4.讨论
案例研究的结果表明,交通管理机构可以通过以下几种方式设计简单的票价折扣方案。下面列出的建议面向特定群体,或者放宽了用户的时间置换约束,以此说明用户的不同特征。交通管理机构可以选择是否面向某一群体,但也可以面向不同群体进行不同程度的干预。这些干预措施的可行性取决于乘客对复杂性、合作机会以及财务影响的态度。
定价结构:折扣结构可以模仿消费回扣,在一段时间内(例如每周)提供一次大额返还。这可能会吸引那些忽视小额以及定期折扣的用户,凸显节约总量。另一种选择是引入彩票政策,而不是保证返还。通过让注册用户有机会中彩,造成只有那些对价格更敏感或对参与感兴趣的用户才会参加,这意味着不改变行为的用户中彩的人数更少。注册要求可以让交通管理机构给用户更高的回报或更高的中彩几率,特别是如果它愿意支付与用户票价差价相同的金额。
定价基础:与其仅根据终点站提供折扣,不如针对起始站、特定线路或替代线路提供优惠。这些选项分别能更好地管理出行时间、车内拥挤或更改出发时间的不确定性。在不太拥挤的线路上打折可以平衡整个交通网络的需求,提高运力利用率。智能手机和位置服务与公共交通支付的一体化,使得采用这种基于线路的策略成为可能。
目标客户信息:提供更个性化的信息将帮助乘客做出更好的出行决策,显示最符合其需求的非高峰出行收益。可能的策略包括针对站点或用户的市场营销,或者让在线出行规划者看到特定时间的票价和拥挤数据。用户还可以通过交通管理机构网站上的个性化页面获得具体的出行建议(可能会根据用户所属群组的信息,或者用户特征与面板分析中的各因素之间的关系)。
相比于用新基础设施增加运力,需求干预见效更快、效率更高,但在公共交通中,需求干预通常被视为临时解决方案,直至运力得到增加。然而,即使在运力增加之后,交通管理机构仍可以将公共交通需求管理策略作为补充,为寻找解决其拥堵和业务需求的最佳方案提供更多工具。
5.结论
本文为公共交通系统需求管理策略的设计与评估提出了一个框架。了解与拥堵有关的需求模式和政策实施的背景,可以帮助决策者基于各种参数设计出更有效的政策干预策略。公共交通需求管理策略的评估和监测不仅要考虑需求的总体变化,同时需要详细分析乘客反应,通过反馈指导该策略的不断优化。AFC数据是持续动态评估的可靠数据来源,相较于过去的数据源,AFC数据可用于更精准地研究需求模式。相较于汇总数据分析,聚类分析和面板分析可以更好地洞察用户对所实施策略的反应,且不同于调研数据,它们可以运用在大规模的应用分析上。
本文利用一个公共交通系统的拥堵数据进行了实例研究,验证了本文提出的评估框架的有效性。结果表明,定价激励能有效地将用户转移出高峰时段,导致需求在时间上的再分配。我们对所有用户需求模式的变化进行分析后发现,早鸟优惠对错峰出行有影响,尽管可能不足以逆转外源客流的增长。此外,更多的分解分析(disaggregate analysis)表明,应关注通勤者和间歇用户,优惠活动的目标行程在他们的行程中占相当大的量,而且他们愿意接受票价差异。本研究中其他群组的出行次数太少,不是优惠活动的优先考虑对象,或者需要其他类型的激励措施鼓励他们在非高峰时段出行。面板分析进一步表明,考虑到用户强烈反对改变出行时间,部分设计可能需要调整。增加用户出行的灵活性,改进多式联运,更好地瞄准对价格敏感的用户,都是提高效率的有效方法,通过纵向分析进行监测可以为长期干预提供信息。
本文对行为改变者的识别分析依赖于智能卡数据,将行为改变与优惠活动的设计相关联。考虑在调查的同时进行面板分析的未来研究将使我们可以更精确地预测用户的反应,并更好地控制其他因素,如生活方式特征和社会人口特征。此外,我们还可以对用户行为改变的程度进行更详细的建模,例如序贯选择模型可首先用于对用户是否改变行为的决策建模,其次对有行为改变的行程建模(Ben-Akiva、Lerman and Lerman, 1985)。
(国务院发展研究中心资源与环境政策研究所李继峰译)
参考文献
Anupriya, A., Graham, D., Hrcher, D., & Anderson, R.J.(2018).The Impact of Early Bird Scheme on Commuter Trip Scheduling in Hong Kong: A Causal Analysis Using Travel Card Data.Paper presented at the Transportation Research Board 97th Annual Meeting, Washington DC, United States.
Arthur, D., & Vassilvitskii, S.(2007).K-means++: the Advantages of Careful Seeding.Paper presented at the Proceedings of the Eighteenth Annual ACM-SIAM Symposium on Discrete Algorithms, New Orleans, Louisiana.
Bai, J.(1994).Least Squares Estimation of a Shift in Linear Processes.Journal of Time Series Analysis, 15(5), 453-472.doi:10.1111/j.1467-9892.1994.tb00204.x.
Bamberg, S.,Fujii, S., Friman, M., & Grling, T.(2011).Behaviour Theory and Soft Transport Policy Measures.Transport Policy, 18(1), 228-235.doi:https://doi.org/10.1016/j.tranpol.2010.08.006.
Bamford, C.G., Carrick, R.J., Hay, A.M., & MacDonald, R.(1987).The Use of Association Analysis in Market Segmentation for Public Transport: a Case Study of Bus Passengers in West Yorkshire, UK.Transportation, 14(1), 21-32.doi:10.1007/BF00172464.
Batarce, M., Muoz, J.C., & Ortúzar, J.d.D.(2016).Valuing Crowding in Public Transport: Implications for Cost-benefit Analysis.Transportation Research Part A: Policy and Practice, 91, 358378.doi:https://doi.org/10.1016/j.tra.2016.06.025.
Ben-Akiva, M.E., Lerman, S.R., & Lerman, S.R.(1985).Discrete Choice Analysis: Theory and Application to Travel Demand (Vol.9): MIT press.
Brickman, P., & Campbell, D.(1971).Hedonic Relativism and Planning the Good Society: New York: Academic Press.
Cervero, R.(1990).Transit Pricing Research.Transportation, 17(2), 117-139.doi:10.1007/BF02125332.
Currie, G.(2009).Exploring the Impact of the “Free before 7” Campaign on Reducing Overcrowding on Melbournes Trains.Paper presented at the 32nd Australasian transport research forum, Auckland, New Zealand.
Currie, G.(2011).Design and Impact of a Scheme to Spread Peak Rail Demand Using Pre-peak Free Fares.Paper presented at the European Transport Conference Glasgow, Scotland.
Dale, S., Frost, M.W.,Ison, S.G., & Warren, P.(2015).Evaluating Transport Demand Management Interventions.Paper presented at the Transportation Research Board 94th Annual Meeting, Washington DC, United States.
Ekstrm, J., Sumalee, A., & Lo, H.K.(2012).Optimizing Toll Locations and Levels Using a Mixed Integer Linear Approximation Approach.Transportation Research Part B: Methodological, 46(7), 834-854.doi:https://doi.org/10.1016/j.trb.2012.02.006.
Eriksson, L.,Nordlund, A.M., & Garvill, J.(2010).Expected Car Use Reduction in Response to Structural Travel Demand Management Measures.Transportation Research Part F: Traffic Psychology and Behaviour, 13(5), 329-342.doi:https://doi.org/10.1016/j.trf.2010.06.001.
Ferguson, E.(1990).Transportation Demand Management Planning, Development, and Implementation.Journal of the American Planning Association, 56(4), 442-456.doi:10.1080/01944369008975448.
Grling, T., Eek, D., Loukopoulos, P., Fujii, S., Johansson-Stenman, O., Kitamura, R., ...Vilhelmson, B.(2002).A Conceptual Analysis of the Impact of Travel Demand Management on Private Car Use.Transport Policy, 9(1), 59-70.doi:https://doi.org/10.1016/S0967-070X(01)00035-X.
Grling, T., & Fujii, S.(2006).Travel Behavior Modification: Theories, Methods, and Programs.Paper presented at the 11th international conference on travel behavior research, Kyoto, Japan.
Grling, T., & Schuitema, G.(2007).Travel Demand Management Targeting Reduced Private Car Use: Effectiveness, Public Acceptability and Political Feasibility.Journal of Social Issues, 63(1), 139-153.doi:10.1111/j.1540-4560.2007.00500.x.
Giuliano, G.(1992).Transportation Demand Management: Promise or Panacea?Journal of the American Planning Association, 58(3), 327-335.doi:10.1080/01944369208975811.
Gordon, J.,Koutsopoulos, H., Wilson, N., &Attanucci, J.(2013).Automated Inference of Linked Transit Journeys in London Using Fare-Transaction and Vehicle Location Data.Transportation Research Record: Journal of the Transportation Research Board, 2343, 17-24.doi:10.3141/2343-03.
Goulet-Langlois, G.,Koutsopoulos, H.N., & Zhao, J.(2016).Inferring Patterns in the Multi-week Activity Sequences of Public Transport Users.Transportation Research Part C: Emerging Technologies, 64, 1-16.doi:https://doi.org/10.1016/j.trc.2015.12.012.
Greene-Roesel, R., Castiglione, J., Guiriba, C., & Bradley, M.(2018).BART Perks: Using Incentives to Manage Transit Demand.Transportation Research Record: Journal of the Transportation Research Board.doi:10.1177/0361198118792765.
Halvorsen, A.,Koutsopoulos, H.N., Lau, S., Au, T., & Zhao, J.(2016).Reducing Subway Crowding: Analysis of an Off-Peak Discount Experiment in Hong Kong.Transportation Research Record: Journal of the Transportation Research Board, 2544, 38-46.doi:10.3141/2544-05.
Hamdouch, Y., Florian, M., Hearn, D.W., & Lawphongpanich, S.(2007).Congestion Pricing for Multimodal Transportation Systems.Transportation Research Part B: Methodological, 41(3), 275-291.doi:http://dx.doi.org/10.1016/j.trb.2006.04.003.
Henn, L., Douglas, N., & Sloan, K.(2011).Surveying Sydney Rail Commuters Willingness to Change Travel Time.Paper presented at the 34th Australasian Transport Research Forum Adelaide, Australia.
Hrcher, D., Graham, D.J., & Anderson, R.J.(2017).Crowding Cost Estimation with Large Scale Smart Card and Vehicle Location Data.Transportation Research Part B: Methodological, 95, 105-125.doi:http://dx.doi.org/10.1016/j.trb.2016.10.015.
Hurdle, J.(2014).Use of Public Transit in US Reaches Highest Level Since 1956, Advocates Report.Retrieved from https://www.nytimes.com/2014/03/10/us/use-of-public-transit-in-us-reaches-highestlevel-since-1956-advocates-report.html.
Jolliffe, I.(2011).Principal Component Analysis.In International Encyclopedia of Statistical Science (pp.1094-1096): Springer.
Kachroo, P., Gupta, S., Agarwal, S., & Ozbay, K.(2017).Optimal Control for Congestion Pricing: Theory, Simulation, and Evaluation.IEEE Transactions on Intelligent Transportation Systems, 18(5), 1234-1240.doi:10.1109/TITS.2016.2601245.
Koutsopoulos, H.N., Ma, Z., Noursalehi, P., & Zhu, Y.(2018).Transit Data Analytics for Planning, Monitoring, Control and Information.In C.Antoniou, L.Dimitriou, & F.Pereira (Eds.),Mobility Patterns, Big Data and Transport Analytics(1 ed., pp.448): Elsevier.
Kroes, E., Kouwenhoven, M., Debrincat, L., & Pauget, N.(2014).Value of Crowding on Public Transport in le-de-France, France.Transportation Research Record: Journal of the Transportation Research Board, 2417, 37-45.doi:10.3141/2417-05.
Li, S.-M., & Wong, F.C.L.(1994).The Effectiveness of Differential Pricing on Route Choice.Transportation, 21(3), 307-324.doi:10.1007/BF01099216.
Li, Z., & Hensher, D.A.(2011).Crowding and Public Transport: A Review of Willingness to Pay Evidence and Its Relevance in Project Appraisal.Transport Policy, 18(6), 880-887.doi:https://doi.org/10.1016/j.tranpol.2011.06.003.
Loukopoulos, P.(2007).A Classification of Travel Demand Management Measures.In Threats from Car Traffic to the Quality of Urban Life: Problems, Causes and Solutions (pp.273-292): Emerald Group Publishing Limited.
LTA, S.(2014).Travel smart.Retrieved from http://www.lta.gov.sg/content/ltaweb/en/publictransport/mrt-and-lrt-trains/travel-smart.html.
Luo, D., Cats, O., & Lint, H.v.(2017, 26-28 June 2017).Analysis of Network-wide Transit Passenger Flows Based on Principal Component Analysis.Paper presented at the 2017 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS).
Ma, Z., Ferreira, L., & Mesbah, M.(2014).Measuring Service Reliability Using Automatic Vehicle Location Data.Mathematical Problems in Engineering, 2014.
Ma, Z., & Koutsopoulos, H.N.(2018).Optimal Design of Promotion Based Transit Demand Management Strategies.Working paper.
Ma, Z.,Koutsopoulos, H.N., Chen, Y., & Wilson, N.H.M.(2019).Estimation of Denied Boarding in Rrban Rail Systems: Alternative Formulations and Comparative Analysis.Transportation Research Record.
Mark, S., & Phil, C.(2006).Developments in Transit Fare Policy Reform.Paper presented at the 29th Australasian Transport Research Forum Queensland, Australia.
Maruyama, T., & Sumalee, A.(2007).Efficiency and Equity Comparison of Cordon-and Area-based Road Pricing Schemes Using a Trip-chain Equilibrium Model.Transportation Research Part A: Policy and Practice, 41(7), 655-671.doi:https://doi.org/10.1016/j.tra.2006.06.002.
Maunsell, F.(2007).Demand Management Techniques-peak Spreading.Retrieved from Department for Transport, Transport for London and Network Rail, London, United Kingdom.
Pelletier, M.-P.,Trépanier, M., & Morency, C.(2011).Smart Card Data Use in Public Transit: A Literature Review.Transportation Research Part C: Emerging Technologies, 19(4), 557-568.doi:https://doi.org/10.1016/j.trc.2010.12.003.
Pluntke, C., & Prabhakar, B.(2013).INSINC: A Platform for Managing Peak Demand in Public Transit.JOURNEYS, Land Transport Authority Academy of Singapore, 31-39.
Prudhomme, R., Koning, M., Lenormand, L., & Fehr, A.(2012).Public Transport Congestion Costs: The Case of the Paris Subway.Transport Policy, 21, 101-109.doi:http://doi.org/10.1016/j.tranpol.2011.11.002.
Rose, G.(2007).Appraisal and Evaluation of Travel Demand Management Measures.Paper presented at the 30th Australasian Transport Research Forum, Melbourne, Victoria, Australia.
Rousseeuw, P.J.(1987).Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis.Journal of Computational and Applied Mathematics, 20, 53-65.
Schade, J., & Schlag, B.(2003).Acceptability of Urban Transport Pricing Strategies.Transportation Research Part F: Traffic Psychology and Behaviour, 6(1), 45-61.doi:https://doi.org/10.1016/S13698478(02)00046-3.
Schlag, B., & Teubel, U.(1997).Public Acceptability of Transport Pricing.IATSS Research, 21, 134-142.
Smith, B., & Moniruzzaman, M.(2014).Review of TDM Appraisal and Evaluation Tools.Retrieved from Perth, Australia.
Steg, L.(2003).Factors Influencing the Acceptability and Effectiveness of Transport Pricing.In Acceptability of Transport Pricing Strategies (pp.187-202): Pergamon Press.
Steg, L., & Vlek, C.(1997).The Role of Problem Awareness in Willingness-to-change Car Use and in Evaluating Relevant Policy Measures.Paper presented at the Traffic and Transport Psychology: Theory and Application, Amsterdam, Netherlands.
Taylor, C., Nozick, L., & Meyburg, A.(1997).Selection and Evaluation of Travel Demand Management Measures.Transportation Research Record: Journal of the Transportation Research Board(1598), 4960.
Tibshirani, R., Walther, G., & Hastie, T.(2001).Estimating the Number of Clusters in a Data Set via the Gap Statistic.Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63(2), 411-423.
Tirachini, A., Hurtubia, R., Dekker, T., & Daziano, R.A.(2017).Estimation of Crowding Discomfort in Public Transport: Results from Santiago de Chile.Transportation Research Part A: Policy and Practice, 103, 311-326.doi:https://doi.org/10.1016/j.tra.2017.06.008.
Wang, Z.-j., Li, X.-h., & Chen, F.(2015).Impact Evaluation of a Mass Transit Fare Change on Demand and Revenue Utilizing Smart Card Data.Transportation Research Part A: Policy and Practice, 77, 213224.doi:https://doi.org/10.1016/j.tra.2015.04.018.
Wie, B.-W.(2007).Dynamic Stackelberg Equilibrium Congestion Pricing.Transportation Research Part C: Emerging Technologies, 15(3), 154-174.doi:http://dx.doi.org/10.1016/j.trc.2007.03.002.
Wie, B.-W., & Tobin, R.L.(1998).Dynamic Congestion Pricing Models for General Traffic Networks.Transportation Research Part B: Methodological, 32(5), 313-327.doi:http://dx.doi.org/10.1016/S01912615(97)00043-X.
Yang, H., & Tang, Y.(2018).Managing Rail Transit Peak-hour Congestion with a Fare-reward Scheme.Transportation Research Part B: Methodological, 110, 122-136.doi:https://doi.org/10.1016/j.trb.2018.02.005.
Yap, M., Cats, O., & van Arem, B.(2018).Crowding Valuation in Urban Tram and Bus Transportation Based on Smart Card Data.Transportmetrica A: Transport Science, 1-20.doi:10.1080/23249935.2018.1537319.
Zeileis, A., Kleiber, C., Krmer, W., & Hornik, K.(2003).Testing and Dating of Structural Changes in Practice.Computational Statistics & Data Analysis, 44(1), 109-123.doi:https://doi.org/10.1016/S01679473(03)00030-6.
Zhang, J., Yan, X., An, M., & Sun, L.(2017).The Impact of Beijing Subways New Fare Policy on Riders Attitude, Travel Pattern and Demand.Sustainability, 9(5), 689.
Zhang, Z.,Fujii, H., & Managi, S.(2014).How Does Commuting Behavior Change Due to Incentives? An Empirical Study of the Beijing Subway System.Transportation Research Part F: Traffic Psychology and Behaviour, 24, 17-26.doi:https://doi.org/10.1016/j.trf.2014.02.009.
Zhu, Y.,Koutsopoulos, H.N., & Wilson, N.H.M.(2017a).Inferring Left Behind Passengers in Congested Metro Systems from Automated Data.Transportation Research Part C: Emerging Technologies.doi:https://doi.org/10.1016/j.trc.2017.10.002.
Zhu, Y.,Koutsopoulos, H.N., & Wilson, N.H.M.(2017b).A Probabilistic Passenger-to-Train Assignment Model based on Automated Data.Transportation Research Part B: Methodological.doi:https://doi.org/10.1016/j.trb.2017.04.012.