A passenger-oriented method integrating perimeter control with bus dispatch is proposed for solving passenger dispersion problem under metro interruption. Its essential to use perimeter control to prevent the neighborhood of the affected road network from congestion by postponing or transferring the surplus cars out of the protected area. For executing perimeter control, the theoretical tool of Macroscopic Fundamental Diagram (MFD) is used to interpret the relationship between private cars and buses which is required for transfer passengers from the targeted closed metro station. The framework based on MPC method is used to optimize the control parameters (e.g. the number of vehicles or dynamic split rates allowed to enter protected network). Furthermore, signal timing of the intersections on the boundary of protected network is studied considering the optimized split rates. Finally, the real road network around Zhujiang New Town station of Metro Line No. 5 in Guangzhou is modeled by Aimsun. A number of simulation experiments are conducted, and the efficiency of the proposed management strategy is verified by comparing with different existing strategies. To the best of our knowledge, its the first effort to solve passenger dispersion under subway interruption using the idea of perimeter control based on MFD.

Congestion observed in the transportation systems aggregates various amounts of uncertainty at different levels, making it challenging to achieve a clear understanding regarding empirically-observed traffic instabilities. In the literature, lane changing has been frequently indicated as an important factor of oscillations under high-density flows (Ahn and Cassidy, 2007; Laval and Leclercq, 2010; Zheng, 2014). But oscillations appear also on one-lane roads when a small fluctuation caused by single-vehicle amplifies eventually leading to a jam (Stern et al., 2018). Modelling these phenomena is not a simple task. At microscopic level, for example, many car-following (CF) models, which explicitly reproduce the dynamics governing the actions of the driver-vehicle system while following another vehicle, are not able to properly reproduce traffic oscillation in a satisfactorily way. For this reason, new CF models are regularly introduced with increasing levels of complexity. However, in many cases, this does not lead to an improved understanding of traffic phenomena or to a better traffic simulation as it is difficult to have sufficient data to correctly characterize them.

As the introduction of connected and automated vehicles (CAVs) promises to reduce road space demand and improve traffic flows and safety, adapted transportation and infrastructure planning becomes imperative for urban development. Surprisingly, some major European cities still do not include CAVs in their strategic urban mobility plans which demonstrates the need to increase the awareness of the stakeholders. That is the void the European project CoEXistaims to fill by allowing mobility stakeholders to become "automation-ready".
To this end, the availability of adapted simulation software is needed, and new features have been introduced within the project to enable the simulation and modelling of CAVs. The control logics of a CAV has been connected to a vehicle simulator to analyse the behaviour of CAVs. On the basis of these analyses the microscopic simulation software, PTV Vissim has been enhanced. Empirical data collected from real automated cars on a test track were used to calibrate the behaviour of the CAVs within the model and to suggest default behavioural parameter sets for modelling CAVs.
The results of the validated CAV-ready microsimulation model were used to make supply-side assumptions for macroscopic models. And macroscopic modelling tools were also developed to support strategic CAV planning with both scripts as well as improvements of the PTV Visum software.
Besides CoEXist includes a proof of concept. To that end, eight use cases across Europe were investigated. The improved software and assessment tools were applied to these use cases which attempt to cover the wide range of influencing parameters such as road type, traffic load, CAV penetration rates, etc.