Extracting Travel Demand for Emergency Situations Using Location-Based Social Network Data

Abstract This paper presents the concept of a modular personalized recommendation system, based on existing social networks. The system offers the users in the affected area to evacuate to their nearest best friend or family member who is outside the danger zone. The output of the system is a near real-time OD matrix, which constitutes an input for transportation evacuation models. A preliminary test case shows success in implementing the system on anonymous real location-based social network data.