Research on eco-driving strategy at intersection based on vehicle infrastructure cooperative system. (April 2019)

• Record Type: Journal Article
• Authors: Yang, Zhifa; Zeng, Huanjing; Yu, Zhuo; Wei, Xuexin; Liu, Aimin; Fan, Xianjun
• Is Part Of: Advances in mechanical engineering. Volume 11:Number 4(2019)
• Publication Date: 2019-04
• Subjects: Vehicle infrastructure cooperative system -- eco-driving -- energy conservation -- back-propagation neural network -- VISSIM; Mechanical engineering -- Periodicals; 621.05
• DOI: 10.1177/1687814019843368
• Languages: English
• ISSNs: 1687-8132

Abstract

An eco-driving strategy is established in this article which includes four parts, namely, initial judging model, speed prediction model based on back-propagation neural network, MATLAB curve fitting, and integral. First, based on vehicle infrastructure cooperative systems, the initial judging model is instructed and vehicle road test is conducted. Then, a speed forecast model based on back-propagation neural network had been set up using test data obtained in the previous step. Next eco-driving strategy had been specified using curve fitting based on the forecast speed data and integral in MATLAB. Finally, a verification test had been done using VISSIM simulation tool. The conclusion of the test showed that using eco-driving strategy was conducive to decrease fuel consumption efficiently when driving at intersection. This article provided a specific case in application of vehicle infrastructure cooperative system to study on fuel consumption and emission in city traffic.