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

The data describe freeway car-following behavior (such as velocity, acceleration, and relative position) for the car-following instances observed during 6 data collection runs, collected using an Instrumented Research Vehicle (IRV) along freeways and arterials in western Massachusetts in the summer of 2016 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/b3k6-qwyh) and radar table (https://datahub.transportation.gov/Automobiles/Enhancing-Microsimulation-Models-for-Improved-Work/4qbx-egtn).

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-74ug-57tr\".\"enhancing_microsimulation_models_for_improved_work\"
    LIMIT 100 
"}
EOF

See the Splitgraph documentation for more information.