6 datasets found
  1. a

    New Jersey Annual Average Daily Traffic

    • njogis-newjersey.opendata.arcgis.com
    • hub.arcgis.com
    • +2more
    Updated Mar 23, 2023
    + more versions
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    New Jersey Department of Transportation (2023). New Jersey Annual Average Daily Traffic [Dataset]. https://njogis-newjersey.opendata.arcgis.com/maps/47a9e9abd50b4f7bbc56db38a373cc43
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    Dataset updated
    Mar 23, 2023
    Dataset authored and provided by
    New Jersey Department of Transportation
    Area covered
    Description

    The New Jersey Department of Transportation collects traffic data at over 4300 station locations along all Interstate, U.S. , N.J. and County Routes throughout the State of New Jersey. This map represents the estimated Annual Average Daily Traffic (AADT) values based on the most current station data available. The AADT Flow layer data is displayed in six (6) groups, five (5) representing graduated AADT ranges and one (1) representing no station data. The traffic information is used for planning, design, maintenance and general administration of the roadway systems.

  2. Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ:...

    • data.ny.gov
    • datadiscoverystudio.org
    • +3more
    application/rdfxml +5
    Updated Mar 15, 2016
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    Port Authority of New York and New Jersey (2016). Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ: Beginning 2009 [Dataset]. https://data.ny.gov/Transportation/Freight-Cars-Moved-in-Carfloat-Operations-Port-Aut/hy7n-2fdt
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    csv, xml, application/rssxml, application/rdfxml, json, tsvAvailable download formats
    Dataset updated
    Mar 15, 2016
    Dataset authored and provided by
    Port Authority of New York and New Jerseyhttp://www.panynj.gov/
    Area covered
    New Jersey
    Description

    This dataset provides volume of loaded freight rail cars transported between NY and NJ by New York New Jersey Rail, a carfloat operation owned by the Port Authority of NY & NJ. Total volume, including empty cars, is estimated at twice the volume of loaded. 2013 entry is year-to-date volume at this time

  3. g

    Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ:...

    • gimi9.com
    + more versions
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    Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ: Beginning 2009 | gimi9.com [Dataset]. https://gimi9.com/dataset/data-gov_freight-cars-moved-in-carfloat-operations-port-authority-of-ny-nj-beginning-2009
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    Description

    This dataset provides volume of loaded freight rail cars transported between NY and NJ by New York New Jersey Rail, a carfloat operation owned by the Port Authority of NY & NJ. Total volume, including empty cars, is estimated at twice the volume of loaded. 2013 entry is year-to-date volume at this time

  4. D

    2023 CMP Focus Limited Access Roadway Bottlenecks

    • catalog.dvrpc.org
    • hub.arcgis.com
    • +1more
    esri feature class +4
    Updated Feb 20, 2025
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    DVRPC (2025). 2023 CMP Focus Limited Access Roadway Bottlenecks [Dataset]. https://catalog.dvrpc.org/dataset/2023-cmp-focus-limited-access-roadway-bottlenecks-1
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    xml, json, geojson, esri feature class, htmlAvailable download formats
    Dataset updated
    Feb 20, 2025
    Dataset provided by
    Delaware Valley Regional Planning Commissionhttps://www.dvrpc.org/
    Authors
    DVRPC
    Description

    Focus Limited Access Roadway Bottlenecks contain a road segment on a limited access roadway or approach to a limited access roadway with a high peak hour TTI greater than 1.50 or PTI segment greater than 3.00, and high peak hour vehicle and volume delays. Any trailing adjacent segment with a TTI of 1.40 or more is also included as part of the bottleneck. For each bottleneck, peak travel time vehicle and volume delays are summarized for the immediate bottleneck segment and remaining upstream segments with a TTI of 1.40 or more, or until another bottleneck is encountered.

    There are 145 Focus Limited Access Roadway Bottlenecks identified: 102 in the Pennsylvania subregion and 43 in the New Jersey subregion. These bottlenecks are symbolized by rank in delay from high to low in quartiles separately for the Pennsylvania and New Jersey subregions, with brown locations being the most delayed and yellow the least. Rank is based on travel time vehicle and volume delays.

    CMP Focus Limited Access Roadway Bottleneck Database Fields

    MAPID – Unique map bottleneck identifier by state

    MAPID2 – Unique map bottleneck identifier by DVRPC region; NJ bottlenecks start at identifier 200

    NAME – Names of the intersecting expressways and ramps

    MUNICIPAL – Municipal where intersection exists; for Philadelphia it is the planning district

    COUNTY – County where the intersection exists

    AMPKVEDEL – AM Peak Vehicle Delay

    PMPKVEDEL – PM Peak Vehicle Delay

    HIPKVEDEL – Highest AM or PM Peak Vehicle Delay

    TDPKVEDEL – AM or PM Time of Day of Highest Vehicle Delay

    PKVEDELRK – Peak Vehicle Delay Rank with lowest rank number the most delay

    PKVODELRK – Peak Volume Delay Rank with lowest rank number the most delay

    AMPKVODEL – AM Peak Volume Delay in HH:MM:SS

    PMPKVODEL – PM Peak Volume Delay in HH:MM:SS

    HIPKVODEL – Highest of AM or PM Peak Volume Delay in HH:MM:SS

    HIPKVOLDEV – Highest of AM or PM Peak Volume Delay in number format

    TDPKVODEL – AM or PM Time of Day of Highest Volume Delay

    KEYIDX – Unique identifier link to non-spatial data

    KEYID – Unique identifier link to non-spatial data (number format)

    STATE – AM or PM Time of Day of Highest Volume Delay

    COMMENT – Description of the potential cause of the bottleneck as applicable

    LOTTRMAXMI – Miles of travel time unreliable for the measure (1.50 or more)

    TTTRMAXMI – Miles of truck travel time unreliability for the measure (2.00 or more)

    PHEDVAPMI – Total Peak Hours of Excessive Delay weighted by road miles

    MAXVCMI – Miles of Travel Demand Model forecasted congestion V/C greater than or equal to 0.85 in 2050

    CRINDEXMI – Miles of high crash rate for the measure

    CRINDEXMI – Miles of high crash severity for the measure

    IMRMAXPMI – CMP Objective Measure score to increase mobility and reliability and meet PM3 targets weighted by road miles, where the maximum score is 4.0

    IMRMAXPR – CMP Objective Measure rank of IMRMAXPMI where lower values represent higher scores

    IMIAMAXPMI – CMP Objective Measure score to integrate modes and provide transit where it is most needed weighted by road miles, where the maximum score is 2.0

    IMIAMAXPR – CMP Objective Measure rank of IMIAMAXPMI where lower values represent higher scores

    MRMAXPMI – CMP Objective Measure score to modernize and maintain the existing transportation network, where the maximum score is 1.5

    MRMAXPR – CMP Objective Measure rank of MRMAXPMI where lower values represent higher scores

    SVRMAXPMI – CMP Objective Measure score to achieve Vision Zero, where the maximum score is 2.0

    SVRMAXPR – CMP Objective Measure rank of SVRMAXPMI where lower values represent higher scores

    GCMAXPMI – CMP Objective Measure score to maintain the movement of goods by truck and meet PM3 targets, where the maximum score is 1.5

    GCMAXPR – CMP Objective Measure rank of GCMAXPMI where lower values represent higher scores

    SPMAXPMI – CMP Objective Measure score to maintain and enhance transportation security and prepare for major events, where the maximum score is 1.0

    SPMAXPR – CMP Objective Measure rank of SPMAXPMI where lower values represent higher scores

    LRPMAXPMI – CMP Objective Measure score to support LRP centers, infill, redevelopment and emerging growth areas, environmental sensitive areas, and Environmental Justice and Equity populations, where the maximum score is 3.0

    LRPMAXPR – CMP Objective Measure rank of LRPMAXPMI where lower values represent higher scores

    CMPMAXPMI – Total of of the CMP Objective Measure scores, where the maximum score is 15.0

    CMPMAXPR – Total CMP Objective Measure rank of CMPMAXPMI where lower values represent higher scores

  5. A

    ‘Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ:...

    • analyst-2.ai
    Updated Jan 27, 2022
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    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com) (2022). ‘Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ: Beginning 2009’ analyzed by Analyst-2 [Dataset]. https://analyst-2.ai/analysis/data-gov-freight-cars-moved-in-carfloat-operations-port-authority-of-ny-nj-beginning-2009-d3ae/latest
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    Dataset updated
    Jan 27, 2022
    Dataset authored and provided by
    Analyst-2 (analyst-2.ai) / Inspirient GmbH (inspirient.com)
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New Jersey
    Description

    Analysis of ‘Freight Cars Moved in Carfloat Operations, Port Authority of NY NJ: Beginning 2009’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/a36acd86-84cf-42fe-ad71-b29057ee9753 on 27 January 2022.

    --- Dataset description provided by original source is as follows ---

    This dataset provides volume of loaded freight rail cars transported between NY and NJ by New York New Jersey Rail, a carfloat operation owned by the Port Authority of NY & NJ. Total volume, including empty cars, is estimated at twice the volume of loaded. 2013 entry is year-to-date volume at this time

    --- Original source retains full ownership of the source dataset ---

  6. a

    2023 CMP Focus Roadway Corridor Facilities

    • dvrpc-dvrpcgis.opendata.arcgis.com
    • catalog.dvrpc.org
    Updated Feb 16, 2025
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    DVRPC-GIS (2025). 2023 CMP Focus Roadway Corridor Facilities [Dataset]. https://dvrpc-dvrpcgis.opendata.arcgis.com/items/2678e84cb5554b1797aa708116fba267
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    Dataset updated
    Feb 16, 2025
    Dataset authored and provided by
    DVRPC-GIS
    Area covered
    Description

    Analyzing congestion at the roadway corridor facility level, rather than by roadway segment, can give a better understanding of why some roadway corridors are performing better than others, and enables congestion to be tracked over time. There are 336 Focus Roadway Corridor Facilities in the DVRPC region – 205 in Pennsylvania and 131 in New Jersey.Focus Roadway Corridor Facilities are used to prioritize congested locations and develop a set of focused strategies to manage congestion. Facility limits are delineated based on where there are breaks between Congested Corridor and Subcorridor Areas, and between major interchanges and arterial roadways. Ramps are not included due to lack of traffic volume data, but freeway to freeway interchanges (e.g. I-76 to I-676) with traffic volume data are included.These facilities are symbolized by rank in delay from high to low in quartiles separately for the Pennsylvania and New Jersey subregions, with brown locations being the most delayed and yellow the least. Rank is based on travel time and planning time (95th percentile) vehicle and volume delays. CMP Focus Roadway Corridor Facility Database FieldsMAPID – Unique identifier for the focus roadway corridor facility; NJ identifier starts at 300ROADWAY – Roadway name of the facilityFROMLIMIT – From limit roadway of the facilityTOLIMIT – To limit roadway of the facilityMILES – Length of the facility in milesLIMITACCES – Facility access typeValid values: Yes – Limited access No – Not limited access MUNICIPAL – Municipalities the facility is within; if too many then indicate “various”COUNTY – County the facility is withinAADT – Annual Average Daily Traffic for both directions of travelTTAMVEHDEL – Highest AM Peak Vehicle Travel Time DelayTTPMVEHDEL – Highest PM Peak Travel Time Vehicle DelayTTHIVEHDEL – Highest of AM and PM Peak Travel Time Vehicle DelayTTTDVEHDEL – Time of Day of Highest Peak Travel Time Vehicle DelayValid values: AM – AM Peak PM – PM Peak TTRKVEHDEL – Highest Peak Travel Time Vehicle Delay Rank with lower numbers indicating the most delay TTRKVOLDEL – Highest Peak Travel Time Volume Delay Rank with lower numbers indicating the most delay TTAMVOLDEL – Highest Peak Travel Time AM Volume Delay TTPMVOLDEL – Highest Peak Travel Time PM Volume Delay TTHIVOLDEL – Highest of AM and PM Peak Travel Time Volume DelayTTTDVOLDEL – Time of Day of Highest Peak Travel Time Volume DelayValid values: AM – AM Peak PM – PM Peak TTAMHHMMSS – Highest of AM Peak Travel Time Volume Delay in HH:MM:SSTTPMHHMMSS – Highest of PM Peak Travel Time Volume Delay in HH:MM:SSPTAMVEHDEL – Highest AM Peak Planning Time Vehicle DelayPTPMVEHDEL – Highest PM Peak Planning Time Vehicle DelayPTHIVEHDEL – Highest of AM and PM Peak Planning Time Vehicle DelayPTTDVEHDEL – Time of Day of Highest Peak Planning Time Vehicle DelayValid values: AM – AM Peak PM – PM Peak PTRKVEHDEL – Highest Peak Planning Time Vehicle Delay Rank with lower numbers indicating the most delay PTRKVOLDEL – Highest Peak Planning Time Volume Delay Rank with lower numbers indicating the most delay PTAMVOLDEL – Highest Peak Planning Time AM Volume Delay PTPMVOLDEL – Highest Peak Planning Time PM Volume Delay PTHIVOLDEL – Highest of AM and PM Peak Planning Time Volume DelayPTTDVOLDEL – Time of Day of Highest Peak Planning Time Volume DelayValid values: AM – AM Peak PM – PM Peak PTAMHHMMSS – Highest of AM Peak Planning Time Volume Delay in HH:MM:SSPTPMHHMMSS – Highest of PM Peak Planning Time Volume Delay in HH:MM:SSTKAADT – Truck Annual Average Daily Traffic for both directions of travelTKRKVOLDEL – Highest Truck Peak Planning Time Volume Delay Rank with lower numbers indicating the most delay TKAMVOLDEL – Highest Truck Peak Planning Time AM Volume Delay TKPMVOLDEL – Highest Truck Peak Planning Time PM Volume Delay TKHIVOLDEL – Highest of AM and PM Truck Peak Planning Time Volume DelayTKTDVOLDEL – Time of Day of Highest Peak Truck Planning Time Volume DelayValid values: AM – AM Peak PM – PM Peak TKAMHHMMSS – Highest of AM Peak Truck Planning Time Volume Delay expressed in HH:MM:SSTKPMHHMMSS – Highest of PM Peak Truck Planning Time Volume Delay expressed in HH:MM:SSSTATE – State the facility is withinLOTTRMAXMI – Miles of travel time unreliability for the measure (1.50 or more)LOTTRMAXPM – Miles of travel time unreliability (LOTTRMAXMI) per road mileTTTRMAXMI – Miles of truck travel time unreliability for the measure (2.00 or more) TTTRMAXPM – Miles of truck travel time unreliability (TTTRMAXMI) per road milePHEDVAPMI – Total Peak Hours of Excessive Delay weighted by road miles MAXVCMI – Miles of Travel Demand Model forecasted congestion V/C greater than or equal to 0.85 in 2050 MAXVCPMI – Miles of Travel Demand Model forecasted congestion (MAXVCMI) per road mile CRINDEXMI – Miles of high crash rate for the measureCRINDEXPMI – Miles of high crash rate (CRINDEXMI) per road mileCRINDEXMI – Miles of high crash severity for the measureCRINDEXPMI – Miles of high crash severity (CRINDEXMI) per road mileIMRMAXPMI – CMP Objective Measure score to increase mobility and reliability and meet PM3 targets weighted by road miles, where the maximum score is 4.0IMRMAXPR – CMP Objective Measure rank of IMRMAXPMI where lower values represent higher scores IMIAMAXPMI – CMP Objective Measure score to integrate modes and provide transit where it is most needed weighted by road miles, where the maximum score is 2.0IMIAMAXPR – CMP Objective Measure rank of IMIAMAXPMI where lower values represent higher scoresMRMAXPMI – CMP Objective Measure score to modernize and maintain the existing transportation network, where the maximum score is 1.5MRMAXPR – CMP Objective Measure rank of MRMAXPMI where lower values represent higher scoresSVRMAXPMI – CMP Objective Measure score to achieve Vision Zero, where the maximum score is 2.0SVRMAXPR – CMP Objective Measure rank of SVRMAXPMI where lower values represent higher scoresGCMAXPMI – CMP Objective Measure score to maintain the movement of goods by truck and meet PM3 targets, where the maximum score is 1.5GCMAXPR – CMP Objective Measure rank of GCMAXPMI where lower values represent higher scoresSPMAXPMI – CMP Objective Measure score to maintain and enhance transportation security and prepare for major events, where the maximum score is 1.0SPMAXPR – CMP Objective Measure rank of SPMAXPMI where lower values represent higher scoresLRPMAXPMI – CMP Objective Measure score to support LRP centers, infill, redevelopment and emerging growth areas, environmental sensitive areas, and Environmental Justice and Equity populations, where the maximum score is 3.0LRPMAXPR – CMP Objective Measure rank of LRPMAXPMI where lower values represent higher scoresCMPMAXPMI – Total of of the CMP Objective Measure scores, where the maximum score is 15.0CMPMAXPR – Total CMP Objective Measure rank of CMPMAXPMI where lower values represent higher scoresVOLDEL2017 – Volume Delay 5-6 PM in 2017 VOLDEL2021 – Volume Delay 5-6 PM in 2021VOLDEL2022 – Volume Delay 5-6 PM in 2022TTD070817 – 7-8 AM Travel Time Vehicle Delay in 2017TTD171817 – 5-6 PM Travel Time Vehicle Delay in 2017TTTD070817 – 7-8 AM Travel Time Volume Delay in 2017TTTD171817 – 5-6 PM Travel Time Volume Delay in 2017PTD070817 – 7-8 AM Planning Time Vehicle Delay in 2017PTD171817 – 5-6 PM Planning Time Vehicle Delay in 2017PTTD070817 – 7-8 AM Planning Time Volume Delay in 2017PTTD171817 – 5-6 PM Planning Time Volume Delay in 2017TTD070821 – 7-8 AM Travel Time Vehicle Delay in 2021TTD080921 – 8-9 AM Travel Time Vehicle Delay in 2021TTD161721 – 4-5 PM Travel Time Vehicle Delay in 2021TTD171821 – 5-6 PM Travel Time Vehicle Delay in 2021TTTD070821 – 7-8 AM Travel Time Volume Delay in 2021TTTD080921 – 8-9 AM Travel Time Volume Delay in 2021TTTD161721 – 4-5 PM Travel Time Volume Delay in 2021TTTD171821 – 5-6 PM Travel Time Volume Delay in 2021PTD070821 – 7-8 AM Planning Time Vehicle Delay in 2021PTD080921 – 8-9 AM Planning Time Vehicle Delay in 2021PTD161721 – 4-5 PM Planning Time Vehicle Delay in 2021PTD171821 – 5-6 PM Planning Time Vehicle Delay in 2021PTTD070821 – 7-8 AM Planning Time Volume Delay in 2021PTTD080921 – 8-9 AM Planning Time Volume Delay in 2021PTTD161721 – 4-5 PM Planning Time Volume Delay in 2021PTTD171821 – 5-6 PM Planning Time Volume Delay in 2021TTI060721 – 6-7 AM Travel Time Index in 2021TTI070821 – 7-8 AM Travel Time Index in 2021TTI080921 – 8-9 AM Travel Time Index in 2021TTI091021 – 9-10 AM Travel Time Index in 2021TTI101121 – 10-11 AM Travel Time Index in 2021TTI111221 – 11-12 AM Travel Time Index in 2021TTI121321 – 12-1 PM Travel Time Index in 2021TTI131421 – 1-2 PM Travel Time Index in 2021TTI141521 – 2-3 PM Travel Time Index in 2021TTI151621 – 3-4 PM Travel Time Index in 2021TTI161721 – 4-5 PM Travel Time Index in 2021TTI171821 – 5-6 PM Travel Time Index in 2021TTI181921 – 6-7 PM Travel Time Index in 2021TTI192021 – 7-8 PM Travel Time Index in 2021TTI202121 – 8-9 PM Travel Time Index in 2021TTD070822 – 7-8 AM Travel Time Vehicle Delay in 2022TTD080922 – 8-9 AM Travel Time Vehicle Delay in 2022TTD161722 – 4-5 PM Travel Time Vehicle Delay in 2022TTD171822 – 5-6 PM Travel Time Vehicle Delay in 2022TTTD070822 – 7-8 AM Travel Time Volume Delay in 2022TTTD080922 – 8-9 AM Travel Time Volume Delay in 2022TTTD161722 – 4-5 PM Travel Time Volume Delay in 2022TTTD171822 – 5-6 PM Travel Time Volume Delay in 2022PTD070822 – 7-8 AM Planning Time Vehicle Delay in 2022PTD080922 – 8-9 AM Planning Time Vehicle Delay in 2022PTD161722 – 4-5 PM Planning Time Vehicle Delay in 2022PTD171822 – 5-6 PM Planning Time Vehicle Delay in 2022PTTD070822 – 7-8 AM Planning Time Volume Delay in 2022PTTD080922 – 8-9 AM Planning Time Volume

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New Jersey Department of Transportation (2023). New Jersey Annual Average Daily Traffic [Dataset]. https://njogis-newjersey.opendata.arcgis.com/maps/47a9e9abd50b4f7bbc56db38a373cc43

New Jersey Annual Average Daily Traffic

Explore at:
Dataset updated
Mar 23, 2023
Dataset authored and provided by
New Jersey Department of Transportation
Area covered
Description

The New Jersey Department of Transportation collects traffic data at over 4300 station locations along all Interstate, U.S. , N.J. and County Routes throughout the State of New Jersey. This map represents the estimated Annual Average Daily Traffic (AADT) values based on the most current station data available. The AADT Flow layer data is displayed in six (6) groups, five (5) representing graduated AADT ranges and one (1) representing no station data. The traffic information is used for planning, design, maintenance and general administration of the roadway systems.

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