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15 Daytime Increase in Crash Costs per Work Period Operations Most temporary lane closures Nighttime performed during daytime Operations operations Most temporary lane closures performed during nighttime operations AADT Figure 1. Theorized relationships between increased traffic crash risk and roadway traffic demand at nighttime and daytime work operations that require temporary lane closures. provide important insights into this issue, it should be re- In order to accomplish the analysis approach described in membered that the findings may not represent all possible the previous section, researchers required details about the types of work zones where a decision of whether to work at daily (and nightly) work activity performed by the highway night must be made. contractor at each project such as: hours of work, hours and locations of temporary lane closures set up and removed, and the number of travel lanes closed each work period. Project Data Collection details such as these must be extracted manually from the daily The experimental plan for this portion of the study called diaries of the project inspectors who were onsite each day or for the collection of crash and project activity data across a night. A few states have construction management databases range of geographically dispersed highway work zones nation- (such as the Trnsport SiteManager software available through ally, each of which involved occasional to frequent temporary the American Association of State Highway and Transportation lane closures to complete the work. For some of the projects, Officials [AASHTO]) where this information may be entered these temporary lane closures occur primarily during daytime electronically (49). Even so, it was necessary for research staff hours; for the other projects, these temporary lane closures to sit down with either the diaries or the SiteManager pro- occur almost exclusively at night. Researchers targeted states gram itself to extract the pertinent information for each work that participate in the FHWA HSIS so that multiple years of period on each project of interest. In addition to work activ- crash data, annual average daily traffic (AADT), and roadway ity information, researchers also required information about characteristic data would be more easily accessible. Ultimately, the traffic control plan used, construction phasing, etc., for projects were identified from four HSIS states: each project. Two- to three-person data collection teams traveled to California, each state, except Ohio, to gather the necessary project data North Carolina, for analysis. Ohio uses a construction management database Ohio, and that they were willing to download and send electronically, Washington. negating the need to travel to that state. In the other three instances, the state DOT staff in each state provided key Originally, the intent was to obtain data from several proj- assistance in gaining the data collection access to the neces- ects in Texas as well. However, the lack of available crash data sary project records. In most cases, the projects themselves prompted researchers to drop that state from the analysis. had been closed out and the records archived, and so the Researchers contacted department of transportation (DOT) DOT staff had to request that the files be pulled and trans- officials in each of the other states to request assistance in ported to a location where the research team could use them. identifying suitable candidate projects to use in this study. An Once the records were in hand, the data collection team had initial list of 92 projects was generated through this effort. to verify that all of the necessary information was available

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16 and that the project was useable. In a few cases, project diary is conducted in the area where a roadway changes to or information or traffic control plans were misplaced and not from a limited access facility. Researchers decided not to in- with the rest of the project documents. For those situations, no clude these projects in the dataset since the accident trends project data could be collected. From the initial list, data were on these roadways may differ from the rest of the dataset. located and retrieved by research staff for 84 of the projects. Ten of the Ohio projects could not be used since the elec- Once the data collection team returned to the office, re- tronic diary data did not include the exact work times searchers requested crash and roadway inventory data for (e.g., midnight to 5 am), information concerning lane each project segment length for the duration that the project closures, or both. Researchers contacted the Ohio DOT itself was active and for several years preceding. Additional to obtain more detailed hard-copy diaries but found details regarding the before periods for each project can be that the hard-copy diaries did not contain any additional found in Appendix A. Researchers actually requested data for information. an additional upstream distance around each project to permit During the data collection and reduction stages, it was an- a check for indicators that traffic queues or other work-zone- ticipated that the 2005 Ohio crash data would become related effects were contributing to crashes occurring in available; however, this did not come to fruition. Thus, two those adjacent segments. A high percentage of crashes coded Ohio projects conducted during this time period could not as "work zone involved" in adjacent segments over the dura- be used. tion of the project was the key indicator that the effects of the One of the Ohio projects could not be used since the mile work zone were extending beyond the limits of the project. points where the project occurred were missing from the In these cases, the limits of the project were then expanded HSIS. to incorporate those segments. When the project limits were Washington did not provide 1997 and 1998 crash data to expanded, the added segment generally totaled less than FHWA for inclusion in the HSIS. Thus, four Washington 0.5 mi per direction. projects conducted during this time period could not be The number of usable projects was further reduced due to used. the following issues that unfortunately were not discovered until after the data collection effort: This reduced the final dataset to a total of 64 projects. Even though somewhat smaller than the initial list of proj- Based on the roadway inventory data, three projects con- ects targeted, this dataset is substantial. An overall sum- tained sections of roadway that were not limited access mary of project characteristics and crash statistics is presented facilities (i.e., freeway). This occurs when the work activity in Table 9. Overall, the projects encompass approximately Table 9. Summary of project characteristics and crash statistics. Statistic State North California Ohio Washington Overall Carolina Duration of Projects, Days: Total of All Projects in Sample 6,719 11,329 5,710 6,048 29,806 Average per Project 419.9 566.5 571.0 336.0 466.0 Standard Deviation 215.6 549.6 363.5 321.3 399.0 Minimum per Project 74 44 81 40 40 Maximum per Project 862 2,114 1,033 1,236 2,114 Lengths of Projects, Miles: Total of All Projects in Sample 110.9 155.9 44.0 154.0 464.8 Average per Project 6.9 7.8 4.4 8.6 7.3 Standard Deviation 4.4 7.2 2.8 18.2 10.6 Minimum per Project 1.4 2.0 0.3 0.7 0.3 Maximum per Project 17.0 30.2 9.4 80.5 80.5 Traffic Exposure of Projects, mvm: Total of All Projects in Sample 4,369.5 4,742.0 1,371.7 2,430.4 12,913.6 Average per Project 273.1 237.1 137.2 135.0 201.8 Standard Deviation 359.6 315.0 159.1 193.4 279.4 Minimum per Project 27.6 3.4 25.7 0.7 0.7 Maximum per Project 1,425.8 1,234.5 544.1 716.1 1,425.8 Traffic Crashes Occurring during Projects: Total of All Projects in Sample 6,613 4,831 2,776 3,008 17,228 Average per Project 413.3 241.6 277.6 167.1 269.2 Standard Deviation 607.3 325.0 412.1 272.6 415.3 Minimum per Project 27 0 12 0 0 Maximum per Project 2,292 1,294 1,382 1,105 2,292 Average per Mile per Year 289.0 106.96 200.8 139.6 245.9

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17 465 centerline-mi of roadway and over 82 years of work, for closures were in place that reduced the available capacity of which researchers had to manually determine days and hours the roadway. of work activity and whether temporary lane closures were present. Both project length and duration were highly variable, A fourth possible category, daytime and nighttime periods with an average length of slightly more than 7 mi and an aver- when the project was inactive and temporary lane closures age duration of about 16 months. Actual lengths ranged from were in place, was very limited in the dataset and so was not 0.3 to 80.5 mi, and durations ranged from 40 days to 5.8 years. considered in this analysis. Also summarized in Table 9 are the work zone crashes occur- Researchers attempted to ensure that the projects obtained ring on these projects. More than 17,000 crashes were reported from each state were somewhat balanced between those that during the performance of these 64 projects. Additional proj- had work activity and temporary lane closures during the day, ect details and crash statistics can be found in Appendix A. and those that had work activity and temporary lane clo- Next, Table 10 summarizes the daytime and nighttime sures at night. Ultimately, however, very few projects with crash rates per 100 mvm that would normally be expected for daytime work activities and temporary lane closures were the sample project locations in each state if a work zone were available from California and Ohio. Therefore, this category not present. As shown, these non-work zone crash rates is overrepresented by North Carolina and Washington proj- tended to be higher at night than during the day. Furthermore, ects. Also, the projects obtained from California and Ohio the difference between the nighttime and daytime rates tended tended to be on higher AADT facilities than those from North to be greater for the severe crashes. These numbers indicate Carolina and Washington. that, even in the absence of a work zone, driving at night is Researchers hypothesized that increases in crash risk dur- normally more risky for drivers than driving during the day ing the inactive periods of the project (relative to the crash risk on a per-vehicle-mile traveled basis. Although the per-mvm normally expected on that roadway segment) reflected the rates are usually higher on roadway facilities nationally at influences that temporary geometric changes and other work night than during the day, the much lower traffic volumes zone design decisions had upon safety. Similarly, crash risk using the facilities at night means that the actual number of increases during periods of work activity but with no tempo- crashes occurring on a per-night, per-mile basis is still usually rary lane closures was assumed to reflect the combined effects less than for a per-day, per-mile basis on the same facility. of the geometric changes/work zone design decisions and dis- Researchers developed exposure estimates and stratified tractions and turbulence caused by work activities adjacent to the crashes occurring during each project in the database into the travel lanes. Finally, the increase in crash risk during peri- one of six categories: ods of work activity with temporary lane closures represented the combined effect of geometric changes/work zone design Daytime and nighttime periods when the project was inac- decisions, work activity distractions and turbulence, and tive and no temporary lane closures were in place in the additional traffic turbulence caused by the temporary roadway work zone; capacity restrictions. Table 11 illustrates this concept. Daytime and nighttime periods when work activity was The projects used in this study varied widely in terms of the occurring somewhere within the project but temporary relative amount of work activity performed during the day lane closures were not in place (i.e., no work was occurring and night, as well as the frequency with which these active in the way of travel); and work periods required one or more travel lanes to be tem- Daytime and nighttime periods when work activity was oc- porarily closed. This is illustrated in Table 12. Averaged across curring somewhere within the project and temporary lane each state and over the entire study sample, the projects tended to be active more often during the day than at night Table 10. Expected (non-work zone) average crash in North Carolina, Ohio, and Washington (the California rates in the project dataset. projects were approximately equally active day or night). However, much of the activity during the day at these projects Crash Crashes per 100 mvm occurred outside the roadway, whereas most of the work State Severity Nighttime Daytime California 97.1 78.7 activity at night involved temporary lane closures. Specifically, Severe North Carolina 91.6 72.1 when work occurred at night on the sample projects, 88 percent (Injury or Ohio 92.7 77.1 of the time it involved a temporary lane closure. In contrast, Fatality) Washington 87.5 89.7 Overall 92.8 78.1 temporary lane closures were utilized only 26 percent of the California 150.7 151.8 time that work activity occurred during the day. Of course, North Carolina 153.5 121.4 PDO Ohio 248.4 231.2 these statistics may not be indicative of all freeway projects Washington 112.6 108.9 in these states because projects involving temporary lane Overall 155.8 140.5 closures were specifically targeted in this analysis.