期刊文献+

基于离散-连续选择模型的通勤出行时间预测 被引量:2

Prediction of commuter's time allocation with discrete-continuous choice model
原文传递
导出
摘要 把握出行者的日时间分配是交通行为分析的重要内容之一.本文基于离散-连续建模思想,结合运用Ordered Probit离散选择模型和Hazard连续选择模型,建立了由上班(上学),下班(放学)出发时刻模型和上班(上学),下班(放学)出行耗时模型组成的通勤时间预测模型系统,预测了通勤者的日时间安排.研究表明,所建模型能够以较高的预测精度,预测通勤者的活动-出行时间安排.研究将为活动-出行行为的整体建模预测和分析奠定时间轴预测基础,为城市居民的交通行为分析提供模型工具,为制定交通管理政策,解决城市交通拥挤问题提供决策分析依据. Time allocation is an important issue in travel behavior analysis. Based on the theory of discrete-continuous modeling, this paper presents a model system for commuter's daily time allocation, which is composed of two models for departure time forecasting and two for travel duration prediction. Ordered probit model and hazard model are employed for discrete and continuous modeling, respectively. Based on the model system, commuter's daily time allocation is predicted. The results indicate that the goodness-of-fit of the model system is acceptable. This study can contribute to the development of a comprehensive full-scale model of daily activity-travel patterns. It also provides basis for the theoretical work about travel behavior analysis and modeling as well as the empirical work of transportation planning and management.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2013年第10期2679-2684,共6页 Systems Engineering-Theory & Practice
基金 国家自然科学基金(50908099) 博士后科学基金面上项目(20100481055)
关键词 通勤出行 活动 时间安排 出发时刻 出行耗时 离散-连续模型 ORDERED PROBIT模型 Hazard模型 commute trip activity time allocation departure time travel duration coupled discrete-continuous choice model ordered probit model hazard model
  • 相关文献

参考文献3

二级参考文献51

  • 1陆建,王炜.城市居民出行时耗特征分析研究[J].公路交通科技,2004,21(10):102-104. 被引量:17
  • 2Srinivasan S, Bhat C R. A multiple discrete-continuous model for independent- and joint-discretionary-activity participation decisions[J]. Transportation, 2006, 33(5): 497-515.
  • 3Goulias K G. Activity-based travel forecasting: What are some issues? [ C ]//Activity-based Travel Forecasting Conference. New Orleans: Transportation Institute, 1996: 37-49.
  • 4Kuppam A R,Pendyala R M. A structural equations analysis of commuters' activity and travel patterns[J]. Transportation, 2001, 28(1): 33-54.
  • 5Choo S, Mokhtarian P L. Telecommunications and travel demand and supply: Aggregate structural equation models for the US[ J]. Transportation Research Part A, 2007, 41(1): 4- 18.
  • 6Yamamoto T, Kitamura R. An analysis of time allocation to in-home and out-of-home discretionary activities across working days and non-working days[J]. Transportation, 1999, 26(2) : 211 - 230.
  • 7Lee Y, Hickman M. Household type and structure, time use pattern, and trip chaining behavior[C]//The 83rd Transportation Research Board Annual Meeting. Washington, D. C., 2004.
  • 8Bhat C R, Nair N S. VMT mix modeling for mobile source emissions forecasting: Formulation and empirical application [ R]. Austin, Texas: Center for Transportation Research, the University of Texas at Austin, 2000.
  • 9Sivakumar A, Bhat C R. A fractional split distribution model for statewide commodity flow analysis[J]. Transportation Research Record, 2002, 1790: 80-88.
  • 10Papke L E, Wooldridge J M. Econometric methods for fractional response variables with an application to 401(K) plan participation rates[J]. Journal of Applied Econometrics, 1996, 11(6) : 619 - 623.

共引文献38

同被引文献10

引证文献2

二级引证文献22

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部