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首页> 外文学位 >Developing Static and Dynamic Multimodal Transportation System Models to Estimate Individual Commuter Footprints Using ArcGIS, Google Maps and Here360.
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Developing Static and Dynamic Multimodal Transportation System Models to Estimate Individual Commuter Footprints Using ArcGIS, Google Maps and Here360.

机译：开发静态和动态多式联运系统模型，以使用ArcGIS，Google Maps和Here360估算各个通勤者的足迹。

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摘要

According to the U.S. Greenhouse Gas (GHG) Emissions and Sinks (2015), 27% of GHG emissions in the U.S. are produced by the Transportation sector, second only to the Electric Power Industry with 29%. A vast majority of these emissions are associated with single occupant (Drive-alone) automobile trips. While many policies exist for incentivizing alternative transportation modes, especially for commuting trips, only a few tools are available for estimating the potential benefits. Furthermore, the potential benefits are estimated using aggregate models and assumptions of commute behavior and existing transportation systems. Accordingly, to improve the accuracy of these estimates and potential impact of these policies, this research focuses on developing models to estimate footprints of individual commuters using real-world multimodal transportation systems.;Two different multimodal transportation system modeling approaches were developed and compared: 1. static models were developed using ESRI's ArcGIS 10.5 and its Network Analyst extension and Model Builder programming language, and 2. dynamic models were developed by the implementation of Google Maps and Here360 APIs in R Studio. Comparisons of the results of the static and dynamic models were further analyzed under two conditions: free flow and congested traffic. The developed multimodal transportation systems included six travel choices: Drive-alone, Bicycle, Walking, Bicycle-bus, Walking-bus and Carpool. The developed models computed individualized commuter estimates for six travel measures: travel time, distance and cost, and CO2, VOC, and NOX emissions. A real-world case study was developed for commuters in Fresno, CA. A mixture of real-life and synthetic data comprising 218 commuters was used in the study.;Conclusions of this research include valuable insights about merits and limitations of the static and dynamic modeling approaches. Additionally, the results include multiple comparisons between the travel measure estimates of the two modeling approaches using different travel modes, and under the two traffic conditions. Outcomes of this research could prove valuable in transforming the existing approaches for estimating impacts of policies on alternative transportation incentives.
机译：根据美国温室气体（GHG）排放和汇（2015），美国27％的温室气体排放是由运输部门产生的，仅次于电力行业的29％。这些排放中的绝大多数与单人（单人驾驶）汽车旅行有关。尽管存在许多鼓励替代交通方式的政策，尤其是通勤旅行的政策，但只有少数工具可用来估算潜在的利益。此外，潜在收益是使用通勤行为和现有运输系统的综合模型和假设进行估算的。因此，为了提高这些估算的准确性和这些政策的潜在影响，本研究着重于开发使用现实世界中的多式联运系统估算单个通勤者足迹的模型。静态模型是使用ESRI的ArcGIS 10.5及其Network Analyst扩展和Model Builder编程语言开发的； 2.动态模型是通过在R Studio中实现Google Maps和Here360 API来开发的。在两种情况下，对静态和动态模型结果的比较进行了进一步分析：自由流和拥塞交通。发达的多式联运系统包括六个旅行选择：单人驾驶，自行车，步行，自行车，步行巴士和拼车。所开发的模型计算出六个行程量度的个人通勤者估计：行程时间，距离和成本，以及CO2，VOC和NOX排放量。在加利福尼亚州弗雷斯诺市为通勤者开发了一个实际案例研究。这项研究使用了包含218名通勤者的现实生活和综合数据的混合物。该研究的结论包括有关静态和动态建模方法的优缺点的宝贵见解。此外，结果包括在两种交通条件下使用不同的出行方式的两种建模方法的出行度量估计之间的多次比较。这项研究的成果可能会证明对改变现有方法以评估政策对替代性交通刺激措施的影响是有价值的。

著录项

  • 作者

    Schwanz, Annemarie.;

  • 作者单位

    California State University, Fresno.;

  • 授予单位 California State University, Fresno.;
  • 学科 Engineering.;Civil engineering.;Transportation.
  • 学位 M.S.
  • 年度 2017
  • 页码 69 p.
  • 总页数 69
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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