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Transportation professionals strive to gain a deeper understanding of household travel behavior patterns for the purposes of modeling, planning, and maintaining transportation systems. Decision-makers also strive to utilize these patterns for educating, promoting and encouraging the use of alternatives to driving in general and to driving alone in particular. This paper focuses on using innovative technology in travel data collection. The ubiquity of portable devices, such as mobile phones and personal digital assistants (PDAs) in today’s world, provides opportunities to revolutionize travel surveys. In the past, data have been obtained through labor intensive paper and/or telephone interviews then input into computers for analyses. While mobile devices can be utilized as modern survey replacements, the requirement of constant user interaction presents many challenges. This paper discusses the design and field tests of TRAC-IT, a smart application for mobile devices that interrelates real-time user input with global positioning system (GPS) data, while adapting to user behavior to create a comprehensive tool that improves the quality and quantity of collected data. Initial limited field tests show a mean of 6.2 reported daily trips per individual. More comprehensive travel behavior data are anticipated when TRAC-IT is used by a larger number of households for longer durations.
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Stored only when both papers are in the corpus — 3 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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