Based on this idea, the objective of this paper is to develop, implement, and validate an experiment platform that integrates
a microscopic traffic simulator with multiple driving simulators (TSMDS) in a real-time environment. When multiple
drivers control their vehicles individually through the DS, the MTS enables the control of multiple user-driven vehicles in
running environments in full accordance with the drivers’ intentions; autonomous vehicles in the driving environment
are driven by the traffic flow model (e.g., car-following, lane-changing) of the MTS. Driver behavior research based on the
DS will benefit from easy-to-define realistic traffic flow in the virtual driving environment and the ability to study the impact
of multi-vehicle interactions on traffic flow. For traffic flow research, the human-in-the-loop element, as well as unconventional
driving behavior, both previously unavailable to MTS models, will provide opportunities to include individual driver
characteristics in the analysis. The wider range of scenarios that can be studied on a DS will also in turn provide more
accurate data for modeling the traffic flow in the MTS. Finally, two complicated experiments (one is the lane changing experiments
at a recurring on-ramp bottleneck and another is the left-turn experiments at a two-phase signalized intersection in
Shanghai) are conducted to validate the integrated experiment platform.
This paper is organized as follows. Section 2 presents an overview of the research work. Section 3 describes the developed
simulation framework and provides a detailed description of its different components. Two case studies for the TSMDS
validation are presented in Sections 4 and 5 respectively. Section 6 ends the article with concluding remarks.