Abstract
The growth in Intelligent Transportation Systems (ITS) has enhanced the way mobility in contemporary cities is managed. Given the growth in availability of traffic data that contains location-aware datasets, congestion and pollution indexes can be developed. Metropolitan cities such Johannesburg due to their economic activities, attract commuters into the city on a daily basis seeking greener pastures. This has led to major freeways and roads experiencing high levels of congestion. 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 explore the congestion and C02 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. Using a mathematic model, we develop a relationship between congestion and pollution to visualise the variations in pollution and congestion levels during varies scenarios. We demonstrate this by comparing datasets for 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, C02 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.