| 基于SP调查的需求组合模型参数标定方法 |
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| 引用本文： | 杨超,蔡意田,何树林.基于SP调查的需求组合模型参数标定方法[J].同济大学学报(自然科学版),2013,41(9):1372-1377. |
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| 作者姓名： | 杨超 蔡意田 何树林 |
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| 作者单位： | 同济大学 道路与交通工程教育部重点实验室，上海 201804;同济大学 道路与交通工程教育部重点实验室，上海 201804;同济大学 建筑设计研究院（集团）有限公司，上海 200092 |
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| 基金项目： | 新世纪优秀人才支持计划（NCET-08-0406）；国家自然科学基金（71171147） |
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| 摘 要： | 介绍了交通需求组合模型（CTDM），建立了目的地方式选择组合模型，采用逐层估计的极大似然估计法对其进行参数标定.按照意向偏好SP(stated preference)和行为偏好RP(revealed preference)数据结合使用的要求对SP调查方法加以改进，开发了“基于互联网的个体行为调查设计及数据采集平台”进行数据采集.利用调查数据进行需求组合模型参数标定.以上海市嘉定校区学生观影行为为例，对所提出的方法进行验证.结果表明，通过改进的SP数据标定的参数具有较高的精确度.
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| 关 键 词： | 交通需求组合模型 改进SP调查 参数标定 目的地选择 方式选择 |
| 收稿时间： | 2012/9/27 0:00:00 |
| 修稿时间： | 2013/5/27 0:00:00 |
Parameter Calibration of Combined Travel Demand Model Based on Improved SP Survey |
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| YangChao,CaiYitian and HeShulin.Parameter Calibration of Combined Travel Demand Model Based on Improved SP Survey[J].Journal of Tongji University(Natural Science),2013,41(9):1372-1377. |
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| Authors: | YangChao CaiYitian and HeShulin |
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| Institution: | Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China;Tongji University Architectural Design Research Institute, Shanghai 200092, China |
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| Abstract: | The combined travel demand model (CTDM) was introduced and a combined destination mode choice model was established. The model parameters were estimated by employing the stepwise maximum likelihood estimation method. According to the joint use requirement of stated preference (SP) data and the revealed preference (RP) data, the SP off RP survey method was improved. A web based survey software, web based survey design and data collection platform of individual behavior, was developed to collect data, which was used to calibrate the parameters of the combined destination mode choice model. The parameters of model were calibrated with SP/RP data by taking film watching behavior of students in Jiading campus of Tongji University as example. The results show that parameters calibrated by SP/RP data have better accuracy. |
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| Keywords: | combined travel demand model improved SP off RP survey parameter calibration destination choice mode choice |
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