Introduction

The concept of a smart city is fast becoming a key instrument in transforming living environments in a better way to enhance the operational efficiency of a transportation system. This paper presents a framework to assess transportation performance measures and smart-growth of cities around the U.S. by including physical activity as one of the main criteria.

Methods

This study employs Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) as a multi-criteria decision analysis (MCDA) method. The proposed assessment framework is comprised of the evaluation of an individual criterion and the assessment of comprehensive results. The criteria are categorized into four groups including network performance, traffic safety, environmental impact, and physical activity. As a case example, the proposed performance measures were examined for forty-six cities in the U.S., and the required data was gathered from multiple sources.

Results

The output of the framework contains sustainability and smart-growth rankings of the selected cities as well as uncertainty and sensitivity analysis. The sensitivity analysis was utilized to determine the quantity that each performance measure or weighting factor requires to alter the smart-growth score. It has been illustrated that the dominancy between reversible pairs in the ranking is critically sensitive for almost 15% of cases.

Conclusion

The results of the proposed framework can be an effective decision supporting tool in analyzing traffic management strategies. Results from the score sensitivity calculation indicate that the proposed framework can be adopted in multifaceted transportation system performance in sustainability and smart-growth of cities.

中文翻译：

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通往可持续发展和智能增长的普遍框架：评估智能城市的多方面运输绩效指标

介绍

智慧城市的概念正迅速成为以更好的方式改善生活环境以提高运输系统的运营效率的关键工具。本文提出了一个框架，通过将体育活动作为主要标准之一，来评估美国各地城市的交通绩效衡量标准和智能增长。

方法

本研究采用了与理想解决方案相似的优先顺序技术（TOPSIS）作为多准则决策分析（MCDA）方法。拟议的评估框架包括对单个标准的评估和对综合结果的评估。这些标准分为四类，包括网络性能，流量安全，环境影响和体育活动。作为示例，对美国46个城市的拟议绩效指标进行了审查，并从多个来源收集了所需数据。

结果

该框架的输出包含所选城市的可持续性和智能增长排名，以及不确定性和敏感性分析。敏感性分析用于确定每个绩效指标或加权因子更改智能增长得分所需的数量。已经表明，在几乎15％的情况下，排名中的可逆对之间的优势极为敏感。

结论

所提出框架的结果可以作为分析交通管理策略的有效决策支持工具。分数敏感性计算的结果表明，所提出的框架可用于城市可持续发展和智能增长的多方面交通系统绩效。