Intelligent Network Flow Optimization Prototype Traffic Management Entity-Based Queue Warning
datahub.transportation.gov | Last Updated 21 May 2024Data is from the small-scale demonstration of the Intelligent Network Flow Optimization (INFLO) Prototype System and applications in Seattle, Washington. Connected vehicle systems were deployed in 21 vehicles in a scripted driving scenario circuiting this I-5 corridor northbound and southbound during morning rush hour. This data set contains queue warning messages that were recommended by the INFLO Q-WARN algorithm and sent by the traffic management center to vehicles to warn drivers upstream of the queue. The objective of queue warning is to provide a vehicle operator sufficient warning of impending queue backup in order to brake safely, change lanes, or modify route such that secondary collisions can be minimized or even eliminated.
This dataset has the following 7 columns:
Column Name | API Column Name | Data Type | Description | Sample Values |
---|---|---|---|---|
DateGenerated | dategenerated | text | Date and time when the queue warning was generated | 1/16/2015 15:36 1/14/2015 15:50 1/13/2015 16:01 1/16/2015 15:32 1/14/2015 15:51 view top 100 |
RoadwayID | roadwayid | number | Id of the roadway where the queue was detected | 1100 1000 view top 100 |
BOQMMLocation | boqmmlocation | number | Mile marker location of the back-of-queue | 179.26 179.76 172.88 159.57 171.31 view top 100 |
FOQMMLocation | foqmmlocation | number | Mile marker location of the front-of-queue | 166 168 172 180 view top 100 |
SpeedInQueue | speedinqueue | number | Average speed of vehicles in queue | 65 0 20 24 13 view top 100 |
RateOfQueueGrowth | rateofqueuegrowth | number | Rate of queue growth from the last location of queue. In other words, rate of growth of the queue from one time interval to another. It can positive indicating a growing queue or negative indicating a dissipating queue. | 0 13 6 9 3 view top 100 |
ValidityDuration | validityduration | number | Interval in seconds the recommendation is valid from the date and time when it was generated | 60 view top 100 |