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18 Table 11. Relationship between work zone analysis periods and influences on work zone safety. Disruptions on Safety Geometric and Work Temporary Roadway Capacity Reductions Effect of Temporary Influences on Safety Lane Work Activity Effect of Off-Travel Disruptions due to Distractions and Effect of Traffic Zone Design Work Zone Analysis Period on Safety When Work Zone Inactive and No X Temporary Lane Closures When Work Zone Active and No Temporary X X Lane Closures When Work Zone Active and Temporary X X X Lane Closures Present As expected, the majority of projects where temporary lane relative to what would have been expected to have occurred if closures were performed during the day occurred at locations the work zone were not present at that location. EB techniques where AADTs were relatively low, and those performed where increase the precision of estimation and correct regression-to- AADTs were relatively high involved predominantly night- the-mean bias (50). Often, the limited duration of a particular time temporary lane closures. This is illustrated graphically in work zone project means that the sample size of crashes avail- Figure 2, which shows the percentage of hours involving a able for use in the analysis is quite small. Regression-to-the- temporary lane closure at each project that was performed mean biases may also exist at some work zone locations if the during nighttime hours (nighttime was defined as beginning selection of roadway segments being targeted for repair and at 7:00 pm, after the evening peak period, and ending at improvement is based partially on the recent crash experi- 6:00 am, prior to the start of the morning peak period). ences of that roadway segment. Consequently, EB techniques As shown, temporary lane closures at projects on roadways provide better estimates of the safety impacts of highway work with AADTs less than about 40,000 vehicles per day (vpd) zones than traditional before-during crash comparisons. were mostly performed during daytime hours, whereas those The EB procedure required researchers to develop safety on freeways with AADTs in excess of 100,000 vpd were almost performance functions (SPFs), using data from a reference all performed at night. Between these ranges, the results were group, of freeway facilities under daytime and nighttime con- mixed. Night work was used extensively on some projects as ditions in each of the states where work zone projects were low as 35,000 vpd, while a few projects on freeways with taken. The estimates from the SPFs were then combined with AADTs of up to 75,000 vpd still had about 60 percent or more crash data occurring within the project limits for several years of temporary lane closures occur during daytime hours. preceding the work at that location. The combination of the SPF and pre-work zone crash data provided a more precise estimate of the crashes that would be expected to occur over Data Analysis a given period of time at that location if the work zone had For each of the work zone analysis periods of interest, re- not been present. The ratio of the actual number of crashes searchers used empirical Bayesian (EB) statistical techniques occurring during the operation of the work zone to the EB es- to estimate the incremental increase in crash risk that occurred timate is then used to estimate the incremental effect of the Table 12. Amount of work activity and temporary lane closures during daytime and nighttime periods in sample projects. State Statistic North California Ohio Washington Overall Carolina % of Time Active, Daytime 20.9 33.5 40.2 26.9 30.6 % of Time Active, Nighttime 20.8 13.6 15.2 15.7 16.0 % of Active Time with Temporary Lane Closures, 21.6 37.0 5.2 34.4 26.2 Daytime % of Active Time with Temporary Lane Closures, 89.8 84.9 88.3 88.9 87.8 Nighttime