Methods for Identifying Truck Crash Hotspots

Joint Authors

Qu, Wenrui
Liu, Shaojie
Zhao, Qun
Qi, Yi

Source

Journal of Advanced Transportation

Issue

Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2020-10-28

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Civil Engineering

Abstract EN

The goal of this study was to develop a new method for identifying the actual risky spots by using the geographic information system (GIS).

For this purpose, in this study, three different methods for detecting hotspots are developed, i.e., (1) the annual average daily traffic (AADT) normalization method, (2) AK crashes (A is the incapacitating crash, and K is the fatal crash) percentage method, and (3) distribution difference method.

To evaluate the performances of these three hotspot detection methods along with a baseline method that only considered the frequency of crashes, we applied these three methods to identify the top 20 hotspots for truck crashes in two representative areas in Texas.

The results indicated that (1) all three proposed methods produced more reasonable results than the baseline method, and (2) the “distribution difference” method outperformed the other methods.

American Psychological Association (APA)

Qu, Wenrui& Liu, Shaojie& Zhao, Qun& Qi, Yi. 2020. Methods for Identifying Truck Crash Hotspots. Journal of Advanced Transportation،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1175367

Modern Language Association (MLA)

Qu, Wenrui…[et al.]. Methods for Identifying Truck Crash Hotspots. Journal of Advanced Transportation No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1175367

American Medical Association (AMA)

Qu, Wenrui& Liu, Shaojie& Zhao, Qun& Qi, Yi. Methods for Identifying Truck Crash Hotspots. Journal of Advanced Transportation. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1175367

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1175367