Guides

Active Transportation Trips

Overview

The active transportation table contains information about fully disaggregate, individual walking and biking trips for a typical weekday and weekend day in each season. Each row of data corresponds to one trip. This dataset can be utilized to generate a number of metrics including origin destination tables and network volumes. Data is released twice a year and is currently available for 2019, 2021, 2022 and 2023. It is available for download in CSV format.

Demographic, socioeconomic and employment information about the trip taker for each individual trip can be added by joining this table with the Demographics & Employment table using the person_id and household_id fields.

Replica does not model scooter trips and does not separate out e-bike trips.

Methodology

Replica’s active transportation data relies on a number of public and private sources including census and census derivative products (e.g. Public Use Microdata Samples (PUMS), American Census Survey (ACS)), built environment data (e.g. the identification of existing physical infrastructure like bike lanes, sidewalks, and paths as well as granular land use data), and observed trip and behavior data sources like Location Based Services (LBS), Point-of-Interest (POI), and consumer transaction data.

Replica uses these sources of data to generate a synthetic population, representative of everyone in the built environment without compromising any specific person's or group's privacy. This approach allows us to account for everyone and estimate the universe of travel, while maintaining some longitudinal consistency despite changes in any individual data source, like penetration fluctuations. Our location data sets are used to understand travel sequences and routes, allowing us to build tens of millions of behavior models that are then assigned to every synthesized person. They are not used for mode determination, a practice that we have found to be inaccurate.

Replica then uses three models to assign movements to the individuals in the synthetic population, including the activity sequence model, the location choice model, and finally the mode choice model. The latter determines how each trip will be made based on the state of the transportation network, accounting for available transit options, multiple driving routes, and availability of bike lanes and pedestrian-accessible facilities. For each trip that we determine is made, for each individual (based on everyone in the country) we model several options in different modes and ascribe a probability score for each. This probability is informed by each person's primary commute mode, as indicated by the census, the access the person has to different modes, patterns from location data sources on the local activity there (i.e. including up-to-date WFH preferences), as well as the state of the built environment (e.g. how long trip alternatives will take), factoring in time-specific variables like congestion. Where available, the data is calibrated and validated against ground truth count data, sourced from both private and publicly available data sources as well as customers. At this time, Replica only includes purposeful non-motorized travel in its model. Recreational trips (such as jogging for a workout, or a walk around a neighborhood or park that starts and ends at home) are not included.

Use the link below to see Replica's full seasonal mobility model methodology:
Seasonal Mobility Model Methodology Summary (Places)
Seasonal Mobility model Methodology Extended (Places)

Schema

Field NameContent TypeSample ValueDescription
activity_idString15323941267251300000A randomly assigned unique identifier defined for each trip. A trip is defined as travel between two locations with a discrete purpose at the origin and destination. Some intermediate stops with short dwell time may be captured within a single trip. Criteria for this dwell time may vary. Examples of trips:
• Home > Work,
• Work > Gym,
• Shop > Eat,
• Home > Starbucks drive-thru > Work
person_idString4339817784218880000A randomly assigned unique identifier for each person modeled within the synthetic population.
household_idString14408018579505000000A randomly assigned unique identifier for each household modeled within the synthetic population.
modeStringWALKINGPrimary transportation mode used for the trip.  A trip is often made up of multiple travel modes, such as a journey to work that includes a walk to a rail station followed by a subway ride. In this case two modes were used by the traveler during their trip, walking and public transit. Only the primary mode of travel across a set of trip segments is included. The primary mode is determined using the following ranking: 1) Public transit, 2) Driving (private auto)/Auto passenger/Taxi/TNC, 3) Biking, 4) Walking. This table is limited to the following:
• BIKING: Trips made by people biking. Replica does not model scooter trips and does not separate out e-bike trips
• WALKING: Trips made by people walking
travel_purposeStringWORKThe destination activity assigned to a synthetic person. For example, if a person is traveling to work, the purpose of the trip is 'Work,' whereas if a person is traveling to a restaurant the activity is 'Eat.' Valid values are:
• COMMERCIAL: Trips by medium and heavy trucks for deliveries and other commercial purposes
• EAT: Trips to restaurants
• HOME: Trips where the destination is the person's home
• LODGING: Trips by visitors to overnight accommodation such as a hotel
• MAINTENANCE: Trips to hairdressers, auto shops, banks, and a variety of other locations for the purpose of conducting errands
• OTHER: Catch-all category for all other trips not assigned any of the purposes listed herein
• RECREATION: Trips to recreational destinations such as parks and swimming pools
• REGION_DEPARTURE: Trips by visitors to a port-of-exit, such as an airport, or major train station
• SCHOOL: Trips to schools such as community colleges and universities
• SHOP: Trips to stores and other commercial centers
• SOCIAL: Trips for social activities
• STAGE: Trips made by non-residents that start and end outside the region
• WORK: Trips where the destination is the person's workplace
• WORK FROM HOME: Trips where a resident is returning home to work (specifically for residents who are working from home on the modeled day). For example, if a person goes out to lunch during the work day, their return trip home will be labeled “work_from_home"
tour_typeStringCOMMUTEIndicates what type of tour that included this trip. Tours are travel events that start at one location and return to that same location. For example, when a person travels to work and returns home, this is a home-based work tour. A tour can have two or more trips.  Valid options are: 
• WORK_BASED: Tours that started and ended at work, excluding commute. For example: Work > Eat > Work.
• COMMUTE: Tours from home to work and back home. Also includes intermediate stops at other destinations. For example: Home > Recreation > Work > Shop > Home
• OTHER_HOME_BASED: Tours that started and ended at home, excluding commutes. For example: Home > Shop > Eat > Home
previous_activity_typeStringHOMEThe activity assigned to a synthetic person prior to starting travel. Valid values are:
• COMMERCIAL: Trips by medium and heavy trucks for deliveries and other commercial purposes
• EAT: Trips to restaurants
• HOME: Trips where the destination is the person's home • LODGING: Trips by visitors to overnight accommodation such as a hotel
• MAINTENANCE: Trips to hairdressers, auto shops, banks, and a variety of other locations
• OTHER: Catch all category for all other trips not assigned any of the purposes listed herein
• RECREATION: Trips to recreational destinations such as parks and swimming pools
• REGION_DEPARTURE: Trips by visitors to a port-of-exit, such as an airport, or major train station
• SCHOOL: Trips to schools such as community colleges and universities
• SHOP: Trips to stores and other commercial centers
• SOCIAL: Trips for social activities
• STAGE: Trips made by non-residents that start and end outside the region
• WORK: Trips where the destination is the person's workplace
timezoneStringAmerica/Los_AngelesTimezone of the trip’s start location, using standard tz naming conventions.
start_timeTime2019-01-10 06:08:00 America/Los_AngelesDate and 24-hour time of trip start, reported as yyyy-mm-dd hh:mm:ss timezone.
start_local_hourInteger12Hour of day that the trip started, reported in the local time zone in 24-hour time format. Values in this field range between 0 and 23.
end_timeTime2019-01-10 07:11:04 America/Los_AngelesDate and 24-hour time of trip end, reported as yyyy-mm-dd hh:mm:ss timezone.
end_local_hourInteger14Hour of day that the trip ended, reported in the local time zone in 24-hour time format. Values in this field range between 0 and 23.
duration_minutesInteger63Duration of trip in minutes, calculated as the difference between the trip start_time and end_time.
distance_milesFloat10.7999733493896Distance in miles measured along the trip route.
transit_route_idsStringNULL for this table
network_link_idsString10541610554341416382Unique ID assigned to the link (road segment) that the trip is associated with.
vehicle_typeString (len 20)NULL for this table
vehicle_fuel_typeStringNULL for this table
vehicle_fuel_technologyStringNULL for this table
origin_bgrpString(len 12)410510010004The US Census Bureau-assigned FIPS code of the block group from which the trip originated.
origin_bgrp_latFloat45.492294Latitude of the geometric centroid for the origin block group, reported in decimal degrees, WGS 84.
origin_bgrp_lngFloat-122.65334Longitude of the geometric centroid for the origin block group, reported in decimal degrees, WGS 84.
destination_bgrpString (len 12)410510079001US Census Bureau-assigned FIPS of the block group in which the trip ended.
destination_bgrp_latFloat45.557407Latitude of the geometric centroid for the destination block group, reported in decimal degrees, WGS 84.
destination_bgrp_lngFloat-122.54931Longitude of the geometric centroid for the destination block group, reported in decimal degrees, WGS 84.
origin_land_use_l1StringresidentialThe primary land use category of the trip origin. Valid options are: 
• residential
• commercial
• mixed_use
• industrial
• civic_institutional
• transportation_utilities
• open space
• agriculture
• other
• unknown
origin_land_use_l2Stringsingle_familyThe secondary land use category of the trip origin. Valid options are:
• single_family
• multi_family
• office
• retail
• non_retail_attraction
• education
• healthcare
• military
• civic_institutional
• ​​transportation_utilities
• open_space
• agriculture
• other
• unknown
destination_land_use_l1StringcommercialThe primary land use category of the trip destination. Valid options are:
• residential
• commercial
• mixed_use
• industrial
• civic_institutional
• transportation_utilities
• open space
• agriculture
• other
• unknown
destination_land_use_l2Stringnon_retail_attractionThe secondary land use category of the trip destination. Valid options are:
• single_family
• multi_family
• office
• retail
• non_retail_attraction
• education
• healthcare
• military
• civic_institutional
• ​​transportation_utilities
• open_space
• agriculture
• other
• unknown
origin_building_use_l1StringresidentialThe primary building use category of the trip origin. Valid options are: 
• residential
• commercial
• industrial
• civic_institutional
• transportation_utilities
• open space
• agriculture
• other
• unknown
origin_building_use_l2Stringsingle_familyThe secondary building use category of the trip origin. Valid options are:
• single_family
• multi_family
• office
• retail
• non_retail_attraction
• education
• healthcare
• military
• civic_institutional
• ​​transportation_utilities
• open_space
• agriculture
• other
• unknown
destination_building_use_l1StringcommercialThe primary building use category of the trip destination. Valid options are: 
• residential
• commercial
• industrial
• civic_institutional
• transportation_utilities
• open space
• agriculture
• other
• unknown
destination_building_use_l2Stringnon_retail_attractionThe secondary building use category of the trip destination. Valid options are:
• single_family
• multi_family
• office
• retail
• non_retail_attraction
• education
• healthcare
• military
• civic_institutional
• ​​transportation_utilities
• open_space
• agriculture
• other
• unknown