Developing Short-Term Safety Performance Functions for Freeways at Different Aggregation Levels by Using Multi-State Microscopic Traffic Detector Data
Safety Performance Functions (SPFs) have been widely used by researchers and practitioners to conduct roadway safety evaluation. Traditional SPFs are usually developed by using annual average daily traffic (AADT) along with geometric characteristics. However, the high level of aggregation may lead to a failure of capturing the temporal variation in traffic volume, speed, weather, crashes, and other factors. In this study, short-term SPFs at different aggregation levels were developed based on microscopic traffic detector data from California, Florida, and Virginia. More specifically, five aggregation levels were considered: (1) annual average weekday hourly traffic (AAWDHT), (2) annual average weekend hourly traffic (AAWEHT), (3) annual average weekday peak/off-peak traffic (AAWDPT), (4) annual average day of the week traffic (AADOWT), and (5) annual average daily traffic (AADT). Model estimation results showed that the segment length and volume, as exposure variables, are significant across all the aggregation levels. Average speed is significant with a negative coefficient, and the standard deviation of speed was found to be positively associated with the crash frequency. It is noteworthy that the HOV operation status was found to have a positive effect on crash frequency across all the aggregation levels. The model comparison results in prediction performance showed that the short-term SPFs performed similarly with the AADT-based SPF, and the AADOWT and AAWDPT models consistently performed slightly better than the other models, which implies that the differences between the day of the week and peak/off-peak periods should be considered in the development of crash prediction models. The model transferability results indicated that the short-term SPFs between Florida and Virginia are transferrable, while the models between California and the other two states are not transferrable.
- Record URL:
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Supplemental Notes:
- This paper was sponsored by TRB committee ACS20 Standing Committee on Safety Performance Analysis.
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Corporate Authors:
Transportation Research Board
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Authors:
- Yuan, Jinghui
- Abdel-Aty, Mohamed
- Fu, Jingwan
- Wu, Yina
- Yue, Lishengsa
- Eluru, Naveen
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Conference:
- Transportation Research Board 100th Annual Meeting
- Location: Washington DC, United States
- Date: 2021-1-5 to 2021-1-29
- Date: 2021
Language
- English
Media Info
- Media Type: Digital/other
- Features: Figures; Maps; References; Tables;
- Pagination: 22p
Subject/Index Terms
- TRT Terms: Annual average daily traffic; Cluster analysis; Crash risk forecasting; Data collection; Freeways; High occupancy vehicle lanes; Microscopic traffic flow; Traffic safety; Vehicle detectors
- Geographic Terms: California; Florida; Virginia
- Subject Areas: Highways; Planning and Forecasting; Safety and Human Factors;
Filing Info
- Accession Number: 01764274
- Record Type: Publication
- Report/Paper Numbers: TRBAM-21-03284
- Files: TRIS, TRB, ATRI
- Created Date: Feb 4 2021 11:00AM