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...
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2024-01-01
|
| Series: | BIO Web of Conferences |
| Subjects: | |
| Online Access: | https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01089.pdf |
| _version_ | 1797352922266206208 |
|---|---|
| author | Blinova Tatiana Kumar Rakesh Kansal Lavish Bhandari Prabhakar Guven Ugur Prasanna Y. Lakshmi |
| author_facet | Blinova Tatiana Kumar Rakesh Kansal Lavish Bhandari Prabhakar Guven Ugur Prasanna Y. Lakshmi |
| author_sort | Blinova Tatiana |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T13:23:44Z |
| format | Article |
| id | doaj.art-97a8177be89e45afa7ab06b427d32cff |
| institution | Directory Open Access Journal |
| issn | 2117-4458 |
| language | English |
| last_indexed | 2024-03-08T13:23:44Z |
| publishDate | 2024-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | BIO Web of Conferences |
| spelling | doaj.art-97a8177be89e45afa7ab06b427d32cff2024-01-17T15:02:13ZengEDP SciencesBIO Web of Conferences2117-44582024-01-01860108910.1051/bioconf/20248601089bioconf_rtbs2024_01089Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation TestBlinova Tatiana0Kumar Rakesh1Kansal Lavish2Bhandari Prabhakar3Guven Ugur4Prasanna Y. Lakshmi5Department of Management, and Innovation, National Research University Moscow State University of Civil EngineeringUttaranchal UniversityLovely Professional UniversityK R Mangalam UniversityGD Goenka UniversityGRIET, BachupallyThis 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.https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01089.pdfdata-intensive traffic managementreal-time insightstraffic flow optimizationroad safety enhancementurban congestion reduction |
| spellingShingle | Blinova Tatiana Kumar Rakesh Kansal Lavish Bhandari Prabhakar Guven Ugur Prasanna Y. Lakshmi Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test BIO Web of Conferences data-intensive traffic management real-time insights traffic flow optimization road safety enhancement urban congestion reduction |
| title | Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test |
| title_full | Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test |
| title_fullStr | Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test |
| title_full_unstemmed | Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test |
| title_short | Data-Intensive Traffic Management: Real-Time Insights from the Traffic Management Simulation Test |
| title_sort | data intensive traffic management real time insights from the traffic management simulation test |
| topic | data-intensive traffic management real-time insights traffic flow optimization road safety enhancement urban congestion reduction |
| url | https://www.bio-conferences.org/articles/bioconf/pdf/2024/05/bioconf_rtbs2024_01089.pdf |
| work_keys_str_mv | AT blinovatatiana dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest AT kumarrakesh dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest AT kansallavish dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest AT bhandariprabhakar dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest AT guvenugur dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest AT prasannaylakshmi dataintensivetrafficmanagementrealtimeinsightsfromthetrafficmanagementsimulationtest |