Simulation Analysis on Influence of Congestion Propagation on  Operation of Carsharing Systems

HU Lu; LIANG Zhimei; JIANG Yangsheng

doi:10.3969/j.issn.0258-2724.20220231

Volume 58 Issue 3

Jun. 2023

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Journal of Southwest Jiaotong University > 2023 > 58(3): 499-510.

SHI Haiou, YUAN Quan, ZHANG Yunlin, ZENG Wenqu, ZHENG Qing, DING Guofu. Multi-Discipline Forward Collaborative Design Technology Based on BIM Interaction and Data-Driven[J]. Journal of Southwest Jiaotong University, 2021, 56(1): 176-181. doi: 10.3969/j.issn.0258-2724.20200035

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HU Lu, LIANG Zhimei, JIANG Yangsheng. Simulation Analysis on Influence of Congestion Propagation on Operation of Carsharing Systems[J]. Journal of Southwest Jiaotong University, 2023, 58(3): 499-510. doi: 10.3969/j.issn.0258-2724.20220231

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Simulation Analysis on Influence of Congestion Propagation on Operation of Carsharing Systems

doi: 10.3969/j.issn.0258-2724.20220231

HU Lu^{1, 2
,},
LIANG Zhimei^{1, 2
,},
JIANG Yangsheng^{1, 2}

1.
School of Transportation and Logistics, Southwest Jiaotong University, Chengdu 610031, China
2.
National Engineering Laboratory of Integrated Transportation Big Data Application Technology, Southwest Jiaotong University, Chengdu 610031, China

Received Date: 31 Mar 2022
Rev Recd Date: 31 Aug 2022

Available Online: 28 Apr 2023

Publish Date: 22 Sep 2022

Abstract

Abstract

With the increasing penetration of carsharing, vehicle overflow and congestion propagation at the level of station and path tend to be serious. In order to describe the influence mechanism of congestion propagation on the operation of carsharing systems, firstly, a queuing network of the carsharing system is built with time-varying and state-dependence properties. Secondly, based on C# language and O²DES framework of discrete event simulation, a simulation model of the carsharing system under dynamic stochastic environment is proposed, which allows for the influence of vehicle–road interaction and congestion propagation. The influence of congestion propagation on the operation of the carsharing system is analyzed in terms of the station and path levels. Finally, a small-scale carsharing system, i.e., three stations in Chengdu, is exemplified. The proposed model and the infinite queuing model in virtual space are compared and analyzed under different transfer ratios, demands and road congestion scenarios. The results show that congestion propagation at the stations and paths will decline the system service rate by 9.3%–16.9%. Compared with the infinite queuing model, the proposed model can better reflect the actual operation of the carsharing system because of considering congestion propagation. When the occupancy rate of the road network reaches 70% (the road network is in moderate congestion), the proposed carsharing system can achieve maximum benefits. The introduction of the carsharing system will bring new changes to the dynamic allocation of road resources. When the proportion of users from public transportation to the carsharing system exceeds 70%, it will intensify the congestion of the road network, which is not conducive to the effective operation and sustainable development of the carsharing system.
- sharing transportation,
- queuing network,
- discrete event simulation,
- carsharing system,
- congestion propagation,
- vehicle–road interaction

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References

[1]	YE J H, WANG D G, LI X, et al. Assessing one-way carsharing’s impacts on vehicle ownership: evidence from Shanghai with an international comparison[J]. Transportation Research Part A: Policy and Practice, 2021, 150: 16-32. doi: 10.1016/j.tra.2021.05.012
[2]	张淼,惠英,汪鸣泉. 汽车共享对城市温室气体排放的影响[J]. 中国人口 · 资源与环境,2012,22(9): 48-53. doi: 10.3969/j.issn.1002-2104.2012.09.008 ZHANG Miao, HUI Ying, WANG Mingquan. Urban greenhouse gas emission of car sharing[J]. China Population, Resources and Environment, 2012, 22(9): 48-53. doi: 10.3969/j.issn.1002-2104.2012.09.008
[3]	XU M, MENG Q, LIU ZY. Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment[J]. Transportation Research Part B:Methodological, 2018, 111: 60-82. doi: 10.1016/j.trb.2018.03.001
[4]	BAPTISTA P, MELO S, ROLIM C. Car sharing systems as a sustainable transport policy: a case Study from Lisbon, Portugal[M]//ATTARD M, SHIFTAN Y. Transport and Sustainability. [S.l.]: Emerald Group Publishing Limited, 2015: 205-227.
[5]	NANSUBUGA B, KOWALKOWSKI C. Carsharing: a systematic literature review and research agenda[J]. Journal of Service Management, 2021, 32(6): 55-91. doi: 10.1108/JOSM-10-2020-0344
[6]	曹可心,邓羽. 城市共享汽车分布的时空演变及影响因素研究:以北京市主城区为例[J]. 地理科学,2021,41(10): 1792-1801. CAO Kexin, DENG Yu. Spatial-temporal characteristics and impacting factors of carsharing in Beijing[J]. Scientia Geographica Sinica, 2021, 41(10): 1792-1801.
[7]	伊二妮. 基于排队论的汽车共享服务系统车辆配置优化研究[D]. 青岛: 山东科技大学, 2018.
[8]	EFTHYMIOU D, ANTONIOU C, WADDELL P. Factors affecting the adoption of vehicle sharing systems by young drivers[J]. Transport Policy, 2013, 29: 64-73. doi: 10.1016/j.tranpol.2013.04.009
[9]	刘向,洪林,王宁,等. 基于时空消耗的共享汽车拥堵治理效用研究[J]. 汽车工程学报,2020,10(5): 335-341. doi: 10.3969/j.issn.2095-1469.2020.05.04 LIU Xiang, HONG Lin, WANG Ning, et al. Research on the effect of car-sharing on traffic congestion management based on spatiotemporal consumption[J]. Chinese Journal of Automotive Engineering, 2020, 10(5): 335-341. doi: 10.3969/j.issn.2095-1469.2020.05.04
[10]	高永,安健,全宇翔. 网络约租车对出行方式选择及交通运行的影响[J]. 城市交通,2016,14(5): 1-8. doi: 10.13813/j.cn11-5141/u.2016.0501 GAO Yong, AN Jian, QUAN Yuxiang. The impact of APP-based car sharing on travel mode shift and transportation operation performance[J]. Urban Transport of China, 2016, 14(5): 1-8. doi: 10.13813/j.cn11-5141/u.2016.0501
[11]	张三省,苏倩,张俊青. 基于系统动力学的网约车政策对城市交通的影响研究[J]. 天津大学学报(社会科学版),2019,21(6): 494-502. ZHANG Sanxing, SU Qian, ZHANG Junqing. Analysis of the influence of ride-hailing policy on urban traffic based on system dynamics[J]. Journal of Tianjin University (Social Sciences), 2019, 21(6): 494-502.
[12]	ZHAO M, LI X, YIN J, et al. An integrated framework for electric vehicle rebalancing and staff relocation in one-way carsharing systems: model formulation and Lagrangian relaxation-based solution approach[J]. Transportation Research Part B: Methodological, 2018, 117: 542-572. doi: 10.1016/j.trb.2018.09.014
[13]	HU L, LIU Y. Joint design of parking capacities and fleet size for one-way station-based carsharing systems with road congestion constraints[J]. Transportation Research Part B: Methodological, 2016, 93: 268-299. doi: 10.1016/j.trb.2016.07.021
[14]	DENG Y H, CARDIN M A. Integrating operational decisions into the planning of one-way vehicle-sharing systems under uncertainty[J]. Transportation Research Part C: Emerging Technologies, 2018, 86: 407-424. doi: 10.1016/j.trc.2017.11.018
[15]	KASPI M, RAVIV T, TZUR M. Parking reservation policies in one-way vehicle sharing systems[J]. Transportation Research Part B: Methodological, 2014, 62: 35-50. doi: 10.1016/j.trb.2014.01.006
[16]	马舒予,胡路,吴佳媛,等. 共享电动汽车系统车队规模与停车泊位数优化[J]. 交通运输工程与信息学报,2022,20(3): 31-42. MA Shuyu, HU Lu, WU Jiayuan, et al. Fleet size and parking capacity optimization of electric carsharing system[J]. Journal of Transportation Engineering and Information, 2022, 20(3): 31-42.
[17]	蒋阳升,李衍,李皓,等. 基于模块化仿真的共享汽车联合调度优化[J]. 西南交通大学学报,2023,58(1): 74-82. doi: 10.3969/j.issn.0258-2724.20210083 JIANG Yangsheng, LI Yan, LI Hao, et al. Optimization for joint relocation of carsharing based on modular simulation[J]. Journal of Southwest Jiaotong University, 2023, 58(1): 74-82. doi: 10.3969/j.issn.0258-2724.20210083
[18]	PARK S, YU W. Analysis of system parameters for one-way carsharing systems[J]. Transportation Letters: the International Journal of Transportation Research, 2021,14(3): 1-11.
[19]	LI H B, ZHU Y C, CHEN Y X, et al. The object-oriented discrete event simulation modeling: a case study on aircraft spare part management[C]//2015 Winter Simulation Conference (WSC). Huntington Beach: IEEE, 2015: 3514-3525.
[20]	LI H B, ZHOU C H, LEE B K, et al. Capacity planning for mega container terminals with multi-objective and multi-fidelity simulation optimization[J]. IISE Transactions, 2017, 49(9): 849-862. doi: 10.1080/24725854.2017.1318229
[21]	张维戈,陈连福,黄彧,等. M/G/K排队模型在电动出租汽车充电站排队系统中的应用[J]. 电网技术,2015,39(3): 724-729. doi: 10.13335/j.1000-3673.pst.2015.03.021 ZHANG Weige, CHEN Lianfu, HUANG Yu, et al. Application of M/G/K queuing model in queuing system of electric taxi charging station[J]. Power System Technology, 2015, 39(3): 724-729. doi: 10.13335/j.1000-3673.pst.2015.03.021
[22]	李仕鹏. 基于排队论的汽车共享优化设计[D]. 杭州: 杭州电子科技大学, 2013.
[23]	KENDALL D G. Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded Markov chain[J]. The Annals of Mathematical Statistics, 1953, 24(3): 338-354
[24]	ZEIGLER B P, PRAEHOFER H, KIM T G. Theory of modeling and simulation: integrating discrete event and continuous complex dynamic systems[M]. 2nd edition. Pittsburgh: Academic Press, 2000: 4-5.
[25]	HU L, ZHAO B, ZHU J X, et al. Two time-varying and state-dependent fluid queuing models for traffic circulation systems[J]. European Journal of Operational Research, 2019, 275(3): 997-1019. doi: 10.1016/j.ejor.2019.01.020

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