Construction of high-precision driving cycle based on Metropolis-Hastings sampling and genetic algorithm

Due to the increasing complexity of the current traffic environment, the existing construction methods of working conditions have large errors and poor representativeness. Therefore, it is difficult to reflect the fuel consumption and emission of vehicles in the actual road environment. To solve the...

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Published inTransportation research. Part D, Transport and environment Vol. 118; p. 103715
Main Authors Yang, D.P., Liu, T., Zhang, X.M., Zeng, X.H., Song, D.F.
Format Journal Article
LanguageEnglish
Published Elsevier Ltd 01.05.2023
Subjects
Driving cycle construction
Genetic algorithm
Metropolis-Hastings sampling
Stepwise regression method
Stepwise regression method
Driving cycle construction
Metropolis-Hastings sampling
Genetic algorithm
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Abstract Due to the increasing complexity of the current traffic environment, the existing construction methods of working conditions have large errors and poor representativeness. Therefore, it is difficult to reflect the fuel consumption and emission of vehicles in the actual road environment. To solve the problem, combine the advantages of the Genetic Algorithm (GA) and Metropolis-Hastings Sampling (MHS) methods, a high-precision construction method-based on stepwise regression characteristic parameter selection for fuel consumption-oriented driving cycles is proposed. Firstly, to improve the construction efficiency and effect of driving cycles, a fuel consumption-oriented characteristic parameter selection method based on stepwise regression is proposed; Then, to overcome the disadvantage of the traditional MC method just taking finite discrete values, MHS is applied to the random transition of the velocity-acceleration state; Finally, the driving cycle construction method is design. According to experimental verification and algorithm comparison, the research results show that the maximum and average relative deviations of characteristic parameters of the driving cycle obtained from the MHS-GA method are 0.074% and 0.48%, respectively, and the relative deviation of fuel consumption is 1.01%. The driving cycle based on the MHS-GA method is more representative than existing methods.
AbstractList Due to the increasing complexity of the current traffic environment, the existing construction methods of working conditions have large errors and poor representativeness. Therefore, it is difficult to reflect the fuel consumption and emission of vehicles in the actual road environment. To solve the problem, combine the advantages of the Genetic Algorithm (GA) and Metropolis-Hastings Sampling (MHS) methods, a high-precision construction method-based on stepwise regression characteristic parameter selection for fuel consumption-oriented driving cycles is proposed. Firstly, to improve the construction efficiency and effect of driving cycles, a fuel consumption-oriented characteristic parameter selection method based on stepwise regression is proposed; Then, to overcome the disadvantage of the traditional MC method just taking finite discrete values, MHS is applied to the random transition of the velocity-acceleration state; Finally, the driving cycle construction method is design. According to experimental verification and algorithm comparison, the research results show that the maximum and average relative deviations of characteristic parameters of the driving cycle obtained from the MHS-GA method are 0.074% and 0.48%, respectively, and the relative deviation of fuel consumption is 1.01%. The driving cycle based on the MHS-GA method is more representative than existing methods.
ArticleNumber 103715
Author Zeng, X.H.
Zhang, X.M.
Yang, D.P.
Liu, T.
Song, D.F.
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Driving cycle construction
Metropolis-Hastings sampling
Genetic algorithm
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Snippet Due to the increasing complexity of the current traffic environment, the existing construction methods of working conditions have large errors and poor...
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StartPage 103715
SubjectTerms Driving cycle construction
Genetic algorithm
Metropolis-Hastings sampling
Stepwise regression method
Title Construction of high-precision driving cycle based on Metropolis-Hastings sampling and genetic algorithm
URI https://dx.doi.org/10.1016/j.trd.2023.103715
Volume 118
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