Multiple-Factors Aware Car-Following Model for Connected and Autonomous Vehicles

Autor:	Jialing Luo, Yucong Hu, Zhiwei Chen, Hao Wu, Huaqing Ma
Rok vydání:	2021
Předmět:	Multiple factors Computer science Mechanical Engineering Distributed computing Traffic simulation Car following Civil and Structural Engineering
Zdroj:	Transportation Research Record: Journal of the Transportation Research Board. 2676:649-662
ISSN:	2169-4052 0361-1981
Popis:	The emergence of connected and autonomous vehicles (CAV) is of great significance to the development of transportation systems. This paper proposes a multiple-factors aware car-following (MACF) model for CAVs with the consideration of multiple factors including vehicle co-optimization velocity, velocity difference of multiple PVs, and space headway of multiple PVs. The Next Generation Simulation (NGSIM) dataset and the genetic algorithm are used to calibrate the parameters of the model. The stability of the MACF model is first theoretically proved and then empirically verified via numerical simulation experiments. In addition, the VISSIM software is partially redeveloped based on the MACF model to analyze mixed traffic flows consisting of human-driven vehicles and CAVs. Results show that the integration of CAVs based on the MACF model effectively improves the average velocity and throughput of the system.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::7a7a783b4f896c849a222191bc177d08 https://doi.org/10.1177/03611981211045205 Zobrazit plný text záznamu