A prediction-evaluation method for road network energy consumption: Fusion of vehicle energy flow principle and Two-Fluid theory

Bin Sun, Qijun Zhang, Le Hu, Chao Zou, Ning Wei, Zhenyu Jia, Xiaoyang Zhao, Jianfei Peng, Hongjun Mao and Zhong Wu

Physica A: Statistical Mechanics and its Applications, 2023, vol. 626, issue C

Abstract: Urban road traffic is a significant source of energy consumption and emissions in the transportation sector. Implementing energy-saving and emission-reduction technology requires further development of systems for predicting and evaluating the energy consumption of the road network. This paper constructs an urban road network traffic energy consumption prediction model (S-RNEM), which couples the principle of vehicle energy flow with the Two-Fluid model based on the proposed traffic flow decomposition assumption. According to the observed data for light and heavy vehicles, road network energy consumption evaluation index e is developed via parameters n, p. The results of the three road network structures demonstrate that decreasing the design speed and the number of lanes of high-energy-consumption roads may reduce the total energy consumption of the road network by 12% and 4%, respectively, and that the former’s energy-saving impact is better than the latter. The evaluation index e can accurately measure the energy consumption of the road network. Energy consumption growth is positively associated with the value of e when e is bigger than 0. Energy consumption growth is inversely related to the value of e when e is smaller than 0. The S-RNEM has an excellent prediction accuracy, evidenced by the average absolute percentage error of 14.2% for sections and 1.5% for the road network between the predicted value and the actual energy consumption. This research can assist in developing energy-saving and emission-reduction technologies for urban road traffic.

Keywords: Road network; Macro traffic; Energy consumption prediction; Energy consumption assessment; Two-Fluid model (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:626:y:2023:i:c:s0378437123006325

DOI: 10.1016/j.physa.2023.129077

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