深圳大学学报理工版

随着特大城市的发展,柴油车等高排放车辆成为城市的主要移动污染源之一,对大气环境质量控制造成越来越大的压力.基于道路交通车辆的车牌自动识别数据集,从识别断面的车辆通过时空数据推算车辆的行驶轨迹,获取城市级别高排放车辆的热点行驶路径、出行特征及活动规律,为制定车辆减排政策(如高排放车辆的管控及低排放区划定等)提供定量方法和科学依据.提出基于地图应用程序开发接口(application programming interfaces, API)导航的车辆行驶轨迹重构方法,较为真实地还原车辆行驶路径,并结合移动源排放测算(motor vehicle emission simulator, MOVES)模型对行驶车辆的多种污染物排放进行估算.以中国深圳市运行的柴油车为研究对象,分析验证该方法的可行性及可靠性.结果表明,该方法可完整重构柴油车在深圳市的运行轨迹,并实现对排放的估算,为机动车污染物减排提供辅助决策支持.

With the rapid development of megacities, high emission vehicles such as diesel vehicles have become one of the main sources of mobile pollution in cities, which causes more and more pressure on the atmospheric environment. By exploiting automatic license plate recognition data set of road traffic vehicles, we propose a methodology to the vehicle trajectory reconstruction based on the map's real-time navigation application programming interfaces(API). Firstly, we establish the vehicle trajectory from the spatio-temporal data of vehicles in the recognition section. Then we obtain the hot routes, travel characteristics and activity rules of high emission vehicles in the city level. Finally, we combine the trajectory reconstruction results with the emission model of motor vehicle emission simulator(MOVES)to estimate the diesel vehicle emission. In the case study of Shenzhen, we analyze and verify the feasibility and reliability of this method. The experimental results show that the proposed method can reconstruct the trajectory of diesel vehicles in Shenzhen and achieve the estimation of emission, which can provide decision support for vehicle emission reduction.

引言
1 柴油车轨迹还原方法
2 轨迹重构步骤
3 机动车尾气排放模型
4 深圳市柴油车轨迹重构和排放案例分析
5 结语

图1 研究流程图<br/>Fig.1 Flow chart of research ideas

图1 研究流程图
Fig.1 Flow chart of research ideas

图2 车辆轨迹行程划分示意图<br/>Fig.2 Schematic diagram of vehicle track travel division

图2 车辆轨迹行程划分示意图
Fig.2 Schematic diagram of vehicle track travel division

图3 子轨迹OD提取算法流程<br/>Fig.3 OD extraction algorithm flow of sub-trajectory

图3 子轨迹OD提取算法流程
Fig.3 OD extraction algorithm flow of sub-trajectory

图4 地图导航可能路径还原示意图<br/>Fig.4 Possible path restoration map using map navigation API

图4 地图导航可能路径还原示意图
Fig.4 Possible path restoration map using map navigation API

图5 路径匹配示意图<br/>Fig.5 Path matching diagram

图5 路径匹配示意图
Fig.5 Path matching diagram

图6 子轨迹时空信息示意图<br/>Fig.6 Schematic diagram of spatio-temporal information of sub-trajectories

图6 子轨迹时空信息示意图
Fig.6 Schematic diagram of spatio-temporal information of sub-trajectories

图7 MOVES排放模型测算步骤图 <br/>Fig.7 Calculation step diagram of MOVES emission model

图7 MOVES排放模型测算步骤图
Fig.7 Calculation step diagram of MOVES emission model

图8 坐标校准后监测点分布图<br/>Fig.8 (Color online)Distribution map of monitoring points after coordinate calibration

图8 坐标校准后监测点分布图
Fig.8 (Color online)Distribution map of monitoring points after coordinate calibration

图9 轨迹重构热力图<br/>Fig.9 (Color online)Thermodynamic diagram of trajectory reconstruction

图9 轨迹重构热力图
Fig.9 (Color online)Thermodynamic diagram of trajectory reconstruction

图10 柴油车运行强度热力图<br/>Fig.10 (Color online)Thermodynamic diagram of operating strength of diesel vehicles

图10 柴油车运行强度热力图
Fig.10 (Color online)Thermodynamic diagram of operating strength of diesel vehicles

图11 随机5辆柴油车运行轨迹图<br/>Fig.11 (Color online)Trajectory diagram of random five diesel vehicles

图11 随机5辆柴油车运行轨迹图
Fig.11 (Color online)Trajectory diagram of random five diesel vehicles

图12 各区间柴油车期望线图<br/>Fig.12 (Color online)Expectation line diagram of diesel vehicles in each section

图12 各区间柴油车期望线图
Fig.12 (Color online)Expectation line diagram of diesel vehicles in each section

表1 08:00— 09:00主要货运通道排放估算结果及路段信息<br/>Table 1 Emission estimation result and section information of main freight channels from 08:00 am to 09:00 am

表1 08:00— 09:00主要货运通道排放估算结果及路段信息
Table 1 Emission estimation result and section information of main freight channels from 08:00 am to 09:00 am

表2 主要货运通道排放总量在08:00— 09:00所有还原路径排放总量占比<br/>Table 2 Total emissions from major freight channels:total emissions from all reduction paths from 08:00 am to 09:00 am

表2 主要货运通道排放总量在08:00— 09:00所有还原路径排放总量占比
Table 2 Total emissions from major freight channels:total emissions from all reduction paths from 08:00 am to 09:00 am

[1] 中华人民共和国生态环境部. 中国机动车环境管理年报(2019)[EB/OL].(2019- 09- 04)[2020- 02- 05].http://www.mee.gov.cn/hjzl/sthjzk/ydyhjgl/201909/P020190905586230826402.pdf.
[2] 周磊,王伯光,汤大钢.重型柴油车对空气质量的影响及其排放的控制[J].环境科学,2011, 32(8):2177-2183.
[3] OLIVEIRA-NETO F M, HAN L D, JEONG M K. Tracking large trucks in real time with license plate recognition and text-mining techniques[J]. Die Quintessenz, 2009, 2121(2121): 121-127.
[4] 阮树斌,王福建,马东方,等. 基于车牌识别数据的机动车出行轨迹提取算法[J]. 浙江大学学报工学版, 2018, 52(5): 23-31.
[5] 王龙飞. 基于车牌照的车辆出行轨迹分析方法与实践研究[D]. 西安:长安大学, 2011.
[6] RAO Wenming, WU Y, XIA Jingxin, et al. Origin-destination pattern estimation based on trajectory reconstruction using automatic license plate recognition data[J]. Transportation Research Part C: Emerging Technologies, 2018, 95: 29- 46.
[7] FENG Yu, SUN Jian, CHEN Peng. Vehicle trajectory reconstruction using automatic vehicle identification and traffic count data[J]. Journal of Advanced Transportation, 2015, 49(2): 174-194.
[8] MONTANINO M, PUNZO V. Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns[J]. Transportation Research Part B: Methodological, 2015, 80: 82-106.
[9] 曹杨. 基于MOVES模型的深圳市机动车排放清单研究[D]. 哈尔滨:哈尔滨工业大学, 2018.
[10] 郝艳召,邓顺熙,邱兆文,等. 基于MOVES模型的西安市机动车排放清单研究[J]. 环境污染与防治, 2017, 39(3): 227-231.
[11] HUANG Wenke, HU Mingwei. Estimation of the impact of traveler information apps on urban air quality improvement[J]. Engineering, 2018, 4(2): 224-229.
[12] 黄文柯. 基于多方法建模的出行信息服务app交通与环境效益评估[D]. 深圳:深圳大学, 2017.
[13] XIE Yuanchang, CHOWDHURY M, BHAVSAR P, et al. An integrated modeling approach for facilitating emission estimations of alternative fueled vehicles[J]. Transportation Research Part D: Transport and Environment, 2012, 17(1): 15-20.
[14] ABOU-SENNA H, RADWAN E, WESTERLUND K, et al. Using a traffic simulation model(VISSIM)with an emissions model(MOVES)to predict emissions from vehicles on a limited-access highway[J]. Journal of the Air & Waste Management Association, 2013, 63(7): 819-831.
[15] United States EPA. MOVES2014a user guide[EB/OL].(2015-11- 01)[2019- 05- 01]. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100NNCY.pdf.
[16] United States EPA. MOVES2014 and MOVES2014a technical guidance: using MOVES to prepare mission inventories for state implementation plans and transportation conformity[EB/OL].(2018- 08- 01)[2019- 05- 01]. https://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100 V7EY.pdf.

备注

引言

1 柴油车轨迹还原方法

2 轨迹重构步骤

3 机动车尾气排放模型

4 深圳市柴油车轨迹重构和排放案例分析

5 结语

补充材料文件请点击下载

期刊信息

备注

引言