Analytical Procedures for Determining the Impacts of Reliability Mitigation Strategies (2012) / Chapter Skim
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154 C h a p t e r 8 Introduction The predictive models that can be used in transportation modeling and analysis applications are of three kinds: 1. Adjustment factors (percentage reduction)
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155 Table 8.1. General Linkages Between Improvements and Model Variables Action to Improve Reliability Effect on Reliability Model Variable Affected Add Capacity Add new through lanes Increases design capacity.
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156 Action to Improve Reliability Effect on Reliability Model Variable Affected Weather Management (continued) Microlevel weather forecasting Reduces impact of weather events on pavement and crashes.
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157 44 Lanes blocked per incident, a function of 4▪ Presence of shoulders, and 4▪ Local policy concerning moving lane-blocking incidents to the shoulder; or • Average incident duration. Improvements or strategies that affect demand are accounted for twice in the model: in the demand-to-capacity (d/c)
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158 research projects currently underway, their results can be adapted to the modeling framework in a similar manner. relationship Between Incident Management efficiency and Model Variables The incident management factors in Table 8.2 relate primarily to the technological (physical)
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159 longer and more trips to be made. Longer trips can result from the location decisions for place of residence and business.
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160 three effects noted above (modal diversion, trip distribution, and trip frequency) , but also route diversion (in which travelers shift the routes they use but do not alter their origins or destinations)
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161 The situation is further clouded because no empirical studies have been done on the induced demand effect of operational treatments. Unlike capacity expansions (the basis of previous elasticity work)
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162 itsbenefits.its.dot.gov/its/benecost.nsf/ID/E4BFDFEF91B742D285 256FB90052C4BB? OpenDocument&Query=Home.
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