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中国城市交通堵塞机率的计算及其政策启示 被引量:3

The Computation of Urban Transportation Congestion Probability and Its Implications for Solving Urban Transportation Problems in China
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摘要 运用数学方法,计算了城市交通堵塞的机率,量化分析了边际车辆产生的交通拥挤外部性,并进一步探讨了此研究对解决我国城市交通问题的启示。结果显示:如果城市车辆和道路同步增长,每条道路上交通堵塞的平均机率呈加速增长的态势,这个增长过程可以用抛物线口朝上的右支来刻画;并且,随着城市车辆规模的增加,边际车辆的增加造成的交通堵塞的增量呈直线上升。在现实中,城市道路增长速度远跟不上城市车辆的增长速度,这极大地增加了交通堵塞的机率。中国城市规模巨大,交通拥挤外部性明显;大城市交通用地比例低(约占城市用地的10%),城市有效交通用地比例更低,这些都是造成我国大城市交通拥挤的重要因素。针对上述研究结果,本文提出了降低我国城市交通堵塞机率的一些措施,其中,发展卫星城、建立多中心的城市空间(土地利用)格局是降低城市交通堵塞机率的最为关键的措施。 Using the mathematics method, this article calculated the urban transportation congestion probability, and analyzed negative externality of traffic congestion caused by the increasing vehicle, and further discussed the implications resulted from this study for solving urban transportation problems in China. The results show that: if urban vehicles and roads synchronously increase, on each road the traffic jam average probability exhibits the trend of the accelerating growth, which can be pictured by the parabola; and along with the size of urban vehicles increase, the traffic jam linearly increases caused by the increase of margin vehicles. In the reality, the rate of urban road increase is lower than that of urban vehicles, and much lower than that of the traffic jam probability. In China, city size is huge, so the traffic congestion externality is obvious. In the municipal areas, the share of transportation land of the whole urban land is very low (around 10%), and the share of urban effective transportation land are smaller. These are important factors affecting urban transportation congestion. In view of the above findings, this article provides some measures for reducing urban transportation jam probability, among which to develop some satellite towns or to establish multi-central land use pattern are essential.
作者 谈明洪
出处 《地理科学进展》 CSCD 北大核心 2010年第1期110-116,共7页 Progress in Geography
基金 国家自然科学基金项目(40971112) 国家科技支撑项目(2006BAB15B00)
关键词 交通堵塞 机率 启示 中国 transportation jam probability implication China
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