Your browser doesn't support javascript.
EXPLORING THE POTENTIAL OF TRAFFIC INDEX DATA TO ANALYZE ESSENTIAL TRAFFIC IMPACT IN DEVELOPING CITIES
Coronavirus Research Database; 2020.
Non-conventional | WHO COVID | ID: grc-743629
ABSTRACT
In developing countries, metropolitan cities, due to their economic activities, attract an increasing amount of commuters on a daily basis. This has led to major freeways and roads experiencing high levels of congestion and consequently high pollution levels. In 2020, due to a global pandemic of an outbreak of Corona Virus (COVID-19), the national government declared a national shutdown with only essential traffic being allowed to operate. Given the scenario of the national lock-down this allows for the statistical analysis of the impact of essential traffic on the overall transportation system. Consequently the aim of the paper was to assess the congestion and CO2 emission impact of essential traffic for the City of Johannesburg. Using an exploratory approach, we monitored and collected traffic congestion data from the Tomtom traffic index for the metropolitan city of Johannesburg, South Africa. We develop a relationship between congestion and pollution to visualise the daily variations in pollution and congestion levels. We demonstrate this by comparing variations in congestion levels in two epochs, viz the period without movement restrictions and the period whereby movement is restricted. The results reveal essential traffic on the congestion index to be below 22 percent for both weekends and weekdays. A scenario common only during weekends in 2019. Whilst for the emission index, CO2 levels are approximately less than 45 percent throughout the week. The paper concludes the investment into mining and analysing traffic data has a significantly role for future mobility planning in both the developed and developing world and, more generally, improving the quality of commuting trips in the city.

Full text: Available Collection: Databases of international organizations Database: WHO COVID Type of study: Experimental Studies Year: 2020 Document Type: Non-conventional

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: Databases of international organizations Database: WHO COVID Type of study: Experimental Studies Year: 2020 Document Type: Non-conventional