Vital Signs: Time in Congestion - Corridor (Updated October 2018)
data.bayareametro.gov | Last Updated 24 Oct 2018VITAL SIGNS INDICATOR Time Spent in Congestion (T7) FULL MEASURE NAME Time Spent in Congestion LAST UPDATED October 2018 DATA SOURCE MTC/Iteris Congestion Analysis No link available CA Department of Finance Forms E-8 and E-5 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-8/ http://www.dof.ca.gov/Forecasting/Demographics/Estimates/E-5/ CA Employment Division Department: Labor Market Information http://www.labormarketinfo.edd.ca.gov/ CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Time spent in congestion measures the hours drivers are in congestion on freeway facilities based on traffic data. In recent years, data for the Bay Area comes from INRIX, a company that collects real-time traffic information from a variety of sources including mobile phone data and other GPS locator devices. The data provides traffic speed on the region’s highways. Using historical INRIX data (and similar internal datasets for some of the earlier years), MTC calculates an annual time series for vehicle hours spent in congestion in the Bay Area. Time spent in congestion is defined as the average daily hours spent in congestion on Tuesdays, Wednesdays and Thursdays during peak traffic months on freeway facilities. This indicator focuses on weekdays given that traffic congestion is generally greater on these days; this indicator does not capture traffic congestion on local streets due to data unavailability. This congestion indicator emphasizes recurring delay (as opposed to also including non-recurring delay), capturing the extent of delay caused by routine traffic volumes (rather than congestion caused by unusual circumstances). Recurring delay is identified by setting a threshold of consistent delay greater than 15 minutes on a specific freeway segment from vehicle speeds less than 35 mph. This definition is consistent with longstanding practices by MTC, Caltrans and the U.S. Department of Transportation as speeds less than 35 mph result in significantly less efficient traffic operations. 35 mph is the threshold at which vehicle throughput is greatest; speeds that are either greater than or less than 35 mph result in reduced vehicle throughput. This methodology focuses on the extra travel time experienced based on a differential between the congested speed and 35 mph, rather than the posted speed limit. To provide a mathematical example of how the indicator is calculated on a segment basis, when it comes to time spent in congestion, 1,000 vehicles traveling on a congested segment for a 1/4 hour (15 minutes) each, [1,000 vehicles x ¼ hour congestion per vehicle= 250 hours congestion], is equivalent to 100 vehicles traveling on a congested segment for 2.5 hours each, [100 vehicles x 2.5 hour congestion per vehicle = 250 hours congestion]. In this way, the measure captures the impacts of both slow speeds and heavy traffic volumes. MTC calculates two measures of delay – congested delay, or delay that occurs when speeds are below 35 miles per hour, and total delay, or delay that occurs when speeds are below the posted speed limit. To illustrate, if 1,000 vehicles are traveling at 30 miles per hour on a one mile long segment, this would represent 4.76 vehicle hours of congested delay [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 35 miles per hour) = 33.33 vehicle hours – 28.57 vehicle hours = 4.76 vehicle hours]. Considering that the posted speed limit on the segment is 60 miles per hour, total delay would be calculated as 16.67 vehicle hours [(1,000 vehicles x 1 mile / 30 miles per hour) - (1,000 vehicles x 1 mile / 60 miles per hour) = 33.33 vehicle hours – 16.67 vehicle hours = 16.67 vehicle hours]. Data sources listed above were used to calculate per-capita and per-worker statistics. Top congested corridors are ranked by total vehicle hours of delay, meaning that the highlighted corridors reflect a combination of slow speeds and heavy traffic volumes (consistent with longstanding regional methodologies used to generate the “top 10” list of congested segments). Historical Bay Area data was estimated by MTC Operations staff using a combination of internal datasets to develop an approximate trend back to 1998. To explore how 2017 congestion trends compare to real-time congestion on the region’s freeways, visit 511.org.
This dataset has the following 17 columns:
Column Name | API Column Name | Data Type | Description | Sample Values |
---|---|---|---|---|
ID | id | text | US-101 I-880 I-580 CA-85 I-280 view top 100 | |
Location | location | text | Start and endpoints of the congested segment | AT A ST CONNECTOR FROM NB US-101 (SAN JOSE) to BERNAL RD AT REDWOOD RD (CASTRO VALLEY) AT FREMONT AVE SAN ANTONIO RD to EMBARCADERO RD view top 100 |
Year | year | number | 2017 view top 100 | |
cs_rank | cs_rank | number | 2017 congestion ranking for segment | 117 33 124 29 14 view top 100 |
rank | rank | text | 71 118 123 8 75 view top 100 | |
County1 | county1 | text | County where congested segment is located | SANTA CLARA ALAMEDA CONTRA COSTA SAN MATEO SAN FRANCISCO view top 100 |
County2 | county2 | text | If congested segment spans two counties, second county where congested segment is located | ALAMEDA CONTRA COSTA SAN FRANCISCO SONOMA view top 100 |
County3 | county3 | text | view top 100 | |
Route1 | route1 | text | Freeway route number of congested segment | US-101 I-580 I-880 CA-85 I-680 view top 100 |
Route2 | route2 | text | If congested segment is shared by multiple freeways, second freeway route number | I-238 I-280 I-580 I-80 I-880 view top 100 |
Direction1 | direction1 | text | Direction (NB, SB, etc.) of Route 1 | SB NB WB EB view top 100 |
Direction2 | direction2 | text | Direction (NB, SB, etc.) of Route 2 | NB EB view top 100 |
Length | length | number | Length of congested segment in miles | 2.59 0.3 0.34 3.99 0.5 view top 100 |
StartHour | starthour | calendar_date | Start hour of observed congestion | 1899-12-31T14:55:00.000 1899-12-31T07:35:00.000 1899-12-31T14:45:00.000 1899-12-31T06:25:00.000 1899-12-31T15:20:00.000 view top 100 |
EndHour | endhour | calendar_date | End hour of observed congestion | 1899-12-31T18:50:00.000 1899-12-31T09:10:00.000 1899-12-31T18:00:00.000 1899-12-31T09:30:00.000 1899-12-31T19:00:00.000 view top 100 |
VHD | vhd | number | Vehicle-hours of delay on segment, calculated as congested hours of delay times number of vehicles affected | 110 30 70 20 290 view top 100 |
Source | source | text | INRIX_2018 view top 100 |