Traffic speed is generally considered a core issue in roadway safety. Previous studies show that faster travel is not necessarily associated with an increased risk of being involved in a crash. When vehicles travel at the same speed in the same direction (even high speeds, as on interstates), they are not passing one another and cannot collide as long as they maintain the same speed. Conversely, the frequency of crashes increases when vehicles are traveling at different rates of speed. There is no doubt that the greater speed variation is, the greater the number of interactions among vehicles is, resulting in higher crash potential. This research tries to identify all major factors that are associated with speed variation on multilane highways, including roadway access density, which is considered to be the most obvious contributing factor. In addition, other factors are considered for this purpose, such as configuration of speed limits, characteristics of traffic volume, geometrics of roadways, driver behavior, environmental factors, etc. A microscopic traffic simulation method based on TSIS (Traffic Software Integrated System) is used to develop mathematical models to quantify the impacts of all possible factors on speed variation.

This study aims to compare three distinct methods used to compute access density and provide a comprehensive weighted methodology to enable standardization for research and application in the future. Access density is a widely used concept that calculates the number of access points within a given distance and has been extensively applied to studies related to crash modeling, operational impact and planning. Methods used in past research show that access density is computed differently by different studies and all studies do not include all access points. The weighted methodology proposed takes into account all access points including driveways, intersections and median openings and categorizes them into geometric combinations. Each geometric combination have potential number of conflict points which include diverging, weaving, merging and crossing movements depending on the type of access point. Weights were assigned to each geometry type based on these conflict point ratio. In conclusion the study identifies and compares methods previously used to compute access density and accordingly, recommends a weighted methodology that includes all access points which can be used as a standard, universal measure all access density related studies including but not limited to safety impacts, operational impacts and planning guidelines.

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.

Two-way left-turn lane (TWLTL) is one of the common median treatments on the roadway. It is found that a number of crashes reported in Florida State are related to TWLTLs. This research focused on evaluating the effect of TWLTLs on these crashes by using the statistical crash prediction model that can estimate the expected number of crashes on TWLTLs. The crash database for analysis was extracted from the Florida Traffic Crash Database based on the TWLTL section list provided by FDOT and combined with some traffic characteristics. It consisted of totally 1688 sample sections within a three-year period from 1996 to 1998. Based on the crash database, distribution fittings for Poisson, Negative Binomial and Lognormal regression were conducted for average number of crashes. According to the results, statistical crash predictive model was developed to estimate the average number of crashes. Negative Binomial regression was applied with four variables, ADT, access density, posted speed and number of lanes for the TWLTL sections. The regression parameters were estimated by using maximum likelihood method with statistical software. The findings of the analysis indicated that all of the variables adopted in the predictive model significantly affect the occurrence of crashes. And the average number of crashes increases with the increase of ADT, access density and number of lanes, while with the decrease of posted speed. After that, the goodness-of-fit of developed model was performed in term of Pearson's R-square and likelihood ratio index. The results showed that the Negative Binomial regression model could explain the relationship between the variables and the crash occurrence In the third part, an approach was developed to identify the TWLTL sections with safety concern. For an undivided roadway, the approach can be carried out to judge if the TWLTL is appropriate to be selected as the median treatment. During the process, the whole database was divided into six categories according to the posted speed and number of lanes. By adopting the selected percentile value from the distribution of average number of crashes for each category in the predictive model, the critical ADT values according to specific access density, number of lane and posted speed level for each category were calculated and tabulated. With the comparison of the actual ADT value and the critical ADT value, if the actual ADT is higher than the critical value, the TWLTL section is determined as the critical section, which means the TWLTL is not appropriate to be selected as the median treatment in this roadway section.

Major crossroads are designed to facilitate the conflicting movements of numerous vehicles in a manner that is both safe and efficient. Accesses located within the functional areas of major crossroads add complication to intersection activity due to additional conflicts arising from ingressing and egressing movements at the accesses. In this research, the impact of accesses on crashes within major crossroad functional areas was analyzed. Specifically, the effects of access spacing within functional areas and access setback from intersections were addressed. In order to conduct the analysis, the functional areas of 159 signalized major arterial crossroads across the state of Utah were examined. A database was built containing the frequency, type, and severity of functional area crashes as well as the intersection and roadway characteristics within the functional area. Statistical analyses were conducted to determine the influence of accesses in intersection functional areas on functional area crashes. The statistical analyses show that the existence of accesses within the functional areas was correlated with increased crashes and crash severity costs. In particular, an increase in commercial access density was associated with increases in crash totals, crash rates, and rear end crashes in intersection functional areas. The analyses also showed that study site intersections meeting Utah Department of Transportation (UDOT) corner clearance standards exhibited fewer right angle crashes and lower crash severity costs. Finally, intersections that prohibited all unsignalized access had lower crash totals, crash rates, right angle crash totals, and rear end crash totals than intersections that allowed some unsignalized access.