Improved Criteria for Estimating Calibration Factors for Highway Safety Manual (HSM) Applications

The Highway Safety Manual (HSM) estimates roadway safety performance based on predictive models that were calibrated using national data. Calibration factors are then used to adjust these predictive models to local conditions for local applications. The HSM recommends that local calibration factors be estimated using 30 to 50 randomly selected sites that experienced at least a total of 100 crashes per year. It also recommends that the factors be updated every two to three years, preferably on an annual basis. However, these recommendations are primarily based on expert opinions rather than data-driven research findings. Furthermore, most agencies do not have data for many of the input variables recommended in the HSM. This dissertation is aimed at determining the best way to meet three major data needs affecting the estimation of calibration factors: (1) the required minimum sample sizes for different roadway facilities, (2) the required frequency for calibration factor updates, and (3) the influential variables affecting calibration factors. In this dissertation, statewide segment and intersection data were first collected for most of the HSM recommended calibration variables using a Google Maps application. In addition, eight years (2005-2012) of traffic and crash data were retrieved from existing databases from the Florida Department of Transportation. With these data, the effect of sample size criterion on calibration factor estimates was first studied using a sensitivity analysis. The results showed that the minimum sample sizes not only vary across different roadway facilities, but they are also significantly higher than those recommended in the HSM. In addition, results from paired sample t-tests showed that calibration factors in Florida need to be updated annually. To identify influential variables affecting the calibration factors for roadway segments, the variables were prioritized by combining the results from three different methods: negative binomial regression, random forests, and boosted regression trees. Only a few variables were found to explain most of the variation in the crash data. Traffic volume was consistently found to be the most influential. In addition, roadside object density, major and minor commercial driveway densities, and minor residential driveway density were also identified as influential variables.

Use of expert panels in highway safety: A critique

Expert panels have been used extensively in the development of the "Highway Safety Manual" to extract research information from highway safety experts. While the panels have been used to recommend agendas for new and continuing research, their primary role has been to develop accident modification factors—quantitative relationships between highway safety and various highway safety treatments. Because the expert panels derive quantitative information in a “qualitative” environment and because their findings can have significant impacts on highway safety investment decisions, the expert panel process should be described and critiqued. This paper is the first known written description and critique of the expert panel process and is intended to serve professionals wishing to conduct such panels.

Exposure measures for evaluating highway safety issues. Volume 2 - users manual. Final report.

Federal Highway Administration, Washington, D.C.

Highway safety management process - evaluation manual.

Mode of access: Internet.

Highway safety management process - planning and programming manual.

Mode of access: Internet.

Highway safety program manual. Volume 11, addendum 1. Communications manual.

Mode of access: Internet.

Highway safety program manual. Volume 102 - highway safety plan.

Mode of access: Internet.

Highway safety program manual.

Supplements accompany some volumes.

Empirical investigation of interactive highway safety design model accident prediction algorithm : Rural intersections

One major gap in transportation system safety management is the ability to assess the safety ramifications of design changes for both new road projects and modifications to existing roads. To fulfill this need, FHWA and its many partners are developing a safety forecasting tool, the Interactive Highway Safety Design Model (IHSDM). The tool will be used by roadway design engineers, safety analysts, and planners throughout the United States. As such, the statistical models embedded in IHSDM will need to be able to forecast safety impacts under a wide range of roadway configurations and environmental conditions for a wide range of driver populations and will need to be able to capture elements of driving risk across states. One of the IHSDM algorithms developed by FHWA and its contractors is for forecasting accidents on rural road segments and rural intersections. The methodological approach is to use predictive models for specific base conditions, with traffic volume information as the sole explanatory variable for crashes, and then to apply regional or state calibration factors and accident modification factors (AMFs) to estimate the impact on accidents of geometric characteristics that differ from the base model conditions. In the majority of past approaches, AMFs are derived from parameter estimates associated with the explanatory variables. A recent study for FHWA used a multistate database to examine in detail the use of the algorithm with the base model-AMF approach and explored alternative base model forms as well as the use of full models that included nontraffic-related variables and other approaches to estimate AMFs. That research effort is reported. The results support the IHSDM methodology.

Governors highway safety associations and transportation planning: Exploratory factor analysis and structural equation modeling

The Intermodal Surface Transportation Efficiency Act (ISTEA) of 1991 mandated the consideration of safety in the regional transportation planning process. As part of National Cooperative Highway Research Program Project 8-44, "Incorporating Safety into the Transportation Planning Process," we conducted a telephone survey to assess safety-related activities and expertise at Governors Highway Safety Associations (GHSAs), and GHSA relationships with metropolitan planning organizations (MPOs) and state departments of transportation (DOTs). The survey results were combined with statewide crash data to enable exploratory modeling of the relationship between GHSA policies and programs and statewide safety. The modeling objective was to illuminate current hurdles to ISTEA implementation, so that appropriate institutional, analytical, and personnel improvements can be made. The study revealed that coordination of transportation safety across DOTs, MPOs, GHSAs, and departments of public safety is generally beneficial to the implementation of safety. In addition, better coordination is characterized by more positive and constructive attitudes toward incorporating safety into planning.

Further notes on the application of zero-inflated models in highway safety

The intent of this note is to succinctly articulate additional points that were not provided in the original paper (Lord et al., 2005) and to help clarify a collective reluctance to adopt zero-inflated (ZI) models for modeling highway safety data. A dialogue on this important issue, just one of many important safety modeling issues, is healthy discourse on the path towards improved safety modeling. This note first provides a summary of prior findings and conclusions of the original paper. It then presents two critical and relevant issues: the maximizing statistical fit fallacy and logic problems with the ZI model in highway safety modeling. Finally, we provide brief conclusions.

Safety performance models for urban intersections in Brazil

This paper presents a modeling effort for developing safety performance models (SPM) for urban intersections for three major Brazilian cities. The proposed methodology for calibrating SPM has been divided into the following steps: defining the safety study objective, choosing predictive variables and sample size, data acquisition, defining model expression and model parameters and model evaluation. Among the predictive variables explored in the calibration phase were exposure variables (AADT), number of lanes, number of approaches and central median status. SPMs were obtained for three cities: Fortaleza, Belo Horizonte and Brasilia. The SPM developed for signalized intersections in Fortaleza and Belo Horizonte had the same structure and the most significant independent variables, which were AADT entering the intersection and number of lanes, and in addition, the coefficient of the best models were in the same range of values. For Brasilia, because of the sample size, the signalized and unsignalized intersections were grouped, and the AADT was split in minor and major approaches, which were the most significant variables. This paper also evaluated SPM transferability to other jurisdiction. The SPM for signalized intersections from Fortaleza and Belo Horizonte have been recalibrated (in terms of the COx) to the city of Porto Alegre. The models were adjusted following the Highway Safety Manual (HSM) calibration procedure and yielded C-x of 0.65 and 2.06 for Fortaleza and Belo Horizonte SPM respectively. This paper showed the experience and future challenges toward the initiatives on development of SPMs in Brazil, that can serve as a guide for other countries that are in the same stage in this subject. (C) 2014 Elsevier Ltd. All rights reserved.

A digest of state alcohol-highway safety related legislation. Second edition.

Mode of access: Internet.

A digest of state alcohol-highway safety related legislation. Third edition.

Mode of access: Internet.

A digest of state alcohol-highway safety related legislation. Fourth edition.

Mode of access: Internet.