|Table of Contents|

Design model of traffic network based on stochastic supply and stochastic demand(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2012年04期
Page:
67-74
Research Field:
交通运输规划与管理
Publishing date:

Info

Title:
Design model of traffic network based on stochastic supply and stochastic demand
Author(s):
YU Xin-xin1; 2;  LU Hua-pu2;  LI Yang-yang3;  SUN Xu2;  BIAN Chang-zhi2; 4
1. Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China; 2. Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China; 3. School of Automobile, Chang'an University, Xi'an 710064, Shaanxi, China; 4. China Academy of Urban Planning and Design, Beijing 100044, China
Keywords:
traffic planning;  discrete traffic network;  uncertain theory;  bi-level programming theory;  Monte Carlo simulation;  genetic algorithm
PACS:
U491.1
DOI:
-
Abstract:
In order to improve the traditional design method of traffic network based on definitive supply and definitive demand, the bi-level programming theory and traffic assignment theory were used, and the design model of traffic network based on stochastic supply and stochastic demand was set up. The Monte Carlo simulation, genetic algorithm and traffic assignment algorithm were applied in model solving process, and Nguyen-Dupuis traffic network was used to solve the model. Calculation result indicates that when the OD demand increases, the total travel time increases. When the construction budget increases, the total travel time decreases. When both supply and demand are uncertain, the effect of increasing construction budget on decreasing total travel time is more significant. Under different conditions, the maximum value of total travel time is 1.69×105 h, and the minimum value is 8.89×104 h. When the average value of OD demand is 350 veh·h-1 and the construction budget increases from 10 million yuan to 15 million yuan, the total travel time decreases by 3.47% under certain supply. The uncertain degrees of stochastic supply and stochastic demand have important influence on the design method of traffic network. 9 tabs, 17 figs, 19 refs.

References:

[1] YANG Hai, BELL M G H. Models and algorithms for road network design: a review and some new developments[J]. Transport Reviews, 1998, 18(3): 257-278.
[2] WONG S C, YANG Hai. Reserve capacity for a signal controlled road network[J]. Transportation Research Part B: Methodological, 1997, 31(5): 397-402.
[3] 许 良,高自友.基于连通可靠性的城市道路交通离散网络设计问题[J].燕山大学学报,2007,31(2):159-163. XU Liang, GAO Zi-you. Urban road transportation discrete network design based on connectivity reliability[J]. Journal of Yanshan University, 2007, 31(2): 159-163.(in Chinese)
[4] 刘娟娟,范炳全,祝炳发.双层规划在城市交通污染控制中的一个应用[J].管理工程学报,2005,19(4):87-90. LIU Juan-juan, FAN Bing-quan, ZHU Bing-fa. An apply of bilevle programming in the urban transport pollution control[J]. Journal of Industrial Engineering and Engineering Management, 2005, 19(4): 87-90.(in Chinese)
[5] MENG Qiang, YANG Hai. Benefit distribution and equity in road network design[J]. Transportation Research Part B: Methodological, 2002, 36(1): 19-35.
[6] FRIESZ T L, ANANDALINGAM G, MEHTA N J, et al. The multiobjective equilibrium network design problem revisited: a simulated annealing approach[J]. European Journal of Operational Research, 1993, 65(1): 44-57.
[7] TZENG G H, TSAUR S H. Application of multiple criteria decision making for network improvement plan model[J]. Journal of Advanced Transportation, 1997, 31(1): 48-74.
[8] UKKUSUI S V, MATHEW T V, WALLER S T. Robust transportation network design under demand uncertainty[J]. Computer-Aided Civil and Infrastructure Engineering, 2007, 22(1): 6-18.
[9] YIN Ya-feng, MADANAT S M, LU Xiao-yun. Robust improvement schemes for road networks under demand uncertainty[J]. European Journal of Operational Research, 2009, 198(2): 470-479.
[10] WATLING D. A second order stochastic network equilibrium model, I: theoretical foundation[J]. Transportation Science, 2002, 36(2): 149-183.
[11] CLARK S, WATLING D. Modeling network travel time reliability under stochastic demand[J]. Transportation Research Part B: Methodological, 2005, 39(2): 119-140.
[12] SHAO Hu, LAM W H K, TAM M L. A reliability-based stochastic traffic assignment model for network with multiple user classes under uncertainty in demand[J]. Networks and Spatial Economics, 2006, 6(3): 173-204.
[13] KAROONSOONTAWONG A, WALLER S T. Integrated network capacity expansion and traffic signal optimization problem: robust bi-level dynamic formulation[J]. Network and Spatial Economics, 2009, 10(4): 525-550.
[14] CHEN A, YANG Hai, LO H K, et al. A capacity related reliability for transportation network[J]. Journal of Advanced Transportation, 1999, 33(2): 183-200.
[15] LO H K, LUO X W, SIU B W Y. Degradable transport network: travel time budget of travellers with heterogeneous risk aversion[J]. Transportation Research Part B: Methodological, 2006, 40(9): 792-806.
[16] SIU B W Y, LO H K. Doubly uncertain transportation network: degradable capacity and stochastic demand[J]. European Journal of Operational Research, 2008, 191(1): 166-181.
[17] LAM W H K, SHAO Hu, SUMALEE A. Modeling impacts of adverse weather conditions on a road network with uncertainties in demand and supply[J]. Transportation Research Part B: Methodological, 2008, 42(10): 890-910.
[18] NGUYEN S, DUPUIS C. An efficient method for computing traffic equilibria in networks with asymmetric transportation costs[J]. Transportation Science, 1984, 18(2): 185-202.
[19] 陆化普,蔚欣欣,卞长志.发生吸引量不确定的离散交通网络设计模型[J].统计与决策,2011(6):8-12. LU Hua-pu, YU Xin-xin, BIAN Chang-zhi. Model and algorithm of discrete network design problem under trip production-attraction uncertainty[J]. Statistics and Decision, 2011(6): 8-12.(in Chinese)

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Last Update: 2012-08-30