Statistical approach for the region-oriented volume of freight transport on highway
-
摘要: 提出了在地公路货物运输量的概念, 将非营运货车和外地货车纳入了在地货物运输量的统计范畴, 归纳了基础数据集; 通过分析车辆注册地、使用性质、路网等级和车流流向等因素, 提出了在地货物运输量的统计思路和拆分逻辑, 建立了在地公路货运量和货物周转量统计模型; 基于本市籍营运货车产生的货运量, 提出了在地货运量规模指数用以评估在地货运量的相对偏移程度和外地货车的参与程度。研究结果表明: 控制极限误差在10%以下时, 5种基础数据集, 即货运专项调查数据、高速公路联网收费数据、普通公路抽样调查数据、普通公路交通量调查数据和车辆管理所在册货车数据可完成在地货物运输量的精细化推算; 提出的统计模型使所研究城市创造每万元GDP的货物周转量与全国平均水平的相对偏差率为0.45%, 具有一致性; 所研究城市的在地货运量规模指数为2.47, 说明实体经济发达的城市中外地货车在当地参与运输的程度偏高; 本市籍营运货车货物运输量不足以支撑当地经济规划; 本市籍在册营运货车少并不能代表本市运力不足, 所研究城市的本市籍营运货车主要承担短途运输, 在总市内货运量中占66.28%, 而外地货车主要承担市际与省际间的货物交流, 在总跨市货运量中占79.16%;货车按车型计费后, 每种货车车型的平均载货质量与按车流划分的重车比将是在地货物运输量统计的关键参数; 省际间3轴及以上货车车流量存在着不均衡性。Abstract: The concept of region-oriented freight transportation volume was proposed. Non-commercial trucks and nonlocal trucks were included in the statistics category of the region-oriented freight transportation volume, and the basic data sets were summarized. The factors of the registration place, usage, level of the highway network, and traffic flow direction of the vehicles were analyzed. Statistical thoughts and splitting logic of the freight transportation volume, and statistical models of freight volume and freight turnover volume were developed. Based on the freight volume of registered local commercial trucks, a scale index of region-oriented freight volume was created and used to evaluate the relative offset degree and involvement of nonlocal trucks. Analysis results show that when the limit error is controlled within 10%, the region-oriented freight volume can be evaluated exactly by five basic data sets: special survey data on freight transport, expressway network toll collection data, sample survey data of highway, traffic volume survey data of highway, and truck data in the register of vehicle management. For the studied city, the proposed statistical model embodies a 0.45% relative deviation rate of the freight turnover to create GDP per ten thousand yuan with the national average level, which is consistent. The scale index of region-oriented freight volume is 2.47, which indicates that nonlocal trucks involved in local freight transportation to a high degree in cities with developed real economy. The freight transportation volume of commercial trucks registered at the local government office is not sufficient to support economic planning. However, a lack of registered trucks does not indicate an insufficient transportation capacity. The commercial trucks registered locally mainly undertake short-distance freight transportation, which accounts for 66.28% of the total in-city freight volume. Nonlocal trucks mainly undertake inter-city and inter-provincial goods, which accounts for 79.16% of the total volume. In the near future, when trucks are charged by vehicle type, the average load of each vehicle type and the rate of each loaded truck in total will be key parameters for the evaluation of the region-oriented freight transportation volume. In addition, inter-provincial disequilibrium existed in the traffic volume of trucks with 3 axles or more.
-
表 1 不同省籍的货车车流量
Table 1. Traffic flow of trucks of different provinces
104 veh 省份 安徽籍 江苏籍 江西籍 福建籍 湖南籍 广东籍 安徽省内 139.68 2.41 4.04 江苏省内 481.58 45.68 5.18 江西省内 90.58 33.74 20.41 福建省内 106.39 180.70 6.81 湖南省内 29.04 5.27 30.32 广东省内 342.32 935.40 284.52 
下载: 导出CSV
表 2 基础数据集可完成的统计维度
Table 2. Achieved statistic dimensions based on essential data sets
基础数据集 本市籍营运货车 本市籍非营运货车 本省外市籍货车 外省籍货车 货运专项调查数据 √ 高速公路联网收费数据 √ √ √ √ 普通公路抽样调查数据 √ √ √ √ 普通公路交通量调查数据 √ √ √ √ 车辆管理所在册货车数据 √ √
下载: 导出CSV
表 3 干线公路货物运输量统计的关键信息
Table 3. Key information of freight transport volume statistics on trunk highway lines
采集或调查项目 说明 数据来源 数据时间 数据时间精确到小时 普通公路交通量调查数据和补充抽样调查 车牌号 调查车辆全部7位车牌号 货车轴数/车型 按货车轴数/车型分类 空车或重车标记 表示车辆的空驶状态 补充抽样调查 行程起止点 一次运输的起止点, 精确到县区级 使用性质 车辆是否为营运货车 行驶线路 本趟次运输是否全程普通公路行驶
下载: 导出CSV
表 4 货物运输量统计的关键参数
Table 4. Key parameters of freight transport volume statistics
轴数 平均载货量/t 重车比/% 高速公路货物运输量拆分系数/% 进市 出市 市内 本市籍营运货车 本市籍非营运货车 本省外市籍货车 外省籍货车 2 4.10 68.88 69.24 72.09 15.82 5.34 51.42 27.42 3 7.28 71.32 70.41 73.18 4 11.17 86.57 83.84 84.09 5 10.95 78.71 85.52 81.86 6 19.99 76.09 77.24 81.31
下载: 导出CSV
表 5 在地货运量结构比例
Table 5. Structural proportions of region-oriented freight volume
% 车辆注册地 车辆类型 进市 出市 市内 小计 本地货车 本市籍营运货车 5.31 4.69 29.19 39.19 本市籍非营运货车 0.93 0.73 7.99 9.65 外地货车 本省外市籍货车 9.93 10.65 3.26 23.84 外省籍货车 12.09 11.63 3.60 27.32 合计 28.26 27.70 44.04 100.00
下载: 导出CSV
-
[1] 梁仁鸿, 仵思燃. 公路货物运输量统计新试行方案问题及完善思路研究[J]. 公路交通科技, 2018, 35(7): 151-158. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201807021.htmLIANG Ren-hong, WU Si-ran. Study on problems and improvement of highway freight volume statistics trail scheme[J]. Journal of Highway and Transportation Research and Development, 2018, 35(7): 151-158. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201807021.htm [2] 陈小叶. 公路运输量抽样误差控制研究[D]. 西安: 长安大学, 2015.CHEN Xiao-ye. The research on controlling sampling error of road transportation volume[D]. Xi'an: Chang'an University, 2015. (in Chinese). [3] U. S. Department of Transportation, Bureau of Transportation Statistics. Transportation statistics annual report[R]. Washington DC: U. S. Department of Transportation, Bureau of Transportation Statistics, 2003. [4] U. S. Department of Transportation, Bureau of Transportation Statistics. Transportation statistics annual report[R]. Washington DC: U. S. Department of Transportation, Bureau of Transportation Statistics, 2017. [5] 陈荫三, 肖润谋, 闫晟煜, 等. 2017中国高速公路运输量调查分析报告[R]. 北京: 人民交通出版社股份有限公司, 2018.CHEN Yin-san, XIAO Run-mou, YAN Sheng-yu, et al. Statistics and analysis report of expressway of China in 2017[R]. Beijing: China Communication Press Co., Ltd, 2018. (in Chinese). [6] 闫晟煜, 肖润谋. 基于收费数据的高速公路运输量指标特征[J]. 交通运输工程学报, 2018, 18(6): 112-120. doi: 10.3969/j.issn.1671-1637.2018.06.012YAN Sheng-yu, XIAO Run-mou. Index characteristics of expressway transportation volume based on toll collection data[J]. Journal of Traffic and Transportation Engineering, 2018, 18(6): 112-120. (in Chinese). doi: 10.3969/j.issn.1671-1637.2018.06.012 [7] 刘拥华, 陈维民, 缪和匠, 等. 公路路网货物运输量月度波动系数推算方法[J]. 交通运输系统工程与信息, 2015, 15(5): 123-127, 149. doi: 10.3969/j.issn.1009-6744.2015.05.018LIU Yong-hua, CHEN Wei-min, MIAO He-jiang, et al. Calculation method of monthly fluctuation coefficient on highway network freight transportation volumes[J]. Journal of Transportation Systems Engineering and Information Technology, 2015, 15(5): 123-127, 149. (in Chinese). doi: 10.3969/j.issn.1009-6744.2015.05.018 [8] 张志俊. 区域煤炭公路运输问题研究[D]. 西安: 长安大学, 2015.ZHANG Zhi-jun. Study on the regional road transportation of coal[D]. Xi'an: Chang'an University, 2015. (in Chinese). [9] 陈荫三. 高速公路运输量研究[J]. 中国公路学报, 2005, 18(2): 94-98. doi: 10.3321/j.issn:1001-7372.2005.02.019CHEN Yin-san. Study of freeway transportation volume[J]. China Journal of Highway and Transport, 2005, 18(2): 94-98. (in Chinese). doi: 10.3321/j.issn:1001-7372.2005.02.019 [10] 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): 93-100. 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): 93-100. (in Chinese). http://transport.chd.edu.cn/article/id/201105015 [11] 赵怀鑫, 孙星星, 徐倩倩, 等. 基于灰熵法的公路货运量和货物周转量关联因素分析[J]. 交通运输工程学报, 2018, 18(4): 160-170. doi: 10.3969/j.issn.1671-1637.2018.04.017ZHAO Huai-xin, SUN Xing-xing, XU Qian-qian, et al. Analysis of relavant factors for highway freight volume and freight turnover based on grey entropy method[J]. Journal of Traffic and Transportation Engineering, 2018, 18(4): 160-170. (in Chinese). doi: 10.3969/j.issn.1671-1637.2018.04.017 [12] 张文会, 崔淑华, 邓红星. 公路货物运输量灰色马尔可夫预测模型[J]. 武汉理工大学学报(交通科学与工程版), 2011, 35(4): 658-661. doi: 10.3963/j.issn.1006-2823.2011.04.003ZHANG Wen-hui, Cui Shu-hua, DENG Hong-xing, et al. Grey-markov model for predicting freight volume in road[J]. Journal of Wuhan University of Technology (Transportation Science and Engineering), 2011, 35(4): 658-661. (in Chinese). doi: 10.3963/j.issn.1006-2823.2011.04.003 [13] 靳文舟, 张全. 属地道路货物运输统计调查研究[J]. 公路交通科技, 2005, 22(4): 139-143. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200504037.htmJIN Wen-zhou, ZHANG Quan. Study on regional freight transportation investigation and statistics[J]. Journal of Highway and Transportation Research and Development, 2005, 22(4): 139-143. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK200504037.htm [14] 孙东泉. 日本道路货物运输的发展现状及特点[J]. 综合运输, 2014(4): 69-74. https://www.cnki.com.cn/Article/CJFDTOTAL-YSZH201404017.htmSUN Dong-quan. Development status and characteristics of road freight transportation in Japan[J]. China Transportation Review, 2014(4): 69-74. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-YSZH201404017.htm [15] 任翠萍. 中国道路货运数据框架设计——基于中美货运数据的对比分析[D]. 西安: 长安大学, 2013.REN Cui-ping. Study on the framework design of road freight data——perspective on the comparison between China and U. S. [D]. Xi'an: Chang'an University, 2013. (in Chinese). [16] 杨洋. 中国区域工业化与交通资源配置协调研究[D]. 北京: 北京交通大学, 2013.YANG Yang. Research on the coordination between regional industrialization and transportation resources allocation in China[D]. Beijing: Beijing Jiaotong University, 2013. (in Chinese). [17] 雷永巍. 基于多源数据融合的公路网货物运输指标统计与预测方法研究[D]. 广州: 华南理工大学, 2018.LEI Yong-wei. Research on statistics and forecasting method of highway network cargo transportation index based on multi-source data fusion[J]. Guangzhou: South China University of Technology, 2018. (in Chinese). [18] WANG Zhong, ZHANG Ying-ying, LIAN Lian, et al. Evaluating transportation infrastructure investment on a regional level: a system dynamics simulation[J]. Simulation: Transactions of the Society for Modeling and Simulation International, 2018, 94(10): 943-954. [19] DE JONG G, TAVASSZY L, BATES J, et al. The issues in modeling freight transport at the national level[J]. Case Studies on Transport Policy, 2016, 4(1): 13-21. [20] ASHRAFI Z, SHAHRAKI H S, BACHMANN C, et al. Quantifying the criticality of highway infrastructure for freight transportation[J]. Transportation Research Record, 2017, 2610(1): 10-18. [21] WINKLER C, MOCANU T. Impact of political measures on passenger and freight transport demand in Germany[J]. Transportation Research Part D: Transport and Environment, 2020, 87: 102476-1-11. [22] ZHAO Na-le, QI Tong-yan, YU Lei, et al. A practical method for estimating traffic flow characteristic parameters of tolled expressway using toll data[J]. Procedia—Social and Behavioral Science, 2014, 138: 632-640. [23] 闫晟煜, 肖润谋. 基于收费数据的高速公路事故影响区域判定[J]. 公路交通科技, 2013, 30(8): 134-139. https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201308025.htmYAN Sheng-yu, XIAO Run-mou. Decision of affected area of freeway accidents based on toll collection data[J]. Journal of Highway and Transportation Research and Development, 2013, 30(8): 134-139. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLJK201308025.htm [24] HAUKE G, FUSTER D, DOWEIDAR M H. Variational multiscale a-posteriori error estimation for multi-dimensional transport problems[J]. Computer Methods in Applied Mechanics and Engineering, 2008, 197(33-40): 2701-2718. [25] 李郁菡. 宁波干线公路货物运输量调查及其与GDP关联研究[D]. 西安: 长安大学, 2018.LI Yu-han. Investigation of arterial highway freight volume and study on the relatedness between freight volume and GDP of Ningbo[D]. Xi'an: Chang'an University, 2018. (in Chinese). [26] ALINA J, MCGRATH R D, LEITMANOVA I F. Using constraints in freight volume to identify regional needs for roadway infrastructure[J]. Promet—Traffic and Transportation, 2020, 32(2): 237-246. [27] 祝宏宇. 义乌道路货物运输价格指数体系及信息平台构建研究[D]. 长春: 吉林大学, 2011.ZHU Hong-yu. Price index system and its information platform construction for Yiwu road goods transport system[D]. Changchun: Jilin University, 2011. (in Chinese). [28] BAO Dan-wen, ZHANG Xiao-ling, GU Jia-yu. Evaluation method for green ecological airports in China based on combination weighting[J]. Promet—Traffic and Transportation, 2018, 30(4): 419-428. [29] 周禹初, 温旭红, 张仕俊. 不同运输方式货运周转量与GDP的协整关系分析[J]. 铁道货运, 2017, 35(10): 15-19, 24. https://www.cnki.com.cn/Article/CJFDTOTAL-TDHY201710005.htmZHOU Yu-chu, WEN Xu-hong, ZHANG Shi-jun. Analysis on the cointegration relationship between the freight turnover volume of different transport modes and GDP[J]. Railway Freight Transport, 2017, 35(10): 15-19, 24. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-TDHY201710005.htm [30] 杨铭. 基于车辆定期检验平台的运输量统计研究[D]. 西安: 长安大学, 2011.YANG Ming. Study on transportation volume statistics based on regular vehicle inspection platform[D]. Xi'an: Chang'an University, 2011. (in Chinese). -
点击查看大图
图(1) / 表(5)
计量
- 文章访问数: 493
- HTML全文浏览量: 200
- PDF下载量: 193
- 被引次数: 0
