基于开放数据的MATSim场景设计与分析:墨西拿市用例

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Annamaria Ficara;Maria Fazio;Antonio Celesti;Massimo Villari
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引用次数: 0

摘要

近年来,由于越来越多的汽车驶入老旧的城市平面,我们的城市变得越来越拥挤。因此,即使是中小城市的交通时间也与大城市不相上下。为了改善现代城市的交通管理,可以使用特定的模拟工具来分析不同交通计划对交通的影响,从而为每个城市找到最合适的解决方案。然而,没有高级计算机技能的城市交通管理者通常很难使用这些工具。在本文中,我们利用多代理交通模拟(MATSim)提供了一个简单的工具,便于最终用户更好地规划私人和公共交通的交通策略。特别是,从墨西拿市提供的公开数据出发,我们开发了一款能够处理 MATSim 事件的软件工具。此外,我们还提出了一种衡量标准,用于评估道路对骑自行车者的安全性。从软件提供的实验结果中,我们发现了超载最严重的路段,并估算了按出发时间小时计算的旅行时间分布。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and Analysis of a MATSim Scenario From Open Data: The Messina City Use Case
In the last years, our cities become more and more crowded due to the increasing number of cars into old city planes. So, even small/medium cities experience a travel time comparable with the bigger ones. To improve mobility management in modern cities, specific simulation tools can be used to analyze the impact of different mobility plans on mobility and, therefore to find the most suitable solution for each city. However, these tools are often hard to be used by city traffic managers without advanced computer skills. In this article, we used a multiagent transport simulation (MATSim) to provide a simple tool that can be easily used by end-users to better plan mobility strategies for both private and public transportation. In particular, starting from the open data provided by the city of Messina, we have implemented a software tool able to process MATSim events. Moreover, we propose a metric to estimate the safety of roads for cyclists. From the experimental results provided by the proposed software, we are able to discover the most overloaded links and estimate the travel time distribution by hour of departure time.
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS
CiteScore
18.50
自引率
11.50%
发文量
812
审稿时长
6 months
期刊介绍: The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.
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