Statistical approach to the diagnosis of the dynamics of urban mobility under the influence of the road congestion situation in the city of Douala, Cameroon

Abstract

Smooth movement is an essential function and an indicator of a healthy city. Cities being engines of growth, congestion is a real cancer for the country’s economy. In this sense, linking travel habits and the increase in the level of congestion in a city is very important. The objective of this work is to diagnose, using a statistical approach, the dynamics of urban mobility influenced by the traffic congestion situation in the city of Douala. For this, the study focuses on two aspects; the first aspect concerns the multivariate descriptive analysis of motorists’ travel habits. The methods used involve first submitting surveys to motorists in vehicle technical inspection centers and processing the data in IBM SPSS statistical software. Follow-up of the analysis of the correlation between the congestion level and some required solutions. The second aspect focuses on the principal component analysis (PCA) that is performed. The determination of Kaiser-Meyer-Olkin (KMO) indices, the Bartlett significances, and the Pearson correlation coefficients are also done. The results show that the travel habits of motorists create a massive use of roads at certain specific time slots, in addition to extra-municipal trips mainly oriented towards the city center and the administrative district due to the monocentric situation of the city, which contributes to the increase in the level of congestion in the city. The correlation shows that there is significance between the level of congestion and the solutions considered, but this correlation is more or less moderate, which shows that the solutions considered can be used in the short term to alleviate congestion in the city.