Highway Safety Manual Calibration: Estimating the Minimum Required Sample Size

Crash frequency has been identified by many experts as one of the most important safety measures, and the Highway Safety Manual (HSM) encompasses the most commonly accepted predictive models for predicting the crash frequency on specific road segments and intersections. The HSM recommends that the models be calibrated using data from a jurisdiction where the models will be applied. One of the most common start-up issues with the calibration process is how to estimate the required sample size to achieve a specific level of precision, which can be a function of the variance of the calibration factor. The published research has indicated great variance in sample size requirements, and some of the sample size requirements are so large that they may deter state departments of transportation (DOT) from conducting calibration studies. In this study, an equation is derived to estimate the sample size based on the coefficient of variation of the calibration factor and the coefficient of variation of the observed crashes. Using this equation, a framework is proposed for state and local agencies to estimate the required sample size for calibration based on their desired level of precision. Using two recent calibration studies, South Carolina and North Carolina, it is shown that the proposed framework leads to more accurate estimates of sample size compared with current HSM recommendations. Whereas the minimum sample size requirement published in the HSM is based on the summation of the observed crashes, this paper demonstrates that the summation of the observed crashes may result in calibration factors that are less likely to be equally precise and the coefficient of the variation of the observed crashes can be considered instead.

New Intersection Crash Prediction Models for the Second Edition of the Highway Safety Manual

The objective of this research was to develop new intersection crash prediction models for consideration in the second edition of the Highway Safety Manual (HSM), consistent with existing methods in HSM Part C and comprehensive in their ability to address a wide range of intersection configurations and traffic control types in rural and urban areas. The focus of the research was on developing safety performance functions (SPFs) for intersection configurations and traffic control types not currently addressed in HSM Part C. SPFs were developed for the following general intersection configurations and traffic control types: rural and urban all-way stop-controlled intersections; rural three-leg intersections with signal control; intersections on high-speed urban and suburban arterials (i.e., arterials with speed limits greater than or equal to 50 mph); urban five-leg intersections with signal control; three-leg intersections where the through movements make turning maneuvers at the intersections; crossroad ramp terminals at single-point diamond interchanges; and crossroad ramp terminals at tight diamond interchanges. Development of severity distribution functions (SDFs) for use in combination with SPFs to estimate crash severity as a function of geometric design elements and traffic control features was explored; but owing to challenges and inconsistencies in developing and interpreting the SDFs, it was recommended for the second edition of the HSM that crash severity for the new intersection configurations and traffic control types be addressed in a manner consistent with existing methods in Chapters 10, 11, and 12 of the first edition, without use of SDFs.

Crash Prediction Models for Horizontal Curve Segments on Two-Lane Rural Roads in Thailand

The number of road crashes continues to rise significantly in Thailand. Curve segments on two-lane rural roads are among the most hazardous locations which lead to road crashes and tremendous economic losses; therefore, a detailed examination of its risk is required. This study aims to develop crash prediction models using Safety Performance Functions (SPFs) as a tool to identify the relationship among road alignment, road geometric and traffic conditions, and crash frequency for two-lane rural horizontal curve segments. Relevant data associated with 86,599 curve segments on two-lane rural road networks in Thailand were collected including road alignment data from a GPS vehicle tracking technology, road attribute data from rural road asset databases, and historical crash data from crash reports. Safety Performance Functions (SPFs) for horizontal curve segments were developed, using Poisson regression, negative binomial regression, and calibrated Highway Safety Manual models. The results showed that the most significant parameter affecting crash frequency is lane width, followed by curve length, traffic volume, curve radius, and types of curves (i.e., circular curves, compound curves, reverse curves, and broken-back curves). Comparing among crash prediction models developed, the calibrated Highway Safety Manual SPF outperforms the others in prediction accuracy.

Safety Performance of Crossroad Ramp Terminals at Single-Point and Tight Diamond Interchanges

Single-point diamond interchanges and tight diamond interchanges are two alternative interchange types that are considered in urban areas where right-of-way is usually limited. The Highway Safety Manual First Edition predictive methods for freeways and interchanges are capable of estimating the safety performance of freeway mainline, freeway-ramp terminal, and ramp proper segments associated with these interchange types. However, limited research has been conducted to predict and compare the safety performance of the crossroad ramp terminals for these two alternative interchange designs, as would be necessary for a performance-based approach to interchange alternatives analysis. Planners, designers, and safety managers would benefit from having tools to compare the safety performance of these crossroad ramp terminals to make more informed decisions about their use and application in the urban environment. Research was undertaken with the objective of developing new intersection crash prediction models for crossroad ramp terminals at single-point diamond interchanges and crossroad ramp terminals at tight diamond interchanges. In general, it was found that the crash prediction models for crossroad ramp terminals at single-point diamond interchanges predicted more crashes than the models for crossroad ramp terminals at tight diamond interchanges in higher volume conditions. The differences were primarily driven by the property-damage-only crash predictions. Comparisons of the crash prediction models suggested that the two sets of models appear compatible and provide reasonable results over the range of applicable traffic volume conditions.

Application of Data-Driven Safety Analysis to Support Port Authority Investment Decisions for Converting Conventional Toll Plazas to Open-Road Tolling

Capital improvement projects have the potential to enhance safety, mobility, and environmental quality, but these projects can include considerable costs. When making investment decisions, it is important for agencies to understand the costs in relation to the potential benefits. For several years, transportation agencies have analyzed and quantified the operational and environmental impacts of proposed projects. More recently, the first edition of the Highway Safety Manual and related resources have provided agencies with the tools needed to quantify the safety impacts of proposed projects. This paper describes the use of data-driven safety analysis methods by the Port Authority of New York and New Jersey to quantify the direct and indirect safety benefits of the proposed conversion of conventional toll plazas to open-road tolling. The analysis estimated the direct safety benefits (i.e., change in the number of crashes) and indirect safety benefits (i.e., change in travel time, fuel costs, and emissions resulting from crashes). These changes were converted to dollars, providing an estimate of the present value benefits based on the expected service life of the enhanced toll systems. The analysis indicated the conversions could reduce crashes by more than 900 annually, including the prevention of nearly 30 injury crashes annually. Indirect safety benefits included more than 200,000 h in reduced travel time, 335,000 gal of fuel saved, and nearly 3,000 metric tons of CO2 reduced annually. Over the 15-year life cycle, this would provide an estimated benefit of more than $200 million from crashes directly and $367 million in indirect benefits.

Regression to the mean correction for Collision Modification Factors

Collision Modification Factors (CMFs) are a simple method of representing the effectiveness of road safety treatments. With the release of the Highway Safety Manual (HSM) and the recent launching of a CMF Clearinghouse website, CMFs are likely to become more widely used for estimating the effects of potential road safety treatments. The presence of regression to the mean (RTM) bias has long been shown to affect the accuracy of CMFs that did not account for the RTM in their development. The purpose of this research was to study how the RTM depends on the number of years of data used for selecting high collision sites for treatment and on the relative number of sites selected. From this analysis, a function based on the number of years, percentage of high collision sites selected, and the mean and standard deviation of the site population from which the treated sites are drawn was developed to more accurately estimate the magnitude of the RTM effect. This function can be used to adjust CMFs that do not account for RTM, complementing the procedure developed and used to correct CMFs included in the HSM.

Multi-objective optimization of single-lane roundabout geometric design: safety, mobility, and environmental sustainability

Mobility, safety performance and environmental sustainability are priorities in the geometric design of roundabouts. This thesis presents a multi-objective optimization methodology for the geometric design of single-lane roundabouts. Mobility is defined in terms of roundabout delay and modeled using the (UK) empirical model. The collision frequency represents the safety objective, and modeled using the methodology outlined in the Highway Safety Manual. Environmental sustainability is represented by NOX, HC, CO2, and CO vehicle emissions and is modeled using the vehicle specific power (VSP) methodology. The presented model directly identifies the optimal geometric parameters of roundabouts. Traffic data, site conditions, and guidelines limitations were used as input data while the output decision values that minimize delay, collisions, and vehicle emissions are the optimal geometric parameters. The practical application of the proposed model is illustrated using an application example. The model was validated using an actual location, and a sensitivity analysis was conducted.

Multi-objective optimization of single-lane roundabout geometric design: safety, mobility, and environmental sustainability

Mobility, safety performance and environmental sustainability are priorities in the geometric design of roundabouts. This thesis presents a multi-objective optimization methodology for the geometric design of single-lane roundabouts. Mobility is defined in terms of roundabout delay and modeled using the (UK) empirical model. The collision frequency represents the safety objective, and modeled using the methodology outlined in the Highway Safety Manual. Environmental sustainability is represented by NOX, HC, CO2, and CO vehicle emissions and is modeled using the vehicle specific power (VSP) methodology. The presented model directly identifies the optimal geometric parameters of roundabouts. Traffic data, site conditions, and guidelines limitations were used as input data while the output decision values that minimize delay, collisions, and vehicle emissions are the optimal geometric parameters. The practical application of the proposed model is illustrated using an application example. The model was validated using an actual location, and a sensitivity analysis was conducted.

Calibration of the Highway Safety Manual and the SafetyAnalyst Methodologies for Ontario Highways

SafetyAnalyst and the Highway Safety Manual (HSM) are two tools that are expected to revolutionize highway safety analyses. A key issue that allows SafetyAnalyst and HSM to become the new standards in road safety engineering is the calibration of their safety performance functions (SPFs) across time and jurisdictions. In this study, the methodologies of SafetyAnalyst and HSM are calibrated for Ontario to evaluate the effective transferability of their SPFs to local topographical conditions. A SafetyAnalyst calibration has been completed for Ontario highways and freeways, intersections, and ramps for six years (1998-2003) of traffic and accident counts. A data set which consists of 78 kilometres of rural two-lane two-way highways and 71 three- and four-legged stop controlled intersections located in the eastern and central regions of the Ministry of Transportation of Ontario (MTO) with six years (2002 to 2007) of traffic volume and collision counts has been used to evaluate the HSM SPFs to Ontario data. Several goodness-of-fit (GOF) measures are computed to assess the transferability and suitability of the crash models for applicability in Ontario. The study suggests that while most of the SafetyAnalyst SPFs for highways and ramps are not adaptable to Ontario data, the recalibrated SafetyAnalyst SPFs for intersections and also the recalibrated HSM Part C predictive models for two-lane rural highways and intersections provide satisfactory results in comparison to the crash models developed specifically for Ontario. Finally, this research highlights the substantial need for future improvements in data quality for more reliable safety performance estimations and evaluations.