Real-Time Traffic Camera Data for Enhanced Route Planning

Modern navigation apps efficiently provide routes but often lack a visual representation of real-time traffic conditions along the journey. This paper introduces a method to enhance navigation tools by integrating live traffic camera data, offering users precise, context-aware information about route conditions. Standard navigation services primarily focus on the fastest or shortest routes, often overlooking crucial factors such as individual preferences. To address these challenges, our system combines the Google Maps Directions API with public traffic feeds, such as those from 511NY, to incorporate real-time traffic camera data. Users can check current traffic patterns, including vehicle counts. The program selects only cameras near the route and refines this selection by considering their orientation relative to the travel direction. Moreover, live camera feeds are analyzed using computer vision tools to estimate the number of automobiles. Rather than suggesting alternative routes, the system enhances user decision-making by providing real-time visual data on traffic conditions. Its scalable framework paves the way for future integration of additional real-time data sources, such as crowdsourced images and intelligent city sensors, for more comprehensive insights. This study demonstrates how real-time traffic imagery can improve route selection and highlights the need for technologies that better serve users.