多模式公交网络中考虑定制公交的活动与出行建模

交通运输系统工程与信息 ›› 2019, Vol. 19 ›› Issue (4): 20-27.

• 综合交通运输体系论坛 • 上一篇下一篇

多模式公交网络中考虑定制公交的活动与出行建模

付晓^*，顾宇，刘志远

东南大学交通学院，南京 210096

收稿日期:2018-12-04 修回日期:2019-03-07 出版日期:2019-08-25 发布日期:2019-08-26
作者简介:付晓(1988-)，女，安徽蚌埠人，副教授.
基金资助:
国家自然科学基金/National Natural Science Foundation of China(71601045)；江苏省自然科学基金/Natural Science Foundation of Jiangsu Province, China(BK20160676)；江苏省“六大人才高峰”高层次人才项目/Six Talent Peaks Project of Jiangsu Province(RJFW-006).

Scheduling Activity and Travel Patterns in Multi-modal Transit Networks with Customized Bus Services

FU Xiao, GU Yu, LIU Zhi-yuan

School of Transportation, Southeast University, Nanjing 210096, China

Received:2018-12-04 Revised:2019-03-07 Online:2019-08-25 Published:2019-08-26

摘要/Abstract

摘要：

近年来，由于一些新型交通服务的出现与迅速发展，多模式公交网络包含了更多的交通模式.定制公交作为一种创新的公共交通服务，在中国许多城市引起了人们的广泛关注. 针对包含定制公交的多模式公交网络，本文提出了基于活动的模型以模拟出行者的活动与出行行为.本模型探究了由于定制公交的出现，人们在多模式公交网络中的行为决策变化，并采用了超级网络以同时模拟用户的活动与出行行为.为研究定制公交的容量约束与预约机制，在模型中有效模拟了用户的逐日学习与调整过程.本文通过实例验证了所提出模型的有效性，结果显示，定制公交的运营显著影响了出行者的活动与出行行为.

关键词: 综合交通运输, 活动与出行决策, 网络建模, 多模式公交网络, 逐日学习与调整, 定制公交服务

Abstract:

In recent years, emerging mobility services are developed rapidly which make people face a wide range of transport modes in multi-modal transit networks. As an innovative mode of public transit, customized bus (CB) services attract increasing attention in many cities of China. In this paper, an activity- based model is proposed for scheduling individuals’daily activity- travel patterns (DATPs) in multi-modal transit networks with the emerging CB services. The change of individuals’activity and travel choice behavior is investigated after CB services are introduced in multi-modal transit networks. A super- network platform is adopted to simultaneously consider individuals’activity and travel choices. To describe the CB subscription process considering capacity constraint, a day- to- day learning and adjustment process is incorporated in the proposed model. A numerical example is conducted to illustrate the proposed model. The results show that the operation of CB significantly impact individuals’DATP choices.

Key words: integrated transportation, activity and travel choice behavior, network modeling, multi-modal transit network, day-to-day learning and adjustment, customized bus services

中图分类号:

付晓，顾宇，刘志远. 多模式公交网络中考虑定制公交的活动与出行建模[J]. 交通运输系统工程与信息, 2019, 19(4): 20-27.

FU Xiao, GU Yu, LIU Zhi-yuan. Scheduling Activity and Travel Patterns in Multi-modal Transit Networks with Customized Bus Services[J]. Journal of Transportation Systems Engineering and Information Technology, 2019, 19(4): 20-27.

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链接本文: http://www.tseit.org.cn/CN/abstract/abstract19865.shtml

http://www.tseit.org.cn/CN/Y2019/V19/I4/20

参考文献

[1] ARENTZE T, TIMMERMANS H. Multistate supernetwork approach to modelling multi- activity, multimodal trip chains[J]. International Journal of Geographical Information Science, 2004, 18(7): 631- 651.

[2] FU X, LAM W H K. Modelling joint activity-travel pattern scheduling problem in multi- modal transit networks[J]. Transportation, 2016， DOI: 10.1007/ s11116-016-9720-8.

[3] LIU T, CEDER A. Analysis of a new public-transportservice concept: Customized bus in China[J]. Transport Policy, 2015(39): 63-76.

[4] 郑汉, 张星臣, 王志美. 混合车型需求响应公交服务定制问题研究[J]. 交通运输系统工程与信息, 2018, 18 (2): 157-163. [ZHENG H, ZHANG X C, WANG Z M. Design of demand- responsive service by mixed- type vehicles[J]. Journal of Transportation Systems Engineering and Information Technology, 2018, 18(2): 157-163.]

[5] 雷永巍, 林培群, 姚凯斌. 互联网定制公交的网络调度模型及其求解算法[J]. 交通运输系统工程与信息, 2017, 17(1): 157-163. [LEI Y W, LIN P Q, YAO K B. The network scheduling model and its solution algorithm of internet customized shuttle bus[J]. Journal of Transportation Systems Engineering and Information Technology, 2017, 17(1): 157-163.]

[6] AN N, BRAEKERS K, DECLERCQ K, et al. Assessing the impact of different policy decisions on the resource requirements of a demand responsive transport system for persons with disabilities[J]. Transport Policy, 2015 (44): 48-57.

[7] DIANA M, QUADRIFOGLIO L, PRONELLO C. A methodology for comparing distances traveled by performance-equivalent fixed-route and demand responsive transit services[J]. Transportation Planning &Technology, 2009, 32(4): 377-399.

[8] 徐红利, 周晶, 徐薇. 考虑参考点依赖的随机网络用户均衡与系统演化[J]. 系统工程理论与实践, 2010, 30 (12): 2283-2289. [XU H L, ZHOU J, XU W. Stochastic network user equilibrium and system evolution with dependence on reference point[J]. Systems Engineering - Theory & Practice, 2010, 30(12): 2283- 2289.]

[9] JHA M, MADANAT S, PEETA S. Perception updating and day- to- day travel choice dynamics in traffic networks with information provision[J]. Transportation Research Part C, 1998, 6(3): 189-212.

[10] BOGERS E, VITI F, HOOGENDOORN S. Joint modeling of advanced travel information service, habit, and learning impacts on route choice by laboratory simulator experiments[J]. Transportation Research Record Journal of the Transportation Research Board, 2005, 1926(1): 189-197.

[11] CHEN R, MAHMASSANI H. Travel time perception and learning mechanisms in traffic networks[J]. Transportation Research Record Journal of the Transportation Research Board, 2004, 1894(1894): 209- 221. 上接第12 页 [4] 袁长伟, 吴群琪, 韦达利, 等. 考虑拒载的出租车市场平衡机制与优化模型[J]. 中国公路学报, 2014, 27(6): 91-97. [YUAN C W, WU Q Q, WEI D L, et al. Optimal modeling and equilibrium mechanism of taxi market with consideration of service refusal[J]. China Journal of Highway and Transport, 2014, 27(6): 91-97.] [5] 尹贻林, 杨旋. 新兴移动打车软件对我国出租车市场均衡

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多模式公交网络中考虑定制公交的活动与出行建模

Scheduling Activity and Travel Patterns in Multi-modal Transit Networks with Customized Bus Services

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