Optimization of VDOT Safety Service Patrols to Improve VDOT Response to Incidents; Social Responsibility to Investigate Radicalized Posts in Online Chat Forums
Campbell, Elizabeth, School of Engineering and Applied Science, University of Virginia
Seabrook, Bryn, EN-Engineering and Society, University of Virginia
Porter, Michael, EN-Eng Sys and Environment, University of Virginia
The Capstone Project focuses on the Virginia Department of Transportation (VDOT) and the routing of their Safety Service Patrol Vehicles (SSPs). SSPs are a fleet of cars that travel on major highways in the state of Virginia aiming to detect incidents and help in their clearance to minimize traffic costs and congestion. The first semester, the team focused on data cleaning and evaluating the ability of the SSP vehicles including gaps in detection. Additionally, the team focused on detection and clearance time of the vehicles, disparities between detection in different regions in the state of Virginia, evaluation of different detection methods (SSPs, traffic cameras, police cars, etc) and off route detection (detection not on the major highway routes). As the SSP program stands, the SSP vehicles are placed on the highways, changing overtime to better fit the incidents, by word from the patrollers and not by statistical analysis of the most optimal locations. The second phase of the project focused on building an algorithm that would optimally place the SSP vehicles throughout the highway system to increase SSP performance and minimize total response time. A genetic algorithm, an algorithm that is based on natural selection to find the most optimal result, was implemented, looping through possible routes SSPs may take to ultimately be as close to an incident before it happens. This algorithm took data from previous roots combined with incident data to optimize the SSP routes.
The STS Research Paper discusses possible solutions to minimize the number of mass shootings and investigate the radicalization on online chat forums that leads to physical behavior. The mass shootings in this paper are tied to white supremacist linked attacks and their posts on online radicalized forums. The attackers are radicalized quickly online because of the echo-chamber effect that the Internet has (Wood, 2019). Researchers suggest that one of the best ways to stop the radicalization that leads to attacks is to drive the radicalized online forums underground further from mainstream media so that new users will be less likely to join. Additionally, administrators of the radicalized sites should take these pages offline, and internet service providers should stop providing services to these users. Also, public officials should ensure that they are not using inflammatory language that can easily be mimicked and translated into the hateful rhetoric that attackers use online.
BS (Bachelor of Science)
Actor-Network Theory, Genetic Algorithm, Chat Forums, Routing Optimization
School of Engineering and Applied Science
Bachelor of Science in Systems Engineering
Technical Advisor: Michael Porter
STS Advisor: Bryn Seabrook
Technical Team Members: Elizabeth Campbell, Emma Chamberlayne, Julie Gawrylowicz, Colin Hood, Allison Hudak, Matthew Orlowsky, Emilio Rivero
All rights reserved (no additional license for public reuse)