Enhancing Microsimulation Models for Improved Work Zone Planning: Car-Following Data from Northern Virginia (Instances)

The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 59 data collection runs, performed through the Federal Highway Administration (FHWA) Turner Fairbank Highway Research Center’s (TFHRC) Living Laboratory (LL). Data were collected using an Instrumented Research Vehicle (IRV) along freeways in northern Virginia to better understand work zone driver behaviors. The USDOT Volpe National Transportation Systems Center (Volpe Center) identified, isolated, and classified individual car following instances from within the raw datasets (classification parameters included roadway type, level of congestion, and speed limit), then processed, refined, and cleaned the dataset.

This table contains the car-following instances recorded by Volpe staff. See also the runs table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/285w-yjf5) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/uvrt-varj).

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/enhancing-microsimulation-models-for-improved-work-k74u-yqu6\".\"enhancing_microsimulation_models_for_improved_work\"
    LIMIT 100 
"}
EOF

See the Splitgraph documentation for more information.