DHANBAD URBAN ROADS PROJECT
Dhanbad, known as the Coal Capital of India, is one of the largest industrial towns of Jharkhand State. A proposed loan from the World Bank aims to improve the city's road network and public transport systems. The government of Jharkhand prepared the Comprehensive Mobility Plan for Dhanbad, a master urban infrastructure development project. The World Bank South Asian Regional Unit enlisted a Capstone team to review the Comprehensive Mobility Plan and associated project report containing the scope and magnitude of the proposed road improvements. The team traveled to Dhanbad where they conducted multiple site visits and interviews with key stakeholders. The team used the gathered data to identify areas for improvement and advance project goals. The team's research supported the development of innovative initiatives-such as contextual planning, multi-purpose programming, solar lighting, and other urban design solutions-that will help tackle the social and environmental challenges of implementing the Dhanbad Roads project.
A STUDY ON THE RECENT RISE IN ROAD FATALITIES
The United States Department of Transportation (USDOT) serves the nation by ensuring a fast, safe, efficient, accessible, and convenient transportation system that meets vital national interests. Between 2014 and 2015, traffic-related fatalities rose across the US by seven percent. The USDOT engaged the Capstone team with investigating potential causes of this spike in fatalities. Through an extensive literature review, expert interviews, data analysis, and use of the geographic information system mapping, the team identified the relationship between fatal crashes and several key variables. Using the Fatality Analysis Reporting System data in conjunction with analysis of select data variables, the team assessed which variables were likely to be directly associated with the recent increase. The team concluded that many variables, ranging from climate change to economic growth, influence the occurrence of traffic-related accidents resulting in deaths. The team's research and analysis culminated in a set of recommendations for the USDOT aimed at improving roadway safety throughout the United States.
CREATING A SUSTAINABLE INVENTORY MANAGEMENT SYSTEM
The Alliance for Positive Change (Alliance) helps New Yorkers make promising transitions toward improved health, housing, recovery, and self-sufficiency. Alliance offers a diverse range of individualized professional services. The organization enlisted a Capstone team to help identify inefficiencies with supply ordering, inventory management (specifically the MetroCard process), and systematizing operations at the Comprehensive AIDS Services Alliance Washington Heights site. The MetroCard process provides clients with a round-trip pass for attending appointments, meeting directly observed therapy requirements, and accessing other services. However, tracking and distribution were not centralized, resulting in clients receiving multiple cards and the travel assistance program being consistently over budget. Utilizing information from interviews with key staff members, the Capstone team designed and implemented an efficient tracking system, leveraging technology to transform the process from paper to digital. The final report contains recommendations to effectively implement this new workflow across all agency sites in the future.
BUILDING A STREET DETERIORATION MODEL TO PREDICT THE FUTURE QUALITY RATING OF STREETS
The New York City Department of Transportation (DOT) is responsible for maintaining 6,000 miles of streets and highways within city limits by prioritizing the funding of street reconstruction work based on a 10-point quality rating system. DOT leverages a pavement deterioration model to predict the future rating of roads and inform its budget allocations. DOT engaged a Capstone team in supporting efforts to maximize efficiency through the measurement of relevant rating variables. To quantify the influence of different variables on street ratings, the team chose segment ID-the unique number for each street-as the smallest analyzing unit and regressed segment ID on related variables, including defects, street cut permits, past reconstruction activities, traffic route, and borough. The team established data rules, cleaned the dataset, built a regression model using STATA, and interpreted the results of the analysis. The team's research culminated in the creation of a deterioration model for rating prediction and a set of recommendations to help guide DOT on when and where to execute street reconstruction or resurfacing with available resources.