Stochastic event simulation model for quantitative prediction of road tunnel downtime
Section snippets
Introduction and background
Road tunnels are an essential part of modern transportation infrastructure. The construction of tunnel infrastructure is relatively expensive and time-consuming as compared to other transportation infrastructure. However, once completed, a tunnel is generally an efficient solution to transportation needs spatially and environmentally. With the increasing urbanization and environmental considerations, society and the transportation network are expected to become increasingly dependent on tunnel
Simulation methodology
This study aims to develop a Monte-Carlo-type probabilistic simulation model that will generate functionality loss events and corresponding tunnel closure duration. Firstly, a numerical metric for tunnel functionality is defined, which was adopted from a previous study (Khetwal et al., 2019) as:where Ln(t) is the number of lanes that are open to traffic at time t, Ltot is the total number of lanes, Sn(t) is the
Model implementation
The probabilistic model presented in the previous section was implemented using the Monte Carlo simulation. In this study, a five-module program was developed in MATLAB to simulate tunnel functionality time history considering random and planned disruptive events. The overall structure of the program is shown in Fig. 5. Each of the five modules is responsible for generating the occurrence and tunnel functionality loss corresponding to a specific type of event discussed in the previous section.
Simulation example and preliminary validation
While a probabilistic simulation model cannot be validated on an individual event basis, model outcome validation can be performed by comparing the simulated random event distribution with realistic tunnel operation data and observing the trend on event distribution. Because tunnel operation resilience has not been studied widely, the amount of data suitable for overall operation simulation validation is minimal. In a previous study (Khetwal et al., 2020b), realistic tunnel functionality data
Conclusion
To evaluate tunnel functionality loss and resilience quantitatively, a tunnel functionality metric was defined by its ability to accommodate through traffic. In this study, a probabilistic simulation framework was established to simulate tunnel functionality over time by considering several critical influential factors and random disruptive events. Within the proposed framework, the occurrence and severity of disruptive events were simulated using underline probabilistic models (model
CRediT authorship contribution statement
Sandeep Singh Khetwal: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing. Shiling Pei: Conceptualization, Writing – original draft, Writing – review & editing. Marte Gutierrez: Writing – review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Acknowledgement
The authors gratefully acknowledge the financial support of the University Transportation Center for Underground Transportation Infrastructure (UTC-UTI) at the Colorado School of Mines under Grant No. 69A3551747118 from the US Department of Transportation (DOT). The opinions expressed in this paper are those of the authors and not of US DOT. The authors would also like to acknowledge the assistance of Colorado Department of Transportation (especially Weiyan Chen and Steve Harrelson) for their
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