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27 slightly different values for the injury-crash AMF and the on median-related or all crashes is even less clear. The basic fatal-crash AMF. The decision was then made to combine the objective of the research was to develop AMFs for median AMF values from the two models to produce the recom- width for different types of roads. mended AMFs. Table 12 provides these combined AMFs. To illustrate the use of these AMFs, consider a road on Methodology which the mean speed is 60.0 mph. If some measure is ex- The preferred method for developing an AMF is to conduct pected to increase the mean speed by 2.0 mph, injury acci- a before-after study in which the treatment installation/ dents are expected to increase by a factor of 1.10 and fatal removal/change date is known, and thus the safety before and accidents by a factor of 1.18. Thus, what may appear to be a after this date can be tracked. The current state-of-the-art small change in mean speed has a large impact on accidents. methodology for conducting such studies makes use of an EB It is expected that these AMFs would be usable for treat- approach, which helps to account for issues such as regression ments associated with change in mean speed on freeways and to the mean, changes in traffic volumes, and changes in crashes rural highways. Their usefulness for urban-street treatments over time that are due to other factors (e.g., weather). However, is less certain. There were some indications in the data that there are a number of treatments in the roadway environment speed change related to passive treatments on urban streets that are not "installed" or changed in a manner that allows for had less effect on crash frequency than is shown in Table 12 a before-after study. Median width is one such treatment. It is (i.e., an AMF closer to 1.0) and that the effect of active speed very unlikely that the median width on a highway will ever be control on these streets (i.e., road humps, traffic circles, chi- changed without making other significant changes to the geo- canes, and so forth) may not be fully captured here. However, metric cross-section. For example, the most common change neither of these indications was found to be fully confirmed in median width would occur when additional travel lanes are in the statistical analysis. In the absence of other knowledge, being added to the left-hand side of a roadway, thus narrowing it is concluded that the tabulated AMFs can be applied to the median. In this case, the fact that there is a significant both active and passive treatments on urban streets. How- change other than the change in median width makes it more ever, the user should understand that there is less certainty difficult to isolate the effects of the change in width in an EB about the AMFs when they are used for urban streets than before-after evaluation. In this case, a cross-section model that when they are used for freeways and rural highways. predicts safety on the basis of varying median widths, traffic volumes, and other factors is still the most feasible option for Effect of Median Width determining the expected safety benefits as median width changes. In this evaluation, negative binomial (NB) regression Description of Treatment and Crash Types models were developed with crash frequency as the dependent of Interest variable and site characteristics such as traffic volume, shoul- Studies on the effect of median width have shown that in- der width, and median width as independent variables. The pa- creasing width reduces cross-median crashes, but the amount rameter estimates from the NB models were used to develop of reduction varies across studies. The effect of median width AMFs. The analysis focused on total crashes and cross-median Table 12. Crash-frequency AMFs for injury and fatal crashes based on initial speed and speed change. Non-fatal Injury Crashes Fatal Injury Crashes v v 0 (mph) v v 0 (mph) (mph) 30 40 50 60 70 80 (mph) 30 40 50 60 70 80 5 0.57 0.66 0.71 0.75 0.78 0.81 5 0.22 0.36 0.48 0.58 0.67 0.75 4 0.64 0.72 0.77 0.80 0.83 0.85 4 0.36 0.48 0.58 0.66 0.73 0.80 3 0.73 0.79 0.83 0.85 0.87 0.88 3 0.51 0.61 0.68 0.74 0.80 0.85 2 0.81 0.86 0.88 0.90 0.91 0.92 2 0.66 0.73 0.79 0.83 0.86 0.90 1 0.90 0.93 0.94 0.95 0.96 0.96 1 0.83 0.86 0.89 0.91 0.93 0.95 0 1.00 1.00 1.00 1.00 1.00 1.00 0 1.00 1.00 1.00 1.00 1.00 1.00 1 1.10 1.07 1.06 1.05 1.04 1.04 1 1.18 1.14 1.11 1.09 1.07 1.05 2 1.20 1.15 1.12 1.10 1.09 1.08 2 1.38 1.28 1.22 1.18 1.14 1.10 3 1.31 1.22 1.18 1.15 1.13 1.12 3 1.59 1.43 1.34 1.27 1.21 1.16 4 1.43 1.30 1.24 1.20 1.18 1.16 4 1.81 1.59 1.46 1.36 1.28 1.21 5 1.54 1.38 1.30 1.26 1.22 1.20 5 2.04 1.75 1.58 1.46 1.36 1.27 v 0 = initial mean travel speed v 0 = initial mean travel speed v = change in mean travel speed v = change in mean travel speed

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28 crashes (definitive and probable). Whether a crash was cross- Table 13. Mile-years by median was deduced based on the location of the crash and the roadway type. movement preceding the crash. Number Area Type Access Control of Lanes Rural Urban Partial or No 4 3,258 1,549 Data Used Access Control 5+ 70 107 Full Access 4 8,331 3,037 Ten years of data (1993 to 2002) on divided roadway sections Control 5+ 1,604 1,970 in California were obtained from HSIS. HSIS has a crash file providing detailed information about individual crashes, a roadway file that has data on traffic volume and other site char- thus it was not possible to develop satisfactory models for this acteristics, and an intersection/ramp file that shows the location group. Hence, AMFs were not developed for this group. of intersections and ramps. Data for about 27,131 mile-years of divided roadway sections without median barriers were ex- Results tracted from HSIS. Sites where the two sides of the roadway were on separate grades were eliminated. To the extent possi- Tables 15 and 16 show the AMFs for median width derived ble, only "traversable" median locations were included in the from the NB models for all crashes and cross-median crashes. dataset. A preliminary analysis of the dataset revealed that me- The AMFs were calculated by using a 10-ft median width as dian widths of 100 ft or larger were coded as 99 ft in the dataset. the base case. It is clear that increasing median width is asso- Hence, all sections with median width coded as 99 ft or larger ciated with a reduction in total crashes as well as with cross- were removed. Sections with "variable median width" were also median crashes. Here are the findings regarding the AMFs: removed. In addition, whenever the type of access control changed for a particular year, data were eliminated for that sec- As expected, median width has a larger effect on cross- tion for that year. Eliminating these sections resulted in 19,933 median crashes than on total crashes; mile-years. Table 13 shows the number of mile-years by access The AMFs for cross-median crashes are very similar for the control, number of lanes, and type of area (i.e., rural or urban). two urban roadway types with full access control (i.e., with For roads with partial or no access control and more than four lanes and five or more lanes); four lanes, the number of mile-years was minimal, and hence, The AMFs for cross-median crashes are very similar for the this group was not considered for the analysis. Table 14 shows two rural roadway types; and the total number of crashes and cross-median crashes for the The AMFs for total crashes are very similar for the two different roadway types. Cross-median crashes represent be- four-lane urban roadway types (with full access control tween 3 percent and 6 percent of total crashes on roads with and partial or no access control). full access control and about 12 percent of total crashes on roads with partial or no access control. Roads with full access Overall, the AMFs are quite similar to those obtained from control experience relatively fewer cross-median crashes previous studies that were also based on cross-sectional probably because these roads generally have larger median models (48, 49, 75, 76, 77). However, this study used a much widths. In the sample for this research, the average median larger sample of mile-years and crashes in arriving at the width for roads with full access control ranged from 55 to 60 AMFs. Separate AMFs were also developed on the basis of ft, whereas the average median width for roads with partial or area type (rural or urban), level of access control (full or no access control ranged from 29 to 40 ft. partial/none), and type of collision (total or cross-median). Full access control roads in rural areas with more than four Hence, the AMFs produced in this effort are those recom- lanes had relatively few cross-median crashes (i.e., 548), and mended in Chapter 5. Table 14. Number of crashes (total and cross-median) by roadway type. Area Type No. of Rural Urban Level of Access Control lanes % % Cross- Cross- Total Cross- Total Cross- Median Median Median Median Partial or No Access 4 13,255 1,593 12.0 28,185 3,438 12.2 Control 4 33,009 1,961 5.9 35,690 1,554 4.4 Full Access Control 5+ 12,624 548 4.3 43,385 1,507 3.5

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29 Table 15. AMFs for median width for roads with full access control. Rural, 4 Lanes, Full Urban, 4 Lanes, Full Urban, 5+ Lanes, Full Access Control Access Control Access Control Median Cross- Cross- Cross- Width (ft) Total median Total median Total median Crashes Crashes Crashes Crashes Crashes Crashes 10 1.00 1.00 1.00 1.00 1.00 1.00 20 0.96 0.86 0.95 0.89 0.93 0.89 30 0.93 0.74 0.90 0.80 0.86 0.79 40 0.90 0.63 0.85 0.71 0.80 0.71 50 0.87 0.54 0.80 0.64 0.74 0.63 60 0.84 0.46 0.76 0.57 0.69 0.56 70 0.81 0.40 0.72 0.51 0.64 0.50 80 0.78 0.34 0.68 0.46 0.59 0.45 90 0.75 0.29 0.65 0.41 0.55 0.40 100 0.73 0.25 0.61 0.36 0.51 0.35 Table 16. AMFs for median width for roads with partial or no access control. Rural, 4 Lanes, Partial or Urban, 4 Lanes, Partial No Access Control or No Access Control Median Cross- Cross- Width (ft) Total median Total median Crashes Crashes Crashes Crashes 10 1.00 1.00 1.00 1.00 20 0.95 0.84 0.95 0.87 30 0.91 0.71 0.90 0.76 40 0.87 0.60 0.85 0.67 50 0.83 0.51 0.81 0.59 60 0.79 0.43 0.77 0.51 70 0.76 0.36 0.73 0.45 80 0.72 0.31 0.69 0.39 90 0.69 0.26 0.65 0.34 100 0.66 0.22 0.62 0.30