Managing curb activities and performance analysis of a network based on VISSIM

Urban intersections such as the confluence of 21st, 22nd, and 23rd Streets in Washington, D.C., exemplify the growing congestion challenges faced by modern cities. This intersection, a critical node in the city’s transportation network, accommodates a diverse mix of commuters, tourists, and pedestrians. The increasing prevalence of ride-sharing platforms like Uber and Lyft has significantly altered traffic dynamics at this location, contributing to more frequent curbside stops and exacerbating peak-hour congestion. The limited curb space, originally intended for transient use, is now a frequent bottleneck, further complicated by unpredictable pedestrian-vehicle interactions, thereby raising safety concerns. This study investigates the effects of implementing additional parking spaces at the intersection during a surge event at the George Washington Memorial Hospital. Using PTV VISSIM, a microscopic traffic simulation software, the study analyzes changes in key performance metrics including Level of Service (LOS), vehicle delay, and queue length. The research also evaluates the impact of modifying signal timing parameters green, yellow, and red intervals on overall network performance. A comprehensive literature review is provided to contextualize the simulation findings. It is important to note that the current model does not account for pedestrian volumes. Traffic volume data were obtained from DC Open Data to calibrate the simulation. The study concludes by discussing the implications of curbside usage and signal timing optimization in urban traffic management.