基于网络的安全服务巡逻车拥塞管理模型

Christian Yip, Phillip J. Fiorenzo, Kil Do Jung, Jaime Tupper, Yaraslau Loban, J. Santos
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引用次数: 0

摘要

交通拥堵是美国公路交通系统中最紧迫的问题之一,也是全国驾车者最关心的问题之一。这不仅会给通勤者带来心理压力,还会因浪费工作时间和提高交通成本而造成经济损失。汉普顿路大都市区是弗吉尼亚州最拥挤的城市地区之一,每年因交通造成的经济损失高达10亿美元。维吉尼亚运输部(VDOT)一直在整合安全服务巡逻(SSP)计划,通过持续部署SSP车辆来协助公路事故管理,从而更快地解决事故并提供其他减少拥堵的方法。研究小组采用系统工程方法设计了一个基于网络的建模框架,用于分析汉普顿路大都市区的交通拥堵情况。本研究的最终目标是开发一个概率模拟模型,该模型将能够分析当前系统以及在整个网络中定位SSP车辆的替代策略,并最终减轻高速公路拥堵传播的连锁反应。对结果的统计分析有望揭示该地区最具影响力的公路交通因素,并为弗吉尼亚州的驾车者提供SSP计划的其他好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A network-based congestion management model for Safety Service Patrol vehicle deployment
Traffic congestion is one of the most pressing issues in the US highway transportation systems and is a primary concern for motorists nationwide. Not only does it pose a psychological strain on commuters, it also results in monetary losses through wasted working hours and heightened transportation costs. The Hampton Roads metropolitan area is one of the most congested urban regions in the Commonwealth of Virginia, and monetary losses due to traffic have amounted to $1 billion annually. The Virginia Department of Transportation (VDOT) has been incorporating the Safety Service Patrol (SSP) program to assist highway incident management through the continuous deployment of SSP vehicles, thus resolving incidents faster and providing other means of reducing congestion. The research team has adopted a systems engineering approach for designing a network-based modeling framework for analyzing traffic congestion scenarios in the Hampton Roads metropolitan area. The end goal of this study is to develop a probabilistic simulation model that will enable the analysis of the current system as well as alternative strategies for positioning the SSP vehicles throughout the network and to ultimately alleviate the ripple effects propagated by highway congestions. Statistical analysis of results is expected to reveal the most influential highway mobility factors in the region, as well as provide other benefits of the SSP program to Virginia motorists.
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