In Cali, Colombia, urban mobility and air quality face significant challenges due to high traffic volumes, particularly during peak hours. This study evaluates and optimizes urban mobility while reducing pollutant emissions in critical areas of Cali, using advanced simulation tools. The Simulation of Urban Mobility (SUMO) software, combined with data from Google Maps, was employed to create detailed traffic models and emission assessments. Through the integration of SUMO with OSM Web Wizard and Netedit, realistic traffic scenarios were generated, focusing on the Universidades station area, a critical node in the city’s public transportation system. The study analyzed the impact of various traffic management strategies, including the implementation of smart traffic lights equipped with sensors, which dynamically adjust signal timings based on traffic conditions. Results indicated a significant reduction in carbon dioxide, nitrogen oxides, and particulate matter emissions due to optimized traffic flow and reduced vehicle idling times. The implementation of smart technologies not only improved traffic efficiency but also demonstrated substantial environmental benefits. This research provides actionable insights for urban planners and policymakers aiming to enhance sustainable urban mobility and air quality. Future work should focus on expanding these strategies to other congested urban areas and exploring additional smart technologies to further reduce environmental impacts.
Optimization of Urban Mobility and Reduction of Pollutant Emissions in Cali, Colombia: A Study Based on SUMO and Google Maps Data
2024-09-25
1725709 byte
Conference paper
Electronic Resource
English
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