8.2.1 Analysis Tools and Methods

Typical analysis tools and methods for alternatives analysis include:
  • Sketch-level or macroscopic tools
    : Used for high-level alternatives analysis for general order-of-magnitude estimates of travel demand and traffic operations. Examples are CAP-X and HCM service volume tables.
  • TDM
    : Used for alternatives analysis to compare scenarios or screen alternatives at a high level.
    • TDM outputs are typically used to determine the benefits and impacts of major highway improvements. Common outputs include origin and destination data, route choice, v/c, and vehicle miles traveled. Examples are TransCAD and Cube.
  • Deterministic tools
    : Used in alternatives analysis to quickly determine the LOS (e.g., density, speed, and delay) of isolated or smaller-scale facilities. They are limited in their ability to analyze network or system effects. Examples are Synchro and Highway Capacity Software.
  • Traffic signal optimization tools
    : Used to optimize signal timings for intersections, corridors, or networks. These tools can incorporate items such as intersection capacity, cycle lengths, splits, and signal coordination and offset. They are used to perform alternatives analysis for intersections or interchanges. Examples are Synchro and PASSER.
  • Simulation tools
    : Used to simulate the traffic flows and movement of individual vehicles and pedestrians. These tools produce detailed outputs, need higher levels of effort, and can either be deterministic or stochastic in nature. They are best suited for alternatives analysis that involve oversaturated conditions, complex geometric configurations, and alternative intersections. Examples are Vissim, CORSIM, and DynusT.
  • Safety analysis and tools
    : Safety analysis can be performed in terms of historical crash analysis or predictive safety analysis. Historical crashes (in terms of crash type, frequency and severity, contributing factors) are typically examined to select crash countermeasures in the alternatives analysis. Crash predictive methods can be used to estimate changes in the number of crashes associated with alternatives analysis. CMF are typically used as a multiplicative factor to estimate the expected number of crashes.