01698113

Component

The Highway Safety Manual (HSM) presents a variety of methods for quantitative network segmentation. Existing approaches to determine segment lengths for safety analysis require engineering judgement and are subject to a lack of standard metrics for assessing segmentation performance. This paper presents a novel methodology that determines optimal segment lengths and innovates network segmentation methods for reliable safety analysis. The methodology is based on spectral analysis of crash density in the spatial frequency domain (SFD) in which low frequency components represent trends while high frequency components represent details and randomness. By proposing the one- dimensional spatial frequency domain analysis (SFDA), this paper discovered the characteristic of power spectral concentration within the low frequency band. Based on this finding, this paper further proposes the power spectral segment length (PSSL) for determine optimal segment lengths and the power spectral percentage (PSP) for assessing the segmentation performance. The methodology extended the knowledge of network segmentation and aggregation of crash data from a non-traditional perspective. It leads to the low-pass filtering method that outperforms the sliding window method, and an improved wavelet-based method that identifies high-risk segments properly.

This paper was sponsored by TRB committee ANB20 Standing Committee on Safety Data, Analysis and Evaluation.

19-02342

English

24p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Crash data; Fourier transforms; Highway safety; Spectrum analysis; Wavelets

Highway Safety Manual

Segment length

Data and Information Technology; Highways; Safety and Human Factors

Transportation Research Board Annual Meeting 2019 Paper #19-02342

TRIS, TRB, ATRI

Dec 7 2018 9:46AM