The Future of American High-Speed Rail: Analyzing and Discovering the Most Effective High-Speed Rail Development Methods on Promising Rail Corridors in the United States
Advisor: Basel (Andrew) Hamzawsky
The development of high-speed rail (HSR) in the United States has long been hindered by challenges related to market structures, government policies, and environmental factors. This research aims to explore and identify the most effective, sustainable, and equitable high-speed rail development frameworks applicable to promising U.S. corridors. By comparing successful international HSR systems—such as those in Europe, Asia, and Morocco—this study will evaluate how factors like network coverage, environmental impact, safety, and equity can be optimized within the U.S. context. Key questions addressed include determining which market structures best spur HSR development, how to ensure ticket affordability, and how to minimize environmental impacts while maximizing safety and usage.
To assess different international HSR models, a comprehensive rubric will be developed to weigh each market structure's economic, environmental, and political outcome against the current U.S. market's government and topographical conditions. The goal of this research is to provide policymakers with a framework to implement efficient, safe, and equitable high-speed rail projects that reduce the country's reliance on unsustainable road and air travel. This research is particularly relevant given the recent successes of Florida’s Brightline and the growing demand for sustainable short and medium-haul intercity transit. Through this analysis, the study aims to lay the foundation for a modern high-speed rail network that addresses economic and environmental concerns in the U.S. transportation landscape.
Project Blog
Week 0
Hello everyone, my name is Maxim and welcome to my Week 0 Senior Project Blog! I am excited to embark on this personal academic journey while sharing my progress in the field of transportation economics. In this blog, I will be going over the importance of my research topic, introduce my project/project advisors, and mention some things to look forward to in Week 1.
Importance of the Subject/Background Research:
Since the creation of Japan's Shinkansen in 1964, high-speed rail (HSR) has significantly evolved (Cao & Zhu, 2017). From France's TGV to China’s 22,000 km HSR network, countries from across the world have seen the benefits HSR development has had on sustainability, urbanization, and economic growth (Cao & Zhu, 2017). With this technology proliferating throughout the globe, countries are implementing HSR in vastly different market systems (Jiao et al., 2013).
Despite nearly 50 years of international experience, the U.S. faces distinct problems in developing HSR, requiring careful analysis and research to develop satisfactory solutions (Saat & Barkan, 2013). Existing U.S. initiatives involve 64 corridors, covering 15,552 miles of route and reaching 163 of the 250 largest metropolitan areas (Schwieterman & Scheidt, 2007). However, 87% of the identified railroad mileage is operated by freight-oriented railroads, presenting unique technical and operational challenges of either building a new railroad network or creating capacity-limiting agreements with freight train companies (Saat & Barkan, 2013).
Recent trends show a bottom-up approach to projects, with governments prioritizing the improvement of existing corridors for higher-speed services rather than dedicated HSR lines due to the extremely high start-up costs and long-term commitment to building new infrastructure as seen in the California high-speed rail project (Schorung, 2022). This restoration of old rail infrastructure leads to trains running at significantly slower speeds than other high-speed rail projects, with the claimed “high-speed” Acela corridor running on average only 68 miles per hour (Handler, 2014). Congressional initiatives, such as the Passenger Rail Investment and Improvement Act of 2008, aimed to promote HSR development, but implementation challenges persist with no new Acela trackage being built since then (Peterman et al., 2009).
With the Brightline West Palm Beach - Miami high-speed rail segment becoming profitable and its new high-speed rail operations expanding to Orlando, it is evident that there is a demand for high-speed rail in the United States. With HSR’s massive benefits but high capital costs required to make HSR projects work, it is especially crucial for HSR development to be done safely and efficiently. Wanting to identify the most optimal HSR development method, I decided to make my research question be: What is the most effective, sustainable, and equitable approach to high-speed rail development in the United States?
Research Project and Advisors Introduction:
With the assistance of my onsite advisor Mr. Hamzawsky and my offsite advisor at the High Speed Rail research department of the Ukrainian Railways, I will analyze how well the European Union’s, Japan’s, China’s, Morocco’s, South Korea’s, and Saudi Arabia’s high speed rail development method performed in each of these 6 sub-questions:
1: What high-speed rail market structure has been the most effective on a per-kilometer basis in spurring high-speed rail network development/network coverage?
2: What high-speed rail market structure has been the most equitable in providing cheap and accessible tickets in the context of the country's cost of living?
3: What high-speed rail market structure has resulted in the most limited environmental impact?
4: What high-speed rail market structure has resulted in the safest high-speed rail infrastructure?
5: What high-speed rail market structure has the highest utilization rates?
6: What high speed rail market structure has the highest profit margins?
Each of these sub-questions will be evaluated on a rubric scale from 1-10 established by a literature review of what is considered a success and a failure for each sub-question.
After assigning a raw score for each subquestion for each development method, I will then assign a different weight to each sub question based on how much the American government prioritizes a successful outcome in this lens (i.e prioritizing economic efficiency over ticket equity). I will then multiply the weight to the subquestion by the raw score received out of ten, adding up each development method's weighted subscores to determine which development method has the highest total score or most ideal for the United States.
Week 1 Future Plan:
For week 1, I plan to complete the rubric criteria for at least 3 of the subquestions. To achieve this, I aim to create a coding rubric with key numbers/terms to look out for when analyzing the specific development methods. An hypothetical example to illustrate this coding rubric would be that to get a 5 on the economic effectiveness of the development method, the project would have to be between 40-50% over initial budget. If it's less over budget, it gets a higher score. If more over budget, then a lower score. This would remove my personal biases out of the equation, as just qualitative analysis may result in error caused by a lack of research standardization. Overall, I am very excited to start this project and I hope my resulting framework can guide future HSR development in the United States.
Thank you for reading and see you next week!
Sources
Cao, J., & Zhu, P. (2017). High-Speed Rail. Transportation Letters, 9(4), 185–186. https://doi.org/10.1080/19427867.2017.1318472
Handler, M. (2014). Planning for a New Northeast Corridor. http://www.realtransit.org/PlanningForANewNortheastCorridor.pdf
Jiao, J., Harbin, J., & Li, Y. (2013). Fast Tracks: A Comparison of High-Speed Rail in China, Europe and the United States. Journal of Transportation Technologies, 03(02), 57–62. https://doi.org/10.4236/jtts.2013.32a007
Peterman, D.R., Frittelli, J.F., & Mallett, W.J. (2009). High-Speed Rail (HSR) in the United States.
Saat, M.R., & Barkan, C.P. (2013). Investigating Technical Challenges and Research Needs Related to Shared Corridors for High-Speed Passenger and Railroad Freight Operations.
Schorung, M. (2022). A Geographical Contribution on Interurban Passenger Rail Transportation in the United States.
Schwieterman, J.P., & Scheidt, J. (2007). Survey of Current High-Speed Rail Planning Efforts in the United States. Transportation Research Record, 1995, 27 - 34.
Week 1
Week 0 Recap:
Hello everyone and welcome back! Before I dive into my findings, I would like to recap my previous post. In my week 0 post, I outlined the critical importance of studying high-speed rail (HSR) development methods by examining the benefits HSR has brought to countries like Japan, China, and France in terms of sustainability, urbanization, and economic growth. I also delved into the persistent challenges the U.S. faces, including the oligopoly freight railroads have over U.S. rail trackage and the high fixed capital costs required to build new HSR infrastructure. Given these challenges, I believe that my research provides a helpful role in potentially capturing the untapped market for HSR in the U.S., providing an effective top-down blueprint for officials to utilize when building a world class, American HSR network. If you are interested in understanding the topic further, please visit my Week 0 post or click here to see my full project proposal.
Week 1 Results:
This week, I started discussing the key factors for High Speed Rail construction success with my outside advisor Oleg Yakovenko, Director of Strategy and Transformation at JSC Ukrainian Railways. In our conversations, Mr. Yakovenko suggested a very important resource for my research: the International Union of Railways’ High Speed Rail Handbook. This resource stressed the importance of evaluating HSR projects success based on if it lived up to its suggested projections and not how it exactly compared to other countries' methods (especially when it comes to construction costs as geography and labor costs vary significantly from country to country). This made me reevaluate my current criteria for the assessment of a HSR method’s success. Consequently, I decided to revise my 6 initial sub-questions and turn them into the 8 sub-questions displayed below:
Sub-Question 1: What high-speed rail market structure has been the most effective on a per kilometer basis in spurring high-speed rail network development/network coverage?
Sub-Question 2: What high-speed rail market structure has been the most effective in limiting cost overruns?
Sub-Question 3: What high-speed rail market structure has been the most effective in limiting construction time overruns?
Sub-Question 4: What high-speed rail market structure has the highest intercity market share percentage?
Sub-Question 5: What high-speed rail market structure has been the most equitable in providing cheap and accessible tickets in context of the country's cost of living?
Sub-Question 6: What high-speed rail market structure has resulted in the most limited environmental impact?
Sub-Question 7: What high-speed rail market structure has resulted in the safest high-speed rail infrastructure?
Sub-Question 8: What high speed rail market structure has the highest profit margins?
With the addition of 2 additional sub-questions that I will need to answer for, I decided this week to complete the parts of the rubric for the first 4 of the 8 sub-questions, the results which you can access here. When developing this rubric, a great resource that I was able to find was NYU’s Transit Cost Project preliminary data analysis on worldwide HSR development. His data analysis of 75+ different high speed rail routes served as a really great source in developing the method analysis rubric, especially when determining the exact rubric numbers for sub-questions 1, 2, and 3.
Week 2 Future Plan:
For next week, my plans are to complete filling out the last 4 sub-questions in the rubric while also finalizing the list of countries to study. Additionally, I will decide what location to choose for an example implementation of the optimal high speed rail development method in the United States, with me currently deciding between the Chicago/Great Lakes Region and Texas. While the project has definitely been difficult in terms of finding sources in the English language that exactly fit my research needs, this project has definitely been an enjoyable challenge as I try to learn more about an industry I see a potential career in.
Thank you for tuning in and see you guys next week!
Week 2
Week 1 Recap:
Hello everyone and welcome back! Before I dive into my findings, I would like to recap my previous post. Last week, I began discussing the key factors for high-speed rail (HSR) construction success with my outside advisor, Oleg Yakovenko, Director of Strategy and Transformation at Ukrainian Railways. He recommended the International Union of Railways' High Speed Rail Brochure, which emphasized evaluating HSR projects based on whether they meet projected goals, rather than directly comparing them to other countries' methods, especially regarding construction costs. This led me to revise my initial six sub-questions into eight, focusing on various market structures' effectiveness in areas like network development, cost and time overruns, market share, ticket equity, environmental impact, safety, and profit margins. I also worked on completing the rubric for the first four sub-questions, drawing on NYU’s Transit Cost Project's preliminary data analysis, which was particularly helpful in setting rubric metrics for sub-questions 1, 2, and 3.
Week 2:
This week, I continued talking with my outside advisor Mr. Yakovenko, who was able to suggest some great sources for my research including the JR Central (Japan’s) 2020 annual report, Amtrak’s 2023 annual report, and the Asian Development Bank’s Handbook on High Speed Rail and Quality of Life. From the first 2 sources, I was able to develop a rubric for the sub questions assessing the equitability and profitability of HSR. On the other hand, the ADB’s Handbook was able to reduce two sub questions from my research, as the Handbook mentioned that high speed rail safety has been very homogenized/standardized. In fact, HSR across the European Union has been increasingly standardized from local country-specific automatized signal control networks like France’s Transmission Voie Machine (TVM) and Spain’s Anuncio de Señales y Frenado Automático (ASFA) to European Train Control System standards as required by European Union directive 2016/797 (European Union, 2016). Like the ETCS, systems in China, Japan, and Korea have implemented automatic train control (ATC) as safe measures to prevent collisions from driver error, automatically breaking in cases of overspeed or damage detected by the train (Korea uses TVM, while China uses its own ATC system called CTCS which is very similar to ETCS). Overall, most if not all HSR systems use forms of ATC to enhance operational safety, as a result not requiring a safety assessment for every HSR development method. Furthermore, safety assessments are fairly standardized due to the International Rail Union (UIC)’s standardized safety procedure. As a result of the highly standardized nature of high speed rail, I eliminated this research question. Lastly, I eliminated the environmental sub question as there isn’t one standard, country-wide approach to constructing HSR infrastructure. Rather, HSR construction is a more step-by-step individualized approach determined by the route’s geography and topography. As a result, I eliminated this research question, resulting in a finalized list of 6 sub-questions with a developed rubric.
In terms of the HSR development methods studied for my research, I decided to study large, existing HSR networks (over operational 1,000 km) that still have significant construction (over 300 km in construction) with operational capabilities above 150 mph. This led to my finalized list of 8 countries:
China
Spain
France
Germany
Japan
South Korea
Italy
Turkey
I will analyze each country's HSR development method based on how well it succeeded in each of the 6 criteria, with the optimal HSR development method being chosen after being adjusted to the weighted score for each category depending on how much . Using this method, with some local US market revisions, I will produce a proposed high-speed rail project connecting Texas including San Antonio, Austin, Dallas, and Houston. I chose to study Texas due to its mostly flat terrain, current state government surplus, optimal intercity distances, and a surplus of demand . These reasons will be expanded upon in future blogs. But as I will discuss this route selection in my final project/presentation, I decided to save this selection for later. Overall, I am very excited to see what my research results in and I hope that my research can spur the HSR development boom that can improve US city interconnectivity.
Thank you for reading and see you in my next blog post!
Week 3
Hello everyone and welcome back! Before I dive into this week’s progress, I’d like to recap what I worked on last week. Last week, I continued working on completing my research rubric with my outside advisor, Mr. Oleg Yakovenko. With his help, I found several valuable sources to strengthen my research, including JR Central’s 2020 annual report, Amtrak’s 2023 annual report, and the Asian Development Bank’s Handbook on High-Speed Rail and Quality of Life. From these reports, I was able to eliminate the environmental subquestion, as I found that high speed rail environmental impact widely varied based on the topography of the region/project. Furthermore, I was able to eliminate the safety subquestion due to worldwide standardization of ATCS (Automated Train Control Systems) preventing potential safety mishaps by train drivers. Some examples of these systems include the European Train Control System, the Transmission Voie Machine, and the Chinese Train Control System. On some Chinese and Japanese lines, the entire train control system is fully automated, which is known as ATC or Automatic Train Control. This left me with a streamlined list of six core sub-questions, which I would use to analyze eight countries with extensive HSR networks and ongoing expansion: China, Spain, France, Germany, Japan, South Korea, Italy, and Turkey. This international method analysis will contribute to the final proposal of a HSR network connecting San Antonio, Austin, Dallas, and Houston, which will use the optimal international HSR development method as the base of the proposal. I chose Texas for my HSR proposal due to Texas’ flat terrain and the “sweet spot” in terms of distance for HSR competitiveness.
Week 3:
This week, I started analyzing each country’s HSR success on a cost per km basis and year per km basis. I collected this data from the NYU Transit Costs Project’s HSR cost database, allowing me to save a significant amount of time collecting data for these 2 sub questions. Although this database was very large, I did need to do supplemental research to include the full timeline of projects and include projects which the project could not find data on. This was especially the case in China and Germany, where some projects required me to translate my search queries into German and Chinese to find the data I was looking for. Although this was troubling at first, I did end up getting the hang of it as I did it more and more times.
After getting sufficient data to do data analysis, I ended up creating an excel spreadsheet with the data analysis calculations, as well as the countries performance on the established HSR rubric. You can see my progress on the Senior Project Research spreadsheet here.
While conducting my data analysis, I found that the data analysis of the Transit Costs Project had an issue when it came to the average cost per km and years spent per kilometer for each country. Instead of assigning a weight to each project based on how long the project was distance wise, the Transit Costs Project just treated each project equally for each country. This gave shorter HSR projects more weight than they should have, skewing the data typically to produce results that show that the country’s HSR construction method was more expensive per kilometer and longer to build per kilometer than actually. You can see this disparity by looking at the non-adjusted and adjusted per/km calculations for each country. By making this correction, my research had the correct per/km value for cost and time spent building the kilometer statistics. Inputting each country's cost and time per km statistics, I assigned them a grade based on the previously established rubric.
For next week, I will continue answering the 6 sub questions with the goal being to answer 2 sub questions for each country. I intend to do so by reading government reports and updating my senior project excel spreadsheet. Thank you for reading and see you guys next week!
Week 4: Ticket Equity and Route Marketshare
Hello everyone and welcome back! Before diving into this weeks progress, here’s a recap on what I worked on last week:
Last week, I answered the first two research sub-questions pertaining to the construction cost and construction time per kilometer. Using the Transit Costs database as supplementary sources to complete information the project was not able to find, I was able to find how successful each country was at building high speed rail on a cost and time analysis. In terms of adjusted PPP cost per kilometer, the countries building the cheapest high speed rail were found to be Spain and France, with 26.76 million and 25.6 million spent per kilometer respectively. In regards to construction time per km, China is by far the fastest in building high speed rail the fastest, on average spending only 0.01 years per kilometer. In days, this means that China spends only 3.65 days on average to build 1 kilometer of high speed rail. The closest to China was France, which averaged 0.025 years per kilometer or 9.125 days per kilometer.
Week 4:
This week, I continued assessing the 8 countries’ high speed rail development methods by looking at the average price of tickets per kilometer and the average route market share of the constructed high speed rail segments in comparison to air and road travel.
To assess each country’s ticket price equity, I initially used NYU Marron Transportation Institute fellow Aron Levy’s calculations discussing German, Japanese, and French ticket fares per km in comparison to Acela, which I adjusted to 2025 dollars by multiplying it by the inflation percentage. For Korea, Italy, Turkey, China, and Spain, I had to calculate the average fare per km by finding local sources that provided the ticket prices and travel distances and then convert the rate from local currency to dollars using purchasing power parity metrics calculated annually by the World Bank. From these calculations, I found that Spain and Turkey had the most equitable fares. Spain’s average fares per km rate was found to be $0.149 per km, with Turkey performing slightly better with a rate of $0.139 per km. On the other end of the spectrum, Japan and China had the highest fares on a per km basis of $0.266 and $0.30 respectively. The reason for China’s less equitable ticket prices is likely due to the recent struggles in the Chinese real estate market, where many real estate developers defaulted on their loans including the giant Evergrande. Since then, the government corporation Chinese Railways has increased fares to reduce the extremely high debt of $849 billion to ensure the stability of the company among the volatile Chinese construction and real estate market. In the case of Japan, the reason likely stems from the very high construction/maintenance costs of high speed rail in Japan due to the mountainous terrain requiring significant construction of tunnels and bridges as seen in the Transit Cost Project’s higher tunnel and bridge percent calculations for Japan.
To assess each country on the average market share that each new high speed route captured, I used Peter Jorritsma’s method to calculate estimated market share (s) as a function of travel time (t):
s = 1 / (0.031 * 1.016^t + 1)
Using the estimated travel time by dividing the distance by the max speed, we can find the max market share that this route could have. After calculating the market share for each route, I averaged the percent market share and assigned a score based on the established rubric. From my data, I found that South Korea and Spain had the highest average market share percentages, averaging 86.92% and 88.16% maximum market share respectively. On the other hand, the worst maximum market share was China, as the government's priority of full country connectivity led to the construction of routes outside the distance sweetspot of maximum competitiveness (usually between 160-800 km or 100-500 miles). So although China has some of the highest average high speed rail speeds out of any country, routes like Lanzhou - Urumqi (1,776 km or 1,100 mi) significantly brought the average market share down.
Week 5 Goal:
For next week, I will answer the last 2 sub questions of the assessment rubric by reading government reports and updating my senior project spreadsheet which you can see my real time progress and calculations here. Thank you for reading and see you guys next week!
Week 5: Profitability and Cost Overruns
Hello everyone and welcome back! Before diving into this weeks progress, here’s a recap on what I worked on last week:
Last week, I addressed two research questions, examining ticket price fairness and market share potential for high-speed rail systems. For the fare analysis, I referenced NYU Marron researcher Aron Levy's work on German, Japanese, and French ticket prices per kilometer, updating the figures to 2025 dollars. For other countries like Korea, Italy, Turkey, China, and Spain, I calculated fares per kilometer using local ticket prices and distances, converting currencies through World Bank purchasing power parity data. Spain and Turkey offered the most affordable fares at $0.149 and $0.139 per kilometer respectively, while Japan ($0.266/km) and China ($0.30/km) had the highest prices.
To assess market competitiveness, I used Peter Jorritsma's market share formula (s = 1 divided by (0.031 multiplied by 1.016 to the power of t, plus 1)) where t represents travel time. Spain and South Korea showed the strongest potential market capture at 88.16% and 86.92% respectively, while China's performance in this category suffered because many of its routes, like the 1,776 km Lanzhou-Urumqi line, are too long to compete effectively with air travel.
Week 5:
This week, I attempted to answer the last 2 questions of my assessment rubric which were percent cost overrun and high speed rail profitability. To answer the percent project cost overrun, I used local or international auditory watchdog sources to find the average percent cost overrun. After conducting my calculations, I found that the best countries at preventing high speed rail project cost overruns were France and China, averaging a cost overrun of only 14.78% and 14.83% respectively. On the other hand, Turkey, South Korea, and Italy really struggled with cost overruns, averaging 266%, 217%, and 196% respectively. I believe the stark differences in the cost overruns stem from a couple factors: mainly economies of scale, inefficient allocation of funding, and inadequate budget assessments. I believe the first and the third factors stem from the fact that the countries have smaller networks in comparison to Spain, China, and France, leading to less consistent budget forecasting and construction methods due to the countries’ engineers/economists not having as much previous experience building/forecasting high speed rail.
For the high speed rail profitability question, I found that across all eight countries, high speed rail itself was found to be unprofitable. Furthermore, governments weren’t very transparent with the exact losses, so I had to eliminate this research question from my research due to a lack of exact results. While there are some profitable routes like Tokyo-Osaka, Beijing-Shanghai, and Paris-Lyon, there are much less of these routes in comparison to the country's nationwide networks. Instead of conducting a quantitative analysis, I qualitatively looked at how other countries made up the losses by taking advantage of how new transit induces residential development aka transit-based-development. This is especially present in Japan, where private JR companies supplement their revenue by developing profitable real estate around the train stations they operate. In fact, currently 15% of JR east revenue comes from real estate surrounding train stations and is where JR East is heavily investing, targeting a 50-50 split of JR East’s revenue between real estate and transportation after 2027. Given the success of the real estate business that these privatized JR companies have had, it’s evident that a similar system should be implemented for the developers to make a significant profit by building the proposed Texas high speed rail project to entice capital investment.
Week 6 Goal:
For next week, I will identify category weighting based on American high speed rail priorities by reading government proposals, government regulations, and recent Federal Railways Administration/Texas DOT press releases/mandates. These institutional priorities will be implemented into my senior project spreadsheet, which you can see my real time progress here. Thank you for reading and see you guys next week!
Week 6: American High Speed Rail Priorities and Method Results
Hello everyone and welcome back! Before diving into this weeks progress, here’s a recap on what I worked on last week:
Last week, I focused on answering the final two questions of my assessment rubric—percent cost overrun and high-speed rail profitability. To analyze cost overruns, I used data from local and international watchdog sources and calculated that France and China had the lowest average overruns at 14.78% and 14.83%, respectively. In contrast, Turkey, South Korea, and Italy faced much higher overruns at 266%, 217%, and 196%, which I attributed to limited economies of scale, inefficient funding allocation, and less accurate budget assessments due to smaller and less experienced networks. For the profitability question, I discovered that high-speed rail systems were generally unprofitable across all eight countries, and due to a lack of government transparency about financial losses, I had to drop the question from my quantitative analysis. Instead, I shifted to a qualitative approach and studied how countries like Japan offset losses through transit-oriented development. I found that JR East currently earns 15% of its revenue from real estate and plans to increase that to a 50-50 split with transportation by 2027. This highlighted the potential for similar models to be applied to my final project (the Texas high-speed rail proposal) to attract further private investment into the project.
Week 6:
With this refresher, I would like to move into my research and the rationale for the weighting of each category for my rubric. Assigning different weights to each category is crucial to achieve a more accurate grade of each development method, as countries’ development methods are established with factors of success that are likely different to the United States’ . A great example of a famous method that is praised as a success but would not work in the United States is China. With China prioritizing city connectivity over route financial viability, its fast but more expensive construction (adjusted to PPP) would not fit the United States’ goal of financially sustainable HSR infrastructure. The weight of each category was established on a scale from 1-10, with 1 being the least important and 10 being the most important. This category weight is then multiplied by the raw grade, giving the weighted grade for that category. With the explanation of the rubric weight complete, let’s move into the justification for each category's weight.
The construction cost of the infrastructure is the biggest roadblock and concern that the United States is facing in regards to the viability of government-run high speed rail in America. This is especially the case with California High Speed Rail, which has tainted public belief in the future of American high speed rail with its ballooning costs of over $106 billion (3 times the original cost estimate) and constant delays in the construction of even the first phase of the project.
Furthermore, the U.S. Transportation Secretary Sean P. Duffy's recent announcement regarding the termination of a $60 million grant to plan the Texas high speed rail route further indicates that the private sector will be the main driver in the construction of this infrastructure. To quote Mr. Duffy: “If the private sector believes this project is feasible, they should carry the pre-construction work forward, rather than relying on Amtrak and the American taxpayer to bail them out.” This message is further highlighted by the success of the private venture Brightline, which has now runs semi-high speed trains (maximum of 125 mph or 200 kmh) from Miami to Orlando while costing a comparatively low 5 billion for its extension from West Palm Beach to Orlando. It is evident that if the Texas high speed rail project is built, the private sector will spur the majority of its development.
Given the private sector’s expected high involvement in the project, the main priority of the project will be to keep construction costs as low as possible to limit the amount of debt the project will incur in the construction of the project. Given this cost prioritization, I gave the category weight for Construction Cost and Percent Cost Overrun Weight a 10. Adding onto the priorities of the private sector, return on investment and the time frame of the return of investment are also prioritized. Consequently, the category weight for market share capture and construction time were given a 9 and 8, respectively. Given the private sector's priorities of generating a profit as quickly as possible, ticket equity will be deprioritized. Instead, the sector would maximize revenue by targeting higher paying business consumers and filling the remaining seats as much as possible through advanced price discrimination methods seen currently in the aviation market. As a result, the Ticket Price Equity weight was only given a 4.
After tallying the total grades for each category, Spain ended up being the most ideal high speed rail development method. For a by category breakdown and to see the country by country calculations for each, please visit my spreadsheet here.
Country | Final Method Grade
Spain | 323
France | 310
China | 251
Germany | 227
Japan | 78
Turkey | 45
Italy | 10
South Korea | 7
Week 7 Goal:
Next week, I will be planning out my initial route and station locations, utilizing the Spanish method for high speed rail planning including station location, depot location, and track layout. Thank you for reading and see you guys next week!
Week 7: From Station Location to Construction Cost Reduction: Key Strengths of Spanish HSR Design
Hello everyone and welcome back! Here’s a quick recap of what I worked on last week:
I finalized the weighting system for my assessment rubric to evaluate global high-speed rail (HSR) models based on U.S. priorities. Since development strategies vary by country, I assigned weights (on a 1–10 scale) to reflect factors most critical to the U.S.—with construction cost and percent cost overrun ranked highest (10). This was due to the massive budget issues plaguing projects like California High Speed Rail, which has exceeded $106 billion.
Given recent federal decisions—like the withdrawal of a $60 million grant for Texas HSR—it's clear that future U.S. HSR development will rely heavily on private investment. As a result, I also gave high weights to market share capture (9) and construction time (8), since fast returns are essential for private backers. Ticket price equity, on the other hand, was given a lower weight (4), as private operators are likely to use revenue-maximizing strategies.
Using this rubric, Spain ranked as the most suitable model for U.S. adoption. Using Spain’s framework for HSR development, I will develop a plan for high speed rail in Texas, which I will explain further below.
Week 7 Progress:
In the last week, I worked on researching Spain’s approach to route planning, using their insights to develop a potential Texas High Speed rail network.
Spanish Approach to Route Planning:
The Spanish approach to route planning can be described in three key ideas: minimize construction cost, prioritize central urban integration of HSR stations to maximize multimodal connections, and build competitive routes with high potential route market capitalization.
Minimize Construction Cost:
When it comes to HSR construction, Spanish HSR routes often take the path of least resistance. Whether it's by utilising existing rail connections to get into cities or building slower, cheaper HSR where more expensive, higher speed HSR is not needed to be competitive. A great example of this is the Atlantic Axis route, where trains between A Coruna and Vigo only run at 200-250 km/hour due to their close proximity of only 155 km. Applying this framework, Texas High Speed rail can minimize high speed rail construction cost through a couple steps:
When entering cities, purchase and modernize existing freight rail connections that run into the middle of the city to reduce construction costs.
Alternative: Build high speed rail next to highways where land is cheap and there is space to build elevated rail
This model of construction is used in the Brightline West project, where high speed rail will run along Interstate 15 between Las Vegas and Rancho Cucamonga.
Build high speed stations in places where existing Amtrak stations exist in downtowns to limit real estate purchasing costs.
Alternative: Build it where currently parking garages exist, as the land value of the real estate on average is much cheaper than commercial real estate in downtowns and increase the walkability of the downtown area, attracting further development in the surrounding area.
For shorter distance spur branches, build lower speed rail to connect to the main network where higher speed is not needed to be competitive (i.e. in areas where airport access is limited or nonexistent).
Build on as flat of a terrain as possible, limiting the amount of tunnels. This is reflected in the Transit Costs Project’s database, where it shows that Spain’s tunneling and elevated percentages are some of the lowest out of the high speed rail countries, with only 13.85% of the routes on average being in tunnels and only 3.85% of the routes being elevated.
Central Urban Integration:
One of the key factors of Spanish high speed rail success is the placement of high speed rail stations in the densest areas of the respective cities. Stations like Barcelona-Sants and Madrid Atocha are located in the center of the city, which allows local public transportation systems to develop rail, metro, and bus connections around the station. This makes High Speed Rail a more competitive option to consumers, as the station’s centralized location and convenience of travel makes consumers prefer the longer train ride because the consumers make up for this time in the saved commute to and from the airport, which is typically found on the outskirts of the city like in the case of Madrid Barajas and Barcelona El Prat Airport.
Furthermore, Spain, following Switzerland’s and Netherlands’ example, has now started building high speed rail connections to the airport. By 2026, Madrid Barajas will have a high speed rail stop. This is to further diminish the uncompetitive and environmentally unsustainable short-haul domestic flights, as most of the remaining aviation market share high speed rail has not captured in Spain is due to long distance travelers buying flights to smaller cities in Spain with a layover in a larger city like Madrid (ex: New York - Madrid - Sevilla). While this may seem damaging to airlines as they lose route market share, this loss is offset by more long distance connecting flights being sold through mutualistic code sharing partnerships with high speed rail companies. Because rail schedules are more frequent and rail has quicker turnaround times, airlines can code share these train routes through a partnership with HSR company, providing passengers more flexibility when it comes to layovers, more comfortable travel arrangements through, and lower operational costs as they still have the same network coverage while operating less flights.
A great example of this is the Swiss Air Partnership between the Swiss Railways (SBB) and Swiss Airlines. After an initial five year partnership between 2019 and 2024, the companies decided to prolong their partnership “indefinitely”, signifying the tremendous success that this partnership has been for both companies in terms of revenue generation. I had the privilege of utilizing this service over winter break from New York to Basel through an air to rail connection in Zurich, a trip me and my family would have likely taken with another airline if it was not for the convenient layover in Zurich due to the higher frequency rail schedule.
Applying this framework, Texas High Speed rail maximize multimodal connectivity through 2 measures:
Build stations in the middle of cities, allowing the local governments to develop local transportation hubs, arenas, and convention centers around the station. In cases where the existing Amtrak station is centrally located, that land will be redeveloped to
Build high speed rail connections with airports that have a large volume of international and intercontinental flights to foster air-HSR partnerships to expand intercity transportation accessibility.
Build Competitive Routes with High Potential Route Market Capitalization:
Another key factor of success in Spanish High Speed Rail is their route selection process, using the least amount of kilometers to reach the most number of people. This is very evident in the route map of the Madrid - Barcelona route, where planners did not build the most direct route in favor of connecting cities like Zaragoza (population of 683,000) and Tarragona (population of 100,000) to the high speed rail network.
Applying this framework, Texas High Speed can increase potential route market capitalization through 2 measures:
Do not always build the most direct route, sometimes extend the length of track to reach large population metro areas in between the start and end destination cities.
If the cities are too far away from the main line, build lower speed commuter rail to connect the center of the displaced city to the main line.
Week 8 Goal: For Week 8, I plan to show a finished Texas high speed rail plan implementing all of the suggested solutions that came from analyzing the Spanish HSR network. Thank you for reading and see you guys next week!
Week 8: Connecting College Students and Airports - Texas HSR Network Overview
Hello everyone and welcome back! Here’s a quick recap of what I worked on last week:
Last week I researched the key factors of success that allowed Spanish HSR to grow quickly and thrive. And beyond simply reach a large level of economies of scale, my research determined that the three key factors of Spanish HSR location were construction cost minimizations, the maximization of multimodal connections through the central urban/airport integration of HSR stations, and integration of dense population centers into HSR routes to increase potential market reach.
Week 8 Progress:
Using the factors identified in the previous week as the framework for the Texas HSR route design, here is my finalized route design (the blog posted my image too blurry, so please click here to see my design). To explain this design, I will explain my station selections in a macro overview of route design and its relation to the Spanish HSR design principles, followed by a more in depth overview of exact station location and depot locations in the city/surrounding areas.
Build Competitive Routes with High Potential Route Market Capitalization:
Building on the key points of Spanish HSR design of:
Do not always build the most direct route, add detours to reach large population metro areas in between the start and end destination cities.
If the cities are too far away from the main line, build lower speed commuter rail to connect the center of the displaced city to the main line.
My design integrates this design philosophy by slightly diverging each of the 3 main routes to maximize potential population reach. Through this design alteration, I was able to include the cities of Waco (pop. 304,865), Killeen–Temple (pop. 501,333), Bryan/College Station (pop. 281,445), and Austin (pop. 2,473,275). As a result, the proposed Texas HSR network will reach the top 4 largest metro areas in Texas (Dallas, Houston, San Antonio, and Austin), the 7th largest metro area in Texas (Killeen-Temple), the 12th largest metro area in Texas (Waco), and the 14th largest metro area in Texas (College Station - Bryan) according to Census data. Through this network design, over 21.5 million people or approximately 68% of the Texas population, will be reached by HSR. While the amount of annual passengers will likely not reach the total population of the area in the first 5 years, it is a good predictor of the potential ceiling that the project has. According to the Senior Vice President of Amtrak High Speed Rail Andy Byford, just the route between Dallas and Houston had over 12 million total trips in 2022, with this number likely to increase as the addition of HSR and its convenience induces additional demand. Utilizing the Spanish network design philosophy, this design maximizes network reach, giving HSR the best chance at succeeding in Texas and the United States.
Furthermore, the close distances of the major cities of Dallas, Houston, Austin, and San Antonio allow for the routes to be highly competitive versus air and road travel. Using Peter Joritsma’s method of estimated HSR market share from my research in week 4, the average potential market share of these large intercity routes based on the estimated travel time is 88.32%. HSR is 2 hours or less in nearly every route, priming HSR to be in a position to completely dominate the market according to transportation consulting firm ALG.
Route | Potential Average Speed (in mph) | Potential Route Length (in miles) | Route estimated travel time (in mins) | Estimated Market Share
Austin to San Antonio | 138 | 75.3 | 32.73913043 | 95.05%
Dallas to Austin | 138 | 186.42 | 81.05217391 | 89.91%
Dallas to Houston | 138 | 285 | 123.9130435 | 81.86%
Dallas to San Antonio | 138 | 261.72 | 113.7913043 | 84.12%
Houston to Austin | 138 | 151.7 | 65.95652174 | 91.88%
Houston to San Antonio | 138 | 227 | 98.69565217 | 87.07%
Average | 88.32%
Minimize Construction Cost - Macro Overview:
Before getting into the points discussed in my analysis of Spanish HSR last week, I would like to discuss an obvious design idea that was overlooked in last week's blog post - limiting network track length. As seen in my map design, my design tried to have each part of the track be used for multiple lines (ex:track coming from Dallas being used for both the Dallas-Houston and Dallas-San Antonio routes), reducing the total network length by approximately 35% if the routes were connected directly, correlating to an approximate 35% in cost savings using this design. While routes will now be longer than if done directly point to point, the route distance will be at most a 22% detour on the Houston-Austin-San Antonio Route. With the Spanish HSR average commercial speed being 222 km/hr(138 mi/hr), this 80km (50 mile) detour will only result in 20 minutes added onto the route. As a result, the total estimated travel time of the trip will only be 99 minutes, allowing the route to still be very competitive against air and road travel. Now with that out of the way, let's move onto the the key points of Spanish HSR design mentioned last week:
For shorter distance spur branches, build lower speed rail to connect to the main network where higher speed is not needed to be competitive (i.e. in areas where airport access is limited or nonexistent).
Build on as flat of a terrain as possible, limiting the amount of tunnels. This is reflected in the Transit Costs Project’s database, where it shows that Spain’s tunneling and elevated percentages are some of the lowest out of the high speed rail countries, with only 13.85% of the routes on average being in tunnels and only 3.85% of the routes being elevated.
The application of design principle number three was used to create a spur branch from Temple (on the main line) to Kileen. To highlight it on the map, the route is denoted by the red line. Given the short distance of 25 miles between the two cities while being off the mainline of Dallas - San Antonio, it is not necessary to build high speed rail on this route. By modernizing the existing rail connection between the two cities, HSR developers can save millions of dollars by not building significant excess capacity.
When it comes to the topography of the proposed route, the entire HSR network will go through the flatlands section of Texas. The route avoids the mountains found west of Austin, Killeen–Temple, and San Antonio, with the elevation of the entire route ranging from approximately 20 to 200 meters above sea level per the topographic map database. For comparison, the first Spanish high speed rail line, from Madrid to Seville, had an elevation range of 0 to 800 m. As a result, the percentage of trackage that is needed to be elevated or go through tunnels will likely be less than through alternative Texas HSR routes, saving developers millions of dollars.
Central Urban Integration:
Building on the key points of the central urban integration of Spanish HSR:
Build stations in the middle of cities, allowing the local governments to develop local transportation hubs, arenas, and convention centers around the station. In cases where the existing Amtrak station is centrally located, that station will be redeveloped and modernized to typical high speed rail standards.
Build high speed rail connections with airports that have a large volume of international and intercontinental flights to foster air-HSR partnerships to expand intercity transportation accessibility.
The high speed rail design integrates the first point by modernizing and expanding existing Amtrak stations or building new stations where parking garages were. This is to limit land acquisition costs. The station locations are also placed strategically, typically on the outskirts of the central business district to induce development and allow the high speed rail developer to make money off the rise in land value rail transportation creates.
In terms of airport integration, the high speed rail network connects Texas residents to the two largest airports in terms of long-haul and international flights: Dallas Fort Worth and George Bush Intercontinental Airport. By connecting to these airports, airlines can partner with competing high speed rail providers to sell. This is especially relevant to residents of smaller cities on the lines like College Station, Waco, and Killeen-Temple, who now can reach significantly more American, European, and Asian destinations with just one convenient transfer from the train to the airport.
One last form of urban integration that I considered was station proximity to college campuses. While not mentioned as a key success point of Spanish design, college students are one of the largest car-free demographics in the United States. As a result, high HSR usage by college students is a great indicator of short-term and long-term project success. As a result, the universities of Baylor (located in Waco, 20,000 students), UT Austin (53,000 students), and Texas A&M (located in College Station, 79,000 students) are all a walkable distance from the HSR stations.
Minimize Construction Cost - Micro Overview:
To achieve central urban integration while limiting costs, my design integrates the Spanish cost-saving approaches of:
Purchasing and modernizing existing rail connections that run into the middle of the city.
Building high speed rail next to highways that enter the city
Building high speed stations in places where existing Amtrak stations exist in downtowns to limit real estate purchasing costs.
Building new stations where currently parking garages/empty lots exist
In every city destination, these design principles were utilized to create cheap stations with high connectivity.
Since Spanish high speed rail typically utilizes dedicated HSR-speed level trackage, the existing tracks need to be evaluated on the feasibility of modernizing for HSR use. When considering if existing trackage can be utilized, the rail connections were evaluated on three factors:
How straight is the rail trackage, what speeds is the track design potentially capable of.
Are there alternative rail routes that can take on the train demand lost by dedicating this route solely to high speed rail.
What percentage of the track has road-level crossings, how feasible is it to create over/underpasses to minimize road-level crossings.
After considering these three factors, here’s how the design utilizes existing rail connections in major metropolitan cities:
To connect the Dallas central station to the DFW airport, Arlington, and the Fort Worth stations, my design suggested modernizing the existing Trinity Railways Express route.
To connect the Houston Airport to the Houston central station, the design utilizes the existing Union Pacific(UP) Lufkin Subdivision tracks.
To enter San Antonio and reach the San Antonio central station, UP Del Rio tracks will be modernized.
To enter and exit Temple, the UP Waco track will be modernized.
Between Temple and Kileen, the BNSF Lampasas subdivision will be shared with freight rail as a spur route from the main HSR network.
To enter and exit College Station, the UP Navasota branch will be used.
Where existing rail connections did not work to enter the center of cities, the alternative of building high speed rail above or alongside interstates was suggested. This is the case in Austin and Waco, where the high speed rail runs along the I-35 into and out of the cities. To see the layout of station locations and exact proposed routes to enter the city, please click here.
Given that these routes had well defined right of ways, the freight rail companies, BNSF and Union Pacific, would likely be uninterested in selling their freight rail trackage at market value. As a result, government intervention through eminent domain would likely be needed to complete this project. This incentivizes the HSR developers to work with the government through a Public-Private partnership, making the HSR network become more equitable and accessible for Texas residents through government mandated student or affordable pricing programs.
This is all I had for this week. For next week, I plan to discuss the economic model aspect of the network, diving deeper into rail stock, rail gauge, maintenance facilities, and how the economic model will induce high speed rail competition. Thank you for reading my blog and see you next week!
Week 9: Texas HSR Economic Model
Hello everyone and welcome back! Here’s a quick recap of what I worked on last week:
Last week, I developed the finalized plan for the layout of the Texas High Speed rail utilizing Spanish high speed rail design principles. This included station location, urban high rail routing, and potential station connectivity. The finalized network provides high speed rail access to over 21 million Texans, connecting 68% of the Texas population with just 885 kilometers (or 550 miles) of track.
Week 9 Progress:
This week, I developed the economic model to make Texas HSR financially sustainable while limiting government subsidies. After analyzing the Spanish post HSR market liberalisation in accordance with EU standards, the economic model proposed for the HSR system is a two-tier public-private partnership, which splits the HSR network into the high speed rail developer and the operators. I call this model the airport model, as like how airports are separate from airlines, this model separates the infrastructure operators/managers from the actual train operators. This model has several pros, namely:
Monopoly prevention. Since the developer does not operate trains, multiple HSR operators can enter the market. This newfound competition results in a higher quantity of seats on the route supplied, resulting in cheaper fares and higher market share capture vs road and air as seen in ALG’s analysis on the impacts of Spanish HSR liberalization.
Specialization: By separating the infrastructure developers from the HSR operators, it allows both tiers to focus more narrowly on generating profit through real estate development or HSR train operation . Additionally, the barrier to entry for HSR operators is lowered significantly, as new players only need to raise money for HSR stock/labor and not carry the burden of paying back the high fixed cost of the infrastructure.
While the system has worked well in Europe and Spain, one of the biggest drawbacks to this system is that the infrastructure development requires significant government funding to bridge its budget deficit. This makes the original model not entirely applicable to the U.S. ever since U.S. Transportation Secretary Sean P. Duffy's announcement of the termination of Amtrak’s $60 million grant to plan the Texas high speed rail route.The announcement signified that the private sector will be the main driver in the construction of this infrastructure, making long-term profit generation a vital factor for the viability of this project. As a result, it is crucial for the infrastructure developer, who is limited in the amount they can charge operators to use the HSR infrastructure due to the Public-Private-Partnership deal with the government, to find alternative and lucrative means of turning a profit.
Inspired by the case studies of JR Railways in Japan and the Hong Kong MTR, my model allows the high speed rail developers to make money through real estate surrounding the train stations. Since land values jump with the construction of public transportation, the infrastructure developer can make money by owning and profiting off the jump of the land values next to the high speed rail station. This model has allowed JR Central and MTR to be some of the only public transportation systems to be profitable, with 40% of MTR’s total revenue in 2016 stemming from real estate investments. By collaborating with the government to obtain land surrounding the station through eminent domain, the mutualistic relationship between the infrastructure developer and government leads to the creation of more well developed cities that preserve the social benefits and the equitability of the HSR project. Additionally, the infrastructure developer can create partnerships with local real estate developers that allow the company to recoup their losses without risking significant additional funding to generate returns. To see a diagram of how all the stakeholders in the economic model come together and interact, please click here.
Next Week:
For next week, I plan to discuss the track width, suggested train stock, potential market players, and potential depot locations. Thank you for reading and see you next time!
Week 10: Final Touches
Hello everyone and welcome back! Here’s a quick recap of what I worked on last week:
Last week, I explained the economic model behind the project, explaining the dual tier Public-Private partnership where the infrastructure developer supplements his income by developing real estate surrounding the HSR stations. I also explained the origins of this model from Japan and Hong Kong, where the Hong Kong MTR gets 40% of its income from real estate development.
Week 10 Progress:
This week, I put the final touches on my project by sorting out potential depot locations, identifying the optimal track gauge and train stock, and discussing potential market player operators.
Depot Locations:
When it comes to the placement of depot locations, the Spanish approach to HSR depots is by usually placing them on the outskirts of the cities that are the end destinations of the routes. This placement of the depot is strategic, as the locations have lower real estate acquisition costs while still having room for growth for the depot.
Additionally, the Spanish have maintenance centers also located between the end destinations, providing additional service capacity to trains if needed. As a result, my suggested design includes three peripheral depots - Houston, San Antonio, and Waco-Dallas - as well as a central depot in Temple. In San Antonio, the design takes advantage of a freight yard that will be unused due to the repurposing of the current UP Del Rio freight track to enter San Antonio. As a result, significant real estate acquisition is not needed since the freight yard is included in the purchase of the UP Del Rio trackage. To see the map of the potential depots and stations, click here.
Track Gauge and High Speed Train Stock:
In Spain, the HSR runs on Iberian Gauge (1,668 mm), the most common railroad gauge on the Iberian peninsula. This allows for easy lower speed - high speed rail interoperability and allows the Infrastructure developer/government to save money by not changing existing rail to a different gauge. Since lower speed rail in the United States runs on the standard gauge of 1,435 mm, the suggested Texas HSR gauge is 1,435 mm.
Given that Standard Gauge trains with HSR capabilities are already manufactured in the United States, the Acela Avline (Amtrak) and Brightline Siemens American Pioneer 220s are the suggested trains to be used in HSR.
Potential Market Players:
While likely new operators will be formed to compete in the HSR market, there are two current operators that can be competitive in the market:
Brightline: With significant experience operating private higher-speed rail in the United States, Brightline can pose to be a very strong competitor in the Texas HSR network. With existing trains that can reach 125 mph(200 kmh) and Siemens American Pioneer trains on order that can reach 200 mph(321 kmh), Brightline’s existing HSR infrastructure and experiences primes the company to be a very competitive market player in the earliest years of the Texas HSR operation.
Amtrak: Since Amtrak Acela trains have the capacity to operate high speed rail at 150 mph (241 kmh) and Texas HSR is a very competitive route in terms of potential market share generation percentage, Amtrak has the ability to generate profits that can offset its net loss train routes elsewhere.
With these three last factors now being accounted for, I can officially say that my project is complete. I have had a lot of fun completing this project, and I want to thank my in school advisor Mr. Hamzawsky and my out of school advisor Mr. Yakovenko for providing me with the tools and support to make this project a success! I knew coming in that my project was very ambitious, given that I had to limit my research to the first five weeks and the actual proposal to the last five weeks, but I am very happy that I was able to achieve the ambitious goals I set out for myself. Please look out for my final concluding post next week and thank you for reading!
Week 12: Concluding Blog
Hello everyone and welcome back to my concluding Senior Project blog post!
This week, I finished my deliverable - a research paper that discussed how the best international HSR development method was identified as well as the entire Texas HSR proposal. At 8,500 words long or 47 pages in length, it is definitely a long read. But I am very proud of all of the work I put into creating such a comprehensive document. To see the final paper, please click here.
This week I also presented my findings in the Senior Project Presentation event. I enjoyed sharing my findings with members of the Basis community and even the owner of the event space, sharing my passion for public transportation and rail transport. I felt my presentation was certainly a success, as I was able to succinctly put out my findings in a well executed and engaging presentation (at least this was the feedback I got from the audience). If you were able to attend, I want to thank you for listening and engaging with me through very thoughtful questions. I always enjoy any time I get to talk about transportation, so I want to thank Basis for giving me a platform to share my works to a significant portion of students and faculty. If you would like to see or revisit my final presentation, please click here.
Overall, I am happy to say that my project was a success, achieving all the goals I had set out for myself at the start of this research process. This project has certainly been a challenge, especially in the time management department. But I have been able to learn a lot and really dive deep into the intricacies of HSR. I want to thank my advisors Mr. Hamzawsky and Mr. Yakovenko, as well as my parents, for supporting me on this incredible journey. I have had a lot of fun, and I am excited to continue pursuing my passion for transportation studying Civil Engineering and Management Science and Engineering (MS&E) at Stanford.
Thank you again and till next time,
Maxim