The attempts to predict crashes on freeways through statistical modeling involving capacity driven measures of traffic flow (e.g., AADT) and road geometry have spanned for more than two decades. However, success in crash prediction involving these static data has so far been limited. In recent times, some researchers made efforts to accommodate the weather conditions and seasonal effects to bet...

The crash prediction models of the Highway Safety Manual (HSM), 2010 estimate the expected number of crashes for different facility types. Models in Part C Chapter 12 of the first edition of the HSM include crash prediction models for divided and undivided urban arterials. Each of the HSM crash prediction models for highway segments is comprised of a "Safety Performance Function," a function of...

Computational human body models are widely used for automotive crash-safety research and design and as such have significantly contributed to a reduction of traffic injuries and fatalities. Currently crash simulations are mainly performed using models based on crash-dummies. However crash dummies differ significantly from the real human body and moreover crash dummies are only available for a l...

Crash prediction models have been very popular in highway safety analyses. However, in highway safety research, the prediction of outcomes is seldom, if ever, the only research objective when estimating crash prediction models. Only very few existing methods can be used to efficiently predict motor vehicle crashes. Thus, there is a need to examine new methods for better predicting motor vehicle...

This study investigates the use of crash prediction models and micro-simulation to develop an effective surrogate safety assessment measure at the intersection level. With the use of these tools, hypothetical scenarios can be developed and explored to evaluate the safety impacts of design alternatives in a controlled environment, in which factors not directly associated with the design alternat...

Travel demand management (TDM) consists of a variety of policy measures that affect the effectiveness of transportation systems by changing travel behavior. The primary objective of such TDM strategies is not to improve traffic safety, although their impact on traffic safety should not be neglected. The main purpose of this study is to simulate the traffic safety impact of conducting a telework...

The future of traffic management and highway safety lies in proactive traffic management systems. Crash prediction models that use real-time traffic flow variables measured through a series of loop detectors are the most important component of such systems. A previous crash prediction model was developed with the matched case-control logistic regression technique. Although the model achieved re...

Travel Demand Management (TDM) consists of a variety of policy measures that affect the transportation system’s effectiveness by changing travel behavior. Although the primary objective to implement such TDM strategies is not to improve traffic safety, their impact on traffic safety should not be neglected. The main purpose of this study is to investigate differences in the traffic safety conse...

INTRODUCTION To date, many prognostic models have been proposed to predict the outcome of patients with traumatic brain injuries. External validation of these models in different populations is of great importance for their generalization. The present study was designed, aiming to determine the value of CRASH prognostic model in prediction of 14-day mortality (14-DM) and 6-month unfavorable out...

The current planning practice addresses safety implicitly as a byproduct of adding capacity and operational efficiency to the transportation system. Safety conscious planning is a new proactive approach to the prevention of crashes by establishing inherently safe transportation networks through integrating safety consideration into the transportation planning process. One of the major concerns ...