Proposal

Below you will find a writing sample in the form of a research grant proposal. This was created from an assignment in a technical writing class. The assignment was to create a research grant proposal to be submitted for funds for a project over the summer. The proposal follows an outline used by the University of Central Florida’s office of Undergraduate Research.

Title

“Streamlining UCF Transportation: An AI Approach to Campus Traffic Flow Improvement”

Background and Significance

As UCF continues to grow at a rapid pace, more and more students, faculty, and staff are relying on a variety of transportation options to get around campus. These options include everything from cars and buses to bikes, electric scooters, and skateboards. However, with increased demand for transportation services, there have been significant challenges such as traffic congestion and limited parking spaces, especially at the beginning of the semester. These challenges not only create stress and frustration for students but also for faculty and staff.

To address these concerns, this research project will explore the use of artificial intelligence to improve transportation efficiency and the flow of traffic around the UCF campus. The project will demonstrate the effectiveness of AI in streamlining transportation routes, reducing congestion, and improving the flow of traffic. This will lead to reduced commute times and reduced stress around finding parking for commuters.

The framework that will guide this project is based on the principles of AI and transportation engineering. The AI approach will use machine learning algorithms to analyze transportation data that is collected around the campus to help predict the flow of traffic at UCF. The project will also involve developing and testing AI algorithms to optimize transportation routes and improve the flow of traffic.

Another approach that the project will implement will be the use of mathematical modeling and optimization techniques to design transportation routes that are safe and efficient. This approach will involve analyzing current transportation data and identifying bottlenecks in the current system.

Overall, this project has the potential to make a significant contribution not only to the field of transportation engineering and AI but also to the happiness and satisfaction of UCF students and faculty alike. It aims to provide a more effective transportation system for the UCF community which will lead to reduced commute times, improved flow of traffic, and reduced stress.

Research Methods

The research project will employ multiple methods to address the question of improved traffic flow.

The first step will be the collection of data on transportation patterns and patterns of traffic flow around campus. This will involve a survey of students, faculty, and staff to gather information on their transportation habits. Additionally, traffic data will be collected using sensors and cameras installed in key locations around the campus. The collected data will then be analyzed using a variety of statistical techniques to try to identify patterns of transportation behavior and traffic flow. We will analyze the survey data to identify the most common transportation modes used on campus and their relevant traffic patterns. Using the traffic data we collect with cameras and sensors, we will analyze congestion hotspots and assess the impact of different transportation modes on those areas. For example: the ratio of persons per car compared with the ratio of persons per bus.

We will use these findings to develop an AI model that can optimize transportation routes and methods to help reduce congestion and improve the flow of traffic around the UCF campus. We will implement machine learning algorithms to predict patterns of traffic and develop routes that minimize congestion and travel time.

The developed AI model will be tested and validated using simulation models to assess its effectiveness in improving traffic flow and reducing congestion on the UCF campus. A virtual model will be implemented using existing maps and data to simulate a virtual model of traffic routes on campus and to test the AI model’s performance under different scenarios.

The success of the project will be evaluated by comparing the traffic flow and commute times both before and after the implementation of the AI’s suggested improvements in the virtual model. Also, feedback from students, faculty, and staff will be collected via survey to assess the suggestions made by the AI model to verify that the changes align with the needs and expectations of those that use the transportation services every day.

Below is a rough timeline for the project during the summer semester.

Expected Outcomes

Upon completion of this research project, we will generate several deliverables. Our primary deliverable is a comprehensive report that details the findings from our study. This report will cover the transportation patterns and traffic flow at the UCF campus, along with the effectiveness of the AI model in enhancing traffic flow and reducing congestion. Furthermore, we will prepare a presentation to share our findings with the UCF community through various channels, such as an undergraduate research poster presentation or a white paper distributed to members of the community.

The report will be a valuable addition to the transportation engineering field and should offer insight into the potential for AI to help improve transportation system efficiency. This knowledge could guide future research in this area. The study will also help support the practical application of AI in transportation engineering and highlight areas for further research and refinement.

For the UCF community itself, our research will deliver helpful information about traffic flow and patterns on campus and could be implemented to have a direct impact on the lives of UCF students and faculty. The findings will contribute to the creation of more efficient and environmentally friendly transportation systems and have a positive effect on the lives of those that use these systems.

Also, the project will allow students the opportunity to gain valuable experience in AI and traffic engineering. Students will be involved in gathering and analyzing transportation data, as well as developing and testing the AI model to optimize routes. This experience will sharpen students’ research abilities and give them the confidence needed to continue developing as researchers in the future if desired.

Literature Review

Preliminary Work and Experience

My previous coursework in Python, C, and mathematics through Calculus has provided me with a foundation to solve the complex problems associated with working with various AI models. This will be a solid foundation with which to move forward in completing the research project. The programming courses, specifically Python and C, have equipped me with the essential skills that I will utilize to tackle the problem of working with AI to optimize traffic flows around campus. These languages are widely used in the field of AI and data analysis, and my proficiency in them will be invaluable for handling complex tasks related to the project.

Furthermore, the mathematical knowledge I’ve gained through studying Calculus is crucial for understanding the underlying principles and algorithms in AI and transportation engineering. This understanding enables me to approach problem-solving more analytically and to apply advanced mathematical techniques to optimize traffic flow and transportation routes.

IRB/IACUC Statement

This proposal does not require IRB or IACUC approval, as it does not involve direct contact with human subjects (e.g., interviews or surveys) nor does it involve research on animal subjects.

Budget

The proposed budget for the research project is as follows: Data collection and processing: