PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS
Traffic congestion is a serious problem in many cities, resulting in lost time, increased air pollution, and reduced quality of life. In the past few years, time series models have been widely used to predict traffic flows and congestion. This study analyzes traffic data collected over several years...
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| Format: | Article |
| Language: | Russian |
| Published: |
North-Caucasus Federal University
2023-05-01
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| Series: | Современная наука и инновации |
| Subjects: | |
| Online Access: | https://msi.elpub.ru/jour/article/view/1450 |
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| author | V. V. Lutsenko N. N. Kucherov A. V. Gladkov |
| author_facet | V. V. Lutsenko N. N. Kucherov A. V. Gladkov |
| author_sort | V. V. Lutsenko |
| collection | DOAJ |
| description | Traffic congestion is a serious problem in many cities, resulting in lost time, increased air pollution, and reduced quality of life. In the past few years, time series models have been widely used to predict traffic flows and congestion. This study analyzes traffic data collected over several years and develops a predictive model based on time series analysis techniques. The model takes into account various factors that contribute to congestion, such as time of day, day of the week, and junction. The results show that the model effectively predicts traffic congestion with a high degree of accuracy, which can be used to make rational decisions and reduce urban traffic congestion |
| format | Article |
| id | doaj-art-681f67dbe4de4981b13e12d59991c7a3 |
| institution | Kabale University |
| issn | 2307-910X |
| language | Russian |
| publishDate | 2023-05-01 |
| publisher | North-Caucasus Federal University |
| record_format | Article |
| series | Современная наука и инновации |
| spelling | doaj-art-681f67dbe4de4981b13e12d59991c7a32025-08-20T03:57:48ZrusNorth-Caucasus Federal UniversityСовременная наука и инновации2307-910X2023-05-0101475510.37493/2307-910X.2023.1.41439PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSISV. V. Lutsenko0N. N. Kucherov1A. V. Gladkov2North-Caucasus Federal University, Faculty of mathematics and computer science named after Professor N. I. ChervyakovNorth-Caucasus Federal University, Faculty of mathematics and computer science named after Professor N. I. ChervyakovNorth-Caucasus Federal University, Faculty of mathematics and computer science named after Professor N. I. ChervyakovTraffic congestion is a serious problem in many cities, resulting in lost time, increased air pollution, and reduced quality of life. In the past few years, time series models have been widely used to predict traffic flows and congestion. This study analyzes traffic data collected over several years and develops a predictive model based on time series analysis techniques. The model takes into account various factors that contribute to congestion, such as time of day, day of the week, and junction. The results show that the model effectively predicts traffic congestion with a high degree of accuracy, which can be used to make rational decisions and reduce urban traffic congestionhttps://msi.elpub.ru/jour/article/view/1450traffic forecastingholt-winter methodarima modelintelligent transportation systemtime series forecasting. |
| spellingShingle | V. V. Lutsenko N. N. Kucherov A. V. Gladkov PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS Современная наука и инновации traffic forecasting holt-winter method arima model intelligent transportation system time series forecasting. |
| title | PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS |
| title_full | PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS |
| title_fullStr | PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS |
| title_full_unstemmed | PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS |
| title_short | PREDICTING TRAFFIC CONGESTION BASED ON TIME SERIES ANALYSIS |
| title_sort | predicting traffic congestion based on time series analysis |
| topic | traffic forecasting holt-winter method arima model intelligent transportation system time series forecasting. |
| url | https://msi.elpub.ru/jour/article/view/1450 |
| work_keys_str_mv | AT vvlutsenko predictingtrafficcongestionbasedontimeseriesanalysis AT nnkucherov predictingtrafficcongestionbasedontimeseriesanalysis AT avgladkov predictingtrafficcongestionbasedontimeseriesanalysis |