Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/208200
Authors: 
Scholl, Lynn
Elagaty, Mohamed
Ledezma-Navarro, Bismarck
Zamora, Edgar
Miranda-Moreno, Luis
Year of Publication: 
2019
Series/Report no.: 
IDB Working Paper Series No. IDB-WP-1054
Abstract: 
Due to a lack of reliable data collection systems, traffic fatalities and injuries are often under-reported in developing countries. Recent developments in surrogate road safety methods and video analytics tools offer an alternative approach that can be both lower cost and more time efficient when crash data is incomplete or missing. However, very few studies investigating pedestrian road safety in developing countries using these approaches exist. This research uses an automated video analytics tool to develop and analyze surrogate traffic safety measures and to evaluate the effectiveness of temporary low-cost countermeasures at selected pedestrian crossings at risky intersections in the city of Cochabamba, Bolivia. Specialized computer vision software is used to process hundreds of hours of video data and generate data on road users' speed and trajectories. We find that motorcycles, turning movements, and roundabouts, are among the key factors related to pedestrian crash risk, and that the implemented treatments were effective at four-legged intersections but not at traditional-design roundabouts. This study demonstrates the applicability of the surrogate methodology based on automated video analytics in the Latin American context, where traditional methods are challenging to implement. The methodology could serve as a tool to rapidly evaluate temporary treatments before they are permanently implemented and replicated.
Subjects: 
Traffic safety
pedestrians
surrogate measures
machine learning
developing countries
JEL: 
L91
R41
Persistent Identifier of the first edition: 
Creative Commons License: 
https://creativecommons.org/licenses/by-nc-nd/3.0/igo/legalcode
Document Type: 
Working Paper

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