REU
About RIDE
Improving upon transportation systems is of paramount importance because reliable, affordable, and consistent forms of transportation lead to greater employment, higher education, quality health care and food, social and civic engagement, and participation in everyday activities.
The RIDE Research Experience for Undergraduates (REU) Site will provide undergraduate students an immersive and interdisciplinary experience in community engaged research focused on improving the transportation experience for various communities. REU students will participate in research in civil engineering, health policy, industrial engineering, information management, legal studies, psychology, and regional planning.
The RIDE REU will run from June 2 - August 8, 2025.
Students
Weeks
Projects
Faculty and PhD Student Mentors
Program Details
In addition to learning and growing as a researcher, you will also:
Field Trips
Students will visit and learn more about places such as:
Professional Development Seminars
Seminars will include topics such as how to:
Eligibility Details
You must be:
There are no minimum GPA requirements and prior research experience is not required. As long as you have a passion and eagerness for doing research, please apply!
The priority application due date is February 14, 2025.
Summer 2025 Projects
- Teenage Driver Education
-
Teenage drivers are involved in an alarming number of fatal crashes. Though drivers education is required for teens under age 18 in the state of MA, there is mixed evidence as to the effectiveness of drivers’ education courses, especially as it relates to the delivery and format of drivers’ education. It is also unknown whether drivers’ education can be used to train drivers on how to interact with Advanced Driver Assistance Systems (ADAS), e.g., adaptive cruise control. The objective of this research is to better understand the effectiveness of driver education and training as well as how such education and training can improve use and understanding of ADAS.
As a student on the research team, you will develop knowledge and skills in how to recruit participants, run driving simulator studies, and conduct the resulting data analysis. You will be responsible for a number of tasks that include data management (recording, synthesizing, and filing data), logistics (scheduling participants and simulator setup), data collection (surveys, eye tracking, and driving simulator output), and potentially data analysis (statistical analysis). This work by the REU student will contribute to the larger project by assisting in the collection of data on the effectiveness of driver education. Future work can have implications for redesigning and reimagining driver education curriculum. - Number of REU Students: 1
- Mentors: Prof. Shannon Roberts and Intisar Becic
-
Community Partner
Local Driving Schools
- Future of Work in Automated Commercial Motor Vehicles
-
We hope to investigate how automation can be designed to lead to new job opportunities and greater equity within the world of trucking. In comparison to most work in long haul trucking that assume driverless automation, this project centers the driver in the process of imagining the future of work in trucking.
As a student on the research team, you will develop knowledge and skills in how to conduct interviews, Photovoice sessions, and ride alongs. You will be responsible for a number of tasks that include data management (labeling photos and slides; time-keeping), logistics (scheduling meetings; checking off participant forms and to-do items), data collection (note-taking; transcription), and potentially data analysis (statistical analysis; thematic coding). This work by the REU student will contribute to the larger project by assisting in the collection of data on the perspectives of drivers, tech designers, and others on the role of automation in their work. Future work can have implications for gender and race diversity in trucking by investigating how trucking could remain a good job while integrating automation. - Number of REU Students: 1
- Mentors: Prof. Shannon Roberts and Jaji Pamarthi
-
Community Partner
Truck Unions
- Community-Centered Traffic Safety
-
Traffic-related roadway fatalities and injuries are at an all-time high with disproportionate impact across various socio-cultural and economic communities. There is a need for more holistic approaches to traffic safety through community-centered safety programs. This research will examine efficacy of citation fine structures, cultural appropriateness of safety messages, emerging technology-driven solutions, such as smartphone crowdsourcing applications and analysis of design features of transit stops which can provide real-time insight on community-specific safety concerns. Researchers will engage stakeholders (e.g., interviews, surveys and focus groups), analyze both crash, citation, and crowdsourced data, as well as perform site evaluations of crash-prone areas which will provide a comprehensive and multi-faceted set of strategic solutions to traffic safety challenges.
Desired skillset: (1)Exceptional interpersonal communication skills; (2) Self starter/ Motivation to excel the project; (3)Detail oriented; (4) Critical thinking skills and ability to analyze data. - Number of REU Students: 2
- Mentor: Dr. Francis Tainter, Angelina Caggiano, and Tolu Oke
-
Community Partner
TBD
- Adolescent driving and risky decision making/behavior
-
Adolescence is a period of rapid social, emotional, behavioral, cognitive, and neurobiological change and development that includes shifts in riskier decision-making and behavior that are connected to potentially dangerous driving (e.g., speeding, driving under the influence). There remains a need for improving understanding of the risky decision making and behavioral processes underlying dangerous behaviors, in diverse populations, and at different points of development across adolescence. A core set of research questions arise: Do developmental changes in risky decision making and behavior operate in the same way or in distinct ways for females and males, for youth across the socioeconomic spectrum, and for youth who hold distinct racial and ethnic identities?
For this project, students will analyze two existing longitudinal datasets (funded by NIH DA036017; NIH HD054805) that include large, diverse US and international samples of youth from 12-19 years of age; cognitive, behavioral and/or neurobiological measures of risky decision making; and direct measures of driving risks (e.g., a driving simulation “stoplight” task [see figure] and survey items), along with other closely related health risk behaviors (e.g., substance use). Students will learn to apply a variety of data analysis techniques to answer research questions or test competing hypotheses, to draw conclusions with translational significance and broader impacts for diverse populations of youth and communities. Students should have some prior exposure to and understanding of basic probability and statistics (e.g., mean, standard deviation, correlation), and interest in and eagerness to learn new statistical techniques. No prior statistical software experience is required (students will learn this as part of the experience). - Number of REU Students: 2
- Mentor: Prof. Kirby Deater-Deckard and Ziqian Zola Gong
-
Community Partner
TBD
- Exploring Cell Phone Use While Driving and Emerging Technologies for Behavior Mitigation
-
This project aims to address the pressing issue of cell phone use while driving, which contributes significantly to distracted driving crashes and fatalities. Despite various legislative efforts and technological interventions like texting prevention apps (e.g., OnMyWay) and features such as Apple’s "Do Not Disturb" mode, the adoption, user acceptance, and overall effectiveness of these technologies remain unclear. To bridge this gap, the study will use a combination of online surveys and semi-structured interviews to gather insights into driving behaviors, cellphone usage patterns, and factors influencing the use of technology designed to reduce distracted driving.
As an REU student, you will gain hands-on experience in data collection and analysis methods, including managing survey data, conducting interviews, and analyzing both quantitative and qualitative data. You will also assist with participant recruitment and engagement, including setting up interviews with both drivers and technology developers to explore their perspectives on the current and future use of these technologies. This project offers a unique opportunity to explore how technology can be harnessed to improve road safety, and it will contribute to the development of evidence-based interventions and policy recommendations aimed at mitigating distracted driving caused by cell phone use. - Number of REU Students: 1
- Mentor: Dr. Isabelle Wandenkolk
-
Community Partner
TBD
- Sea Rise Mitigation Planning for Lieutenants Island Road, MA
-
Climate change leads to more frequent and severe floods, storm surges, and changes in tidal patterns that disproportionally affect coastal areas. Sea level rise is projected to reach 10-12 inches in the next 30 years threatening the wellbeing of communities, especially those in/close to coastal areas. It is critical to develop climate change mitigation and adaptation strategies and ensure that actions are informed and guided by local knowledge through meaningful community engagement to ensure transportation access and quality of life for all. This project will focus on Lieutenant Island and the road connecting it to the mainland to first assess flood risk and then propose cost-effective mitigation strategies. REU students will assist with various aspects of the project, including: (1) On the ground reconnaissance of existing conditions of the site including ,but not limited to, ground surveys, pictures, resource area determination, flood hazards, etc.; (2) Conduct meaningful community engagement through interviews and focus groups with residents to further understand challenges and allow them to contribute to potential mitigation strategies; (3) Documentation of the transportation resiliency problems from information collected through steps (1) and (2); (4) Identification of mitigation strategy alternatives that consider cost, environmental impact (shellfishing, tidal flow, salt marsh, etc.), constructability and the impacts of construction on the island’s access to the mainland, and anticipated future maintenance; (5) Determination of permit types that would be needed (Local, State and Federal). Expected outcomes include a report summarizing existing conditions and proposed alternatives for sea level rise mitigation and road resilience. - Number of REU Students: 1
- Mentors: Prof. Eleni Christofa, Prof. Chengbo Ai, and Bryan Remache-Patino
-
Community Partner
Town of Wellfleet
- Schematic Bicycle Route Mapping and its Impact on GHG Emissions
-
Schematic maps are linear cartograms that represent networks. By employing spatial distortion, schematic maps convey topological information with clarity and simplicity, in contrast to geographically accurate networks. Over the past several decades, studies have shown that schematic maps can improve spatial learning and navigation in a network and are more efficient for route-finding and navigation tasks in bus and metro networks. Despite all the benefits of schematic maps, they have not been widely researched or adopted for bicycle networks. Bicycle maps present unique challenges associated with representing multiple types of information, including bicycle infrastructure, road, grade, connectivity as well as landmarks. Research questions related to this project include: 1) What are desirable elements and codifiable design rules for a schematic bicycle map? 2) Can a schematic map increase bicycle use? If so, by how much? 3) What is the potential for schematic maps for greenhouse gas emissions reduction?
This project is part of a larger effort to design effective bicycle schematic maps and assess their effectiveness in bicycle mode choice increases and greenhouse gas (GHG) emission reductions. For this project, the REU student will assist with: (1) designing and administering surveys to understand bicyclist needs and usage in the study area; (2) conducting bicycle counts to assess bicycling traffic before and after the introduction of schematic bicycle maps; (3) estimating a bicycle demand model using machine learning methods and the obtained data counts before and after the introduction of the maps; and (4) estimate mode choice shift and associated GHG emissions reduction. The RIDE REU student will collaborate with the faculty advisors and graduate student in this project, as well as a second REU student who will be funded by the CEET REU Site and will be focusing on the optimization methods to design schematic bicycle maps. - Number of REU Students: 1
- Mentor: Prof. Eleni Christofa, Prof. Jimi Oke, and Mohhammed Mohhammed
-
Community Partner
Transportation sustainability and planning officials in Northampton
- Don't overlook the small stuff: Understanding the risk of culvert failure to community resilience
-
Small scale infrastructure such as culverts are understudied and vulnerable to damage during flooding events. The failure of culverts can lead to disconnection and longer commutes. This is especially challenging in rural areas where there is less redundancy in the transportation network. More concerning, vulnerable populations historically experience disproportionate impact. Therefore, it is important to identify culverts which are especially damaging to the system and whose failure could cause disconnection to critical services. This project focuses on identifying network criticality metrics for culverts during flooding events. The work will be computational, and students will gain skills in GIS, Python, and data analysis. - Number of REU Students: 2
- Mentor: Prof. Jessica Boakye, Prof. Egemen Okte, and Amma Agyekum
-
Community Partner
TBD
Application Information
Below are the required components of the application:
Essay
Tips
One of the most frequent pieces of advice for writing an essay is “show don’t tell”, but with personal statements you should show AND tell. The people reading your application will be busy, overwhelmed, and will have 100 other applications to read, so you want to make it easy for them to see what traits make you shine. This means explicitly use those trait words in your text, and back it up with proof. Example-“After a week of my experiment failing, I knew I needed to develop a creative solution. So I drew from my experience with materials research to employ an unusual polymer that fixed the errors I was getting.” or “I independently developed a protocol to collect the data.” The show part is important too. Don’t just say “I am creative and independent” without evidence.
More advice on what to do and what not to doIt is always useful to have at least one other person (ideally a graduate student or professor) read your statement. It can be helpful to get feedback at multiple stages as you write more drafts. While friends and parents may not be as knowledgeable about the exact format for academic personal statements they can still offer great advice on grammar, persuasiveness, clarity, etc.
Resume
Tips
Recommendation Letter
Tips
What is a recommendation letter?A recommendation letter is a letter written by someone who has taught or supervised you in an educational setting. It provides detailed information about your characteristics, accomplishments, experience, and preparedness for entering the RIDE REU program. This is done by describing what you have done in your educational career thus far, as well as describing your potential to succeed.
Who should you choose to write your letters?We highly recommend choosing letter writers who know you well and are able to describe your strengths. Ideally, you want letter writers who are tenured or tenure-track professors who can speak to your academic and/or research abilities. If you conducted research that was mostly overseen by a graduate student or postdoc, you can ask them to provide text/details for a letter to the overseeing professor who will then write your letter of recommendation. Avoid letters from friends or family members.
What should be included in a recommendation letter?The letter should begin by describing the relationship between you and the letter writer. For example, is this person your former professor or someone who supervised you in a research setting? It can be helpful to explain why the letter writer feels qualified to write a letter for the applicant. The middle paragraph(s) should describe examples of your experience, characteristics, and accomplishments that will make you successful in our RIDE REU program. The letter should explain why the applicant is qualified and what makes them likely to be successful. The letter should close with an offer for the writer to answer further questions or provide more information if needed and an affirmation of the writer’s recommendation for you to be in the RIDE REU program.
How do I ask for a recommendation letter?Give your letter writers at least a month to write your letter. When asking for a letter of recommendation, make their lives easier by providing content and direction. What qualities are you trying to highlight in your application? Ask them to speak to those qualities. Also send the professor your resume. They may interact with a lot of students and may not remember exactly what you did or accomplished. Make it easier for them by highlighting any major accomplishments you want them to include. Remember, writing letters of recommendation is part of their job, so don’t feel bad asking for one.
Transcript
Unofficial transcripts are fine. We only want to see what classes you have taken. We ARE NOT focused on your GPA and there is no minimum GPA.
Contact Us
Amherst, MA
Phone: 413-545-2165
Email: scroberts@umass.edu
The priority application due date is February 14, 2025. Recommendation letters are due on March 1, 2025.