Critical Infrastructure Renewal: A Framework for Fuzzy Logic Based Risk Assessment and Microscopic Traffic Simulation Modelling

被引:2
|
作者
Alam, M. D. Jahedul [1 ]
Habib, Muhammad Ahsanul [1 ,2 ]
Quigley, Kevin [3 ,4 ]
机构
[1] Dalhousie Univ, Civil & Resource Engn, Halifax, NS B3H 4R2, Canada
[2] Dalhousie Univ, Sch Planning, Halifax, NS B3H 4R2, Canada
[3] Dalhousie Univ, MacEachen Inst Publ Policy & Governance, Halifax, NS B3H 4R2, Canada
[4] Dalhousie Univ, Sch Publ Adm, Halifax, NS B3H 4R2, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
re-decking; fuzzy logic; delay probability; micro simulation; traffic impacts;
D O I
10.1016/j.trpro.2017.05.164
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This paper presents a comprehensive framework for risk assessment and micro simulation modelling to assess traffic impacts during re-decking of a major suspension bridge identified as Critical Infrastructure (CI) in Halifax, Canada. The bridge is being replaced while maintaining traffic during day time. As re-decking is relatively a rare and unknown construction event for a Cable Bridge, unexpected risk event and uncertainty would be associated with complex engineering manoeuvring during the re-decking of the bridge. Therefore, this study proposes a fuzzy logic approach to estimate the construction related bridge opening delay, and subsequently develops a micro simulation-based traffic network model to assess the traffic impacts on transport network. Weather data, traffic volume and signal data obtained from multiple data sources have been used during the risk assessment and micro simulation modelling. The results suggest that the likelihood of bridge opening delay could range from 18%-30% for an hour period to 40% for 3 hour period depending on the level of consequence on any day in December. The average potential delay is obtained as 22 minutes, 1.5 hours, and 2.6 hours for low consequence, medium consequence, and high consequence respectively. Based on the delay analysis, this study evaluates three alternative bridge opening delay scenarios. It is observed that the increment in number of operating vehicles becomes steady at 30% suggesting the network has reached its capacity. The results also reveals that any delay over 2 hours in bridge opening would add a slight change to the impacts on the network. This study will help policy-makers to develop risk mitigation plans and contingencies to ensure better management of traffic during 18 months long re-decking of this critical infrastructure. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:1397 / 1415
页数:19
相关论文
共 50 条
  • [21] Framework of microscopic traffic flow simulation on highway infrastructure system under hazardous driving conditions
    [J]. Chen, Suren (suren.chen@colostate.edu), 1600, Bellwether Publishing, Ltd. (02):
  • [22] GENETIC FUZZY LOGIC APPROACH TO LOCAL RAMP METERING CONTROL USING MICROSCOPIC TRAFFIC SIMULATION
    Yu, X. F.
    Xu, W. L.
    Alam, F.
    Potgieter, J.
    Fang, C. F.
    [J]. 2012 19TH INTERNATIONAL CONFERENCE MECHATRONICS AND MACHINE VISION IN PRACTICE (M2VIP), 2012, : 290 - 297
  • [23] Research of Intersection Traffic Signal Control and Simulation Based on Fuzzy Logic
    Zhu, Chunxia
    Wang, Tiying
    Li, Jinsong
    [J]. 2018 2ND INTERNATIONAL WORKSHOP ON RENEWABLE ENERGY AND DEVELOPMENT (IWRED 2018), 2018, 153
  • [24] Study on Optimal Control and Simulation for Urban Traffic Based on Fuzzy Logic
    Li, Junce
    Zhang, Huazhong
    [J]. INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTATION TECHNOLOGY AND AUTOMATION, VOL 1, PROCEEDINGS, 2008, : 936 - 940
  • [25] A fuzzy logic-based risk assessment framework for the crude oil transportation supply chain
    Ilyas, Muhammad
    Jin, Zhihong
    Ullah, Irfan
    Almujibah, Hamad
    [J]. OCEAN ENGINEERING, 2024, 311
  • [26] Financial Risk Assessment Model Based on Fuzzy Logic
    Yang, Xiuqiong
    [J]. JOURNAL OF ELECTRICAL SYSTEMS, 2024, 20 (01) : 192 - 205
  • [27] Fuzzy Logic based Modelling and Simulation Approach for The estimation of Tire Forces
    Jayachandran, R.
    Ashok, S. Denis
    Narayanan, S.
    [J]. INTERNATIONAL CONFERENCE ON DESIGN AND MANUFACTURING (ICONDM2013), 2013, 64 : 1109 - 1118
  • [28] Modeling and simulation of logistic processes: risk assessment with a fuzzy logic technique
    Gajovic, Vladimir
    Kerkez, Marija
    Kocovic, Jelena
    [J]. SIMULATION-TRANSACTIONS OF THE SOCIETY FOR MODELING AND SIMULATION INTERNATIONAL, 2018, 94 (06): : 507 - 518
  • [29] A GIS-based framework for high-level climate change risk assessment of critical infrastructure
    Hawchar, Lara
    Naughton, Owen
    Nolan, Paul
    Stewart, Mark G.
    Ryan, Paraic C.
    [J]. CLIMATE RISK MANAGEMENT, 2020, 29
  • [30] The Design and Simulation of Intelligent Traffic Signal Control System Based on Fuzzy Logic
    Lin, Yi
    [J]. FOUNDATIONS OF INTELLIGENT SYSTEMS (ISKE 2013), 2014, 277 : 965 - 973