Gini Coefficient : A Measure of Travel Time Reliability?

This study examines if the Gini coefficient, which is a widely used measure of income/wealth inequality in a country/society, could be used as a measure of travel time reliability. To be considered a valid measure of travel time reliability, the Gini coefficient should at least agree with existing and widely used reliability measures. We study if the Gini coefficient is in alignment with existing reliability measures by examining the degree to which it correlates with the established measures. Since travel times generally follow right-skewed distributions, we simulate the parameters of four right-skewed distributions: i.log-normal, ii. burr, iii. gamma, and iv. Weibull distributions following which we compute the existing reliability measures as well as the Gini coefficient for each of the parameters. We then compute the correlation coefficients between the Gini coefficient and other established reliability measures. We find that the Gini coefficient is strongly correlated with travel time reliability measures like Buffer-Index, Coefficient of Variation, Width and Skewness for Log-Normal and Gamma distribution. Finally, we test our hypothesis on a travel time data collected using Bluetooth detectors. We perform K-means clustering to segregate the travel rates from the data into two clusters. After determining the suitable distribution for travel rates in each cluster, we compute the Gini coefficient and other reliability measures based on the parameters of the fitted distributions. This study shows that not only does the Gini coefficient agree with existing reliability measures for some distributions, it also helps in intuitively discerning and communicating travel time reliability