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原文传递 Learning Traveler's Risk Preference to Travel Time Reliability Using GPS Probe Data

题名：	Learning Traveler's Risk Preference to Travel Time Reliability Using GPS Probe Data
正文语种：	中文
作者：	Zeng Wei-liang Miwa Tomio Morikawa Takayuki
作者单位：	epartment of ivil Engineering,Nagoya University,Nagoya 464-8603,Japan EcoTopia Science Institute,Nagoya University,Nagoya 464-8603,Japan Institute of Innovation for Future Society,Nagoya University,Nagoya 464-8603,Japan
关键词：	ITS risk-averse preference travel time reliability support vector machine probe vehicle navigation GPS
摘要：	Travel time reliability has been regarded as an important factor in traveler's route choice decisions.This study explores travelers' risk preferences to travel time reliability when they plan a trip.The degree of risk-averse preference is formulated by comparing the on-time arrival probabilities of the least expected travel time path and the selected path under the theory of stochastic dominance.To provide a suitable default value of α (degree of risk-averse preference) for α-reliable shortest path problem in stochastic network, support vector machine is applied to learn and predict the travelers' risk preferences by considering variously individual properties (gender, age) and pre-trip information (OD distance, departure time).Large-scale trip records form probe vehicles are utilized to empirical analysis.The tested performances show that the predicted degrees of risk-averse preference by using support vector machine are much closer to the observed data than linear regression.
会议日期：	20150427
会议举办地点：	南京
会议名称：	2015年南京第十四届亚太智能交通论坛
出版日期：	2015-04-27
母体文献：	2015年南京第十四届亚太智能交通论坛论文集