Stochastic simulation and validation of Markov models of real driving cycles

Abstract

The driving cycle is a time series of the vehicle speed reflecting its movement in real road conditions. The WLTC (Worlwide harmonized Light duty Test Cycle) valid from August 2017 is based on real driving profiles derived from research and statistical analysis of road traffic in Europe, the USA and Asia. In addition to certification and comparative research, driving cycles are used in the process of virtual design of drive systems and embedded control algorithms, traffic management or intelligent road transport. Regardless of the intended use, the standard test does not guarantee the correctness of the results obtained. There is a need to generate many different driving cycles that meet the established equivalence conditions. The article discusses the methods of stochastic simulation and assessment of equivalence of obtained traffic models. The Monte Carlo method of Markov chains was used in the research. The comparative criteria are defined using the statistical parameters of the vehicle speed time series and the corresponding multifractal spectra. The synthesis was carried out at predetermined length of time series. The experiment carried out involved the study of traffic in real road conditions of urban driving and extra-urban large agglomerations during working days.

Evaluation of the Minimum Number of Local Driving Cycles Required to Represent the Traffic of Distinct Cities: A Case Study of Two Brazilian Metropolises

“…For the development of driving cycles, two of the main methods employed and accepted in the literature were adopted, following the recommendation of Santos et al: 1) the micro-trip method for urban driving cycles and 2) the Markov chain method for highway driving cycles (16)(17)(18)(19)(20)(21)(22)(23)(24)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41).…”