Individual Trips Documentation ¶

Overview ¶

The indiv_trip.csv file contains detailed trip-level information for individual (person-specific) tours, representing the most granular level of travel behavior in CTRAMP. Each record represents a single trip segment, which may be either a stop-based trip (between intermediate stops) or a direct trip (when no stops are made).

Note: This documentation reflects the actual field structure found in model output files (verified against 2015-tm22-dev-sprint-04 run). The file contains exactly 19 fields as documented below.

Actual fields: hh_id, person_id, person_num, tour_id, stop_id, inbound, tour_purpose, orig_purpose, dest_purpose, orig_mgra, dest_mgra, trip_dist, parking_mgra, stop_period, trip_mode, tour_mode, tranpath_rnum, sampleRate, avAvailable

File Purpose ¶

Individual trips provide the foundation for transportation analysis and modeling by capturing: - Detailed trip chains with intermediate stops - Trip-level mode choices and timing - Origin-destination patterns at the MGRA level - Trip purposes and activity sequencing - Transportation network loading data

Key Relationships ¶

Links to household.csv via hh_id
Links to person.csv via person_id and person_num
Links to indiv_tour.csv via hh_id, person_id, and tour_id
Referenced by transportation network models for trip assignment

Field Specifications ¶

Identification Fields ¶

Field	Type	Description	Example Values
`hh_id`	INTEGER	Household identifier linking to household.csv	100001, 100002
`person_id`	INTEGER	Person identifier linking to person.csv	1000010101, 1000010102
`person_num`	INTEGER	Person number within household (1-based)	1, 2, 3, 4
`tour_id`	INTEGER	Tour identifier within person (0-based)	0, 1, 2

Trip Sequencing ¶

Field	Type	Description	Valid Values
`stop_id`	INTEGER	Stop/trip sequence identifier within tour	0-based: 0, 1, 2; -1 for direct trips
`inbound`	INTEGER	Trip direction indicator	0=outbound, 1=inbound

Trip Sequencing Logic: - stop_id = -1: Direct trip (no intermediate stops) - stop_id = 0: First stop/trip on half-tour - stop_id = 1,2,3: Subsequent stops/trips on half-tour - Outbound trips (inbound = 0): From home toward tour destination - Inbound trips (inbound = 1): From tour destination toward home

Tour Context ¶

Field	Type	Description	Allowed Values
`tour_purpose`	TEXT	Primary purpose of parent tour	See individual tour purposes

Tour Purpose Reference (Actual Values): - Mandatory: “Work”, “School”, “University” - Non-Mandatory: “Escort”, “Shop”, “Maintenance”, “Discretionary”, “Visiting”, “Eating Out” - At-Work: “Work-Based”

Trip Purposes ¶

Field	Type	Description	Purpose Categories
`orig_purpose`	TEXT	Purpose at trip origin	Activity purposes or “Home”/”Work”
`dest_purpose`	TEXT	Purpose at trip destination	Activity purposes or “Home”/”Work”

Common Trip Purposes (Actual Values): - Home/Work Anchors: “Home”, “Work” - Activities: “Shop”, “Maintenance”, “Discretionary”, “Visiting”, “Eating Out” - Education: “School”, “University” - Support: “Escort” (drop-off/pick-up activities) - Work-Related: “Work-Based”, “work related”

Spatial Attributes ¶

Field	Type	Description	Valid Range
`orig_mgra`	INTEGER	Origin MGRA (Micro Geographic Analysis Zone)	Valid MGRA IDs
`dest_mgra`	INTEGER	Destination MGRA	Valid MGRA IDs
`parking_mgra`	INTEGER	Parking location MGRA (for auto modes)	Valid MGRA IDs or 0

Temporal Attributes ¶

Field	Type	Description	Valid Range
`stop_period`	INTEGER	Trip departure time period	1-48 (30-minute periods)

Time Period Conversion: - Period 1 = 3:00-3:29 AM - Period 2 = 3:30-3:59 AM
- Period 12 = 8:30-8:59 AM (morning commute) - Period 24 = 2:30-2:59 PM (early afternoon) - Period 36 = 8:30-8:59 PM (evening) - Period 48 = 2:30-2:59 AM (next day)

Mode Choice ¶

Field	Type	Description	Valid Values
`trip_mode`	INTEGER	Trip-specific transportation mode	1-17 (see mode dictionary)
`tour_mode`	INTEGER	Parent tour transportation mode	1-17 (same as trip_mode for tours without stops)

Transportation Mode Dictionary (17 modes):

Mode ID	Mode Name	Category	Description
1	SOV_GP	Auto	Single occupant vehicle, general purpose lanes
2	SOV_PAY	Auto	Single occupant vehicle, toll/express lanes
3	SR2_GP	Auto	Shared ride 2 person, general purpose lanes
4	SR2_HOV	Auto	Shared ride 2 person, HOV lanes
5	SR2_PAY	Auto	Shared ride 2 person, toll/express lanes
6	SR3_GP	Auto	Shared ride 3+ person, general purpose lanes
7	SR3_HOV	Auto	Shared ride 3+ person, HOV lanes
8	SR3_PAY	Auto	Shared ride 3+ person, toll/express lanes
9	WALK	Non-Motorized	Walk only
10	BIKE	Non-Motorized	Bicycle
11	WALK_LOC	Transit	Walk to local bus
12	WALK_LRF	Transit	Walk to light rail/ferry
13	WALK_EXP	Transit	Walk to express bus
14	WALK_HVY	Transit	Walk to heavy rail
15	WALK_COM	Transit	Walk to commuter rail
16	DRIVE_LOC	Transit	Drive to local bus
17	DRIVE_LRF	Transit	Drive to light rail/ferry

Performance Metrics ¶

Field	Type	Description	Units
`trip_dist`	REAL	Trip distance	Miles

Distance Calculation: - Calculated using shortest path algorithms - May use auto or transit networks depending on trip mode - For walk/bike trips, uses pedestrian/bicycle network distances

Model Metadata ¶

Field	Type	Description	Valid Range
`tranpath_rnum`	REAL	Transit path choice random number	0.0-1.0 (or -999 for non-transit)
`sampleRate`	REAL	Household sampling rate	0.0-1.0
`avAvailable`	INTEGER	Autonomous vehicle availability flag	0=no, 1=yes

Trip Generation Logic ¶

Stop-Based Trips ¶

When tours include intermediate stops, multiple trip records are generated:

Example Outbound Half-Tour with 2 stops:
- stop_id=0, inbound=0: Home → Stop 1
- stop_id=1, inbound=0: Stop 1 → Stop 2  
- stop_id=2, inbound=0: Stop 2 → Tour Destination

Example Inbound Half-Tour with 1 stop:
- stop_id=0, inbound=1: Tour Destination → Stop 1
- stop_id=1, inbound=1: Stop 1 → Home

Direct Trips (No Stops) ¶

When tours have no intermediate stops:

Direct Tour Example:
- stop_id=-1, inbound=0: Home → Tour Destination
- stop_id=-1, inbound=1: Tour Destination → Home

Purpose Assignment Logic ¶

Trip purposes are assigned based on stop/destination activities:

Home/Work Anchor: Trips to/from home use “Home”, trips to/from work use “Work”
Stop Purposes: Intermediate stops use activity-specific purposes (shopping, othMaint, etc.)
Tour Purposes: Final destinations use tour-level purposes
Activity Chains: Sequential stops create purpose chains (e.g., Home→Shopping→Bank→Home)

Mode Choice Hierarchy ¶

Tour vs. Trip Mode Relationships ¶

Tour Mode: Overall transportation mode for entire tour
Trip Mode: May differ from tour mode for individual trip segments
Mode Constraints: Trip modes must be compatible with tour mode capabilities

Examples: - Auto tour (tour_mode = 1-8): Trip modes typically match tour mode - Transit tour (tour_mode = 11-17): May include walk trips for station access - Walk/Bike tour (tour_mode = 9-10): All trips use same non-motorized mode

Transit Path Choice ¶

For transit trips (trip_mode = 11-17): - tranpath_rnum contains random number for path choice modeling - Used for selecting among multiple transit route options - Critical for transit assignment and capacity analysis

Survey Data Integration ¶

Mapping Survey Data to Trip Records ¶

When transforming survey data to match CTRAMP trip format:

Trip Chaining: Group survey trips into tours, then decompose into trip segments
Purpose Mapping: Translate survey activity purposes to CTRAMP purpose categories
Mode Harmonization: Map survey transportation modes to 17-mode CTRAMP system
Time Conversion: Convert survey times to CTRAMP 30-minute time periods
Spatial Mapping: Geocode survey locations to MGRA system

Common Survey Data Challenges ¶

Activity Classification: Survey purposes may not directly map to CTRAMP categories
Tour Definition: Surveys may record trips without clear tour structure
Mode Detail: Survey modes may be more or less detailed than CTRAMP system
Timing Precision: Survey times may need rounding to 30-minute periods
Transfer Trips: Complex transit journeys may require trip segment decomposition

Validation Rules ¶

Data Quality Checks ¶

-- Check valid stop sequencing
SELECT hh_id, person_id, tour_id, stop_id, inbound 
FROM indiv_trip 
WHERE stop_id NOT IN (-1, 0, 1, 2, 3) OR inbound NOT IN (0, 1);

-- Verify mode consistency
SELECT DISTINCT trip_mode FROM indiv_trip 
WHERE trip_mode NOT BETWEEN 1 AND 17;

-- Check time periods
SELECT COUNT(*) FROM indiv_trip 
WHERE stop_period NOT BETWEEN 1 AND 48;

-- Validate trip sequencing within tours
SELECT hh_id, person_id, tour_id, COUNT(*) as trip_count,
       COUNT(CASE WHEN inbound = 0 THEN 1 END) as outbound_trips,
       COUNT(CASE WHEN inbound = 1 THEN 1 END) as inbound_trips
FROM indiv_trip 
GROUP BY hh_id, person_id, tour_id
HAVING outbound_trips = 0 OR inbound_trips = 0;  -- Tours should have both directions

Geographic Consistency ¶

-- Check for trips within same MGRA (very short trips)
SELECT COUNT(*) FROM indiv_trip 
WHERE orig_mgra = dest_mgra AND trip_dist > 0.1;  -- Flag suspicious cases

-- Validate MGRA codes exist in geography
SELECT DISTINCT orig_mgra FROM indiv_trip 
WHERE orig_mgra NOT IN (SELECT mgra_id FROM mgra_geography);

Tour-Trip Linkages ¶

-- Verify trip counts match tour stop attributes
SELECT t.hh_id, t.person_id, t.tour_id,
       t.num_ob_stops, t.num_ib_stops,
       COUNT(CASE WHEN it.inbound = 0 THEN 1 END) - 1 as actual_ob_stops,
       COUNT(CASE WHEN it.inbound = 1 THEN 1 END) - 1 as actual_ib_stops
FROM indiv_tour t
LEFT JOIN indiv_trip it ON t.hh_id = it.hh_id 
  AND t.person_id = it.person_id 
  AND t.tour_id = it.tour_id
GROUP BY t.hh_id, t.person_id, t.tour_id, t.num_ob_stops, t.num_ib_stops
HAVING actual_ob_stops != t.num_ob_stops 
    OR actual_ib_stops != t.num_ib_stops;

Usage Examples ¶

Trip Chain Analysis ¶

-- Analyze complete trip chains for shopping tours
SELECT 
  hh_id, person_id, tour_id,
  STRING_AGG(orig_purpose || '→' || dest_purpose, ' | ' ORDER BY inbound, stop_id) as trip_chain,
  COUNT(*) as trip_segments,
  SUM(trip_dist) as total_distance
FROM indiv_trip 
WHERE tour_purpose = 'shopping'
GROUP BY hh_id, person_id, tour_id
ORDER BY total_distance DESC
LIMIT 10;

Mode Choice Analysis ¶

-- Trip vs tour mode choice consistency
SELECT 
  tour_mode,
  trip_mode,
  COUNT(*) as trip_count,
  AVG(trip_dist) as avg_distance
FROM indiv_trip
GROUP BY tour_mode, trip_mode
HAVING COUNT(*) > 100
ORDER BY tour_mode, trip_mode;

Temporal Distribution ¶

-- Trip departure time patterns by purpose
SELECT 
  dest_purpose,
  CASE 
    WHEN stop_period BETWEEN 1 AND 12 THEN 'Early AM (3:00-8:59)'
    WHEN stop_period BETWEEN 13 AND 24 THEN 'Morning (9:00-14:59)'
    WHEN stop_period BETWEEN 25 AND 36 THEN 'Afternoon (15:00-20:59)'
    ELSE 'Evening (21:00-2:59)'
  END as time_of_day,
  COUNT(*) as trip_count,
  AVG(trip_dist) as avg_distance
FROM indiv_trip 
WHERE stop_id >= 0  -- Exclude direct trips
GROUP BY dest_purpose, time_of_day
ORDER BY dest_purpose, time_of_day;

Stop Pattern Analysis ¶

-- Distribution of stop patterns by tour purpose
SELECT 
  tour_purpose,
  MAX(CASE WHEN inbound = 0 THEN stop_id END) + 1 as outbound_stops,
  MAX(CASE WHEN inbound = 1 THEN stop_id END) + 1 as inbound_stops,
  COUNT(DISTINCT tour_id) as tour_count
FROM indiv_trip 
WHERE stop_id >= 0
GROUP BY hh_id, person_id, tour_id, tour_purpose
GROUP BY tour_purpose, outbound_stops, inbound_stops
ORDER BY tour_purpose, outbound_stops, inbound_stops;

Transit Trip Analysis ¶

-- Transit trip characteristics
SELECT 
  trip_mode,
  CASE 
    WHEN trip_mode BETWEEN 11 AND 15 THEN 'Walk Access'
    WHEN trip_mode BETWEEN 16 AND 17 THEN 'Drive Access'
  END as access_mode,
  COUNT(*) as trip_count,
  AVG(trip_dist) as avg_distance,
  AVG(tranpath_rnum) as avg_path_random
FROM indiv_trip 
WHERE trip_mode BETWEEN 11 AND 17
GROUP BY trip_mode
ORDER BY trip_mode;

Network Loading Applications ¶

Individual trip data provides the foundation for transportation network analysis:

Auto Assignment: Trip origins/destinations and departure times for traffic loading
Transit Assignment: Transit trip paths and boarding/alighting patterns
Active Transportation: Walk/bike trip volumes for facility planning
Time-of-Day Analysis: Temporal trip distribution for capacity planning
Mode Share Analysis: Transportation mode usage patterns by geography and demographics

The granular nature of trip data enables detailed network performance evaluation and infrastructure investment analysis.