Abstract
In the last decades, the socio-demographic evolution of the population has substantially changed mobility demand, posing new challenges in minimizing urban congestion and reducing environmental impact. In this scenario, understanding how different modes of transport can efficiently share (partially or totally) a common infrastructure is crucial for urban development. To this aim, we present a stochastic model-based analysis of critical intersections shared by tram traffic and private traffic, combining a microscopic model of the former with a macroscopic model of the latter. Advanced simulation tools are typically used for such kind of analyses, by playing various traffic scenarios. However, simulation is not an exhaustive approach, and some critical, possibly rare, event may be ignored. For this reason, our aim is instead to adopt suitable analytical solution techniques and tools that can support instead a complete, exhaustive analysis, so being able to take into account rare events as well. Transient analysis of the overall traffic model using the method of stochastic state classes is adopted to support the evaluation of relevant performance measures, namely the probability of traffic congestion over time and the average number of private vehicles in the queue over time. A sensitivity analysis is performed with respect to multiple parameters, notably including the arrival rate of private vehicles, the frequency of tram rides, and the time needed to recover from traffic congestion.
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Notes
By traffic congestion we identify the situation when the number of vehicles arriving is higher than the number of vehicles that can flow across the intersection.
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Acknowledgements
This work has been partially funded by the Fondazione Cassa di Risparmio di Firenze (Grant No. 2014.0771). We thank GEST for disclosing data about actual tram operation in Florence.
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Carnevali, L., Fantechi, A., Gori, G. et al. Stochastic modeling and analysis of road–tramway intersections. Innovations Syst Softw Eng 16, 215–230 (2020). https://doi.org/10.1007/s11334-019-00355-1
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DOI: https://doi.org/10.1007/s11334-019-00355-1