Measures of effectiveness and performance measures in project-level traffic forecasting
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Measures of effectives (MOEs) are direct outputs of travel models to gauge the amount of travel for an alternative and to understand the alternative’s impacts. Performance measures relate directly to transportation plan objectives and give an indication about whether the plan’s objectives and goals are being attained, once implemented. Performance measures should preferably be calculated from real-world data. It is possible for a travel forecasting model and its post-processors to compute MOEs that resemble performance measures. This section will deal mainly with MOEs. Standard MOEs from travel models include vehicle-hours-travel and vehicle-miles-traveled. These two MOEs may be broken out by functional class and/or by location. Other easily computed MOEs are total hours of delay and average speed. Travel models may also be able to roughly estimate air pollution emissions from vehicles, greenhouse gas emissions, and fuel consumption.
Caution needs to be exercised when interpreting MOEs because travel models do not encompass all possible behavioral responses by travelers. For example, a travel model might suggest that fuel consumption would decline with a lowering of delays at signals. However, if the travel model does not include feedback to the distribution step or if the travel model does not include a land-use component, then offsetting increases in trip length owing to reduced delays at signals would not have been accounted for in the total fuel consumptions estimates.