Urban transportation challenges: Analysis and the mitigation strategies for road accidents, noise pollution and environmental impacts
Urban transportation faces critical challenges, including road accidents, noise pollution, and environmental impacts. Rising accident rates lead to fatalities, injuries, congestion, and increased pollution. High noise levels at signalized intersections affect the quality of life, while prolonged veh...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-07-01
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| Series: | Open Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/eng-2025-0123 |
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| Summary: | Urban transportation faces critical challenges, including road accidents, noise pollution, and environmental impacts. Rising accident rates lead to fatalities, injuries, congestion, and increased pollution. High noise levels at signalized intersections affect the quality of life, while prolonged vehicle idling contributes to carbon emissions and fuel wastage. This study analyzes accident rates, contributing factors, and future traffic prediction. It also assesses noise pollution and the environmental impact of vehicle idling. The methodology includes data collection on accidents, vehicle ownership, noise levels, and fuel consumption, which are analyzed using the Statistical Package for Social Sciences. Carbon emissions are evaluated based on the Intergovernmental Panel on Climate Changes guidelines. The accident prediction model demonstrates strong statistical relationships among key parameters like fatalities, injuries, and vehicle registration. Noise levels peak during rush hours and weekends, while fuel loss and emissions result from extended idling. The study offers insights for policymakers to enhance road safety, manage noise pollution, and optimize traffic flow at signalized intersections. This study integrates accident prediction modelling, noise pollution assessment, and fuel loss analysis at signalized intersections in Bengaluru. By employing statistical modelling, real-world data collection, and intersection-specific emissions analysis, it provides comprehensive insights for improving urban traffic management and sustainability. |
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| ISSN: | 2391-5439 |