为了改善历史文化街区的交通出行环境，在北京南锣鼓巷胡同区及附近人口密集的区域开 展调查，进行历史街区出行行为研究。首先，为了提高模型的准确度与可靠性，研究了不同服务人群、服务范围之间的差异性。通过对数据的初步分析，将出行方式划分为公共交通、慢行交通、私人交通3 类，并分析得出该区域内慢行交通出行比例最低。然后，利用SPSS软件对特性变 量与出行方式选择进行相关性分析，筛选特征变量。最后，建立多项Logit 模型（Multinomial Logit Model，简称MNL） 对历史街区出行行为进行分析，并使用南锣鼓巷实测数据对模型进行标定。研究结果表明，居民户口、年龄、月收入、汽车拥有量、胡同宽度、胡同单行线、游客影 响、慢行交通意愿等因素对出行方式选择均有显著影响。

In order to improve the traffic environment in the historical and cultural neighborhoods, an investigation in Nanluoguxiang and the densely populated areas nearby was conducted. The travel behaviors of residents of Nanluoguxiang were studied. Firstly, in order to improve the accuracy and reliability of the model, the differences in service crowds and service areas were studied. Through the preliminary analysis of the data, the travel modes were divided into public transport, slow-moving traffic and private transport. The ratio of slow-moving traffic is the lowest among the three travel modes. Then, the SPSS was used to analyze the relativity between attribute variables and travel mode selection, and the feature variables were screened. Finally, the MNL(Multinomial Logit Model) for analyzing the travel behaviors of residents in the historical district was established, and the parameters were calibrated by the actual survey data of Nanluoguxiang. The results show that residents′ household registration, age, monthly income, car ownership, alley′s width, alley′s single line, tourists′ influence and slow-moving traffic intentions have significant influence on travel behavior.