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Transportation Performance Management

 

New York--Newark, NY--NJ--CT 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 New York--Newark, NY--NJ--CT Urbanized Area covers parts of New Jersey and New York. Targets are agreed upon by several transportation agencies and apply to the entire area.

  • Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita

    • Trend through 2025

      Desired trend: ↓

      New York--Newark, NY--NJ--CT Annual Hours of Excessive Delay Per Capita


  • Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita 2021 2022 2023 2024 2025
    Condition/Performance 20.9 -- -- -- --
    Targets -- -- 22.0 -- 21.0

  • Annual Hours of Peak-Hour Excessive Delay (PHED) Per Capita

    (New Jersey) Note - We appreciate FHWA for correcting the baseline from 20.3 to 20.9. We believe that there was a calculation issue with FHWA's version of the HPMS which did not include eight TMCs in NYC that have PHED metric values of above 1 million in 2021 in calculating the total PHED for the entire UZA. The 2-year 4-year targets have remained the same. The following points are considered in the PHED Target Setting process. • Policy Goals - This performance measure (associated with the federal Congestion Mitigation and Air Quality Program) deals with excessive traffic congestion and the role that it plays in pollutant emissions. - The goals of all partner agencies address the need to appropriately manage traffic congestion. The “excessive” part of the PHED name is because 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. - The “per capita” implies that the total delay is shared by all residents; hence it is considered beneficial for some trips to be avoided or shifted to walking or biking or shifted out of the peak period. • Data - This is a measure of congestion on all roadways on the National Highway System (NHS) (mostly roads that are principal arterials or greater functional class) in the urbanized area. - The measure sums up the delay experienced by travelers throughout an entire year on those roads, specifically during the 6-10 am and 3-7 pm weekday peak periods. - Travel times in this measure are from the National Performance Management Research Data Set (NPRMDS), based on archived probe-based traffic data. Traffic volumes are from the national Highway Performance Monitoring System (HPMS). Vehicle occupancies and time-of-day travel distributions are from national survey data and established estimation formulas. • Trends - The NPMRDS data is new and imperfect but continues to improve over time. However, this makes analysis of PHED trends difficult, as it is difficult to tell changes due to data improvements from changes due to performance changes. - Related measures of congestion and delay have shown pre-pandemic increases. - Previous long-term forecasts of a similar measure suggest modest increases over time, but this modeling was conducted prior to the COVID-19 pandemic.

    (New York) A trend analysis of the UZA levels for the Annual Hours of Peak Hour Delay for 2016 through 2021 was undertaken. As part of the trend analysis a linear trend was developed to estimate values for 2024 and 2026. To account for likely influences to the measure’s values (e.g.., trends in working from home, uncertain direction of the economy), the 2024 and 2026 targets were held constant, at 22.0. As trends further evolve over 2022 and 2023, we will continue to review the values for 2026 as part of the mid-performance period report for 2024.

  • Data Sources:
    2022 Biennial Performance Report
    2022 HPMS Data Submittal

  • Non-Single Occupancy Vehicle (Non-SOV) Travel

    • Trend through 2025

      Desired trend: ↑

      New York--Newark, NY--NJ--CT % Non-SOV Travel


  • Non-Single Occupancy Vehicle (Non-SOV) Travel 2021 2022 2023 2024 2025
    Condition/Performance 52.4 -- -- -- --
    Targets -- -- 52.4 -- 52.5

  • Non-Single Occupancy Vehicle (Non-SOV) Travel

    (New Jersey) The following points are considered in the Non-SOV Target Setting process. • Policy Goals - This performance measure (associated with the federal Congestion Mitigation and Air Quality Program) recognizes the role that single-occupant vehicles play in contributing to traffic congestion and pollutant emissions. - The goals of all partner agencies reflect strong support for non single-occupant modes, including public transit, ridesharing, walking, and biking. • Data - Non-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 5-year 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 surveys collected over a five-year period, with a time lag. Thus, the baseline refers to 2016-2020 values, the 2-year target to 2018-2022, and 4-year target to 2020-2024. • Trends - Percent Non-SOV Travel has modestly increased in recent years (pre-pandemic), associated with factors such as growth in transit ridership. This has accompanied population growth and positive and negative employment changes. - Long term forecasts (plan horizon years) show minimal increases in percent non-SOV travel, but this modeling was conducted prior to the COVID-19 pandemic. - This is a percentage measure. If trip making continues to grow, the absolute number of non-SOV trips would increase even if the percentage stayed the same. - Non-SOV travel during the COVID-19 pandemic increased greatly, largely reflective of commuters working from home. While it is likely that commuting may return to pre-pandemic conditions during this performance period, because the measure includes surveys collected over five years, the value reported at the end of the performance period will be from the 2020-2024 ACS, and thus surveys collected during the height of the pandemic will still be included. • Impacts - Changes are incremental to the five-year reporting periods intrinsic to this measure, and there is a year lag in reporting. Any impacts of agency plans and programs must essentially already be underway to register. - The ability of the existing public transit system to accommodate increased ridership is limited. Expansion of the transit network is limited over the target time frame. - Continued increases in teleworking, ridesharing, transportation network companies (TNCs), walking and biking would contribute to increases for this measure. - Land use, housing locations and work locations will continue to affect trip making and the use of non-SOV modes. - Changes in pricing (e.g., congestion pricing, fuel costs, transit fares) would affect this measure. • Uncertainties - The COVID-19 pandemic has introduced several uncertainties. Will there be long-term changes in travel behaviors, or will the public resume pre-pandemic behaviors at some point? Potential changes that impact peak period excessive delay include increased telecommuting, decreased peak period driving, increased home deliveries of goods and services, and the reluctance to return to public transit. - Global factors also introduce uncertainties. The increase in inflation may alter travel behaviors, particularly increased gas prices. - As mentioned above, New York City may (or may not) implement congestion pricing during this time period. If successful, this may greatly reduce peak period excessive delay in this UZA. - The variability in the trends (including numerous external factors) discussed above means that there is a significant range of likely values for this measure in coming years. • Approach - Based on these considerations, the NYC/NJ MPOs and state DOTs are agreeing that an appropriate 2-year target (for 2023) would maintain the baseline value. The 4-year target represents a very small increase in non-SOV travel, reflecting the policy goal to increase this measure in the long term. - The agencies fully expect to revisit and likely adjust this target in two years as allowed by FHWA.

    (New York) A trend analysis of the UZA levels for the Percent of Non-SOV Travel for 2016 through 2021 was undertaken.

    As part of the trend analysis a linear trend was developed to estimate values for 2024 and 2026. In an effort to account for likely influences to the measure’s values (i.e., trends in working from home, uncertain direction of the economy), and increasing values for the targets were chosen based on anticipated increases to transit and active transportation use.

    NYSDOT and NYMTC will review the target for 2026 as part of the mid-performance period report for 2024.

  • Data Sources:
    2022 Biennial Performance Report
    2022 HPMS Data Submittal

Updated: 01/09/2024
Federal Highway Administration | 1200 New Jersey Avenue, SE | Washington, DC 20590 | 202-366-4000