Abroad in Israel: HOT lane networks and exploring Israel

April 9th, 2018Undergraduate Student Life

By Amy Vogel ‘20 I can't believe I've already been at the Technion for five weeks; the time is flying by! I've just returned from a week of vacation for Passover, but the weeks leading up to the holiday were like (literally) running a marathon! Me after running the "Technion Marathon," a 5K race that is basically like running a marathon because the university is built on the top of a mountain. Here at the Technion, I've been enjoying the more "Course 6" side of Course 1-ing. For Omar's PhD, he is researching the possibilities of dynamic HOT lane networks. HOT (high occupancy/toll) lanes are much like HOV (high occupancy vehicle) lanes, except that they involve a toll. In the special case of dynamic tolls, there would be a sign on the highway before the HOT lane starts, marking the estimated travel time on the HOT lane, as well as the price, which would change depending on the estimated travel time. Due to the laws of supply and demand, the system is a lot more complex than it may sound. For example, you could imagine that if a 20-mile HOT lane on I-95 was advertised with a 15-minute travel time, and cost just $1, it would become flooded with commuters, thus doubling or tripling the travel time, and consequently angering thousands of Bostonian drivers. My point is, dynamic HOT networks present an interesting challenge, and I am helping Omar with the code needed to investigate this topic. So, after a [...]

By Amy Vogel ‘20

I can’t believe I’ve already been at the Technion for five weeks; the time is flying by! I’ve just returned from a week of vacation for Passover, but the weeks leading up to the holiday were like (literally) running a marathon!

Me after running the “Technion Marathon,” a 5K race that is basically like running a marathon because the university is built on the top of a mountain.

Here at the Technion, I’ve been enjoying the more “Course 6” side of Course 1-ing. For Omar’s PhD, he is researching the possibilities of dynamic HOT lane networks. HOT (high occupancy/toll) lanes are much like HOV (high occupancy vehicle) lanes, except that they involve a toll. In the special case of dynamic tolls, there would be a sign on the highway before the HOT lane starts, marking the estimated travel time on the HOT lane, as well as the price, which would change depending on the estimated travel time.

Due to the laws of supply and demand, the system is a lot more complex than it may sound. For example, you could imagine that if a 20-mile HOT lane on I-95 was advertised with a 15-minute travel time, and cost just $1, it would become flooded with commuters, thus doubling or tripling the travel time, and consequently angering thousands of Bostonian drivers. My point is, dynamic HOT networks present an interesting challenge, and I am helping Omar with the code needed to investigate this topic.

So, after a week of debugging my code, at 7pm right before Passover vacation started, my code finally ran correctly!!! This week, we will start by refining the input into the code; we are using public data on the Ayalon highway, a major highway in Israel that runs through the greater Tel Aviv area.

Although there is probably no better feeling than when code runs without an error message, going outside of the Technion gates can be fun, too. A few weeks ago, my roommate and I took a trip to the beach in Haifa — although it’s not quite summer yet in Israel, it’s certainly warm enough for an afternoon beach excursion.

Sunset on the beach in Haifa

I also went right before Passover on a trip for Technion International students to see an English stand-up comedy show in Tel Aviv, which was a ton of fun. And later that week, some other students in my lab and I went into downtown Haifa and ate some amazing ice cream creations.

Some amazing and beautiful ice cream concoctions from Glidium

As they say in Hebrew, shavua tov (“good week”)!

Amy Vogel ’20 is studying abroad in Israel at Technion this semester, where she is working alongside Tomer Toledo, PhD ’03.

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So, What Exactly is Machine Learning?: Inside a CEE Capstone Project

April 4th, 2018Undergraduate Student Life

By Jill Dressler ’18 and Rachel Galowich ’18 Machine learning is a 21st century buzzword, but what does it really mean? When we sat down in Professor Saurabh Amin’s office to first begin discussing our senior capstone project, machine learning sounded like a concept from another planet, a field that only computer scientists could enter. Yet, here we are, about two months deep into a fascinating capstone project that applies machine learning theory to civil engineering applications in transportation. And we are thriving. As Course 1 undergraduates, we have to complete a senior capstone in order to graduate. It serves as an opportunity to get a taste of a semester long research project, perhaps to inspire some of us to on to get our PhDs or write a thesis for a master’s degree. I’m Jill Dressler, and I’m writing this blog post with my colleague and best friend, Rachel Galowich. We are both doing our capstone project under the advisement and support of Professor Saraubh Amin and Doctoral Candidate Jeffrey Liu. We hope that this blog post and the few that follow it can give you a bit of an inside look into our project. Here is a little bit of background information: The Massachusetts Department of Transportation (MassDOT) has several hundred cameras scattered across Massachusetts roadways. They oversee traffic flow, infrastructure quality, and traveler safety across thousands of miles of streets and highways...and they are recording it all! The hundreds of cameras stream hundreds of thousands of images to [...]

By Jill Dressler ’18 and Rachel Galowich ’18

Machine learning is a 21st century buzzword, but what does it really mean? When we sat down in Professor Saurabh Amin’s office to first begin discussing our senior capstone project, machine learning sounded like a concept from another planet, a field that only computer scientists could enter. Yet, here we are, about two months deep into a fascinating capstone project that applies machine learning theory to civil engineering applications in transportation. And we are thriving.

As Course 1 undergraduates, we have to complete a senior capstone in order to graduate. It serves as an opportunity to get a taste of a semester long research project, perhaps to inspire some of us to on to get our PhDs or write a thesis for a master’s degree. I’m Jill Dressler, and I’m writing this blog post with my colleague and best friend, Rachel Galowich. We are both doing our capstone project under the advisement and support of Professor Saraubh Amin and Doctoral Candidate Jeffrey Liu.

We hope that this blog post and the few that follow it can give you a bit of an inside look into our project. Here is a little bit of background information:

The Massachusetts Department of Transportation (MassDOT) has several hundred cameras scattered across Massachusetts roadways. They oversee traffic flow, infrastructure quality, and traveler safety across thousands of miles of streets and highways…and they are recording it all! The hundreds of cameras stream hundreds of thousands of images to the Highway Operations Center every day. Dedicated MassDOT employees monitor the roadways and respond to events as needed. The current system faces several technical limitations, including delayed response time to weather events, heavy traffic, and vehicular accidents.

So basically, we have all of these images being processed into a database, but we have not even broken the surface of their potential. Google has a software that can place labels on these images (think: “asphalt,” “snow,” “bridge,” etc.). From here, Professor Amin has invited Rachel and I on board to help use the labeled images to develop classification and prediction methods for future data. This may sound convoluted, so let us try to simplify it.

There are two scenarios that may make this a bit clearer. First, imagine that a police dashcam takes a picture on a highway and we need some way to localize the image. Can we use the existing image database to organize the data in such a way that we can quickly assess where the image was taken based on label similarities? Second, imagine it’s a Tuesday at 5:33PM and you are sitting in dead-stop traffic on the freeway. Was there any way to predict this seven-minute span would have significantly worse traffic flow than the previous seven minutes? These are simplifications of the questions we hope to answer.

Stay tuned for our next blog where we will go into a little bit more detail about how we are employing machine learning techniques (but don’t worry, we won’t go all super-nerd on you!). Thanks for reading!

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Professor Lydia Bourouiba featured in “Storied Women of MIT” series

March 29th, 20182018 News in Brief

Assistant Professor Lydia Bourouiba was featured in the “Storied Women of MIT” video series for Women's History Month. The video highlights Bourouiba’s contributions to the field of fluid mechanics as they are applied to disease transmission. The series was produced by MIT Video Productions. Watch the video here.

Assistant Professor Lydia Bourouiba was featured in the “Storied Women of MIT” video series for Women’s History Month. The video highlights Bourouiba’s contributions to the field of fluid mechanics as they are applied to disease transmission. The series was produced by MIT Video Productions. Watch the video here.

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Abroad in Israel: Settling in and learning the ropes

March 16th, 2018Undergraduate Student Life

By Amy Vogel ’20 I have been in Israel now for about 3 weeks, and loving every minute of it. After I got off the plane, I got to spend a few nice days with my family in Tel Aviv and Jerusalem before heading up to Haifa. We celebrated the Jewish holiday of Purim together, which was a lot of fun! Two weeks ago on Sunday, I moved into my dorm at the Technion ("the MIT of Israel"). I live in an apartment-style dorm shared with four other international research students, and they are great roommates! My airplane right before landing in Tel Aviv The professor I am working for here is Tomer Toledo, PhD ’03 in Civil and Environmental Engineering/ Transportation Research Institute at MIT. My first official day of work was the Monday after I moved in, and one of Tomer's students, Omar, welcomed me and showed me around. For his PhD, Omar is working on designing efficient toll lane systems with dynamic pricing, and this is also the project I'll be working on while I'm here. Last week was mostly my orientation to the school and to the research; I learned how to use a transportation-modeling software called TransModeler. I also learned about the Cell Transmission Model (CTM), which can be used for lots of different things, but in this case we are applying it to modeling traffic flow. This week I got to work on building a MATLAB program that would read in data from TransModeler [...]

By Amy Vogel ’20

I have been in Israel now for about 3 weeks, and loving every minute of it. After I got off the plane, I got to spend a few nice days with my family in Tel Aviv and Jerusalem before heading up to Haifa. We celebrated the Jewish holiday of Purim together, which was a lot of fun! Two weeks ago on Sunday, I moved into my dorm at the Technion (“the MIT of Israel”). I live in an apartment-style dorm shared with four other international research students, and they are great roommates!

My airplane right before landing in Tel Aviv

The professor I am working for here is Tomer Toledo, PhD ’03 in Civil and Environmental Engineering/ Transportation Research Institute at MIT. My first official day of work was the Monday after I moved in, and one of Tomer’s students, Omar, welcomed me and showed me around. For his PhD, Omar is working on designing efficient toll lane systems with dynamic pricing, and this is also the project I’ll be working on while I’m here.

Last week was mostly my orientation to the school and to the research; I learned how to use a transportation-modeling software called TransModeler. I also learned about the Cell Transmission Model (CTM), which can be used for lots of different things, but in this case we are applying it to modeling traffic flow.

This week I got to work on building a MATLAB program that would read in data from TransModeler and run macroscopic simulations. In other words, while TransModeler will show each individual car driving along the highway, we are interested in modeling the overall flow of cars on the highway, and how that changes with time.

Running a practice simulation on TransModeler (look familiar?)

Since I started work, I have met a handful of the other graduate students working on related projects, many of whom are also Tomer’s students. And I’ve had some fun, too!

Last weekend I went into Haifa’s German Colony with my roommate, and we walked by the Bahai Gardens and then ate at a delicious restaurant called Fattoush. This week, I tried out an acting/improv class for people trying to learn Hebrew, and I had a lot of fun with that!

View of Bahai Gardens

Delicious food at Fattoush

I haven’t decided yet how I’ll spend this weekend, but I am looking forward to the many weeks and weekends to come, and hope to have as many interesting experiences as I can squeeze into three months.

Amy Vogel ’20 is studying abroad in Israel at Technion this semester, where she is working alongside Tomer Toledo, PhD ’03.

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Research from Professor David Simchi-Levi shows that traditional sampling method can be used to address inventory constraints

March 15th, 20182018 News in Brief

Research from Professor David Simchi-Levi shows that the Thompson sampling method, developed in the 1930s, can be combined with a linear algorithm to address revenue management problems. Simchi-Levi demonstrates that the Thompson sampling can be naturally combined with a classical linear program formulation to include inventory constraints, and can be applied in airline, internet advertising and online retail industries. The paper was accepted for publication in Operations Research. Read more on MIT News.

Research from Professor David Simchi-Levi shows that the Thompson sampling method, developed in the 1930s, can be combined with a linear algorithm to address revenue management problems. Simchi-Levi demonstrates that the Thompson sampling can be naturally combined with a classical linear program formulation to include inventory constraints, and can be applied in airline, internet advertising and online retail industries. The paper was accepted for publication in Operations Research. Read more on MIT News.

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Professor Penny Chisholm featured in “Storied Women of MIT” series

March 13th, 20182018 News in Brief

Institute Professor Penny Chisholm was featured in the “Storied Women of MIT” video series for Women's History Month. Chisholm is highlighted for her role in discovering Prochlorococcus, the smallest, most abundant photosynthetic organism. The series was produced by MIT Video Productions. Watch the video here.

Institute Professor Penny Chisholm was featured in the “Storied Women of MIT” video series for Women’s History Month. Chisholm is highlighted for her role in discovering Prochlorococcus, the smallest, most abundant photosynthetic organism. The series was produced by MIT Video Productions. Watch the video here.

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