Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test

¹ Department of Management, and Innovation, National Research University Moscow State University of Civil Engineering, 129337 Yaroslavskoe shosse, 26, Moscow, Russia
² Uttaranchal University, Dehradun 248007, India, rakeshkumaruim@uumaul.in
³ Lovely Professional University Phagwara, Punjab, India
⁴ K R Mangalam University, Gurgaon, India,
⁵ GD Goenka University, Sohna, Haryana, India
⁶ GRIET, Bachupally, Hyderabad, Telangana, India

^* Corresponding author: tatianablinova@bk.ru

Abstract

This research examined the effectiveness of data-intensive traffic management in urban settings using real-time insights from traffic management simulation experiments. The examination of data on traffic flow revealed a noteworthy decrease in congestion, with a 25% increase in traffic velocity during peak hours. Real-time information led to a 40% drop in the severity of traffic accidents and a 50% reduction in reaction times. Improved road safety was aided by a 30% decrease in accidents during inclement weather thanks to real-time weather data. To further optimize urban traffic flow, dynamic traffic management operations based on real-time information also resulted in a 20% reduction in congestion. These results highlight the revolutionary potential of data-intensive traffic management, offering safer and more effective urban transportation solutions by incorporating real-time information into traffic control plans.