Periodic polynomial regression analysis of urban driving characteristics
Riga Technical University, Faculty of Mechanical Engineering, Transport and Aeronautics, Department of Automotive Engineering, 1 Kalku Str., LV1658 Riga, Latvia
Urban driving characteristics with a focus on energy consumption have been tested in Riga on three main city streets with inflexible coordinated traffic lights control. The aim of this article is to investigate periodic polynomial regression analysis method to analyse car urban driving parameters’ change during weekday twenty-four hours to assess the influence of vehicle technologies on energy consumption in city driving, to map the energy demand on Riga city main street sections and to evaluate the traffic lights control on flow energetic characteristics. The tests have been done using GPS and OBD data loggers on a test car repetitively driven along a pre-planned route at around-the-clock hours. A regression analysis using periodic polynomials was developed and applied to evaluate the traffic flow characteristics with a given time shift. It was concluded that using polynomial regression function, the polynomial order has to be at least seven although a visual conformation of good regression line to the measured data has to be checked especially with lower orders. To evaluate the traffic conditions at a given 20 minutes to one hour shift the application of regression function is limited for the periods with fast changing traffic flow, especially after the end of rush hours when the usability of regression line for the given data has to be checked individually for tested street sections.