How information heterogeneity influences traffic congestion during hurricane evacuation

被引:2
|
作者
Verma, Rajat [1 ]
Lei, Zengxiang [1 ]
Xue, Jiawei [1 ]
Shen, Jiauyen [2 ]
Gehlot, Hemant [1 ]
Ukkusuri, Satish, V [1 ]
Murray-Tuite, Pamela [2 ]
机构
[1] Purdue Univ, Lyles Sch Civil Engn, W Lafayette, IN 47907 USA
[2] Clemson Univ, Glenn Dept Civil Engn, Clemson, SC USA
基金
美国国家科学基金会;
关键词
hurricane; evacuation; traffic; congestion; information; simulation; percolation; mobility behavior; MODEL; UNDERSTAND; TIME;
D O I
10.1109/ITSC48978.2021.9564797
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We investigate the effects of the amount and kind of information received by hurricane evacuees on the level of urban evacuation-induced traffic congestion. With the help of agent-based simulation driven by survey data for evacuees of Hurricane Matthew in Jacksonville, FL, we find that sending evacuation notices to households stands out as the most dominant factor impacting evacuation congestion. We use travel time metrics and introduce a percolation congestion index to show that congestion increases marginally by providing more mandatory than voluntary notices, which compensates for the benefits that are obtained by higher evacuation. We also observe that segments of commonly used evacuation routes in the flood-prone areas are more likely to be congested during the evacuation period than the other road segments. This study affirms the importance of evacuation notices in evacuation planning and suggests that planning agencies might benefit by strategically sending these notices to people to control peak congestion.
引用
收藏
页码:1833 / 1838
页数:6
相关论文
共 50 条
  • [21] Traffic mixing in deterministic two-lane model of Hurricane evacuation
    Tanaka, Katsunori
    Nagatani, Takashi
    Hanaura, Hirotoshi
    PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2007, 380 (490-502) : 490 - 502
  • [22] Evaluating Road Utilization during Hurricane Evacuation: A Case Study of Hurricane Ian
    Ebrahim, Ruqayah
    Li, Yitong
    Ji, Wenying
    CONSTRUCTION RESEARCH CONGRESS 2024: ADVANCED TECHNOLOGIES, AUTOMATION, AND COMPUTER APPLICATIONS IN CONSTRUCTION, 2024, : 1229 - 1237
  • [23] Modeling and predicting evacuation flows during hurricane Irma
    Lingzi Hong
    Vanessa Frias-Martinez
    EPJ Data Science, 9
  • [24] Measuring the vulnerability of disadvantaged populations during hurricane evacuation
    Bian, Ruijie
    Wilmot, Chester G.
    NATURAL HAZARDS, 2017, 85 (02) : 691 - 707
  • [25] Measuring the vulnerability of disadvantaged populations during hurricane evacuation
    Ruijie Bian
    Chester G. Wilmot
    Natural Hazards, 2017, 85 : 691 - 707
  • [26] Machine Learning for the Activation of Contraflows during Hurricane Evacuation
    Burris, John W.
    Shrestha, Rahul
    Gautam, Bibek
    Bista, Bibidh
    PROCEEDINGS OF THE FIFTH IEEE GLOBAL HUMANITARIAN TECHNOLOGY CONFERENCE GHTC 2015, 2015, : 254 - 258
  • [27] The Brewing Storm: ICU Evacuation during Hurricane Sandy
    King, Mary
    Dorfman, Molly
    CRITICAL CARE MEDICINE, 2013, 41 (12)
  • [28] Modeling and predicting evacuation flows during hurricane Irma
    Hong, Lingzi
    Frias-Martinez, Vanessa
    EPJ DATA SCIENCE, 2020, 9 (01)
  • [29] Geophysical and Social Influences on Evacuation Decision-Making: The Case of Hurricane Irma
    Ersing, Robin L.
    Pearce, Christianne
    Collins, Jennifer
    Saunders, Michelle E.
    Polen, Amy
    ATMOSPHERE, 2020, 11 (08)
  • [30] How does evacuation risk change over time? Influences on evacuation strategies during accidental toxic gas releases
    Zhang, Weihua
    Li, Chaoying
    Gai, Wenmei
    INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2024, 108