Linear regression analysis of regional mean speed of Athens city network using drone data: A multi-modal approach

The work proposes a multi-modal regional mean speed regression analysis for the city network of Athens, Greece. The dataset from pNUEMA experiment is used in the present context. Accumulations and mean speeds of different modes are estimated and compared to each other. Besides, the mean running speeds of all modes are also computed and compared. The mean speed of each mode is assumed to be a linear combination of accumulations of all modes and regression analysis is performed. Ordinary Least Squares (OLS) and Partial Least Squares (PLS) methods are used in the current work. It is noticed that multicollinearity between different modes is weak in the current dataset. The quality of multi-modal regression fits is compared to the uni-modal ones, where the mean speed of a given mode is assumed to be a function of the accumulation of that mode only. It is concluded that multi-modal regression fits outperform their uni-modal counterparts in terms of R2 and Root Mean Squared Relative Error (RMSRE).