Estimating Urban Traffic Safety and Analyzing Spatial Patterns through the Integration of City-Wide Near-Miss Data: A New York City Case Study

Autor: Chuan Xu, Jingqin Gao, Fan Zuo, Kaan Ozbay

Publikováno v: Applied Sciences, Vol 14, Iss 14, p 6378 (2024)

City-wide near-miss data can be beneficial for traffic safety estimation. In this study, we evaluate urban traffic safety and examine spatial patterns by incorporating city-wide near-miss data (59,277 near-misses). Our methodology employs a grid-base

Externí odkaz: https://doaj.org/article/38060a34668b406ea403501f1ae0b5d0

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Determining an Improved Traffic Conflict Indicator for Highway Safety Estimation Based on Vehicle Trajectory Data

Autor: Hongguang Chang, Ji Qiu, Jiang Ruoxi, Naikan Ding, Bing Liu, Jingan Wu, Shunying Zhu

Publikováno v: Sustainability, Vol 13, Iss 9278, p 9278 (2021)
Sustainability
Volume 13
Issue 16

Currently, several traffic conflict indicators are used as surrogate safety measures. Each indicator has its own advantages, limitations, and suitability. There are only a few studies focusing on fixed object conflicts of highway safety estimation us

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5b6b85eea4261d2f5206f8bc2f6457bf
https://www.mdpi.com/2071-1050/13/16/9278

Validation of Simulated Safety Indicators with Traffic Crash Data

Autor: Alessandro Vitale, William Sommario, Borja Alonso Oreña, Giuseppe Guido, Vittorio Astarita, Vincenzo Pasquale Giofrè, Marcella Marino, Luigi Dell´Olio

Publikováno v: Sustainability
Volume 12
Issue 3
Sustainability, Vol 12, Iss 3, p 925 (2020)
Sustainability 2020, 12(3), 925
UCrea Repositorio Abierto de la Universidad de Cantabria
Universidad de Cantabria (UC)

The purpose of this document is to validate a new methodology useful for the estimation of road accidents resulting from possible driver distractions. This was possible through a statistical comparison made between real accident data between 2016 and

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::62e2ff631c64b5cf40467c3cccf1e02f

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