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Transportation demand management (TDM) strategies are designed to motivate people to modify their travel choices, particularly the drive-alone preference. TDM strategies and policies seek to increase transportation system efficiency and achieve specific objectives such as reduced traffic congestion, road and parking cost savings, increased safety, improved mobility for non-drivers, energy conservation, and pollution emission reductions. Marketing these strategies to the “consumer” in an effective way that results in behavioral changes necessitates a sustained understanding of how, when, where, and why people travel. Therefore, accurate, timely, and comprehensive data are vital in understanding/influencing the consumer as well as for general transportation planning. Data collection processes must make use of new, emerging technologies that help refine the task of monitoring and measuring the behavior to be modified as well as to reduce the burden of data collection on the participant. This paper presents the design, implementation, and testing of the TRAC-IT software architecture for GPS-enabled mobile phones in order to enable both passive and active travel behavior data collection while also supporting real-time location-based services that benefit the end-user. The resulting system presents a unique opportunity to collect high-resolution individual travel behavior data that are instantly transferred to a server for analysis by transportation professionals while giving the user a direct incentive for continuing to participate in long-term travel surveys.
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Stored only when both papers are in the corpus — 22 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
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