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Frontiers of Structural and Civil Engineering

Front Arch Civil Eng Chin    2009, Vol. 3 Issue (2) : 195-203     https://doi.org/10.1007/s11709-009-0032-3
RESEARCH ARTICLE |
Simulation model based on Monte Carlo method for traffic assignment in local area road network
Yuchuan DU(), Yuanjing GENG, Lijun SUN
Key Lab. of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China
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Abstract

For a local area road network, the available traffic data of traveling are the flow volumes in the key intersections, not the complete OD matrix. Considering the circumstance characteristic and the data availability of a local area road network, a new model for traffic assignment based on Monte Carlo simulation of intersection turning movement is provided in this paper. For good stability in temporal sequence, turning ratio is adopted as the important parameter of this model. The formulation for local area road network assignment problems is proposed on the assumption of random turning behavior. The traffic assignment model based on the Monte Carlo method has been used in traffic analysis for an actual urban road network. The results comparing surveying traffic flow data and determining flow data by the previous model verify the applicability and validity of the proposed methodology.

Keywords traffic assignment      local area road network      turning ratio      Monte Carlo method     
Corresponding Authors: DU Yuchuan,Email:ycdu@mail.tongji.edu.cn   
Issue Date: 05 June 2009
 Cite this article:   
Yuchuan DU,Yuanjing GENG,Lijun SUN. Simulation model based on Monte Carlo method for traffic assignment in local area road network[J]. Front Arch Civil Eng Chin, 2009, 3(2): 195-203.
 URL:  
http://journal.hep.com.cn/fsce/EN/10.1007/s11709-009-0032-3
http://journal.hep.com.cn/fsce/EN/Y2009/V3/I2/195
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Fig.1  Local area road network in city
Fig.2  Abstract schematic drawing of local area road network
directionaverage fluctuation valueof turning ratio/%average value ofcoefficient of variation/%80 fractile of coefficientof variation/%
turn left2.148.5611.73
go straight3.395.217.17
turn right0.929.3314.99
Tab.1  Statistical results on turning ratio changes in 76 intersections
Fig.3  Time-varying drawings of turning ratio in some intersections. (a) East inlet of Zhongshan Road–Wuzhong Road intersection; (b) south inlet of Jiangning Road–Changshou Road intersection
Fig.4  Relationship between mean absolute value of relative tolerance and “simulation vehicle” amount
Fig.5  Schematic drawing of road network for testing
Fig.6  GIS distribution drawing of assignment flow in road network for testing
S/Nroad link No.assignmentflow/(pcu/day)actually measured data/(pcu/day)tolerance/(pcu/day)relative tolerance /%absolute value of relative tolerance /%
1119009185774322.332.33
221840420308-1904-9.379.37
331943321571-2138-9.919.91
4618688182514372.392.39
51012473115988757.557.55
61714106133747325.485.48
7181463015770-1140-7.237.23
8206511168246-3135-4.594.59
922182411719710446.076.07
1023911311246-2133-18.9718.97
11251758418066-482-2.672.67
12262108923872-2783-11.6611.66
132711486110054814.374.37
14322531830655-5337-17.4117.41
Tab.2  Comparison table between actually traffic data of field survey equipment and calculation results of model
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