The Bureau of Policy and Planning’s Research Unit works collaboratively with different offices within the Department to bring to fruition research ideas and needs. The 2017 and 2018 Research Work Program incorporated projects in the areas of engineering; policy and planning; safety; pavements; environmental; and, data and information technology. We look forward to continuing to expand our research topics during the 2019 and 2020 Work Program.
Introduction of New Employees to Research
New minds, new innovative ideas!
Research thrives on creative thinking and innovation. So what better way to seek fresh and new ideas, than to tap into the minds of those newcomers joining the CTDOT. Research staff has recognized this and so has taken advantage of reaching out to the new employees during their orientation - to apprise them of opportunities available to them and to contribute to research by sharing their ideas. Managers and supervisory staff have been reminded to continue to support their employees and encourage them to use the Research Section as a resource. Visit the research webpage for more information about research activities.
Have a Research Idea?
Submit your innovative ideas or research needs, throughout the year, using the Research Project Suggestion Form. As aptly stated by Albert Szent-Gyorgyi - “Research is to see what everybody else has seen, and to think what nobody else thought.”
Take advantage of the AASHTO TC3 trainings!
TC3 on-line training courses are available in the categories of construction, materials, maintenance, traffic and safety, pavement preservation and employee development. CTDOT personnel can access the trainings free of charge 24/7, start and stop sessions to fit their schedules, as well as print personalized certificates. The registration process is easy to follow. For more information, contact the Training Center.
AASHTO-RAC High Value Research Sweet Sixteen Award
The UConn safety analysis study titled, "Reduction in Nonfatal-Injury Motor Vehicle Crashes with Anti-icing Technology," was awarded the 2017 AASHTO-Research Advisory Council (RAC) High Value Research Sweet Sixteen award. The data for this study was mined from the collaborative research project between CTDOT and Connecticut Academy of Science and Engineering. The report is published in the Transportation Research Record (TRR), journal of the Transportation Research Board.
I am pursuing my Ph.D. in the Transportation and Urban Engineering Program at UConn, and have been working on the CTDOT research project, SPR-2296, “The Development and Execution of a Statewide Household Travel Survey.” Under the supervision of Dr. Karthik Konduri, I have had the opportunity to get involved in the data cleaning aspect of this project. One of the tasks, as part of the data cleaning endeavor, was to “link” trips reported by the respondents, such that all trips reported in the clean data set joins an activity origin to an activity destination. For example, assessing instances where respondents have reported their home to work journey as three separate trips: such as, (i) walk to the car from the house; (ii) drive to the parking lot; (iii) walk to the office from the parking lot; and then, simply reporting it as a single car trip between the home and work location. The fascinating part of the task is to try and understand the respondents' thought process as if they were providing their responses, and then, recreating them in the form of rules and heuristics, so that misreporting can be corrected with reasonable accuracy. So far, the project has offered me the opportunity to undertake new challenges and I look forward to continue working on the project.
I am a Connecticut native and proud member of the UConn graduating class of 2016. Currently, I am a first year master’s student in the Transportation and Urban Engineering Program at UConn. Having completed my undergraduate course work at UConn, I was provided with the opportunity to participate in work over the summer, which has been ongoing into this academic year. In particular, I have been involved with the CTDOT research project SPR-2296, “The Development and Execution of a Statewide Household Travel Survey,” with my advisor Dr. Karthik Konduri. My work on this project has been focused on creating a tool for data visualization. To elaborate, we began work to implement an interactive dashboard where users could actively filter and refine graphs, maps, and tables to explore trends quickly and easily. Using the travel survey data, we have been able to create this dashboard, in a select instance, with the hope that faster and easier visualization of data will be helpful for policy and planning purposes. Moving forward, we aim to expand this tool so that it can be made completely open source and available to any interested parties. This project has been particularly interesting and challenging to me, as I have been afforded the chance to actively participate in the building of this tool from the ground up. To this point, learning the tools of open-source programing, while working in the context of transportation planning and design, has been a wonderful experience.
I am a doctoral candidate in the Department of Geography and a Research Assistant at the Center for Real Estate in the School of Business, both at UConn. Post bachelors in Geography and masters in Geographic Information Science, I am a geographer specializing in urban change, particularly using Geographic Information Systems (GIS) to study large-scale urban redevelopment projects. Under the direction of Professor Jeffrey Cohen, I am currently working on the CTDOT research project SPR-2301, “Impacts of CTfastrak on Real Estate and Urban Economic Development: Phase 1”, investigating the impact of CTfastrak on property values and urban economic development in Central Connecticut. I have been working to compile a parcel-level geospatial database of relevant economic and GIS data. The experience taught me how to correctly structure a research study that examines the impact of a new transit investment on property values and other aspects of economic development. I hope to apply a similar approach to future research projects on urban transit (e.g., examining the decision-making behind the support or opposition to intra-urban highway removal).
I am a Ph.D. candidate in the Department of Civil and Environmental Engineering at UConn, specializing in Structural Engineering. My research has been focused on structural reliability, coastal multi-hazards and coupled structural dynamic analysis. I have worked with Dr. Wei Zhang on the CTDOT sponsored research project SPR-2299, “Resiliency Analysis to Storm Surge for I-95 Right-of-Way at Long Wharf/New Haven, CT.” During the project, my main research focus was on the statistical analysis and numerical simulation of hurricane-induced wind, wave and surge in New Haven, CT. This project gave me an idea of how to tackle a specific engineering problem starting with the problem identification; literature review; data collection; processing and analyses; and, moving towards the evaluation and possible problem-solving strategy. In addition, the project gave me an in-depth understanding of the characteristics of wind, wave, and storm surge under extreme weather conditions, which led to development of interests in investigating the bridge performance under combined hurricane wind and wave actions.
1.) Connecticut Pedestrian Safety Study and Strategic Plan Development. This research study aims: 1) To conduct a statewide pedestrian crash analysis, which considers location, traffic volumes, roadway geometry and roadway classification, to identify locations with high pedestrian crash rates; and, 2) To study these locations/intersections to gain a better understanding of non-motorist and driver behavior in order to develop a strategic safety plan to reduce risk taking behavior and improve pedestrian safety in Connecticut. The data will be collected by video recordings and analyzed to study non-motorist and driver behavior patterns amongst other parameters.
2.) Development of the Digital Design Environment ProjectWise™ – Phase 2. This is a collaborative project between the CTDOT offices of AEC Applications and Roadway Information Systems Unit. The major focus of this project is the development of a geospatial asset tracking system, ATLAS, and the Transportation Enterprise Database (TED), which currently exists as a prototype. This will move CTDOT towards accomplishing a readily accessible agency-wide system, where high quality data sets are maintained and formatted for consumption and analysis in an effective and efficient manner.
3.) Development of a Quality Management Plan for Pavement Condition Data in Connecticut. This project is focused on evaluating the quality of pavement data collected by the CTDOT and the development of a pavement data quality management plan to accomplish the data requirements for the federal National Highway Performance Program.
1.) Development of the Digital Design Environment ProjectWise™ – Phase 1. This research project accomplished the implementation of the cloud-based ProjectWise Online from Bentley Systems Inc., that has delivered a robust project and asset document management system for managing the CTDOT Capital Road and Bridge Program with tremendous cost savings.
2.) Conference Proceedings of the Northeast Autonomous Vehicle Summit. As the automated vehicle technology evolves, there are many technical, logistical, and legal issues that the current system governing the surface transportation is not prepared to handle. To foster a discussion, UConn, CTDOT and FHWA, hosted a Summit in late March of 2017. Officials from across the Northeast got together to discuss a myriad of concerns with a variety of stakeholders including governmental officials, researchers, as well as the developers of the autonomous vehicle technology.
3.) Preparation of the Implementation Plan of AASHTO Mechanistic-Empirical Pavement Design Guide (M-EPDG) in Connecticut: Phase II – Expanded Sensitivity Analysis and Validation with Pavement Management Data. The Mechanistic-Empirical Pavement Design Guide (M-EPDG) is intended to better quantify the physical causes of stresses in pavement structures and develop a pavement design that can withstand these stresses. The M-EPDG uses deterioration models to predict cumulative pavement damage and these models use default values derived from data across the United States. It considers design parameters for traffic, structure conditions, environment, and allows the user to specify a reliability level of the predictions. In order to maximize the M-EPDG distress models effectiveness, there is a need to calibrate them using data obtained locally in order to be applicable for the particular materials, construction practices, and environmental conditions encountered in Connecticut. Phase I of this project conducted statistical sensitivity analyses for all of the input ranges identified as pertinent for Connecticut including mix properties, environmental factors, underlying structures, etc. The Phase II research study expanded the sensitivity analysis to a wide range of pavement structures and soils and established adequate levels of hierarchy for the most important M-EPDG inputs. In addition, an extensive validation analysis of the accuracy of the M-EPDG model predictions was conducted using CTDOT’s Pavement Management Information System (PMIS) data.
4.) Resiliency Analysis of Storm Surge for Interstate 95 Right-of-Way at Long Wharf / New Haven, CT. This report identified the resiliency strategies for transportation assets in the Long Wharf area in the city of New Haven, CT, based on the comprehensive review of the resiliency options utilized across US coastal regions.
Application of 3D Scanning for Bridge Inspection
3D scanners are commonly used in medicine, heritage preservation, design, forensics, reverse engineering, architecture, etc. But use of 3D scanners for bridge inspection is the novel idea of an ingenious UConn professor, Dr. Arash Zaghi, and his research team. Pilot field testing with the CTDOT bridge inspection team confirmed the feasibility of the application. In addition to speeding up the inspection process, the 3D scans offer great advantages including high resolution digital archiving of the images and 3D data; in-office post-processing of the data, as and when necessary; accurate estimation of the residual capacity of a damaged bridge section with finite element modeling, etc. This information is of significant value to CTDOT as it can help make informed decisions regarding the prioritization of rehabilitation projects and allocation of funds. The research project to implement this technology at CTDOT will commence soon.
You may have noticed something new installed above the intersections along the Berlin Turnpike in the past few months. Gridsmart® is a new, 360 degree video-based traffic intersection vehicle detection system, that provides numerous benefits to the Department that traditional in-road loop sensors do not.
Gridsmart® is a non-intrusive technology, requiring no saw cuts in the pavement for installation, which reduces lane closure and installation time.
Advanced video detection algorithms built into the system can provide 24/7 automated data collection from the time of installation. Data including vehicle turning movements, volumes and lengths can be downloaded in intervals ranging from as little as 5-minutes to an hour. Additionally, complete per-vehicle record information can be obtained from the system, and reported in a number of commonly used formats.
The GRIDSMART Iconic Bell Camera
Detection Perspective from the Bell Camera
If you have any ideas or suggestions for the next CTDOT Research Bulletin, please feel free to e-mail Flavia Pereira at Flavia.Pereira@ct.gov
Connecticut Department of Transportation, 2800 Berlin Turnpike, P. O. Box 317546, Newington, CT 06131