In a traditional safety impact analysis, it is necessary to have crash data on existing roadway conditions in the field and a few years must pass before accumulating reliable crash data. This is a time-consuming approach and there remains uncertainty in the crash data due to the random nature of crash occurrences. The Surrogate Safety Assessment Model (SSAM) was developed for resolving these issues. With SSAM, a conflict analysis is performed in a simulated environment. A planned improvement alternative under study is modeled and no physical installation of the alternative is needed. Hence, the method using a simulation software along with SSAM consumes less time compared to other traditional safety analysis methods that may require a physical installation of the new alternative and a long wait time for data collection. The purpose of this study is to evaluate if SSAM can be used to assess the safety of a highway segment or an intersection in term of the number and type of conflicts and to compare the safety effects of multiple access management alternatives with less time, less cost and less uncertainty than the traditional safety analysis methods. To meet the purpose of the study, two study sections, one on University Parkway in Orem and Provo and the other on Main Street in American Fork were selected and analyzed in this research. Based on the findings from the calibration of SSAM on the University Parkway study section, an evaluation of the effect of converting a TWLTL median into a raised median on a section of Main Street (US-89) from 300 West to 500 East in American Fork was performed using SSAM working on VISSIM simulation's trajectory files of the study section. This evaluation study was conducted to show how SSAM could be used to evaluate the effect of access management alternatives using surrogate safety measures. The analysis showed that a raised median would be much safer than a TWLTL median for the same level of traffic volume. Approximately a 32 to 50 percent reduction in the number of crossing conflicts was achieved when a raised median was used in lieu of a TWLTL median at the Main Street study section.

The Utah Department of Transportation (UDOT) has completed a Light Detection and Ranging (LiDAR) data inventory that includes access locations across the UDOT network. The new data are anticipated to be extremely useful in better defining safety and in completing a systemwide analysis of locations where safety could be improved, or where safety has been improved across the state. The Department of Civil and Environmental Engineering at Brigham Young University (BYU) has worked with the new data to perform a safety analysis of the state related to access management, particularly related to driveway spacing and raised medians. The primary objective of this research was to increase understanding of the safety impacts across the state related to access management. These objectives were accomplished by using the LiDAR database to evaluate driveway spacing and locations to aid in hot spot identification and to develop relationships between access design and location as a function of safety and access category (AC). Utah Administrative Rule R930-6 contains access management guidelines to balance the access found on a roadway with traffic and safety operations. These guidelines were used to find the maximum number of driveways recommended for a roadway. ArcMap 10.3 and Microsoft Excel were used to visualize the data and identify hot spot locations. An analysis conducted in this study compared current roadway characteristics to the R930-6 guidelines to find locations where differences occurred. This analysis does not indicate the current AC is incorrect; it simply means that the assigned AC does not meet current roadway characteristic based on the LiDAR data analysis. UDOT can decide what this roadway will become in the future and help shape each segment using the AC outlined in the R930-6. A hierarchal Bayesian statistical before-after model, created in previous BYU safety research, was used to analyze locations where raised medians have been installed. Twenty locations where raised medians were installed in Utah between 2002 to 2014 were used in this model. The model analyzed the raised medians by AC. Only three AC were represented in the data. Regression plots depicting a decrease in crashes before and after installation, posterior distribution plots showing the probability of a decrease in crashes after installation, and crash modification factor (CMF) plots presenting the CMF values estimated for different vehicle miles traveled (VMT) values were all created as output from the before-after model. Overall, installing a raised median gives an approximate reduction of 53 percent for all crashes. Individual AC analysis yielded results ranging from 32 to 44 percent for all severity groups except severity 4 and 5. When the model was only run for crash severity 4 and 5, a larger reduction of 57 to 58 percent was found.