Intelligent Network Flow Optimization Prototype Traffic Management Entity-Based Queue Warning

Data 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.

Querying over HTTP

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

curl https://data.splitgraph.com/sql/query/ddn \
    -H "Content-Type: application/json" \
    -d@-<<EOF
{"sql": "
    SELECT *
    FROM \"datahub-transportation-gov/intelligent-network-flow-optimization-prototype-fnkc-y5dk\".\"intelligent_network_flow_optimization_prototype\"
    LIMIT 100 
"}
EOF

See the Splitgraph documentation for more information.