Commuting Cost Calculator

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  • Average 2019 cost per mile for automobile operation as estimated by the American Automobile Association includes fuel, insurance, depreciation, maintenance. :
    $.596
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Travel Demand Forecasting

The region has developed computational tools to predict household, commercial vehicle, and freight travel under a variety of socioeconomic conditions and public policy scenarios. Predictive tools are applied region wide in the development of plans and programs and to calculate the on-road mobile source emissions contribution to Baltimore’s air quality. Member organizations apply the predictive tools in preparing jurisdiction plan’s transportation elements and conducting corridor impact studies.

Trip-Based Model

The region’s aggregate trip-based model supports regional plan development and assists transportation engineers in the design of projects. The trip-based model predicts person travel for home and non-home based purposes in addition to medium and heavy trucks and commercial vehicles based on Traffic Analysis Zones (TAZ) that can be found under the Boundaries group on the Baltimore Regional GIS Data Center. A User’s Guide documents the trip-based model directory and approach.

Synthetic Household and Population Generation

The prediction of every person’s travel activity requires the generation of a household and person roster. The synthetic generation process applies demographic models and the pOPulation Trends: Interpreting Cohort Shifts (pOPTICS) to Cooperative Forecasting Committee demographic forecasts for marginal controls. The synthetic generation process is described in Updates to the BMC Population Synthesis Model: Incorporating Controls at Multiple Geographic Resolutions.

Activity-Based Models

The region has developed the Initiative to Simulate Individual Travel Events (InSITE) model. InSITE predicts each person’s long-term choices, daily activity patterns (DAP) and travel in the region outputting a person’s vehicle choice, work/school location, as well as tour roster containing the sequence of travel and the origin location, departure time, mode, destination location, activity and duration for each trip including joint household activities.

A Model Design Plan reflects identified regional technical needs and a National Panel of Peer Expert’s recommendations. The Maryland Travel Survey was analyzed and documented in the InSITE Model Estimation Report. The InSITE Validation Documentation examines the reasonableness of model results. An InSITE User’s Guide provides information on model setup and application.

Freight Models

The region in partnership with State Highway Administration (SHA) and funding from SHRP2 C20 grant, developed a freight modeling system that predicts a freight/commercial vehicle tour roster representing the sequence of pick-up and drop-off trips for freight and the goods and service calls for commercial vehicles. The Freight and Commercial Vehicle Model Development documents the modeling approach.

Dynamic Traffic Assignment

The region, in partnership with SHA and with funding from SHRP2 C10, is integrating the InSITE model with Dynamic Traffic Assignment (DTA). The enhanced procedure determines the choice of route, time of day, mode and destination with consideration of the effects of congestion, improving the estimation of delay, travel time estimates, as well as the model’s sensitivity to traffic policy scenarios. The Final Report documents the integration method and validation