High Speed Railway Project Development and Regional Accessibility Improvement: the First Experience in India

Home , Eastern Freeway (Mumbai), Frecciargento, Frecciarossa 1000, Fuxing (train), Hexie (train), Korea Train Express

FACULTY OF CIVIL AND INDUSTRIAL ENGINEERING

Master Degree in Transport System Engineering

Thesis High Speed Railway Project Development and Regional Accessibility Improvement: The First Experience in India

Supervisor: Candidate: Prof. Eng. Antonio Musso Amal Kuzhiparambil Purushothaman Co-Supervisor: N° 1722321 Dr. Eng. Cristiana Piccioni

Academic Year 2018/2019

Table of contents

Summary 1. Introduction 1.1 Study purpose 1.2 Research background 1.3 Research methodology 1.4 Key issues 2. The Reference framework 2.1 Definition of high-speed rail 2.2 HSR benefits 2.3 HS Rail around the world 2.3.1 Japan 2.3.2 Italy 2.3.3 France 2.3.4 Germany 2.3.5 Spain 2.3.6 China 3. The accessibility concept 3.1 Definition of accessibility 3.2 Accessibility indicators 3.3 A basic benchmarking exercise 4. Accessibility and HSR projects: an insight into international experiences 4.1 The Madrid-Barcelona HSR case study, Spain 4.2 The China HSR case study 4.3 The Seoul HSR case study, Korea 4.4 Brisbane - Melbourne proposed HSR, Australia 5. Building an accessibility indicators framework 5.1 Identification of Accessibility indicators 5.2 A selection of accessibility indicators 5.2.1 Weighted average travel times (Location indicator) 5.2.2 Economic potential

5.2.3 Daily accessibility indicator 5.2.4 Economic accessibility 6. Pilot study: the Mumbai – Ahmedabad HSR project 6.1 HSR project background 6.1.1 Necessity of HSR System in India 6.2 Major cities affected by the project 6.2.1 Mumbai 6.2.2 Surat 6.2.3 Vadodara 6.2.4 Ahmedabad 6.3 HSR Project overview 6.3.1 Basic characteristics 6.3.2 Stations 6.3.3 Train operation plans 6.4 Accessibility assessment 6.4.1 Calculation and evaluation of indicators 6.4.2 Weighted average travel times (location indicator) 6.4.3 Economic potential 6.4.4 Daily accessibility indicator 6.4.5 Economic indicator 7. Lessons learned from a comparative analysis 7.1 Summary of pilot study 7.2 Comparative analysis with Madrid-Barcelona HSR ex-ante/ex-post evidences 7.3 Recommendations for adopting the selected indicators 8. Conclusions and Recommendations 8.1 Future research developments

List of Acronyms List of Figures List of Tables References

Summary

High-Speed Rail (HSR) is emerging all over the world as an increasingly popular and efficient means of transport. After five decades of International experience developing nations like India is investing in HSR infrastructure. Mumbai- Ahmedabad rail corridor is the first experience in India. Benefits of such a huge investment are an issue of concern. On this background, the thesis aims at understanding the project development and regional accessibility improvement.

This thesis tries to provide a further contribution to the study of global HSR networks. On this light, the thesis also includes a critical review of the Mumbai- Ahmedabad HSR project in terms of functional and performance features. Further, this aims to investigate on the regional accessibility enhancement achieved by the new infrastructure.

In order to evaluate the accessibility improvement, this study put forward a set of specific indicators derived from a benchmarking exercise. By analyzing from international experiences, how well different types of accessibility indicators are able to capture the accessibility changes. A set of accessibility indicators are introduced. Using these indicators, relative changes accessibility of the study area are presented and analyzed. The results provide an understanding of differential effects on regional accessibility based on the geographical location and size of urban areas along the HSR corridor under study.

Acknowledgment

This project would not have been possible without the help of my advisers, so many thanks to Prof. Eng. Antonio Musso and Dr. Eng. Cristiana Piccioni for the effort and the time you gave to me.

I thank my family for their prayers and blessings for giving me the force during the whole Master Degree, without you this would have never happened.

I thank my friends for their effort and help in completing my thesis.

Thanks to my University Sapienza University of Rome, and for each prof. who taught me, Stefano Ricci, Antonio Musso, Guido Gentile, Mattia Giovanni Crespi, Paolo De Girolamo, Paola Di Mascio, Gaetano Fusco, Massimo Guarascio, Gabriele Malavasi, Luca Persia, and Liana Ricci.

I was one of the lucky students who had the honour of being taught under such professors.

Chapter 1

Introduction

1.1 Study purpose

Developing nations like India is taking its first step on High-Speed Rail (HSR) investment after five decades of international experience. This paper is intended to review Mumbai- Ahmedabad HSR project development and assess the regional accessibility improvements.

An observation on the specific project details provides a better idea about the quality of the system as a transport facility among the present international standard of HSR networks. In addition, the thesis details the overview of HSR networks and the socio-economic background of the region.

In order to evaluate the accessibility improvement, the project aims at developing a set of accessibility indicators and methodology from identified best practices around the world. Finally, the identified set of indicators are introduced in Mumbai-Ahmedabad HSR and evaluated.

1.2 Research background

The quest for speed and growing impact of global warming to the transportation industry are primary reasons behind the new HSR initiatives all over the world. HSR project demands large scale investments so, the functional quality and ability to perform as a transport system becomes a key concern.

Domestic transportations are an important factor for economic development. Although India has a large and diverse transport network with its own challenges, they can overcome by introducing energy-efficient technologies and improved performance. India is the seventh largest nation with more than a billion populations, has a large potential to invest in transport infrastructure

The concept of accessibility is used in many scientific research fields such as transport planning, urban regional planning, feasibility studies, etc. Accessibility studies play a key

7 role in policy making and give an important tool for understanding the economic impacts. In addition, accessibility analysis studies address the link between the spatial structure of the region and travel pattern of its residents. Therefore, it is very important to identify a set of accessibility indicator that is closely related to the purpose of research.

1.3 Research methodology

The goal of the research is to evaluate the Mumbai- Ahmedabad HSR project details and assess the regional accessibility improvement achieved. The study included a global HSR framework, literature review on accessibility and accessibility indicator, insights to international experience, case study background and project review, selection of indicators and its calculation under case study data and evaluation of findings obtained.

Various research techniques were applied in each stage of methodology. Firstly, setting a reference framework for the study. Global statuses of HSR in some nation are described, followed by the introduction of basic HSR details. The study chose Japan, considering it as the pioneer in HSR transport. Four countries from Europe such as Italy, France, Germany and Spain as a consolidated HSR system. Considering a new and innovative system, Chinese HSR is also included in the study.

In a further literature review, the accessibility concept is introduced. Definition of accessibility, accessibility indicators and supporting literature have included. Because the focus of the thesis is to a find a set of indicators to initiate the case study, evidence from international experiences are discussed in building an accessibility indicator framework, four indicators are selected from the identified studies. The indicators selected are weighted average travel time (location indicator), economic potential, daily accessibility indicator, and economic accessibility. These indicators of technical and functional characteristics are discussed.

In the background to the case study, the regional socio-economic and transport scenarios are discussed. The current transport situation of the project affected cities precedes the HSR project overview. Apart from the basic HSR characteristics, the thesis focus on HSR stations and train operation plans to enlighten the accessibility analysis. Next, the selected indicators are calculated using the collected case study data’s. A comparative analysis with component modes and identified international experience build further understanding of regional accessibility improvements.

In summary, the general outline of the research is covered as per the above- mentioned approach. The thesis report devotes to draft the research and finding with explicit details, easily understandable structure, supporting maps and diagrams and necessary references.

1.4 Key issues

Changes in transport infrastructure produce a progressive contribution of space by shortening travel time and transport costs. The high-speed rail has the potential to boost links between cities to a condition formerly unimaginable. Its competitiveness as a mode of transport depends on the quality of service, access times to major economic activities and potential to carry a large volume of passengers. As the HSR infrastructure brings a large financial burden with it, its benefit is a major issue of concern.

The initial questions emerged alone with the objective of the thesis are the methodology and level of the approach of the study. The HSR impact level and limitations as an academic thesis were a matter of concern. Thus, the first challenge is in defining between national, international or focused within an urban agglomeration level of studies and appropriate methodology. The selection of methodology raises another concern about data acquisition. As expensive onboard surveys are out of the reach of this paper, the scope of GIS-based tools must be explored.

The selection of indicators is a core issue in measuring accessibility changes. In fact, the result can be very distinct depending on the indicators used. Thus, defining and selection of indicators kept as a matter of great concern in this thesis work. It is known that is the conceptualization various the indicators respond differently and provide complementary results of accessibility changes. So, selecting a set of indicators capable of addressing all these concerns is a major issue needed to overcome.

Certainly, by overcoming these challenges the thesis kept setting a benchmark in analyzing the regional accessibility improvements by HSR. In addition, the initiatives can be successfully implemented for the case study also.

Chapter 2

The Reference Framework

2.1 Definition of High-Speed Rail

High Speed Rail (HSR) can be defined as a rail service that can achieve faster speeds than most of the conventional rail services due to better technical specifications for horizontal and vertical alignment of the track, operating systems such as signaling, and rolling stock. HSR has been sought after in various nations over Europe and Asia to give enhanced mobility and trigger monetary advancement.

The vital factors that recognize HSR from ordinary rail in Europe & Asia include:

• Dedicated traveler lines with limited or no common use with cargo; • Expansion of an HSR arrange that covers existing rail systems with established demand; • Use of city center stations that offer solid incorporation with other regional, commuter, and metro/rapid transit networks; • Use of established framework throughout the HSR system; and • Use of electric traction to power rolling stock

The International Union of Railways (UIC) has developed a definition of HSR: “High speed rail is a combination of a lot of elements which constitutes a whole “system”: infrastructure (new lines designed for speeds above 250 km/h and in some cases, upgraded existing lines for speeds up to 200 or even 220 km/h), rolling stock (special designed train sets), operating conditions and equipment, etc.”

A high-speed system comprises of the following physical components: 1) Stations which are merged with local transport systems; 2) Track; 3) Civil infrastructure including earth work, bridges, tunnels, grade separations and associated reconfigurations of existing infrastructure to prepare for the new arrangement; 4) Facilities to perform and handle the framework and vehicles; 5) Systems including signaling, communications and associated electromagnetic spectrum acquisition;

6) Traction power; and 7) Vehicles.

High Speed Rail which is employed with the utmost commercial speed of 320km/h in the world has been constructed by fusing various technologies which are contradictory from the traditional ones. In order to avoid the huge losses that can occur in an accident caused due to high vibrations of the rolling stock and to achieve safe high-speed operation, progressively advanced technologies have been implemented. Numerous technologies that are proven to be comparatively better such as the structure and maintenance methodology of track, rolling stock, electrification system and Automatic Train Control (ATC), etc. have been acquired to HSR.

Referring to the rolling stock, the technology development regarding running resistance in high speed are, adhesion coefficient, running stability, power collection of pantographs, bearing metal, wind pressure occurred when the train runs into the passage, crossing of trains, and braking distance, etc. have been created. Rolling stock which has aerodynamic shape and sophisticated body structure has been built up.

As to power, there is improvement of advances, for example, catenary structure bearable for high speed, regular functioning and enforcement of its material, compounding of catenary and installation of vibration reduction equipment to reduce the vibration caused by high speed. Thus, proving the reliability of HSR.

Referring to signaling system, for instance, Automatic Train Control (ATC) which displays signal on the indicator in the rail car (cab signal) and interlocks brake with cab signal has been made and installed in order to accomplish high-speed operation, since there is no scope for human blunder.

As listed above, various methodologies which include track, electric signal and rolling stock, etc. has been introduced for the better results to achieve safe high-speed operation. Thus, HSR system is one unique framework integrated with many advanced technologies.

2.2 HSR benefits

The very concept of HSR is intended in drastic betterment of economic growth. Growth is observed in all fields such as tourism, employment, trade, transportation etc. Benefits in terms of greater speed, improved safety, greater reliability, accurate frequency were achieved. Cities were brought closer, thereby improving trade opportunities between different markets, different people and different cities. It also attracted plethora of tourists resulting in economic productivity.

Mostly operating at greater frequencies than conventional rail and having fewer delays with improvised access to various destinations, HSR is considered as a savior. Apart from a deadly accident in China in July 2011, high-speed rail operations have maintained excellent safety records and had never experienced much injury or fatality. In air and road travel restricted regions, HSR has come to the rescue. Shifting the means of transportation to HSR has benefited passengers traveling for less than two and half hours. The redirection of about 80% passengers from road and air trips to HSR added up free space in conventional rail promoting cargo services, other intercity and commuter rail services. For instance, the United Kingdom has tended to limit requirements on its West Coast Main Line with the execution of the proposed High-Speed line. In Japan, the main motivation for implementing the Tokaido line between Tokyo and Osaka was to provide additional capacity to the transportation network, rather than to reduce travel times.

Employment, wages, trade in urban markets and output saw an immense boost in regional and local economies. Improved working conditions, easy face to face interactions, minimized cost of travel enabled labor to work efficiently and thus, enhancing productivity, business competitiveness, leading to higher wages.

HSR gives more noteworthy ecological benefits and energy efficiencies than different methods of long-distance travel. The natural benefits of fast rail rely upon a few conditions: strong ridership, clean energy sources to power trains, and mode shift from less efficient forms of transportation. For example, Shinkansen trains are expected to utilize one-quarter the energy of airplanes and one-sixth that of private automobiles per passenger mile. To achieve environmental benefits, highspeed trains must increase load factors to realize the greatest efficiencies.

High-speed rail is the main accessible method of long-distance travel that does not depend on motor fuels. It is powered by electricity, which is considered a better option over petroleum generated power. Moreover, energy planning ensures the reduction of greenhouse gases and other harmful pollutants.

2.3 High Speed Rail around the world

2.3.1 Japan Japan encountered a huge economic growth a decade after World War II. Initiating the Tokaido-Shinkansen project was an evidence to it. it helped meeting the connectivity demand in the densely populated areas of Osaka and Tokyo. Even during the 1950s, with around 45 million people, the road and rail networks were congested. To address this issue, Japan initiated its first HSR line in 1964, leading to the expansion of the existing huge networks. The networks spread, multiplying the country's wealth eventually resulting in economic growth.

Figure 1- HSR network of Japan (source: Japan Stations website)

The Tokaido line: The Tokaido line connected three main cities namely, Tokyo, Osaka and Nagoya (approximately 30, 16 and 8.5 million inhabitants, respectively). It has recorded that 5.3 billion passengers travelled between Tokyo and Osaka since 1964 and the

Tokaido Shinkansen itself carried more than 10 billion passengers as per the report of CJRC (Central Japan Railway Company report). Tokyo- (operating kilometres) Osaka Okayama Hiroshima Fukuoka (552.6 km) (732.9 km) (894.2 km) (1,174 km)

Travel Time (Shinkansen) 2 hr 22 min 3 hr 09 min 3 hr 44 min 4 hr 46 min

Number of services a per day 250 128 99 67 (Shinkansen)

Table 1 Serving 355 million passengers annually, Japan’s national high-speed network today has a total length of 3,041 km (1,890 miles). In a shorter time of just two and a half hours, the original line running from Tokyo to Osaka, which covers 515 kilometers (320 miles) is considered the main transportation axis. Shinkansen courses totally on separate rail, subsequently, not influenced by slower nearby trains or cargo. The shinkansen utilizes Figure 2 Japan HSR performance 1435mm standard measures and utilizes an ATC (Automatic Train Control) framework, eliminating the need of trackside signals.

2.3.2 Italy Italy is one of the pioneers in HSR industry who were the first to start such network in Europe. Italian high-speed trains link country's major cities, with even more routes being planned and under construction. Italy made it first step in the quest for speed in year 1939 itself. An ETR 212 set a record on an average speed over long distance between Florence and Milan with maximum speed of 203 km/h. The foremost high-speed rail route in Italy, opened in 1977, connecting Rome with Florence. The top speed on the line was 250 km/h, giving an end-to-end trip time of about 90 minutes with an average speed of 200 km/h (120 mph). This line used a 3 kV DC supply. High-speed service was publicized on the Rome-Milan line in 1988-89 with the ETR 450 Pendolino train, with a top speed of 250 km/h and reducing travel times from about 5 hours to 4 hours. The model train ETR X 500 was the first Italian train to reach 300 km/h on the Direttissima on 25 May 1989.

Figure 3 - Italy HSR map

Passenger service is delivered by Trenitalia and, since April 2012, by NTV-Italo, the world's first private open-access operator of high-speed rail to compete with a state-owned monopoly. 25 million passengers voyaged on the network in 2011. In 2015, ridership increased to 55 million for Trenitalia and 9.1 million for NTV, for a combined 64 million passengers.

Trenitalia's high-speed trains are called Alta Velocità (AV), and are broken down into three categories: Frecciarossa, Frecciargento, and Frecciabianca. Frecciarossa trains are the fastest, reaching speeds of up to 190 MPH (300 km/h). Services on the high-speed lines is delivered by Trenitalia and privately owned NTV.

The AV train network joins Turin, Milan, Bologna, Florence, Rome, Naples, and Salerno. While Italo operates on a different set of rail lines, connects Turin, Milan, Venice, Padua, Bologna, Florence, Rome, Naples, and Salerno.

Frecciarossa trains

Frecciarossa high-speed trains, operated by Trenitalia, reaches speeds of 300 km/h and offer maximum comfort, making trips between Italian cities as short as possible. It makes more than 120 daily connections throughout Italy, from Turin and Milan in the north, to Salerno and Bari in the south. There are 28 non-stop Frecciarossa trains between Milan and Rome every day, making the journey in just under 3 hours. Frecciarossa trains that stop on the way in Bologna and Florence still make the trip in just over 3.5 hours. During peak travel times, there are 12 trains leaving Milan to Rome and 13 leaving Rome to Milan.

There are 36 daily Frecciarossa trains between Milan and Naples, and that trip takes just over 4 hours. There are 10 Frecciarossa trains between Turin and Rome daily, with stops in Milan, Bologna, and Florence along the way. Frecciarossa trains make the connection from Bologna to Florence 70 times daily in around 37 minutes.

The Frecciarossa 1000 is a deluxe environmentally-friendly option with the most advanced technology available. It has 16 powerful engines and can reach speeds of 400km/h. The train is also fully silent and has the certification of environmental impact.

Frecciargento trains

The Frecciargento trains links Rome to Venice, Verona, Bari/Lecce, Lamezia Terme / Reggio Calabria on both high-speed lines and traditional lines. Frecciargento trains reach speeds up to 250 km/h Rome – Venice – Rome: 26 daily connections in a 3 and half hours.

Rome – Verona – Rome: 6 daily connections. Out of that, 2 Frecciargento trains will continue up to Brescia, allowing passengers to benefit from the recent doubling of the Bologna – Verona line, and takes only 3 hours between Verona and Rome.

Rome – Bari – Rome: 10 connections which makes only 4-hour journey.

Rome – Reggio di Calabria – Rome: There are 10 connections daily.

Frecciabianca trains

Trains offer service on traditional lines from Milan to Venice, Udine, Trieste, Genoa, Rome, Bari, and Lecce. Frecciabianca trains can reach speed of 250 km/h.

Figure 4 - Major freccia High-speed line map

2.3.3 France Following the footsteps of Japan, France set its own HSR network. From 1970 onwards, France is kept on building HSR systems, the main line being between Paris and Lyon. HSR standards of France such as gauges, voltage and signaling are adopted by most of the European countries. Paris played a prominent role in the field of business and politics. Efforts were being made to develop Paris, thus a rail link connecting Paris and Lyon (the corridor to south-east France) became the initial HSR service in France. The population of France was relatively low, and Paris gradually emerged to be the central hub. The line expanded outwards from Paris to connect other important destinations. It served various corridors in and around Paris.

Figure 5 - France HSR network Many European countries incorporated the French HSR standardizations. The French rail operating company, SNCF, reports that its TGVs have taken the dominant share of the air-rail travel market in many of the high-speed corridors, taking over 90 percent in the Paris-Lyon market. The total number of rail passengers raised following its inauguration, rising from 12.5 million in 1980 to carrying 110 million passengers per year.

2.3.4 Germany Germany, the third nation to build up the HSR systems in 1991 and named its fast trains as InterCity Express later became Intercity-express. Comparing the west-east introduction of the rail network built before WWII and the current north-south patterns of industrial cooperation, a decision has been made to change the network to encourage cargo transportation from the northern ports towards the southern industrial regions. Thus, the initial two new lines were those connecting Hannover and Würzburg and Mannheim and Stuttgart, respectively. The principle objective was to determine blockage issues in bound passages and to support north south cargo traffic.

Figure 6 - Germany HSR map (source: Transport Journal)

German strategy is significantly different from the models embraced by Japan and France, whose framework is connecting distant city-pairs with few intermediate stops. The main idea is to upgrade existing rail lines providing more space with higher speed service and simultaneously building new high-speed lines. From the data available, the cumulative sum of passengers is roughly 1.25 billion in 2015.

Upgraded Line Cologne-Aachen 250km/h

Partially new line Hanover-Berlin 250km/h (new line) 200km/h (existing sections) Nuremberg-Munich 300km/h (new line 200km/h (existing sections) Fully newly line Cologne- Frankfurt 300km/h

Hanover-Wurzburg 280km/h

Mannheim-Stuttgart 280km/h

Erfurt-Leipzig 300km/h

Lines not yet completed Frankfurt- Mannheim 300km/h

Nuremberg- Erfurt 300km/h

Karlsruhe-Basel 250km/h

Hananu-Gelnhausen 300km/h

Stuttgart-Wendlingen 250km/h

Wendlingen-Ulm 250km/h

Table 2 - German HSR lines

2.3.5 Spain The first line was opened in 1992, connecting the cities of Madrid, Córdoba and Seville. The Alta Velocidad Española (AVE) uses standard gauge. This permits direct connections to outside Spain through the link to the French network at the Perthus tunnel.

Line Speed(km/h) Length(km) Start of Construction construction completion

Madrid-Seville 300 472 1989 1992

Córdoba-Malaga 300 155 2001 2007

Madrid-Valladolid 350 179.6 2001 2007

Madrid-Barcelona 350 621 1995 2008

Madrid-Valencia 350 391 2004 2010

Albacete-Alicante 350 171.5 - 2013

Barcelona-French border 350 150.8 2004 2013

Valladolid-León 350 162.7 2009 2015

Valladolid-Burgos 350 134.8 2009 2016-2017

Seville-Cádiz 250 157 2001 2015

León-Gijon 350 - 2009 2017

Olmedo-Zamora-Galicia 350 435.0 2004 2011-2018

Murcia-Almeria 300 184.3 Unknown After 2018

Burgos-Vitoria 350 98.8 2009 2019

Basque Y 250 175 2006 2019

Mediterranean Corridor 250-350 >1300 2004 2013-2022

Madrid-Caceres-Mérida- 350 640 2008 After 2020

Table 3 Spain HSR lines

By 2020, Spain should have connected almost all provincial capitals to Madrid in less than 3 hours and Barcelona within 6 hours with high-speed trains. The Spanish and Portuguese high- speed lines have European standard and UIC track gauge of 1,435 mm and electrified with 25 kV at 50 Hz from overhead wire. The first HSL from Madrid to Seville is equipped with LZB train control system, later lines with ETCS. Alta Velocidad Española (AVE) is a service of high-speed rail in Spain operated by Renfe, the Spanish national railway company, at speeds of up to 310 km/h. Alta Velocidad Española As of August 2017, the Spanish AVE system is the longest HSR network in Europe with 3,240 km and the second longest in the world, after China's.

Figure 7 - Spain Rail Network map

Three companies have built or will build trains for the Spanish high-speed railway network: Spanish Talgo, French Alstom and German Siemens AG. Bombardier Transportation is a partner in both the Talgo-led and the Siemens-led consortium. France will eventually build 25 kV TGV lines to the Spanish border, but multi-voltage trains will still be needed. To this end, RENFE decided to convert 10 existing AVE S100 trains to operate at this voltage (as well as the French signalling systems), which will cost 30 M€ instead of the previously expected 270 M€ for new trains.

2.3.6 China The HSR of china is most immensely used mode of transport in china. It is the longest in the world and is designed for speeds of 250–350 km/h. the total length being 29,000 km, it covers 30 of the 33 provincial-level administrative divisions excluding Macau, Ningxia, and Tibet. It plans to cover 38,000 km by 2025.

The HSR of China was planned back in the 1990s, inspired from Japanese Shinkansen experiences. China Railway is the successor of the former Ministry of Railways. The China railway corporation owns it, under the brand China Railway High- speed (CRH). The CRH was launched in the year April 2007, consisting of two trains sets namely, Hexie Hao and Fuxing Hao and later extended.

Figure 8 China HSR map

Track network and major lines

China's conventional high-speed railway network is made up of four components:

• a national grid of mostly passenger dedicated HSR lines (PDLs), • other regional HSRs connecting major cities, • certain regional "intercity" HSR lines, and • other newly built or upgraded conventional rail lines, mostly in western China, that can carry high-speed passenger and freight trains.

Major High-Speed Rail Lines Lines Open Date Length(km) Speed(km/h)

Beljing-Shanghal 30/06/2011 1,318 300-350

Beljing-Guangzhou 26/12/2012 2,298 200-300

Beljing-Xi’an 26/12/2012 1,216 250-300

Shanghal- Guangzhou 10/12/2014 1,647 250-300

Shanghal-Kunming 28/12/2016 2,252 300-300

Xi’an-Shanghal 10/09/2016 1,509 250-300

Xi’an-chengdu 30/09/2017 643 250

Inter-city High Speed Trains Beljing-Tianjin 01/08/2008 119 300

Guangzhou-Zhuhai 31/12/2012 117 200

Guangzhou-Shenzhen 26/12/2011 116 300

Shanghal-Nanjing 01/07/2010 301 300

Nanjing-Hangzhou 01/07/2013 249 300

Table 4 China HSR lines

Ridership

Since the initial journey of YEAR MILLION RIDERS an HSR train in China, annual ridership has risen from 61.21 2013 672 million in 2007 to 420 million in 2014 893 2011, making China's HSR service the most heavily used in the HSR 2015 1161 service market. In October 2010, CRH service more than 1,000 2016 1440 trains per day, with a daily 2017 1713 ridership of about 925,000 as of May 2015, a total of 1469 CRH 2018 2001 trainsets were put into use.

Table 5 China HSR ridership data

Chapter 3

The accessibility concept

3.1 Definition of accessibility

The concept of accessibility is based on the premise that space constrains the number of opportunities available; consequently, accessibility influences both the travel costs and the levels of service use and participation in desired activities of people living in a specific. There are wide variations in the definition of accessibility and the appropriate definition always depends upon the intended application. Some fields of application are: business or industrial location selections, travel demand forecasting, population distribution and growth and transportation planning.

The following are well-known definitions of accessibility put forwarded by different scholars:

o “The benefits provided by a transportation/land-use system”. o “The ease with which any land-use activity can be reached from a location using a particular transport system”. o “The ease with which activities or destinations can be reached from a certain place and with a certain transport system” o “The extent to which land-use and transport systems enable (groups of) individuals to reach activities or destinations by means of a (combination of) transport mode(s)”

Based on their definition, certain components of accessibility can be identified:

The land-use component reflects the land-use system, consisting of: a) the amount, quality and spatial distribution opportunities supplied at each destination; b) the demand for these opportunities at origin locations; and c) the confrontation of supply of and demand for opportunities, which may result in competition for activities with restricted capacity.

The transportation component describes the transport system, expressed as the disutility for an individual to cover the distance between an origin and a destination using a specific

27 transport mode; included are the amount of time (travel, waiting and parking), costs (fixed and variable) and effort (including reliability, level of comfort, accident risk, etc.). This disutility results from the confrontation between supply and demand. The supply of infrastructure includes its location and characteristics (e.g. maximum travel speed, number of lanes, public transport timetables, travel costs). The demand relates to both passenger and freight traffic.

The temporal component reflects the temporal constraints, i.e. the availability of opportunities at different times of the day, and the time available for individuals to participate in certain activities (e.g. work, recreation).

The individual component reflects the needs (depending on age, income, educational level, household situation, etc.), abilities (depending on people’s physical condition, availability of travel modes, etc.) and opportunities (depending on people’s income, travel budget, educational level, etc.) of individuals. These characteristics influence a person’s level of access to transport modes and spatially distributed opportunities.

In essence, considering these concepts, in this research project, accessibility is defined as follows:

“Accessibility is the ease with which individuals can reach a destination from a certain place within a region and with a certain transport mode”

Accessibility must be considered in parallel with the concept of mobility. While mobility is concerned the performance of transport systems depends widely on accessibility. Accessibility measures are thus capable of assessing feedback effects between transport infrastructure and modal participation. Some accessibility measures also include behavioral determinants for activity patterns in space and time, and the responses of transport users to physical conditions.

The time when accessibility explicitly takes on board, the land use-transport connection, handles trip numbers and travel time were used as indicators. Later on, the multiple components of accessibility, accessibility can be measured in different ways.

Accessibility can be measured by different ways on the individual level (person- based), or at the location level (place-based). Whereas person-based metrics focus on the

28 individual component, place-based metrics mainly account for the land use and transport components. The individual component is sometimes included in location-based studies by stratifying population by age group or socio-economic characteristics, and by segmenting destinations (by job types for example). Location-based metrics typically accounts for the number of opportunities that can be reached from a specific location, based on the travel costs to destinations using a specific mode. Location-based accessibility is most commonly used by policy-makers as it provides a comprehensive measure of the land use and transport system at the regional level and so in this study also.

3.2 Accessibility indicators

In order to have strong positive public support for huge investment required for the conceptualization, planning, development and operation of HSR project, it is important to fully grasp the contributions by HSR towards transportation, economic, environmental, social and wider regional impacts in the HSR corridor, region and beyond. However, because of the difficulties in quantifying some of these impacts, justification is always an ambiguous one. Thus, the explicit indication of accessibility improvement is important tool for decision makers.

Accessibility impacts of a new transportation system is measured by means of a wide variety of accessibility indicators. These indicators reflect the numerous approaches to the concept of accessibility as discussed, several existing studies. Accessibility indicators are based on different accepts such as location of an area with respect to opportunities, activities or assets existing in other areas and in the area itself, where ‘area’ may be a region, a city or a corridor.

Most accessibility measurements combine travel impediment and attractiveness of different destination. Travel impediment is usually expressed in different cost units such as distance, travel time or generalized cost of transport that combines travel time, travel cost and other travel dis-utilities. Attractiveness of urban agglomerations depend on their masses such as population, employment or gross domestic product (GDP).

Accessibility indicators differ in complexity. More complex accessibility indicators take account of the connectivity of transport networks by distinguishing between the

29 network and the activities or opportunities that can be reached. These indicators always include in their formulation a spatial impedance term that describes the ease of reaching other such destinations of interest.

Further in this study, considering the data availability, the easiness in results interpretation and communication, level of study and research objectives different accessibility indicators are identified and discussed in the following chapters.

3.3 A basic benchmarking exercise

Benchmarking is the process of comparing the existing practices, identifying the best one and adopting well-defined improvements to enhance the performance. Benchmarking is also important to policy makers seeking to improve the performance of an HSR system.

In this thesis, the idea of benchmarking is initiated to put forward a set of accessibility indicators focusing on HSR service accessibility comparison to other modes at regional level. Accessibility measurement studies conducted all around the world for feasibility studies, urban planning or research objectives are using wide variety of indicators. Parameters such as travel time, distance, location and socio-economic variables are used in many indicators in different ways and results in indicating different focus. For example, the same “travel time decay” is used in daily accessibility indicator and economic potential in different manners, with and without distance decay. Furthermore, most studies use more than one indicator. So, a proper selection of indicators is relevant, so as to define an assessment framework consistent with the aims of this thesis work. More precisely, a benchmark exercise has been carried out to identify a specific set of indicators best fit to the research objectives, gain necessary performance increase as well as to understand accessibility improvement achieved by HS rail compared to other transport modes in competition.

Chapter 4

Accessibility and HSR projects: an insight into international

experiences

4.1 Madrid—Barcelona HSR case study, Spain

The accessibility impact study of the high-speed line Madrid-Barcelona-French border covered both the national and European level. A geographic information system (GIS) and detailed surveying is used to carry out this study.

Selected Indicators: Three specific indicators are used in order to measure accessibility impact, which respond to different conceptualizations and offer complementary information to the problem of changes in accessibility. They are respectively: Weighted average travel times; Economic potential and Daily accessibility indicator. Study Area: The Highspeed line connects Madrid- Zaragoza – Barcelona of the Spanish high-speed network.

Figure 9 - The European high-speed network in the study area: scenario 2005.

Travel time savings: Direct travel time savings along the HSR line, the new HSR line saves 2-hour 48 min in direct comparison with other competitive modes. From 5-hour 28 min to 2-hour 40 min, it is of 51.2 % of saving in total travel time.

Routes Travel time, 2005 Travel time saving

Without new line With new line Absolute %

Madrid- 5 h 28 min 2 h 40 min 2 h 48 51.2 Barcelona min

Madrid– 3 h 3 min 1 h 25 min 1 h 38 53.5 Zaragoza min

Zaragoza - 3 h 27 min 1 h 15 min 2 h 12 68.6 Barcelona min

Table 6 – Change in travel time (source: Gutierrez 2001)

Weighted Average travel time: The weighted average travel time is calculated not only for the cities along the line but also for many European agglomerations in the study area (those with more than 300,000 inhabitants). Logically, the greatest benefits is for cities along the HSR line, and the study also accounts those cities better access with each other and to the cities in the rest of Europe.

Figure 10 - Weighted average travel time change in the study area, Spain

The new line brings reduction of 25 minutes that is about 5% of the average travel times between all the selected urban agglomerations. The populations which obtain the highest time savings is Zaragoza with 160 minutes of average travel time, that is up to 22%. Table 3 also shows large benefits for Barcelona (17.8%), Madrid (13.7 % of time saving) and other cities directly at the new HSR lines serving area.

Economic potential: From the economic potential value calculated for many cities in the study area, the average variation in economic potential of the selected urban agglomeration (only with increase of 1.45%) is much less than the one which correspondence to location indicator (average travel time reduced by 5%). The table shows the European cities located far from the new line undergo very little variation in their potential values. In fact, changes in the accessibility are mostly concentrated on cities which are directly connected to the new line than the location indicator. As shown the city that most benefit from new HSR network is the city Zaragoza (37%), which is situated close to too large populations such as Madrid and Barcelona and above that, comparatively less benefits for Barcelona (16%) and for Madrid (8%). Furthermore, the trend points out to the benefits of the cities in Spanish sector as not only from better connectivity with Barcelona, also the improved connectivity with most of the European cities located beyond the French boarder.

Daily accessibility: The average accessible population within the 4-hour travel time limit for the selected cities shows rise about a million inhabitants in average. From 20.7 million to 21.1 million inhabitants, which means an increase of 1.64%. This values from the table indicates rise of average number of accessible inhabitants of each city in travel time limit. In fact, the daily accessibility indicator has a very concentrated effect. The rise in total accessible population is important in Barcelona, total of 7.7 million inhabitants and 139% rise, which corresponds to the nearest urban populations such as Madrid, Valladoid and Marseilles.

Key findings: On accessibility improvements, the effect of new HSR line relevant not only in Spanish region that connected by the HS rail, but the study also extents to the effect on the Iberian Peninsula.

In conceptualization, the three indicators have used a different approach. When the location indicator (Weighted average travel time) focus over relationship over long distances and simultaneously, the daily accessibility indicator emphasis the relationships

34 over short distances. Logically, the results are quite different: very concentrated effects for daily accessibility indicator, less concentrated in economic potential and relatively more dispersed in the location indicator.

4.2 The China Railway High-speed Network

China’s large-scale HSR network has significantly high influence on both accessibility and connectivity. Changes in connectivity largely affect the external relations among cities, recently China has invested in transport infrastructure have much focus in HS rail connectivity. Thus, here examines the impact of China’s HS rail network on the overall connectivity and model centrality of the city network, as evaluated by passengers’ trains from 2009 to 2013

Study area: Researchers have applied accessibility to examine efficiency or economic gain HSR impact studies in China. It has calculated the accessibility effects of HSR for 2009 and 2013 and reported huge benefits to the cities connected with HSR and cities in the prosperous customer region than that of non-HSR cities and cities in the hinder-land did. One of the mostly discussed issues is HSR station locations HSR stations in Chinese cities are mostly situated outside the city core area in sub urban or even rural areas. This requires an extra link to the cities and also results in the decentralization. The following study on accessibility of Chinese HSR and the selection of indicator should focus on these issues also.

Figure 11 Study area map, China

Accessibility indicator and methodology: The study applies a commonly used gravity model for measuring accessibility. It takes the following form.

퐸푦 Y 푖 Ai = ∑ 푌 (푇푖푗)훼

Value A represent the accessibility of city j, Ej measure the destination attractiveness at location j and T is the travel time by rail between origin in j and destination of j, Y denotes the year in which A is measured. The parameter α reflects traveler’s sensitivity to travel time increase its value is generally calibrated from travel surveys and here took as 1.

Accessibility growth from 2006 to 2014 can be influenced by both reduced rail time and increased jobs. As the objective of the study focus, the independent effect of HSR on accessibility should be accounted. Two accessibilities are calculated. Other than base accessibility, an accessibility of the cities using 2006 data for employment but with 2014 rail times is also calculated. So, the difference between the estimated and the base value can be referred as the contribution of HSR.

The accessibility improvements are calculated using the above-mentioned indicator for four territorial regions such as Eastern China, Central China, Western China and North Eastern China consisting of 19 cities nation-wide.

Key finding: From the results obtained from calculating the above-mentioned indicator, it is evident that the accessibility increased from 2006 to 2014 nation-wide (186.2%), in four territorial regions and in all 19-city cluster. Four regional clusters show more than double increase in accessibility scores. Within the territorial region, cities show varying levels of gains in accessibility. The region that experienced lowest increase in accessibility is Tianshan Northridge (85.7%), because of its remote location and comparatively less population and economic concentration. Similarly, the highest improvement in accessibility in this period is for central china with 206% of rise. It is clear that the central plain consist of regions like central Shangxi and central plain, relatively developed and populated. But the individual city in the study area with highest increase is North Bay (240%) and this region has high urban population concentration. The cities, like Nnning, Venue of Asean expo, with two third of its population focused on cities includes in the North Bay region. It is evident that the indicators are reflecting these scenarios.

Accordingly, researchers adopt different approaches for better understanding of the indicators. Mapping the accessibility scores of cities cluster to visualize the spatial patterns of accessibility associated with HSR. Second, calculation of co-efficient of

37 variation to examine the potential effect of HSR on within-region disparity. Third, to better understand the role of HSR separated from the effects of economic growth, decomposed the observed changes in economic growth effect and other effects.

In summary, the Chinese study shows facts that, HSR improved travel time not only for cities located on HSR lines but also for the non-HSR cities owing to HSR’s network effects. The magnitude of accessibility varied HSR shrinks time space and makes remotely located opportunity distribute unevenly over the space throughout the country. As China plans to expand its HSR network to connect to connect more cities, it is timely important to research on ways to integrate plans for HSR routing and station siting with regional spatial development plans in order to avoid overheating and over-investment in HSR infrastructure.

4.3 The Seoul HSR case study, Korea

Study area: The Korea Train eXpress (KTX) became operational in April 2004, it is evident that the high- speed inter-city service has been creating positive impacts on forming a model share structure comfortable to the notion competitive advantage between travel modes. The increase in ridership is generally accepted as the influence of accessibility improvement also. Here, the systemized accessibility analysis with a case study of the Seoul metropolitan area is stated. It is the area covering 12% of total national area (11,753 km2) and of 46% of national population with a population above 25 million and is fifth largest metropolitan area in the world.

Figure 12 - Seoul case study area

Indicators and Methodology: For measuring accessibility either conventional or log sum type measure can be used, but this approach is carried out with developing a modified Hansen type index to investigate the accessibility of Korean high-speed rail. Thus, by

39 eliminating the surveying and other data acquisition, difficulties if log sum type measures over the conventional indicators.

Accessibility Aj at original j directly varies with the opportunity S of the socio- economic activities of destinations j and inversely with transport costs can be written as:

Aj =∑ f-1 (Cij)

and by fixing the socio-economic opportunities and formulating the cost as a linear function of the attributes of trips weighted by their parameters. The assessment is to quality the degree of accessibility of different geographic regions.

The assessment has broadly 5 stages. First, the patronage of KTX of each origin zone is plotted against the zonal accessibility. The data of ridership collected from the survey is used with generalized cost of the location to measure the accessibility. Second, a function which best fits with the obtained observation is drawn. Then, third, an ANOVA test (Analysis of Variance) is applied to classify the high-speed rail impact boundary of zones. The boundary is set as high, medium or low in ridership and good, fair or poor is zonal accessibility as being a set of acceptable criteria for the accessibility analysis. Fourth, the point of tangency between the loci of the decay functions and impact boundary determines the zonal accessibility. Thus, each observations accessibility and ridership’s are evident. The unit of measurement has normalized patronage that was defined as the demand divided by population. Finally, a mapping audit is conducted. In particular, a GIS-based approach is adopted because GIS is a visually appealing and cost- effective tool in which many different data sets can be easily displayed in single or multiple layers.

Key Findings: The Figure 13 that shows the ANOVA test plotted for the ridership and accessibility. These directly give the classification of KTX impact boundaries and degrees of accessibility. The summary of the data also gives idea about observations fall in each category and the corresponding values. Here,20 observations fall in high and 25 in medium and 23 in low, the unit of measurement is the normalized patronage that was defined as the demand by population.

Figure 13 - Test result, Seoul case study

Summary of data

Boundary Count Sum Average Variance

High 20 203.37 10.17 12.21

Medium 25 120.23 4.81 7.94

Low 23 39.27 1.71 1.06

Table 7 – key findings, Seoul case study

Figure 14 shows the accessibility classification of the region. It is evident in the map that the good accessibility region consists of Seoul and some Gyonggi province areas in the southern region of the Seoul metropolitan area. This area leans to South. Specifically, North Seoul is excluded and but some regions of Gyonggi; province regions are included.

Figure 14 - Accessibility change plotted on study area

Further, when connecting the GIS mapped data to ridership measure from the test results and economic status of the region (Korea National Statistical Office Data), many observations can be put forwarded. Such as the accessibility of North West Gyonggi is not poor, but the ridership is not at a corresponding level. Again, this would be the result of economic power of the residents in this area (KNSO data). Observing such socio- economic scenarios in correlation with test result can provide trends and beneficiaries. Thus, the study measures the accessibility and plot the connection under lies with the rider potential and regional economic status to it.

4.4 Brisbane – Melbourne proposed HSR, Australia

After the successful contribution of HS rail to global transport connectivity in Japan, Europe and China, Australia has been under investigation since 1980s.Many studies has conducted at regional and national level on the accessibility improvement can be achieved through HSR network. An ex-ante analysis on the regional accessibility improvement is stated as follows:

Proposed HSR alignment and study area: The linear alignment shown in figure x is used to assess the regional accessibility impacts of the proposed HSR system. This alignment is proposed by AECOM et al. The proposed HSR alignment connects four Australian Eastern States (VIC, ACT, NSW and QLD) and their capital cities (Melbourne, Canberra, Sydney and Brisbane) respectively in a linear network fashion. Australian HSR system is expected to be capable of operating speeds of up to 350km/hr. The Australian HSR system will take maximum of 6 hours travel time from Melbourne to Brisbane. It will take only about 3 hours from both Melbourne to Sydney and Sydney to Brisbane. Canberra will be an hour travel time from Sydney and 2 hours from Melbourne.

Sydney and Brisbane are large cities (more than 1 million population) and Canberra, Newcastle and Gold Coast are intermediate cities (more than 300,000 population) on Australian HSR alignment. The major regional towns in Australian HSR corridor are Shepperton, Albury Wodonga, Wagga, Goulburn, Bowral, Gosford, Taree, Port Macquarie, Coffs Harbor, Grafton and Lismore/Ballina/Casino.

Selected indicators: For the purpose of this analysis, four accessibility indicators are used. They are respectively: location indicator, economic potential indicator, daily accessibility indicator and commuting accessibility indicator. These indicators respond to different conceptualizations and offer complementary information about the issue of accessibility.

These selected accessibility indicators are calculated for year 2011 for three competing transport modes, such as roads, conventional rails and proposed HSR to predict the accessibility improvements come from the proposed Australian HSR system. The accessibility calculation needs both transport network data (e.g. travel time, travel costs) and attractiveness or mass (population) of the urban agglomerations. The cities in the research area with a population of higher than 20,000 inhabitants where the proposed HSR stations located are included in the study. Similar data of these cities were collected

43 from official population census statistics of Australia. Each indicators and research findings are discussed here:

Figure 15 - Proposed Australian HSR layout

Location Accessibility Indicator: From the calculated results, it is evident that the intermediate towns show more improvements in location accessibility than the larger cities at the both ends. The analysis shows that Australian HSR will improve the location accessibility of all cities the HSR connects by minimum of 65% in comparison with existing ground transport system. It is also clear that the location accessibility changes for all cities will be similar, however, outlying regional areas such as Shepperton, Canberra, Gosford, Lismore and Gold Coast will have better location accessibility increase than other areas.

Economic Potential: Improvement in economic potential is very high and evident comparing with the previous indicator. The study shows that Australian HSR will

44 improve the economic potential the cities from 200% to 320% compared with maximum population reached per unit of time by existing efficient ground transport system (i.e., roads). It also shows that the Australian HSR will improve the economic potential of the regional towns such as Shepperton, Wagga Wagga, Gosford and Lismore more than large capital cities and other nearby regional agglomerations.

Daily Accessibility: In terms of daily accessibility indicator, almost all the cities show double the improvement in the number of people. It is also clear that the remote regional towns (Albury-Wodonga, Wagga Wagga, Canberra, Port Macquarie, and Coffs Harbor) are the highest beneficiaries of the daily accessibility improvements. Moreover, Sydneysiders will be able to reach all population within the HSR corridor within 3 hours of one directional travel (i.e., daily accessibility). Moreover, Australian HSR will result two bands of daily accessibility regions: Melbourne to Sydney (southern HSR daily accessibility region with catchment of ten million people) and Sydney to Brisbane (northern HSR daily accessibility region with catchment of 8 million people).

Commuting Accessibility: The study shows that commuting accessibility of peripheral regional towns (Shepperton, Goulburn, Bowral and Lismore) associated with three large cities (Melbourne, Sydney and Brisbane) will improve significantly. Australian HSR will result three bands of commuting regions: Melbourne to Shepparton (southern HSR commuting region with catchment of 4 million people), Canberra to Newcastle (central HSR commuting region with catchment of 5 million people) and Lismore to Brisbane (northern HSR commuting region with catchment of 3 million people).

Expected Findings: All the four indicators show that the proposed Australian HSR system will significantly improve the regional accessibility of all urban agglomerations by bringing them closure to each other compared with the existing accessibility. However, the peripheral regional towns to three major cities in Australia are the biggest winners in terms of regional accessibility change. Improvement in the regional accessibility of the urban agglomerations along the HSR corridor is one of the major benefits of Australian High-Speed rail network as the accessibility improvements are proved to have positive impacts on regional socio-economic development.

Chapter 5

Building an accessibility indicators framework

5.1 Identification of accessibility indicators

In chapter 4, a selection of past experiences concerning HSR accessibility assessment have been presented. One is from Europe, two from Asia and the last one comes from Australia. Each study varies from each other in their level of approach, study area, conceptualization of indicators, data required, data collection method and representation of main outcomes. All the factors mentioned in Chapter 4 have been considered in this thesis work in order to formulate a set of indicators and approach best fit for the Indian case study.

Study area: The project under study is the part of regional network of Indian railway between Mumbai and Ahmedabad. So, the selection of indicators gives prominence to regional level approach. Among the identified studies in Chapter 4, Seoul and Australian cases are more regional level than the other two. On the other hand, studies focusing on such as China and Spain cases, cover a more national and international level of. Besides, both studies focus a network instead of a single line connecting two cities.

Indicators: The use of indicators help in scientific identification, quantification and ranking of area with varying degrees of accessibility. Generally, most of the studies use gravity model for measuring accessibility as in the case study of China. In the case study of Soul metropolitan area, as detailed in previous chapter, a modified form of conventional indicators is used. Both such cases, the indicators combine two components, the impedance and locational attractiveness. While in other two studies multiple indicators are used. Moreover, some indicators used in Spain and Australia case studies are quite similar. This helps in understanding the flexibility of indicators in addressing different scenarios.

Data collection: Data required, and possible methods of data collection are important while identifying indicators. Conducting surveys as well as processing large amount of data is a heavy task. Reliability and quality of the data is also relevant. Case studies previously discussed suggest that the use of GIS based tools in data acquisition

46 along with regional socio-economic statistics is a well-known and widely accepted practice. In most cases, data like population and other economics attractiveness can be projected from the last census.

Illustration method: Each assessment study provides a large scale set of information. However, if information is not easily grasped with implication, it will be ignored or potentially misinterpreted. This results in slow, poor or uninformed decision-making process. According to the four studies discussed above, the best way of illustrating the result is projecting the calculated values into a map along with measured accessibility values. This method gives faster understanding of the values in connecting with corresponding regions, thus enabling easy comparison among different scenarios. In the Seoul case study (section 4.3) results provide an accessibility assessment in connecting with ridership. However, such results cannot be represented in a single map and in such case the analytical complexity increases accordingly.

International experiences described in Chapter 4 shows the usage of several indicators such as conventional gravity models, modified Hansen type, location accessibility indicator (weighted average travel times), Economic potential and daily accessibility indicator. Besides, other relevant measures such as Economic accessibility and Global accessibility are also discussed. The Global accessibility concept can be partially covered through the location indicator.

As the intention of this study is to measure the accessibility improvement at regional level, not to calculate the possible catchment areas of the infrastructure, the global accessibility indicator can be intended as out of scope. Further, the indicators in the case studies use economic activities only as a function to represent the economic attractiveness for example the use of population in economic potential or location indicator. Thus, an economic indicator with direct depiction of economic values provide better understanding.

According to what experienced in the selected “good practices”, taking into account the dataset built through a focused data collection along with the main purpose of this study, three specific accessibility indicators have been chosen, as follows: : Location accessibility indicator (Weighted average travel times), Economic potential and Daily accessibility indicator along with economic indicator. Such indicators will be further investigated in the following chapters and then used in the Mumbai- Ahmedabad HSR case study.

5.2 A selection of accessibility indicators

In this chapter all the selected indicator is discussed with corresponding formulations. The concept of each indicators and differences in the result are also discussed in the following sub sections. The discussion is elaborated with reference to the case studies listed along the chapter 4. The discussion is developed by understanding each indicator individually and comparing among selected indicators also.

5.2.1 Weighted average travel times (location indicator) The weighted average travel time between each node and all urban agglomerations is calculated taking as weight the mass of the centers according to the following; 푛 ∑푗=1(푇푖푗. 푀푗) 퐿푖 = 푛 ∑푗=1 푀푗

Where Li is the accessibility (location) of node i, Tij is the travel time by the minimal- time route through the network between node i and all urban agglomerations is used as weight to value the importance of the minimal-time routes. The measure is not a gravity- based indicator (there is no distance-decay), so that, unlike economic potential it does not place the emphasize on short distance. Thus, for example, in the economic potential model, discussed in the Spain case study, the relationship Madrid-Guadalajara could weigh more than the relationship of two potentially larger cities Madrid and Paris, because Guadalajara is very closer to Madrid than Paris. This average-distance-based indicator should be interpreted from the locational rather than the economic point of view. But economic implications are obvious, since the spatial situation of the regions within country is a factor of attractiveness and development capabilities of the region. This measure expresses the relative location of each place and the extent to which a new link modifies this location by reducing access time to the main urban agglomeration. The results are very easily interpreted, for example: from node A the average travel time to all centers is 400 min in the scenario “without the line” and 360 min in the scenario “with the line”, which means a time saving of 40 min.

5.2.2 Economic potential The economic potential is a gravity-based measure, widely used in accessibility studies. It is a measure of the nearness or accessibility of a given volume of economic

48 activity of a particular point/region and can be interpreted as the volume of economic activity to which region has access, after the cost/time of covering the distance to that activities have been accounted for. According to this model, the level of opportunity (accessibility) between a node i and a destination node j is positively related to the mass of the destination and inversely proportional to some power of the distance between both nodes. Its classical mathematical expression is as follows:

푛 Mj Pi= ∑ a 푗=1 Tij

Where Pi is the economic potential of node i, a is a parameter reflecting the rate of increasing of the friction of distance (distance decay) and the other terms are still known. In this paper (as in most accessibility studies) the parameter values a used is 1. Using higher values than 1 means giving too much importance to relations over short distance (which would not seem appropriate when analyzing the effect of a new infrastructure of a national nature such as the line which is the object of this study) and it also means increasing the problem known as self-potential.

When discussing the former indicator (Weighted average travel time), it has been argued that in the evaluation of the impact of large transport infrastructure it would seem reasonable to point out the long distance effect. Yet from a merely economic point of view, there is doubt that the economic effects of a new infrastructure are inversely related to the distance (there are many trips over short distance and few trips over long distances), so that in this context it would seem appropriate to use a gravity-based operationalization. Therefore, the interpretation of the result provided by this indicator must be carried out from an economic view point; the indicator measures the economic potential of each place in each of the scenario considered and the change in potential caused by the new infrastructure true.

5.2.3 Daily accessibility indicator This indicator consists of calculating the amount of population or economic activity that can be reached from a node within a certain travel time limit. The time limit is usually established in 2 or 4 h, so that it is possible to go and return the day and carry out an activity at the visit location. The limit of 3 h travel is considered as a critical cut- off point since it represents the likely limit of comfortable day return business traffic, although the limit of 3 h is the likely cut-off point for major transfer from air to rail

49 transport. The travel time limit is set by considering the level of study and project background. This measurement is particularly useful for calculating accessibility in business and tourist trips, for the need to stay overnight in the destination city means an important extra expense for both companies and individuals. In fact, the empirical evident shows that new high-speed lines produce an increase not only in the number of travelers in the relations served by the line, but also in the proportion of those who return within the same day. In the context of the high-speed train, this indicator provides basically the number of possible business contacts (for business trips) and the market potential (for tourist trips). It measures how much population can be reached from a place (or can reach a place) in a certain travel time limit and the changes in accessible population brought about by a new infrastructure. The results are of the following type: from city A, within a travel time limit of 2 h, 10 million inhabitants can be reached in the scenario “without the line” and 15 million in the scenario “with the line”, which means an increase of 5 million inhabitant.

5.2.4 Economic Indicator There is no doubt that the mode choice has greater influence of force in accessing an infrastructure. When a user makes a mode choice decision, his perceived cost includes the money value along with time and other monetary costs he needs to pay for the trip. On accessibility issue, the fare of the trip can consider as an indicator of accessibility study primarily of this reason. And, the fare of HSR or any other modes is easily available and as it is directly in money value, the results are easily understandable too.

Considering the fare as an indicator, the willingness to pay and economic condition of users are should be accounted. Willingness to pay is the amount that an individual is willing to sacrifice to procure the transportation service. These facts highly influence on mode choice. So, the users’ behaviour on mode choice is influenced by willingness to pay and it highly depends on the income of passengers. Thus, the service offered is not only judged by quality of the service but also the capability of service users. Therefore, along with the fare, the income level also should be accounted. The GDP or GDP per Capita values can be analysed on this context.

As an indicator of accessibility, a comparison of fare with other available modes is also an important aspect. An HSR line should be able to provide service at acceptable fare to a particular class of users the transport system is targeting. Thus, in this case study includes comparison between different modes and a cross country comparison of fare.

Chapter 6

Pilot study: Mumbai – Ahmedabad HS Rail project

6.1 HS Rail project background

Transport infrastructure plays a key factor for the development of a country. One cannot over emphasize the importance of transportation than call it the 'lifeline' of a nation. Everybody is looking forward for fastest and efficient means of transport infrastructure for transportation. Good physical connectivity in the urban and rural areas is essential for economic growth. India, the seventh largest nation with over a billion population, has one of the largest transport sectors among the world.

Domestic transportation is a key factor for economic growth and transportation issues and infrastructural delays affect a nation's progress and India needs much faster and efficient transportation systems.

6.1.1 Necessity of HSR System in India Rail transport systems is one of the most efficient and more economical means of transport than road. Also, Rail construction costs are lower than road for comparable levels of traffic. Historically, the Indian railways have played a leading role in carrying passengers and cargo across India’s vast territory.

There are several strong arguments and reasons which support the introduction of HSR in the country. In the year ending March 2018, IR carried 8.26 billion passengers and transported 1.16 billion tons of freight. Apart from diverting passengers from road and air, HSR generates a new class of passengers as well. With the average operating speeds of around 250 km/h, HSR helps bring settlements 500 km apart within two hours of each other. By Rail Experts, HSR has been a catalyst for economic growth, a stimulus for the development of satellite towns, helping alleviate migration to metropolises. Providing services from and to city centers, HSR serves important centers in route, providing value for time through express and easy access to tier-II and tier-III cities.

As per JICA survey, Indians travel more and longer distance. By 2020-21, Indians will travel on average thrice as much as they travelled in 2000-01. There are a lot of commercial and industrial establishments over the country. The introduction of HSR is a key facility that is likely to cut down on time and cost of travel across key financial sectors or links. This in turn will make way for more investments and enterprises and generally boost “Make in India” initiatives. One of the key concerns in recent times is the high rate of unemployment in the country. Introduction of HSR will generate employment by the thousands, particularly in cities such as Pune, Surat and Ahmadabad, where manufacturing industries are rapidly growing.

Figure 16 - Mumbai-Ahmedabad HSR map

6.2 Major cities affected by the project

The Mumbai - Ahmedabad HSR project connect four major cities of the region such as Mumbai, Surat, Vadodara, and Ahmedabad along with several intermediate cities.

Figure 17 - Population density in the project affected area

6.2.1 Mumbai Mumbai is the most populated city of India and estimated about 12.4 million people. Mumbai account for slightly more than 6.16% of Indian economy contributing 10% of factory employment, 30% of income and 40% of foreign trade like most of the metropolitan cities. Mumbai has a large influx of people from rural area looking for employment.

Socio Economic Facts

Population in 2011 (2001)

Mumbai City 3,145,966 (3,326,837)

Mumbai Suburban 9,332,481 (8,587,000)

Greater Mumbai (Total) 12,478,447 (11,913,837)

MMR 20,748,395 (18,414,288)

Decadal Growth Rate (%)

Mumbai City (-) 5.75

Mumbai Suburban 8.01

Greater Mumbai (Total) 4.74

Area (2011)

Mumbai City 157 km2

Mumbai Suburban 446 km2

MMR 4,355 km2

Per Capita Income (2010-2011) Rs 1,41 lakh

GDDP at Constant Price in Rs 1,689,730 million 2010-2011(2004-2005 Prices)

Table 8 - Socio economic facts, Mumbai

The infrastructure of transport in Mumbai has to appear to the rising demand. Mumbai has 16.4 million houses i.e., twice as many people as those in New York city.

Mumbai is the most populated city of India and estimated about 12.4 million people. Mumbai account for slightly more than 6.16% of Indian economy contributing 10% of factory employment, 30% of income and 40% of foreign trade like most of the metropolitan cities. Mumbai has a large influx of people from rural area looking for employment.

The infrastructure of transport in Mumbai has to appear to the rising demand. Mumbai has 16.4 million houses ie, twice as many people as those in New York city.

Roads

Eastern Freeway: It links P.D Mello road in south Mumbai to the eastern express highway (EEH) at Ghatkopar which 16.8 km is about long and among 13.59 km stretch of the freeway comprising two of three segment are operational and the rest is to be completed.

Figure 18 - Mumbai Road map

Coastal Road (West): The coast road is along the western coast from Narima point to Malad 35 km long with inter changes at 18 locations connecting major roads. It also connects both western and southern Mumbai.

Railways

Metro Rail: The metro rail system is 146 km length. It goes through the greater Mumbai region from north to south and connects the airport and CBD which is located on the southern part of the island.

Figure 19 - Railway network map of Mumbai

Mono Rail: Mumbai mono rail is 19.54 km and has 17 stations between Chempur and Walada depot.

Western Railway: It connects the corridor from Avalmaidan to Virar.

6.2.2 Surat Surat is one of the major cities and the 8th largest city of India. It has the largest sea port and it is now a center for diamond industry. The city is located 284 km South of the Gujarat’s capital Gandhinagar, 265 km South of Ahmedabad and 289 km North of Mumbai. It is one of the most fast-growing cities (GDP 11.5% over the last 7 years) and it is known as the first smart IT Indian city. The city has 2.97 million internet users which is 65% of total population.

Surat railway was built in 1860. The railway connects 245 bus routes linking major localities. Surat international airport located in Magalala is 11 km South-West of Surat. Apart from main city Surat airport also enters to narrow localities of South Gujarat.

Figure 20 – Mumbai socio-economic and transport scenarios

Population Concentration: The current population density varies from 10,400/sq.km to 53,000/sq.km and it is expected to vary between 34,000 and 50,000/sq.km in the coming 2 years.

Transport Systems: Most of the people travel across the region through road. Due to this, these region faces traffic problem like congestion, air pollution and noise pollution.

The road network of Surat city is 372 km in 1976 to 644 km in 1990 showing an increase rate of 18kms per annum.

Figure 21 - Transport network of Surat

The 3 existing railway stations in the city having 36 pairs of passenger trains in total of 72 trains in both directions.

6.2.3 Vadodara It is the one of the largest cities in Gujarat as compared to Ahmedabad and Surat with population 1.67 million people. Vadodara is the city with many large-scale industries like India Oil Cooperation, IPCL, GACL, and many other major government and private authority large scale industries have been setup. Over 35% of India’s power transmission and distribution equipment manufacture industries are in this city. Many other developing projects for IT and stock exchange are in progress.

Figure 22 - Vadodara rail network

Transport System in Vadodara

Vadodara has major rail and road network connecting with Delhi and Mumbai with Ahmedabad. The transportation activities in Vadodara through air, rail and road are discussed in the following.

Air

Vadodara airport is in North East of the city. It is the second green airport in India. It has connection flights from major cities like Mumbai, New Delhi, Hyderabad, Chennai, Kolkata and Bangalore.

Figure 24 Vadodara socio-economic facts

Railway

Vadodara railway is one of the oldest railways in India. The 10 major railways stations in Vadodara are Pratapnagar, Vishwanitri, Makarapa, Karajan, Miygan, Itola, Varnama, Bijwa, Ranoli, Nandesar. It now belongs to the Western railway zone of Indian railway main line. It is the busiest railway in Gujarat with 358 trains passing each day. Major long route trains like Rajadhani, Shabari, Durando and other Mail/ express trains passes through these areas.

Road

Vadodara road connects Delhi and Gandhinagar with Ahmadabad to Surat which passes through Mumbai by National Highway. Many road extension projects of National Highway passing through Vadodara is been taking place.

There are over one hundred buses in Vadodara which is having a seat capacity of 33 to 50 persons. The people travelling through public and private transportation through this road is facing many problems due congestion in peak time hours.

6.2.4 Ahmedabad Ahmedabad is sixth largest metropolitan city in India with a population of 68 million people. Ahmedabad is the fastest growing city in India and is listed as the 3rd fastest growing city in the world after the Chine’s cities. The GDP of Ahmedabad is US $ 64 billion in the year of 2014. The city is known for its cotton textiles, gem stones and jewelries, the industries like automobile industry, chemical industry are growing in a faster rate.

Figure 25 Ahmedabad socio-economic facts

Transport

Ahmedabad is one of six operating divisions in the Western Railway zone. Railway lines connect the city to towns in Gujarat and major Indian cities. Ahmedabad railway station, locally known as Kalupur station is the main terminus with 11 others. The mass-transit metro system, MEGA for the cities of Ahmedabad and Gandhinagar is under construction since March 2015.The North-South and East-West corridors are expected to complete by 2019.

National Highway 48 passes through Ahmedabad and connects with Delhi and Mumbai. The National Highway 147 also links Ahmedabad to Gandhinagar. It is connected to Vadodara through National Expressway 1, a 94 km (58 mi) long expressway with two exits. This expressway is part of the Golden Quadrilateral project.

In 2001, Ahmedabad was ranked as the most polluted city in India, out of 85 cities, by the Central Pollution Control Board. The Gujarat Pollution Control Board gave auto rickshaw drivers an incentive of ₹10,000 to convert all 37,733 auto rickshaws in Ahmedabad to cleaner burning compressed natural gas to reduce pollution. As a result, in 2008, Ahmedabad was ranked as 50th most polluted city in India.

“Janmarg” is a bus rapid transit system in the city. It is operated by Ahmedabad Janmarg Limited, a subsidiary of Ahmedabad Municipal Corporation and others. Inaugurated in October 2009, the network expanded to 89 kilometers (55 mi) by December 2015 with daily ridership of 1,32,000 passengers.

Sardar Vallabhbhai Patel International Airport, 15 km (9.3 mi) from the city Centre, provides domestic and international flights. It is the busiest airport in Gujarat and the eighth busiest in India with an average of 250 aircraft movements a day. Another airport, The Dholera International Airport is proposed near Fedara (30 km from city). It will be the largest airport in India with a total area of 7,500 hectares.

6.3 HSR Project overview

India has undergone rapid economic growth in recent years, and along with this growth has come a sharp rise in the volume of people and goods being transported in the country. To meet this demand, the Ministry of Railways (MOR) and the Republic of India, prepared the “Indian Railway Vision 2020” in December 2009. Seven routes have been chosen as candidates for the High-Speed Railway (HSR). MOR and Republic of India designates the line between Mumbai and Ahmedabad (approximately 500 kms as the first HSR section to be constructed.

The region targeted by the study is a corridor having a length of approximately 500 kms that links Mumbai which is located in the state of Maharashtra in western India and Gujarat, which form the target region of the study as provided in the image below.

Figure 26 Mumbai-Ahmedabad HSR alignment

The study area extends two states and two union territories in western India, namely Maharashtra state, Gujarat state, Dadra and Nagar Haveli and Daman and Diu. For HSR that operates at the maximum speed of 250–350 km/h, the vision plans to implement projects by 2020. Furthermore, it will also make plans for multiple routes to connect the commercial centers, tourist spots, pilgrimage destinations, and so on. Overall

65 cost of the construction is estimated to be Rs. 490-546 billion. And that of Rolling stock is Rs. 67.83 billion.

Because the high-speed trains will enter the conventional line stations, the track gauge and car width of the high-speed trains will be the same as the trains operate on the conventional lines. ERTMS level 2 will be used as signaling standard and the rolling stock will be the EMU, which is the mainstream of high-speed railway today. The feeding method will use the AC 2*25kV system, which is standard for high-speed railway around the world.

6.3.1 Basic characteristics The construction method and operation method summarized in the ‘Characteristics of section” in the above image are the important items in the selection of technical specification in the pre-feasibility study by the French consultants. The main characteristics are as follows:

• Because the high-speed trains will enter the conventional line stations, the track gauge and car width of the high-speed trains will be the same as the trains operate on the conventional lines. • The signaling and telecommunication system ERTMS Level 2, which is the interoperability standard in Europe, is selected. • The rolling stock will be the EMU, which is the mainstream of high-speed railway today. • The feeding method will use the AC 2x25kV system, which is the standard for high-speed railway in the world. • The track will be ballast-less to enable operation at 350 km/h in the future.

Although it will mainly be an HSR line, the alignment is designed assuming entry into conventional line stations, thus the same 1,676 mm gauge as the conventional lines will be used. The plan is to cross Thane Creek by bridge. From a natural environment point of view, because the surrounding area of Thane creek is designed as the Sanjay Gandhi national park, it is subject to strict development regulations. As for crossing the Thane creek SU1 route which will cross it at the downstream was recommended. However, the construction will be affected because it will interfere with some of the Sanjay Gandhi

National park. The bridge of the SU2 route, which will cross the Thane creek at the upstream, will also interfere with the Sanjay Gandhi national park. Moreover, since it is planed that the route will pass through the eastern side of the Sanjay Gandhi sanctuary north of Thane, it will interfere with part of the sanctuary thus the development regulations are expected to remain a problem.

Because the plan is made for the Pune- Mumbai – Ahmedabad section, the alignment near Navi Mumbai is designed in a delta shape to split into the Mumbai, Ahmedabad, and Pune directions.

The breadth of the formation level is 13.6 m, which is wider than the plan which our study team recommends. As a result, the required dimensions of the land and structures are bigger. The long tunnels comply with the tunnel safety standards of European specifications. The single-track tunnels will be constructed in parallel, with connection to each other at an interval of 500 m as an evacuation route.

Overview of Project Section Mumbai-Ahmedabad Gauge 1676 mm Civil engineering structures Length: approximately 504 kms Track structure Ballast-less Fastened tracks Signalling system ERTMS Level 2 GSM-R Overhead catenary line Simple catenary system Telecommunications GSM-R Fare collection Use conventional method because the card system is still in development Train operation 80 trains/day (one-direction) Rolling stocks E5 Series Shinkansen Train length approximately 200 m Alignment Construction standard for the design maximum speed of 350 km/h (maximum curve radius 6425 m) Financial and economic analysis Operating cost Rs. 2.05 billion Maintenance cost: rolling stock Rs. 1.45 billion, Infrastructure Rs. 2.54 billion Table 9 – Project overview, Mumbai-Ahmedabad HSR

Rolling Stock

EMU is the mainstream train set use in latest HSR which will also be used in this project. The maximum speed is 350 kms/h, which is the feasible speed stated in the rolling

67 stock specification, rather than the actual operating speed. It uses 1676 mm gauge considering operation through conventional lines. Each bogie has 5 seats per row, car width is 3265 mm, 8 cars per train set with the capacity of 600 people.

Electric power

The feeding system will be 2*25kV, the so-called Auto Transformer. It is becoming standard feeding system of high-speed railways in the world. For the receiving system, the receiving of a single-phase from the power company’s three-phase extra high voltage transmission lines (225kV) is used.

Signaling and telecommunication unit

The ERTMS level 2 signaling system is used for the project used by European HSR systems. ERTMS is developed to standardize the train protection systems so that trains in Europe can operate interchangeably in all its countries.

Earthquake detection function

In HSR, it is important to stop the trains as soon as possible wen there is a disaster of the danger of a disaster in order to prevent major accidents. The train will automatically stop when the earthquake exceeds 65 MG.

As a result of the development of power electronics technology, the AC motor driving system controlled by VVVF inverter is now used in wide ranges. In the case of EMU type high-speed rolling stock, AGV trains use AC synchronous motors and other trains AC induction motors. Induction motors are more advantageous in that they feature a simple structure.

A train set of EMU type high speed railways is composed of plural traction units, each having a transformer, converter-inverter and traction motor. Attention shall duly be paid on to the traction unit to ensure environment-compatible propulsion performance, guarantee redundancy against component failure.

6.3.2 Stations A station for the region from an extensive point of view has to be connected to the regional transport mode such as Metro, BRT, taxi, buses and private vehicle and also existing railway stations in several points to supply a connection for wide spread HSR users. Roads, parking areas and station facilities for passengers will be designed to handle large number of passengers with safety and with convenience.

Si. No Station name Distance 1 Mumbai 0 k 000 2 Thane 27 k 950 3 Virar 65 k 170 4 Boisar 104 k 260 5 Vapi 167 k 940 6 Bilimora 216 k 580 7 Surat 264 k 580 8 Bharuch 323 k 110 9 Vadodara 397 k 060 10 Anand/Nadiad 447 k 380 11 Ahmedabad 500 k 190 12 Sabarmati 505 k 750 Table 10 List of stations, Mumbai-Ahmedabad HSR

Out of the 12 stations, 3 stations have connectivity to Metro lines (Mumbai, Ahmadabad and Sabarmati). All the stations have bus connectivity. Moreover 4 stations have conventional rail connectivity which are Mumbai, Thane, Ahmadabad and Sabarmati.

Structure types for elevated stations are categorized into two types based on the platform type of each station. There are Island platform with 2 platforms and 4 lines which has a RC rigid Frame, Separate platform with 2 platforms and 5 lines with an integrated type of structure. Stations with this type of structure are, Thane, Boisar, Surat, Bharuch, Vadodara, Ahmedabad, Sabarmati. Separate platform with 2 platforms with 4 lines has either rigid frame or hybrid type structure. Stations with this type of structure are, Virar, Vapi, Bilomora, Anand/Nadiad.

6.3.3 Train operation plans Train operation plan give the idea about the conditions with which the trains should run on the line. It acts as a guideline for the train operators.

The basic concepts of train operation plan are as follows:

• To set maximum operation speed at 320 km/h to shorten the travelling time. (Maximum design speed for the future is 350 km/h) • To adopt the average passengers load factor of 70% for setting operation plan. • To set 2 types stop-patterns of train: In view of diverse needs of passengers, a variety of origin and destination and a need to shorten the travelling time, two types (rapid and each stop train) should be planned • To separate operation time zone and maintenance time zone. ➢ Train operation time zone: 6:00-24:00 (0:00) ➢ Maintenance service time zone: 0:00-6:00

Two types of train planned are rapid train and each stop train. Rapid train will only stop at major stations and each stop train will stop at every station. As the stations where rapid train shall stop, Surat, Vadodara and Ahmadabad stations are proposed while considering the fact that the number of passengers is overwhelming large between Mumbai and Ahmedabad, between Mumbai and Surat and between Mumbai and Vadodara.

Si. No Station name Distance Rapid train Each stop train 1 Mumbai 0 k 000 ● ● 2 Thane 27 k 950 ● 3 Virar 65 k 170 ● 4 Boisar 104 k 260 ● 5 Vapi 167 k 940 ● 6 Bilimora 216 k 580 ● 7 Surat 264 k 580 ● ● 8 Bharuch 323 k 110 ● 9 Vadodara 397 k 060 ● ● 10 Anand/Nadiad 447 k 380 ● 11 Ahmedabad 500 k 190 ● ● 12 Sabarmati 505 k 750 ● ● Table 11 – Stop pattern, Mumbai-Ahmedabad HSR

6.4 Accessibility assessment

6.4.1 Calculation and evaluation of indicators The indicators identified through the benchmarking exercise are introduced in the section 5.2. In order to analyze the regional accessibility changes all the identified indicators should be calculated using the pilot project data stated along the chapter 6. The computation of those indicators using Mumbai-Ahmedabad HSR project details and operational data is discussed in the following sections. The results of computation using Excel solvers and corresponding data illustration using charts and graphs are also included.

6.4.2 Weighted average travel times (location indicator) The location accessibility indicator for the cities through which the HS rail line passes is listed in the Table 12. The mass of the agglomerations is used as weight to value the importance of minimal-time routes.

Location accessibility indicator

scenarios differences

CITIES without HSR (min) with HSR (min) Absolute %

Mumbai 119 50 69 58

Thane 127 51 76 60

Virar 145 54 90 63

Boisar 169 58 111 66

Vapi 194 63 131 67

Bilimora 212 68 145 68

Surat 235 73 162 69

Bharuch 281 84 198 70

Vadodara 276 96 180 65

Anand/Nadiad 341 108 234 68

Ahmedabad 391 120 272 69

Table 12 Location indicator, Mumbai-Ahmedabad HSR

Figure 27 Absolute change in Weighted average travel time, Mumbai-Ahmedabad HSR

The new line will bring reduction of 151 minutes of average travel time ie, about 65% in the average travel time between the selected urban agglomeration. As the study only covers the reduction of travel time of cities which are directly connected by the HSR line, the city shows highest reduction in absolute travel time is Ahmedabad, with 272 minutes difference in new HSR line i.e., 69 % of the average travel time. In fact, the city with highest benefit is Bharuch (70%). Bharuch shows a reduction of 198 minutes and the city’s location in between two largest populations Mumbai and Ahmedabad influence on this scenario. As explained, the location indicator does not emphasis on short distances, along the line of HSR, cities such as Vapi, Bilimora, Surat and Bharuch show marginal improvements than the cities in vicinity to the large agglomeration since like Mumbai or Ahmedabad

The trend also shows more benefit to the cities with comparatively under developed transport system in comparing with metros like Mumbai or Ahmedabad by introducing a new high-speed rail network.

6.4.3 Economic potential The economic potential value is calculated for all the cities in the study area, it shows an average of 45 % rise in economic potential, i.e., 8,096 rises in the absolute value. The average change in the economic potential is less than the rise shown is the previous indicator, weighted average travel time (69 %). Economic Potential scenarios Difference Cities Without HSR With HSR Absolute % Mumbai 77,363 101,522 24,159 31 Thane 455,195 631,270 176,075 39 Virar 217,995 328,498 110,503 51 Boisar 205,517 300,965 95,448 46 Vapi 156,139 228,875 72,736 47 Bilimora 171,542 260,544 89,001 52 Surat 100,059 141,899 41,841 42 Bharuch 231,571 338,690 107,120 46 Vadodara 112,989 170,513 57,525 51 Anand/Nadiad 176,863 264,198 87,336 49 Ahmedabad 63,040 92,040 29,000 46 Table 13 - Economic potential, Mumbai-Ahmedabad HSR

Economic Potential 700000 600000 500000 400000 300000 200000

100000 EconomicPotential 0

Cities

scenarios Without HSR scenarios With HSR

Figure 28 Change in Economic potential value, Mumbai-Ahmedabad HSR

Figure 29 - Heat map showing Average Economical potential along the HS Rail line (scenario without HSR)

The city with highest improvement in economic potential is Bilimora of 52% with new line, simultaneously Virar and Vadodara. As mentioned, the potential indicator is a gravity-based model and the values of cities near to the largely populated also reflect this trend. The intermediate cities near to Ahmedabad and Mumbai such as Virar, Bilimora and Vadodara show comparatively higher values. The self-potential of the Mumbai, Thane and Ahmedabad influence the economic potential values of the cities. However, the intermediate cities show the highest improvement economic potential, and this will reflect the regional economic development.

Figure 30 - Heat map showing Average Economic potential along the HS Rail line (scenario with HSR)

Comparing the heat map indicating economic potential change to the difference in weighted average travel time, the intermediate cities in vicinity to the bigger cities like Mumbai and Ahmedabad are showing more improvements than the cities in far. In general, the higher accessibility values are concentrated in the urban agglomerations around the mega cities, as HSR lines allow them to reach the major cities with a shorter travel time.

6.4.4 Daily accessibility indicators In daily accessibility indicator the travel time limit should be determined first. Instead of embracing European scenario, this study adapted Chinese experiences on fixing travel time limits. The cut of limit in this study is set of 2 hour and by considering the people’s willingness to travel and current transport scenarios of the region. With the building of the new line the average accessible population with in the 2 hours travel time limit for the selected urban agglomeration shows a rise of 5 million. This level of improvements doubtfully high for a project but when accounting the fact that the Mumbai-Ahmedabad HS rail connects one of the largest populations in the world makes the values justifiable. Daily accessibility indicator Scenarios Difference cities Without HSR With HSR Absolute % Mumbai 26,119,320 34,008,348 7,889,028 30 Thane 27,743,731 46,620,280 18,876,548 68 Virar 4,001,238 6,715,554 2,714,316 68 Boisar 4,281,086 6,936,055 2,654,969 62 Vapi 6,093,138 9,607,820 3,514,682 58 Bilimora 6,311,277 9,607,820 3,296,543 52 Surat 8,421,142 12,607,820 4,186,678 50 Bharuch 8,500,445 12,607,820 4,107,375 48 Vadodara 15,703,560 20,607,820 4,904,259 31 Anand/Nadiad 9,936,931 15,880,069 5,943,138 60 Ahmedabad 9,718,792 14,483,408 4,764,616 49 Table 14 Daily accessibility indicator, Mumbai-Ahmedabad HSR

Daily accessibility indicator 80000000

60000000

40000000

20000000 limit)

0 Number People of (in travel time

Scenarios Without HSR Scenarios With HSR

Figure 31 Change in daily accessibility indicator, Mumbai-Ahmedabad HSR

Figure 32 Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario without HSR)

The percentage of rise in the accessible population in the major cities is showing less rise in comparing with the intermediate cities. This is because of the large population concentration in the cities with already developed accessible transportation network. In the pilot project, Mumbai and Ahmedabad is showing this trend and with a rise of less than 40 % rise in the number of accessible populations by the new line. On the other hand, the intermediate cities such as Vapi, Bilimora, Surat, Bharuch shows potential rise of more than 3 times ie, the number of people can reach these cities to carry out their purposes and return in the same day is increased from half million to more than 3 million as a reason of the project. The result also should interpret with the fact that these intermediate cities comes under the 2 hours travelling limit of both Mumbai and Ahmedabad.

Figure 33 - Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario with HSR)

In summary, the daily accessibility indicators forecast the economic boost in the cities like Boisar, Billimore and Surat than Mumbai and Ahmedabad through introduction of the new line. As it is already stated, this indicator provides an idea about the numbers possible business contacts and market potentials like tourism, it is evident that the new high-speed rail line will boost the regional economic growth and balance the regional accessibility.

6.4.5 Economic Accessibility The correlation of economic indicator and accessibility change is already discussed in the previous chapters. It is important to understand the influence of economic indicator in accessibility improvement. So, the influence of economic indicator is analyzed in two methods. One is cross country study. In cross country analysis, it accounts the financial status of the users and their willingness to pay in different countries already implemented and data available. GDP per capita of these countries compared with India’s GDP per capita. And unit fare of each country is compared for the year 2014 (as the data availability limited to the project announced in 2014) and for a projected price of the year of opening. Secondly, fare level of other modes, compare air fare and rail fare with HSR fare.

Cross Country fare Comparison : Figure 34 shows the fare for High Speed Railway for 500km in INR by country. As shown in the figure, the fare for the case of 1.5 times as much as the fare for railway in 1A class in India is nearly equal to the fare in China.

Figure 34 - Cross country comparison, Mumbai-Ahmedabad HSR

The amount that an individual is willing to sacrifice to procure the transportation service, highly depends on the income level of passengers. Following figure shows the GDP per capita as of 2012 in USD at current price. The GDP (nominal) per capita in India is approximately USD,500 in 2012. Comparing the countries which have the HSR, the

GDP per capita in India as of 2012 is low. For instance, the GDP per capita in France is 28 times of the GDP per capita in India but the unit price is only four times higher. Even if it is assumed that the GDP will increase at 5 to 7 percent, the GDP per capita in India in 2023, the year of opening HSR, is USD 4,5801. Considering the fact, it is assumed that the travelers in India regard the cost as important more than travel time comparing with the developed countries.

60,000 46,01146,707 39,16141,22341,86643,615 40,000 28,67033,115 20,33622,589 14,302 20,000 6,07110,527 1,501 4,508 GDP GDP percapita 0

Countries

Figure 35 - Cross country comparison (source: data elaboration from JICA Report)

As shown in Figure 35, the unit fare is mostly high in the country with high GDP per capita. As GDP per capita indicates the financial performance of the country and thereby the capability to afford the service. Thus, if India aims for the service level of China or Russia for the time being, it is recommended that the unit fare level for HSR should be range of 0.08 – 0.14 USD (Rs. 4.72 – 8.85) per kilometer, same as China or Russia as of 2012.

Fare Level for Other Transportation Modes

Comparing the service level of HSR with other transport modes, four alternatives fare for HSR is accounted in this study, namely 1) average fare of 2AC class and 3AC class 2) same fare level as 1AC class of existing railway, 3) 1.5 times of 1AC class fare, and 4) 2.0 times of 1AC class fare.

FARE COMPARISON By mode

Air

Bus (A/C)

Rail (1AC)

RAil (3AC)

Rail (SL)

India (Rail 1A*2.0 Case)

India (Rail 1A*1.5 Case)

India (Rail 1A*1.0 Case)

India (Rail Avg. 2A&3A Case)

0 500 1000 1500 2000 2500 3000 3500 Fare for 500 km (INR)

Figure 36 - Fare comparison by mode (source: data elaboration from JICA Report)

The above chart shows the comparison of fare with other modes. It is clearly evident that the HSR mode is far cheaper than the air fare and comparatively higher than rail fare. When we add the comfort, time and safety HSR gains more edges than other modes. Even though HSR is costly compared to bus and low-class fare of rail, it still holds as a factor to cause a major mode shift to a certain category of people. Those categories of people who currently affords the higher class of conventional rail and a major share of air transport in the region. Thus, the fare level directly indicates the affordability and thereby improving the accessibility such category of the Mumbai – Ahmedabad region.

Chapter 7

Lessons learned from a comparative analysis

7.1 Summary of the pilot study.

In this pilot study, a set of identified indicators have been used to analyze the regional accessibility from Mumbai-Ahmedabad HS rail project. This specific project is adequate to the definition of HS rail transport system in its technical and operational features, and thereby initiates the benchmarking exercise.

Four indicators identified from international experiences are used in this study, such as Location indicator, Economic potential, Daily accessibility indicator and Economic indicator. Except economic indicator, other three indicators give direct measure of accessibility improvements, as in listed in Table . Alternately, economic indicator provides a comparative analysis with competent modes and international scenarios. Each indicator is evaluated separately on chapter 6.4.

Indicator Improvements Absolute % Location indicator 151 minutes 65 % Economic potential 8096 EP value 45 % Daily accessibility indicator 5713832 inhabitants 52 % Table 11 – summary of the pilot study, Mumbai-Ahmedabad HSR

The highest average improvement in accessibility for the total group of the urban agglomeration in study area is recorded for location indicator. Correspondingly, both economic potential and daily accessibility indicators show improvement in accessibility. The economic advantages with competent modes of transport are evident and well- illustrated through economic accessibility indicator. It is evident that the effects of the new line on accessibility will not be limited to the major metropolitan regions such as Mumbai and Ahmedabad, but also in other areas of the regions like Virar, Surat and Vadodara, through which the HSR passes. On the other hand, the accessibility impact of the new HSR line will have an asymmetrical nature, since the large metropolitan cities in the both ends of the line with higher weight of agglomeration than the other cities in the study area.

In summary, the identified indicators explicitly state the accessibility improvement achieved. Although, the study has limitations on an in-depth research of the transport situation in pilot cities, this simple exercise has already asserted the effectiveness of selected indicators. In addition, while evaluating, an indicator should not be analysed in isolation. Understanding the interaction between the indicators will provide a more meaningful and complete picture of the transport systems under study. The study also demonstrated that it is difficult to obtain consistent data from all participants but with the use of IT enabled tools and GIS tools facilitate this issue up to certain level.

7.2 Comparative analysis with Madrid-Barcelona HSR ex-ante/ex-post evidences.

Comparison to the similar experience provides better understanding of regional accessibility improvement through HSR. Here, Madrid-Barcelona HSR evidence can be analyzed in comparing to the case study. The ex-ante study already explained in section 4.1 uses the similar indicators of Mumbai-Ahmedabad case study. Besides, Madrid- Barcelona HSR allows the possibility of ex-post analysis and data availability for duration of 10 years instead of other relatively new HSR networks

An ex-ante analysis outlined in the section 4.1 explicitly states the accessibility improvement with other modes. As the ex-ante term means, which gives an expected value before the event that is before the HSR replaces the traffic in the region.

The ex-ante analysis result of Madrid-Barcelona HSR is much less than the Mumbai-Ahmedabad case study. This difference can be seen in every indicator under study. The maximum improvement shown for weighted average travel is 22% in Madrid- Barcelona HSR at Zaragoza, which is less than the average value of weighted average travel time (69%) on Indian HSR. Similarly, the economic potential indicator also shows a rise of 45% average value, while Zaragoza is 37% and Barcelona has only 16%. This difference is evident in daily accessibility indicator also, though the travel time limit and regional population are different. When, Mumbai-Ahmedabad HSR shows a rise of 5 million inhabitancies in ridership whereas, the Spain case study shows a rise of 1 million (1.64%) in daily accessibility indicator.

Observing an ex-post evidence of Madrid-Barcelona HSR along with the comparison of ex-ante studies of both projects gives better understanding of future regional accessibility improvements by Mumbai-Ahmedabad HSR. The ex-post analysis of Madrid-Barcelona HSR carried out between 2000 and 2010 by using the same indicators such as weighted average travel time, Economic potential and daily accessibility indicators.

On ex-post analysis improvement in weighted average travel time is 28% is higher than the ex-ante study conducted. But no large difference is evident. Similarly, ex-ante and ex-post values of Economic potentials of Madrid-Barcelona HSR are 45% and 47% respectively. As expected, the ex-post result is higher, but no marginal difference can be

84 seen. Meanwhile, the daily accessibility indicator is showing difference of 1 million to 1.5 million between ex-post and ex-ante scenarios.

By summing up, all the indicators calculate in ex-ante and ex-post studies shows better accessibility improvements with no marginal difference in values. It should be noted that the ex-post evidences are higher that the calculated ex-ante values. Thus, similar improvement can be expected to the Mumbai-Ahmedabad HSR and this ex-post evidence support the exercise conducted.

7.3 Recommendations for adopting the selected indicators

The identification and implementation of accessibility indicators in the pilot study also put forwards some suggestions in adopting the indicators. The prime notion is about understanding the accessibility change. Though the indicators show accessibility improvement in the calculation, the result is inconsistent without understanding of which indicator used. Because, as mentioned earlier, indicators behave differently based on their conceptualization. So, the study recommends intercepting the indicators as the proposed set not in isolation.

Further, regarding the data used. Apart from the transport network data, information about the population, GDP and other attractiveness of destination centers are used. This case study recommended that the selection of such parameters (e.g. Mj -in weighted average travel time) should be based on data availability and reliability. This study included population indices because of the reliability of National Census data for the case study. Academic researches or basic level previously studies can be used with online GIS tools like NASA Cedac earth data or similar platform. For further researches demanding a more detailed level of calculation only recommends expensive GIS surveys

Modifications to adapt to regional socio-economic scenarios are also considered. The travel time limit used for calculating the daily accessibility indicators is based on the regional peculiarities such as willingness to travel. In pilot study, this limit is set to higher than European limit by considering the Asian countries such as China with similar backgrounds. In preference, the study recommends a separate detailed surveying before fixing such variables considering the depth researches and affordability.

Chapter 8

Conclusions and Recommendations

This thesis work has carried out an analysis on regional accessibility improvement related to the project development of Mumbai- Ahmedabad HSR. This project is the first HSR experience in India. Prior to exploring the main subject, an overview of international HSR systems has been provided along with a critical description of the concept of accessibility.

Subsequently, a methodology for analyzing the regional accessibility of the case study has been developed. As the motive of this paper stressed, this research intended to identify and critically discuss a set of accessibility indicators followed by analyzing the best practice from international experience. The selected indicators are weighted average travel time (location indicator), economic potential, daily accessibility indicator and economic indicator. As the study focus on regional accessibility improvement the accessibility evaluation also proceeds with detailing of socio-economic backgrounds of each city in the study area.

Considering the conclusion on the analysis the regional accessibility improvement is explicit. Simultaneously, the inference on each indicator is distinct as the four indicators offer complementary information about accessibility, since they respond to different conceptualization. The magnitude and distributions of regional accessibility improvements are stated and compared for the selected accessibility indicators. The results vary from indicators to indicators. Concentrated effects on economic potential indicators and daily accessibility indicators, whereas dispersed effects on location indicator and economic indicator aim attention at user’s affordability of the infrastructure.

In summary, the selection of indicators must caution because different conclusions could be achieved according to geographical scale and accessibility indicator selected. The study indicates definite improvement in regional accessibility with certain disparities. The analysis also justifies the selection of indicators by addressing both economic oriented and infrastructure-oriented growth between the scenarios with or without HSR. This analysis method and selected set of indicators are not restricted to HSR, but focus was kept on HSR infrastructure.

8.1 Future research developments

The increasing focus by governments and international development institutions in infrastructure-based investment requires initiatives targeting the accessibility improvement. The benchmarking concept studied under this research could be a useful tool to support this drive for results. The global reach of international financial institutions allows effective dissemination of knowledge and would suggest that such a benchmarking initiative should be initiated as part of their development work.

It is therefore recommended that a gradual full-scale development/ implementation of a simple benchmarking initiative for urban transport in transition and developing countries be implemented. This implementation will typically involve initiatives such as refining the definition of the core indicators to take account of the complexity of HS rail transport; collecting the relevant data for targeted implementation; and Establishing a cooperative mechanism for continuous data collection.

Transport system is changing its phase in fast pace and concurrently the information technology. Thus, linking the IT enabled tools to different process of benchmarking and its implementation can play major role the future work. The role or scope of technologies can be foreseen as developing a web-based data sharing and dissemination platform that includes data analysis; the scope of GIS based online tools to collect trip data such as travel time and destination choices; possibility of real time data set available for the self-driving automated cars and its data accuracy and the possible advancement of transport system analysis software like ArcGIS and other transport modelling software’s.

List of Acronyms

ACT Australian Capital Territory

AECOM AECOM Technology Cooperation

ANOVA Analysis of Variance

ATC Automatic Train Control

AV Alta Velocita

AVE The Alta Velocidad Española

BRT Bus rapid transit

CBD Central Business District

EEH Eastern Express Highway

EMU Electric multiple unit

ERTMS European Rail Traffic Management System

ETCS European Train Control System

ETR Elettro Treno Rapido

GACL Gujarat Alkalies and Chemicals Limited

GDP Gross Domestic Product

GIS Geographic Information System

HSL High-Speed Line

HSR High-Speed Railways

INR Indian rupee

IPCL Indian Petrochemicals Corporation Limited

JICA Japan International Cooperation Agency

KNSO Korea National Statistical Office

KTX Korea Train express

LZB Linienzugbeeinflussung (cab signalling and train protection system)

MOR Ministry of Railways

NASA National Aeronautics and Space Administration

NSW New South Wales

NTV Nuovo Trasporto Viaggiatori

QLD Queens lands

RENFE Spanish National Rail Network

SNCF Société Nationale des Chemins de Fer français (French National Railway)

TGV Train à Grande Vitesse

UIC International Union of Railways

USD United States Dollar

VIC Victoria, Australia

VVVF variable-voltage/variable-frequency

List of figures Figure 1- HSR network of Japan (source: Japan Stations website) ------14 Figure 2 - Japan HSR performance ------15 Figure 3 - Italy HSR map ------16 Figure 4 - Major freccia High-speed line map ------18 Figure 5 - France HSR network ------19 Figure 6 - Germany HSR map (source: Transport Journal) ------20 Figure 7 - Spain Rail Network map ------23 Figure 8 - China HSR map ------24 Figure 9 - The European high-speed network in the study area: scenario 2005. ------32 Figure 10 - Weighted average travel time change in the study area, Spain ------33 Figure 11 - Study area map, China ------36 Figure 12 - Seoul case study area ------39 Figure 13 - Test result, Seoul case study ------41 Figure 14 - Accessibility change plotted on study area ------42 Figure 15 - Proposed Australian HSR layout ------44 Figure 16 - Mumbai-Ahmedabad HSR map ------53 Figure 17 - Population density in the project affected area ------54 Figure 18 - Mumbai Road map ------56 Figure 19 - Railway network map of Mumbai ------57 Figure 20 – Mumbai socio-economic and transport scenarios ------58 Figure 21 - Transport network of Surat ------59 Figure 22 - Vadodara rail network ------60 Figure 23 - Mumbai socio-economic and transport scenarios ------60 Figure 24 - Vadodara socio-economic facts ------61 Figure 25 - Ahmedabad socio-economic facts ------63 Figure 26 - Mumbai-Ahmedabad HSR alignment ------65 Figure 27 - Absolute change in Weighted average travel time, Mumbai-Ahmedabad HSR ------72 Figure 28 - Change in Economic potential value, Mumbai-Ahmedabad HSR ------73 Figure 29 - Heat map showing Average Economical potential along the HS Rail line ------74 Figure 30 - Heat map showing Average Economic potential along the HS Rail line (scenario with HSR) -- 75 Figure 31 - Change in daily accessibility indicator, Mumbai-Ahmedabad HSR ------76 Figure 32 - Heat map showing Daily Accessibility Indicator along the HS Rail line ------77 Figure 33 - Heat map showing Daily Accessibility Indicator along the HS Rail line (scenario with HSR) --- 78 Figure 34 - Cross country comparison, Mumbai-Ahmedabad HSR ------79 Figure 35 - Cross country comparison (source: data elaboration from JICA Report) ------80 Figure 36 - Fare comparison by mode (source: data elaboration from JICA Report) ------81

List of tables

Table 1 Japan HSR lines ...... 15 Table 2 - German HSR lines ...... 21 Table 3 Spain HSR lines ...... 22 Table 5 China HSR lines ...... 25 Table 6 China HSR ridership data ...... 26 Table 7 Change in travel time (source: Gutierrez 2001) ...... 33 Table 8 Key findings, Seoul case study ...... 41 Table 9 Socio economic facts, Mumbai ...... 55 Table 10 Project overview, Mumbai-Ahmedabad HSR ...... 67 Table 11 List of stations, Mumbai-Ahmedabad HSR ...... 69 Table 12 Stop pattern, Mumbai-Ahmedabad HSR ...... 70 Table 13 Location indicator, Mumbai-Ahmedabad HSR ...... 71 Table 14 Economic potential, Mumbai-Ahmedabad HSR ...... 73 Table 15 Daily accessibility indicator, Mumbai-Ahmedabad HSR ...... 76

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