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Challenges to evaluation of CO2 impacts of intelligent transportation systems

机译:智能交通系统对CO 2 影响评估的挑战

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ITS systems can help reduce CO2 emissions in three different ways, which need to be evaluated using different modeling paradigms. The ITS systems that reduce demand for vehicle travel should be analyzed using regional transportation planning models that explicitly represent modal choice and pricing sensitivity of travel choices. The ITS systems that improve vehicle operating efficiency should be evaluated using microscopic models of the effects on individual vehicles, and the results should be extrapolated to the system level based on travel statistics. ITS systems that improve infrastructure efficiency will generally require use of microscopic traffic simulation models, combined with new data representing how driver behavior is influenced by these systems in practice. Finally, concerns about latent and induced demand effects of transportation improvements need to be addressed with new research that reveals the real elasticities of travel demand.
机译:ITS系统可以通过三种不同的方式帮助减少CO 2 排放,这需要使用不同的建模范例进行评估。应当使用区域交通规划模型来分析减少车辆出行需求的ITS系统,该模型应明确表示出行选择的方式选择和价格敏感性。应该使用微观模型对单个车辆的影响进行评估,以提高车辆运行效率的ITS系统,并应基于行驶统计将结果推算到系统级别。提高基础设施效率的ITS系统通常将需要使用微观交通模拟模型,并结合表示在实践中这些系统如何影响驾驶员行为的新数据。最后,需要通过揭示旅行需求真正弹性的新研究来解决对运输改善的潜在和诱发需求影响的担忧。

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