苏黎世联邦理工

Adaptive Planning of Transport Infrastructure under Uncertainty

项目介绍

ETH Zurich is one of the leading universities of the world with a strong focus on science and engineering. In 2010 it established the Singapore-ETH Centre (SEC) in collaboration with the National Research Foundation (NRF) to do interdisciplinary research on pressing problems.

The centre currently runs several research programmes with the Future Cities Laboratory (FCL) as one of the programmes. It is home to a community of over 100 PhD, postdoctoral and Professorial researchers working on diverse themes related to sustainable cities and resilient infrastructure systems. In the course of their work, researchers actively collaborate with universities, research institutes, industry, and government agencies with the aim of offering practical solutions.

The Chair of Infrastructure Management lead by Professor Dr. Bryan T. Adey in the Institute of Construction and Infrastructure Management of the Department of Civil, Environmental and Geomatic Engineering has an opening for a PhD researcher in the planning of transportation infrastructure.

Project background

In recent times, cities have experienced an unprecedented period of flux, whether triggered by disruptive technology, political upheavals, emergent social trends or the ongoing global pandemic. These growing uncertainties have prompted cities to rethink land use and transportation infrastructure provision planned for the future. In this sense, adaptive planning proposes to cope with uncertainty by committing to a few short-term actions, leaving options open for the future and continually adapting by learning how uncertainty unfolds over time. The ETH and NUS have a new project “AMIL” within the Future Cities Lab – Global Research Programme (FCL-G) that aims to integrate mobility, land use and infrastructure into a resilient, adaptive system that responds to changing needs, through a three-pronged approach. First, social network surveys in Zurich and Singapore will monitor and examine the ‘drivers of change’, by assessing changes in social and economic activity. Second, novel transport modelling and simulation techniques will be developed that can handle the unique challenges posed by the ‘city in flux’, with dynamically adaptive land use and demand responsive transportation systems. Third, exploratory modelling, decision-making under uncertainty methods (e.g. real-options) and optimization methods will be employed to formulate adaptive plans that can respond to short-term and long-term change. The project will bring tools, insights, methods and procedures that can provide decision-support for planning across relevant scales of time and space. Simulation models and software tools will be developed in consultation with an expert panel of practitioners and policymakers, with a goal to enable adaptive planning, improve resilience to shocks such as COVID-19, and reduce misalignment of provision and emerging demand in the long-term. These learnings will be applied to a study of infrastructure corridors and urban development across intercity, city-wide and local scales in both Alpine and Southeast Asian contexts, with Zurich and Singapore as the main hubs under study. The project will be guided by regular stakeholder workshops in both contexts, and will produce a suite of open-source software tools and planning recommendations developed in collaboration with an inter-agency working group for adaptive mobility, land use and infrastructure.

Job description

The goal of the research is to advance the state-of-the-art of infrastructure planning under uncertainty by developing new tools and methods for model-based adaptive planning for infrastructure systems. The research is to improve the adaptive infrastructure planning process through the development of future scenarios, the potential interventions on the system, the monitoring strategy and the selection and optimization phase. The main contributions of this research will be: 1) advancing the modelling of future uncertainty, including its spatial distribution and endogeneity; 2) developing top-down models (e.g. system dynamics) and integrating them with bottom-up models (e.g. agent-based modelling) for adaptive planning, and 3) exploring the use of advanced techniques in sequential decision-making, such as reinforcement learning, for complex planning problems to circumvent the “curse of dimensionality”.

The case study to be used in the research is the city-state of Singapore and regional connections (e.g. Singapore-Johor corridor). Potential interventions to be evaluated include but are not limited to the expansion of highways and rail infrastructure, mobility on-demand services, Integrated Transport Hubs and flexible land use policies (see, for example, the Singapore Land Transport Master Plan by LTA and the Long Term Plan Review by URA). This research will contribute to the development of a methodology to be used to plan infrastructure systems that are more responsive to future needs, and will consequently result in improved success and prosperity for the regions in which they are embedded.

The candidate is expected to work closely with other researchers in Singapore who will focus on the assessment of future societal trends, their implications on transport needs and the impact of potential interventions through agent-based models (MATSIM). Additionally, the candidate is expected to participate in regular exchanges and coordination with the research team in Zürich working on similar topics.

Your profile

The successful candidate for this PhD position will have a

  • Masters degree in spatial planning, transport planning, civil engineering, systems engineering or a related field, and
  • will have experience with computer modelling and simulation (e.g. random networks, exploratory modelling, reinforcement learning)
  • Good grasp of probability theory, traffic modelling, risk assessment, R, python and GIS.
  • Proficiency in written and spoken English.

项目概览

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欧陆, 瑞士 所在地点
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截止日期 2022-09-01
苏黎世联邦理工

院校简介

苏黎世联邦理工是国际研究型大学联盟、全球大学高研院联盟、IDEA联盟成员,是闻名全球的世界顶尖研究型大学,连续多年位居欧洲大陆高校翘首。
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