Research on Markov property analysis of driving cycles and its application. (August 2016)

• Record Type: Journal Article
• Authors: Shi, Shuming; Lin, Nan; Zhang, Yan; Cheng, Jingmin; Huang, Chaosheng; Liu, Li; Lu, Bingwu
• Is Part Of: Transportation research. Volume 47(2016)
• Page Start: 171
• Page End: 181
• Publication Date: 2016-08
• Subjects: Markov process -- Driving cycles -- Transition probability matrix -- VA probability; Transportation -- Research -- Periodicals; Transportation -- Environmental aspects -- Periodicals; 354.76
• DOI: 10.1016/j.trd.2016.05.013
• Languages: English
• ISSNs: 1361-9209

Abstract

Highlights: The Markov property of driving cycles in small time scale was proved. The state in Markov chain contains velocity and acceleration. Relationship between driving cycle, VA and transition matrix was illustrated. Applications of Markov property were also discussed. Abstract: The Markov property of driving cycles was discussed by making a thorough description of their essential characteristics. The Markov chain, a useful tool for designing and expressing driving cycles, has been increasingly used in the field of driving cycles in recent years. Although the Markov property of driving cycles left unproved, some researchers have taken it for granted that it is appropriate to design driving cycle with Markov chain. In our research, the vehicle dynamics model and the car-following model were used to establish the two-dimensional Markov state transition model. On the other hand, the driving data from the city of Changchun were collected to analyze how states (in Markov theory) correlation changes with the increase of time intervals. After the Markov property had been proven, the theory of ergodicity was applied to reveal the relationship between velocity-acceleration joint probability distribution (VA Probability) and state transition matrix. Finally, the application of Markov property was also discussed briefly. This research will lay a theoretical foundation for designing driving cycles and ECO driving (Economical and Ecological).