基于实时路况地图的短期养护作业开始时间优化

doi:10.13229/j.cnki.jdxbgxb20200138

Abstract

Abstract:

A real-time traffic status data acquisition method based on real-time traffic map was first proposed， and then a method that can convert real-time traffic status into real-time traffic volume was put forward. Based on this real-time traffic volume data and the classic delay calculation method based on queuing theory， the delays caused by maintenance operations at different start time can be calculated， the total cost due to the maintenance can be further obtained and compared， and therefore the optimal maintenance operation start time can be obtained. The reliability of the real-time traffic status data to real-time traffic volume data conversion method and the feasibility of optimizing the maintenance operation start time based on real-time traffic map data are verified by actual cases.

Key words: road engineering, maintenance operation, time optimization, real-time traffic map, data acquisition, queuing theory

CLC Number:

U418.2

Zhe-pu XU,Qun YANG. Short⁃term maintenance operation start time optimization based on real⁃time traffic map data[J].Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1763-1774.

Figures/Tables 23

Fig.1

Table 1

Traffic status and corresponding RGB range"

实时交通状态	颜色	RGB阈值
顺畅	绿	$G ≠ B ?? a n d ?? R ≤ 240$
缓行	橙	$G ≠ B ?? a n d ?? R > 240$
拥堵	红	$G = B ?? a n d ?? R ≥ 200$
严重拥堵	紫	$G = B ?? a n d ?? R < 200$

Table 1

Fig.2

Table 2

Parameters of practical model for expressways"

设计车速U_s/（km·h^-1）	单车道通行能力C/（pcu·h^-1）	$α 1$	$α 2$	$α 3$
120	2200	0.93	1.88	4.85
100	2200	0.95	1.88	4.86
80	2000	1.00	1.88	4.90
60	1800	1.20	1.88	4.88

Table 2

Fig.3

Table 3

Summary of total delay DLi calculation formula for each td in work zone"

一级判断	二级判断	当前时段延误计算公式	备注
当前无累积排队车辆	$Q i ≤ C$	$d 1 = (V 1 - V 2) 2 / (2 ? a 1 ? V 1) d 2 = (1 / V 2 - 1 / V 1) ? L d 3 = (V 1 - V 2) 2 / (2 ? a 2 ? V 1) d 4 = Q i / [C ? (C - Q i)] D L i = (d 1 + d 2 + d 3 + d 4) ? Q i ? t$	此时路况畅通
当前无累积排队车辆	$Q i > C$	$d 1 = (V 1 - V 2) 2 / (2 ? a 1 ? V 1) d 2 = (1 / V 2 - 1 / V 1) ? L d 3 = (V 1 - V 2) 2 / (2 ? a 2 ? V 1) D 4 = Q i - 1 t d + 12 (Q i - C) t d 2 D L i = (d 1 + d 2 + d 3) ? Q i ? t + D 4$	排队开始形成
当前有累积排队车辆	$Q i < C$	$d 1 = (V 1 - V 2) 2 / (2 ? a 1 ? V 1) d 2 = (1 / V 2 - 1 / V 1) ? L d 3 = (V 1 - V 2) 2 / (2 ? a 2 ? V 1) D 4 = Q i - 1 2 2 (C - Q i) D L i = (d 1 + d 2 + d 3) ? Q i ? t + D 4$	排队开始消散
当前有累积排队车辆	$Q i ≥ C$	$d 1 = (V 1 - V 2) 2 / (2 ? a 1 ? V 1) d 2 = (1 / V 2 - 1 / V 1) ? L d 3 = (V 1 - V 2) 2 / (2 ? a 2 ? V 1) D 4 = Q i - 1 t d + 12 (Q i - C) t d 2 D L i = (d 1 + d 2 + d 3) ? Q i ? t + D 4$	排队继续增加

Table 3

Fig.4

Fig.5

Table 4

Fig.6

Fig.7

Table 5

Table 6

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Table 7

Fig.13

Table 8

Table 9

Fig.14

References 29

1	Committee on a study for a future strategic highway research program. Strategic Highway Research: Saving Lives, Reducing Congestion, Improving Quality of Life—Special Report 260[M]. National Academies Press, 2001.
2	曲大义, 杨晶茹, 邴其春, 等. 基于干线车流排队特性的相位差优化模型[J]. 吉林大学学报: 工学版, 2018, 48(6): 1685-1693.
	Qu Da-yi, Yang Jing-ru, Bing Qi-chun, et al. Arterial traffic offset optimization based on queue characteristics at adjacent intersections[J]. Journal of Jilin University(Engineering and Technology Edition), 2018, 48(6): 1685-1693.
3	姚荣涵, 刘美妮, 徐洪峰. 信号控制交叉口车均延误模型适用性分析[J]. 吉林大学学报: 工学版, 2016, 46(2): 390-398.
	Yao Rong-han, Liu Mei-ni, Xu Hong-feng. Applicability analysis of vehicle delay models for isolated signalized intersection[J]. Journal of Jilin University(Engineering and Technology Edition), 2016, 46(2): 390-398.
4	Lin H F, Fu Q, Zhang H J, et al. Influence of heavy vehicles on traffic flow in highway work zone based on delay analysis[J]. Journal of Tongji University(Natural Science), 2008(3): 335-338.
5	Chen C P, Evans D, Schonfeld P M. Work zone optimization for multiple-lane highway resurfacing projects with time constraints and alternate route[C]∥85th Annual Meeting of the Transportation Research Record, Washington DC, 2006: 30-45.
6	Du B, Chien S, Lee J, et al. Artificial neural network model for estimating temporal and spatial freeway work zone delay using probe-vehicle data[J]. Transportation Research Record, 2016, 2573(1): 164-171.
7	Du B, Chien S, Lee J, et al. Predicting freeway work zone delays and costs with a hybrid machine-learning model[J]. Journal of Advanced Transportation, 2017, 2017: 1-8.
8	Lee H Y. Optimizing schedule for improving the traffic impact of work zone on roads[J]. Automation in Construction, 2009, 18(8): 1034-1044.
9	朱永光. 高速公路施工区交通组织与作业段长度优化研究[D]. 西安: 长安大学材料科学与工程学院, 2010.
	Zhu Yong-guang. Optimization of traffic organization & work zone lengths in freeway[D]. Xi'an: School of Materials Science and Engineering, Chang'an University, 2010.
10	徐吉谦, 陈学武. 交通工程总论[M]. 3版. 北京: 人民交通出版社, 2008.
11	Pokorny P. Determining traffic levels in cities using google maps[C]∥International Conference on Mathematics & Computers in Sciences & in Industry, Greece, 2017: 144-147.
12	刘瑶杰. 基于实时路况的交通拥堵时空聚类分析[D]. 北京: 首都师范大学资源环境与旅游学院, 2014.
	Liu Yao-jie. Clustering analysis of traffic congestion based on real-time traffic conditions[D]. Beijing: College of Resource Environment and Tourism, Capital Normal University, 2014.
13	王芹, 谢元礼, 段汉明, 等. 基于实时路况的西安交通拥堵研究[J]. 西北大学学报: 自然科学版, 2017, 47(4): 622-626.
	Wang Qin, Xie Yuan-li, Duan Han-ming, et al. On Xi'an traffic congestion based on real-time traffic data[J]. Journal of Northwest University(Natural Science Edition), 2017, 47(4): 622-626.
14	佚名. 百度地图API详解之地图坐标系统[EB/OL].[2011-07-02].
15	江波. 基于浮动车数据的实时交通状态估计[D]. 济南: 山东大学控制科学与工程学院, 2011.
	Jiang Bo. Estimation of real-time traffic state based on floating car data[D]. Jinan: School of Control Science and Engineering, Shandong University, 2011.
16	周洋. 基于GPS浮动车的高速公路实时路况系统的研究[D]. 南昌: 南昌航空大学航空制造工程学院, 2012.
	Zhou Yang. Research on real-time traffic system of the highway based on GPS floating vehicle[D]. Nanchang: School of Aeronautical Manufacturing Engineering, Nanchang Hangkong University, 2012.
17	张亚平, 杨龙海, 刘丽华, 等. 交通流理论[M]. 哈尔滨: 哈尔滨工业大学出版社, 2016.
18	王炜. 公路交通流车速-流量实用关系模型[J]. 东南大学学报: 自然科学版, 2003, 33(4): 487-491.
	Wang Wei. Practical speed-flow relationship model of highway traffic-flow[J]. Journal of Southeast University(Natural Science Edition), 2003, 33(4): 487-491.
19	周荣贵, 钟连德. 公路通行能力手册[M]. 北京: 人民交通出版社股份有限公司, 2017.
20	Jiang Y. A model for estimation of traffic delays and vehicle queues at freeway work zones[J]. Transportation Quarterly, 2001, 55(4): 65-81.
21	周茂松. 公路养护作业区交通优化的若干问题研究[D]. 上海: 同济大学交通运输工程学院, 2005.
	Zhou Mao-song. Study on several issues of traffic optimization in highway maintenance work zone[D]. Shanghai: College of Transportation Engineering, Tongji University, 2005.
22	Park S B, Douglas K D, Griffith A S, et al. Factors of importance for determining daytime versus nighttime operations in oregon[J]. Transportation Research Record, 2002, 1813(1): 305-313.
23	李晓龙. 运营高速公路施工作业区安全保障技术及工作区长度研究[D]. 西安: 长安大学运输工程学院, 2014.
	Li Xiao-long. A study on optimization design of safety control technology and length for highway work zone[D]. Xi'an: College of Transportation Engineering, Chang'an University, 2014.
24	许国初. 道路用户成本分析与应用研究[D]. 长沙: 湖南大学土木程程学院, 2008.
	Xu Guo-chu. Road user cost analysis and applied research[D]. Changsha: College of Civil Engineering, Hunan University, 2008.
25	吴江玲. 高速公路养护作业区车辆换道行为及模型研究[D]. 西安: 长安大学运输工程学院, 2017.
	Wu Jiang-ling. Lane-changing behavior analysis and modeling of lane-changing in work zones on freeways[D]. Xi'an: College of Transportation Engineering, Chang'an University, 2017.
26	国家统计局. 中国统计年鉴2018[M]. 北京: 中国统计出版社, 2018.
27	谢胜加. 高速公路沥青路面养护效益评价方法研究[D]. 南京: 东南大学交通学院, 2016.
	Xie Sheng-jia. Research on evaluation method of maintenance benefit of highway asphalt pavement[D]. Nanjing: School of Transportation, Southeast University, 2016.
28	Dixon K K, Hummer J E, Lorscheider A R. Capacity for North Carolina freeway work zones[J]. Transportation Research Record, 1996, 1529(1): 27-34.
29	潘玉利. 路面管理系统原理[M]. 北京: 人民交通出版社, 1998.

Related Articles 15

[1]	Chang-ping WEN,Huan-xia REN. Constitutive relation with double yield surfaces of bioenzyme⁃treated expansive soil based on Lade model [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(5): 1716-1723.
[2]	Yuan-yuan WANG,Lu SUN,Wei-dong LIU,Jin-shun XUE. Constraint improvement of binocular reconstruction algorithm used to measure pavement three-dimensional texture [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(4): 1342-1348.
[3]	Yong PENG,Han-duo YANG,Xue-yuan LU,Yan-wei LI. Effect of void characteristics on virtual shear fatigue life of asphalt mixtures using discrete element method [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 956-964.
[4]	Wei-gang ZHU,Chao ZHU,Ya-qiu ZHANG,Hai-bin WEI. Construction and quality evaluation of digital elevation model based on convolution grid surface fitting algorithm [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 1073-1080.
[5]	Yong-chun CHENG,He LI,Li-ding LI,Hai-tao WANG,Yun-shuo BAI,Chao CHAI. Analysis of mechanical properties of asphalt mixture affected by aggregate based on grey relational degree [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 925-935.
[6]	Ya-feng GONG,Yun-ze PANG,Bo WANG,Guo-jin TAN,Hai-peng BI. Mechanical properties of new prefabricated box culvert structure based on road conditions in Jilin Province [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(3): 917-924.
[7]	En-hui YANG,Jia-qiu XU,You-zhi TANG,Ao LI,Yan-jun QIU. Effect of warm mixing agents on fracture and aging properties of asphalt [J]. Journal of Jilin University(Engineering and Technology Edition), 2021, 51(2): 604-610.
[8]	Wen-ting DAI,Ze-hua SI,Zhen WANG,Qi WANG. Test on road performance of soils stabilized by sisal fiber and ionic soil stabilizer with cement [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 589-593.
[9]	Yu FANG,Li-jun SUN. Urban bridge performance decay model based on survival analysis [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(2): 557-564.
[10]	Yi-bin LI,Jia-min GUO,Qin ZHANG. Methods and technologies of human gait recognition [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 1-18.
[11]	Ying WANG,Ping LI,Teng-fei NIAN,Ji-bin JIANG. Short-term water damage characteristics of asphalt mixture based on dynamic water scour effect [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 174-182.
[12]	Ping WAN,Chao-zhong WU,Xiao-feng MA. Discriminating threshold of driving anger intensity based on driving behavior features by ROC curve analysis [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 121-131.
[13]	Rui XIONG,Ning QIAO,Ci CHU,Fa YANG,Bo-wen GUAN,Yan-ping SHENG,Dong-yu NIU. Investigation on low-temperature rheology and adhesion properties of salt-doped asphalt mortars [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 183-190.
[14]	Chun-feng ZHU,Yong-chun CHENG,Chun-yu LIANG,Bo XIAO. Road performance experiment of diatomite⁃basalt fiber composite modified asphalt mixture [J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(1): 165-173.
[15]	Sheng-tong DI,Chao JIA,Wei-guo QIAO,Kang LI,Kai TONG. Loading rate effect of meso⁃damage characteristics of crumb rubber concrete [J]. Journal of Jilin University(Engineering and Technology Edition), 2019, 49(6): 1900-1910.

Metrics

Viewed

Full text

Abstract

Cited

Shared

Discussed

Comments

Recommended 0

No Suggested Reading articles found!

序号	交通量/［pcu·（h·ln）^-1］	速度均值/（km·h^-1）	序号	交通量/［pcu·（h·ln）^-1］	速度均值/（km·h^-1）
1	1040	67.7	7	1080	65.7
2	1100	65.1	8	1060	61.1
3	1080	61.7	9	980	62.5
4	1020	69.9	10	1060	65.1
5	1100	60.2	11	1000	67.1
6	940	68.8	12	940	65.1

序号	交通量/［pcu·（h·ln）^-1］	序号	交通量/［pcu·（h·ln）^-1］	序号	交通量/［pcu·（h·ln）^-1］
1	1800	5	1740	9	1860
2	1800	6	1920	10	1860
3	1740	7	1680	11	1680
4	1920	8	1680	12	1740

场景	畅通速度/（km·h^-1）	畅通交通量/（pcu·h^-1·ln^-1）	拥堵速度/（km·h^-1）	拥堵交通量/（pcu·h^-1·ln^-1）
1	67	1047	18	1911
2	63	1200	18	1911
3	70	850	18	1911
4	67	1047	5	2100

项目	总费用最大	总费用最小
总费用/元	5 772 700	17 429
施工费用/元\|占比/%	10 562\|0.2	10 562\|60.6
延误费用/元\|占比/%	5 761 228\|99.8	5 958\|34.2
事故费用/元\|占比/%	83\|0.0	84\|0.48
燃油费用/元\|占比/%	824\|0.0	825\|4.7

Short⁃term maintenance operation start time optimization based on real⁃time traffic map data

RICH HTML

PDF (PC)