonbergen to Barkarby operate every 5 minutes between 7:00 am and 9:00 am.

Since the amount of rolling stock fleet required for the T11 branch of alternative C, equal to 18, does not differ from alternative B, the operation at stations with less frequent services should be also examined. The operation at Kista and Sickla stations, that are affected by the alternative operation C, is analyzed and presented on Figures 6.14 and 6.15.

Table 6.4 summarizes the evaluation criteria in details.

Table 6.4: Operational efficiency of the expanded Blue line for short services.

Alternative C Stations Standing passengers (%) Empty seats (%) Kista – 62.86 Sickla 13.75 16.46

49 Chapter 6. Analysis of Alternative Timetable Proposals

6.2.1 Alternatives B & C: Comparison

Figures 6.16 and 6.17 indicate the operational efficiency improvement at the stations for alternative operation C, comparing to alternative B, that was concluded to be more efficient than alternative A.

Figure 6.16: Comparison of alternative operations B & C at Kista (Northbound).

Figure 6.17: Comparison of alternative operations B & C at Sickla (Southbound).

Less seats remain empty between 08:00 and 10:00 am at both stations, leading to a more efficient operation of alternative timetable C. Table 6.5 presents how the proportion of standing passengers and empty seats is expected to change, from alternative operation B to C.

Table 6.5: Percentage change of standing passengers and empty seats for alternative operation C.

Percentage change (Alternative C) Stations Standing passengers (%) Empty seats (%) Kista – - 2.32 Sickla + 0.25 - 6.31

50 Chapter 6. Analysis of Alternative Timetable Proposals

Comparing alternatives B and C, it is shown that the amount of seats, that are not occupied during the alternative operation C, is expected to drop by almost 2.5% and 6.5% after the train stops at Kista and Sickla, respectively, which leads to a more efficient operation of T11 branch. On the other hand, the proportion of standing passengers does not significantly increase.

51 Chapter 6. Analysis of Alternative Timetable Proposals

52 Chapter 7

Conclusion

7.1 Summary

The current thesis is a study about the operation of the expanded Blue metro line in Stockholm, concerning the expected average travel demand in 2030. Considering the rail timetable construction methodology that is described, the analysis of the existing Blue metro line that is observed to satisfy the operator during the morning rush hour at stations of larger demand and the time constraint assumptions that are made, three alternative timetables are proposed and evaluated. The evaluation of their operational efficiency is based on two criteria, the number of rolling stock needed and the percentage of seats that are not occupied.

Alternative A refers to timetables for T10 and T11 branches of the future Blue line, using 4-minute-headway for the ”rush service” and 8-minute-headway for the ”nor- mal service”. Alternative B presents a less frequent service, where the metro trains operate every 5 and 10 minutes during the rush and non rush hour, respectively. It is concluded that the alternative operation A is less efficient than B, since the amount of rolling stock fleet needed for alternative A is 21 % larger and consequently, the number of occupied seats is smaller. Finally, alternative C, which is based on the second alternative, introduces short services operating between Hallonbergen and Sickla, stations that can be used as terminals.

Tables 7.1 and 7.2 summarize and compare the results of the three alternatives, concluding that alternative C provides an efficient operation of the expanded Blue line and hence, it satisfies the operating company. Specifically, the percentage of the non occupied seats for the alternative operation C is expected to be 9.28 % and 12.48 % lower than alternative A at Kista and Sickla stations, respectively.

53 Chapter 7. Conclusion

Table 7.1: Rolling stock needed

Trains Timetables T10 T11 Alternative A 24 24 Alternative B 20 18 Alternative C 20 18

Table 7.2: Operational efficiency of the alternative timetable proposals.

Empty seats (%) Stations Alt. A Alt. B Alt. C Slakthusomr˚adet 37.25 26.24 26.24 Kista 72.14 65.18 62.86 Sickla 28.94 22.77 16.46

However, since the average expected travel demand data are only available and due to lack of hour-to-hour demand variation, the results might not be accurate. Moreover, timetables for T10 and T11 branch of the future Blue line are simultane- ously planned in order to achieve regularity and avoid conflicts between the trains. However, a perfectly regular timetable is difficult to be constructed.

7.2 Further analysis

The timetables created in the thesis are limited to the morning rush hour and the operation results are expected to be different for the afternoon rush hour. Passenger volumes are expected to vary between the morning and afternoon rush hour, since people travel to the opposite direction in the afternoon. Further study is needed so as to evaluate the operational efficiency of the Blue metro line among a whole weekday.

Additionally, further optimization of frequency, combination of short and normal services among the day and rolling stock allocation would lead to a more efficient metro operation. Moreover, operational efficiency is assessed assuming that only C20 full-length metro cars are used. By considering the combination of full and short-length metro cars regarding the variation of the travel demand, are needed to be considered during weak-hour-services to improve capacity.

Crew scheduling, which is not examined in the current project, is the final step of railway planning where the stations where the drivers start and complete their shifts are assigned. Furthermore, financial criteria are not directly studied in the current project, and hence a cost benefit analysis (CBA) would be a more accurate criterion of examining the operator’s satisfaction.

Finally, Friends Arena, the Swedish national arena, located close to the metro sta- tion at Solna centrum has capacity for 50 thousands people. In order to avoid

54 Chapter 7. Conclusion overcrowded trains on days when popular events take place, additional services on T11 branch of the line towards south, could be occasionally included in the normal service some time before and after the event.

55 Chapter 7. Conclusion

56 Bibliography

[1] Stockholms L¨ans Landsting, SLL, 2015, Befolkningst¨atheteri Stockholms l¨an 2013 och prognoser f¨or2023, Befolkningsprognos 2015-2024/50. [2] Stockholms L¨ansLandsting, SLL, 2015, Future-bound on board the new Metro. [3] Liebchen, C. and M¨ohring,R. H., 2002, A Case Study in Periodic Timetabling, Electronic Notes in Theoretical Computer Science, Elsevier Science. [4] Kroon, L.G., Peeters, L.W.P., Wagenaar, J.C., Zuidwijk, R.A., 2012, Flexible connections in PESP models for cyclic passengers railway timetabling, Erasmus University Rotterdam. [5] Tzieropoulos, P. and Emery, D., 2009, How regular is a regular-interval timetable? Theoretical foundations and assessment methodology, 9th Swiss Transport Research Conference. [6] Niu, H. and Zhou, X., 2013, Optimizing urban rail timetable under time- dependent demand and oversaturated conditions, Transportation Research Part C, Elsevier. [7] Sun, L., Jin, J.G., Lee, D.-H., Axhausen, K.W., Erath, A., 2014, Demand-driven timetable design for metro services, Transportation Research Part C, Elsevier. [8] Ghoseiri, K., Szidarovszky, F., Asgharpour, M.J., 2004, A multi-objective train scheduling model and solution, Transportation Research Part B, Elsevier. [9] Goverde, R., 2007, Railway timetable stability analysis using max-plus system theory, Transportation Research Part B, Elsevier. [10] Delorme, X., Gandibleux, X., Rodriguez, J., 2007, Stability evaluation of a railway timetable at station level, Science Direct, Elsevier. [11] Lai, Y.C., Ip, C.S., Huang, S.Y., 2015, Development of the operational stability and efficiency evaluation model for metro systems, 6th International Conference on Railway Operations Modelling and Analysis, RailTokyo. [12] Peeters, L., 2003, Cyclic Railway Timetable Optimization, Erasmus Research Institute of Management (ERIM) Erasmus University Rotterdam, ISBN 90-5892- 042-9. [13] Toshiba Japan, 2016, Trueline Cloud, Timetable Editor, http://www.toshiba.co.jp/sis/railwaysystem/en/products/information/transportation/trueline/, Accessed: 2016-04-01.

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[18] AB Storstockholms Lokaltrafik, SL, 2015, Sl Rapport, Fakta om SL och l¨anet 2014, SL 2015-1293.

[19] WSP, 2012, Rapport, Befolkningsprognos f¨orSundbybergs stad ˚ar2012-2026 .

[20] Bombardier, 2016, Transportation Project, Metro C20-Stockholm, Sweden, http://www.bombardier.com/en/transportation/projects/project.c20- stockholm-sweden.html, Accessed: 2016-04-09.

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58 Appendix A

59 Appendix A.

Figure A.1: The track layout of the expanded line [25].

60 Appendix A.

Figure A.2: Graphical timetable of T10 branch using a headway of 4 minutes.

61 Appendix A.

Figure A.3: Graphical timetable of T11 branch using a headway of 4 minutes.

62 Appendix A.

Figure A.4: Graphical timetable of T10 & T11 merged branches using a headway of 4 minutes.

63 Appendix A.

Figure A.5: Graphical timetable of T10 branch using a headway of 5 minutes.

64 Appendix A.

Figure A.6: Graphical timetable of T11 branch using a headway of 5 minutes.

65 Appendix A.

Figure A.7: Graphical timetable of T10 & T11 merged branches using a headway of 5 minutes.

66 Appendix A.

Figure A.8: Graphical timetable of T11 branch using a headway of 5 minutes and short services.

67 Appendix A.

68 Appendix B

69 Appendix B.

Table B.1: Travel times (sec) on T10 [25].

T10 Southbound Northbound Origin Destination Trip time Origin Destination Trip time Hju Ten 85 Hag R˚ag 101 Ten Rib 103 R˚ag H¨od 89 Rib Ris 116 H¨od Bah 67 Ris Duv 90 Bah Stb 59 Duv Sbg 71 Stb Svm 63 Sbg Ssd 73 Svm Sop 55 Ssd Huv 81 Sop Slh 92 Huv V¨as 85 Slh Gup 73 V¨as Sha 104 Gup Sfa 128 Sha Fhp 72 Sfa Ktg 141 Fhp R˚ah 78 Ktg Tce 64 R˚ah Tce 80 Tce R˚ah 74 Tce Ktg 63 R˚ah Fhp 80 Ktg Sfa 138 Fhp Sha 73 Sfa Gup 108 Sha V¨as 92 Gup Slh 79 V¨as Huv 81 Slh Sop 86 Huv Ssd 75 Sop Svm 56 Ssd Sbg 73 Svm Stb 57 Sbg Duv 70 Stb Bah 59 Duv Ris 90 Bah H¨od 66 Ris Rib 117 H¨od R˚ag 88 Rib Ten 96 R˚ag Hag 140 Ten Hju 126

70 Appendix B.

Table B.2: Travel times (sec) on T11 [25].

T11 Southbound Northbound Origin Destination Trip time Origin Destination Trip time Bsn Bas 99 Nac J¨al 74 Bas Aka 136 J¨al Sik 99 Aka Hub 68 Sik Hbk 125 Hub Kis 83 Hbk Sfa 82 Kis Hab 240 Sfa Ktg 141 Hab N¨ar 78 Ktg Tce 64 N¨ar Soc 92 Tce R˚ah 74 Soc V¨as 110 R˚ah Fhp 80 V¨as Sha 94 Fhp Sha 73 Sha Fhp 72 Sha V¨as 92 Fhp R˚ah 78 V¨as Soc 101 R˚ah Tce 80 Soc N¨ar 88 Tce Ktg 63 N¨ar Hab 73 Ktg Sfa 138 Hab Kis 243 Sfa Hbk 75 Kis Hub 83 Hbk Sik 126 Hub Aka 69 Sik J¨al 98 Aka Bas 130 J¨al Nac 97 Bas Bsn 136

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