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.

Investigation of surrogate measures for safety assessment of two-way stop controlled intersections.

Crash prediction models used to estimate safety at intersections, road, and highway segments are traditionally developed using various traffic volume measures. There are issues with this approach and surrogate safety measures such as conflicts and delays can overcome them. This study investigates the relationships between crash frequencies and traffic volume, intersection delay, and conflicts to explore the viability of these models for estimating safety at two-way stop controlled intersections. The database used includes 78 three leg and 55 four leg intersections within the Greater Toronto Area. Crash prediction models were developed and evaluated based on goodness-of-fit measures and CURE plots. Two conflict estimation techniques are compared in order to determine which is best suited for two-way stop controlled intersection simulations. This study also investigates the use of the models for estimating the safety impact of implementing a left turn lane on a major approach of a three leg intersection.

Investigation of surrogate measures for safety assessment of two-way stop controlled intersections.

Crash prediction models used to estimate safety at intersections, road, and highway segments are traditionally developed using various traffic volume measures. There are issues with this approach and surrogate safety measures such as conflicts and delays can overcome them. This study investigates the relationships between crash frequencies and traffic volume, intersection delay, and conflicts to explore the viability of these models for estimating safety at two-way stop controlled intersections. The database used includes 78 three leg and 55 four leg intersections within the Greater Toronto Area. Crash prediction models were developed and evaluated based on goodness-of-fit measures and CURE plots. Two conflict estimation techniques are compared in order to determine which is best suited for two-way stop controlled intersection simulations. This study also investigates the use of the models for estimating the safety impact of implementing a left turn lane on a major approach of a three leg intersection.

Evaluation of the Predictive Capabilities of Simulated Peak Hour conflict Based Crash Prediction Models

Road traffic crashes are one of the major causes of deaths worldwide. A safety prediction model is designed to estimate the safety of a road entity and in most cases these models link traffic volumes to crashes. A major problem with such models is that crashes are rare events and that crash statistics do not take into account everything that may have contributed to the crashes. The use of traffic conflicts to measure safety can overcome these problems as conflicts occur more frequently than crashes and can be easily estimated using micro simulation. For the purpose of this thesis, simulated peak hour conflict based crash prediction models are developed for 113 Toronto signalized intersections and their predictive capabilities are evaluated. The effects of a hypothetical left turn treatment on crashes and conflicts are also explored and compared to the study conducted by Srinivasan et al (2012). Lastly, the transferability of SSAM prediction models is evaluated to explore how well the models predict crashes for Toronto intersections.

Safety Evaluation of Freeway Speed-Change Lanes Based on Crashes and Simulated Conflicts

To facilitate the evaluation of the safety performance of freeway merge, diverge, and weave areas, conventional crash-based Safety Performance Functions (SPFs) were developed using generalized linear models (GLM) with a negative binomial (NB) error structure. However, crash-based SPFs may not take into account all factors that contribute to the crashes. The use of simulated conflicts as a surrogate safety measure to predict crashes can address this issue and provide recommendations for the designs and traffic control strategies. This approach was explored by using Surrogate Safety Assessment Model (SSAM) and VISSIM software to generate and analyze conflicts for merge areas on Ontario freeways. Crash-conflict integrated SPFs with different Time to Collision (TTC) thresholds were then developed and compared. Their predictive capabilities were also evaluated. To complement this analysis, the transferability of US crash prediction models to Ontario data was evaluated and the goodness-of-fit of these models was explored.