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53 Understanding the roles of root cause(s) and contributing tistically significant analysis of the reduction in the number of factors is important. If the fundamental weaknesses of the sys- collisions following the implementation of a given treatment. tem are not identified and improved, the likelihood of inci- The state of the art in safety study methodology generally dents recurring is increased. requires the use of empirical Bayes analysis, but contemporary Ideally, safety treatments should address the root causes to statistical approaches such as empirical Bayes analysis are still have the best effect on conditions leading to a collision. If pos- relatively new to transportation studies, and have not been sible, a holistic approach should be used to determine root applied to the field of LRT safety. No references to LRT and causes and contributing factors, and safety treatments that will empirical Bayes analysis were found during the literature provide the best overall safety effects for the system. By consid- review, survey, or other inquiries. The literature review found ering the entire system, practitioners can avoid taking a narrow no statistical analyses of LRT collision data that were statisti- view that may modify one aspect of the system without taking cally defensible in terms of contemporary statistical analysis into account other issues and repercussions. It some cases methods. where the root cause is difficult to control, it may be possible The lack of studies using statistically sophisticated and defen- to mitigate the number and/or severity of crashes by treating a sible methods can be attributed to several issues. Firstly, as sug- contributing factor in an effective matter. gested above, transportation and LRT safety practitioners are not usually familiar with contemporary statistical methods. In addition, data issues include the lack of essential and sufficient Determining LRT Safety Issues collision data; the lack of vehicular, pedestrian, and LRV vol- and Identifying Treatments ume data; and the lack of rail and highway inventory informa- Chapter 2 identified a list of the safety issues noted by agen- tion, including the dates on which safety treatments were cies and SSOs. Chapter 3 outlined the data quality and quan- implemented. In the survey of local LRT agencies, for example, tity problems facing LRT safety analysis. Because of these data 10 of the 17 agencies that answered the question on four- problems, it is difficult to determine the root causes of LRT quadrant gates did not record the installation date. The survey collisions in a statistically significant analysis. It is also difficult found that non-recording of date information ranged from to undertake a statistical analysis of the effectiveness of a given 27% to 88%, depending on the treatment. safety treatment. To determine the feasibility of adopting an empirical Bayes This section outlines methods that can be used to determine analysis to examine the safety impacts of selected treatments LRT safety issues and identify treatments. Anecdotal informa- along LRT alignments, it is essential to first determine the data tion available from agency and SSO staff who work with LRT that are needed to carry out the analysis. (Data availability and alignments, formal LRT safety analysis (where available), the data quality are discussed in Chapter 3.) safety literature, consultation with professionals, and the site The studies available are generally limited in scope and do visits to LRT agencies were used to identify some of the most not examine the holistic safety impacts of the various treat- common or severe LRT collision types. The section then iden- ments being studied. For example, devices such as pre-signals tifies some surrogate (proxy) measures that can help agencies and advance signals have been widely implemented through- identify potential safety hazards. out North America. The focus of these studies of pre-signals and advance signals, however, is on signal violations or the impact on LRVmotor vehicle crashes. No studies have exam- Studying LRT Safety Issues and Treatments ined the system-wide impacts of such treatments--for exam- Most previous studies of safety along LRT alignments have ple, the possibility that the implementation of a new traffic examined treatments using simple before-and-after compar- signal at a location could result in an increase in crashes, such isons of collisions, anecdotal evidence, collision surrogate as rear end collisions, that involve only motor vehicles. measures such as violations, or a combination of two or three of these approaches. Standard "t" tests require sufficiently Determining the Highest Risk long periods to elapse both before and after studies. Where LRT Safety Issues the number of years is limited and/or the numbers involved are small, an unusually "high" year and a "low" year after Unlike motor vehicles, LRVs cannot swerve, and even emer- could reflect regression to the mean rather than an effect of gency stop conditions do not enable the LRV to avoid pedes- the treatment. trians who are errant or walking counter to traffic control Although the effectiveness of treatments (such as LRV- devices. Nevertheless, Korve et al. in TCRP 17 (2) found that activated signs) in reducing the number of incidents of risky collisions between pedestrians and LRVs are the least common behavior on the part of motorists has been well demonstrated type of LRT-related collision. Collisions between pedestrians (1, 2), LRT safety studies to date have not been based on sta- and LRVs in the systems reviewed represented only about 10%