Philadelphia, PA--NJ--DE--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 Philadelphia, PA--NJ--DE--MD Urbanized Area covers parts of Delaware, Maryland, New Jersey, and Pennsylvania. 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 13.1 -- -- -- -- Targets -- -- 15.2 -- 15.1
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
(Delaware) The Congestion Mitigation Air Quality Program traffic congestion measure considers excessive traffic congestion and the role it plays in pollutant emissions. The goal for all partner agencies was to address the need to appropriately manage traffic congestion. The "excessive" part of the PHED measure indicates that some level of congestion is recognized as acceptable and is thus not counted. This corresponds to the recognition that it is not possible or even desirable to eliminate all congestion delay; some congestion accompanies economic activity and thriving places. This is a measure of congestion on all roadways on the National Highway System (NHS), which includes the Interstate Highway system and most principal arterials or greater functional class in the urbanized area. The measure indicates traffic delay experienced by travelers throughout an entire year on roadways, specifically during peak periods defined as weekdays from 6 am to 10 am and partner agencies agreed on the afternoon peak period from 3 pm to 7 pm, rather than 4 pm to 8 pm. Excessive delay means the extra amount of time spent in congested conditions that are lower than the speed threshold, which is defined as 20 miles per hour (mph) or 60 percent of the posted speed limit, whichever is greater. Travel times in this measure are derived from the National Performance Management Research Data Set (NPMRDSv2 & v3), based on archived probe-based traffic data. Traffic volumes and vehicle mix (cars, buses, and trucks) are from the national Highway Performance Monitoring System (HPMS). Vehicle occupancies (cars - 1.7, buses - 13.3, and trucks - 1.0) and time-of-day travel distributions are from national survey data and established estimation formulas. The Probe Data Analytics (PDA) Suite Map-21 tools were used to process this data and calculate the PHED measure. The NPMRDS data is fairly new and imperfect, but the best source available and approved for use. It is appropriate to consider the analysis for this measure to be also considered a benchmark. Targets were established in part based on past performance of the annual hours of PHED per capita measure. The performance in 2019 was 14.6, and then dropped sharply in 2020 to 7.3 due in large part to impacts from COVID-19, and then increased in 2021 to 13.1. The baseline year is 2021 and the required 2-year and 4-year targets are 15.2 and 15.1, respectively. The four-year target is one-tenth of an hour per capita less than the two-year target in anticipation of future projects contributing to some overall reductions in excessive delay. Additional factors considered in establishing the targets were past population, employment, transit ridership and vehicle miles traveled trends; DVRPC travel demand model traffic, population and employment forecasts; and best available information on future travel patterns based on percentage of people that might work from home, take transit, and drive alone. With economic growth, increases in the number of people traveling and the movement of freight on the NHS would likely result in increases in delay. This would only be partially balanced by population growth reflected in the “per capita” portion of the measure. Also, consideration was given to anticipated "state of good repair" and Infrastructure Investment and Jobs Act projects that might slow traffic due to work zones, and to continued growth in e-commerce that may contribute to some excessive delay. There were numerous projects identified in the state Transportation Improvement Program (TIPs) in the urbanized area that are anticipated to reduce some excessive delay and might "move the needle" on the measure.
(Maryland) The Congestion Mitigation Air Quality Program traffic congestion measure considers excessive traffic congestion and the role it plays in pollutant emissions. The goal for all partner agencies was to address the need to appropriately manage traffic congestion. The "excessive" part of the PHED measure indicates that some level of congestion is recognized as acceptable and is thus not counted. This corresponds to the recognition that it is not possible or even desirable to eliminate all congestion delay; some congestion accompanies economic activity and thriving places. This is a measure of congestion on all roadways on the National Highway System (NHS), which includes the Interstate Highway system and most principal arterials or greater functional class in the urbanized area. The measure indicates traffic delay experienced by travelers throughout an entire year on roadways, specifically during peak periods defined as weekdays from 6 am to 10 am and partner agencies agreed on the afternoon peak period from 3 pm to 7 pm, rather than 4 pm to 8 pm. Excessive delay means the extra amount of time spent in congested conditions that are lower than the speed threshold, which is defined as 20 miles per hour (mph) or 60 percent of the posted speed limit, whichever is greater. Travel times in this measure are derived from the National Performance Management Research Data Set (NPMRDSv2 & v3), based on archived probe-based traffic data. Traffic volumes and vehicle mix (cars, buses, and trucks) are from the national Highway Performance Monitoring System (HPMS). Vehicle occupancies (cars - 1.7, buses - 13.3, and trucks - 1.0) and time-of-day travel distributions are from national survey data and established estimation formulas. The Probe Data Analytics (PDA) Suite Map-21 tools were used to process this data and calculate the PHED measure. The NPMRDS data is fairly new and imperfect, but the best source available and approved for use. It is appropriate to consider the analysis for this measure to be also considered a benchmark. Targets were established in part based on past performance of the annual hours of PHED per capita measure. The performance in 2019 was 14.6, and then dropped sharply in 2020 to 7.3 due in large part to impacts from COVID-19, and then increased in 2021 to 13.1. The baseline year is 2021 and the required 2-year and 4-year targets are 15.2 and 15.1, respectively. The four-year target is one-tenth of an hour per capita less than the two-year target in anticipation of future projects contributing to some overall reductions in excessive delay. Additional factors considered in establishing the targets were past population, employment, transit ridership and vehicle miles traveled trends; DVRPC travel demand model traffic, population and employment forecasts; and best available information on future travel patterns based on percentage of people that might work from home, take transit, and drive alone. With economic growth, increases in the number of people traveling and the movement of freight on the NHS would likely result in increases in delay. This would only be partially balanced by population growth reflected in the “per capita” portion of the measure. Also, consideration was given to anticipated "state of good repair" and Infrastructure Investment and Jobs Act projects that might slow traffic due to work zones, and to continued growth in e-commerce that may contribute to some excessive delay. There were numerous projects identified in the state Transportation Improvement Program (TIPs) in the urbanized area that are anticipated to reduce some excessive delay and might "move the needle" on the measure.
(New Jersey) The Congestion Mitigation Air Quality Program traffic congestion measure considers excessive traffic congestion and the role it plays in pollutant emissions. The goal for all partner agencies was to address the need to appropriately manage traffic congestion. The "excessive" part of the PHED measure indicates that some level of congestion is recognized as acceptable and is thus not counted. This corresponds to the recognition that it is not possible or even desirable to eliminate all congestion delay; some congestion accompanies economic activity and thriving places. This is a measure of congestion on all roadways on the National Highway System (NHS), which includes the Interstate Highway system and most principal arterials or greater functional class in the urbanized area. The measure indicates traffic delay experienced by travelers throughout an entire year on roadways, specifically during peak periods defined as weekdays from 6 am to 10 am and partner agencies agreed on the afternoon peak period from 3 pm to 7 pm, rather than 4 pm to 8 pm. Excessive delay means the extra amount of time spent in congested conditions that are lower than the speed threshold, which is defined as 20 miles per hour (mph) or 60 percent of the posted speed limit, whichever is greater. Travel times in this measure are derived from the National Performance Management Research Data Set (NPMRDSv2 & v3), based on archived probe-based traffic data. Traffic volumes and vehicle mix (cars, buses, and trucks) are from the national Highway Performance Monitoring System (HPMS). Vehicle occupancies (cars - 1.7, buses - 13.3, and trucks - 1.0) and time-of-day travel distributions are from national survey data and established estimation formulas. The Probe Data Analytics (PDA) Suite Map-21 tools were used to process this data and calculate the PHED measure. The NPMRDS data is fairly new and imperfect, but the best source available and approved for use. It is appropriate to consider the analysis for this measure to be also considered a benchmark. Targets were established in part based on past performance of the annual hours of PHED per capita measure. The performance in 2019 was 14.6, and then dropped sharply in 2020 to 7.3 due in large part to impacts from COVID-19, and then increased in 2021 to 13.1. The baseline year is 2021 and the required 2-year and 4-year targets are 15.2 and 15.1, respectively. The four-year target is one-tenth of an hour per capita less than the two-year target in anticipation of future projects contributing to some overall reductions in excessive delay. Additional factors considered in establishing the targets were past population, employment, transit ridership and vehicle miles traveled trends; DVRPC travel demand model traffic, population and employment forecasts; and best available information on future travel patterns based on percentage of people that might work from home, take transit, and drive alone. With economic growth, increases in the number of people traveling and the movement of freight on the NHS would likely result in increases in delay. This would only be partially balanced by population growth reflected in the “per capita” portion of the measure. Also, consideration was given to anticipated "state of good repair" and Infrastructure Investment and Jobs Act projects that might slow traffic due to work zones, and to continued growth in e-commerce that may contribute to some excessive delay. There were numerous projects identified in the state Transportation Improvement Program (TIPs) in the urbanized area that are anticipated to reduce some excessive delay and might "move the needle" on the measure.
(Pennsylvania) The two- and four-year targets were established based on various considerations. While COVID-19 cases are declining and workers that previously took transit are returning to the office and using public transit, some will likely switch modes and drive alone for health reasons, contributing to excessive delay. The four-year target is one-tenth of an hour per capita less than the two-year target in anticipation of future projects contributing to some overall reductions in excessive delay. With economic growth, increases in the number of people traveling, and the movement of freight on the NHS would likely result in increases in delay. This would only be partially offset by population growth reflected in the “per capita” portion of the measure. Also, consideration was given to IIJA and “State of Good Repair” projects that will slow down traffic during construction, and to continued growth in e-commerce that may contribute to delays. Numerous projects in the PA TIP (FY2023-2026) were identified that could help reduce excessive delay.
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Data Sources:
2022 Biennial Performance Report
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 30.6 -- -- -- -- Targets -- -- 30.0 -- 30.0
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
(Delaware) Non-Single Occupant Vehicle (SOV) travel includes carpool, train, bus, walk, bike, taxi, rideshare, working at home, etc.; anything other than driving alone. Percent non-SOV travel for the urbanized area is calculated using U.S. Census American Community Survey data about journey-to-work trips for residents of the urbanized area. While all trips (not just journey-to-work) would be ideal to track, this regularly updated, approved dataset is recognized as the best available. The data reflects five-year averages, with a time lag. Thus, the baseline refers to 2016-2020 values, the 2-year target to 2018- 2022 values, and the 4-year target to 2020-2024 values. Goals of all partner agencies reflect strong support for increasing non-SOV travel modes, including public transit, ridesharing, walking and biking. Targets were established in part based on past performance of the journey to work U.S. Census ACS 5-year estimates of percent Non-SOV travel and trending through the performance period. There was a slight increase in percent non-SOV travel from 2010 through 2019 and then a more substantial increase in 2020 due in large part to increases in people working from home as a result of COVID. Other factors considered were past population, employment, and transit ridership trends, and best available information on future travel patterns based on percentage of workers that might work from home, take transit, and drive alone. Future projects that were anticipated to be completed in the performance period that might "move the needle" on the measures were considered, such as various transit station improvements and transit service line extensions that could increase Non-SOV travel. Based on these considerations, the Philadelphia Urbanized Area MPO and State DOT partners agreed on a slight decrease from the baseline of 30.6, with 2-year and 4-year targets both at 30.0 percent.
(Maryland) Non-Single Occupant Vehicle (SOV) travel includes carpool, train, bus, walk, bike, taxi, rideshare, working at home, etc.; anything other than driving alone. Percent non-SOV travel for the urbanized area is calculated using U.S. Census American Community Survey data about journey-to-work trips for residents of the urbanized area. While all trips (not just journey-to-work) would be ideal to track, this regularly updated, approved dataset is recognized as the best available. The data reflects five-year averages, with a time lag. Thus, the baseline refers to 2016-2020 values, the 2-year target to 2018- 2022 values, and the 4-year target to 2020-2024 values. Goals of all partner agencies reflect strong support for increasing non-SOV travel modes, including public transit, ridesharing, walking and biking. Targets were established in part based on past performance of the journey to work U.S. Census ACS 5-year estimates of percent Non-SOV travel and trending through the performance period. There was a slight increase in percent non-SOV travel from 2010 through 2019 and then a more substantial increase in 2020 due in large part to increases in people working from home as a result of COVID. Other factors considered were past population, employment, and transit ridership trends, and best available information on future travel patterns based on percentage of workers that might work from home, take transit, and drive alone. Future projects that were anticipated to be completed in the performance period that might "move the needle" on the measures were considered, such as various transit station improvements and transit service line extensions that could increase Non-SOV travel. Based on these considerations, the Philadelphia Urbanized Area MPO and State DOT partners agreed on a slight decrease from the baseline of 30.6, with 2-year and 4-year targets both at 30.0 percent.
(New Jersey) - Non-Single Occupant Vehicle (SOV) travel includes carpool, train, bus, walk, bike, taxi, rideshare, working at home, etc.; anything other than driving alone. Percent non-SOV travel for the urbanized area is calculated using U.S. Census American Community Survey data about journey-to-work trips for residents of the urbanized area. While all trips (not just journey-to-work) would be ideal to track, this regularly updated, approved dataset is recognized as the best available. The data reflects five-year averages, with a time lag. Thus, the baseline refers to 2016-2020 values, the 2-year target to 2018- 2022 values, and the 4-year target to 2020-2024 values. Goals of all partner agencies reflect strong support for increasing non-SOV travel modes, including public transit, ridesharing, walking and biking. Targets were established in part based on past performance of the journey to work U.S. Census ACS 5-year estimates of percent Non-SOV travel and trending through the performance period. There was a slight increase in percent non-SOV travel from 2010 through 2019 and then a more substantial increase in 2020 due in large part to increases in people working from home as a result of COVID. Other factors considered were past population, employment, and transit ridership trends, and best available information on future travel patterns based on percentage of workers that might work from home, take transit, and drive alone. Future projects that were anticipated to be completed in the performance period that might "move the needle" on the measures were considered, such as various transit station improvements and transit service line extensions that could increase Non-SOV travel. Based on these considerations, the Philadelphia Urbanized Area MPO and State DOT partners agreed on a slight decrease from the baseline of 30.6, with 2-year and 4-year targets both at 30.0 percent.
(Pennsylvania) The two- and four-year targets were established based on various considerations. The measure shows a slight trend increase from the five-year ACS (2006–2010) to five-year ACS (2015–2019), and then a more substantial increase in five-year ACS (2016-2020) due in large part to increases in people working from home due to COVID-19. While workers are returning to the office closer to 2019 levels, some that drove alone will likely continue to work from home, increasing percent Non-SOV travel. People will likely go back taking transit and carpooling closer to 2019 levels, but some will likely shift modes and drive alone leading to reductions in in percent Non-SOV travel. The PA TIP (FY2023-2026) includes the Ardmore Transportation Center and Exton Station improvement projects and the new service extension project from Elwyn to Middletown in Delaware County, which could contribute to increasing Non-SOV travel.
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Data Sources:
2022 Biennial Performance Report
2022 HPMS Data Submittal