基于手机信令数据的居民出行调查扩样模型

Sample Expansion Model of Household Travel Survey Using Cellphone Data

摘要:

系统分析了居民出行调查的误差成因，简要介绍了传统加权扩样模型并分析了其局限性，特别是对沉默出行需求揭示不足的缺点。结合手机信令数据用于出行行为研究的优势及特点，提出了利用手机信令数据进行居民出行调查扩样及对挖掘沉默出行需求的方法。设计了包含5个主要步骤的居民出行调查样本数据、交通运行监测数据和手机信令数据相结合的扩样模型结构。以驻点分类技术为基础，建立了基于手机信令数据的出行活动分布模型。在获取长周期手机信令数据推断人口职住分布的基础上，基于居民出行调查RP（revealed preference）数据对交通方式划分模型参数进行了标定。从出行目的组成、时间分布和出行距离分布3个方面，对比分析了调查样本、传统加权扩样模型和新模型的计算结果的差异，结果表明新模型在揭示因瞒报、漏报而产生的沉默出行需求方面作用显著。

Abstract:

In this paper， the causes of errors in household travel surveys were analyzed， the traditional weighted sample expansion model was introduced， and its limitations， especially the lack of unreported trip records were analyzed. Combining the advantages and characteristics of the research method using cellphone data on travel behaviors， a novel model of using cellphone data to expand the sample of household travel surveys and mining unreported trip records was proposed. A sample expansion model was designed including five steps， combining the household travel survey data， traffic operation monitoring data， and cellphone data. Based on the stationary point classification technology， a travel behavior distribution model based on cellphone data was established. The parameters of the model split model were calibrated based on the revealed preference data of household travel surveys. The difference between the results of the survey sample， the traditional weighted sample expansion model， and the proposed model was analyzed from the aspects of travel purpose composition， time of day， and travel distance distribution. The results show that the model proposed reveals the unreported trip record caused by false reports and omissions.