手机APP出行调查系统开发及其模型应用研究

出行调查是出行需求预测模型的重要的数据来源,而国内外近几年使用的调查方法费时费力、数据量不大且很多处于理论阶段无法应用到实际中.为了解决当前调查方法中存在的问题,设计了一套基于手机APP的出行调查系统,同时还探讨了将收集到的出行数据运用到交通规划模型中的问题.该系统在注册填写个人信息以及收集轨迹数据的基础上,利用当前定位技术无法准确获知居民室内位置的特点,以达到收集居民出行数据的目的.具体方法是计算一定时间内轨迹数据的定位精度和速度来判断该段时间居民是否停留,然后将识别出的停留点根据距离进行合并,居民出行结束后在合并后的停留点位置填写相应的出行信息.从在上海青浦区的居民调查中可知,此系统使用的停留点识别方法其识别精度达到96%,因此利用该方法能够客观地收集居民出行过程中活动的空间位置和时间信息,对提升出行预测模型的精度具有重要意义. 

A Mobile Phone APP for Travel Survey and its Application

Travel survey is an important data source for travel demand forecasting models.It is primarily relying on artificial completed,which is time-consuming and laborious.Besides,its data amount is too small to be used in actual situations.To solve these problems,a mobile phone APP for travel survey is developed and its application on traffic planning is developed.Currently,a person who stays indoor cannot be accurately located by mobile phone data.In this study,velocity and accuracy of trajectory data of mobile phone are used to identify whether the person stays or not.Then "stay points" are merged according to distance.People can use this APP to add their travel information on these "stay points".Compared with a travel survey in Qingpu district in Shanghai,the recognition accuracy of the APP is 96%.This method can objectively collect spatial location and time information of travel activities of people,and is of great significance to improve the accuracy of travel forecasting models.