Incorporating Reliability Performance Measures into the Transportation Planning and Programming Processes: Technical Reference (2014) / Chapter Skim
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From page 138... ...
137 D BENEFITS AND COSTS OF FULL OPERATIONS AND ITS DEPLOYMENT: TECHNICAL APPENDIX D.1 BACKGROUND This technical appendix provides a general overview of the methodology used in the study of the potential benefits of fully deploying operations and ITS strategies. This study was initiated by the U.S.
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138 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE The analysis methodology used in this study was developed to identify the incremental benefits and costs of the strategies contained in the full operations and ITS deployment scenario. To identify these incremental impacts, it was necessary to estimate what travel conditions would be in the full operations and ITS deployment scenario, as compared with a scenario that did not contain any operations and ITS deployments.
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139 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Annual Benefit AMNO AMFull MDNO MDFull PMNO PMFull OPNO OPFull Number of Days per Year∑= − − − − ∗ where AMNo = Performance measure from the AM Peak Period: No Operations and ITS Deployment Scenario, AMFull = Performance measure from the AM Peak Period: Full Operations and ITS Deployment Scenario, MDNo = Performance measure from the Midday Period: No Operations and ITS Deployment Scenario, MDFull = Performance measure from the Midday Period: Full Operations and ITS Deployment Scenario, PMNo = Performance measure from the PM Peak Period: No Operations and ITS Deployment Scenario, PMFull = Performance measure from the PM Peak Period: Full Operations and ITS Deployment Scenario, OPNo = Performance measure from the Off-Peak Period: No Operations and ITS Deployment Scenario, and OPFull = Performance measure from the Off-Peak Period: Full Operations and ITS Deployment Scenario. The value of the annual benefit was then determined by applying the appropriate benefit values from the IDAS tool to the incremental change in the performance measures.
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140 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE The analysis of the impacts of full operations and ITS deployment used the default IDAS procedures, parameters, and impacts, except when noted. These parameters and impact values were held constant in the three case study regions to produce comparable results.
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141 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE sonable representations of the expected effect of the individual deployments. This study, however, includes combinations and intensities of deployment that exceed any that have been tested using this methodology, and it was the opinion of technical reviewers that the initial estimates of the cumulative impact to incident-related delay of all the deployments overstated the potential reduction.
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142 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE demand in these four periods represented approximately 9.3 million daily person trips traveling between 2,999 possible origins and destinations. Approximately 69% of this travel occurs in the Cincinnati region.
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143 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE A second modification to the Seattle model networks was required to allow the analysis of ramp metering strategies. On-ramp facilities are not represented in the current Seattle models.
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144 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Deployment Scenario, which contained the full complement of operations and ITS deployments. Note that for those scenarios that contained the negative impacts of inclement weather or construction activity conditions, the deployment scenario was enhanced by adding either weather or work zone mitigation strategies, or both, as appropriate to the conditions included in the scenario.
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145 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Simulation of Weather Impacts Three different weather situations were considered in this analysis: clear, rain, and snow. Clear weather scenarios were represented using the baseline roadway network from the travel demand model.
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146 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Additional Weather and Work Zone Mitigation Strategies Additional weather and work zone mitigation strategies were deployed and analyzed in the appropriate Full Operations and ITS Deployment Scenarios containing the negative impacts of inclement weather and/or construction activity. These operations and ITS strategies are not currently included as available components for analysis within the IDAS tool.
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147 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Estimating the Annual Impact of the Full ITS Deployment Scenario in Cincinnati Each of the 40 individual scenarios was analyzed separately to estimate the likely traffic conditions that would occur for each given time-of-day period with similar weather, construction activity, and operations and ITS deployment intensity. The results of the individual scenarios were then annualized by applying a weight to each scenario representing how many days that scenario would be anticipated to occur in a typical year.
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148 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE Figure D.1 Proportion of days assumed for annualization. Peak Period – No Operations and ITS Clear, 26% Rain, 10% Ice/Snow, 18% Clear w/ Roadwork, 38% Rain w/ Roadwork, 7% Clear, 20% Rain, 8% Ice/Snow, 18% Clear w/ Roadwork, 45% Rain w/ Roadwork, 8% Clear, 20% Rain, 8% Ice/Snow, 18% Clear w/ Roadwork, 45% Rain w/ Roadwork, 8% Peak Period – Full Operations and ITS Off-Peak Period – Full Operations and ITS Off-Peak Period – No Operations and ITS Clear, 13% Rain, 7% Ice/Snow, 18%Clear w/ Roadwork, 52% Rain w/ Roadwork, 10% TABLE D.4 ANNUALIZATION WEIGHTS FOR CINCINNATI, OHIO Roadwork Weather AM Midday PM Off-Peak No Ops and ITS Full Ops and ITS No Ops and ITS Full Ops and ITS No Ops and ITS Full Ops and ITS No Ops and ITS Full Ops and ITS No Clear 49 66 49 66 49 66 49 32 No Rain 21 24 21 24 21 24 21 18 No Ice/Snow 46 46 46 46 46 46 46 46 Yes Clear 113 96 113 96 113 96 113 130 Yes Rain 21 18 21 18 21 18 21 24 Total 250 250 250 250 250 250 250 250
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149 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE D.6 STUDY CAVEATS As documented in this appendix, the analyses of the three case study regions were conducted using similar but not identical approaches and assumptions. Therefore, comparisons of major trends across the three regions are generally valid.
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150 INCORPORATING RELIABILITY PERFORMANCE MEASURES INTO THE TRANSPORTATION PLANNING AND PROGRAMMING PROCESSES: TECHNICAL REFERENCE In addition to the model differences noted, other factors and parameters internal to the individual region's models may also affect the estimated impacts. Model characteristics such as the length of peak periods, volume-delay functions, and mode choice sensitivity may also promote differences in the analysis results.
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