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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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Suggested Citation:"Appendix D: Initial Study Designs." National Academies of Sciences, Engineering, and Medicine. 2018. Assessing Interactions Between Access Management Treatments and Multimodal Users. Washington, DC: The National Academies Press. doi: 10.17226/25344.
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150 A P P E N D I X D : I N I T I A L S T U D Y D E S I G N S Initial Study Designs Introduction This appendix documents the initial study designs developed for each of the 20 AM techniques identified in Table 74 (of Appendix C). The design elements described for each of the AM techniques include the following:  Modal focus  Study objectives, method, scope, and output results  Analysis scale  Operations data source  Safety data source  Performance measures The information in the initial study designs was used in the technique assessment procedure described in Appendix C. For each technique, the associated study design elements were used to compute the cost to develop performance relationships for the needed travel mode and performance measure categories. These cost estimates are provided in Appendix C. Study Designs for Original Techniques Technique: 1a. Establish Traffic Signal Spacing Criteria Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for operational effects on the truck travel mode; and for safety effects on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the truck travel mode; and safety performance relationships for pedestrian, bicycle, transit and truck travel modes. Key elements of the proposed study design are presented in Table 84. The study design will likely produce a relationship that describes the change in safety or operations associated with different traffic signal spacing. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in delay or speed associated with different traffic signal spacing.

151 Table 84. Study design for traffic signal spacing. Technique: Establish Traffic Signal Spacing Criteria Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of through lanes, signal timing, density of intermediate access points, intersection control, functional classification of cross streets, vehicle volume, turn vehicle percent, speed limit, heavy vehicle percent, Pedestrian Existing relationship Bicycle Existing relationship Transit Existing relationship Truck Average travel speed Safety Field _ Simulation X Crash reports In addition to the variables listed above, pedestrian volume on the main and crossing streets, bicycle volume on the main and crossing streets, transit stop location (near side/far side), transit vehicle occupancy, transit vehicle headway Pedestrian Vehicle-pedestrian conflicts, vehicle speed Bicycle Vehicle-bicycle conflicts and speed differential Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study method will be used with a database consisting of many corridors that collectively have a range of signal spacing. Operations Data Source It is likely that truck drivers will be responsive and compliant with traffic signal controls, so the source for operations data is simulation. A simulation testbed will be established using several different prototype corridors with a range of signal spacing. Key independent variables that may influence the effect of traffic signal spacing on truck operations are listed in Table 84. Safety Data Source Reported crash data will be acquired for a large number of corridors that collectively have a range of signal spacing. These data will then be evaluated to determine if there are sufficient pedestrian-, bicycle-, transit-, and truck-related crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for these volumes. This option may require a relatively large amount of project resources.

152 Performance Measures The performance measures are listed in Table 84. These performance measures will be obtained from the aforementioned data sources. Technique: 1b. Establish Spacing for Unsignalized Access Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of this technique on pedestrian, transit, and truck travel modes. It is also unavailable for the safety effects of this technique on the bicycle, transit, and truck modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the pedestrian, transit, and truck travel modes; and safety performance relationships for the bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 85. The study design will likely produce a relationship that describes the change in operations and safety performance when different spacing is used for unsignalized access points. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with different spacing for unsignalized access points.

153 Table 85. Study design for access point spacing. Technique: Establish Spacing for Unsignalized Access Analysis Scale: _X Corridor ___Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of through lanes, density of intermediate access points, main street functional classification, transit vehicle headway, vehicle and pedestrian volumes, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, median type Pedestrian Person delay Bicycle Existing relationship Transit Person delay, average travel speed Truck Average travel speed Safety Field X Simulation Crash reports In addition to the variables listed above, bicycle volumes, width of outside lane, bicycle lane presence, width of bicycle lane, presence of on-street parking, width of parking Pedestrian Existing relationship Bicycle Vehicle-bicycle conflicts and speed differential Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied on corridors so the analysis scale is “corridor.” A cross-sectional study method will be used with a database consisting of many corridors that collectively have a range of access point spacing. Operations Data Source Travelers will react to the presence or absence of all unsignalized access drives they encounter, so the source for operations data is simulation. A simulation testbed will be established using several different prototype corridors with a range of access point spacing and segment length. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 85. Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed established for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data.

154 As a second choice, crash data may be acquired for a large number of locations where different unsignalized intersection spacing can be found. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Bicycle volume is unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for this volume. This second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures for the pedestrian, bicycle, transit, and truck travel modes are listed in the last column of Table 85. These performance measures will be obtained from the aforementioned data sources. Technique: 1c. Establish Corner Clearance Criteria Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. The literature review results also indicate that this technique is likely to have negligible effect on the operations or safety of pedestrians and bicyclists. As a result, this study design is focused on the transit and truck modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for transit and trucks. Key elements of the proposed study design are presented in Table 86. The study design will likely produce a relationship that describes the change in safety or operations as corner clearance distances are adjusted. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in identified operations performance measures associated with the use of different corner clearance distances.

155 Table 86. Study design for corner clearance. Technique: Establish Corner Clearance Criteria Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of through lanes, intersection control, functional classification of main street, transit vehicle headway, transit stop location (near side/far side), vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, distance between signalized intersection and access point, median type Pedestrian Negligible effect Bicycle Negligible effect Transit Person delay Truck Delay Safety Field _ Simulation X Crash reports Same as above. Pedestrian Negligible effect Bicycle Negligible effect Transit Transit-involved crash reports Truck Truck-involved crashes Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” Even so, it is expected that success will be most easily achieved by investigating a cross-sectional database consisting of many intersections configured with varying corner clearances. Operations Data Source It is likely that transit and truck drivers will be responsive to the corner clearances embedded into the configuration of each intersection, so the source for operations data is simulation. A simulation testbed will be established using several different signalized intersection configurations and a range of distances to the nearest access point. Key independent variables that may influence the effect of corner clearance on operations performance measures are listed in Table 86. Safety Data Source Reported crashes will be the source for safety data. These data will be collected for a large number of locations with varying corner clearances. These data will then be evaluated to determine if there are sufficient transit- and truck-related crashes to quantify a relationship between crash frequency and corner clearance distance.

156 Performance Measures The performance measures for the transit and truck travel modes are listed in the last column of Table 86. These performance measures will be obtained from the aforementioned data sources. Technique: 2a and 2b. Install Non-Traversable Median on Undivided Highway and Replace TWLTL with Non-Traversable Median Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of these techniques on the bicycle and truck travel modes; and it is also unavailable for the safety effects of these techniques on the transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the bicycle and truck travel modes, and safety performance relationships for the transit and truck travel modes. Key elements of the proposed study design are presented in Table 87. The study design will likely produce a relationship that describes the change in safety or operations when a non-traversable median is installed. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a non-traversable median.

157 Table 87. Study design for non-traversable median. Technique: Non-Traversable Median Analysis Scale: X Corridor _ Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes, lane and shoulder width, density of intermediate access points, intersection control, functional classification of major street, vehicle volume, bicycle volume, turn vehicle percent, speed limit, heavy vehicle percent, median type, presence of on- street parking, width of on- street parking, area type. Pedestrian Existing relationship Bicycle Average travel speed Transit Existing relationship Truck Average travel speed Safety Field Simulation X Crash reports Same as above. Include transit vehicle occupancy transit vehicle headway, transit stop location (near side/far side). Exclude bicycle volume. Pedestrian Existing relationship Bicycle Existing relationship Transit Transit-involved crashes Truck Truck-involved crashes Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study method will be used with a database consisting of many corridors that collectively have a range of median types. Operations Data Source It is likely that travelers will be compliant with the installed form of median treatment, so the source for operations data is simulation. A simulation testbed will be established using several different prototype corridors that have an undivided cross section, a two-way left-turn lane (TWLTL) median, or a non- traversable median. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 87. Safety Data Source Reported crashes will be the source for safety data. A number of corridors will be studied that have an undivided cross section, a TWLTL, or a non-traversable median. These data will then be evaluated to determine if there are sufficient transit- and truck-related crashes to quantify a performance relationship.

158 Performance Measures The performance measures are listed in the last column of Table 87. These performance measures will be obtained from the aforementioned data sources. Technique: 2c. Close Existing Median Openings Modal Focus The results of the literature review indicate that the only quantitative information currently available for evaluating this technique has to do with its effect on bicycle safety. Therefore, this study design is focused on the operational effects of this technique on the pedestrian, bicycle, transit, and truck travel modes; and the safety effects of this technique on the pedestrian, transit, and truck modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. Key elements of the proposed study design are presented in Table 88. The study design will likely produce a relationship that describes the change in safety or operations when an existing median opening is closed. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the closure of an existing median opening.

159 Table 88. Study design for closing existing median openings. Technique: Close Existing Median Openings Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking, area type. Pedestrian Person delay Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Delay, out-of- direction travel Safety Field Simulation X Crash reports Same as above. Exclude bicycle volume. Pedestrian Vehicle-pedestrian crashes Bicycle Existing relationship Transit Transit-involved crashes Truck Truck-involved crashes Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A before– after study method will be used. A number of corridors will be studied before and after the median openings are closed. Operations Data Source Traveler behavior will be responsive to the presence or absence of a median opening, so the source for operations data is simulation. A simulation testbed will be established using several different prototype corridors, all of which have median openings to represent the “before” condition. These median openings will be removed from the testbed to represent the “after” condition. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 88.

160 Safety Data Source Reported crashes will be the source for safety data. A number of corridors will be identified and studied that have had median openings closed in the recent past These data will then be evaluated to determine if there are sufficient pedestrian-, transit-, and truck-related crashes to quantify a performance relationship. Pedestrian volume is unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for this volume. Performance Measures The performance measures are listed in the last column of Table 88. These performance measures will be obtained from the aforementioned data sources. Technique: 2d. Replace Full Median Opening with Median Designed for Left Turns from the Major Roadway Modal Focus The results of the literature review indicate that the only quantitative information currently available for evaluating this technique has to do with its effect on bicycle safety. Therefore, this study design is focused on the operational effects of this technique on the pedestrian, bicycle, transit, and truck travel modes; and the safety effects of this technique on the pedestrian, transit, and truck modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. Key elements of the proposed study design are presented in Table 89. The study design will likely produce a relationship that describes the change in safety or operations when a full median opening is replaced with a median designed to accommodate only left turns from the major roadway. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the redesigned median opening.

161 Table 89. Study design for replacing a full median opening with a median designed for left turns from the major roadway. Technique: Replace a Full Median Opening with a Median Designed for Left Turns from the Major Roadway Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking, area type. Pedestrian Person delay Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Exclude bicycle volume. Pedestrian Vehicle-pedestrian conflicts Bicycle Existing relationship Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of unsignalized access points will be studied before and after the median opening is changed to limit turn movements. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype intersections with full median openings to represent the “before” condition. To represent the “after” condition, these median openings will be changed in the testbed to accommodate only left turns from the major road. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 89.

162 Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed assembled for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where median openings have been installed to accommodate major street left turns. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. However, this second- choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 89. These performance measures will be obtained from the aforementioned data sources. Technique: 3c. Install a Continuous TWLTL on an Undivided Highway Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for evaluating the operational effects of this technique on bicycle and truck travel modes. Additionally, quantitative information is currently unavailable for evaluating the safety effects of this technique on bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the bicycle and truck travel modes; and safety performance relationships for the bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 90. The study design will likely produce a relationship that describes the change in safety or operations when a continuous TWLTL median is installed on an undivided highway. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a continuous TWLTL.

163 Table 90. Study design for installation of a continuous TWLTL on an undivided highway. Technique: Installation of a Continuous TWLTL on an Undivided Highway Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Width of lanes, density of access points, area type, median type, abutting land use, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, bicycle volume, vehicle volume, turn vehicle percent, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Existing relationship Bicycle Average travel speed Transit Existing relationship Truck Average travel speed Safety Field Simulation X Crash reports In addition to the variables listed above, transit vehicle headway, transit stop location (near side/far side), transit vehicle occupancy. Pedestrian Existing relationship Bicycle Vehicle-bicycle crashes Transit Transit-involved crashes Truck Truck-involved crashes Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study method will be used with a database consisting of a number of corridors that have either an undivided cross section or a TWLTL. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype corridors that have an undivided cross section or a TWLTL. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 90. Safety Data Source Reported crash data will be acquired for a large number of corridors. These corridors will have either an undivided cross section or a TWLTL. These data will then be evaluated to determine if there are sufficient bicycle-, transit-, and truck-related crashes to quantify a performance relationship. Bicycle

164 volume is unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for this volume. Performance Measures The performance measures are listed in the last column of Table 90. These performance measures will be obtained from the aforementioned data sources. Technique: 3d. Install U-Turns as an Alternative to Direct Left Turns Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of this technique on the pedestrian, bicycle, and transit travel modes. Quantitative information is also currently unavailable for the safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the pedestrian, bicycle, and transit travel modes; and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 91. The study design will likely produce a relationship that describes the change in safety or operations when a U-turn is installed or permitted as an alternative to direct left turns. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a U-turn as an alternative to direct left turns.

165 Table 91. Study design for median U-turns as an alternative to direct left turns. Technique: U-Turns as an Alternative to Direct Left Turns Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent – including U-turns, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Existing relationship Safety Field X Simulation Crash reports Same as above. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A before– after study method will be used. A number of sites will be studied before and after median U-turns have been added as an alternative to direct left turns. A “site” for this study will include both the median opening at which the U-turn is completed and the nearby intersection at which the direct left turns were completed (before the U-turn was installed or permitted). Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype corridors without median U-turns to represent the “before” condition. The median U-

166 turns will be added to the testbed to represent the “after” condition. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 91. Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed used for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for these volumes. Performance Measures The performance measures are listed in the last column of Table 91. These performance measures will be obtained from the aforementioned data sources. Technique: 4a. Install Right-Turn Deceleration Lane Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the transit and truck travel modes. Also unavailable is information describing the effect of this technique on bicycle operations. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. Key elements of the proposed study design are presented in Table 92. The study design will likely produce a relationship that describes the change in safety or operations when a right-turn deceleration lane is installed. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a right-turn deceleration lane.

167 Table 92. Study design for installation of a right-turn deceleration lane. Technique: Installation of a Right-Turn Deceleration Lane Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes, width of lanes, density of intermediate access points, land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street, transit vehicle headway, transit stop location (near side/far side), bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on- street parking, presence of right-turn channelization. Pedestrian Existing relationship Bicycle Person delay Transit Person delay Truck Delay Safety Field X Simulation Crash reports Same as above. Exclude bicycle volume. Pedestrian Existing relationship Bicycle Existing relationship Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of intersections will be studied before and after a right- turn deceleration lane is installed. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype intersections without right-turn deceleration lanes to represent the “before” condition. The right-turn deceleration lanes will be added to the testbed intersections to represent the “after” condition. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 92.

168 Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed used for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the transit-, and truck-related conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient transit-, and truck- related crashes to quantify a performance relationship. Performance Measures The performance measures are listed in the last column of Table 92. These performance measures will be obtained from the aforementioned data sources. Technique: 4b. Install Continuous Right-Turn Lane Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 93. The study design will likely produce a relationship that describes the change in safety or operations when a continuous right-turn lane is installed. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a continuous right-turn lane.

169 Table 93. Study design for installation of a continuous right-turn lane. Technique: Installation of a Continuous Right-Turn lane Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay, average travel speed Bicycle Person delay, average travel speed Transit Person delay, average travel speed Truck Delay, average travel speed Safety Field Simulation X Crash reports In addition to the variables listed above, pedestrian volume on the main and crossing streets, bicycle volume on the main and crossing streets Pedestrian Vehicle-pedestrian crashes Bicycle Vehicle-bicycle crashes Transit Transit-involved crashes Truck Truck-involved crashes Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of street segments will be studied before and after a continuous right-turn lane is installed. Each segment is considered a study site. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype street segments without a continuous right-turn lane to represent the “before” condition. The continuous right-turn lane will be added to the testbed segments to represent the “after” condition. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 93.

170 Safety Data Source Reported crashes will be the source for safety data. A number of street segments will be identified and studied that in the recent past have had a continuous right-turn lane installed. These data will then be evaluated to determine if there are sufficient pedestrian-, bicycle-, transit-, and/or truck-related crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost- effective to measure so adjacent land use will be used as a surrogate for these volumes. Performance Measures The performance measures are listed in the last column of Table 93. These performance measures will be obtained from the aforementioned data sources. Technique: 5a. Consolidate Driveways Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for evaluating the operational effects of driveway consolidation on the bicycle and truck travel modes. Additionally, quantitative information is currently unavailable for evaluating the safety effects of this technique on the pedestrian, bicycle, ant truck travel modes. This technique is not expected to have a significant effect on the operations or safety of the transit mode. As a result, this particular travel mode will not be included in the study design. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the bicycle and truck travel modes, and safety performance relationships for the pedestrian, bicycle, and truck travel modes. Key elements of the proposed study design are presented in Table 94. The study design will likely produce a relationship that describes the change in safety or operations when two or more driveways are consolidated. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the consolidation of two or more driveways.

171 Table 94. Study design for consolidate driveways. Technique: Consolidating Driveways Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, bicycle volume, vehicle volume, turn vehicle percent, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking Pedestrian Existing relationship Bicycle Person delay, out-of- direction travel Transit Negligible effect Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Include pedestrian volume. Pedestrian Vehicle-pedestrian conflict frequency Bicycle Vehicle-bicycle conflicts Transit Negligible effect Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study will be used with a database consisting of many corridors that collectively have a range in the number of consolidated driveways. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype corridors that collectively have a range in the number of driveways that have been consolidated. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 94. Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed used for the operations data will also be used to acquire the safety data. Some investigation of the literature will be

172 needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for these volumes. This second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 94. These performance measures will be obtained from the aforementioned data sources. Technique: 5b. Channelize Driveways to Discourage or Prohibit Left Turns Modal Focus The results of the literature review indicate that the only quantitative information currently available for evaluating this technique has to do with its effect on bicycle safety. Therefore, this study design is focused on the operational effects of this technique on the pedestrian, bicycle, transit, and truck travel modes, and on the safety effects of this technique on the pedestrian, transit, and truck modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. Key elements of the proposed study design are presented in Table 95. The study design will likely produce a relationship that describes the change in safety or operations when a driveway is channelized to discourage or prohibit left-turn movements. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of driveway channelization.

173 Table 95. Study design for channelizing driveways to discourage or prohibit left turns. Technique: Channelizing Driveways to Discourage or Prohibit Left Turns Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations X Field Simulation number of major street lanes, width of major street lanes, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Exclude bicycle volume. Pedestrian Vehicle-pedestrian conflicts Bicycle Existing relationship Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A cross-sectional study method will be used. A number of driveways will be identified that collectively include and exclude channelization to prohibit all left turns. Operations Data Source Field data will be required to conduct the operational analysis. A number of driveway sites will be identified that collectively include and exclude channelization to prohibit left turns. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 95.

174 Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. A simulation testbed will be established using several prototype unsignalized intersections formed by a public road and one or two driveway approaches. The intersections will allow all traffic movements for the “before” conditions. The intersections in the testbed will reconfigured to prohibit left turn movements for the “after” conditions. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian volume is unlikely to be available or cost- effective to measure so adjacent land use will be used as a surrogate for this volume. This second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 95. These performance measures will be obtained from the aforementioned data sources. Technique: 6b. Locate/Relocate the Intersection of a Parallel Frontage Road and a Crossroad Farther from the Arterial-Crossroad Intersection Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of this technique on the truck travel mode. It is also unavailable for the safety effects of this technique on the pedestrian, bicycle, transit, and truck modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. The study design will likely produce a relationship that describes the change in safety or operations when a crossroad intersection is relocated farther from the interchange. Key elements of the proposed study design are presented in Table 96. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the increased separation distance between the interchange and the nearest crossroad intersection.

175 Table 96. Study design for intersection spacing on interchange crossroad. Technique: Relocate a Frontage/Crossroad Intersection Farther From its Adjacent Arterial/Crossroad Intersection Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of through lanes, signal timing, density of intermediate access points, intersection control, functional classification of cross streets, vehicle volume, turn vehicle percent, speed limit, heavy vehicle percent. Pedestrian Existing relationship Bicycle Existing relationship Transit Existing relationship Truck Average travel speed Safety Field _ Simulation X Crash reports In addition to the variables listed above, pedestrian volume on the main and crossing streets, bicycle volume on the main and crossing streets, transit stop location (near side/far side), transit vehicle occupancy, transit vehicle headway. Pedestrian Vehicle-pedestrian conflicts, vehicle speed Bicycle Vehicle-bicycle conflicts and speed differential Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A cross-sectional study method will be used. A “site” for this study will include the signalized intersection that was relocated, the nearest crossroad-ramp terminal, and the street segment between the intersection and terminal. Operations Data Source The source for truck operations data is simulation. A simulation testbed will be established using several different prototype sites that collectively have a range in distance between the crossroad-ramp terminal and the adjacent signalized intersection. Key independent variables that may influence the effect of this technique on truck operations are listed in Table 96. Safety Data Source Reported crash data will be acquired for a large number of locations that collectively have a range in distance between the crossroad-ramp terminal and the adjacent signalized intersection. These data will then be evaluated to determine if there are sufficient pedestrian-, bicycle-, transit-, and truck-related

176 crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for these volumes. Performance Measures The performance measures for all modes are listed in the last column of Table 96. These performance measures will be obtained from the aforementioned data sources. Technique: B-3-1. Install Median Barrier with No Direct Left-Turn Ingress or Egress Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of this technique on the bicycle, transit, and truck travel modes. It is also unavailable for the safety effects of this technique on the pedestrian, transit, and truck modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships that describe the effect of this technique on the aforementioned travel modes. Key elements of the proposed study design are presented in Table 97. The study design will likely produce a relationship that describes the change in safety or operations when a median barrier is installed to prevent direct left-turn movements. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of this technique.

177 Table 97. Study design for installation of median barrier with no direct left-turn ingress or egress. Technique: Installation of Median Barrier with No Direct Left- Turn Ingress or Egress Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, density of intermediate access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on- street parking, width of on-street parking. Pedestrian Existing relationship Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Exclude bicycle volume. Include pedestrian volume. Pedestrian Vehicle-pedestrian conflicts frequency Bicycle Existing relationship Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of access points will be studied before and after the median opening was reconfigured to prohibit left turns. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype intersections with full median openings to represent the “before” condition. To represent the “after” condition, these median openings will be changed in the testbed to prohibit left turns. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 97.

178 Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed assembled for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian volume is unlikely to be available or cost- effective to measure so adjacent land use will be used as a surrogate for this volume. However, this second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 97. These performance measures will be obtained from the aforementioned data sources. Technique: B-4-6. Move the Sidewalk-Driveway Crossing Laterally Away from the Roadway Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 98. The study design will likely produce a relationship that describes the change in safety or operations when the sidewalk crossing of a driveway is moved farther away from the roadway. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the increasing the lateral offset between the roadway and sidewalk at a driveway.

179 Table 98. Study design for moving the sidewalk crossing of a driveway away from the roadway. Technique: Move the Sidewalk Crossing of a Driveway Farther Away from the Roadway Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations X Field Simulation number of lanes, width of lanes, width of sidewalk, abutting land use, area type, upstream/downstream intersection control, distance to upstream/downstream intersections, signal timing, functional classification of major street, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay, out-of- direction travel Bicycle Person delay Transit Person delay Truck Delay Safety X Field Simulation Crash reports Same as above. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A cross-sectional study method will be used. A number of driveway locations will be studied that include a range of distances between the sidewalk and the roadway. Operations Data Source It will be necessary to collect field data in order to evaluate the operational effects of this access management technique. A number of driveway sites that include a range of distances separating the sidewalk from the roadway will be examined with respect to operational performance characteristics. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 98.

180 Safety Data Source It will be necessary to collect field data in order to evaluate the safety effects of this access management technique. The same sites used for the operations data source will also be used as the safety data source, and in this case the sites will be examined with respect to their safety performance characteristics. Key independent variables that may influence the effects of this access management technique on safety are listed in Table 98. Performance Measures The performance measures are listed in the last column of Table 98. These performance measures will be obtained from the aforementioned data sources. Technique: B-5-2-2. Require Access on Collector Street in Lieu of Additional Driveway on Highway Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 99. The study design will likely produce a relationship that describes the change in safety or operations when a collector street provides property access in lieu of the nearby highway. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with relocating access from the highway to the adjacent collector street.

181 Table 99. Study design for requiring access on collector instead of a nearby highway. Technique: Require Access on Collector Street Instead of a Nearby Highway Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes on nearby highway, median type on nearby highway, width of lanes on collector and nearby highway, density of access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of nearby highway, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit on collector and nearby highway, heavy vehicle percent on collector and nearby highway, presence of on-street parking on collector and nearby highway, width of on-street parking. Pedestrian Person delay Bicycle Person delay, out- of-direction travel Transit Person delay Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of sites will be studied before and after the driveway is relocated. A “site” for this study includes the driveway that is located on the major street and the driveway after it is relocated on the collector street. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype sites that have driveways only on the major street to represent the “before” condition. The driveway will be relocated to the collector street in the testbed to represent the “after” condition. Key

182 independent variables that may influence the effects of this access management technique on operations are listed in Table 99. Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed assembled for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. However, this second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 99. These performance measures will be obtained from the aforementioned data sources. Technique: B-5-2-3. Relocate or Reorient Access Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 100. The study design will likely produce a relationship that describes the change in safety or operations when an access point is relocated or reoriented. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the access point relocation or reorientation.

183 Table 100. Study design for relocation or reorientation of an access point. Technique: Relocation or Reorientation of an Access Drive Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes, width of lanes, median type, distance to nearest upstream/downstream access point, density of intermediate access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and upstream/downstream cross streets, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay Bicycle Person delay, out-of- direction travel Transit Person delay, out-of- direction travel Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of street segments will be studied before and after the access point is relocated or reoriented. Operations Data Source The source for operations data is simulation. A simulation testbed will be established using several different prototype street segments with one or more access points to represent the “before” condition. To represent the “after” condition, the access points will be relocated or reoriented in the testbed. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 100.

184 Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed assembled for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. However, this second-choice option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in the last column of Table 100. These performance measures will be obtained from the aforementioned data sources. Technique: B-6-8. Replace Curb Parking with Off-Street Parking Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of this technique on trucks. Additionally, information is unavailable for the safety effects of this technique on the pedestrian, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for trucks; and safety performance relationships for the pedestrian, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 101. The study design will likely produce a relationship that describes the change in safety or operations when on-street parking is replaced with off-street parking. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the removal of on-street parking.

185 Table 101. Study design for removing curb parking. Technique: Replacing Curb Parking with Off-Street Parking Analysis Scale: X Corridor Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Segment length, number of lanes, width of lanes, median type, density of intermediate access points, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street, vehicle volume, turn vehicle percent, speed limit, heavy vehicle percent, number of curb parking spaces, width of curb parking spaces. Pedestrian Existing relationship Bicycle Existing relationship Transit Existing relationship Truck Average travel speed Safety Field Simulation X Crash reports In addition to the variables listed above, transit vehicle headway, transit stop location (near side/far side), pedestrian and transit volume, transit vehicle occupancy. Pedestrian Vehicle-pedestrian crashes Bicycle Existing relationship Transit Transit-involved crashes Truck Truck-involved crashes Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study method will be used with a database consisting of many corridors that collectively have no curb parking, some curb parking, and full curb parking. Operations Data Source The source for truck operations data is simulation. A simulation testbed will be established using several different prototype corridors with a range in the proportion of the street with curb parking. Key independent variables that may influence the effects of this access management technique on truck operations are listed in Table 101. Safety Data Source Reported crash data will need to be acquired for a large number of corridors. The corridors included in the database will be those that have undergone in the recent past a change in the proportion of the street having curb parking. The crash data will be evaluated to determine if there are sufficient mode-specific

186 crashes to quantify a performance relationship. Pedestrian volume is unlikely to be available or cost- effective to measure so adjacent land use will be used as a surrogate for this volume. Performance Measures The performance measures are listed in the last column of Table 101. These performance measures will be obtained from the aforementioned data sources. Technique: B-6-10. Install Roundabout Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational effects of a roundabout on trucks. Quantitative information is also currently unavailable for the safety effects of a roundabout on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the truck travel mode; and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 102. The study design will likely produce a relationship that describes the change in safety or operations when a roundabout is installed at an existing traditionally configured intersection. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a roundabout.

187 Table 102. Study design for installation of a roundabout. Technique: Installation of a Roundabout Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes, width of lanes, upstream/downstream median type, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street and cross street, turn vehicle percent, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Existing relationship Bicycle Existing relationship Transit Existing relationship Truck Delay, out-of- direction travel Safety Field X Simulation Crash reports Same as above. Include pedestrian, bicycle, and transit volume; transit vehicle headway, transit stop location (near side/far side); transit vehicle occupancy. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A. The study design is focused on the unshaded modes. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A before–after study method will be used. A number of intersections will be studied before and after the roundabout is installed. Operations Data Source The source for truck operations data is simulation. A simulation testbed will be established using several different prototype intersections having a traditional configuration to represent the “before” condition. To represent the “after” condition, these intersections will be changed in the testbed to a roundabout. Key independent variables that may influence the effects of this access management technique on truck operations are listed in Table 102. Safety Data Source Simulation-based conflicts will be the first-choice source for safety data. The same testbed assembled for the operations data will be used to acquire the safety data. Some investigation of the literature will be needed to assess the strength of the connection between the conflict measures obtained from the

188 simulation and crash frequency or severity. If a strong connection is not identified in the literature, then some project resources may be needed to establish the relationship using crash data. As a second choice, crash data may be acquired for a large number of locations where this technique has been applied. These data will then be evaluated to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian and bicycle volume are unlikely to be available or cost-effective to measure so adjacent land use will be used as a surrogate for these volumes. As a third choice, conflict data may be acquired for a reasonable number of roundabouts in urban areas. These data will then be compared to conflict data for traditional intersection forms to determine if there are sufficient mode-specific crashes to quantify a performance relationship. Pedestrian and bicycle volume will be obtained concurrently with the conflict data. Performance Measures The performance measures are listed in the last column of Table 102. These performance measures will be obtained from the aforementioned data sources. Technique: B-7-11. Improve Driveway Sight Distance or Regulate Minimum Sight Distance Modal Focus The results of the literature review indicate that quantitative information is currently unavailable for the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian, bicycle, transit, and truck travel modes. Key elements of the proposed study design are presented in Table 103. The study design will likely produce a relationship that describes the change in safety or operations when an improvement is made to increase driveway sight distance. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the increase in driveway sight distance.

189 Table 103. Study design for improve driveway sight distance. Technique: Improve Driveway Sight Distance Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations X Field Simulation Number of approach lanes, width of lanes, width and lateral location of sidewalk, median type, abutting land use, area type, upstream/downstream intersection control, signal timing, functional classification of major street, transit vehicle headway, transit stop location (near side/far side), pedestrian, bicycle, transit, and vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, presence of on-street parking, width of on-street parking. Pedestrian Person delay Bicycle Person delay Transit Person delay Truck Delay Safety X Field Simulation Crash reports Same as above. Pedestrian Vehicle-pedestrian conflicts Bicycle Vehicle-bicycle conflicts Transit Transit-involved conflicts Truck Truck-involved conflicts Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” A cross-sectional study method will be used. A number of driveways will be identified that collectively possess a range of sight distances. Some sites in the database will need to be considered to have “limited” sight distance based on the prevailing speed on the roadway. Operations Data Source Field data will be necessary to evaluate operations. A number of driveway sites that collectively include a range of sight distances will be identified and studied with respect to their operational performance characteristics. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 103.

190 Safety Data Source Field data will also be necessary to evaluate safety. The same sites used for the operations data source will also be used as the safety data source. Key independent variables that may influence the effects of this access management technique on safety are listed in Table 103. Performance Measures The performance measures are listed in the last column of Table 103. These performance measures will be obtained from the aforementioned data sources. Study Designs for Supplemental Techniques Technique: Install Driveways with the Appropriate Return Radii, Throat Width, and Throat Length Modal Focus The results of the literature review indicate that quantitative information is not available to describe the operational and safety effects of this technique on the pedestrian and bicycle modes. There is some qualitative information available describing the technique’s operational effects on these modes. There is also some qualitative information available on the technique’s safety effects on the pedestrian and bicycle modes. The panel has indicated that research on the transit and truck modes for this technique are low priority. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for the pedestrian and bicycle travel modes. Key elements of the proposed study design are presented in Table 104. The study will likely produce relationships that describe the change in safety or operations associated with different driveway widths and right-turn radii. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. The sites selected for study will be located on streets that do not provide on-street parking. They will have adequate driveway sight distance. The sites will also be located in cities that are known to have either (1) reasonably complete records of vehicle-pedestrian and vehicle-bicycle crashes, or (2) a formal relationship with local hospitals and trauma centers for the purpose of sharing patient information that describe pedestrian and bicycle crash events.

191 Table 104. Study design for driveway design. Technique: Install Driveways with the Appropriate Return Radii, Throat Width, and Throat Length Analysis Scale: _ Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations X Field _ Simulation Through lanes on the main street, bike lane presence and width, speed limit, motorized vehicle volume, truck volume, transit volume, pedestrian volume, bicycle volume, angle of intersection, driveway inbound lanes and width, driveway outbound lanes and width, driveway median presence and width, throat length, driveway vertical grade, driveway return radii or angle, presence and length of main right-turn lane, presence and area of island channelization for right turn, offset to sidewalk Pedestrian Person delay, stops Bicycle Person delay, stops Transit not applicable Truck not applicable Safety Field _ Simulation X Crash reports Same as above Pedestrian Vehicle-pedestrian crashes Bicycle Vehicle-bicycle crashes Transit not applicable Truck not applicable Study Method: Cross-sectional Note: The study design is focused on the unshaded modes. Analysis Scale This technique is applied at individual driveways, so the analysis scale is “site.” A cross-sectional study method will be used with a database consisting of many sites that collectively have a range of driveway widths and right-turn radii. Operations Data Source Field data will be necessary to evaluate operations. A number of driveway sites that collectively include a range of right-turn radius and throat width will be identified and studied with respect to their operational performance characteristics. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 104. Safety Data Source Reported crash data will be acquired for a large number of driveways that collectively have a range of right-turn radius and throat width. These data will then be evaluated to determine if there are sufficient

192 pedestrian-related and bicycle-related crashes to quantify a performance relationship. This option may require a relatively large amount of project resources. Performance Measures The performance measures are listed in Table 104. These performance measures will be obtained from the aforementioned data sources. Technique: TWLTL vs. Restrictive (Non-Traversable) Median Modal Focus This technique is focused on the operational and safety effects of non-traversable medians (NTM) and two-way left-turn lanes (TWLTLs). The results of the literature review indicate that quantitative information is currently unavailable for the operational effect of NTM or TWLTL presence on the bicycle and truck travel modes; and it is also unavailable for the safety effects of NTM or TWLTL presence on the transit, and truck travel modes. As a result, this study design is focused on these modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations performance relationships for the bicycle and truck travel modes, and safety performance relationships for the transit and truck travel modes. Safety performance relationships for the pedestrian and bicycle modes will be developed from information found in the literature. Key elements of the proposed study design are presented in Table 105.

193 Table 105. Study design for TWLTL vs. non-traversable median. Technique: TWLTL vs. Non-Traversable Median Analysis Scale: X Corridor _ Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of lanes, lane and shoulder width, density of intermediate access points, intersection control, functional classification of major street, vehicle volume, bicycle volume, turn vehicle percent, speed limit, heavy vehicle percent, median type, presence of on- street parking, width of on- street parking, area type. Pedestrian Existing relationship Bicycle Average travel speed Transit Existing relationship Truck Average travel speed Safety Field Simulation X Crash reports Same as above. Include transit vehicle occupancy transit vehicle headway, transit stop location (near side/far side). Exclude bicycle volume. Pedestrian Existing relationship Bicycle Existing relationship Transit Transit-involved crashes Truck Truck-involved crashes Study Method: Cross-sectional Note: shaded cells in the Performance Measures column identify travel modes for which either quantitative performance relationships exist in the literature or the effect of the technique is unlikely or negligible. Existing relationships are documented in Appendix A for Techniques 2a & 2b, and 3c. Note: The study design is focused on the unshaded modes. The study design will likely produce a relationship that describes the change in safety or operations when a non-traversable median is installed. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in the identified operations performance measures associated with the installation of a non-traversable median. Analysis Scale The subject technique is applied along a corridor, meaning the analysis scale is “corridor.” A cross- sectional study method will be used with a database consisting of several urban street corridors. Some of the streets will have a non-traversable median and others will have a TWLTL. Operations Data Source It is likely that travelers will be compliant with the installed form of median treatment, so the source for operations data is simulation. A simulation testbed will be established using several different prototype corridors that have either a TWLTL or a non-traversable median. Key independent variables that may influence the effects of this access management technique on operations are listed in Table 105.

194 Safety Data Source Reported crashes will be the source for safety data. A number of corridors will be studied that have either a TWLTL or a non-traversable median. These data will then be evaluated to determine if there are sufficient transit- and truck-related crashes to quantify a performance relationship. Reported vehicle- pedestrian and bicycle-pedestrian crash data will also be acquired and used to validate the safety performance relationships developed from information found in the literature. Performance Measures The performance measures are listed in the last column of Table 105. These performance measures will be obtained from the aforementioned data sources. Technique: 1c. Establish Corner Clearance Criteria (revised) Modal Focus The results of the literature review indicate that quantitative information is not available to describe the operational and safety effects of this technique on the pedestrian, bicycle, transit, and truck travel modes. As a result, this study design is focused on the development of operations and safety relationships for all four modes. Study Objectives, Method, Scope, and Output Results The objective of this study is to develop operations and safety performance relationships for transit and trucks. Key elements of the proposed study design are presented in Table 106. The study design will likely produce a relationship that describes the change in safety or operations as corner clearance distances are adjusted. The safety relationships are likely to be described as crash modification factors (or crash modification functions). A similar type of factor or function may be produced using the operations data. This factor or function will describe the change in identified operations performance measures associated with the use of different corner clearance distances. Analysis Scale The subject technique is applied at an intersection, meaning the analysis scale is “site-specific.” Even so, it is expected that success will be most easily achieved by investigating a cross-sectional database consisting of many intersections configured with varying corner clearances.

195 Table 106. Study design for corner clearance (revised). Technique: Establish Corner Clearance Criteria Analysis Scale: Corridor X Site-specific Performance Measure Category Data Source Key Independent Variables Travel Mode Performance Measures Operations Field X Simulation Number of through lanes, intersection control, functional classification of main street, transit vehicle headway, transit stop location (near side/far side), vehicle volume, turn vehicle percent, transit vehicle occupancy, speed limit, heavy vehicle percent, distance between signalized intersection and access point, median type Pedestrian Person delay, pedestrian space Bicycle Person delay Transit Person delay Truck Delay, curb encroachments Safety Field _ Simulation X Crash reports Same as above. Pedestrian Vehicle-pedestrian crashes Bicycle Vehicle-bicycle crashes Transit Transit-involved crashes Truck Truck-involved crashes Study Method: Cross-sectional Operations Data Source It is likely that transit and truck drivers will be responsive to the corner clearances embedded into the configuration of each intersection, so the source for operations data is simulation. A simulation testbed will be established using several different signalize intersection configurations and a range of distances to the nearest access point. Key independent variables that may influence the effect of corner clearance on operations performance measures are listed in Table 106. Safety Data Source Reported crashes will be the source for safety data. These data will be collected for a large number of locations with varying corner clearances. These data will then be evaluated to determine if there are sufficient transit- and truck-related crashes to quantify a relationship between crash frequency and corner clearance distance. Performance Measures The performance measures for the transit and truck travel modes are listed in the last column of Table 106. These performance measures will be obtained from the aforementioned data sources.

Next: Appendix E: Final Study Designs »
Assessing Interactions Between Access Management Treatments and Multimodal Users Get This Book
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TRB’s National Cooperative Highway Research Program (NCHRP) Web-Only Document 256: Assessing Interactions Between Access Management Treatments and Multimodal Users describes operational and safety relationships between access management techniques and the automobile, pedestrian, bicycle, public transit, and truck modes. This contractor's report may help assist in the selection of alternative access management techniques based on the safety and operation performance of each affected travel mode.The roadway system must accommodate many types of users—bicyclists, passenger cars, pedestrians, transit, and trucks. This report examines the interactions between multimodal operations and access management techniques and treatments, and the trade-off decisions that are necessary.

NCHRP Research Report 900: Guide for the Analysis of Multimodal Corridor Access Management accompanies this report.

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