Title: Measurement method of green traffic vehicle exhaust emission based on spark algorithm

Authors: Fangling Zhang

Addresses: College of Automobile Engineering, Hunan Communication Polytechnic, Changsha 410132, China

Abstract: There are some problems in the traditional measurement methods of green traffic vehicle exhaust emissions, such as large measurement error and long measurement time. This paper proposes a measurement method of green traffic vehicle exhaust emissions based on spark algorithm. By extracting the green traffic vehicle trajectory, and preprocessing the vehicle trajectory data through the batch descent gradient method, according to the green traffic vehicle trajectory data, calculate the concentration of the substances in the vehicle exhaust, and obtain the green traffic vehicle exhaust emission index; map, overlay and grid it, and build the green traffic vehicle exhaust emission measurement model. With the help of spark streaming in spark algorithm to modify the green traffic vehicle emission measurement model, the optimal solution of the model is the optimal value of vehicle emission measurement. The results show that the error of the proposed method is always less than 3%.

Keywords: spark algorithm; AIS data; driving trajectory; regional emissions; exhaust emissions.

DOI: 10.1504/IJETM.2022.120730

International Journal of Environmental Technology and Management, 2022 Vol.25 No.1/2, pp.65 - 76

Received: 26 Feb 2021
Accepted: 19 May 2021
Published online: 04 Feb 2022 *

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