Summer Undergraduate Research Experience (SURE)
Projects 2025
UMTRI Project #1: Adaptive Safety Designs for Injury Prevention: Human Modeling and Simulations
Faculty Mentor: Jingwen Hu, jwhu@umich.edu
Prerequisites:
- Proficiency in Matlab or other programing tools
- Interested in machine-learning, statistical modeling, and/or injury biomechanics research
- Demonstrated ability in 3D human geometry model and/or FE model development and application is a plus
Project Description: Unintentional injuries, such as those occurred in motor vehicle crashes, falls, and sports are a major public health problem worldwide. Finite element (FE) human models have the potential to better estimate tissue-level injury responses than any other existing biomechanical tools. However, current FE human models were primarily developed and validated for midsize men, and yet significant morphological and biomechanical variations exist in human anatomy. The goals of this study are to develop parametric human geometry and FE models accounting for the geometric variations in the population, and to conduct a feasibility study using population-based simulations to evaluate the influence of human morphological variation on human impact responses in motor-vehicle crashes and sport-related head impacts. Specifically, in this study, students will use medical image analysis and statistical/machine-learning methods to quantify the geometric variance of the skeleton among the population; use mesh morphing methods to rapidly morph a baseline human FE model to a large number of human models with a wide range of size and shape for both males and females; conduct impact simulations with those models; and use machine-learning models to build surrogate models for injury assessment toward adaptive safety designs.
Research Mode: In Lab, Online or Hybrid
UMTRI Project #2: Driver State Monitoring for Automated Vehicles
Faculty Mentor: Monica L.H. Jones, mhaumann@umich.edu
Prerequisites: Motivated students, keen to work both independently and within a group. Some experience with scientific programming languages is required (e.g. Mathematica, MatLab, Python). Familiarity with computer vision programming is desired.
Project Description: With increasing automation (SAE Levels 2 and 3), the role of the driver will transition from Driver Driving (DD) to Driver Not Driving (DND). Freed from completing operational tasks of driving, drivers will have a much larger behavioral repertoire. Driver state monitoring (DSM) systems attempt to predict the driver’s readiness to respond to a takeover request or other emerging need within the situation from information obtained from cameras and other sensors. These systems face several challenges to comprehensively track the continuum of possible driver postures and behaviors. Many research questions persist with respect to the efficacy and effectiveness of DSM systems. The results of this project may identify disallowed states and provide further design guidance for DSMs.
This project explores the characteristics and behaviors associated with non-nominal postures, driver engagement, monitoring, and state levels – under day and night conditions. It also seeks to quantify driver responses to unscheduled automated-to-manual (non-critical) transitions in L3 automated driving conditions. Data were gathered on the American Center for Mobility closed test facility. Continuous measures during in-vehicle exposures include: 2D image and 3D depth data, physiological response, driver performance and behavior data, vehicle data, and available DSM outputs.
Student researchers will also assist with data analysis, develop image processing models &/or computational models that predict driver engagement.
Research Mode: In Lab, Hybrid
UMTRI Project #3: Context and Causation Analysis of Crashes : A Hybrid Method of Natural Language Processing
Faculty Mentor: Shan Bao, shanbao@umich.edu
Prerequisites: Motivated students who are comfortable working with a big group. Having skills with Natural Language Processing is a great plus!!
Project Description: To advance our understanding and develop robust crash scenarios, we propose using Natural Language Processing (NLP) modeling techniques to analyze crashes from various perspectives. Cause and context are crucial for crash analysis and scenario construction, as they provide deeper insights into the circumstances surrounding each incident. By examining the interrelationships among various factors, such as driver behavior, environmental conditions, and road characteristics, we can better identify the underlying causes of crashes and propose effective solutions.
The research team will be working with industry experts directly on this project. Student researchers will assist with data collection, analysis, and result interpretation.
Research Mode: In lab or Hybrid
UMTRI Project #4: Developing Test Procedures to Evaluate Accessibility of Vehicle Controls and Displays
Faculty Mentor: Kathleen D. Klinich, kklinich@umich.edu
Prerequisites: Experience with vehicle HMI, user needs analysis, design of controls. Interest in working with people who have disabilities and improving their in-vehicle experiences. Students with disabilities encouraged to apply!
Project Description: We have a new project where we will be conducting research to develop guidelines for ensuring accessible vehicle interfaces that are inclusive. During the summer of 2025, we will be developing laboratory and dynamic (Mcity) test procedures to assess the usability of vehicle controls and displays by people with different types of disabilities. Student researchers could help test fixture design, pilot laboratory testing, and data analysis.
Research Mode: In lab, hybrid
UMTRI Project #5: Data to Go: Mobile App for Human Centered Transportation Research
Faculty Mentor: Monica L.H. Jones, mhaumann@umich.edu
Prerequisites: Prior experience with Python and/or JavaScript for app development
Project Description: UMTRI researchers often perform studies involving volunteers traveling as passengers in vehicles. For this project, the student researcher will continue to develop and pilot test an app intended to be a customizable, versatile research toolkit that can be used in any transportation research involving the collection of participants’ data in real-world settings. Applications include recording volunteers’ experience during travel, passive (continuous) monitoring of time history and GPS location, and physical response to vehicle acceleration exposure using smartphone’s IMU sensor. The app should be easily reconfigurable to adjust to the needs of different research studies, such as paratransit evaluations, passenger motion sickness, and teenage driver behavior, etc. The app also needs to be accessible, requiring both screen and voice input options.
Research Mode: In Lab, Hybrid
UMTRI Project #6: Mobile AR App Development For 3D Body Shape Modeling
Faculty Mentor: B-K. Daniel Park, keonpark@umich.edu
Prerequisites: (this field is optional)
Proficiency in computer programming languages (e.g., C#, C++, Unity)
Project Description:
This project aims to create a smartphone app that utilizes 3D statistical body shape models. UMTRI has been a global leader in the field of parametric human anatomy modeling. 3D body shape models, developed using data from 3D laser scans and anthropometric measurements of individuals with diverse body characteristics, serve as the foundation of this technology. They enable the rapid generation of subject-specific 3D avatars and provide anthropometric predictions applicable to various domains, including engineering, medicine, and design. To foster knowledge sharing and facilitate potential collaborations, we have been sharing our developed models through the website, HumanShape.org, which has proven to be an excellent platform. This project seeks to enhance user experiences by transferring online models to a smartphone app and delivering more valuable experiences to users. Accomplishing this objective will necessitate utilizing cutting-edge programming techniques such as 3D visualization, mobile app design, and statistical analysis.
Research Mode: In Lab, Remote, Hybrid
UMTRI Project #7: Automated Vehicle Malfunction and Coping Strategies Development Under Complex Urban Environments
Faculty Mentor: Shan Bao, shanbao@umich.edu
Prerequisites: Team players who are motivated in working with other group members. Experience with human factors knowledge and/or HMI design and/or natural language modeling experiences are plus!
Project Description:
Automated systems that control/drive a vehicle or assist a driver may fail/malfunction at any time while driving in traffic and lead to crashes. This project is designed to understand the typical and important failure types and taxonomies for automated vehicle systems under complet urban roads, as well as to develop coping strategies in mitigating hazards of such vehicle failures and supporting safe and efficient responses for drivers from both subject and surrounding vehicles. A hybrid approach is proposed to address the research questions both qualitatively and quantitatively.
The research team will be working with industry experts directly on this project. Students will have hands-on experiences working on scenarios simulation,and AV testing under different conditions.
Research Mode: In-lab (Mcity testing), Online or Hybrid
UMTRI Project #8: Software for Human Centered Design
Faculty Mentor: Matt Reed, mreed@umich.edu
Prerequisites: Prior experience with Python and/or JavaScript for web development
Project Description:
The Biosciences Group has developed a wide range of statistical models of human posture and body shape for use in human-centered design. However, the complexity of these models is such that relatively few people are able to use them. The goal of this project is to make more of these models available online for people around the world to use for human centered design. (As an example, see: http://humanshape.org/). The tools include interactive analysis of standard anthropometry (body dimensions), three-dimensional anthropometry, head and face geometry, and vehicle occupant postures.
The student(s) will work with the faculty to develop and deploy online design tools. Experience with Python is preferred, but we also have opportunities for candidates with strong web development experience using JavaScript.
Research Mode: In-person, Remote, or Hybrid
UMTRI Project #9: Generative AI for 3D Human Postures under Physical Constraints
Faculty Mentor: Wenbo Sun, sunwbgt@umich.edu
Prerequisites:
- Proficiency in Python
- Experience with deep neural networks, especially generative adversarial networks and their variations (such as CGAN, WGAN, etc.)
- Familiar with neural network architecture designs for specific datasets
- Experience with hyper-parameter tuning based on pre-trained models
- Experience with great lake computing
- Experience with transfer learning is desired
Project Description: Generative models have been widely used for image generation and large language models in the computer vision field. Some existing works have been developed for 3D human postures. However, there is often the case that the generated samples do not incorporate physical constraints due to the lack of training samples under such constraints. For example, existing generative models fail to generate postures when a subject is trying to reach an object under an obstacle. In this study, we would like to leverage limited samples to set a physical-knowledge-related regularization on the generative model. The student will explore the feasibility of incorporating the regularization terms into different GAN frameworks to achieve a desired convergence performance. The student is expected to conduct code implementation, model training, and hyper-parameter tuning. It is expected that the research project results in a journal / conference paper on the proposed methodology.
Research Mode: Online or hybrid
UMTRI Project #10: Evaluate Accessibility Features of Ride-share/Transportation Apps
Faculty Mentor: Renée St. Louis, rstloui@umich.edu
Prerequisites: Not required, but experience with vehicle HMI, app design, and user interfaces is helpful. Interest in working with people who have disabilities. Students with disabilities are encouraged to apply.
Project Description: We have a new project where we will be conducting research to develop guidelines for ensuring accessible vehicle interfaces that are inclusive of people with varying abilities. One project task involves a scan of the literature, Apple’s iOS App Store, and Google’s Google Play store to determine what apps are available to book ride-share and paratransit services, and to document the outcomes of evaluations of the apps, if any. The student researcher will review app features to determine how accessible they are for people with vision, hearing, cognitive, or mobility disabilities, identifying positive and negative examples that can be used to develop guidelines for accessible app features.
Research Mode: Hybrid
UMTRI Project #11: Develop Vehicle-Human Machine Interface Simulator
Faculty Mentor: Huizhong Guo
Prerequisites: Experience with programming, app development, and HMI/UX design. Interest in working with people who have disabilities. Students with disabilities encouraged to apply!
Project Description: We have a new project where we will be conducting research to develop guidelines for ensuring accessible vehicle interfaces that are inclusive. To allow evaluation of the usability and accessibility of different vehicle infotainment system interfaces, we aim to develop an infotainment interface simulator that can be deployed on a tablet. This simulator will enable us to replicate and test infotainment systems from different vehicles on-market today, as well as to design a more inclusive version tailor to diverse accessibility needs. Students will lead programming and develop this flexible simulation tool.
Research Mode: Hybrid
UMTRI Project #12: Evaluate Mindfulness Apps for Driving Intervention Potential
Faculty Mentor: Colleen Peterson, cmpete@umich.edu
Prerequisites: Not required, but interest in psychology and human behavior is desired. Students with driving experience are encouraged to apply.
Project Description: We are conducting a study on young driver mindfulness and driving behaviors. We recently gathered data using a national survey to identify relationships between mindfulness training/personality traits and driving behaviors, like distracted driving. Next, we will be evaluating the current landscape of mindfulness training for driving intervention potential. Specifically, the student researcher will do a scan of websites, scholarly literature, Apple’s iOS App Store, and Google’s Google Play, etc., to document what apps or other web-based materials are available and their features, including specifically whether any apps have driving-related programming or target teens/young adults. The student may also explore responses from the survey (e.g., thoughts on training, experiences with distracted driving) to identify components that would be useful in an app. Project findings will help determine the feasibility of using current apps for a young driver intervention or the need to develop new programming.
Research Mode: Remote
UMTRI Project #13: Optimizing Electric Vehicle Charging Infrastructure in Long-Term Parking Facilities
Faculty Mentor: Efe Yarbasi, eyarbasi@umich.edu
Prerequisites: Proficiency in programming languages such as Python or MATLAB, interest in sustainable energy systems, transportation engineering, and data analysis.
Project Description: The transition to electric vehicles (EVs) necessitates the development of efficient and sustainable charging infrastructures, especially in high-traffic areas like airport long-term parking facilities. This project aims to optimize EV charging systems by addressing key challenges such as grid load management, synchronization with flight schedules, vehicle pickup times, and the integration of renewable energy sources. Specific research questions include: How can EV charging schedules be aligned with fluctuating flight schedules to minimize grid stress? What innovative systems can effectively connect multiple vehicles to a single charging hub? What is the potential for integrating renewable energy, such as solar power, within airport settings to support EV charging needs?
As an undergraduate researcher, you will engage in exploratory modeling and analysis to develop and test solutions addressing these challenges. You will contribute to designing algorithms that optimize charging times based on real-time flight and parking data, explore scalable charging hub configurations, and assess the feasibility of renewable energy integration.
Research Mode: Hybrid/Remote