Allometric scaling of road accidents using social media crowd-sourced data

被引:2
|
作者
Ghandour, Ali J. [1 ]
Hammoud, Huda [2 ]
Dimassi, Mohammad [3 ]
Krayem, Houssam [4 ]
Haydar, Jamal [4 ]
Issa, Adam [5 ]
机构
[1] Natl Council Sci Res, Beirut, Lebanon
[2] Amer Univ Beirut, Comp & Commun Engn Dept, Beirut, Lebanon
[3] Lebanese Univ, Comp & Commun Engn Dept, Beirut, Lebanon
[4] Islamic Univ Lebanon, Comp & Commun Engn Dept, Khalde, Lebanon
[5] Univ Toronto, Elect & Comp Engn Dept, Toronto, ON, Canada
关键词
Car accidents; Allometric scaling; Road safety; Crowd-sourcing; Seasonality trends; INCIDENT DETECTION; SPATIAL-ANALYSIS; TWITTER;
D O I
10.1016/j.physa.2019.123534
中图分类号
O4 [物理学];
学科分类号
0702 ;
摘要
Traffic accidents in Lebanon are constantly harvesting lives, dramatically changing others, and traumatizing those of their beloved ones. Due to the lack of statutory authority in charge of collecting and reporting accident related data, the Lebanese Road Accident Platform (LRAP) is proposed in this work as a real-time online platform to collect crash events from social media. LRAP allows for autonomous data collection, classification and visualization without human intervention, and aims to help the authorities in laying down the appropriate measures for traffic accidents prevention. After being in production for the last four years, the data extracted from LRAP was used to study the allometric scaling of accidents with respect to different parameters such as district area, population size per district and road network length. Such approach offers a new perspective on traffic accidents' scaling and behavior as a living organism as cities grow. A seasonality trend analysis is also provided to analyze temporal clustering patterns in crash occurrence. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页数:8
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