Original Articles

The Computation of Urban Transportation Congestion Probability and Its Implications for Solving Urban Transportation Problems in China

Expand
  • Institute of Geographic Science and National Resources Researches, CAS, Beijing 100101, China

Online published: 2010-01-25

Abstract

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.

Cite this article

TAN Minghong . The Computation of Urban Transportation Congestion Probability and Its Implications for Solving Urban Transportation Problems in China[J]. PROGRESS IN GEOGRAPHY, 2010 , 29(1) : 110 -116 . DOI: 10.11820/dlkxjz.2010.01.015

References


[1]   O'Sullivan A. Urban economics. Beijing: Citic Publishing House, 2002, 546-608.

[2]   Pucher J, Korattyswaropam N, Mittal N, et al. Urban transport crisis in India. Transport Policy, 2005, 12: 185-198.

[3]  Tadaki S, Nishinari K, Kikuchi M, et al. Analysis of congested flow at the upper stream of a tunnel. Physica A, 2002, 315: 156-162.

[4]   Chen H, Ganesan S, Jia B. Environmental challenges of post-reform housing development in Beijing. Habital International, 2005, 29: 571-589.

[5]   Vasconcellos E A d. Urban change, mobility and transport in S?觔o Paulo: three decades, three cities. Transport Policy, 2005, 12: 91-104.

[6]   Fujita M. Urban economic theory: land use and city size. New York: Cambridge University Press, 1989, 226-270.

[7]   Sim L L, Malone-Lee L C, Chin K H L. Integrating land use and transport planning to reduce work-related travel: a case study of Tampines Regional Centre in Singapore. Habital International, 2001, 25: 399-414.

[8]   北京市统计局, 国家统计局北京调查总队. 北京市统计年鉴. 北京: 中国统计出版社, 2006,75.

[9]   国家统计局. 国际统计年鉴. 北京: 中国财政经济出版社, 2007, 123-128.

[10] Tan M, Li X, Lu C. Urban land expansion and arable land loss of the major cities in China in the 1990s. Science in China (Ser. D Earth Sciences), 2005, 48: 1492-1500.

[11] 刘大庆. 2004年香港经济年鉴. 香港: 香港经济出版社, 2005, 347.

[12] Lam W H K, Tam M L. Why standard modeling and evaluation procedures are inadequate for assessing traffic congestion measures. Transport Policy, 1997, 4: 217-223.

[13] 中国交通年鉴编委会. 中国交通年鉴. 北京: 中国交通年鉴社, 2006, 663-657.

[14] Chan E H W, Tang B S, Wong W S. Density control and the quality of living space: a case study of private housing development in Hong Kong. Habitat International, 2002, 26: 159-175.

[15] Lau S S Y, Giridharan R, Ganesan S. Multiple and intensive land use: case studies in Hong Kong. Habitat International, 2005, 29: 527-546.

[16] 国家统计局城市社会经济调查总队. 2004年中国城市发展报告. 北京: 中国统计出版社, 2005,3-6.

[17] 埃德温·S·米尔斯. 郝寿义译. 区域和城市经济学手册: 城市经济学. 北京: 经济科学出版社, 2003, 200-276.

[18] Olszewski P, Xie L. Modelling the effects of road pricing on traffic in Singapore. Transportation Research Part A, 2005, 39: 755-772.

Outlines

/