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Article

Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods

School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
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Sustainability 2020, 12(19), 8118; https://doi.org/10.3390/su12198118
Received: 4 September 2020 / Revised: 25 September 2020 / Accepted: 26 September 2020 / Published: 1 October 2020
The sustainable development of mankind is a matter of concern to the whole world. Environmental pollution and haze diffusion have greatly affected the sustainable development of mankind. According to previous research, vehicle exhaust emissions are an important source of environmental pollution and haze diffusion. The sharp increase in the number of cars has also made the supply of energy increasingly tight. In this paper, we have explored the use of intelligent navigation technology based on data analysis to reduce the overall carbon emissions of vehicles on road networks. We have implemented a traffic flow prediction method using a genetic algorithm and particle-swarm-optimization-enhanced support vector regression, constructed a model for predicting vehicle exhaust emissions based on predicted road conditions and vehicle fuel consumption, and built our low-carbon-emission-oriented navigation algorithm based on a spatially optimized dynamic path planning algorithm. The results show that our method could help to significantly reduce the overall carbon emissions of vehicles on the road network, which means that our method could contribute to the construction of low-carbon-emission intelligent transportation systems and smart cities. View Full-Text
Keywords: sustainability; intelligent transportation system; IoT; vehicle emissions; environmental protection sustainability; intelligent transportation system; IoT; vehicle emissions; environmental protection
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MDPI and ACS Style

Peng, T.; Yang, X.; Xu, Z.; Liang, Y. Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods. Sustainability 2020, 12, 8118. https://doi.org/10.3390/su12198118

AMA Style

Peng T, Yang X, Xu Z, Liang Y. Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods. Sustainability. 2020; 12(19):8118. https://doi.org/10.3390/su12198118

Chicago/Turabian Style

Peng, Tu, Xu Yang, Zi Xu, and Yu Liang. 2020. "Constructing an Environmental Friendly Low-Carbon-Emission Intelligent Transportation System Based on Big Data and Machine Learning Methods" Sustainability 12, no. 19: 8118. https://doi.org/10.3390/su12198118

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