Микола Кузьмінець, Ю.І. Дубовенко
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摘要

在当前条件下,人员密集的大型战时事件下的城市道路交通优化建模是一个重要问题。地理信息技术将空间分布数据的可视化和智能分析相结合,越来越多地应用于道路管理状态的规划、重建和监测。考虑到上述前提条件,我们认为在世界经验的基础上,研究在城市主要交通路线预先确定的封闭紧凑区域内优化交通强度管理方法的最佳替代方案是可取的。同时,考虑到车辆在正常情况下运动的周期性,以及借助交通灯网络自动调度(“绿波”)对其进行调控的可能性,我们将缩小任务范围。因此,我们将只分析异常高的交通表现,这种情况通常只发生在城市基础设施发生极端事件时,有大量人群参与。这类大型活动包括全球性的宗教、文化和体育活动、公众骚乱和其他一些严重扰乱公共道路网络使用惯例的活动。应当指出,这些措施往往由于这样或那样的原因导致人为地限制该网络的带宽,在进一步分析可能的情况时应考虑到这一点。因此,这项工作的目的是确定交通优化的基本因素,以便在给定的地点分配大量的人,并开发一种合适的算法来节省能源和时间的交通管理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
МУЛЬТИМОДАЛЬНЕ МОДЕЛЮВАННЯ ОПТИМІЗАЦІЇ МІСЬКОГО ДОРОЖНЬОГО ТРАФІКУ ДЛЯ ПЕРСОНАЛОЄМКИХ МАСШТАБНИХ ПОДІЙ ВІЙСЬКОВОГО ЧАСУ
In the current conditions, an important issue is the modeling of urban optimization road traffic for personnel-intensive large-scale wartime events. Geoinformation technologies, which combine visualization and intellectual analysis of spatially distributed data, are increasingly used in planning, reconstruction and monitoring of the state of road management. Taking into account the above-mentioned prerequisites, we consider it expedient to investigate, on the basis of world experience, the best alternatives for optimizing the methods of traffic intensity management in a closed compact area with predetermined routes of the main traffic in the city. At the same time, taking into account the cyclical nature of the movement of vehicles under normal conditions and the possibility of its regulation with the help of automated dispatching of the network of traffic lights ("green wave"), we will narrow down the task. Therefore, we will analyze only abnormally high manifestations of traffic, which occur, as a rule, only during the occurrence of extreme events for the city infrastructure with the participation of large masses of people. Such mega-events include religious, cultural and sports events of a global level, public riots and some other events that dramatically disrupt the established practice of using the public road network. It should be noted that such measures often lead to an artificial limitation of the bandwidth of this network for one reason or another, which should be taken into account in the further analysis of possible scenarios. Therefore, the aim of the work is to determine the basic factors for the optimization of traffic in order to distribute large masses of people in given locations and to develop a suitable algorithm for energy- and time-saving traffic management.
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