Baltimore, MD Urbanized Area Congestion Report
In the line graphs below, FHWA uses Data Collection Year instead of Data Reporting Year to represent snapshot condition/performance at the time the data was collected. More information
The Baltimore, MD Urbanized Area covers parts of Maryland. Targets are agreed upon by several transportation agencies and apply to the entire area.
Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita
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Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita 2021 2022 2023 2024 2025 Condition/Performance 13.9 -- -- -- -- Targets -- -- 14.8 -- 15.7
Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita
- Basis for Targets
- 2-yr Progress
- Basis for 4-yr Target Adjustment
- 4-yr Planned Activities
- 4-yr Progress
(Maryland) For PHED, the targets were developed by using the existing PHED, calculated through the RITIS tool, and then projecting future delay via a linear trend. The year 2020 was omitted from these projections to account for the atypical transportation patterns from the COVID-19 pandemic. An assumption was made that pre-pandemic trends will continue from current performance level. This means the slope of the pre-pandemic trend is shifted to start at observed 2021 levels. 2-Year Target 14.8 hours 4-Year Target 15.7 hours
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Data Sources:
Maryland 2022 Biennial Performance Report
Maryland 2022 HPMS Data Submittal
Non-Single Occupancy Vehicle (Non-SOV) Travel
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Non-Single Occupancy Vehicle (Non-SOV) Travel 2021 2022 2023 2024 2025 Condition/Performance 27.1 -- -- -- -- Targets -- -- 25.3 -- 25.5
Non-Single Occupancy Vehicle (Non-SOV) Travel
- Basis for Targets
- 2-yr Progress
- Basis for 4-yr Target Adjustment
- 4-yr Planned Activities
- 4-yr Progress
(Maryland) For Percent non-SOV travel, the targets were developed by using the existing non-SOV, calculated utilizing ACS 5-year data, and forecasting trend lines for the second performance period. For the Baltimore Urbanized Area, two trend lines were forecasted (1) a long-term trend based on data ranging from 2010 to 2019 and (2) a near-term trend based on data ranging from 2015 to 2019. The average was then taken from the 2- and 4-year data points on these trend lines to develop the 2- and 4-year targets respectively.
This was done because the near-term trend taken alone indicated a slight improvement in performance, but there was uncertainty around how much of the pandemic effects on transit use and work from home will continue. Therefore, the decision was made to also look at longer term trends.
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Data Sources:
Maryland 2022 Biennial Performance Report
Maryland 2022 HPMS Data Submittal