A Time-Series Analysis of Traffic Crashes in New York City

被引：0

作者：

Shaaban, Khaled ^{[1
]}

Ibrahim, Mohamed ^{[2
]}

机构：

[1] Utah Valley Univ, Dept Engn, Orem, UT 84058 USA

[2] Qatar Univ, Dept Civil Engn, Doha, Qatar

来源：

2022 INTERMOUNTAIN ENGINEERING, TECHNOLOGY AND COMPUTING (IETC) | 2022年

关键词：

Fatalities; injuries; ARIMA; driver behavior; accidents; ACCIDENTS;

D O I：

10.1109/IETC54973.2022.9796728

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In New York City, traffic crashes are one of the main causes of fatalities in the city. This study presents a comprehensive time series analysis of road crashes in the city from 2013 to 2019. The crash data were collected, organized, and analyzed at different time levels: yearly, seasonally, monthly and hourly bases. Forecasting of the total number of crashes in the years 2020 to 2025 was conducted using the Box-Jenkins method based on the autoregressive integrated moving average (ARIMA) model. The model was statistically validated using a modified Box-Pierce (Ljung-Box) Chi-Square test. The proposed model was also used for backward prediction of the year 2019 to compare with actual observations. The predicted results showed a good agreement with the actual observed results. The results also showed a strong potential of having a reduction in the total number of crashes in the future.

引用

页数：6

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