Materials developed by K. Watkins, J. LaMondia and C. Brakewood Data Types & Sources Unit 2:...

Materials developed by K. Watkins, J. LaMondia and C. Brakewood

Data Types & Sources

Unit 2: Describing Transit Systems with Data

Outline

• Types of transit data

• Manual data collection

• Automated data collection

TYPES OF TRANSIT DATAWe need to quantify and characterize our systems with different

Service Is Only As Good As Your Data

• We need accurate data to make appropriate decisions for transit service.

• What if we were considering adding a new line to a transit system?– What information would we need to know to

make appropriate design decisions?

What Data is Needed to Maintain Good Service?

7 Demands of Useful Service

How Transit Services Them

It takes me where I want to

It takes me when I

want to go.

It is a good use of my

It is a good use of my money.

It respects

I can trust it.

It gives me freedom

(to change my plans).

Stops/ Stations

Connectivity

Frequency Span Speed or Delay Fares Civility Reliability

Simplicity /Presentation

Three Main Types of Data

• System Level Data– Entire operational overview – Useful for long-range planning, comparing service to similar

regions

• Route Level Data– Characteristics of specific routes – Useful for long-range planning, service planning, route

optimization

• Trip Level Data– Specific details of trips made on transit system– Useful for service planning, route optimization

Service Quality Improvement Cycles

Archive Data

Analyze Performance and Demand

Service Plan

Transit Operation

Automated Data

Gathering

Operational Control &

Passenger Info

Real-time loop

Off-line loop

System Level: National Transit Database (NTD)

• Established by Congress (Title 49 USC 5335a)• Primary source for statistics on transit in US• FTA grantees required to submit data• >660 providers currently report to NTD • Data used to apportion > $5 billion FTA funds• Freely and publically available

2011 National Transit Profile

Does this look familiar?

What is in the NTD?

• Modules include:– Safety and Security – Financials• Capital funds, operating expenses, operator wages

– Assets• Stations and maintenance facilities, transit way

mileage, revenue vehicles

– Resources• Number of employees, energy consumption

– Transit Service (Supplied and Consumed)• Vehicle revenue miles, Vehicle revenue hours, unlinked

passenger trips, passenger miles traveled

NTD Glossary (Expenses)

• Capital Expenses = purchase of equipment

– Useful life > one year and Greater than $5,000

– Includes Facilities (Guideway, Passenger Stations,

Administration Buildings, Maintenance), Rolling Stock

(vehicles), Other Equipment

• Operating Expenses = operation of the agency

– Function (Vehicle Operations, Vehicle Maintenance, Non-

Vehicle Maintenance, General Administration)

– Object Class (Salary&Wages+Fringe= Compensation, Services ,

Materials and Supplies, Utilities, Casualty and Liability,

Purchased Transportation, Other)

NTD Glossary (Service Consumed)

• Unlinked Passenger Trips = boardings

• Passenger Miles = cumulative sum of the distances ridden by each

passenger

• Average Trip Length = avg distance ridden for = passenger miles /

unlinked passenger trips

• Average Passenger Load = avg # pass aboard a vehicle at any one

NTD Glossary (Service Supplied)

• Average Speed = miles / hours in revenue service

• Revenue Service = operation when passengers can board and ride

on the vehicle

• Vehicle Total Miles = all miles from pull out to pull in, including

"deadhead"

• Vehicle Revenue Miles = miles in revenue service

• Vehicle Total Hours = hours from pull out to pull in, including

"deadhead"

• Vehicle Revenue Hours = hours in revenue service

NTD Glossary (Service Supplied)

• Revenue Vehicle = vehicle in fleet available to operate in revenue

service including spares and out for maintenance

• Vehicles Available for Maximum Service = vehicles agency has

available to operate revenue

• Vehicles Operated Maximum Service = largest # vehicles operated

at any one time

• Base Period Requirement = vehicles needed to serve the base (all-

day) transit service

• Peak-to-Base Ratio = Max Service / Base Period

• Percent Spares = (Veh Available – Veh Operated) / Veh Operated

NTD Performance Measures

• Service Efficiency– Operating Expense per Vehicle Revenue Mile– Operating Expense per Vehicle Revenue Hour

• Service Effectiveness– Operating Expense per Passenger Mile– Operating Expense per Unlinked Passenger Trip

• Service Effectiveness– Unlinked Passenger Trips per Vehicle Revenue Mile– Unlinked Passenger Trips per Vehicle Revenue Hour

IN-CLASS EXERCISEHead to www.ntdprogram.gov to complete the

Route and Trip Levels Are Similar

• We describe unlinked passenger trips with– Route Stop Locations– Route Scheduling & Efficiency– Volumes of Passengers– Access/ Egress Locations– Travel and Boarding Times– Trip Purposes

• Two ways to collect this detailed data– Manually– Automatically

Exact Characteristics

Depend on Application

MANUAL DATA COLLECTION

Engineers can tailor route and trip analyses through

Manual Procedure Considerations

• Instruments: – Pencil/paper – Hand-held units

• Route Selection: – 100 percent– Sample

• Type of “Checks”: – Ride check: on-board the vehicle– Point checks: at a specific location

• Surveys also used (at trip-level)

Ride Checks

• Captures an entire route in detail• Data collection is done on-board• Checkers counts the number of boardings,

alightings, & thru-passengers at each stop• Distance between each stop may also be

recorded

• Output: Route-level & Stop-level ridership data

Ride Check Data Sheet - Example

Ride Check - Basic Calculations

1. Total Unlinked Passenger Trips on the Route = Sum of all Boardings

2. Load Profile for the Route = Cumulative Boardings @ Stop – Cumulative Alightings @ Stop

Peak (maximum) load along the route Average load along the route

3. Passenger Miles Traveled on the Route = Sum of Stop-Level Load * Distance between Stops

Example Load Profile

Stop #1

Stop #2

Stop #3

Bus Route Load Profile

Load per StopAverage Load

Peak Load Point: 47 Pax

Average Load: 24 Pax

Point Checks

• Data collection is done at one (or more) stops along a route

• Number of passengers on the vehicle is recorded

• Often conducted at high (peak) load points along a route

Surveys

• Travel surveys are used to estimate complete origin-destination patterns

• Questions include boarding location, alighting location, transfer location

• More next lecture

AUTOMATED DATA COLLECTION

Transit operators are increasingly relying on new technologies…

Automated Data Sources

1. Automated Fare Collection (AFC)2. Automated Passenger Counters (APC)3. Automated Vehicle Location (AVL)

• Archived data from AFC and AVL systems is an important byproduct of installing these systems.

Automated Fare Collection (AFC)

• Magnetic stripe & smart cards• Smart card systems have unique

ID that provides entry (exit) information at the individual level – Data not available in real-time

(coming soon!)• Magnetic stripe and smart cards

together can produce station/stop level data– Rail gateline counts– Bus fare boxes (operator often

punches a key indicating other fare types, such as free passes)

Smart Card Example: OD Estimation

• AM Inbound trip: tap-in at “origin”

• PM Outbound trip: tap-in at “destination”

• Infer that passenger is traveling from Brookhaven to Midtown and back

AM Tap at Brookhaven

PM Tap at Midtown

Automated Passenger Counters (APC)

• Sensors near vehicle doors count passenger on and offs, usually using infrared beams

• Some vehicles also determine weight/steps on-board vehicle

• Typically data not available in real-time • Usually only on a sample (%) of bus fleet;

redistribute buses to determine counts

Automated Vehicle Location (AVL)

• Originally, Signpost-beacon-based used to track the location of buses

• Post-2000, GPS-based technology• Provided in real-time• Usually matched with schedule through Computer

Aided Dispatch (CAD) systems• Also combined with other data sources (AFC & APC)

to capture detailed ridership• Valuable for service planning (i.e. determining

running times, schedule adherence)

Signpost-based AVL

GPS-based AVL

Combining AVL & APC

• Detailed Route Level Analysis

DATA COLLECTION COMPARISON

Manual vs. Automated Data

Manual Data• Low capital costs• High marginal (labor) costs• Small sample sizes– Limited spatial and

temporal variation • Often unreliable (errors by

checkers)• Longer data

collection/processing times

Automated Data

• High capital costs• Low marginal (labor) costs• Large sample sizes

– Detailed temporal and spatial data

• Biases can (usually) be corrected• Available in (quasi) real-time

Passenger Counting Technologies (2008)

Technology / Procedure # Systems PercentageCombination of manual and automatic 44 51.2%Manual (paper and pencil) only 18 20.9%APCs only 12 14.0%Other automated methods (farebox, hand-held units)

12 14.0%

Total systems 33 100.0%

Future Trends

• Increasing use of automated data collection systems– Including mixed modes (manual &

automated)

• More disaggregate data used for planning and decision-making (refined units of analysis)

DATA STANDARDS

Transit Data Consumption

The changing landscape

Schedule

Paper Schedules

109:36

Digitization Interactivity

General Transit Feed Specification

routes.txt

stops.txt

trips.txt

stop_times.txt calendar.txt

agency.txt

shapes.txt

How Does Open Data Help?

Data access models

Agency responds to special requests by

developers

Small subset of riders find this specific tool useful.

Transit Agency

App Developers

Riders

DATAAnyone can access data

Many riders access a diverse market of tools powered by GTFS.

Agency produces data and opens it

Transit Open Data Timeline

Source: Rojas, Francisca (2012) Transit Transparency: Effective Disclosure through Open Data

Materials developed by K. Watkins, J. LaMondia and C. Brakewood44

Open Schedule Data (GTFS) Adoption

Source: Wong, James. (2013). Leveraging the General Transit Feed Specification (GTFS) for Efficient Transit Analysis. Proceedings of the 2013 Transportation Research Board Annual Meeting.

Conclusions

• We need accurate data to make appropriate decisions for transit service.

• The National Transit Database (NTD) is the largest source of transit data in the US.

• Manual data collection consists in recording transit information in person.

• Automatic data collection uses captors in buses to record vehicle location, vehicle loads, etc.

• Future trend of opening up data based on standardized formats.

Reference

Materials in this lecture were taken from:• Walker, J. (2011). Human transit: How clearer thinking about

public transit can enrich our communities and our lives. Island Press.

• Furth, Hemily, Muller, Strathman (2006). “Using Archived AVL-APC Data to Improve Transit Performance and Management. TCRP Report 113." Transportation Research Board.

• National Transit Database Sampling Manual (2009)• "Sampling Tests Automatic Passenger Counters." The Inside

Lane. 26 Sept. 2011.• Boyle, D (2008). "TCRP Synthesis 77: Passenger Counting

Systems.” TRB, National Research Council, Washington, D. C.

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