社交网络信息对出行时刻选择行为的影响

摘要

As social media and location-aware mobile devices are widespread,travelers not only consult travel experience and information from other people,but also share their information by the platform. This media tool provides a new way for reference. The accuracy of information has influence on individual behavior and system performance. This paper employs the Bayesian learning mechanism to simulate the individual dynamic learning of departure timing within one day and day-by-day. The Agent-based method is used. Different schemes,namely no information,inaccuracy information and accuracy information are investigated and compared. Results show that the proposed model could depict travelers'timing behavior and evaluate the system performance caused by different schemes.%随着社交媒体和基于定位的智能手机普及,人们可以通过社交平台获得其他人的出行经验,同时与别人分享自己的出行信息.这种媒体形式为人们提供了新的出行参考途径.显然,信息的准确与否,对人们的行为和交通系统性能会造成影响.本文使用贝叶斯学习更新机制描述人们的动态学习行为,建立出发时刻选择的Agent-based模拟模型,比较准确社交信息、不准确社交信息和没有社交信息对交通系统的影响.数值结果表明,本文所建立的模型可以刻画出行者的行为特征,并反映信息对交通系统的影响.