Georgia Institute of Technology

Promoting Sustainable Travel within Communities through Behavioral Interventions and Emerging Mobility Solutions

Traditionally, interventions to change travel behavior have relied on penalty-based approaches (such as tolls). Recent discussions have shifted towards monetary incentive-based approaches to promote sustainable modes. However, due to limited funding, relying on monetary incentives alone is not sustainable. Hence, it is important to explore the potential of sustainable non-monetary incentives such as gamification, nudges, […]

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How Effective Are Marker Variables at Predicting Attitudinal Factor Scores? An Out-of-Sample Evaluation

Despite the fact that our existing models are not up to the job of predicting travel behavior in today’s rapidly changing landscape, and despite considerable evidence that attitudes help us explain behavior more completely and more meaningfully, attitudes are nowhere to be found in practice-oriented travel demand forecasting models.  Two main objections have been raised

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A Pilot Experimental Project for Predicting Pedestrian Flows using Computer Vision and Deep Learning

Walking for transportation, health, and pleasure is an essential part of people’s lives in most cities. Knowing where people linger, the destinations that attract them, and how those places are accessed could assist in optimizing business locations and providing better security. In addition, predicting and sharing congestion times and locations (perhaps in real-time as in

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