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原文传递 Innovative Data Travel Collection, Recommendations

题名：	Innovative Data Travel Collection, Recommendations
作者：	Lawson, C.
关键词：	Data collection##Travel behavior data##Forecasting travel behavior##Travel surveys##Recommendations##Methodologies##Transportation modeling##
摘要：	This study had the following objectives: 1. To identify and clarify these two emerging effects – real time data and changing culture, 2. To identify the shifts in data collection and transportation modeling that must take place to assist in identifying and forecasting travel behavior, and 3. To discuss the impacts of such operational shifts, both in cost and outcomes to provide NYMTC with the cost and efficacy impacts of incorporating these emerging tools.” To address these objectives, the research team at Albany Visualization and Informatics Lab (AVAIL), led by Dr. Catherine Lawson, PhD., from the University at Albany, conducted a literature review; a cost benefit analysis of current and emerging transportation data surveying and modeling methodologies; and produced a set of recommendations for the near-term and the longer-term. The literature review and cost benefit analysis revealed certain facts about the state of travel data collection in the United States. The paper travel diary remains the predominant instrument for collecting travel data despite its well-documented shortcomings and high cost. GPS devices have grown in popularity but are used primarily as a supplement for paper travel diaries. The value of travel surveying via smartphones is no longer a strictly academic question as numerous agencies have used the smartphone in a travel survey, either as the primary survey instrument or in a subsample (Indiana, Oregon, Singapore, Boulder, etc.). Origin-destination tables used in travel demand models can be constructed from social media posts and call-detail records though these datasets often lack valuable information (such as reliable trip purpose or mode), present incomplete pictures of travel (especially in the case of social media), are prohibitively aggregated, or are not representative. Finally, the research team found it is possible to develop and deploy a travel demand model that does not use travel survey data for inputs, opening the possibility of eliminating or reducing the size of travel surveys.
总页数：	87
报告类型：	科技报告