| 交通信息下基于出行链的通勤出行方式选择行为 |
| 投稿时间：2015-05-27 修订日期：2015-09-15 点此下载全文 |
| 引用本文：张华歆,苏逸飞,智路平.交通信息下基于出行链的通勤出行方式选择行为[J].上海海事大学学报,2016,37(1):49-54. |
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| 基金项目:上海市科学技术委员会项目（13510501700）；上海海事大学校基金（20120081） |
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| 中文摘要:为研究移动互联网广泛应用的背景下通勤者的出行行为，探索交通信息对居民在通勤出行链中出行方式选择行为的影响，以RP（Revealed Preference）调查获取的出行者交通信息使用属性、通勤出行链模式、社会经济属性和出行方式选择行为数据，建立通勤出行方式选择多项Logit模型.研究发现：（1）复杂出行链模式会更多地促进停车换乘（Park and Ride, P&R）方式的生成；（2）随着交通信息查询频率的提高，P&R发生的概率比公共交通和私家车都更高；（3）高收入群体在通勤出行中更愿意选择P&R方式，而非私家车方式；（4）通勤者对交通信息查询的满意度越高，越能促进小汽车出行向公共交通的转移.上述结论为交通需求管理和交通信息诱导等政策制定提供理论基础和实证依据. |
| 中文关键词:通勤 出行方式选择 出行链 交通信息 多项Logit模型 RP调查 |
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| Travel mode choice behavior of commuters based on trip chain and traffic information |
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| Abstract:To investigate the commuters’ travel behavior under the background of widely used mobile internet and the impact of traffic information on the commuters’ travel mode choice in the trip chain, Revealed Preference (RP) survey is adopted to collect the commuters’ data, which include traffic information query attributes, trip chain patterns, socio demographic attributes, and travel mode choice behavior data. A multinomial Logit model is built to quantify the commuters’ travel mode choice. The empirical research shows that: (1) the complex trip chain can promote more Park and Ride (P&R); (2) the higher the frequency of traffic information query, the higher the probability for travelers to choose P&R, and it’s higher than that of public transportation and private cars; (3) the commuters with higher income would rather choose P&R than private cars; (4) the higher the commuters’ satisfaction with traffic information query, the more possible that they transfer from private cars to public transportation. The results above provide theoretical basis and empirical evidence for the policy formulation of the traffic demand management and traffic information guidance. |
| keywords:commuting travel mode choice trip chain traffic information multinomial Logit model Revealed Preference (RP) survey |
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