trip: Trip data

In tripaccess: American Travel Behavior and Access Datasets

Trip data

Description

Include trip related categorical and numeric variables.

Usage

trip

Format

A data frame with 921590 rows (each row is a trip) and 8 columns

household_id

Household identifier. Use both this variable and person_id to join the trip dataset and the person dataset. Use this variable to join the trip dataset and the house dataset.

person_id

Person identifier. Use both this variable and household_id to join the trip dataset and the person dataset.

trip_purpose

Generalized purpose of trip on travel day. A travel day is a 24-hour day that starts at 4:00 a.m. (local time) of the assigned travel day and ends at 3:59 a.m. of the following day. The NHTS randomly assigns the travel days for one-seventh of the sample addresses to each day of the week and the remaining six-sevenths of the households to evenly across weekdays (Monday-Friday).

gas_price

Price of gasoline, in cents, on respondent's travel day.

num_of_people_on_trip

Number of people on trip including respondent on respondent's travel day.

trip_miles

Trip distance in miles on respondent's travel day, derived from route geometry returned. Google Maps was used for routing the shortest path for motorized travel on the road network. Non-motorized modes, like walk and bike, had the shortest path calculated using network routes paths.

trip_duration

Trip duration in minutes on respondent's travel day.

trip_miles_personally_driven_vehicle

Trip distance in miles for personally driven vehicle trips on respondent's travel day. -1 = Appropriate skip.

Source

https://nhts.ornl.gov/

Examples

if (require("tidyverse")) {
# Filtered to shorter trips for a clearer introductory visualization
short_trips <- trip |>
  filter(trip_miles <= 50,
         trip_duration <= 180)

# Filtered to trips with positive distance and duration
positive_distance_trips <- short_trips |>
  filter(trip_miles > 0,
         trip_duration > 0)

# Fit a simple linear regression model
duration_miles_model <- lm(trip_duration ~ trip_miles,
                           data = positive_distance_trips)
summary(duration_miles_model)

# Correlation between trip distance and trip duration
cor(positive_distance_trips$trip_miles, positive_distance_trips$trip_duration)
}

tripaccess documentation built on Aug. 29, 2026, 1:07 a.m.