Alternative approaches to modeling the travel-demand impacts of smart growth
Alternative approaches to modeling the travel-demand impacts of smart growth
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DOI：
10.1080/01944360608976751
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发表时间：
2006-06-01
影响因子：
5.6
通讯作者：
Cervero, Robert
中科院分区：
文献类型：
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作者：
Cervero, Robert
四步出行需求预测模型从来都不是为了估计社区层面的智能增长举措(如过境村庄)对出行的影响，而是为了指导区域公路和交通投资。虽然在增强大规模模型方面取得了进展，但一些分析人士已转向后处理和直接模型，以减少建模时间和成本，并更好地捕捉邻里尺度土地利用策略对交通的影响。本文提供了大夏洛特、旧金山湾区远郊和圣路易斯县南部的铁路和交通导向型土地利用建议的直接或离线建模的例子。这些替代方法为情景测试提供了一个有用的平台，他们的结果显示，将开发集中在火车站附近可以产生可观的乘客红利。这些替代模型适合作为草图规划的补充，而不是取代传统的四步模型。
Four-step travel demand forecasting models were never meant to estimate the travel impacts of neighborhood-level smart growth initiatives like transit villages, but rather to guide regional highway and transit investments. While progress has been made in enhancing large-scale models, some analysts have turned to post-processing and direct models to reduce modeling time and cost, and to better capture the travel impacts of neighborhood-scale land use strategies. This paper presents examples of direct or off-line modeling of rail and transit-oriented land use proposals for greater Charlotte, the San Francisco Bay Area exurbs, and south St. Louis County. These alternative approaches provided a useful platform for scenario testing, and their results revealed that concentrating development near rail stations produced an appreciable ridership bonus. These alternative models are appropriate as sketch-planning supplements to, not substitutes for, traditional four-step models.