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1  Background The Highway Safety Manual (1st Edition) (AASHTO 2010) has revolutionized trans portation engineering practice by providing crash modification factors and functions (CMFs), along with methods that use safety performance functions (SPFs) for assessing and quantifying the safety consequences of planning, designing, and operating highway facilities. The Highway Safety Manual (1st Edition) recognizes that access management is an effective component in the operation and safety of roadways but includes only a few opportunities to quantify the safety effects of access management strategies. The validity of applying access management CMFs to existing SPFs is also in question since most of the SPFs in the Highway Safety Manual (1st Edition) were established without consider ation of base conditions for access management features. The question remains as to whether or not these SPFs, along with the corresponding CMFs, adequately capture the differences in access management features. Objective The objective of NCHRP Project 17Â74 was to develop and refine CMFs and SPFs for access management features and develop guidance to assist transportation agencies in quantifying the safety impacts of their decisions related to access management. Specifically, this project: ⢠Verified the reliability of using existing SPFs from the Highway Safety Manual (1st Edition) to quantify the safety performance of urban and suburban arterials, ⢠Quantified the safety performance of access management features by developing and refining CMFs and SPFs for various levels of analysis (site, segment/intersection, and corridor), ⢠Provided guidance for the use of accessÂmanagementÂrelated CMFs from the Highway Safety Manual (1st Edition) and the CMF Clearinghouse (FHWA n.d.), and ⢠Identified opportunities for future research. Approach The first phase of the project focused on information gathering and refinement of the work plan. This included a literature review, survey of practitioners, data reconnaissance, and gap analysis. The literature review summarized current information on the safety effects of access management strategies at three levels: site, intersection, and corridor. This review formed the basis for the remainder of the project as it helped to identify existing S U M M A R Y Application of Crash Modification Factors for Access Managementâ Volume 2: Research Overview
2 Application of Crash Modification Factors for Access Management highÂquality CMFs and SPFs for access management strategies (which were relatively limited). The literature review also informed the gap analysis, helping to identify areas where highÂquality CMFs and SPFs are not available. The survey of practitioners sought to identify transportation agency policies, practices, needs, and challenges related to quantifying the safety effects of access management strategies. The survey results identified priority strategies, the extent to which agencies are quantifying the safety effects of access management strategies, and the level of analysis (i.e., site, inter section, or corridor) that would be most helpful for future efforts to quantify safety effects. The survey results indicated the following regarding the quantification and tracking of the safety effects of access management strategies and the existence of policy or procedures for assessing these effects: ⢠Most respondents do not quantify the safety effects of access management strategies to support the decisionÂmaking process, ⢠More than 80 percent indicated their agencies do not have a policy or procedure for assessing the safety effects of access management strategies, ⢠Most indicated a priority need for estimating the effects of combination strategies, while less than half indicated a priority need for focusing on individual strategies, and ⢠CorridorÂlevel analysis was the highest priority as opposed to segment/intersection or siteÂlevel analysis. As part of the survey, and through a parallel effort, the project team identified and reviewed existing data sources to determine the availability and quality of data to support this research. The data reconnaissance helped to determine the feasibility of evaluating priority strategies and strategy combinations. It also helped to identify potential data and methodological issues to consider during the data collection and analysis, thus informing the study design and data collection plan. In the review, answers to the following specific questions were sought: ⢠What data are readily available in existing databases? ⢠How many miles of road and counts of intersections (by facility type) are available? ⢠What is the availability of suitable reference locations? ⢠What is the quality of existing data? ⢠Which agencies provided the data? ⢠Who is the point of contact for acquiring the data? Following the literature review, survey, and data reconnaissance, the project team sum marized current knowledge and identified gaps to establish research priorities and appro priate study design(s). The project team then met with the panel to discuss these priorities and determine the focus of the research, considering the schedule, budget, and data avail ability. The primary research question was: How does the existing Highway Safety Manual (1st Edition) Predictive Method (i.e., a combination of SPFs and CMFs) perform for sites with similar geometry but different access management features (e.g., access density and spacing, corner clearance, and turning restrictions) not captured in the crash prediction model? While the research focused on Chapter 12: Urban and Suburban Arterials from the Highway Safety Manual (1st Edition), it also considered the urban and suburban arterial SPFs developed for NCHRP Project 17Â62, âImproved Prediction Models for Crash Types and Crash Severities,â that predict crashes by crash type and severity and will presumably support the Highway Safety Manual (2nd Edition). The following is a list of access management strategies that were a focus of the research: ⢠Manage location, spacing, and design of median openings and crossovers; ⢠Manage location and spacing of unsignalized access;
Summary 3  ⢠Manage the spacing of signalized and unsignalized access on crossroads in the vicinity of freeway interchanges; ⢠Establish functional area and corner clearance criteria; ⢠Manage spacing and density of traffic signals; and ⢠RightÂturn treatment. The second phase of the project implemented the work plan, including data collection, analysis, and documentation. The data collection leveraged existing datasets to minimize duplication of efforts and maximize the amount of data for analysis in this study. Specifically, the project team used existing crash, roadway, and trafficÂcharacteristic data from NCHRP Project 17Â62 and supplemented these datasets with additional access management variables. NCHRP Project 17Â62 data include segments from Ohio and Minnesota and intersections from Ohio and North Carolina. The project team performed manual data collection for over 3,500 intersections, both signalized and stop controlled, and nearly 4,000 segments throughout Ohio, over 240 intersections from North Carolina, and nearly 500 segments from Minnesota. The data analysis focused on assessing, validating, and enhancing the Part C Predictive Method from the Highway Safety Manual (1st Edition) to investigate the effect of access management variables on crash predictions. The following is an overview of the gen eral procedure to assess the Part C Predictive Method from the Highway Safety Manual (1st Edition): 1. Evaluate whether the Part C Predictive Method shows prediction bias for access manage ment features (i.e., does it over or underÂpredict for site characteristics related to access management?); 2. If substantial prediction bias exists, determine if there is a discernable and explainable pattern; 3. Attempt to create CMFs to remove the prediction bias for the access management features. In doing so, evaluate whether the relationships make sense (i.e., is the direction and magnitude of effect reasonable?); and 4. Using a validation dataset, determine whether the findings are consistent among datasets. If no significant bias was found, then it was concluded that the Part C Predictive Method performs well at predicting crashes, and the addition of CMFs for those variables is not likely to improve the prediction performance. If significant prediction bias was observed, the project team employed two alternate but related methodologies to estimate CMFs for each access management strategy. The first approach was based on the calibration of SPFs, and the second was based on estimating a new regression model. To validate the results, the project team used a second stateâs data to test the same crash prediction models and look for consistency in the findings of goodness of fit and any CMFs developed. Based on the results of the analysis, the project team developed a practitionerâs guide (Volume 1 of NCHRP Research Report 974) to assist transportation planners, designers, and traffic engineers in quantifying the safety impacts of access management strategies and making more informed accessÂrelated decisions on urban and suburban arterials (Gross et al. 2021). 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. The safety performance can then be used in the decision pro cess 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 consider ing safety alongside other factors, agencies will better understand the comprehensive costs
4 Application of Crash Modification Factors for Access Management and benefits of projects, which will lead to more informed decisions and more effective investments. The project team vetted the guide with a focus group of 40 practitioners repre senting diverse perspectives on highway safety and access management. The practitioners also represented diverse agencies and organizations, from state and local transportation agencies to consultants and academia. Results The Part C Predictive Method from the Highway Safety Manual (1st Edition) includes separate methods for estimating the safety performance of segments and intersections and both include some access management features. For segmentÂlevel predictions, the Part C Predictive Method accounts for the number and type of driveways along the segment. For intersectionÂlevel predictions, the Part C Predictive Method accounts for the presence of left and rightÂturn lanes, leftÂturn signal phasing (at signalized intersections), and right turnÂonÂred restrictions (at signalized intersections). The research from NCHRP Project 17Â74 confirmed that the Part C Predictive Method performs relatively well across a range of other access management features not accounted for in the existing method. Specifically, the Part C Predictive Method (i.e., a combination of SPFs and CMFs) performs well for sites with similar geometry, 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. Notable scenarios include locations with chan nelized rightÂturn lanes and locations with nearby ramp terminals. As such, this research developed adjustment factors to account for differences in the predictions at locations with channelized rightÂturn lanes and locations with nearby ramp terminals. The following is a summary of those results: ⢠For distance to ramp terminal, bias was not observed in the predictions for signalized intersections. The cumulative residual (CURE) plots did not show substantial bias for stopÂcontrolled intersections although the CURE plot does indicate that for distances under 1,500 ft, there may be an underÂprediction of crashes. The recommended CMF (adjustment factor) for threeÂlegged minor stopÂcontrolled intersection (3ST) sites and fourÂlegged minor stopÂcontrolled intersection (4ST) sites is 2.12 if there is a ramp terminal within 1,500 ft. The CMF is intuitive in that more crashes are predicted as the distance to ramp terminal becomes smaller. ⢠For channelizing rightÂturn lanes, the results were inconsistent and generally not statisti cally significant at the 95Âpercent confidence level for threeÂlegged signalized intersection (3SG) sites, fourÂlegged signalized intersection (4SG) sites, and 4ST sites. For 3ST sites, the recommended CMF (adjustment factor) is 0.72 for the presence of a channelized right turn lane, compared to the base condition of a rightÂturn lane with no channelization. Another significant finding of this research is that the Part C Predictive Method should not be used to estimate the safety effect of variables related to access spacing and density. The Part C Predictive Method is only applicable to estimating the safety performance of individual segments and intersections, 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).
Summary 5  The structure of the data for the Highway Safety Manual (1st Edition) Part C Predictive Method is such that roadways are segmented by intersection, and midblock areas and crashes are assigned to one of the two. One of the important findings of this research was that as the number of intersections in a segment increased, the expected number of segment crashes often decreased. This is contrary to expectations since the presence of more intersections should lead to more conflicts, and certainly not fewer, even away from the intersections. However, the structure of the data may contribute to this counterintuitive finding. Specifically, if more intersections are present, then it is more likely that a crash will be assigned to an intersection and not a segment. Given this finding, the data are not con ducive to segmentÂlevel analysis of some variables (e.g., intersection density, spacing, etc.). Instead, these variables are better assessed at the corridor level. A corridorÂlevel predictive method is presented in NCHRP Research Report 974: Application of Crash Modification Factors for Access ManagementâVolume 1: Practitionerâs Guide that is more appropriate for considering interactions among access management features and estimating the safety effect of variables related to access spacing and density (Gross et al. 2021).