广州花都区电动汽车共享服务仿真研究

doi:10.16182/j.issn1004731x.joss.201811044

摘要/Abstract

摘要： 电动汽车共享服务能够有效降低交通尾气排放,减少私家车拥有量,在智慧城市建设中发挥着重要作用。通过建立电动汽车共享服务微观仿真模型,探讨电动汽车共享措施对城市交通和环境的影响。基于广州花都区的调研数据,构建了包含51个交叉口,107条路段的仿真路网模型,设置5种不同的共享电动汽车服务场景,从多角度实现电动汽车共享服务的评价。仿真结果表明,电动汽车共享服务不会明显影响交通出行效率;然而,其会明显降低交通污染物的排放。

关键词: 电动汽车, 汽车共享, 微观仿真, FLOWSIM

Abstract: Electric vehicle (EV) sharing service plays an important role in the construction of the intelligent city, which can reduce the traffic emissions and cut down the ownership of private cars. In order to explore the traffic and environment effectiveness of the car sharing service, this paper builds a microscopic simulation model of EV sharing service. Based on the survey data, a simulation model containing 51 intersections and 107 roads is conducted. Considering 5 different traffic scenes, the paper evaluates the service from various viewpoints. The results demonstrate that there is no distinct influence on the traffic efficiency. However, the traffic emissions will be reduced evidently.

Key words: electric vehicle, car sharing, microscopic simulation, FLOWSIM

中图分类号:

TP391.9

李婷婷, 吴建平. 广州花都区电动汽车共享服务仿真研究[J]. 系统仿真学报, 2018, 30(11): 4421-4429.

Li Tingting, Wu Jianping. Simulation Study of EV Sharing Service in Huadu District, Guangzhou[J]. Journal of System Simulation, 2018, 30(11): 4421-4429.

参考文献

[1] Wu Y, Wang R, Zhou Y, et al.On-road vehicle emission control in Beijing: past, present, and future[J]. Environmental Science and Technology (S0013-936X), 2011, 45(1): 147-153.
[2] Wang Z.Influence Factor and Promotion Strategy of Electric Vehicles in Cities[J]. Science and Technology Management Research (S1000-7695), 2016, 24: 242-246.
[3] Zhu L, Yu L, Chen X M, et al.Simulated Analysis of Exclusive Bus Lanes on Expressways: Case Study in Beijing, China[J]. Journal of Public Transportation (S1077-291X), 2012, 15(4): 111-128.
[4] Deng T, Nelson J D.Bus Rapid Transit implementation in Beijing: An evaluation of performance and impacts[J]. Research in Transportation Economics (S0739-8859), 2013, 39(1): 108-113.
[5] Boldrini C, Bruno R, Conti M.Characterising demand and usage patterns in a large station-based car sharing system[C]// Computer Communications Workshops. IEEE, 2016: 572-577.
[6] Dias F F, Lavieri P S, Garikapati V M, et al.A behavioral choice model of the use of car-sharing and ride-sourcing services[J]. Transportation (S0049-4488), 2017, 44(6): 1307-1323.
[7] Li W, Li Y, Fan J, et al.Siting of Carsharing Stations Based on Spatial Multi-Criteria Evaluation: A Case Study of Shanghai EVCARD[J]. Sustainability (S2071-1050), 2017, 9(1): 152.
[8] Liu Y Q, Zhang L, Su-Xiu L I, et al. Research on China's Electric Vehicle Car-sharing Business Model Innovation: City Level[J]. Scientific Decision Making (S1006-4885), 2017, 11: 29-53.
[9] Vervaeke M, Calabrese G.Prospective design in the automotive sector and the trajectory of the Bluecar project: An electric car sharing system[J]. International Journal of Vehicle Design (S0143-3369), 2015, 68(4): 245.
[10] Shi X Q, Li X N, Yang J X.Research on Carbon Reduction Potential of Electric Vehicles for Low-Carbon Transportation and Its Influencing Factors[J]. Environmental Science (S0250-3301), 2013, 34(1): 385-394.
[11] Du Y, Wu J, Hu K, et al. Simulation study on improvement of air quality by introducing electric vehicles [J]. International Journal of Modeling Simulation and Scientific Computing (S1793-9623), 2015, 6(4): 1550042 (1)-1550042 (11).
[12] Kudoh Y, Ishitani H, Matsuhashi R, et al.Environmental evaluation of introducing electric vehicles using a dynamic traffic-flow model[J]. Applied Energy (S0306-2619), 2001, 69(2): 145-159.
[13] Bohnes F A, Gregg J S, Laurent A.Environmental Impacts of Future Urban Deployment of Electric Vehicles: Assessment Framework and Case Study of Copenhagen for 2016-2030[J]. Environmental Science and Technology (S0013-936X), 2017, 51(23): 13995-14005.
[14] Wu J, Brackstone M, McDonald M. The validation of a microscopic simulation model: a methodological case study[J]. Transportation Research Part C: Emerging Technologies (S0968-090X), 2003, 11(6): 463-479.
[15] Wu J.Fuzzy logic, Microscopic Simulation and the FLOWSIM model[C]// ACE-UK IT Conference. 1999.
[16] Wu J.Application of Microscopic Transportation Simulation Model on ITS Technology Research and impacts assessment[J]. Journal of Transportation Systems Engineering and Information Technology (S1009-6744), 2001, 1(1): 30-33.
[17] Jia Y, Wu J, Du Y, et al.Study on FLOWSIM and its Application for Isolated Signalized Intersection Assessment[J]. Computer Science (S1002-137X), 2014, 26(10): 2529-2534.
[18] Zhang Q, Guo M, Wu J P.Study on application of FLOWSIM micro-simulation system for urban traffic[J]. Journal of Beijing Jiaotong University (S1673-0291), 2006, 30(6): 16-21.
[19] Jia Y, Wu J, Du Y, et al.Application of FLOWSIM for traffic management and assessment in Shenzhen[J]. Aiaa Journal (S0001-1452), 2015, 27(8): 1881-1887.
[20] Wu J, Brackstone M, McDonald M. Fuzzy sets and systems for a motorway microscopic simulation model[J]. Fuzzy Sets and Systems (S0165-0114), 2000, 116(1): 65-76.
[21] Liu S, Hellendoorn H, Schutter B D.Model Predictive Control for Freeway Networks Based on Multi-Class Traffic Flow and Emission Models[J]. IEEE Transactions on Intelligent Transportation Systems (S1524-9050), 2017, 18(2): 306-320.
[22] Wang J M, Jeong C H, Zimmerman N, et al.Real world vehicle fleet emission factors: Seasonal and diurnal variations in traffic related air pollutants[J]. Atmospheric Environment (S1352-2310), 2018, 184: 77-86.
[23] Liu Y H, Ma J L, Li L, et al.A high temporal-spatial vehicle emission inventory based on detailed hourly traffic data in a medium-sized city of China[J]. Environmental Pollution (S0269-7491), 2018, 236: 324-333.
[24] Keuken M P, Moerman M, Voogt M, et al.Particle number concentration near road traffic in Amsterdam (the Netherlands): Comparison of standard and real- world emission factors[J]. Atmospheric Environment (S1352-2310), 2016, 132: 345-355.
[25] Shang J, Zheng Y, Tong W, et al.Inferring gas consumption and pollution emission of vehicles throughout a city[C]// Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining, New York, New York, USA, 2014.
[26] Luo X, Dong L, Dou Y, et al.Analysis on spatial-temporal features of taxis' emissions from big data informed travel patterns: a case of Shanghai, China[J]. Journal of Cleaner Production (S0959-6526), 2017, 142: 926-935.
[27] Iodice P, Adamo P, Capozzi F, et al.Air pollution monitoring using emission inventories combined with the moss bag approach[J]. Science of the Total Environment (S0048-9697), 2016, 541(11): 1410-1419.