2 research outputs found

    Considering automated vehicle deployment uncertainty in the design of optimal parking garages using real options

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    Parking garages are often currently designed assuming that parking demand will be stable over their lifetime. The looming mobility shift towards automated vehicles (AVs), however, makes parking demand highly uncertain, with some scenarios leading to its complete disappearance at some time in the near future. The design of optimal parking garages needs to take this uncertainty into consideration and may lead to parking garages that can easily be transformed for other uses when beneficial.In situations of large future demand uncertainty, infrastructure owners are increasingly using the real options method to help evaluate the potential benefits of paying more for construction of flexibly designed infrastructure. The real options method, helps owners, to avoid under-, or overinvesting in infrastructure, through the minimisation of their risks. In this work, a methodology, which uses the real options method, is proposed to determine the optimal design of a parking garage located within a residential building.The methodology is used, together with estimates of the uncertainty in the future parking demand due to deployment of AVs, Monte Carlo simulations of the possible futures, stakeholder costs for operation and refurbishment costs for each of the different design alternatives and intervention strategies, to estimate the net benefits over the life-time of the parking garage. The methodology is used to evaluate designs and intervention strategies for the 14000 m2 463-lot parking garage in a residential building in western Switzerland. The designs are a traditional design and a flexible design. The construction of a building according to the two design approaches would bear costs of 10 and 11 million CHF, respectively. The intervention strategies for the traditional building are a single stage intervention strategy and a no intervention strategy. The intervention strategies for the flexible building are a single-stage intervention strategy and a multi-stage intervention strategy. The traditionally designed building costs 2 million CHF to demolish and 29 million CHF to reconstruct as a residential building. The flexibly designed building costs 21 million to adapt for residential use.It is shown that the flexible design and a multi-stage intervention strategy (i.e. transforming the parking garage floor by floor on an as needed basis), provides the highest net benefits (2.2 million CHF). The flexible design and a single-stage intervention strategy provides the second highest net benefits (1.3 million CHF). A traditional design with a single-stage intervention strategy provides 0.5 million CHF in net benefit, and the traditional design with a no intervention strategy results in a net loss of 3.0 million CHF. A sensitivity analysis shows the robustness of the options.Since the use of the proposed methodology helps owners identify all the possible designs and intervention strategies as well as increases their ability to accurately estimate the net-benefit of their decisions, it is concluded that it is advantageous for owners to use the proposed methodology in determining the optimal design of parking garages. Its use will help ensure that they are optimally positioned to deal with the uncertain future

    Exploratory modelling for transport infrastructure planning under future uncertainty

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    Planning transport infrastructure is particularly difficult due to infrastructure’s long-lived nature, unpredictable technological progress and changing mobility trends in society. In complex systems facing major uncertainties, exploratory modelling can help define salient system characteristics and discover potential risks and opportunities by evaluating large ensembles of potential conditions during the planning process. This paper demonstrates how exploratory modelling can provide planning support for a federal highway from Dübendorf to Hinwil in Zürich, Switzerland. We model the future traffic flows at peak hours considering uncertainty in urban development, jobs distribution and future modal share. Current road infrastructure and further potential capacity expansions and reallocations are then tested on their robustness to provide adequate performance (in terms of travel delays) in multiple future scenarios. We use quantitative methods to identify the subset of scenarios representing risks and opportunities for the infrastructure system. The visualization of such subset of scenarios in uncertainty maps can help target interventions only when needed
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