Transportation status of Chinese expressway network in 2011
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摘要: 以中国高速公路联网收费系统数据库为主, 辅以收费站典型抽样调查, 分析了2011年中国高速公路网运输状态。分析结果表明: 与2010年相比, 2011年度高速公路网客运密度增长4.09%;小客车(不大于7座)完成的周转量在旅客周转量中的比重为47.10%, 同比上升2.01%;Ⅰ型客车平均速度下降1.97%, Ⅱ型客车平均速度上升2.07%, Ⅲ型客车平均速度下降0.84%, Ⅳ型客车平均速度下降0.35%;货运密度同比下降1.01%, 汽车列车完成货物周转量的82.31%, 货运车辆的空车走行率为22.24%, 同比上升2.19%;按照GB 1589-2004治超标准, 超限30%以上的货车比重为3.92%。2011年, 中国高速公路旅客运输持续保持了高速增长态势, 货物运输增长态势有所放缓。Abstract: Based on the database of expressway network toll system and the typical sampling investigation data at toll stations, the transportation status of Chinese expressway network in 2011 was analyzed. Analysis result shows that compared with the transportation status in 2010, passenger transportation density in expressway network in 2011 rose by 4.09%. 47.10% of passenger turnover volume was produced by mini-type buses(the seat amount of every bus is less than 8), and the volume rose by 2.01%. The average speed of Ⅰ-type bus reduced by 1.97%, the average speed of Ⅱ-type bus rose by 2.07%, the average speed of Ⅲ-type bus reduced by 0.84%, and the average speed of Ⅳ-type bus reduced by 0.35%. Freight transportation density reduced by 1.01%, and 82.31% of freight turnover volume was produced by tractor-trailer combination. The percentage of empty to loaded truck kilometers was 22.24% and rose by 2.19%. According to the standard of GB 1589—2004, the percentage of trucks with the overweight more than 30% was 3.92%. In 2011, the passenger transportation of Chinese expressway network kept continuous high-speed growth, however, the increasing speed of freight transportation reduced.
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0. Introduction
Asphalt mixture is a three-phase compound comprising of aggregates, asphalt mastic and air voids. At present, the macroscale and overall indices such as air void percent, bulk density, voids in mineral aggregate(VMA) and voids filled with asphalt(VFA), are usually adopted to characterize the volumetric properties of asphalt mixture. These statistical indices simply describe the overall orientation of the specimen, while the microstructure properties of the internal specimen, such as the spatial arrangement of aggregate, aggregate interlock, skeleton contact, mastic distribution and air voids can not be accurately determined. The internal microstructure of asphalt mixture is highly correlated with the long-term performance and mechanical properties of asphalt pavement.
The digital image processing (DIP) technology was initially adopted by Yue to study the shape, orientation and spatial distribution in asphalt mixture[1-5]. Shashidhar adopted the computed tomography (CT) system to scan the distribution of aggregates, mastic and air voids in asphalt mixture, and found the correlation between asphalt pavement rutting and coarse aggregate interlock contact in the specimen[6]. Wang also used CT system and DIP technology to quantify the microstructure of pavement cores with three different gradations drilled from WesTrack testing field[7-8]. The volumetric indices such as VMA, VFA and air void percent of the drilled cores were calculated by DIP method. Air void distributions were scanned by CT and analyzed by DIP technology for two different specimens compacted by Superpave gyratory compactor (SGC) and linear kneading compactor[9], and air void can be fitted using the Weibull distribution curve. Masad utilized the CT images to measure the void distribution and characterize the fluid flow path in connected voids in the field core[10]. The aforementioned research focused more on analyzing the internal structure of the same type of asphalt mixtures by DIP technology, and less on comparing the diversities between different gradation mixtures designed by different methodologies.
The compaction method and aggregate gradation have influence on the internal structure and mechanical performance of asphalt mixture. The AC-16, SMA-16 and OGFC-16 mixture specimens designed by SGC and Marshall methods are scanned by CT and the internal void distributions are measured by DIP technology in this paper. The work also provide digital model for the mechanical simulation and elaborate the mechanical characteri-stics of asphalt mixture.
1. Materials
1.1 Aggregate gradation
Three different gradations are used in the study, namely, a continuous dense AC-16 gradation, a stone matrix asphalt SMA-16 gradation and an open graded friction course OGFC-16 gradation. The gradations for three mixtures are shown in Tab. 1.
Table 1. Passing percents of three gradations
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1.2 Performances of asphalt mixtures
The AC-16 and SMA-16 mixtures are designed using the Marshall method, and their air voids are mainly maintained at 4% and other performance indices are also considered. The main indices for AC-16, SMA-16 and OGFC-16 designed by Marshall method are presented in Tab. 2.
As the design method and controlling criteria for OGFC-16 mixture was not presented in the SuperpaveTM design system, the air void percent and gradation of OGFC-16 are kept in the same for SGC specimens and Marshall specimens in this paper. The optimum asphalt content is 3.7% for OGFC-16 mixture. The optimum asphalt contents are set at 3.7% and 4.7% for AC-16 and SMA-16 mixtures respectively.
Table 2. Performance parameters of asphalt mixtures
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2. CT scanning of internal structures for mixture specimens
2.1 CT system and its technical data
The basic data of CT system adopted in this paper are shown in Tab. 3.
Table 3. Technical data of CT system
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2.2 Scanning slice positions
The scanning slice positions are presented in Fig. 1 for the two compaction method and three gradation specimens.
Figure 1. CT scanning slice positions2.3 Internal structure images of mixture specimens
The scanned CT images of the internal structures for these specimens are listed in Fig. 2 to Fig. 7. The images are arranged from left to right and correspond to slices from top to bottom as shown in Fig. 1.
Figure 2. CT images of AC-16 specimen compacted by Marshall
Figure 3. CT images of AC-16 specimen compacted by SGC
Figure 4. CT images of SMA-16 specimen compacted by Marshall
Figure 5. CT images of SMA-16 specimen compacted by SGC
Figure 6. CT images of OGFC-16 specimen compacted by Marshall
Figure 7. CT images of OGFC-16 specimen compacted by SGC2.4 Calculation method of internal air voids
The threshold between the mastic and aggregate is automatically calculated by edge recognition in digital image analysis soft package Image Pro-plus 5.0. By this method, the internal air void is quantified and measured for the 2D images.
3. Air void distributions among different slices
The DIP method is adopted to calculate the air void distribution and study the influence of aggregate gradations and compaction methods with the aforementioned 6 groups of images.
3.1 Air void distributions in SGC mixture specimens
The air void distributions are shown in Fig. 8 for the different slices along the height of the mixture specimens compacted by SGC.
Figure 8. Air void distributions of mixture specimens compacted by SGCIt can be inferred from Fig. 8 that, throug-hout the specimen height, the air void percents are bigger on the top and at the bottom, and are smaller in the middles of the specimens compacted by SGC.
Meanwhile, the aggregate gradations have remarked influence on the air void distributions through the specimen height. The void percent variance is least for the continuous dense AC-16 gradation, with only 1.5% standard deviation. For the open graded friction course OGFC-16, the variance is comparatively intermediate, with 3.2% standard deviation. The stone matrix asphalt mixture SMA-16 has the largest variance of 7.2% standard deviation.
The internal structure is being rearranged spatially in asphalt mixture when the specimens are compacted by a gyratory compactor. For the three parts of coarse aggregates, medium size aggregates and mastic, they need different amounts of energy to get rearranged. The coarse aggregates need the biggest energy and the mastic needs the smallest energy.
The coarse aggregates have a high content in SMA-16 mixture, and they need high energy to get rearranged spatially, while the low content medium size aggregates need low energy to get rearranged. With the given gyratory compaction energy in the compaction process, the coarse aggregates only have little spatial rearrangement, while middle size aggregates have much spatial rearrangement. The spatial rearrangement is remarkable between the coarse aggregates and the medium size aggregates in compaction process, which makes the significant variance of air void distributions in SMA-16 mixture specimens.
There are low content of coarse aggregates and high content of medium size aggregates in AC-16 mixture. With a given gyratory compaction energy, the spatial rearrangement of coarse aggregates matches well with the medium size aggregates. The result in a consistent spatial rearrangement of the coarse aggregates and medium size aggregates gives the low variance of air void distributions in AC-16 mixture specimens.
The design number of gyratory compaction is 100 for the three gradation mixture specimens in this research. The gyratory compaction energy is higher than the 50 Marshall blows for SMA-16 and OGFC-16 mixtures, which may result in higher variance of air void distributions for SMA-16 and OGFC-16 mixtures compacted by SGC.
Figure 9. Air void distributions of mixture specimens compacted by Marshall3.2 Air void distribution in Marshall mixture specimens
The air void distributions are shown in Fig. 9 among different slices along the height of the mixture specimens compacted by Marshall.
It can be inferred from Fig. 9 that, throug-hout the specimen height, the air void distribution variances are not marked for the specimens compacted by Marshall.
The AC-16 specimen has the lowest variance of air voids, with 0.6% standard deviation. The OGFC-16 specimen has the intermediate, with 1.0% standard deviation. The SMA-16 specimen has the greatest variance of 1.2% standard deviation.
3.3 Influence of air void distribution by compaction style
It can be inferred from the comparison between
Fig. 8 and Fig. 9 that, the air void variances of the specimens compacted by SGC are more significant than that of the specimens compacted by Marshall. Their standard deviations are given as: AC-16 specimens(1.5%, 0.6%), SMA-16 specimens(7.2%, 1.2%), OGFC-16 specimens(3.2%, 1.0%).
The coarse aggregates, medium size aggregates and mastic in the mixture specimen are also rearranged when the mixture specimen is compacted by Marshall blow. But its mechanism is a little different with that of SGC specimen. In the gyratory compacting process of SGC, the three components contact one another and get rearranged smoothly, while in the Marshall method, the components collide rigidly in the compacting process. Because of the angularity of the aggregates, the aggregates need less energy to get rearranged with flexible contact and more energy with rigid collision during the compaction process. The compaction energy of SGC is higher than that of Marshall, especially for SMA-16 and OGFC-16 specimens. As a result, the spatial rearrangement scale of the aggregates in SGC specimens is higher than that in Marshall specimens, and the variance of air void distribution in SGC specimens deviates more greatly than that in Marshall specimens.
4. Air void distribution in cross section
The air void distribution characteristics in the cross section are also studied by the 6 groups CT images. The circular areas at radii R, 0.75R and 0.50R are considered to calculate the air void distribution (Fig. 10). Note that R is the radius of cross section slice.
The 1st and 5th slices of SGC specimens are not included in calculating the air void distribution due to the marked variances of air voids on the top and at the end of SGC specimens. The air void distribution in the cross section of each slice is shown in Fig. 11.
It can be inferred from Fig. 11 that air voids distribute unevenly through the cross sections of AC-16 and SMA-16 mixtures. Generally, the outer parts have more air voids than the inner parts in the cross sections. Air voids increase through the radius length. The "sparse outer and dense inner" pattern gets more obvious in SGC specimens.
Figure 11. Void distributions of mixture specimensFor the OGFC-16 mixture specimens, air void variances are not clear and distribute uniformly in the cross sections of both SGC specimens and Marshall specimens.
In the compaction process of asphalt mixture specimens, some coarse aggregates will be constrained by the steel mould when they get rearranged in the exterior part of the cross section, and their position will get preliminarily fixed. The medium size aggregates and mastic will continuously move in the middle part of the specimens(both in height direction and cross section) and get rearranged fully, and get their optimum spatial positions. The coarse aggregates get fixed in the end section in height direction and in outer part in the cross section, and can not be filled with the uniform middle size aggregates and mastic. As a result, the exterior parts have more air voids in the mixture specimens.
5. Conclusions
(1) Air void distribution is not uniform in asphalt mixture, and it varies greatly with the kind of compacting effort and the gradation of asphalt mixture. Throughout the specimen height, air void percent is greater on the top and at the bottom, and is small in the middle part of the specimen compacted by SGC. The distribution variance is not significant for the specimen compacted by Marshall. Air void distributions are uneven through the cross section of AC-16 and SMA-16 mixtures. The exterior part has more air voids than the inner part in the cross section.
(2) Based on the influence of type of compaction effort, the air void distributions of SGC specimens have more variances than that of Marshall specimens along both height and radial directions.
(3) Based on the influence of aggregate gradation, SMA-16 mixture specimens have more air void distribution variances in both height and radial directions.
(4) For the mixtures compacted by SGC, the bigger variance parts are suggested to be removed in the mechanical performance test. The deviationwould be little if the cores drilled from original SGC specimen without the end part are taken in the mechanical performance tests.
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表 1 乘用车客运比重
Table 1. Passenger transportation proportions of passenger cars
年份 2006 2007 2008 2009 2010 2011 旅客周转量比重/% 29.75 38.12 41.01 43.30 45.09 47.10 客运量比重/% 41.07 46.54 48.54 53.94 56.56 60.09 
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表 2 客车平均速度
Table 2. Average speeds of buses
车型 座位数量 平均速度/(km·h-1) 样本数量/104 veh Ⅰ ≤7 88.69 115 726 Ⅱ 8~19 84.19 3 062 Ⅲ 20~39 81.77 4 936 Ⅳ ≥40 83.93 3 243
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表 3 2006~2011年货物周转量发展趋势
Table 3. Growth trends of freight turnover volumes in 2006-2011
运输方式 2006年 2007年 2008年 2009年 2010年 2011年 周转量/(108 t·km) 周转量/(108 t·km) 增长率/% 周转量/(108 t·km) 增长率/% 周转量/(108 t·km) 增长率/% 周转量/(108 t·km) 增长率/% 周转量/(108 t·km) 增长率/% 铁路 21 954 24 214 10.3 25 106 14.4 25 239 15.0 27 644 25.9 29 130 32.7 内河和沿海水运 12 908 15 599 20.8 17 413 34.9 18 031 39.7 22 428 73.8 26 068 102.0 高速公路 7 458 9 970 33.7 11 981 60.6 13 517 81.2 17 452 134.0 19 802 165.5
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表 4 货车平均速度
Table 4. Average speeds of trucks
车型 轴型 平均速度/(km·h-1) 样本数量/104 veh 单车 2轴4胎 68.78 6 307 2轴6胎 61.09 16 399 3轴和4轴 57.51 8 240 半挂列车 3~6轴 55.65 23 208
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表 5 2011年高速公路货车主要轴型
Table 5. Chief axis types of trucks in 2011
表 6 货车车数比重
Table 6. Amount proportions of trucks
% 车型 2006年 2007年 2008年 2009年 2010年 2011年 2轴4胎 17.48 12.40 10.28 13.39 11.43 11.44 2轴6胎 48.79 42.43 35.36 33.31 31.00 30.84 3轴与4轴单车 13.26 16.42 19.68 15.97 15.76 15.17 半挂列车 20.47 28.75 34.68 37.33 41.81 42.55
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表 7 货车行驶量比重
Table 7. Kilometers proportions of trucks
% 车型 2006年 2007年 2008年 2009年 2010年 2011年 2轴4胎 7.74 6.25 6.84 7.82 6.84 6.76 2轴6胎 38.24 33.67 27.84 24.93 22.62 22.49 3轴与4轴单车 17.60 19.13 18.07 17.22 15.54 14.74 半挂列车 36.42 40.95 47.25 50.03 55.00 56.01
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表 8 货车完成的货物周转量比重
Table 8. Proportions of freight turnover volumes for trucks
% 车型 2006年 2007年 2008年 2009年 2010年 2011年 2轴4胎 1.42 0.95 0.57 1.12 0.78 0.69 2轴6胎 18.60 13.02 9.87 7.47 5.83 5.54 3轴与4轴单车 20.25 19.83 18.07 15.27 12.44 11.46 半挂列车 59.73 66.20 71.49 76.14 80.95 82.31
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表 9 空车走行率
Table 9. Percentages of empty to loaded truck kilometers
% 车型 年份 省内运输 跨省运输 总量 2轴单车 2011 35.30 26.13 31.65 2010 37.60 29.10 33.30 2009 34.77 24.95 30.48 2008 32.78 18.84 26.33 2007 36.17 15.03 24.95 2006 36.01 15.87 26.52 3轴与4轴单车 2011 34.44 12.30 20.23 2010 34.17 12.42 17.93 2009 35.03 9.46 16.95 2008 36.40 10.81 18.05 2007 33.24 8.38 15.00 2006 32.82 9.38 17.73 半挂列车 2011 43.27 10.84 18.48 2010 31.34 13.14 14.90 2009 34.14 7.90 14.73 2008 42.67 10.16 18.37 2007 28.74 10.37 15.28 2006 35.02 9.28 13.93 合计 2011 38.33 13.55 22.24 2010 34.42 16.37 20.05 2009 34.56 11.68 19.84 2008 36.71 12.37 20.97 2007 33.30 11.37 18.93 2006 35.33 10.97 20.13
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表 10 装载货车车数比重
Table 10. Proportions of trucks classified by load conditions
% 治超标准 空车 不超限重车 超限0~30% 超限30%~50% 超限50%~100% 超限大于100% 超限合计 国家强制标准 26.95 44.05 25.08 2.28 1.39 0.25 100.00 路政治超标准 26.95 65.72 6.06 0.76 0.43 0.08 100.00
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表 11 绿色通道运输车辆构成比重
Table 11. Percentages of trucks through green path
轴数 2轴 3轴 4轴 5轴 6轴 绿色通道车辆数比重/% 64.00 7.09 15.11 0.65 13.15 全国高速公路总体车辆数比重/% 42.28 7.74 11.56 5.29 33.13
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表 12 ETC系统相关数据
Table 12. Related data of ETC system
类别 北京 上海 江苏 收费站总数量 181 103 316 设置ETC的收费站数量 175 75 260 ETC覆盖率/% 96.68 72.82 82.28 ETC出口交通量与总出口交通量之比/% 23.23 13.04 10.44 ETC出口车道数量 193 95 303 ETC出口车道平均交通量/(veh·h-1) 38 34 13 ETC出口车道平均交通量小于4 veh·h-1的收费站数量 42 4 116
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[1] 交通运输部综合规划司, 长安大学运输科学研究院. 2010中国高速公路运输量统计调查分析报告[M]. 北京: 人民交通出版社, 2011.Department of Comprehensive Planning, Ministry of Transport, Research Institute of Transporation Science, Chang'an University. Survey and Statistics of Chinese Expressway Transport Volume in 2010[M]. Beijing: China Communications Press, 2011. (in Chinese). [2] 交通运输部综合规划司. 2011年公路水路交通运输行业发展统计公报[R]. 北京: 交通运输部综合规划司, 2012.Department of Comprehensive Planning, Ministry of Transport. Highway and waterway transportation industry statistical bulletin in 2011[R]. Beijing: Department of Comprehensive Planning, Ministry of Transport, 2012. (in Chinese). [3] PARK J Y, GORDON P, MOORE J E, et al. A two-step approach to estimating state-to-state commodity trade flows[J]. The Annals of Regional Science, 2008, 43(4): 1033-1072. [4] WOLF J, BONSALL P, OLIVEIRA M, et al. Review of the potential role of new technologies in the national travel survey[R]. Leeds: University of Leeds, 2009. [5] 秦华容, 杨铭. 美国货运数据需求与供给分析[J]. 物流技术, 2009, 28(2): 145-147. https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS200902047.htmQIN Hua-rong, YANG Ming. Analysis on demand and supply of freight transportation data in America[J]. Logistics Technology, 2009, 28(2): 145-147. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WLJS200902047.htm [6] 陈荫三, 李彬, 肖润谋. 2010年中国高速公路网运输状态[J]. 交通运输工程学报, 2011, 11(6): 68-73. http://transport.chd.edu.cn/article/id/201106011CHEN Yin-san, LI Bin, XIAO Run-mou. Transportation status of Chinese expressway network in 2010[J]. Journal of Traffic and Transportation Engineering, 2011, 11(6): 68-73. (in Chinese). http://transport.chd.edu.cn/article/id/201106011 [7] 杨铭, 秦华容, 陈荫三. 区域公路货物周转量结构分析与推算方法[J]. 交通运输工程学报, 2011, 11(5): 93-99. http://transport.chd.edu.cn/article/id/201105015YANG Ming, QIN Hua-rong, CHEN Yin-san. Structure analysis and calculation method of freight turnover for regional highway[J]. Journal of Traffic and Transportation Engineering, 2011, 11(5): 93-99. (in Chinese). http://transport.chd.edu.cn/article/id/201105015 [8] 中华人民共和国铁道部. 2011年铁道统计公报[R]. 北京: 中华人民共和国铁道部, 2012.The Ministry of Railways of the People's Republic of China. Railway annual statistics bulletin in 2011[R]. Beijing: The Ministry of Railways of the People's Republic of China, 2012. (in Chinese). [9] Bureau of Transportation Statistics, US Department of Transportation. National transportation statistics 2007[R]. Washington DC: Bureau of Transportation Statistics, US Department of Transportation, 2007. [10] Bureau of Transportation Statistics, US Department of Transportation. National transportation statistics 2010[R]. Washington DC: Bureau of Transportation Statistics, US Department of Transportation, 2010. [11] Bureau of Transportation Statistics, US Department of Transportation. National transportation statistics 2011[R]. Washington DC: Bureau of Transportation Statistics, US Department of Transportation, 2011. [12] Bureau of Transportation Statistics, US Department of Transportation. National transportation statistics 2012[R]. Washington DC: Bureau of Transportation Statistics, US Department of Transportation, 2012. [13] 董忠红, 吕彭民. 高等级路面上的车辆动载荷[J]. 长安大学学报: 自然科学版, 2011, 30(1): 95-99. https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201001021.htmDONG Zhong-hong, LU Peng-min. Dynamic load of vehicle on high-class pavement[J]. Journal of Chang'an University: Natural Science Edition, 2011, 30(1): 95-99. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-XAGL201001021.htm [14] 温德坤. 关于高速公路绿色通道车辆快速检查方案的探讨[J]. 交通标准化, 2010(16): 222-224. https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201015064.htmWEN De-kun. Expeditious vehicle detection scheme in green channel on expressway[J]. Communications Standardization, 2010(16): 222-224. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201015064.htm [15] 张玉玲, 林莉贤, 解晓玲. 关于收费公路降低费率和推广ETC问题的分析[J]. 中国交通信息化, 2011(12): 20-23. https://www.cnki.com.cn/Article/CJFDTOTAL-YSZH201111007.htmZHANG Yu-ling, LIN Li-xian, XIE Xiao-ling. Analysis on toll roads to reduce rates and promotion ETC[J]. China ITS Journal, 2011(12): 20-23. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSZH201111007.htm [16] 交通运输部综合规划司. 2001年公路水路交通行业发展统计公报[R]. 北京: 交通运输部综合规划司, 2002.Department of Comprehensive Planning, Ministry of Transport. Highway and waterway transportation industry statistical bulletin in 2001[R]. Beijing: Department of Comprehensive Planning, Ministry of Transport, 2002. (in Chinese). -
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