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1  This practitionerâs guide presents methods to help transportation planners, designers, and traffic engineers quantify the safety impacts of access management strategies and make more-informed access-related decisions regarding urban and suburban arterials. To achieve this objective, the guide presents methods to quantify the safety performance of individual locations (i.e., intersections or segments) as well as corridors that represent multiple adjacent intersections and segments. Potential benefits of using the guide include the following: ⢠Safety-conscious, performance-based practical design and construction. Quantitative safety analysis informs agencies as to which of several project designs is expected to pro- vide the greatest safety benefit to the public. ⢠Understanding of complex projects. Quantitative safety analysis can help practitioners to understand the comprehensive costs and benefits of projects and to compare the safety performance with other factors such as mobility, environmental impacts, and regional economies. ⢠Return on investment. Quantitative safety analysis supports economic analysis, which can help practitioners to make more-informed decisions in planning, programming, and implementing transportation programs, which can improve the rate of return for a given budget. ⢠Documentation of decision process and public involvement. Quantifying the benefits and costs of highway projects also provides documentation to justify and explain the decision process to legislatures and the public. Chapter 2 provides a brief introduction to quantitative safety performance, including definitions of key terms such as crash modification factors and functions (CMFs), safety performance functions (SPFs), observed crashes, predicted crashes, and expected crashes. Appendix B provides a more thorough overview of quantitative safety performance, including basics on the application of quantitative safety methods. Appendix A provides a summary of resources related to access management and safety, indicating how each resource relates to this guide and would support specific analyses or decisions. Chapter 3 provides an overview of access management and background information on the purpose of specific access management strategies. The strategies are divided into four areas: access spacing, roadway cross section, intersections, and property access. The access spacing strategies include unsignalized access density and spacing criteria, signal density and spacing criteria, functional area and corner clearance criteria, and spacing criteria for inter- change crossroads. The roadway cross-section strategies include non-traversable medians, spacing criteria for median openings/crossovers, two-way left-turn lanes (TWLTLs), and conversion of two-way streets to one-way operation. The intersection strategies include left-turn lanes, right-turn lanes, and alternative intersection designs. The property access Application of Crash Modification Factors for Access Managementâ Volume 1: Practitionerâs Guide S U M M A R Y
2 Application of Crash Modification Factors for Access Management strategies include driveway design elements, sight distance at unsignalized access, frontage/ backage roads, and shared driveways and internal cross connectivity. Chapter 3 also presents high-quality CMFs for these access management strategies on urban and suburban arterials. Analysts can use the CMFs to compare the relative safety impacts of access management strategies or apply the CMFs to the observed, predicted, or expected crashes to estimate the magnitude of the expected change in safety. As discussed in Appendix B, the use of observed, predicted, and expected crashes results in varying degrees of reliability. Specifically, applying CMFs to expected or predicted crashes is typically more reliable than applying CMFs to observed crashes. In some instances, the CMFs presented in this chapter can be applied in the segment- and intersection-level predictive methods presented in Chapter 4; however, prior to applying any CMFs that were not developed specifically for use with the predictive method in Chapter 4, there is a need to consider the applicability of the CMFs with respect to crash type, crash severity, and base condition as well as the potential for double-counting crash reductions with each additional CMF. Chapter 3 also includes CMFs inferred from the Highway Safety Manual (1st Edition) (AASHTO 2010). Inferred CMFs are based on the ratio of predicted crashes from one or more statistical models for two conditions of interest. For example, the Highway Safety Manual (1st Edition) provides models for multivehicle driveway and non-driveway crashes per mile, considering the traffic volume, number and type of driveways, and median type (divided or undivided). Using the models, one could predict crashes for various combinations of driveway density, driveway type, median type, and traffic volume, and use the ratio of two predictions to infer the CMF (i.e., the expected change in crashes when converting from one condition to another). In some cases, the inferred CMFs provide a logical relationship. In other cases, it is not reasonable to use the results from cross-sectional models to infer CMFs. Specifically, when cross-sectional models do not account for all differences in safety between the two site types, the comparison of results from two different cross-sectional models may not produce reasonable and reliable CMFs. Further, it is necessary to calibrate cross-sectional models to the same spatial and temporal conditions before using the models to infer CMFs. Counter- intuitive results are presented in a separate section of Chapter 3 with discussion and cautions not to use the CMFs to estimate the safety effect of the specific variables. Chapter 4 presents a method to estimate the safety performance of individual inter sections and segments, including instructions on how to apply CMFs from Chapter 3 to adjust the predictions. The method is consistent with Part C Predictive Method of the Highway Safety Manual (1st Edition) but expands the method to incorporate the safety impacts of addi- tional access management strategies. The Part C Predictive Method already facilitates the consideration of a limited number of access management variables. For segment-level pre- dictions, the existing method accounts for the number and type of driveways along the segment. For intersection-level predictions, the existing method accounts for the presence of left- and right-turn lanes, left-turn signal phasing (at signalized intersections), and right- turn-on-red restrictions (at signalized intersections). The NCHRP Project 17-74 research confirmed that the Part C Predictive Method of the Highway Safety Manual (1st Edition) performs relatively well across a range of several other access management features not accounted for in the existing predictive method. Specifically, the existing Part C Predictive Method (i.e., combination of SPFs and CMFs) performs well for sites with similar geom- etry, but different access management features such as median opening spacing, number of median openings by type, and corner clearance along a segment. There are, however, a few scenarios where the existing models do not perform well across sites with different access management features. Chapter 4 identifies these scenarios and presents adjustment factors to account for differences in the predictions, including channelized right-turn lanes and distance to ramp terminal.
Summary 3  Chapter 4 presents another significant limitation of the Part C Predictive Method with respect to access management. Specifically, the Part C Predictive Method should not be used to estimate the safety effect of variables related to access spacing and density. Chapter 4 is only applicable to estimating the safety performance of individual segments and inter- sections, assuming independence among each unit of analysis. While the results can be aggregated from multiple segments and intersections to estimate the safety performance of a corridor, as suggested in the Highway Safety Manual (1st Edition), this method does not consider the potential interactions among adjacent or nearby sites (e.g., access spacing and density). The existing Part C Predictive Method may even produce counterintuitive results (e.g., fewer estimated segment crashes with an increase in the number of intersections along a corridor). As such, the corridor-level predictive method presented in Chapter 5 is more appropriate for considering interactions among access management features and estimating the safety effect of variables related to access spacing and density. Chapter 5 presents two methods for estimating corridor-level safety performance and provides guidance on when to use each method. The first method combines predictions for individual locations based on the predictive method in Chapter 4. Again, the method does not account for the potential interactions among adjacent or nearby sites and should not be used to estimate the safety effect of variables related to access spacing and density. The second method is based on corridor-level prediction models, which provide a more reli- able method to account for interactions among adjacent sites and among multiple access management strategies. The corridor-level prediction models help to account for situa- tions where safety performance is influenced more by corridor-level characteristics than by the specific characteristics of an individual location. For example, some access manage- ment strategies may shift turning traffic from one location to another (e.g., converting an undivided road to a physically divided road). In other cases, detailed access design (e.g., intersection or median opening spacing) will impact the safety performance of the corridor beyond the simple presence of the feature. In such cases, corridor-level crash predictions are more appropriate than aggregating crash predictions for individual sites. Chapter 6 explains how to communicate analysis results and document access manage- ment planning and design decisions. While the methods in this guide can help to quan- tify and compare the safety performance of alternatives, the analysis effort is futile unless decision-makers use the results to inform decisions. Chapter 6 describes how the guide can serve the needs of both technical and non-technical audiences and acknowledges the poten- tially wide range of expertise and interest within these audiences. The chapter then identifies communication methods and explains how to select and employ appropriate communica- tion methods to target and effectively reach various audiences. Several different measures and formats are presented for conveying the key results to technical and non-technical audi- ences. Measures include technical safety and economic factors such as the expected number of crashes and the return on investment (benefit-cost ratio) as well as more human-centric safety indicators such as lives saved and injuries prevented. The formats provide a balance of simple tabular information and creative graphical displays to present multiple dimensions of the analysis. Regardless of the audience, method, measure, and format, one common theme is the need to engage communication experts throughout the process. In summary, the objective of this guide is to assist transportation agencies in quanti- fying the safety impacts of their decisions related to access management. The safety per- formance can then be used in the decision process to compare against other quantitative measures (e.g., costs, operational efficiency, and environmental impacts) or perceptions (e.g., fairness, convenience, and competitiveness related to property access and businesses). By quantifying safety performance and considering safety alongside other factors, agencies will better understand the comprehensive costs and benefits of projects, which will lead to more-informed decisions and more impactful investments.
