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

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 durin...

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Bibliographic Details
Main Authors: Blinova Tatiana, Kumar Rakesh, Kansal Lavish, Bhandari Prabhakar, Guven Ugur, Prasanna Y. Lakshmi
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:BIO Web of Conferences
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Online Access:https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01089.pdf
Description
Summary: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.
ISSN:2117-4458