Estimating long-term impacts of tunnel infrastructure development on urban sustainability using granular computing

Abstract The rapid growth of metro construction causes adverse effects and even threats; thus, the sustainability assessment becomes extremely important but complex. A novel framework integrating System Dynamics (SD) and Granular Computing (GrC) is proposed to estimate the long-term impacts of tunnel infrastructure development on urban sustainability. An integrated system, consisting of social, economic, and environmental sub-systems, is developed to model urban sustainability. A comprehensive method that integrates Analytic Hierarchy Process (AHP) and entropy weighting methods is proposed to provide a more reliable and objective way to sort information and identify the weight of each criterion. The SD model is established to interpret the relationships of the sub-systems and predict future development. The GrC approach is employed to model and reveal the uncertainties in the SD model and improve reliability. A project case is selected to verify the proposed approach. The results show that the economic system (S2) has better performance than the other two systems, namely social (S1) and environmental systems (S3), which indicates the development of metro lines can boost economic growth. The long-term impact of tunnel infrastructure development on urban sustainability fluctuates over time. The developed approach can be used as a decision tool to assess and estimate the long-term impacts of tunnel infrastructure development on urban sustainability with the consideration of uncertainties in factor measurement and provide decision support for enhancing sustainable urban development.

[1]  Matthew C. Cohen,et al.  A Systematic Review of Urban Sustainability Assessment Literature , 2017 .

[2]  Harish Garg,et al.  Uncertain database retrieval with measure - Based belief function attribute values under intuitionistic fuzzy set , 2021, Inf. Sci..

[3]  Wen Song,et al.  A multistage risk decision making method for normal cloud model considering behavior characteristics , 2019, Appl. Soft Comput..

[4]  Ian Jefferson,et al.  Sustainability assessment for urban underground utility infrastructure projects , 2018 .

[5]  Eda Beyazit,et al.  Are wider economic impacts of transport infrastructures always beneficial? Impacts of the Istanbul Metro on the generation of spatio-economic inequalities ☆ , 2015 .

[6]  J. B. Park,et al.  Characteristics of PM10 and CO2 concentrations on 100 underground subway station platforms in 2014 and 2015 , 2017 .

[7]  Lotfi A. Zadeh,et al.  Toward a theory of fuzzy information granulation and its centrality in human reasoning and fuzzy logic , 1997, Fuzzy Sets Syst..

[8]  T. Dawood,et al.  Toward urban sustainability and clean potable water: Prediction of water quality via artificial neural networks , 2020 .

[9]  Yongtae Park,et al.  A dynamic feasibility analysis of public investment projects: An integrated approach using system dynamics and agent-based modeling , 2015 .

[10]  Guannan Zhou,et al.  Numerical analysis and application of the construction method for the small interval tunnel in the turn line of metro , 2020, Science progress.

[11]  Seyed Sina Mohri,et al.  Locating key stations of a metro network using bi-objective programming: discrete and continuous demand mode , 2019, Public Transport.

[12]  Witold Pedrycz,et al.  Granular Computing in Fuzzy Modeling and Data Mining , 2001 .

[13]  A. Theodore Forrester,et al.  Photoelectric Mixing As a Spectroscopic Tool , 1961 .

[14]  Shohel Amin,et al.  Resilience assessment of safety system at subway construction sites applying analytic network process and extension cloud models , 2020, Reliab. Eng. Syst. Saf..

[15]  Shuming Bao,et al.  An integrated sustainable development approach to modeling the eco-environmental effects from urbanization , 2011 .

[16]  L. Anselin,et al.  Measuring the benefits of air quality improvement: a spatial hedonic approach , 1998 .

[17]  Deyi Li,et al.  A new cognitive model: Cloud model , 2009, Int. J. Intell. Syst..

[18]  Xianguo Wu,et al.  Perceiving safety risk of buildings adjacent to tunneling excavation: An information fusion approach , 2017 .

[19]  Jesús Carrera,et al.  Assessment of the barrier effect caused by underground constructions on porous aquifers with low hydraulic gradient: A case study of the metro construction in Barcelona, Spain , 2015 .

[20]  Brian Edwards.  Sustainability and the Design of Transport Interchanges , 2011 .

[21]  T. Y. Lin,et al.  Granular Computing on Binary Relations II Rough Set Representations and Belief Functions , 1998 .

[22]  Qinghua Hu,et al.  Probability granular distance-based fuzzy rough set model , 2021, Appl. Soft Comput..

[23]  Leandro dos Santos Coelho,et al.  Nonlinear black-box system identification through coevolutionary algorithms and radial basis function artificial neural networks , 2020, Appl. Soft Comput..

[24]  Chuan He,et al.  Analysis of ground settlement induced by Earth pressure balance shield tunneling in sandy soils with different water contents , 2019, Sustainable Cities and Society.

[25]  C. Sioutas,et al.  Particulate matter (PM) concentrations in underground and ground-level rail systems of the Los Angeles Metro , 2011 .

[26]  W. L. Shirley,et al.  Social Vulnerability to Environmental Hazards , 2003 .

[27]  Satish Chandra,et al.  Saturation Flow Model for Signalized Intersection under Mixed Traffic Condition , 2018, Transportation Research Record: Journal of the Transportation Research Board.

[28]  Andrzej Skowron,et al.  Interactive granular computing , 2016 .

[29]  Y. Phillis,et al.  Evaluating strategies for sustainable development: fuzzy logic reasoning and sensitivity analysis , 2004 .

[30]  Volker Coors,et al.  Combining system dynamics model, GIS and 3D visualization in sustainability assessment of urban residential development , 2012 .

[31]  Mutasem El-Fadel,et al.  Vehicular emissions and air quality assessment in roadway tunnels: the Salim Slam tunnel , 2000 .

[32]  S. Shen,et al.  Ground fissures in Xi’an and measures to prevent damage to the Metro tunnel system due to geohazards , 2016, Environmental Earth Sciences.

[33]  Limao Zhang,et al.  Improved Fuzzy Bayesian Network-Based Risk Analysis With Interval-Valued Fuzzy Sets and D–S Evidence Theory , 2020, IEEE Transactions on Fuzzy Systems.

[34]  Dora Foti,et al.  Mechanical behavior of buildings subjected to impulsive motions , 2016, Bulletin of Earthquake Engineering.

[35]  Q. Shen,et al.  A system dynamics model for the sustainable land use planning and development , 2009 .

[36]  Nicholas J. Ashbolt,et al.  Review of multi-criteria decision aid for integrated sustainability assessment of urban water systems , 2008 .

[37]  C.Y. Jim.  Green-space preservation and allocation for sustainable greening of compact cities , 2004 .

[38]  Claudio A. Agostini,et al.  The Anticipated Capitalisation Effect of a New Metro Line on Housing Prices , 2008 .

[39]  Kim Bang Salling,et al.  Applying sustainability theory to transport infrastructure assessment using a multiplicative ahp decision support model , 2015 .

[40]  Li He,et al.  Study of the human evacuation simulation of metro fire safety analysis in China , 2008 .

[41]  Manfred Boltze,et al.  Approaches to Achieve Sustainability in Traffic Management , 2016 .

[42]  Jianhua Hu,et al.  Enhanced Quantile Normalization of Microarray Data to Reduce Loss of Information in Gene Expression Profiles , 2007, Biometrics.

[43]  Mu-Yen Chen,et al.  A hybrid fuzzy time series model based on granular computing for stock price forecasting , 2015, Inf. Sci..

[44]  Yanyong Xiang,et al.  Assessment and control of metro-construction induced settlement of a pile-supported urban overpass , 2008 .

[45]  Xiuling Wang,et al.  Karst geology and mitigation measures for hazards during metro system construction in Wuhan, China , 2020, Natural Hazards.

[46]  Xing Xu,et al.  Methodology for Assessing the Sustainability of Metro Systems Based on Emergy Analysis , 2012 .

[47]  Bernadette O’Regan,et al.  Using system dynamics to model the interaction between environmental and economic factors in the mining industry , 2006 .

[48]  M. Warner,et al.  Cities and Sustainability , 2015 .

[49]  Himanshu Gupta,et al.  Monitoring and analysis of PM10 concentration at Delhi Metro construction sites , 2015 .

[50]  S. Shen,et al.  Analysis of Factors in Land Subsidence in Shanghai: A View Based on a Strategic Environmental Assessment , 2016 .

[51]  U. Alola,et al.  The role of renewable energy, immigration and real income in environmental sustainability target. Evidence from Europe largest states. , 2019, The Science of the total environment.

[52]  Hongyu Chen,et al.  Vulnerability modeling, assessment, and improvement in urban metro systems: A probabilistic system dynamics approach , 2021, Sustainable Cities and Society.

[53]  J. Fiksel.  Sustainability and Resilience: Toward a Systems Approach , 2006, IEEE Engineering Management Review.

[54]  Yige Wang,et al.  A Comprehensive Assessment Approach for Water-Soil Environmental Risk during Railway Construction in Ecological Fragile Region Based on AHP and MEA , 2020, Sustainability.

[55]  Shaoming Liao,et al.  Shield tunneling and environment protection in Shanghai soft ground , 2009 .

[56]  H. Zhang,et al.  Impacts of land use/land cover change and socioeconomic development on regional ecosystem services: The case of fast-growing Hangzhou metropolitan area, China , 2013 .

[57]  Chao Zou,et al.  Assessment of ventilation noise impact from metro depot with over-track platform structure on workers and nearby inhabitants , 2019, Environmental Science and Pollution Research.

[58]  Piotr Gołębiowski,et al.  Approach to the Proecological Distribution of the Traffic Flow on the Transport Network from the Point of View of Carbon Dioxide , 2020, Sustainability.

[59]  Z. Chang.  Financing new metros—The Beijing metro financing sustainability study , 2014 .

[60]  Lei Li,et al.  Color Image Segmentation Algorithms based on Granular Computing Clustering , 2014 .

[61]  Miroslaw J. Skibniewski,et al.  Developing a cloud model based risk assessment methodology for tunnel-induced damage to existing pipelines , 2015, Stochastic Environmental Research and Risk Assessment.

[62]  A. Alola.  The trilemma of trade, monetary and immigration policies in the United States: Accounting for environmental sustainability. , 2019, The Science of the total environment.

[63]  Tsau Young Lin,et al.  Granular Computing: Fuzzy Logic and Rough Sets , 1999 .

[64]  Yue Pan,et al.  A BIM-data mining integrated digital twin framework for advanced project management , 2021 .

[65]  James Aronson,et al.  Restoring natural capital : science, business, and practice , 2007 .

[66]  A. Gospodini.  Urban development, redevelopment and regeneration encouraged by transport infrastructure projects: The case study of 12 European cities , 2005 .

[67]  J. Lai,et al.  Experimental study on the effect of water gushing on loess metro tunnel , 2020, Environmental Earth Sciences.

[68]  Julio J. Ochoa,et al.  The application of urban sustainability indicators – A comparison between various practices , 2011 .

[69]  Bo Zhang,et al.  The Quotient Space Theory of Problem Solving , 2003, Fundam. Informaticae.

[70]  Jian Gu,et al.  Optimizing Bus Line Based on Metro-Bus Integration , 2020 .

[71]  Wolfgang Maennig,et al.  Road noise exposure and residential property prices: Evidence from Hamburg , 2011 .

[72]  Andrzej Skowron,et al.  Toward Problem Solving Support Based on Big Data and Domain Knowledge: Interactive Granular Computing and Adaptive Judgement , 2016 .

[73]  Yiyu Yao,et al.  Granular Computing: basic issues and possible solutions , 2007 .

[74]  B. Cohen.  Urbanization in developing countries: Current trends, future projections, and key challenges for sustainability , 2006 .

[75]  R. D. Groot,et al.  Function-analysis and valuation as a tool to assess land use conflicts in planning for sustainable, multi-functional landscapes , 2006 .

[76]  Yiyu Yao,et al.  Rough sets, neighborhood systems and granular computing , 1999, Engineering Solutions for the Next Millennium. 1999 IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.99TH8411).

[77]  Xianguo Wu,et al.  Towards a Fuzzy Bayesian Network Based Approach for Safety Risk Analysis of Tunnel‐Induced Pipeline Damage , 2016, Risk analysis : an official publication of the Society for Risk Analysis.

[78]  Dennis Y N Li,et al.  Developing Metro Systems in the People’s Republic of China: Policy and Gaps , 2006 .

[79]  Guoyin Wang,et al.  Granular computing: from granularity optimization to multi-granularity joint problem solving , 2016, Granular Computing.

[80]  P. Zhao,et al.  The impact of metro services on housing prices: a case study from Beijing , 2019 .

[81]  Y. Liu,et al.  Community response to construction noise in three central cities of Zhejiang province, China. , 2017, Environmental pollution.

[82]  Chen Chen,et al.  A novel learning cloud Bayesian network for risk measurement , 2020, Appl. Soft Comput..

[83]  Xizhao Wang,et al.  A review on neural networks with random weights , 2018, Neurocomputing.

[84]  Lieyun Ding,et al.  Development of web-based system for safety risk early warning in urban metro construction , 2013 .

[85]  Ronghui Tan,et al.  The effect of new metro stations on local land use and housing prices: The case of Wuhan, China , 2019, Journal of Transport Geography.

[86]  Mukesh Singhal,et al.  The Role of Cloud Computing Architecture in Big Data , 2015 .

[87]  Enrique Herrera-Viedma,et al.  Estimating incomplete information in group decision making: A framework of granular computing , 2020, Appl. Soft Comput..

[88]  Y. Barlas,et al.  Environmental sustainability in an agricultural development project: a system dynamics approach. , 2002, Journal of environmental management.

[89]  D. Sheridan,et al.  Social Vulnerability to Environmental Hazards , 2010 .

[90]  Hiroshi Ishidaira,et al.  Sustainability Analysis for Yellow River Water Resources Using the System Dynamics Approach , 2002 .

[91]  Yi Wang,et al.  An Analysis of the Interactions between Adjustment Factors of Saturation Flow Rates at Signalized Intersections , 2020 .

[92]  Witold Pedrycz,et al.  Granular Computing: Perspectives and Challenges , 2013, IEEE Transactions on Cybernetics.

[93]  Jingtao Yao,et al.  A granular computing framework for self-organizing maps , 2009, Neurocomputing.