Recommended Citation
Pineda-Mendez, R., Guo, Q., Ahmad, N., Romero, M. A., & Tarko, A. P. (2024). Incorporating time-dependent data for proactive safety management (Joint Transportation Research Program Publication No. FHWA/IN/JTRP-2024/01). West Lafayette, IN: Purdue University. https://doi.org/10.5703/1288284317700
DOI
10.5703/1288284317700
Abstract
This study proposed a risk-based safety management framework to supplement the current crash-based safety management system. The proposed tool considers time-dependent factors (e.g., hourly traffic, speed features, weather conditions, signal controls) to help justify operational measures for safety improvements (e.g., variable message signs, variable speed limits, warnings). These selected temporal factors subsequently were included in the developed sequential logit models; and those models, applied hour by hour, were then used to estimate the crash probability and severity level. Two typical roadway elements, rural freeway segments and signalized intersections, were also included in the analysis. The obtained crash risk profiles can be used to predict the expected number of crashes in periods when the operational safety countermeasures are expected to be active based on certain triggering conditions (e.g., traffic, weather, nighttime). These results, together with crash modification factors, may be used in the benefit and cost analysis process to justify the application of specific countermeasures.
Report Number
FHWA/IN/JTRP-2024/01
Keywords
safety management, operational countermeasures, temporal conditions, crash probability, risk profile, logit regression
SPR Number
4540
Performing Organization
Joint Transportation Research Program
Sponsoring Organization
Indiana Department of Transportation
Publisher Place
West Lafayette, Indiana
Date of this Version
2024