Review of Technologies for Mitigating Traffic Accidents in Foggy Conditions
Review of Technologies for Mitigating Traffic Accidents in Foggy Conditions |
||
|
||
© 2024 by IJETT Journal | ||
Volume-72 Issue-12 |
||
Year of Publication : 2024 | ||
Author : Milagros Vara-Teodoro, Oscar Arana-Huanca, Alicia Alva-Mantari, Ana Huamani-Huaracca, Sebastián Ramos-Cosi |
||
DOI : 10.14445/22315381/IJETT-V72I12P107 |
How to Cite?
Milagros Vara-Teodoro, Oscar Arana-Huanca, Alicia Alva-Mantari, Ana Huamani-Huaracca, Sebastián Ramos-Cosi, "Review of Technologies for Mitigating Traffic Accidents in Foggy Conditions," International Journal of Engineering Trends and Technology, vol. 72, no. 12, pp. 77-89, 2024. Crossref, https://doi.org/10.14445/22315381/IJETT-V72I12P107
Abstract
Traffic accidents in foggy conditions represent a significant risk in countries such as Peru, where topography and weather conditions vary considerably. In 2023, the Tax Administration Service of Lima (SAT) reported around 43,000 accidents, with 4% deaths, 66% injuries and 30% runovers. This study employed the PRISMA methodology and bibliometric analysis in Scopus, using Boolean algorithms to filter scientific articles on devices and methods to mitigate accidents in fog between 2002 and 2025. 387 documents were analyzed and processed with RStudio and Google Collaboratory. Of the total, 73.7% corresponded to articles, 24.5% to conference papers and 1.8% to reviews. China led production with 179 documents, followed by the United States with 68. The most relevant advances include adaptive lighting systems and driver assistance devices, such as cameras and radars, which improve visibility and reduce the risk of collisions. Despite the progress, the study recommends developing more accessible and efficient technologies adapted to Peruvian conditions. The use of real-time monitoring and artificial intelligence algorithms is transforming road safety, but more research and collaboration between scientists and engineers is needed to improve road safety, especially in regions with high incidences of fog.
Keywords
Traffic accidents, Fog mitigation, Road safety, Accident prevention, Traffic safety.
References
[1] Enayatollah Homaie Rad et al., “Self-Reported Cycling Behavior and Previous History of Traffic Accidents of Cyclists,” BMC Public Health, vol. 24, no. 1, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[2] Enayatollah Homaie Rad et al., “Fatigue in Taxi Drivers and its Relationship with Traffic Accident History and Experiences: A Cross-Sectional Study in the North of Iran,” BMC Public Health, vol. 24, no. 1, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[3] Injuries Caused by Traffic, World Health Organization, 2023. [Online]. Available: https://www.who.int/es/news-room/fact-sheets/detail/road-traffic-injuries
[4] Xingyu Wang et al., “Research on Highway Rain Monitoring Based on Rain Monitoring Coefficient,” Scientific Reports, vol. 14, no. 1, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[5] Road Traffic Accidents, National Open Data Platform, Open Data, 2024. [Online]. Available:https://www.datosabiertos.gob.pe/dataset/accidentes-de-tr%C3%A1nsito-en-carreteras
[6] Frightening! Nearly 43,000 Traffic Accidents Have Been Recorded in 2023, Lima Tax Administration Service, 2023. [Online]. Available: https://www.sat.gob.pe/WebSiteV9/Noticias/aid/1100.
[7] Satish Kumar Satti et al., “Potholes and Traffic Signs Detection by Classifier with Vision Transformers,” Scientific Reports, vol. 14, no. 1, pp. 1-18, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[8] Moh Syadidul Itqan, Mida Rosida, and Dini Melinda Ulfatul Azizah, “Android Based Learning Media for Dyscalculia Children at Nurul Jadid Islamic Boarding School,” Jurnal Teknologi Pembelajaran, vol. 1, no. 2, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[9] Enrique Santiso et al., “Announcement Signals and Automatic Braking Using Virtual Balises in Railway Transport Systems,” Sensors, vol. 22, no. 5, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[10] Jessica B. Cicchino, “Effects of Automatic Emergency Braking Systems on Pedestrian Crash Risk,” Accident Analysis & Prevention, vol. 172, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[11] Farman Ali et al., “Traffic Accident Detection and Condition Analysis Based on Social Networking Data,” Accident Analysis & Prevention, vol. 151, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[12] Chen-Wei Liang, Chia-Chun Chang, and Jeng-Jong Liang, “The Impacts of Air Quality and Secondary Organic Aerosols Formation on Traffic Accidents in Heavy Fog–Haze Weather,” Heliyon, vol. 9, no. 4, 2023.
[Google Scholar] [Publisher Link]
[13] Yina Wu, Mohamed Abdel-Aty, and Jaeyoung Lee, “Crash Risk Analysis During Fog Conditions Using Real-Time Traffic Data,” Accident Analysis & Prevention, vol. 114, pp. 4-11, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[14] Yuting Zhan, Xuedong Yan, and Xiaomeng Li, “Effect of Warning Message on Driver’s Stop/Go Decision and Red-Light-Running Behaviors Under Fog Condition,” Accident Analysis & Prevention, vol. 150, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[15] Hafiz Mohkum Hammad et al., “Environmental Factors Affecting the Frequency of Road Traffic Accidents: A Case Study of Sub-Urban Area of Pakistan,” Environmental Science and Pollution Research, vol. 26, no. 12, pp. 11674-11685, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[16] Yichuan Peng et al., “Examining the Effect of Adverse Weather on Road Transportation Using Weather and Traffic Sensors,” PLOS ONE, vol. 13, no. 10, 2018.
[CrossRef] [Google Scholar] [Publisher Link]
[17] Jinhua Tan, Li Gong, and Xuqian Qin, “Effect of Imitation Phenomenon on Two-Lane Traffic Safety in Fog Weather,” International Journal of Environmental Research and Public Health, vol. 16, no. 19, 2019.
[CrossRef] [Google Scholar] [Publisher Link]
[18] Chakad Ojani, “Smallness and Small-device Heuristics: Scaling Fog Catchers Down and Up in Lima, Peru,” Social Anthropology/Anthropologie Sociale, vol. 31, no. 2, pp. 39-53, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[19] Kanchan Lakra and Kirti Avishek, “A Review on Factors Influencing Fog Formation, Classification, Forecasting, Detection and Impacts,” Rendiconti Lincei. Scienze Fisiche e Naturali, vol. 33, no. 2, pp. 319-353, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[20] Zouhair Elamrani Abou Elassad, Hajar Mousannif, and Hassan Al Moatassime, “Class-Imbalanced Crash Prediction Based on Real-Time Traffic and Weather Data: A Driving Simulator Study,” Traffic Injury Prevention, vol. 21, no. 3, pp. 201-208, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[21] Jan Theeuwes, and Johan W.A.M. Alferdinck, “The Effectiveness of Side Marker Lamps: An Experimental Study,” Accident Analysis & Prevention, vol. 29, no. 2, pp. 235-245, 1997.
[CrossRef] [Google Scholar] [Publisher Link]
[22] Rafał Doniec et al., “Sensor-Based Classification of Primary and Secondary Car Driver Activities Using Convolutional Neural Networks,” Sensors, vol. 23, no. 12, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[23] Emmanuel Owusu Appiah, and Solomon Mensah, “Object Detection in Adverse Weather Condition for Autonomous Vehicles,” Multimedia Tools and Applications, vol. 83, no. 9, pp. 28235-28261, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[24] I. Gultepe et al., “Fog Research: A Review of Past Achievements and Future Perspectives,” Pure and Applied Geophysics, vol. 164, no. 6-7, pp. 1121-1159, 2007.
[CrossRef] [Google Scholar] [Publisher Link]
[25] I. Gultepe et al., “A Review on Ice Fog Measurements and Modeling,” Atmospheric Research, vol. 151, pp. 2-19, 2015.
[CrossRef] [Google Scholar] [Publisher Link]
[26] Pierre Herckes, Kalliat T. Valsaraj, and Jeffrey L. Collett Jr, “A Review of Observations of Organic Matter in Fogs and Clouds: Origin, Processing and Fate,” Atmospheric Research, vol. 132-133, pp. 434-449, 2013.
[CrossRef] [Google Scholar] [Publisher Link]
[27] Muhammar Khamdevi, “A Systematic Literature Review of Architecture-Related Dew and Fog Harvesting,” Visions for Sustainability, no. 20, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[28] Hasan Ejaz et al., “Bibliometric Analysis of Publications on the Omicron Variant from 2020 to 2022 in the Scopus Database Using R and VOSviewer,” International Journal of Environmental Research and Public Health, vol. 19, no. 19, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[29] Anibal Alviz-Meza et al., “Bibliometric Analysis of Fourth Industrial Revolution Applied to Material Sciences Based on Web of Science and Scopus Databases from 2017 to 2021,” ChemEngineering, vol. 7, no. 1, 2023.
[CrossRef] [Google Scholar] [Publisher Link]
[30] Gricelda Herrera-Franco et al., “Research Trends in Geotourism: A Bibliometric Analysis Using the Scopus Database,” Geosciences, vol. 10, no. 10, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[31] Medi Vijay Kumar, and K. Bharathi, “Trends in Information Seeking Behaviour Research: A Bibliometric Study Using Scopus Database,” College Libraries, vol. 38, no. 4, pp. 20-28, 2023.
[Google Scholar] [Publisher Link]
[32] Raminta Pranckutė, “Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World,” Publications, vol. 9, no. 1, 2021.
[CrossRef] [Google Scholar] [Publisher Link]
[33] Jiong Dong, Kaoru Ota, and Mianxiong Dong, “Exploring Avatar Experiences in Social VR: A Comprehensive Analysis of User Reviews,” IEEE Consumer Electronics Magazine, vol. 13, no. 3, pp. 53-60, 2024.
[CrossRef] [Google Scholar] [Publisher Link]
[34] Jeroen Baas et al., “Scopus as a Curated, High-Quality Bibliometric Data Source for Academic Research in Quantitative Science Studies,” Quantitative Science Studies, vol. 1, no. 1, pp. 377-386, 2020.
[CrossRef] [Google Scholar] [Publisher Link]
[35] Ashwin Pajankar, Visualizing Data with Pandas and Matplotlib, Hands-on Matplotlib, Apress, Berkeley, CA, pp. 211-241, 2022.
[CrossRef] [Google Scholar] [Publisher Link]
[36] Fabio Nelli, Python data analytics: With Pandas, NumPy, and Matplotlib, Springer Nature Link, 2nd ed., 2018.
[Google Scholar] [Publisher Link]