Chicago Traffic Tracker - Historical Congestion Estimates by Segment - 2018-Current
data.cityofchicago.org | Last Updated 16 Jul 2021This dataset contains the historical estimated congestion for over 1,000 traffic segments, starting in approximately March 2018. Older records are in https://data.cityofchicago.org/d/77hq-huss. The most recent estimates for each segment are in https://data.cityofchicago.org/d/n4j6-wkkf. The Chicago Traffic Tracker estimates traffic congestion on Chicago’s arterial streets (non-freeway streets) in real-time by continuously monitoring and analyzing GPS traces received from Chicago Transit Authority (CTA) buses. Two types of congestion estimates are produced every 10 minutes: 1) by Traffic Segments and 2) by Traffic Regions or Zones. Congestion estimates by traffic segments gives observed speed typically for one-half mile of a street in one direction of traffic. Traffic Segment level congestion is available for about 300 miles of principal arterials. Congestion by Traffic Region gives the average traffic condition for all arterial street segments within a region. A traffic region is comprised of two or three community areas with comparable traffic patterns. 29 regions are created to cover the entire city (except O’Hare airport area). There is much volatility in traffic segment speed. However, the congestion estimates for the traffic regions remain consistent for a relatively longer period. Most volatility in arterial speed comes from the very nature of the arterials themselves. Due to a myriad of factors, including but not limited to frequent intersections, traffic signals, transit movements, availability of alternative routes, crashes, short length of the segments, etc. Speed on individual arterial segments can fluctuate from heavily congested to no congestion and back in a few minutes. The segment speed and traffic region congestion estimates together may give a better understanding of the actual traffic conditions.
This dataset has the following 22 columns:
Column Name | API Column Name | Data Type | Description | Sample Values |
---|---|---|---|---|
TIME | time | calendar_date | 2018-02-28T21:40:00.000 2018-03-01T05:20:00.000 2018-02-28T21:01:00.000 2018-03-01T04:20:00.000 2018-02-28T17:40:00.000 view top 100 | |
SEGMENT_ID | segment_id | number | Unique arbitrary number to represent each segment. | 1307 1305 1152 1153 1304 view top 100 |
SPEED | speed | number | Estimated traffic speed in miles per hour. A value of -1 means no estimate is available. | -1 25 23 27 20 view top 100 |
STREET | street | text | Street name of the traffic segment. | Western Pulaski Halsted Ashland Cicero view top 100 |
DIRECTION | direction | text | Traffic flow direction for the segment. | NB SB EB WB NW view top 100 |
FROM_STREET | from_street | text | Start street for the segment in the direction of traffic flow. | Halsted Ashland Western Damen California view top 100 |
TO_STREET | to_street | text | End street for the segment in the direction of traffic flow. | Halsted Ashland Damen Western Kedzie view top 100 |
LENGTH | length | number | Length of the segment in miles. | 0.5 0.51 0.49 0.6 0.53 view top 100 |
STREET_HEADING | street_heading | text | The position of the segment in the address grid. North, South, East, or West of State and Madison. | S W N E view top 100 |
COMMENTS | comments | text | IDOT Signals Possible Outside City Limits Oneway Western Blvd Run Parallel on the East Side IDOT Signals possible in this segment view top 100 | |
BUS_COUNT | bus_count | number | Number of buses providing a GPS feed used to estimate congestion. | 0 1 2 3 4 view top 100 |
MESSAGE_COUNT | message_count | number | Number of GPS probes received(or used) for estimating the speed for that segment. | 0 11 10 12 9 view top 100 |
HOUR | hour | number | Hour of the day. | 12 17 14 16 0 view top 100 |
DAY_OF_WEEK | day_of_week | number | Day of the week. Sunday = 1 | 6 4 5 3 7 view top 100 |
MONTH | month | number | Month of the year. | 7 8 6 9 4 view top 100 |
RECORD_ID | record_id | text | A unique identifier for each record in the dataset. | 2018-02-28T21:40:00.000 2018-03-01T05:20:00.000 2018-02-28T21:01:00.000 2018-03-01T04:20:00.000 2018-02-28T17:40:00.000 view top 100 |
START_LATITUDE | start_latitude | number | Latitude of the start of the segment. | 41.874238 41.816184 41.838046 41.823458 41.83075 view top 100 |
START_LONGITUDE | start_longitude | number | Longitude of the start of the segment. | -87.639487 -87.645915 -87.647745 -87.632709 -87.66551 view top 100 |
END_LATITUDE | end_latitude | number | Latitude of the end of the segment. | 41.83075 41.808864 41.816184 41.823458 41.852646 view top 100 |
END_LONGITUDE | end_longitude | number | Longitude of the end of the segment. | -87.639487 -87.645915 -87.647745 -87.632709 -87.67507424 view top 100 |
START_LOCATION | start_location | point | Location of the start of the segment. | {"coordinates":[-87.646086,41.838046],"type":"Point"} {"coordinates":[-87.645535,41.816184],"type":"Point"} {"coordinates":[-87.645349,41.808864],"type":"Point"} {"coordinates":[-87.645156,41.801585],"type":"Point"} {"coordinates":[-87.645915,41.83075],"type":"Point"} view top 100 |
END_LOCATION | end_location | point | Location of the end of the segment. | {"coordinates":[-87.646935,41.874338],"type":"Point"} {"coordinates":[-87.646086,41.838046],"type":"Point"} {"coordinates":[-87.645349,41.808864],"type":"Point"} {"coordinates":[-87.646517,41.859912],"type":"Point"} {"coordinates":[-87.630574,41.874521],"type":"Point"} view top 100 |