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首页> 外文期刊>Natural Hazards Review >Development of a Large-Scale Traffic Simulation Model for Hurricane Evacuation—Methodology and Lessons Learned
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Development of a Large-Scale Traffic Simulation Model for Hurricane Evacuation—Methodology and Lessons Learned

机译：大型飓风疏散交通仿真模型的开发—方法和经验教训

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This paper focuses on traffic modeling of large-scale hurricane evacuation networks. Several research efforts to date have addressed the evacuation problem from a local perspective. The largest network found in the open literature on microscopic simulation of evacuation operations was of an area 45 miles long and 15 miles wide. The current study models 10 cities with a total length of approximately 2,000 miles of roadway including freeways, arterials, and local streets in two regions in Virginia—the Hampton Roads region and the city of Richmond. This research accomplished the following objectives: (1) estimate the traffic performance of evacuation routes and other major arterial streets; (2) locate the major bottlenecks, congestion, or other operational difficulties in the network; (3) estimate the total network evacuation time; and 4) recommend amendments to the traffic control plan to improve the traffic performance. The simulation results led to the following conclusions: (1) for a category 4 storm with high hotel occupancy, almost all vehicles (99%) were able to exit the network by the end of 27 h; (2) traffic demand on I-64 exceeded capacity for the section between I-64/Fort Eustis Blvd. and I-64/I-295 interchanges, significantly reducing the speed of evacuating vehicles; (3) the reversed lanes can carry more vehicles than their current assigned demand; and (4) for a category 3 storm, the throughput values for different evacuation routes are nearly the same with or without lane reversal. The modeling lessons learned from this research are also documented in the paper. For the network model development, geographic information system maps and a text processing scripting language (e.g., PERL) are shown to be useful tools. Parallel processing is recommended, especially for conducting statistical analysis of output data, given the enormously high run times (25-30 h in the current research) for the detailed simulations. The limitations of microscopic simulation in handling large-scale networks are identified and remedies are suggested.
机译：本文着重于大型飓风疏散网络的流量建模。迄今为止，已有几项研究工作从局部角度解决了疏散问题。关于疏散操作的微观模拟的公开文献中发现的最大网络是45英里长和15英里宽的区域。当前的研究对10个城市进行了建模，这些城市的道路总长度约为2,000英里，包括高速公路，干线和弗吉尼亚州两个地区（汉普顿路地区和里士满市）的当地街道。这项研究实现了以下目标：（1）估算疏散路线和其他主要干道的交通性能； （2）查找网络中的主要瓶颈，拥塞或其他运营困难； （3）估算总网络疏散时间； 4）建议对交通管制计划进行修订，以改善交通绩效。仿真结果得出以下结论：（1）对于酒店入住率较高的第4类风暴，几乎所有车辆（99％）都能在27 h之前退出网络； （2）I-64 / Eustis大道之间的路段对I-64的交通需求超出了容量。和I-64 / I-295互换，大大降低了疏散车辆的速度； （3）倒车道可运载的车辆超过其当前分配的需求； （4）对于第3类暴风雨，无论有无车道逆转，不同疏散路线的吞吐量值几乎相同。本文还记录了从这项研究中学到的建模经验。对于网络模型开发，地理信息系统地图和文本处理脚本语言（例如PERL）显示为有用的工具。考虑到详细模拟的运行时间非常长（本研究中为25-30小时），建议使用并行处理，尤其是对输出数据进行统计分析时。微观模拟在处理大型网络中的局限性被发现并提出了补救措施。

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