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Abstract

With the development of superhighways, research on mixed traffic flow has become increasingly important. This paper aims to investigate the car-following behavior of different vehicle types on superhighways, focusing on the impacts of connected autonomous vehicles (CAVs), human-driven vehicles, and degraded CAVs. By employing the intelligent driver model, the adaptive cruise control model (ACC), and the cooperative ACC model, a fundamental graph was constructed to analyze traffic capacity on superhighways. A decrease followed by an increase in freeway capacity was found to occur as the CAVs’ penetration rate increased. The study reveals that the penetration rate significantly affects traffic flow fluctuations, with higher penetration rates potentially increasing the risk of congestion. The findings provide a theoretical basis for traffic management and optimization on superhighways.

Keywords

superhighway fundamental diagram model mixed traffic flow car-following model microscopic traffic flow

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Fundamental Diagram Model of Superhighway Mixed Traffic Flow Considering Intelligent Networked Vehicles

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