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

Ilil Blum Shem-Tov; Shlomo Bekhor

doi:10.1016/j.trpro.2020.02.094

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

Ilil Blum Shem-Tov, Shlomo Bekhor

Civil and Environmental Engineering

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English
Pages (from-to)	111-118
Number of pages	8
Journal	Transportation Research Procedia
Volume	45
DOIs	https://doi.org/10.1016/j.trpro.2020.02.094
State	Published - 2020
Event	2019 Transport Infrastructure and Systems in a Changing World. Towards a more Sustainable, Reliable and Smarter Mobility, TIS Roma 2019 - Rome, Italy Duration: 23 Sep 2019 → 24 Sep 2019

Keywords

Emergency
Evacuation
Location-Based Social Network
OD matrix

ASJC Scopus subject areas

Transportation

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10.1016/j.trpro.2020.02.094

Cite this

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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.",

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AU - Bekhor, Shlomo

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AB - 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.

KW - Emergency

KW - Evacuation

KW - Location-Based Social Network

KW - OD matrix

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JF - Transportation Research Procedia

T2 - 2019 Transport Infrastructure and Systems in a Changing World. Towards a more Sustainable, Reliable and Smarter Mobility, TIS Roma 2019

Y2 - 23 September 2019 through 24 September 2019

ER -

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

Abstract

Keywords

ASJC Scopus subject areas

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